PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-25 (1483150)

Clipboard (0)
None

Related Articles

1.  Hedging against Antiviral Resistance during the Next Influenza Pandemic Using Small Stockpiles of an Alternative Chemotherapy 
PLoS Medicine  2009;6(5):e1000085.
Mathematically simulating an influenza pandemic, Joseph Wu and colleagues predict that using a secondary antiviral drug early in local epidemics would reduce global emergence of resistance to the primary stockpiled drug.
Background
The effectiveness of single-drug antiviral interventions to reduce morbidity and mortality during the next influenza pandemic will be substantially weakened if transmissible strains emerge which are resistant to the stockpiled antiviral drugs. We developed a mathematical model to test the hypothesis that a small stockpile of a secondary antiviral drug could be used to mitigate the adverse consequences of the emergence of resistant strains.
Methods and Findings
We used a multistrain stochastic transmission model of influenza to show that the spread of antiviral resistance can be significantly reduced by deploying a small stockpile (1% population coverage) of a secondary drug during the early phase of local epidemics. We considered two strategies for the use of the secondary stockpile: early combination chemotherapy (ECC; individuals are treated with both drugs in combination while both are available); and sequential multidrug chemotherapy (SMC; individuals are treated only with the secondary drug until it is exhausted, then treated with the primary drug). We investigated all potentially important regions of unknown parameter space and found that both ECC and SMC reduced the cumulative attack rate (AR) and the resistant attack rate (RAR) unless the probability of emergence of resistance to the primary drug pA was so low (less than 1 in 10,000) that resistance was unlikely to be a problem or so high (more than 1 in 20) that resistance emerged as soon as primary drug monotherapy began. For example, when the basic reproductive number was 1.8 and 40% of symptomatic individuals were treated with antivirals, AR and RAR were 67% and 38% under monotherapy if pA = 0.01. If the probability of resistance emergence for the secondary drug was also 0.01, then SMC reduced AR and RAR to 57% and 2%. The effectiveness of ECC was similar if combination chemotherapy reduced the probabilities of resistance emergence by at least ten times. We extended our model using travel data between 105 large cities to investigate the robustness of these resistance-limiting strategies at a global scale. We found that as long as populations that were the main source of resistant strains employed these strategies (SMC or ECC), then those same strategies were also effective for populations far from the source even when some intermediate populations failed to control resistance. In essence, through the existence of many wild-type epidemics, the interconnectedness of the global network dampened the international spread of resistant strains.
Conclusions
Our results indicate that the augmentation of existing stockpiles of a single anti-influenza drug with smaller stockpiles of a second drug could be an effective and inexpensive epidemiological hedge against antiviral resistance if either SMC or ECC were used. Choosing between these strategies will require additional empirical studies. Specifically, the choice will depend on the safety of combination therapy and the synergistic effect of one antiviral in suppressing the emergence of resistance to the other antiviral when both are taken in combination.
Editors' Summary
Background
Every winter, millions of people catch influenza—a viral infection of the airways—and about half a million people die as a result. These seasonal “epidemics” occur because small but frequent changes in the viral proteins (antigens) to which the human immune system responds mean that an immune response produced one year provides only partial protection against influenza the next year. Influenza viruses also occasionally appear that contain major antigenic changes. Human populations have little or no immunity to such viruses so they can start deadly pandemics (global epidemics). The 1918–19 influenza pandemic, for example, killed 40–50 million people. The last influenza pandemic was in 1968 and many experts fear the next pandemic might strike soon. To prepare for such an eventuality, scientists are trying to develop vaccines that might work against an emerging pandemic influenza virus. In addition, many governments are stockpiling antiviral drugs for the large-scale treatment of influenza and for targeted prophylaxis (prevention). Antiviral drugs prevent the replication of the influenza virus, thereby shortening the length of time that an infected person is ill and protecting uninfected people against infection. Their widespread use should, therefore, slow the spread of pandemic influenza.
Why Was This Study Done?
Although some countries are stockpiling more than one antiviral drug in preparation for an influenza pandemic, many countries are investing in large stockpiles of a single drug, oseltamivir (Tamiflu). But influenza viruses can become resistant to antiviral drugs and the widespread use of a single drug (the primary antiviral) is likely to increase the risk that a resistant strain will emerge. If this did happen, the ability of antiviral drugs to slow the spread of a pandemic would be greatly reduced. In this study, the researchers use a mathematical model of influenza transmission to investigate whether a small stockpile of a secondary antiviral drug could be used to prevent the adverse consequences of the emergence of antiviral-resistant pandemic influenza viruses.
What Did the Researchers Do and Find?
The researchers used their model of influenza transmission to predict how two strategies for the use of a small stockpile of a secondary antiviral might affect the cumulative attack rate (AR; the final proportion of the population infected) and the resistant attack rate (RAR; the proportion of the population infected with an influenza virus strain resistant to the primary drug, a measure that may reflect the impact of antiviral resistance on death rates during a pandemic). In a large, closed population, the model predicted that both “early combination chemotherapy” (treatment with both drugs together while both are available) and “sequential multi-drug chemotherapy” (treatment with the secondary drug until it is exhausted, then treatment with the primary drug) would reduce the AR and the RAR compared with monotherapy unless the probability of emergence of resistance to the primary drug was very low (resistance rarely occurred) or very high (resistance emerged as soon as the primary drug was used). The researchers then introduced international travel data into their model to investigate whether these two strategies could limit the development of antiviral resistance at a global scale. This analysis predicted that, provided the population that was the main source of resistant strains used one of the strategies, both strategies in distant, subsequently affected populations would be able to reduce the AR and RAR even if some intermediate populations failed to control resistance.
What Do These Findings Mean?
As with all mathematical models, the accuracy of these predictions depends on the assumptions used to build the model and the data fed into it. Nevertheless, these findings suggest that both of the proposed strategies for the use of small stockpiles of secondary antiviral drugs should limit the spread of drug-resistant influenza virus more effectively than monotherapy with the primary antiviral drug. Thus, small stockpiles of secondary antivirals could provide a hedge against the development of antiviral resistance during the early phases of an influenza pandemic and are predicted to be a worthwhile public-health investment. However, note the researchers, experimental studies—including determinations of which drugs are safe to use together, and how effectively a given combination prevents resistance compared with each drug used alone—are now needed to decide which of the strategies to recommend in real-life situations. In the context of the 2009 global spread of swine flu, these findings suggest that public health officials might consider zanamivir (Relenza) as the secondary antiviral drug for resistance-limiting strategies in countries that have stockpiled oseltamivir.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000085.
The US Centers for Disease Control and Prevention provides information about influenza for patients and professionals, including specific information on pandemic influenza and on influenza antiviral drugs
The World Health Organization provides information on influenza (in several languages) and has detailed guidelines on the use of vaccines and antivirals during influenza pandemics
The UK Health Protection Agency provides information on pandemic influenza
MedlinePlus provides a list of links to other information about influenza (in English and Spanish)
doi:10.1371/journal.pmed.1000085
PMCID: PMC2680070  PMID: 19440354
2.  Characterizing the Epidemiology of the 2009 Influenza A/H1N1 Pandemic in Mexico 
PLoS Medicine  2011;8(5):e1000436.
Gerardo Chowell and colleagues address whether school closures and other social distancing strategies were successful in reducing pandemic flu transmission in Mexico by analyzing the age- and state-specific incidence of influenza morbidity and mortality in 32 Mexican states.
Background
Mexico's local and national authorities initiated an intense public health response during the early stages of the 2009 A/H1N1 pandemic. In this study we analyzed the epidemiological patterns of the pandemic during April–December 2009 in Mexico and evaluated the impact of nonmedical interventions, school cycles, and demographic factors on influenza transmission.
Methods and Findings
We used influenza surveillance data compiled by the Mexican Institute for Social Security, representing 40% of the population, to study patterns in influenza-like illness (ILIs) hospitalizations, deaths, and case-fatality rate by pandemic wave and geographical region. We also estimated the reproduction number (R) on the basis of the growth rate of daily cases, and used a transmission model to evaluate the effectiveness of mitigation strategies initiated during the spring pandemic wave. A total of 117,626 ILI cases were identified during April–December 2009, of which 30.6% were tested for influenza, and 23.3% were positive for the influenza A/H1N1 pandemic virus. A three-wave pandemic profile was identified, with an initial wave in April–May (Mexico City area), a second wave in June–July (southeastern states), and a geographically widespread third wave in August–December. The median age of laboratory confirmed ILI cases was ∼18 years overall and increased to ∼31 years during autumn (p<0.0001). The case-fatality ratio among ILI cases was 1.2% overall, and highest (5.5%) among people over 60 years. The regional R estimates were 1.8–2.1, 1.6–1.9, and 1.2–1.3 for the spring, summer, and fall waves, respectively. We estimate that the 18-day period of mandatory school closures and other social distancing measures implemented in the greater Mexico City area was associated with a 29%–37% reduction in influenza transmission in spring 2009. In addition, an increase in R was observed in late May and early June in the southeast states, after mandatory school suspension resumed and before summer vacation started. State-specific fall pandemic waves began 2–5 weeks after school reopened for the fall term, coinciding with an age shift in influenza cases.
Conclusions
We documented three spatially heterogeneous waves of the 2009 A/H1N1 pandemic virus in Mexico, which were characterized by a relatively young age distribution of cases. Our study highlights the importance of school cycles on the transmission dynamics of this pandemic influenza strain and suggests that school closure and other mitigation measures could be useful to mitigate future influenza pandemics.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
From June 2009 to August 2010, the world was officially (according to specific World Health Organization [WHO] criteria—WHO phase 6 pandemic alert) in the grip of an Influenza A pandemic with a new strain of the H1N1 virus. The epidemic in Mexico, which had the second confirmed global case of H1N1 virus was first noted in early April 2009, when reports of respiratory hospitalizations and deaths among 62 young adults in Mexico alerted local health officials to the occurrence of atypical rates of respiratory illness. In line with its inter-institutional National Pandemic Influenza Preparedness and Response Plan, the Ministry of Health cancelled school attendance in the greater Mexico City area on April 24 and expanded these measures to the rest the country three days later. The Ministry of Health then implemented in Mexico City other “social distancing” strategies such as closing cinemas and restaurants and cancelling large public gatherings.
Why Was This Study Done?
School closures and other intense social distancing strategies can be very disruptive to the population, but as yet it is uncertain whether these measures were successful in reducing disease transmission. In addition, there have been no studies concentrating on recurrent pandemic waves in Mexico. So in this study the authors addressed these issues by analyzing the age- and state-specific incidence of influenza morbidity and mortality in 32 Mexican States and quantified the association between local influenza transmission rates, school cycles, and demographic factors.
What Did the Researchers Do and Find?
The researchers used the epidemiological surveillance system of the Mexican Institute for Social Security—a Mexican health system that covers private sector workers and their families, a group representative of the general population, that comprises roughly 40% of the Mexican population (107 million individuals), with a network of 1,099 primary health care units and 259 hospitals nationwide. Then the researchers compiled state- and age-specific time series of incident influenza-like illness and H1N1 influenza cases by day of symptom onset to analyze the geographic dissemination patterns of the pandemic across Mexico and defined three temporally distinct pandemic waves in 2009: spring (April 1–May 20), summer (May 21–August 1), and fall (August 2–December 31). The researchers then applied a mathematical model of influenza transmission to daily case data to assess the effectiveness of mandatory school closures and other social distancing measures implemented during April 24–May 11, in reducing influenza transmission rates.
The Mexican Institute for Social Security reported a total of 117,626 people with influenza-like illness from April 1 to December 31, 2009, of which 36,044 were laboratory tested (30.6%) and 27,440 (23.3%) were confirmed with H1N1 influenza. During this period, 1,370 people with influenza-like illness died of which 585 (1.5 per 100,000) were confirmed to have H1N1 influenza. The median age of people with laboratory confirmed influenza like illness (H1N1) was 18 years overall but increased to 31 years during the autumn wave. The overall case-fatality ratio among people with influenza like illness was 1.2%, but highest (5.5%) among people over 60 years. The researchers found that the 18-day period of mandatory school closures and other social distancing measures implemented in the greater Mexico City area was associated with a substantial (29%–37%) reduction in influenza transmission in spring 2009 but increased in late May and early June in the southeast states, after mandatory school suspension resumed and before summer vacation started. State-specific pandemic waves began 2–5 weeks after school reopened for the fall term, coinciding with an age shift in influenza cases.
What Do These Findings Mean?
These findings show that the age distribution of pandemic influenza morbidity was greater in younger age groups, while the risk of severe disease was skewed towards older age groups, and that there were substantial geographical variation in pandemic patterns across Mexico, in part related to population size. But most importantly, these findings support the effectiveness of early mitigation efforts including mandatory school closures and cancellation of large public gatherings, reinforcing the importance of school cycles in the transmission of pandemic influenza. This analysis increases understanding of the age and transmission patterns of the Mexican 2009 influenza pandemic at various geographic scales, which is crucial for designing more efficient public health interventions against future influenza pandemics.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000436.
The World Health Organization provides information about the global response to the 2009 H1N1 pandemic
doi:10.1371/journal.pmed.1000436
PMCID: PMC3101203  PMID: 21629683
3.  Global Mortality Estimates for the 2009 Influenza Pandemic from the GLaMOR Project: A Modeling Study 
PLoS Medicine  2013;10(11):e1001558.
Lone Simonsen and colleagues use a two-stage statistical modeling approach to estimate the global mortality burden of the 2009 influenza pandemic from mortality data obtained from multiple countries.
Please see later in the article for the Editors' Summary
Background
Assessing the mortality impact of the 2009 influenza A H1N1 virus (H1N1pdm09) is essential for optimizing public health responses to future pandemics. The World Health Organization reported 18,631 laboratory-confirmed pandemic deaths, but the total pandemic mortality burden was substantially higher. We estimated the 2009 pandemic mortality burden through statistical modeling of mortality data from multiple countries.
Methods and Findings
We obtained weekly virology and underlying cause-of-death mortality time series for 2005–2009 for 20 countries covering ∼35% of the world population. We applied a multivariate linear regression model to estimate pandemic respiratory mortality in each collaborating country. We then used these results plus ten country indicators in a multiple imputation model to project the mortality burden in all world countries. Between 123,000 and 203,000 pandemic respiratory deaths were estimated globally for the last 9 mo of 2009. The majority (62%–85%) were attributed to persons under 65 y of age. We observed a striking regional heterogeneity, with almost 20-fold higher mortality in some countries in the Americas than in Europe. The model attributed 148,000–249,000 respiratory deaths to influenza in an average pre-pandemic season, with only 19% in persons <65 y. Limitations include lack of representation of low-income countries among single-country estimates and an inability to study subsequent pandemic waves (2010–2012).
Conclusions
We estimate that 2009 global pandemic respiratory mortality was ∼10-fold higher than the World Health Organization's laboratory-confirmed mortality count. Although the pandemic mortality estimate was similar in magnitude to that of seasonal influenza, a marked shift toward mortality among persons <65 y of age occurred, so that many more life-years were lost. The burden varied greatly among countries, corroborating early reports of far greater pandemic severity in the Americas than in Australia, New Zealand, and Europe. A collaborative network to collect and analyze mortality and hospitalization surveillance data is needed to rapidly establish the severity of future pandemics.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every winter, millions of people catch influenza—a viral infection of the airways—and hundreds of thousands of people (mainly elderly individuals) die as a result. These seasonal epidemics occur because small but frequent changes in the influenza virus mean that the immune response produced by infection with one year's virus provides only partial protection against the next year's virus. Influenza viruses also occasionally emerge that are very different. Human populations have virtually no immunity to these new viruses, which can start global epidemics (pandemics) that kill millions of people. The most recent influenza pandemic, which was first recognized in Mexico in March 2009, was caused by the 2009 influenza A H1N1 pandemic (H1N1pdm09) virus. This virus spread rapidly, and on 11 June 2009, the World Health Organization (WHO) declared that an influenza pandemic was underway. H1N1pdm09 caused a mild disease in most people it infected, but by the time WHO announced that the pandemic was over (10 August 2010), there had been 18,632 laboratory-confirmed deaths from H1N1pdm09.
Why Was This Study Done?
The modest number of laboratory-confirmed H1N1pdm09 deaths has caused commentators to wonder whether the public health response to H1N1pdm09 was excessive. However, as is the case with all influenza epidemics, the true mortality (death) burden from H1N1pdm09 is substantially higher than these figures indicate because only a minority of influenza-related deaths are definitively diagnosed by being confirmed in laboratory. Many influenza-related deaths result from secondary bacterial infections or from exacerbation of preexisting chronic conditions, and are not recorded as related to influenza infection. A more complete assessment of the impact of H1N1pdm09 on mortality is essential for the optimization of public health responses to future pandemics. In this modeling study (the Global Pandemic Mortality [GLaMOR] project), researchers use a two-stage statistical modeling approach to estimate the global mortality burden of the 2009 influenza pandemic from mortality data obtained from multiple countries.
What Did the Researchers Do and Find?
The researchers obtained weekly virology data from the World Health Organization FluNet database and national influenza centers to identify influenza active periods, and obtained weekly national underlying cause-of-death time series for 2005–2009 from collaborators in more than 20 countries (35% of the world's population). They used a multivariate linear regression model to measure the numbers and rates of pandemic influenza respiratory deaths in each of these countries. Then, in the second stage of their analysis, they used a multiple imputation model that took into account country-specific geographical, economic, and health indicators to project the single-country estimates to all world countries. The researchers estimated that between 123,000 and 203,000 pandemic influenza respiratory deaths occurred globally from 1 April through 31 December 2009. Most of these deaths (62%–85%) occurred in people younger than 65 years old. There was a striking regional heterogeneity in deaths, with up to 20-fold higher mortality in Central and South American countries than in European countries. Finally, the model attributed 148,000–249,000 respiratory deaths to influenza in an average pre-pandemic season. Notably, only 19% of these deaths occurred in people younger than 65 years old.
What Do These Findings Mean?
These findings suggest that respiratory mortality from the 2009 influenza pandemic was about 10-fold higher than laboratory-confirmed mortality. The true total mortality burden is likely to be even higher because deaths that occurred late in the winter of 2009–2010 and in later pandemic waves were missed in this analysis, and only pandemic influenza deaths that were recorded as respiratory deaths were included. The lack of single-country estimates from low-income countries may also limit the accuracy of these findings. Importantly, although the researchers' estimates of mortality from H1N1pdm09 and from seasonal influenza were of similar magnitude, the shift towards mortality among younger people means that more life-years were lost during the 2009 influenza pandemic than during an average pre-pandemic influenza season. Although the methods developed by the GLaMOR project can be used to make robust and comparable mortality estimates in future influenza pandemics, the lack of timeliness of such estimates needs to be remedied. One potential remedy, suggest the researchers, would be to establish a collaborative network that analyzes timely hospitalization and/or mortality data provided by sentinel countries. Such a network should be able to provide the rapid and reliable data about the severity of pandemic threats that is needed to guide public health policy decisions.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001558.
The US Centers for Disease Control and Prevention provides information about influenza for patients and professionals, including archived information on H1N1pdm09
Flu.gov, a US government website, provides access to information on seasonal and pandemic influenza H1N1pdm09
The World Health Organization provides information on influenza and on the global response to H1N1pdm09, including a publication on the evolution of H1N1pdm09 (some information in several languages). Information on FluNet, a global tool for influenza surveillance, is also available
Public Health England provides information on pandemic influenza and archived information on H1N1pdm09
More information for patients about H1N1pdm09 is available through Choices, an information resource provided by the UK National Health Service
More information about the GLaMOR project is available
doi:10.1371/journal.pmed.1001558
PMCID: PMC3841239  PMID: 24302890
4.  Antiviral Resistance and the Control of Pandemic Influenza 
PLoS Medicine  2007;4(1):e15.
Background
The response to the next influenza pandemic will likely include extensive use of antiviral drugs (mainly oseltamivir), combined with other transmission-reducing measures. Animal and in vitro studies suggest that some strains of influenza may become resistant to oseltamivir while maintaining infectiousness (fitness). Use of antiviral agents on the scale anticipated for the control of pandemic influenza will create an unprecedented selective pressure for the emergence and spread of these strains. Nonetheless, antiviral resistance has received little attention when evaluating these plans.
Methods and Findings
We designed and analyzed a deterministic compartmental model of the transmission of oseltamivir-sensitive and -resistant influenza infections during a pandemic. The model predicts that even if antiviral treatment or prophylaxis leads to the emergence of a transmissible resistant strain in as few as 1 in 50,000 treated persons and 1 in 500,000 prophylaxed persons, widespread use of antivirals may strongly promote the spread of resistant strains at the population level, leading to a prevalence of tens of percent by the end of a pandemic. On the other hand, even in circumstances in which a resistant strain spreads widely, the use of antivirals may significantly delay and/or reduce the total size of the pandemic. If resistant strains carry some fitness cost, then, despite widespread emergence of resistance, antivirals could slow pandemic spread by months or more, and buy time for vaccine development; this delay would be prolonged by nondrug control measures (e.g., social distancing) that reduce transmission, or use of a stockpiled suboptimal vaccine. Surprisingly, the model suggests that such nondrug control measures would increase the proportion of the epidemic caused by resistant strains.
Conclusions
The benefits of antiviral drug use to control an influenza pandemic may be reduced, although not completely offset, by drug resistance in the virus. Therefore, the risk of resistance should be considered in pandemic planning and monitored closely during a pandemic.
Emergence of oseltamivir-resistant influenza strains during a pandemic is likely given the heightened selective pressure if the drug is widely used. Marc Lipsitch and colleagues suggest that resistance would reduce but not completely offset the drug's benefits for pandemic control.
Editors' Summary
Background.
Governments and health authorities worldwide are planning how they would best prepare for and deal with a future influenza pandemic. Seasonal influenza is thought to affect between 5% and 15% of the population worldwide each year. Most people who get influenza recover within a couple of weeks without lasting effects, but a small proportion of patients, mostly young children and elderly people, experience serious complications that can be fatal. An influenza pandemic happens when new variants of the influenza virus emerge against which little immunity exists in the general population. Pandemic influenza strains are transmitted more rapidly than seasonal strains, often sweep across several countries or continents, and make more people ill. There are drugs that can treat and prevent influenza. One of them, oseltamivir (Tamiflu) is an antiviral drug that works by preventing viral particles from being released by infected human cells. Stockpiling large amounts of oseltamivir and related drugs with the intent to treat a large fraction of the population is a key part of pandemic preparedness of many countries. However, it is known that influenza viruses can develop resistance to these drugs.
Why Was This Study Done?
It is not clear how the emergence of oseltamivir-resistant influenza strains would affect the course of any future influenza pandemic. Much research in this area has focused on how likely the new strains are to emerge in the first place, rather than on how they might spread once they had emerged. In the context of an influenza pandemic, antiviral drugs would be used in a large proportion of the population, likely driving the selection and spread of resistant viruses. For this study, the researchers wanted to estimate the likely impact of resistant strains during an influenza pandemic.
What Did the Researchers Do and Find?
These researchers set up a mathematical model (i.e., simulations done on a computer) to mimic the spread of influenza. They then fed a set of assumptions into the computer. These included information about the rate of transmission of influenza from one person to another; what proportion of people would receive antiviral drugs for prophylaxis or treatment; how likely the drugs would be to successfully treat or prevent infection; and in what proportion of people the virus might become resistant to drugs. The modeling led to three main predictions. First, it predicted that widespread use of antiviral drugs such as oseltamivir could quickly lead to the spread of resistant viruses, even if resistant strains emerged only rarely. Second, even with resistant strains circulating, prophylaxis and treatment with oseltamivir would still delay the spread of the pandemic and reduce its total size. Third, nondrug interventions (such as social isolation and school closures) would further reduce the number of cases, but a higher proportion of cases would be caused by resistant strains if these control measures were used.
What Do These Findings Mean?
These findings suggest that, in the event of a future influenza pandemic for which antiviral drugs are used, there is a risk of resistance emerging and resistant strains causing illness in a substantial number of people. This would counteract the benefits of antiviral drugs but not eliminate those benefits entirely. Like all modeling studies, this one relies on realistic assumptions being entered into the model, and it is hard to know closely the model will mimic a real-life situation until the properties of an actual pandemic strain are known. Most studies, including this one, suggest that in the event of a pandemic, antiviral drugs will have an overall beneficial impact on reducing death rates and adverse health outcomes. However, given the sizeable effects of resistance suggested here, its role should be considered in pandemic planning. This includes surveillance that can detect emergence and spread of resistant strains.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/doi:10.1371/journal.pmed.0040015.
World Health Organization: information on pandemic preparedness
World Health Organization: fact sheets on influenza
Information from the UK Health Protection Agency on pandemic influenza
US government website on both pandemic flu and avian flu (information provided by the US Department of Health and Human Services)
doi:10.1371/journal.pmed.0040015
PMCID: PMC1779817  PMID: 17253900
5.  The Severity of Pandemic H1N1 Influenza in the United States, from April to July 2009: A Bayesian Analysis 
PLoS Medicine  2009;6(12):e1000207.
Marc Lipsitch and colleagues use complementary data from two US cities, Milwaukee and New York City, to assess the severity of pandemic (H1N1) 2009 influenza in the United States.
Background
Accurate measures of the severity of pandemic (H1N1) 2009 influenza (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely, resulting in overestimation of the severity of an average case. We sought to estimate the probabilities that symptomatic infection would lead to hospitalization, ICU admission, and death by combining data from multiple sources.
Methods and Findings
We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data—medically attended cases in Milwaukee or self-reported influenza-like illness (ILI) in New York—were used to estimate ratios of symptomatic cases to hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic patients who died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information, and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated an sCFR of 0.048% (95% credible interval [CI] 0.026%–0.096%), sCIR of 0.239% (0.134%–0.458%), and sCHR of 1.44% (0.83%–2.64%). Using self-reported ILI, we obtained estimates approximately 7–9× lower. sCFR and sCIR appear to be highest in persons aged 18 y and older, and lowest in children aged 5–17 y. sCHR appears to be lowest in persons aged 5–17; our data were too sparse to allow us to determine the group in which it was the highest.
Conclusions
These estimates suggest that an autumn–winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with the greatest impact in children aged 0–4 and adults 18–64. These estimates of impact depend on assumptions about total incidence of infection and would be larger if incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the total proportion of the population symptomatically infected were lower than assumed.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every winter, millions of people catch influenza—a viral infection of the airways—and about half a million people die as a result. In the US alone, an average of 36,000 people are thought to die from influenza-related causes every year. These seasonal epidemics occur because small but frequent changes in the virus mean that an immune response produced one year provides only partial protection against influenza the next year. Occasionally, influenza viruses emerge that are very different and to which human populations have virtually no immunity. These viruses can start global epidemics (pandemics) that kill millions of people. Experts have been warning for some time that an influenza pandemic is long overdue and in, March 2009, the first cases of influenza caused by a new virus called pandemic (H1N1) 2009 (pH1N1; swine flu) occurred in Mexico. The virus spread rapidly and on 11 June 2009, the World Health Organization declared that a global pandemic of pH1N1 influenza was underway. By the beginning of November 2009, more than 6,000 people had died from pH1N1 influenza.
Why Was This Study Done?
With the onset of autumn—drier weather and the return of children to school help the influenza virus to spread—pH1N1 cases, hospitalizations, and deaths in the Northern Hemisphere have greatly increased. Although public-health officials have been preparing for this resurgence of infection, they cannot be sure of its impact on human health without knowing more about the severity of pH1N1 infections. The severity of an infection can be expressed as a case-fatality ratio (CFR; the proportion of cases that result in death), as a case-hospitalization ratio (CHR; the proportion of cases that result in hospitalization), and as a case-intensive care ratio (CIR; the proportion of cases that require treatment in an intensive care unit). Because so many people have been infected with pH1N1 since it emerged, the numbers of cases and deaths caused by pH1N1 infection are not known accurately so these ratios cannot be easily calculated. In this study, the researchers estimate the severity of pH1N1 influenza in the US between April and July 2009 by combining data on pH1N1 infections from several sources using a statistical approach known as Bayesian evidence synthesis.
What Did the Researchers Do and Find?
By using data on medically attended and hospitalized cases of pH1N1 infection in Milwaukee and information from New York City on hospitalizations, intensive care use, and deaths, the researchers estimate that the proportion of US cases with symptoms that died (the sCFR) during summer 2009 was 0.048%. That is, about 1 in 2,000 people who had symptoms of pH1N1 infection died. The “credible interval” for this sCFR, the range of values between which the “true” sCFR is likely to lie, they report, is 0.026%–0.096% (between 1 in 4,000 and 1 in 1,000 deaths for every symptomatic case). About 1 in 400 symptomatic cases required treatment in intensive care, they estimate, and about 1 in 70 symptomatic cases required hospital admission. When the researchers used a different approach to estimate the total number of symptomatic cases—based on New Yorkers' self-reported incidence of influenza-like-illness from a telephone survey—their estimates of pH1N1 infection severity were 7- to 9-fold lower. Finally, they report that the sCFR and the sCIR were highest in people aged 18 or older and lowest in children aged 5–17 years.
What Do These Findings Mean?
Many uncertainties (for example, imperfect detection and reporting) can affect estimates of influenza severity. Even so, the findings of this study suggest that an autumn–winter pandemic wave of pH1N1 will have a death toll only slightly higher than or considerably lower than that caused by seasonal influenza in an average year, provided pH1N1 continues to behave as it did during the summer. Similarly, the estimated burden on hospitals and intensive care facilities ranges from somewhat higher than in a normal influenza season to considerably lower. The findings of this study also suggest that, unlike seasonal influenza, which kills mainly elderly adults, a high proportion of deaths from pH1N1infection will occur in nonelderly adults, a shift in age distribution that has been seen in previous pandemics. With these estimates in hand and with continued close monitoring of the pandemic, public-health officials should now be in a better position to plan effective strategies to deal with the pH1N1 pandemic.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000207.
The US Centers for Disease Control and Prevention provides information about influenza for patients and professionals, including specific information on pandemic H1N1 (2009) influenza
Flu.gov, a US government Web site, provides access to information on H1N1, avian and pandemic influenza
The World Health Organization provides information on seasonal influenza and has detailed information on pandemic H1N1 (2009) influenza (in several languages)
The UK Health Protection Agency provides information on pandemic influenza and on pandemic H1N1 (2009) influenza
More information for patients about H1N1 influenza is available through Choices, an information resource provided by the UK National Health Service
doi:10.1371/journal.pmed.1000207
PMCID: PMC2784967  PMID: 19997612
6.  Risk Factors for Severe Outcomes following 2009 Influenza A (H1N1) Infection: A Global Pooled Analysis 
PLoS Medicine  2011;8(7):e1001053.
This study analyzes data from 19 countries (from April 2009 to Jan 2010), comprising some 70,000 hospitalized patients with severe H1N1 infection, to reveal risk factors for severe pandemic influenza, which include chronic illness, cardiac disease, chronic respiratory disease, and diabetes.
Background
Since the start of the 2009 influenza A pandemic (H1N1pdm), the World Health Organization and its member states have gathered information to characterize the clinical severity of H1N1pdm infection and to assist policy makers to determine risk groups for targeted control measures.
Methods and Findings
Data were collected on approximately 70,000 laboratory-confirmed hospitalized H1N1pdm patients, 9,700 patients admitted to intensive care units (ICUs), and 2,500 deaths reported between 1 April 2009 and 1 January 2010 from 19 countries or administrative regions—Argentina, Australia, Canada, Chile, China, France, Germany, Hong Kong SAR, Japan, Madagascar, Mexico, the Netherlands, New Zealand, Singapore, South Africa, Spain, Thailand, the United States, and the United Kingdom—to characterize and compare the distribution of risk factors among H1N1pdm patients at three levels of severity: hospitalizations, ICU admissions, and deaths. The median age of patients increased with severity of disease. The highest per capita risk of hospitalization was among patients <5 y and 5–14 y (relative risk [RR] = 3.3 and 3.2, respectively, compared to the general population), whereas the highest risk of death per capita was in the age groups 50–64 y and ≥65 y (RR = 1.5 and 1.6, respectively, compared to the general population). Similarly, the ratio of H1N1pdm deaths to hospitalizations increased with age and was the highest in the ≥65-y-old age group, indicating that while infection rates have been observed to be very low in the oldest age group, risk of death in those over the age of 64 y who became infected was higher than in younger groups. The proportion of H1N1pdm patients with one or more reported chronic conditions increased with severity (median = 31.1%, 52.3%, and 61.8% of hospitalized, ICU-admitted, and fatal H1N1pdm cases, respectively). With the exception of the risk factors asthma, pregnancy, and obesity, the proportion of patients with each risk factor increased with severity level. For all levels of severity, pregnant women in their third trimester consistently accounted for the majority of the total of pregnant women. Our findings suggest that morbid obesity might be a risk factor for ICU admission and fatal outcome (RR = 36.3).
Conclusions
Our results demonstrate that risk factors for severe H1N1pdm infection are similar to those for seasonal influenza, with some notable differences, such as younger age groups and obesity, and reinforce the need to identify and protect groups at highest risk of severe outcomes.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
In April 2009, a new strain of influenza A H1N1 was first identified in Mexico and the United States and subsequently spread around the world. In June 2009, the World Health Organization (WHO) declared a pandemic alert phase 6, which continued until August 2010. Throughout the pandemic, WHO and member states gathered information to characterize the patterns of risk associated with the new influenza A H1N1 virus infection and to assess the clinical picture. Although risk factors for severe disease following seasonal influenza infection have been well documented in many countries (for example, pregnancy; chronic medical conditions such as pulmonary, cardiovascular, renal, hepatic, neuromuscular, hematologic, and metabolic disorders; some cognitive conditions; and immunodeficiency), risk factors for severe disease following infection early in the 2009 H1N1 pandemic were largely unknown.
Why Was This Study Done?
Many countries have recently reported data on the association between severe H1N1 influenza and a variety of underlying risk factors, but because these data are presented in different formats, making direct comparisons across countries is difficult, with no clear consensus for some conditions. Therefore, to assess the frequency and distribution of known and new potential risk factors for severe H1N1 infection, this study was conducted to collect data (from 1 April 2009 to 1 January 2010) from surveillance programs of the Ministries of Health or National Public Health Institutes in 19 countries―Argentina, Australia, Canada, Chile, China, France, Germany, Hong Kong (special administrative region), Japan, Madagascar, Mexico, the Netherlands, New Zealand, Singapore, South Africa, Spain, Thailand, the United States, and the United Kingdom.
What Did the Researchers Do and Find?
As part of routine surveillance, countries were asked to provide risk factor data on laboratory-confirmed H1N1 in patients who were admitted to hospital, admitted to the intensive care unit (ICU), or had died because of their infection, using a standardized format. The researchers grouped potential risk conditions into four categories: age, chronic medical illnesses, pregnancy (by trimester), and other conditions that were not previously considered as risk conditions for severe influenza outcomes, such as obesity. For each risk factor (except pregnancy), the researchers calculated the percentage of each group of patients using the total number of cases reported in each severity category (hospitalization, admission to ICU, and death). To evaluate the risk associated with pregnancy, the researchers used the ratio of pregnant women to all women of childbearing age (age 15–49 years) at each level of severity to describe the differences between levels.
The researchers were able to collect data on approximately 70,000 patients requiring hospitalization, 9,700 patients admitted to the ICU, and 2,500 patients who died from H1N1 infection. The proportion of patients with H1N1 with one or more reported chronic conditions increased with severity—the median was 31.1% of hospitalized patients, 52.3% of patients admitted to the ICU, and 61.8% of patients who died. For all levels of severity, pregnant women in their third trimester consistently accounted for the majority of the total of pregnant women. The proportion of patients with obesity increased with increasing disease severity—median of 6% of hospitalized patients, 11.3% of patients admitted to the ICU, and 12.0% of all deaths from H1N1.
What Do These Findings Mean?
These findings show that risk factors for severe H1N1 infection are similar to those for seasonal influenza, with some notable differences: a substantial proportion of people with severe and fatal cases of H1N1 had pre-existing chronic illness, which indicates that the presence of chronic illness increases the likelihood of death. Cardiac disease, chronic respiratory disease, and diabetes are important risk factors for severe disease that will be especially relevant for countries with high rates of these illnesses. Approximately 2/3 of hospitalized people and 40% of people who died from H1N1 infection did not have any identified pre-existing chronic illness, but this study was not able to comprehensively assess how many of these cases had other risk factors, such as pregnancy, obesity, smoking, and alcohol misuse. Because of large differences between countries, the role of risk factors such as obesity and pregnancy need further study—although there is sufficient evidence to support vaccination and early intervention for pregnant women. Overall, the findings of this study reinforce the need to identify and target high-risk groups for interventions such as immunization, early medical advice, and use of antiviral medications.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001053.
WHO provides a Global Alert and Response (GAR) with updates on a number of influenza-related topics
The US Centers for Disease Control and Prevention provides information on risk factors and H1N1
doi:10.1371/journal.pmed.1001053
PMCID: PMC3130021  PMID: 21750667
7.  Modeling the Worldwide Spread of Pandemic Influenza: Baseline Case and Containment Interventions 
PLoS Medicine  2007;4(1):e13.
Background
The highly pathogenic H5N1 avian influenza virus, which is now widespread in Southeast Asia and which diffused recently in some areas of the Balkans region and Western Europe, has raised a public alert toward the potential occurrence of a new severe influenza pandemic. Here we study the worldwide spread of a pandemic and its possible containment at a global level taking into account all available information on air travel.
Methods and Findings
We studied a metapopulation stochastic epidemic model on a global scale that considers airline travel flow data among urban areas. We provided a temporal and spatial evolution of the pandemic with a sensitivity analysis of different levels of infectiousness of the virus and initial outbreak conditions (both geographical and seasonal). For each spreading scenario we provided the timeline and the geographical impact of the pandemic in 3,100 urban areas, located in 220 different countries. We compared the baseline cases with different containment strategies, including travel restrictions and the therapeutic use of antiviral (AV) drugs. We investigated the effect of the use of AV drugs in the event that therapeutic protocols can be carried out with maximal coverage for the populations in all countries. In view of the wide diversity of AV stockpiles in different regions of the world, we also studied scenarios in which only a limited number of countries are prepared (i.e., have considerable AV supplies). In particular, we compared different plans in which, on the one hand, only prepared and wealthy countries benefit from large AV resources, with, on the other hand, cooperative containment scenarios in which countries with large AV stockpiles make a small portion of their supplies available worldwide.
Conclusions
We show that the inclusion of air transportation is crucial in the assessment of the occurrence probability of global outbreaks. The large-scale therapeutic usage of AV drugs in all hit countries would be able to mitigate a pandemic effect with a reproductive rate as high as 1.9 during the first year; with AV supply use sufficient to treat approximately 2% to 6% of the population, in conjunction with efficient case detection and timely drug distribution. For highly contagious viruses (i.e., a reproductive rate as high as 2.3), even the unrealistic use of supplies corresponding to the treatment of approximately 20% of the population leaves 30%–50% of the population infected. In the case of limited AV supplies and pandemics with a reproductive rate as high as 1.9, we demonstrate that the more cooperative the strategy, the more effective are the containment results in all regions of the world, including those countries that made part of their resources available for global use.
A metapopulation stochastic epidemic model for influenza shows the need to include air transportation when assessing the occurrence probability of global outbreaks. The impact of the use of antiviral drugs is also measured.
Editors' Summary
Background.
Seasonal outbreaks (epidemics) of influenza—a viral infection of the nose, throat, and airways—affect millions of people and kill about 500,000 individuals every year. Regular epidemics occur because flu viruses frequently make small changes in the viral proteins (antigens) recognized by the human immune system. Consequently, a person's immune-system response that combats influenza one year provides incomplete protection the next year. Occasionally, a human influenza virus appears that contains large antigenic changes. People have little immunity to such viruses (which often originate in birds or animals), so they can start a global epidemic (pandemic) that kills millions of people. Experts fear that a human influenza pandemic could be triggered by the avian H5N1 influenza virus, which is present in bird flocks around the world. So far, fewer than 300 people have caught this virus but more than 150 people have died.
Why Was This Study Done?
Avian H5N1 influenza has not yet triggered a human pandemic, because it rarely passes between people. If it does acquire this ability, it would take 6–8 months to develop a vaccine to provide protection against this new, potentially pandemic virus. Public health officials therefore need other strategies to protect people during the first few months of a pandemic. These could include international travel restrictions and the use of antiviral drugs. However, to get the most benefit from these interventions, public-health officials need to understand how influenza pandemics spread, both over time and geographically. In this study, the researchers have used detailed information on air travel to model the global spread of an emerging influenza pandemic and its containment.
What Did the Researchers Do and Find?
The researchers incorporated data on worldwide air travel and census data from urban centers near airports into a mathematical model of the spread of an influenza pandemic. They then used this model to investigate how the spread and health effects of a pandemic flu virus depend on the season in which it emerges (influenza virus thrives best in winter), where it emerges, and how infectious it is. Their model predicts, for example, that a flu virus originating in Hanoi, Vietnam, with a reproductive number (R0) of 1.1 (a measure of how many people an infectious individual infects on average) poses a very mild global threat. However, epidemics initiated by a virus with an R0 of more than 1.5 would often infect half the population in more than 100 countries. Next, the researchers used their model to show that strict travel restrictions would have little effect on pandemic evolution. More encouragingly, their model predicts that antiviral drugs would mitigate pandemics of a virus with an R0 up to 1.9 if every country had an antiviral drug stockpile sufficient to treat 5% of its population; if the R0 was 2.3 or higher, the pandemic would not be contained even if 20% of the population could be treated. Finally, the researchers considered a realistic scenario in which only a few countries possess antiviral stockpiles. In these circumstances, compared with a “selfish” strategy in which countries only use their antiviral drugs within their borders, limited worldwide sharing of antiviral drugs would slow down the spread of a flu virus with an R0 of 1.9 by more than a year and would benefit both drug donors and recipients.
What Do These Findings Mean?
Like all mathematical models, this model for the global spread of an emerging pandemic influenza virus contains many assumptions (for example, about viral behavior) that might affect the accuracy of its predictions. The model also does not consider variations in travel frequency between individuals or viral spread in rural areas. Nevertheless, the model provides the most extensive global simulation of pandemic influenza spread to date. Reassuringly, it suggests that an emerging virus with a low R0 would not pose a major public-health threat, since its attack rate would be limited and would not peak for more than a year, by which time a vaccine could be developed. Most importantly, the model suggests that cooperative sharing of antiviral drugs, which could be organized by the World Health Organization, might be the best way to deal with an emerging influenza pandemic.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040013.
The US Centers for Disease Control and Prevention has information about influenza for patients and professionals, including key facts about avian influenza and antiviral drugs
The US National Institute of Allergy and Infectious Disease features information on seasonal, avian, and pandemic flu
The US Department of Health and Human Services provides information on pandemic flu and avian flu, including advice to travelers
World Health Organization has fact sheets on influenza and avian influenza, including advice to travelers and current pandemic flu threat
The UK Health Protection Agency has information on seasonal, avian, and pandemic influenza
The UK Department of Health has a feature article on bird flu and pandemic influenza
doi:10.1371/journal.pmed.0040013
PMCID: PMC1779816  PMID: 17253899
8.  Epidemiological Characteristics of 2009 (H1N1) Pandemic Influenza Based on Paired Sera from a Longitudinal Community Cohort Study 
PLoS Medicine  2011;8(6):e1000442.
Steven Riley and colleagues analyze a community cohort study from the 2009 (H1N1) influenza pandemic in Hong Kong, and found that more children than adults were infected with H1N1, but children were less likely to progress to severe disease than adults.
Background
While patterns of incidence of clinical influenza have been well described, much uncertainty remains over patterns of incidence of infection. The 2009 pandemic provided both the motivation and opportunity to investigate patterns of mild and asymptomatic infection using serological techniques. However, to date, only broad epidemiological patterns have been defined, based on largely cross-sectional study designs with convenience sampling frameworks.
Methods and Findings
We conducted a paired serological survey of a cohort of households in Hong Kong, recruited using random digit dialing, and gathered data on severe confirmed cases from the public hospital system (>90% inpatient days). Paired sera were obtained from 770 individuals, aged 3 to 103, along with detailed individual-level and household-level risk factors for infection. Also, we extrapolated beyond the period of our study using time series of severe cases and we simulated alternate study designs using epidemiological parameters obtained from our data. Rates of infection during the period of our study decreased substantially with age: for 3–19 years, the attack rate was 39% (31%–49%); 20–39 years, 8.9% (5.3%–14.7%); 40–59 years, 5.3% (3.5%–8.0%); and 60 years or older, 0.77% (0.18%–4.2%). We estimated parameters for a parsimonious model of infection in which a linear age term and the presence of a child in the household were used to predict the log odds of infection. Patterns of symptom reporting suggested that children experienced symptoms more often than adults. The overall rate of confirmed pandemic (H1N1) 2009 influenza (H1N1pdm) deaths was 7.6 (6.2–9.5) per 100,000 infections. However, there was substantial and progressive increase in deaths per 100,000 infections with increasing age from 0.66 (0.65–0.86) for 3–19 years up to 220 (50–4,000) for 60 years and older. Extrapolating beyond the period of our study using rates of severe disease, we estimated that 56% (43%–69%) of 3–19 year olds and 16% (13%–18%) of people overall were infected by the pandemic strain up to the end of January 2010. Using simulation, we found that, during 2009, larger cohorts with shorter follow-up times could have rapidly provided similar data to those presented here.
Conclusions
Should H1N1pdm evolve to be more infectious in older adults, average rates of severe disease per infection could be higher in future waves: measuring such changes in severity requires studies similar to that described here. The benefit of effective vaccination against H1N1pdm infection is likely to be substantial for older individuals. Revised pandemic influenza preparedness plans should include prospective serological cohort studies. Many individuals, of all ages, remained susceptible to H1N1pdm after the main 2009 wave in Hong Kong.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
From June 2009 to August 2010, the world was officially (according to specific WHO criteria—WHO phase 6 pandemic alert) in the grip of an Influenza A pandemic with a new strain of the H1N1 virus. During this time, more than 214 countries and overseas territories reported laboratory confirmed cases of pandemic influenza H1N1 2009 with almost 20,000 deaths.
While much is already known about patterns of incidence of clinical influenza, the patterns of infection incidence are much more uncertain, because many influenza infections are either asymptomatic or cause only mild symptoms. This means that it is difficult to obtain accurate estimates of risk factors for infection and the overall burden of disease using only clinical surveillance. However, without accurate estimates of infection incidence across different risk groups, it is not possible to establish the number of infections that give rise to severe disease (the per infection rate of severe disease). Consequently, it is difficult to give evidence-based advice for individuals, groups, and populations about the potential benefits of interventions including drugs and vaccines that might reduce the risk of influenza infection.
Why Was This Study Done?
During the 2009 pandemic, some countries and territories, such as Hong Kong, were able to investigate patterns of mild and asymptomatic infection using serological techniques, thus providing information that may help to fill this knowledge gap. Given the high levels of polymerase chain reaction (PCR) testing and the robust reporting of hospital episodes, the main H1N1 pandemic wave in Hong Kong (during September 2009) provided an opportunity to implement a prospective cohort study to investigate the incidence of infection.
What Did the Researchers Do and Find? The researchers collected data on the asymptomatic symptoms of influenza by randomly selecting households to participate in the study. Each member of the household willing to participate had a baseline blood sample taken before the main wave of the pandemic (July to September 2009), then, when clinical surveillance suggested that the main peak in transmission had passed, after the main wave (November 2009 to February 2010). During the study period, participants were asked to report any flu-like symptoms in three ways: to phone the study team and report symptoms in real time; to fill out a paper diary with the day and symptoms; and to report symptoms during a follow-up interview. In parallel, the researchers monitored data on every patient with H1N1 admitted to intensive care units or who died while in the hospital. The researchers then estimated the number of H1N1 infections (infection incidence) per severe case by developing a likelihood-based framework. They used a simulation model to investigate alternate study designs and to validate their estimates of the rate of severe disease per infection.
Using these methods, the researchers found that rates of H1N1 infection during the study period decreased substantially with age: for 3–19 years, the attack rate was 39%; 20–39 years, 8.9%; 40–59 years, 5.3%; and 60 years or older, 0.77%. In addition, patterns of symptom reporting indicated that children experienced symptoms more often than adults. The overall rate of confirmed H1N1 deaths was 7.6 per 100,000 infections. However, there was a substantial and progressive increase in deaths per 100,000 infections with increasing age from 0.66 for 3–19 years up to 220 for 60 years and older. Statistical modeling suggested that 56% of 3–19 year olds and 16% of people overall were infected by the pandemic strain up to the end of January 2010.
What Do These Findings Mean?
The results of this study suggest that more children were infected with H1N1 than adults but most of them did not progress to severe disease. Conversely, although fewer older adults were infected with H1N1, this group was much more likely to experience severe disease. Therefore, should H1N1 infection incidence ever increase in older adults, for example by evolving to become more infectious to this group, average rates of severe disease per infection could be much higher than for the 2009 pandemic. Revised pandemic preparedness plans should include prospective serological cohort studies, such as this one, in order to be able to estimate rates of severe disease per infection.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000442.
WHO has information about the global response to the 2009 H1N1 pandemic
WHO also provides recommendations for the H1N1 post-pandemic period
The government of Hong Kong's Centre for Health Protection provides information about H1N1 in Hong Kong
doi:10.1371/journal.pmed.1000442
PMCID: PMC3119689  PMID: 21713000
9.  Early Pandemic Influenza (2009 H1N1) in Ho Chi Minh City, Vietnam: A Clinical Virological and Epidemiological Analysis 
PLoS Medicine  2010;7(5):e1000277.
Rogier van Doorn and colleagues analyze the initial outbreak, attempts at containment, and establishment of community transmission of pandemic H1N1 influenza in Ho Chi Minh City, Vietnam.
Background
To date, little is known about the initial spread and response to the 2009 pandemic of novel influenza A (“2009 H1N1”) in tropical countries. Here, we analyse the early progression of the epidemic from 26 May 2009 until the establishment of community transmission in the second half of July 2009 in Ho Chi Minh City (HCMC), Vietnam. In addition, we present detailed systematic viral clearance data on 292 isolated and treated patients and the first three cases of selection of resistant virus during treatment in Vietnam.
Methods and Findings
Data sources included all available health reports from the Ministry of Health and relevant health authorities as well as clinical and laboratory data from the first confirmed cases isolated at the Hospital for Tropical Diseases in HCMC. Extensive reverse transcription (RT)-PCR diagnostics on serial samples, viral culture, neuraminidase-inhibition testing, and sequencing were performed on a subset of 2009 H1N1 confirmed cases. Virological (PCR status, shedding) and epidemiological (incidence, isolation, discharge) data were combined to reconstruct the initial outbreak and the establishment of community transmission. From 27 April to 24 July 2009, approximately 760,000 passengers who entered HCMC on international flights were screened at the airport by a body temperature scan and symptom questionnaire. Approximately 0.15% of incoming passengers were intercepted, 200 of whom tested positive for 2009 H1N1 by RT-PCR. An additional 121 out of 169 nontravelers tested positive after self-reporting or contact tracing. These 321 patients spent 79% of their PCR-positive days in isolation; 60% of PCR-positive days were spent treated and in isolation. Influenza-like illness was noted in 61% of patients and no patients experienced pneumonia or severe outcomes. Viral clearance times were similar among patient groups with differing time intervals from illness onset to treatment, with estimated median clearance times between 2.6 and 2.8 d post-treatment for illness-to-treatment intervals of 1–4 d, and 2.0 d (95% confidence interval 1.5–2.5) when treatment was started on the first day of illness.
Conclusions
The patients described here represent a cross-section of infected individuals that were identified by temperature screening and symptom questionnaires at the airport, as well as mildly symptomatic to moderately ill patients who self-reported to hospitals. Data are observational and, although they are suggestive, it is not possible to be certain whether the containment efforts delayed community transmission in Vietnam. Viral clearance data assessed by RT-PCR showed a rapid therapeutic response to oseltamivir.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every year, millions of people catch influenza—a viral infection of the airways—and about half a million people die as a result. These yearly seasonal epidemics occur because small but frequent changes in the influenza virus mean that the immune response produced by infection with one year's virus provides only partial protection against the next year's virus. Sometimes, however, a very different influenza virus emerges to which people have virtually no immunity. Such viruses can start global epidemics (pandemics) and can kill millions of people. Consequently, when the first case of influenza caused by a new virus called pandemic A/H1N1 2009 (2009 H1N1, swine flu) occurred in March 2009 in Mexico, alarm bells rang. National and international public health agencies quickly issued advice about how the public could help to control the spread of the virus and, as the virus spread, some countries banned flights from affected regions and instigated screening for influenza-like illness at airports. However, despite everyone's efforts, the virus spread rapidly and on June 11, 2009 the World Health Organization (WHO) declared that an influenza pandemic was underway.
Why Was This Study Done?
To date, little is known about the spread of and response to 2009 H1N1 in tropical countries. In this study, therefore, the researchers investigate the early progression of the 2009 H1N1 pandemic in Ho Chi Minh City, Vietnam, and the treatment of infected patients. On April 27, 2009, when WHO announced that human-to-human transmission of 2009 H1N1 was occurring, the Vietnamese Ministry of Health mandated airport body temperature scans and symptom questionnaire screening of travelers arriving in Vietnam's international airports. Suspected cases were immediately transferred to in-hospital isolation, screened for virus using a sensitive test called PCR, and treated with the anti-influenza drug oseltamivir if positive. The first case of 2009 H1N1 infection in Vietnam was reported on May 31, 2009 in a student who had returned from the US on May 26, 2009, and, despite these efforts to contain the infection, by the second half of July the virus was circulating in Ho Chi Minh City (community transmission).
What Did the Researchers Do and Find?
The researchers used reports from the Ministry of Health and relevant health authorities and clinical and laboratory data for people infected with 2009 H1N1 and isolated in hospital to reconstruct the initial outbreak and the establishment of community transmission in Ho Chi Minh City. Between April 27 and July 24 2009, three-quarters of a million passengers arriving in the city on international flights were screened at the airport. 200 passenger tested positive for 2009 H1N1 as did 121 nontravelers who were identified during this period after self-reporting illness or through contact tracing. The infected individuals spent 79% of the days when they tested positive for 2009 H1N1 by PCR (days when they were infectious) in isolation; 60% of their PCR-positive days were spent in isolation and treatment. Importantly, travelers and nontravelers spent 10% and 42.2%, respectively, of their potentially infectious time in the community. None of the patients became severely ill but 61% experienced an influenza-like illness. Finally, the average time from starting treatment to clearance of the virus was between 2.6 and 2.8 days for patients who began treatment 1 to 4 days after becoming ill; for those who started treatment on the first day of illness, the average virus clearance time was 2.0 days.
What Do These Findings Mean?
These findings, although limited by missing data, suggest that the strict containment measures introduced early in the 2009 H1N1 pandemic in Ho Chi Minh City may have reduced the circulation of infected people in the community. This reduction in circulation might have delayed the onset of community transmission, suggest the researchers, but because the study was observational, this possibility cannot be proven. However, importantly, these findings show that the containment measures were unable to prevent the eventual establishment of pandemic influenza in Vietnam, presumably because many imported cases were not detected by airport screening. Finally, these findings suggest that in Vietnam, as in other countries, 2009 H1N1 causes a mild disease and that this disease responds quickly to treatment with oseltamivir whenever treatment is started in relation to the onset of illness.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000277.
The US Centers for Disease Control and Prevention provides information about influenza for patients and professionals, including specific information on H1N1 influenza and how to prevent its spread
Flu.gov, a US government website, provides information on H1N1, avian, and pandemic influenza
The World Health Organization provides information on seasonal influenza and has detailed information on H1N1 influenza (in several languages); the WHO Representative Office in Vietnam provides an overview of the current 2009 H1N1 situation in Vietnam
The UK Health Protection Agency provides information on pandemic influenza and on H1N1 influenza
Wikipedia has a timeline of the 2009 H1N1 pandemic (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1000277
PMCID: PMC2872648  PMID: 20502525
10.  Estimating Infection Attack Rates and Severity in Real Time during an Influenza Pandemic: Analysis of Serial Cross-Sectional Serologic Surveillance Data 
PLoS Medicine  2011;8(10):e1001103.
This study reports that using serological data coupled with clinical surveillance data can provide real-time estimates of the infection attack rates and severity in an emerging influenza pandemic.
Background
In an emerging influenza pandemic, estimating severity (the probability of a severe outcome, such as hospitalization, if infected) is a public health priority. As many influenza infections are subclinical, sero-surveillance is needed to allow reliable real-time estimates of infection attack rate (IAR) and severity.
Methods and Findings
We tested 14,766 sera collected during the first wave of the 2009 pandemic in Hong Kong using viral microneutralization. We estimated IAR and infection-hospitalization probability (IHP) from the serial cross-sectional serologic data and hospitalization data. Had our serologic data been available weekly in real time, we would have obtained reliable IHP estimates 1 wk after, 1–2 wk before, and 3 wk after epidemic peak for individuals aged 5–14 y, 15–29 y, and 30–59 y. The ratio of IAR to pre-existing seroprevalence, which decreased with age, was a major determinant for the timeliness of reliable estimates. If we began sero-surveillance 3 wk after community transmission was confirmed, with 150, 350, and 500 specimens per week for individuals aged 5–14 y, 15–19 y, and 20–29 y, respectively, we would have obtained reliable IHP estimates for these age groups 4 wk before the peak. For 30–59 y olds, even 800 specimens per week would not have generated reliable estimates until the peak because the ratio of IAR to pre-existing seroprevalence for this age group was low. The performance of serial cross-sectional sero-surveillance substantially deteriorates if test specificity is not near 100% or pre-existing seroprevalence is not near zero. These potential limitations could be mitigated by choosing a higher titer cutoff for seropositivity. If the epidemic doubling time is longer than 6 d, then serial cross-sectional sero-surveillance with 300 specimens per week would yield reliable estimates when IAR reaches around 6%–10%.
Conclusions
Serial cross-sectional serologic data together with clinical surveillance data can allow reliable real-time estimates of IAR and severity in an emerging pandemic. Sero-surveillance for pandemics should be considered.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every winter, millions of people catch influenza—a viral infection of the airways—and about half a million die as a result. These seasonal epidemics occur because small but frequent changes in the influenza virus mean that the immune response produced by infection with one year's virus provides only partial protection against the next year's virus. Occasionally, however, a very different influenza virus emerges to which people have virtually no immunity. Such viruses can start global epidemics (pandemics) and kill millions of people. The most recent influenza pandemic began in March 2009 in Mexico, when the first case of influenza caused by a new virus called pandemic A/H1N1 2009 (pdmH1N1) occurred. The virus spread rapidly despite strenuous efforts by national and international public health agencies to contain it, and on 11 June 2009, the World Health Organization (WHO) declared that an influenza pandemic was underway. By the time WHO announced that the pandemic was over (10 August 2010), pdmH1N1 had killed more than 18,000 people.
Why Was This Study Done?
Early in the 2009 influenza pandemic, as in any emerging pandemic, reliable estimates of pdmH1N1's transmissibility (how easily it spreads between people) and severity (the proportion of infected people who needed hospital treatment) were urgently needed to help public health officials plan their response to the pandemic and advise the public about the threat to their health. Because infection with an influenza virus does not always make people ill, the only way to determine the true size and severity of an influenza outbreak is to monitor the occurrence of antibodies (proteins made by the immune system in response to infections) to the influenza virus in the population—so-called serologic surveillance. In this study, the researchers developed a method that uses serologic data to provide real-time estimates of the infection attack rate (IAR; the cumulative occurrence of new infections in a population) and the infection-hospitalization probability (IHP; the proportion of affected individuals that needs to be hospitalized) during an influenza pandemic.
What Did the Researchers Do and Find?
The researchers tested nearly 15,000 serum samples collected in Hong Kong during the first wave of the 2009 pandemic for antibodies to pdmH1N1 and then used a mathematical approach called convolution to estimate IAR and IHP from these serologic data and hospitalization data. They report that if the serological data had been available weekly in real time, they would have been able to obtain reliable estimates of IAR and IHP by one week after, one to two weeks before, and three weeks after the pandemic peak for 5–14 year olds, 15–29 year olds, and 30–59 year olds, respectively. If serologic surveillance had begun three weeks after confirmation of community transmission of pdmH1N1, sample sizes of 150, 350, and 500 specimens per week from 5–14 year olds, 15–19 year olds, and 20–29 year olds, respectively, would have been sufficient to obtain reliable IAR and IHP estimates four weeks before the pandemic peak. However, for 30–59 year olds, even 800 specimens per week would not have generated reliable estimates because of pre-existing antibodies to an H1N1 virus in this age group. Finally, computer simulations of future pandemics indicate that serologic surveillance with 300 serum specimens per week would yield reliable estimates of IAR and IHP as soon as the true IAR reached about 6%.
What Do These Findings Mean?
These findings suggest that serologic data together with clinical surveillance data could be used to provide reliable real-time estimates of IARs and severity in an emerging influenza pandemic. Although the number of samples needed to provide accurate estimates of IAR and IHP in real life may vary somewhat from those reported here because of limitations in the design of this study, these findings nevertheless suggest that the level of testing capacity needed to provide real-time estimates of IAR and IHP during an emerging influenza pandemic should be logistically feasible for most developed countries. Moreover, collection of serologic surveillance data from any major city affected early in an epidemic could potentially provide information of global relevance for public health. Thus, the researchers conclude, serologic monitoring should be included in future plans for influenza pandemic preparedness and response and in planning for other pandemics.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001103.
A recent PLoS Medicine Research Article by Riley et al. provides further information on patterns of infection with the pdmH1N1 virus
The Hong Kong Centre for Health Protection provides information on pandemic H1N1 influenza
The US Centers for Disease Control and Prevention provides information about influenza for patients and professionals, including specific information on H1N1 influenza
Flu.gov, a US government website, provides access to information on seasonal, pandemic, and H1N1 influenza
WHO provides information on seasonal influenza and has information on the global response to H1N1 influenza (in several languages)
The UK Health Protection Agency provides information on pandemic influenza and on H1N1 influenza
More information for patients about H1N1 influenza is available through Choices, an information resource provided by the UK National Health Service
doi:10.1371/journal.pmed.1001103
PMCID: PMC3186812  PMID: 21990967
11.  Outcomes from pandemic influenza A H1N1 infection in recipients of solid-organ transplants: a multicentre cohort study 
The Lancet infectious diseases  2010;10(8):521-526.
Summary
Background
There are few data on the epidemiology and outcomes of influenza infection in recipients of solid-organ transplants. We aimed to establish the outcomes of pandemic influenza A H1N1 and factors leading to severe disease in a cohort of patients who had received transplants.
Methods
We did a multicentre cohort study of adults and children who had received organ transplants with microbiological confirmation of influenza A infection from April to December, 2009. Centres were identified through the American Society of Transplantation Influenza Collaborative Study Group. Demographics, clinical presentation, treatment, and outcomes were assessed. Severity of disease was measured by admission to hospital and intensive care units (ICUs). The data were analysed with descriptive statistics. Proportions were compared by use of χ2 tests. We used univariate analysis to identify factors leading to pneumonia, admission to hospital, and admission to an ICU. Multivariate analysis was done by use of a stepwise logistic regression model. We analysed deaths with Kaplan-Meier survival analysis.
Findings
We assessed 237 cases of medically attended influenza A H1N1 reported from 26 transplant centres during the study period. Transplant types included kidney, liver, heart, lung, and others. Both adults (154 patients; median age 47 years) and children (83; 9 years) were assessed. Median time from transplant was 3.6 years. 167 (71%) of 237 patients were admitted to hospital. Data on complications were available for 230 patients; 73 (32%) had pneumonia, 37 (16%) were admitted to ICUs, and ten (4%) died. Antiviral treatment was used in 223 (94%) patients (primarily oseltamivir monotherapy). Seven (8%) patients given antiviral drugs within 48 h of symptom onset were admitted to an ICU compared with 28 (22.4%) given antivirals later (p=0.007). Children who received transplants were less likely to present with pneumonia than adults, but rates of admission to hospital and ICU were similar.
Interpretation
Influenza A H1N1 caused substantial morbidity in recipients of solid-organ transplants during the 2009–10 pandemic. Starting antiviral therapy early is associated with clinical benefit as measured by need for ICU admission and mechanical ventilation.
doi:10.1016/S1473-3099(10)70133-X
PMCID: PMC3045703  PMID: 20620116
12.  Correlates of severe disease in patients with 2009 pandemic influenza (H1N1) virus infection 
Background
In the context of 2009 pandemic influenza (H1N1) virus infection (pandemic H1N1 influenza), identifying correlates of the severity of disease is critical to guiding the implementation of antiviral strategies, prioritization of vaccination efforts and planning of health infrastructure. The objective of this study was to identify factors correlated with severity of disease in confirmed cases of pandemic H1N1 influenza.
Methods
This cumulative case–control study included all laboratory-confirmed cases of pandemic H1N1 influenza among residents of the province of Manitoba, Canada, for whom the final location of treatment was known. Severe cases were defined by admission to a provincial intensive care unit (ICU). Factors associated with severe disease necessitating admission to the ICU were determined by comparing ICU cases with two control groups: patients who were admitted to hospital but not to an ICU and those who remained in the community.
Results
As of Sept. 5, 2009, there had been 795 confirmed cases of pandemic H1N1 influenza in Manitoba for which the final treatment location could be determined. The mean age of individuals with laboratory-confirmed infection was 25.3 (standard deviation 18.8) years. More than half of the patients (417 or 52%) were female, and 215 (37%) of 588 confirmed infections for which ethnicity was known occurred in First Nations residents. The proportion of First Nations residents increased with increasing severity of disease (116 [28%] of 410 community cases, 74 [54%] of 136 admitted to hospital and 25 [60%] of 42 admitted to an ICU; p < 0.001), as did the presence of an underlying comorbidity (201 [35%] of 569 community cases, 103 [57%] of 181 admitted to hospital and 34 [76%] of 45 admitted to an ICU; p < 0.001). The median interval from onset of symptoms to initiation of antiviral therapy was 2 days (interquartile range, IQR 1–3) for community cases, 4 days (IQR 2–6) for patients admitted to hospital and 6 days (IQR 4–9) for those admitted to an ICU (p < 0.001). In a multivariable logistic model, the interval from onset of symptoms to initiation of antiviral therapy (odds ratio [OR] 8.24, 95% confidence interval [CI] 2.82–24.1), First Nations ethnicity (OR 6.52, 95% CI 2.04–20.8) and presence of an underlying comorbidity (OR 3.19, 95% CI 1.07–9.52) were associated with increased odds of admission to the ICU (i.e., severe disease) relative to community cases. In an analysis of ICU cases compared with patients admitted to hospital, First Nations ethnicity (OR 3.23, 95% CI 1.04–10.1) was associated with increased severity of disease.
Interpretation
Severe pandemic H1N1 influenza necessitating admission to the ICU was associated with a longer interval from onset of symptoms to treatment with antiviral therapy and with the presence of an underlying comorbidity. First Nations ethnicity appeared to be an independent determinant of severe infection. Despite these associations, the cause and outcomes of pandemic HINI influenza may involve many complex and interrelated factors, all of which require further research and analysis.
doi:10.1503/cmaj.091884
PMCID: PMC2826467  PMID: 20093297
13.  Supply of Neuraminidase Inhibitors Related to Reduced Influenza A (H1N1) Mortality during the 2009–2010 H1N1 Pandemic: An Ecological Study 
PLoS ONE  2012;7(9):e43491.
Background
The influenza A (H1N1) pandemic swept across the globe from April 2009 to August 2010 affecting millions. Many WHO Member States relied on antiviral drugs, specifically neuraminidase inhibitors (NAIs) oseltamivir and zanamivir, to treat influenza patients in critical condition. Such drugs have been found to be effective in reducing severity and duration of influenza illness, and likely reduced morbidity during the pandemic. However, it is less clear whether NAIs used during the pandemic reduced H1N1 mortality.
Methods
Country-level data on supply of oseltamivir and zanamivir were used to predict H1N1 mortality (per 100,000 people) from July 2009 to August 2010 in forty-two WHO Member States. Poisson regression was used to model the association between NAI supply and H1N1 mortality, with adjustment for economic, demographic, and health-related confounders.
Results
After adjustment for potential confounders, each 10% increase in kilograms of oseltamivir, per 100,000 people, was associated with a 1.6% reduction in H1N1 mortality over the pandemic period (relative rate (RR) = 0.84 per log increase in oseltamivir supply). While the supply of zanamivir was considerably less than that of oseltamivir in each Member State, each 10% increase in kilogram of active zanamivir, per 100,000, was associated with a 0.3% reduction in H1N1 mortality (RR = 0.97 per log increase).
Conclusion
While there are limitations to the ecologic nature of these data, this analysis offers evidence of a protective relationship between antiviral drug supply and influenza mortality and supports a role for influenza antiviral use in future pandemics.
doi:10.1371/journal.pone.0043491
PMCID: PMC3439456  PMID: 22984431
14.  A Review of Adult Mortality Due to 2009 Pandemic (H1N1) Influenza A in California 
PLoS ONE  2011;6(4):e18221.
Background
While children and young adults had the highest attack rates due to 2009 pandemic (H1N1) influenza A (2009 H1N1), studies of hospitalized cases noted high fatality in older adults. We analyzed California public health surveillance data to better characterize the populations at risk for dying due to 2009 H1N1.
Methods and Findings
A case was an adult ≥20 years who died with influenza-like symptoms and laboratory results indicative of 2009 H1N1. Demographic and clinical data were abstracted from medical records using a standardized case report form. From April 3, 2009 – August 10, 2010, 541 fatal cases ≥20 years with 2009 H1N1 were reported. Influenza fatality rates per 100,000 population were highest in persons 50–59 years (3.5; annualized rate = 2.6) and 60–69 years (2.3; annualized rate = 1.7) compared to younger and older age groups (0.4–1.9; annualized rates = 0.3–1.4). Of 486 cases hospitalized prior to death, 441 (91%) required intensive care unit (ICU) admission. ICU admission rates per 100,000 population were highest in adults 50–59 years (8.6). ICU case-fatality ratios among adults ranged from 24–42%, with the highest ratios in persons 70–79 years. A total of 425 (80%) cases had co-morbid conditions associated with severe seasonal influenza. The prevalence of most co-morbid conditions increased with increasing age, but obesity, pregnancy and obstructive sleep apnea decreased with age. Rapid testing was positive in 97 (35%) of 276 tested. Of 482 cases with available data, 384 (80%) received antiviral treatment, including 49 (15%) of 328 within 48 hours of symptom onset.
Conclusions
Adults aged 50–59 years had the highest fatality due to 2009 H1N1; older adults may have been spared due to pre-existing immunity. However, once infected and hospitalized in intensive care, case-fatality ratios were high for all adults, especially in those over 60 years. Vaccination of adults older than 50 years should be encouraged.
doi:10.1371/journal.pone.0018221
PMCID: PMC3071719  PMID: 21483677
15.  Association between the 2008–09 Seasonal Influenza Vaccine and Pandemic H1N1 Illness during Spring–Summer 2009: Four Observational Studies from Canada 
PLoS Medicine  2010;7(4):e1000258.
In three case-control studies and a household transmission cohort, Danuta Skowronski and colleagues find an association between prior seasonal flu vaccination and increased risk of 2009 pandemic H1N1 flu.
Background
In late spring 2009, concern was raised in Canada that prior vaccination with the 2008–09 trivalent inactivated influenza vaccine (TIV) was associated with increased risk of pandemic influenza A (H1N1) (pH1N1) illness. Several epidemiologic investigations were conducted through the summer to assess this putative association.
Methods and Findings
Studies included: (1) test-negative case-control design based on Canada's sentinel vaccine effectiveness monitoring system in British Columbia, Alberta, Ontario, and Quebec; (2) conventional case-control design using population controls in Quebec; (3) test-negative case-control design in Ontario; and (4) prospective household transmission (cohort) study in Quebec. Logistic regression was used to estimate odds ratios for TIV effect on community- or hospital-based laboratory-confirmed seasonal or pH1N1 influenza cases compared to controls with restriction, stratification, and adjustment for covariates including combinations of age, sex, comorbidity, timeliness of medical visit, prior physician visits, and/or health care worker (HCW) status. For the prospective study risk ratios were computed. Based on the sentinel study of 672 cases and 857 controls, 2008–09 TIV was associated with statistically significant protection against seasonal influenza (odds ratio 0.44, 95% CI 0.33–0.59). In contrast, estimates from the sentinel and three other observational studies, involving a total of 1,226 laboratory-confirmed pH1N1 cases and 1,505 controls, indicated that prior receipt of 2008–09 TIV was associated with increased risk of medically attended pH1N1 illness during the spring–summer 2009, with estimated risk or odds ratios ranging from 1.4 to 2.5. Risk of pH1N1 hospitalization was not further increased among vaccinated people when comparing hospitalized to community cases.
Conclusions
Prior receipt of 2008–09 TIV was associated with increased risk of medically attended pH1N1 illness during the spring–summer 2009 in Canada. The occurrence of bias (selection, information) or confounding cannot be ruled out. Further experimental and epidemiological assessment is warranted. Possible biological mechanisms and immunoepidemiologic implications are considered.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every winter, millions of people catch influenza—a viral infection of the airways—and hundreds of thousands of people die as a result. These seasonal epidemics occur because small but frequent changes in the influenza virus mean that an immune response produced one year through infection or vaccination provides only partial protection against influenza the next year. Annual vaccination with killed influenza viruses of the major circulating strains can greatly reduce a person's risk of catching influenza. Consequently, many countries run seasonal influenza vaccination programs. In most of Canada, vaccination with a mixture of three inactivated viruses (a trivalent inactivated vaccine or TIV) is provided free to children aged 6–23 months, to elderly people, to people with long-term conditions that increase their risk of influenza-related complications, and those who provide care for them; in Ontario, free vaccination is offered to everyone older than 6 months.
In addition, influenza viruses occasionally emerge that are very different and to which human populations have virtually no immunity. These viruses can start global epidemics (pandemics) that can kill millions of people. Experts have been warning for some time that an influenza pandemic is long overdue and, in March 2009, the first cases of influenza caused by a new virus called pandemic A/H1N1 2009 (pH1N1; swine flu) occurred in Mexico. The virus spread rapidly and on 11 June 2009, the World Health Organization declared that a global pandemic of pH1N1 influenza was underway. By the end of February 2010, more than 16,000 people around the world had died from pH1N1.
Why Was This Study Done?
During an investigation of a school outbreak of pH1N1 in the late spring 2009 in Canada, investigators noted that people with illness characterized by fever and coughing had been vaccinated against seasonal influenza more often than individuals without such illness. To assess whether this association between prior vaccination with seasonal 2008–09 TIV and subsequent pH1N1 illness was evident in other settings, researchers in Canada therefore conducted additional studies using different methods. In this paper, the researchers report the results of four additional studies conducted in Canada during the summer of 2009 to assess this possible association.
What Did the Researchers Do and Find?
The researchers conducted four epidemiologic studies. Epidemiology is the study of the causes, distribution, and control of diseases in populations.
Three of the four studies were case-control studies in which the researchers assessed the frequency of prior vaccination with the 2008–09 TIV in people with pH1N1 influenza compared to the frequency among healthy members of the general population or among individuals who had an influenza-like illness but no sign of infection with an influenza virus. The researchers also did a household transmission study in which they collected information about vaccination with TIV among the additional cases of influenza that were identified in 47 households in which a case of laboratory-confirmed pH1N1 influenza had occurred. The first of the case-control studies, which was based on Canada's vaccine effectiveness monitoring system, showed that, as expected, the 2008–09 TIV provided protection against seasonal influenza. However, estimates from all four studies (which included about 1,200 laboratory-confirmed pH1N1 cases and 1,500 controls) showed that prior recipients of the 2008–09 TIV had approximately 1.4–2.5 times increased chances of developing pH1N1 illness that needed medical attention during the spring–summer of 2009 compared to people who had not received the TIV. Prior seasonal vaccination was not associated with an increase in the severity of pH1N1 illness, however. That is, it did not increase the risk of being hospitalized among those with pH1N1 illness.
What Do These Findings Mean?
Because all the investigations in this study are “observational,” the people who had been vaccinated might share another unknown characteristic that is actually responsible for increasing their risk of developing pH1N1 illness (“confounding”). Furthermore, the results reported in this study might have arisen by chance, although the consistency of results across the studies makes this unlikely. Thus, the finding of an association between prior receipt of 2008–09 TIV and an increased risk of pH1N1 illness is not conclusive and needs to be investigated further, particularly since some other observational studies conducted in other countries have reported that seasonal vaccination had no influence or may have been associated with reduced chances of pH1N1 illness. If the findings in the current study are real, however, they raise important questions about the biological interactions between seasonal and pandemic influenza strains and vaccines, and about the best way to prevent and control both types of influenza in future.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/ 10.1371/journal.pmed.1000258.
This article is further discussed in a PLoS Medicine Perspective by Cécile Viboud and Lone Simonsen
FightFlu.ca, a Canadian government Web site, provides access to information on pH1N1 influenza
The US Centers for Disease Control and Prevention provides information about influenza for patients and professionals, including specific information on H1N1 influenza
Flu.gov, a US government website, provides access to information on H1N1, avian and pandemic influenza
The World Health Organization provides information on seasonal influenza and has detailed information on pH1N1 influenza (in several languages)
The UK Health Protection Agency provides information on pandemic influenza and on pH1N1 influenza
doi:10.1371/journal.pmed.1000258
PMCID: PMC2850386  PMID: 20386731
16.  Efficacy of Oseltamivir-Zanamivir Combination Compared to Each Monotherapy for Seasonal Influenza: A Randomized Placebo-Controlled Trial 
PLoS Medicine  2010;7(11):e1000362.
Analysis of virological and clinical outcomes from a randomized trial that was terminated early suggest that combined treatment of seasonal influenza in adult outpatients with oseltamivir plus zanamivir is no more effective than either oseltamivir or zanamivir monotherapy.
Background
Neuraminidase inhibitors are thought to be efficacious in reducing the time to alleviation of symptoms in outpatients with seasonal influenza. The objective of this study was to compare the short-term virological efficacy of oseltamivir-zanamivir combination versus each monotherapy plus placebo.
Methods and Findings
We conducted a randomized placebo-controlled trial with 145 general practitioners throughout France during the 2008–2009 seasonal influenza epidemic. Patients, general practitioners, and outcome assessors were all blinded to treatment assignment. Adult outpatients presenting influenza-like illness for less than 36 hours and a positive influenza A rapid test diagnosis were randomized to oseltamivir 75 mg orally twice daily plus zanamivir 10 mg by inhalation twice daily (OZ), oseltamivir plus inhaled placebo (O), or zanamivir plus oral placebo (Z). Treatment efficacy was assessed virologically according to the proportion of patients with nasal influenza reverse transcription (RT)-PCR below 200 copies genome equivalent (cgeq)/µl at day 2 (primary outcome), and clinically to the time to alleviation of symptoms until day 14. Overall 541 patients (of the 900 planned) were included (OZ, n = 192; O, n = 176; Z, n = 173), 49% male, mean age 39 years. In the intention-to-treat analysis conducted in the 447 patients with RT-PCR-confirmed influenza A, 46%, 59%, and 34% in OZ (n = 157), O (n = 141), and Z (n = 149) arms had RT-PCR<200 cgeq/µl (−13.0%, 95% confidence interval [CI] −23.1 to −2.9, p = 0.025; +12.3%, 95% CI 2.39–22.2, p = 0.028 for OZ/O and OZ/Z comparisons). Mean day 0 to day 2 viral load decrease was 2.14, 2.49, and 1.68 log10 cgeq/µl (p = 0.060, p = 0.016 for OZ/O and OZ/Z). Median time to alleviation of symptoms was 4.0, 3.0, and 4.0 days (+1.0, 95% CI 0.0–4.0, p = 0.018; +0.0, 95% CI −3.0 to 3.0, p = 0.960 for OZ/O and OZ/Z). Four severe adverse events were observed. Nausea and/or vomiting tended to be more frequent in the combination arm (OZ, n = 13; O, n = 4; and Z, n = 5 patients, respectively).
Conclusions
In adults with seasonal influenza A mainly H3N2 virus infection, the oseltamivir-zanamivir combination appeared less effective than oseltamivir monotherapy, and not significantly more effective than zanamivir monotherapy. Despite the theoretical potential for the reduction of the emergence of antiviral resistance, the lower effectiveness of this combination calls for caution in its use in clinical practice.
Trial registration
www.ClinicalTrials.gov NCT00799760
Please see later in the article for the Editors' Summary
Editors' Summary
Background
In the last few years, use of the neuraminidase inhibitors, oseltamivir and zanamivir, has been considered a key strategy for limiting the impact of influenza both in individuals (by reducing morbidity and mortality) and collectively (by slowing the virus' spread to buy time for vaccine production, the cornerstone of influenza control). However, there are concerns that widespread use of a single antiviral drug may lead to resistant strains, which could dramatically reduce its effectiveness in future. Theoretically, if well tolerated, and if producing at least additive antiviral activity, the combination of two antiviral agents could offer several advantages such as reducing disease severity and reducing the viral shedding period, which in turn could lead to lower infection rates and reduced resistance especially in immunocompromised patients. Importantly, combining two drugs could ensure optimal treatment of all types of circulating influenza virus and subtypes or variants. The combination of two neuraminidase inhibitors is feasible as both oseltamivir and zanamivir are licensed for seasonal influenza and have different key mutations associated with resistance to each drug.
Why Was This Study Done?
As yet, there have been no robust randomized controlled trials that compare the effectiveness of monotherapy with either oseltamivir or zanamivir with the effectiveness of a oseltamivir-zanamivir combination. Such a study would be important for influenza pandemic planning.
What Did the Researchers Do and Find?
The researchers conducted a randomized, placebo-controlled trial within 145 general practitioners throughout France during the seasonal influenza epidemic in 2008–2009. Adults who visited their general practitioner with symptoms of an influenza-like illness for less than 36 hours and who had a positive influenza A rapid test were randomized to one of three arms: (1) oral oseltamivir 75 mg twice daily plus zanamivir 10 mg by inhalation twice daily, (2) oral oseltamivir 75 mg twice daily plus inhaled placebo, or (3) zanamivir 10 mg by inhalation twice daily plus oral placebo. The effects of the drugs or combination of drugs was assessed virologically, by looking at the proportion of patients with nasal influenza reverse transcription (RT)-PCR below a particular level on day 2 of treatment. Clinical measures of effectiveness included the time to resolution of illness, the number of patients with alleviation of symptoms at the end of treatment, and the incidence of secondary complications of influenza such as otitis, bronchitis, sinusitis, and pneumonia. In the study, patients, general practitioners, and outcome assessors were all blinded to treatment assignments. Due to the emergence of the H1N1 pandemic in 2009, the study's independent data-monitoring committee requested that the researchers terminate the trial early and analyze the results earlier than planned.
541 patients (of the 900 planned) were enrolled in the study (192 in group 1; 176 in group 2; and 173 in group 3) of whom 447 were infected with influenza A. Overall the oseltamivir-zanamivir combination was both virologically and clinically significantly less effective than the oseltamivir monotherapy. In addition, the clinical effects of the oseltamivir-zanamivir combination on time to resolution of symptoms were not significantly different from that of zanamivir monotherapy, suggesting that oseltamivir does not add clinical benefit to zanamivir monotherapy.
What Do These Findings Mean?
The results of this study essentially show that in France during the Winter of 2009 prepandemic (of which 85% was due to of H3N2 virus), in adults with seasonal influenza A virus infection, the combination of oseltamivir and zanamivir was less effective than oseltamivir monotherapy and not significantly more effective than zanamivir monotherapy. These results call for caution in the use of the oseltamivir-zanamivir combination in treatment of adult outpatients. In addition, as the clinical and virological effects of oseltamivir monotherapy over zanamivir monotherapy were superior in this trial, oseltamivir should be the recommended treatment during influenza seasons with predominant H3N2 viruses. However, the results of this study should be confirmed in the coming years on future circulating influenza viruses.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000362.
Wikipedia has information on H3N3 influenza A virus (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
The World Health Organization has a global alert and response site on seasonal influenza
Patient UK provides information about antivirals for influenza
Answers.com has information about oseltamivir and about zanamivir
doi:10.1371/journal.pmed.1000362
PMCID: PMC2970549  PMID: 21072246
17.  Impact of antiviral treatment and hospital admission delay on risk of death associated with 2009 A/H1N1 pandemic influenza in Mexico 
Background
Increasing our understanding of the factors affecting the severity of the 2009 A/H1N1 influenza pandemic in different regions of the world could lead to improved clinical practice and mitigation strategies for future influenza pandemics. Even though a number of studies have shed light into the risk factors associated with severe outcomes of 2009 A/H1N1 influenza infections in different populations (e.g., [1-5]), analyses of the determinants of mortality risk spanning multiple pandemic waves and geographic regions are scarce. Between-country differences in the mortality burden of the 2009 pandemic could be linked to differences in influenza case management, underlying population health, or intrinsic differences in disease transmission [6]. Additional studies elucidating the determinants of disease severity globally are warranted to guide prevention efforts in future influenza pandemics.
In Mexico, the 2009 A/H1N1 influenza pandemic was characterized by a three-wave pattern occurring in the spring, summer, and fall of 2009 with substantial geographical heterogeneity [7]. A recent study suggests that Mexico experienced high excess mortality burden during the 2009 A/H1N1 influenza pandemic relative to other countries [6]. However, an assessment of potential factors that contributed to the relatively high pandemic death toll in Mexico are lacking. Here, we fill this gap by analyzing a large series of laboratory-confirmed A/H1N1 influenza cases, hospitalizations, and deaths monitored by the Mexican Social Security medical system during April 1 through December 31, 2009 in Mexico. In particular, we quantify the association between disease severity, hospital admission delays, and neuraminidase inhibitor use by demographic characteristics, pandemic wave, and geographic regions of Mexico.
Methods
We analyzed a large series of laboratory-confirmed pandemic A/H1N1 influenza cases from a prospective surveillance system maintained by the Mexican Social Security system, April-December 2009. We considered a spectrum of disease severity encompassing outpatient visits, hospitalizations, and deaths, and recorded demographic and geographic information on individual patients. We assessed the impact of neuraminidase inhibitor treatment and hospital admission delay (≤ > 2 days after disease onset) on the risk of death by multivariate logistic regression.
Results
Approximately 50% of all A/H1N1-positive patients received antiviral medication during the Spring and Summer 2009 pandemic waves in Mexico while only 9% of A/H1N1 cases received antiviral medications during the fall wave (P < 0.0001). After adjustment for age, gender, and geography, antiviral treatment significantly reduced the risk of death (OR = 0.52 (95% CI: 0.30, 0.90)) while longer hospital admission delays increased the risk of death by 2.8-fold (95% CI: 2.25, 3.41).
Conclusions
Our findings underscore the potential impact of decreasing admission delays and increasing antiviral use to mitigate the mortality burden of future influenza pandemics.
doi:10.1186/1471-2334-12-97
PMCID: PMC3449201  PMID: 22520743
2009 A/H1N1 influenza pandemic; Neuraminidase inhibitors; Antivirals; Case fatality ratio; Multivariate logistic regression; Hospital admission delay; Pandemic wave; Mexico.
18.  Estimates of Pandemic Influenza Vaccine Effectiveness in Europe, 2009–2010: Results of Influenza Monitoring Vaccine Effectiveness in Europe (I-MOVE) Multicentre Case-Control Study 
PLoS Medicine  2011;8(1):e1000388.
Results from a European multicentre case-control study reported by Marta Valenciano and colleagues suggest good protection by the pandemic monovalent H1N1 vaccine against pH1N1 and no effect of the 2009–2010 seasonal influenza vaccine on H1N1.
Background
A multicentre case-control study based on sentinel practitioner surveillance networks from seven European countries was undertaken to estimate the effectiveness of 2009–2010 pandemic and seasonal influenza vaccines against medically attended influenza-like illness (ILI) laboratory-confirmed as pandemic influenza A (H1N1) (pH1N1).
Methods and Findings
Sentinel practitioners swabbed ILI patients using systematic sampling. We included in the study patients meeting the European ILI case definition with onset of symptoms >14 days after the start of national pandemic vaccination campaigns. We compared pH1N1 cases to influenza laboratory-negative controls. A valid vaccination corresponded to >14 days between receiving a dose of vaccine and symptom onset. We estimated pooled vaccine effectiveness (VE) as 1 minus the odds ratio with the study site as a fixed effect. Using logistic regression, we adjusted VE for potential confounding factors (age group, sex, month of onset, chronic diseases and related hospitalizations, smoking history, seasonal influenza vaccinations, practitioner visits in previous year). We conducted a complete case analysis excluding individuals with missing values and a multiple multivariate imputation to estimate missing values. The multivariate imputation (n = 2902) adjusted pandemic VE (PIVE) estimates were 71.9% (95% confidence interval [CI] 45.6–85.5) overall; 78.4% (95% CI 54.4–89.8) in patients <65 years; and 72.9% (95% CI 39.8–87.8) in individuals without chronic disease. The complete case (n = 1,502) adjusted PIVE were 66.0% (95% CI 23.9–84.8), 71.3% (95% CI 29.1–88.4), and 70.2% (95% CI 19.4–89.0), respectively. The adjusted PIVE was 66.0% (95% CI −69.9 to 93.2) if vaccinated 8–14 days before ILI onset. The adjusted 2009–2010 seasonal influenza VE was 9.9% (95% CI −65.2 to 50.9).
Conclusions
Our results suggest good protection of the pandemic monovalent vaccine against medically attended pH1N1 and no effect of the 2009–2010 seasonal influenza vaccine. However, the late availability of the pandemic vaccine and subsequent limited coverage with this vaccine hampered our ability to study vaccine benefits during the outbreak period. Future studies should include estimation of the effectiveness of the new trivalent vaccine in the upcoming 2010–2011 season, when vaccination will occur before the influenza season starts.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Following the World Health Organization's declaration of pandemic phase six in June 2009, manufacturers developed vaccines against pandemic influenza A 2009 (pH1N1). On the basis of the scientific opinion of the European Medicines Agency, the European Commission initially granted marketing authorization to three pandemic vaccines for use in European countries. During the autumn of 2009, most European countries included the 2009–2010 seasonal influenza vaccine and the pandemic vaccine in their influenza vaccination programs.
The Influenza Monitoring Vaccine Effectiveness in Europe network (established to monitor seasonal and pandemic influenza vaccine effectiveness) conducted seven case-control and three cohort studies in seven European countries in 2009–2010 to estimate the effectiveness of the pandemic and seasonal vaccines. Data from the seven pilot case-control studies were pooled to provide overall adjusted estimates of vaccine effectiveness.
Why Was This Study Done?
After seasonal and pandemic vaccines are made available to populations, it is necessary to estimate the effectiveness of the vaccines at the population level during every influenza season. Therefore, this study was conducted in European countries to estimate the pandemic influenza vaccine effectiveness and seasonal influenza vaccine effectiveness against people presenting to their doctor with influenza-like illness who were confirmed (by laboratory tests) to be infected with pH1N1.
What Did the Researchers Do and Find?
The researchers conducted a multicenter case-control study on the basis of practitioner surveillance networks from seven countries—France, Hungary, Ireland, Italy, Romania, Portugal, and Spain. Patients consulting a participating practitioner for influenza-like illness had a nasal or throat swab taken within 8 days of symptom onset. Cases were swabbed patients who tested positive for pH1N1. Patients presenting with influenza-like illness whose swab tested negative for any influenza virus were controls.
Individuals were considered vaccinated if they had received a dose of the vaccine more than 14 days before the date of onset of influenza-like illness and unvaccinated if they were not vaccinated at all, or if the vaccine was given less than 15 days before the onset of symptoms. The researchers analyzed pandemic influenza vaccination effectiveness in those vaccinated less than 8 days, those vaccinated between and including 8 and 14 days, and those vaccinated more than 14 days before onset of symptoms compared to those who had never been vaccinated.
The researchers used modeling (taking account of all potential confounding factors) to estimate adjusted vaccine effectiveness and stratified the adjusted pandemic influenza vaccine effectiveness and the adjusted seasonal influenza vaccine effectiveness in three age groups (<15, 15–64, and ≥65 years of age).
The adjusted results suggest that the 2009–2010 seasonal influenza vaccine did not protect against pH1N1 illness. However, one dose of the pandemic vaccines used in the participating countries conferred good protection (65.5%–100% according to various stratifications performed) against pH1N1 in people who attended their practitioner with influenza-like illness, especially in people aged <65 years and in those without any chronic disease. Furthermore, good pandemic influenza vaccine effectiveness was observed as early as 8 days after vaccination.
What Do These Findings Mean?
The results of this study provide early estimates of the pandemic influenza vaccine effectiveness suggesting that the monovalent pandemic vaccines have been effective. The findings also give an indication of the vaccine effectiveness for the Influenza A (H1N1) 2009 strain included in the 2010–2011 seasonal vaccines, although specific vaccine effectiveness studies will have to be conducted to verify if similar good effectiveness are observed with 2010–2011 trivalent vaccines. However, the results of this study should be interpreted with caution because of limitations in the pandemic context (late timing of the studies, low incidence, low vaccine coverage leading to imprecise estimates) and potential biases due the study design, confounding factors, and missing values. The researchers recommend that in future season studies, the sample size per country should be enlarged in order to allow for precise pooled and stratified analyses.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000388.
The World Health Organization has information on H1N1 vaccination
The US Centers for Disease Control and Prevention provides a fact sheet on the 2009 H1N1 influenza virus
The US Department of Health and Human services has a comprehensive website on flu
The European Centre for Disease Prevention and Control provides information on 2009 H1N1 pandemic
The European Centre for Disease Prevention and Control presents a summary of the 2009 H1N1 pandemic in Europe and elsewhere
doi:10.1371/journal.pmed.1000388
PMCID: PMC3019108  PMID: 21379316
19.  Fatal Cases of 2009 Pandemic Influenza A (H1N1) in Korea 
The aim of this study was to describe the features of deaths associated with the 2009 pandemic influenza A (H1N1) by 26 November 2009 in Korea. We collected standardized case reports on 115 confirmed deaths through a nationwide enhanced influenza surveillance system. The median age was 61 yr (interquartile range [IQR], 0.2-97 yr) and 58 (50.4%) were females. The case fatality rate was estimated as 16 per 100,000 cases. The age-related mortality rate had a J-shaped curve. Eighty-three patients (72.2%) had at least 1 underlying medical disease. Bacterial co-infections were detected in the blood or sputum specimens from 34 patients. Of the 63 patients who were hospitalized in the intensive care unit (ICU), the median time from symptom onset to hospital admission was 2 days (IQR, 0-22 days), and the median time from hospitalization to ICU admission was 1 day (IQR, 0-17 days). Neuraminidase inhibitors were administered to 100 patients (87.0%), 36% of whom began treatment within 2 days. In conclusion, fatal cases from the 2009 influenza A (H1N1) infection in Korea are mainly aged individuals with underlying disease, and associated with pneumonia, bacterial co-infections, and multi-organ failure.
doi:10.3346/jkms.2011.26.1.22
PMCID: PMC3012845  PMID: 21218025
Influenza A Virus, H1N1 Subtype; Mortality; Complications; Korea
20.  Impact of Seasonal and Pandemic Influenza on Emergency Department Visits, 2003–2010, Ontario, Canada 
Academic Emergency Medicine  2013;20(4):388-397.
Objectives
Weekly influenza-like illness (ILI) consultation rates are an integral part of influenza surveillance. However, in most health care settings, only a small proportion of true influenza cases are clinically diagnosed as influenza or ILI. The primary objective of this study was to estimate the number and rate of visits to the emergency department (ED) that are attributable to seasonal and pandemic influenza and to describe the effect of influenza on the ED by age, diagnostic categories, and visit disposition. A secondary objective was to assess the weekly “real-time” time series of ILI ED visits as an indicator of the full burden due to influenza.
Methods
The authors performed an ecologic analysis of ED records extracted from the National Ambulatory Care Reporting System (NARCS) database for the province of Ontario, Canada, from September 2003 to March 2010 and stratified by diagnostic characteristics (International Classification of Diseases, 10th Revision [ICD-10]), age, and visit disposition. A regression model was used to estimate the seasonal baseline. The weekly number of influenza-attributable ED visits was calculated as the difference between the weekly number of visits predicted by the statistical model and the estimated baseline.
Results
The estimated rate of ED visits attributable to influenza was elevated during the H1N1/2009 pandemic period at 1,000 per 100,000 (95% confidence interval [CI] = 920 to 1,100) population compared to an average annual rate of 500 per 100,000 (95% CI = 450 to 550) for seasonal influenza. ILI or influenza was clinically diagnosed in one of 2.6 (38%) and one of 14 (7%) of these visits, respectively. While the ILI or clinical influenza diagnosis was the diagnosis most specific to influenza, only 87% and 58% of the clinically diagnosed ILI or influenza visits for pandemic and seasonal influenza, respectively, were likely directly due to an influenza infection. Rates for ILI ED visits were highest for younger age groups, while the likelihood of admission to hospital was highest in older persons. During periods of seasonal influenza activity, there was a significant increase in the number of persons who registered with nonrespiratory complaints, but left without being seen. This effect was more pronounced during the 2009 pandemic. The ratio of influenza-attributed respiratory visits to influenza-attributed ILI visits varied from 2.4:1 for the fall H1N1/2009 wave to 9:1 for the 2003/04 influenza A(H3N2) season and 28:1 for the 2007/08 H1N1 season.
Conclusions
Influenza appears to have had a much larger effect on ED visits than was captured by clinical diagnoses of influenza or ILI. Throughout the study period, ILI ED visits were strongly associated with excess respiratory complaints. However, the relationship between ILI ED visits and the estimated effect of influenza on ED visits was not consistent enough from year to year to predict the effect of influenza on the ED or downstream in-hospital resource requirements.
doi:10.1111/acem.12111
PMCID: PMC3748786  PMID: 23701347
21.  Economic Model for Emergency Use Authorization of Intravenous Peramivir 
Objectives
To develop 3 computer simulation models to determine the potential economic effect of using intravenous (IV) antiviral agents to treat hospitalized patients with influenza-like illness, as well as different testing and treatment strategies.
Study Design
Stochastic decision analytic computer simulation model.
Methods
During the 2009 influenza A(H1N1) pandemic, the Food and Drug Administration granted emergency use authorization of IV neuraminidase inhibitors for hospitalized patients with influenza, creating a need for rapid decision analyses to help guide use. We compared the economic value from the societal and third-party payer perspectives of the following 4 strategies for a patient hospitalized with influenza-like illness and unable to take oral antiviral agents: Strategy 1: Administration of IV antiviral agents without polymerase chain reaction influenza testing. Strategy 2: Initiation of IV antiviral treatment, followed by polymerase chain reaction testing to determine whether the treatment should be continued. Strategy 3: Performance of polymerase chain reaction testing, followed by initiation of IV antiviral treatment if the test results are positive. Strategy 4: Administration of no IV antiviral agents. Sensitivity analyses varied the probability of having influenza (baseline, 10%; range, 10%–30%), IV antiviral efficacy (baseline, oral oseltamivir phosphate; range, 25%–75%), IV antiviral daily cost (range, $20–$1000), IV antiviral reduction of illness duration (baseline, 1 day; range, 1–2 days), and ventilated vs nonventilated status of the patient.
Results
When the cost of IV antiviral agents was no more than $500 per day, the incremental cost-effectiveness ratio for most of the IV antiviral treatment strategies was less than $10,000 per quality-adjusted life-year compared with no treatment. When the cost was no more than $100 per day, all 3 IV antiviral strategies were even more cost-effective. The order of cost-effectiveness from most to least was strategies 3, 1, and 2. The findings were robust to changing risk of influenza, influenza mortality, IV antiviral efficacy, IV antiviral daily cost, IV antiviral reduction of illness duration, and ventilated vs nonventilated status of the patient for both societal and third-party payer perspectives.
Conclusion
Our study supports the use of IV antiviral treatment for hospitalized patients with influenza-like illness.
PMCID: PMC3763185  PMID: 21485418
22.  Trends in antiviral therapy of adults hospitalized with influenza in Canada since the end of the 2009 pandemic 
Background
Multiple observational studies have associated antiviral treatment of patients hospitalized with influenza with improved outcome, including reduced mortality. During the 2009–2010 H1N1 pandemic increased use of antiviral treatment of hospital patients was reported. We have carried out prospective surveillance for influenza in patients in a large network of Canadian hospitals since 2006. We wished to assess trends in antiviral use in the two seasons (2010–2011 and 2011–2012) since the end of the pandemic.
Findings
Adults (>16 years) testing positive for influenza at the time of or during admission to participating Canadian hospitals were prospectively reviewed. In 2009–2010 there were 1132 confirmed cases, 1107 in 2010–2011 and 631 in 2011–2012. Information on antiviral therapy was available in >95% in each year. Rising to 89.6% in 2009, the proportion of adult patients treated with antiviral therapy fell to 79.9% and 65.7% in the two subsequent seasons (p < 0.001). Oseltamivir was the antiviral agent used in >98% of cases in each year. The median time from onset of symptoms to initiation of antiviral therapy was three days. The treatment proportion fell across all age groups, co-morbid conditions and disease severity.
Conclusion
Despite evidence for benefit of antiviral therapy, and clinical practice guidelines recommending treatment of this population, antiviral therapy of Canadian adults hospitalized with influenza has progressively fallen in the two seasons since the end of the 2009–2010 influenza pandemic.
doi:10.1186/2047-2994-3-2
PMCID: PMC3895698  PMID: 24405855
23.  Monitoring the Impact of Influenza by Age: Emergency Department Fever and Respiratory Complaint Surveillance in New York City 
PLoS Medicine  2007;4(8):e247.
Background
The importance of understanding age when estimating the impact of influenza on hospitalizations and deaths has been well described, yet existing surveillance systems have not made adequate use of age-specific data. Monitoring influenza-related morbidity using electronic health data may provide timely and detailed insight into the age-specific course, impact and epidemiology of seasonal drift and reassortment epidemic viruses. The purpose of this study was to evaluate the use of emergency department (ED) chief complaint data for measuring influenza-attributable morbidity by age and by predominant circulating virus.
Methods and Findings
We analyzed electronically reported ED fever and respiratory chief complaint and viral surveillance data in New York City (NYC) during the 2001–2002 through 2005–2006 influenza seasons, and inferred dominant circulating viruses from national surveillance reports. We estimated influenza-attributable impact as observed visits in excess of a model-predicted baseline during influenza periods, and epidemic timing by threshold and cross correlation. We found excess fever and respiratory ED visits occurred predominantly among school-aged children (8.5 excess ED visits per 1,000 children aged 5–17 y) with little or no impact on adults during the early-2002 B/Victoria-lineage epidemic; increased fever and respiratory ED visits among children younger than 5 y during respiratory syncytial virus-predominant periods preceding epidemic influenza; and excess ED visits across all ages during the 2003–2004 (9.2 excess visits per 1,000 population) and 2004–2005 (5.2 excess visits per 1,000 population) A/H3N2 Fujian-lineage epidemics, with the relative impact shifted within and between seasons from younger to older ages. During each influenza epidemic period in the study, ED visits were increased among school-aged children, and each epidemic peaked among school-aged children before other impacted age groups.
Conclusions
Influenza-related morbidity in NYC was highly age- and strain-specific. The impact of reemerging B/Victoria-lineage influenza was focused primarily on school-aged children born since the virus was last widespread in the US, while epidemic A/Fujian-lineage influenza affected all age groups, consistent with a novel antigenic variant. The correspondence between predominant circulating viruses and excess ED visits, hospitalizations, and deaths shows that excess fever and respiratory ED visits provide a reliable surrogate measure of incident influenza-attributable morbidity. The highly age-specific impact of influenza by subtype and strain suggests that greater age detail be incorporated into ongoing surveillance. Influenza morbidity surveillance using electronic data currently available in many jurisdictions can provide timely and representative information about the age-specific epidemiology of circulating influenza viruses.
Don Olson and colleagues report that influenza-related morbidity in NYC from 2001 to 2006 was highly age- and strain-specific and conclude that surveillance using electronic data can provide timely and representative information about the epidemiology of circulating influenza viruses.
Editors' Summary
Background.
Seasonal outbreaks (epidemics) of influenza (a viral infection of the nose, throat, and airways) send millions of people to their beds every winter. Most recover quickly, but flu epidemics often disrupt daily life and can cause many deaths. Seasonal epidemics occur because influenza viruses continually make small changes to the viral proteins (antigens) that the human immune system recognizes. Consequently, an immune response that combats influenza one year may provide partial or no protection the following year. Occasionally, an influenza virus with large antigenic changes emerges that triggers an influenza pandemic, or global epidemic. To help prepare for both seasonal epidemics and pandemics, public-health officials monitor influenza-related illness and death, investigate unusual outbreaks of respiratory diseases, and characterize circulating strains of the influenza virus. While traditional influenza-related illness surveillance systems rely on relatively slow voluntary clinician reporting of cases with influenza-like illness symptoms, some jurisdictions have also started to use “syndromic” surveillance systems. These use electronic health-related data rather than clinical impression to track illness in the community. For example, increased visits to emergency departments for fever or respiratory (breathing) problems can provide an early warning of an influenza outbreak.
Why Was This Study Done?
Rapid illness surveillance systems have been shown to detect flu outbreaks earlier than is possible through monitoring deaths from pneumonia or influenza. Increases in visits to emergency departments by children for fever or respiratory problems can provide an even earlier indicator. Researchers have not previously examined in detail how fever and respiratory problems by age group correlate with the predominant circulating respiratory viruses. Knowing details like this would help public-health officials detect and respond to influenza epidemics and pandemics. In this study, the researchers have used data collected between 2001 and 2006 in New York City emergency departments to investigate these aspects of syndromic surveillance for influenza.
What Did the Researchers Do and Find?
The researchers analyzed emergency department visits categorized broadly into a fever and respiratory syndrome (which provides an estimate of the total visits attributable to influenza) or more narrowly into an influenza-like illness syndrome (which specifically indicates fever with cough and/or sore throat) with laboratory-confirmed influenza surveillance data. They found that emergency department visits were highest during peak influenza periods, and that the affect on different age groups varied depending on the predominant circulating viruses. In early 2002, an epidemic reemergence of B/Victoria-lineage influenza viruses caused increased visits among school-aged children, while adult visits did not increase. By contrast, during the 2003–2004 season, when the predominant virus was an A/H3N2 Fujian-lineage influenza virus, excess visits occurred in all age groups, though the relative increase was greatest and earliest among school-aged children. During periods of documented respiratory syncytial virus (RSV) circulation, increases in fever and respiratory emergency department visits occurred in children under five years of age regardless of influenza circulation. Finally, the researchers found that excess visits to emergency departments for fever and respiratory symptoms preceded deaths from pneumonia or influenza by about two weeks.
What Do These Findings Mean?
These findings indicate that excess emergency department visits for fever and respiratory symptoms can provide a reliable and timely surrogate measure of illness due to influenza. They also provide new insights into how different influenza viruses affect people of different ages and how the timing and progression of each influenza season differs. These results, based on data collected over only five years in one city, might not be generalizable to other settings or years, warn the researchers. However, the present results strongly suggest that the routine monitoring of influenza might be improved by using electronic health-related data, such as emergency department visit data, and by examining it specifically by age group. Furthermore, by showing that school-aged children can be the first people to be affected by seasonal influenza, these results highlight the important role this age group plays in community-wide transmission of influenza, an observation that could influence the implementation of public-health strategies such as vaccination that aim to protect communities during influenza epidemics and pandemics.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040247.
• US Centers for Disease Control and Prevention provides information on influenza for patients and health professionals and on influenza surveillance in the US (in English, Spanish, and several other languages)
• World Health Organization has a fact sheet on influenza and on global surveillance for influenza (in English, Spanish, French, Russian, Arabic, and Chinese)
• The MedlinePlus encyclopedia contains a page on flu (in English and Spanish)
• US National Institute of Allergy and Infectious Diseases has a feature called “focus on flu”
• A detailed report from the US Centers for Disease Control and Prevention titled “Framework for Evaluating Public Health Surveillance Systems for Early Detection of Outbreaks” includes a simple description of syndromic surveillance
• The International Society for Disease Surveillance has a collaborative syndromic surveillance public wiki
• The Anthropology of the Contemporary Research Collaboratory includes working papers and discussions by cultural anthropologists studying modern vital systems security and syndromic surveillance
doi:10.1371/journal.pmed.0040247
PMCID: PMC1939858  PMID: 17683196
24.  The impact of influenza A(H1N1)pdm09 compared with seasonal influenza on intensive care admissions in New South Wales, Australia, 2007 to 2010: a time series analysis 
BMC Public Health  2012;12:869.
Background
In Australia, the 2009 epidemic of influenza A(H1N1)pdm09 resulted in increased admissions to intensive care. The annual contribution of influenza to use of intensive care is difficult to estimate, as many people with influenza present without a classic influenza syndrome and laboratory testing may not be performed. We used a population-based approach to estimate and compare the impact of recent epidemics of seasonal and pandemic influenza.
Methods
For 2007 to 2010, time series describing health outcomes in various population groups were prepared from a database of all intensive care unit (ICU) admissions in the state of New South Wales, Australia. The Serfling approach, a time series method, was used to estimate seasonal patterns in health outcomes in the absence of influenza epidemics. The contribution of influenza was estimated by subtracting expected seasonal use from observed use during each epidemic period.
Results
The estimated excess rate of influenza-associated respiratory ICU admissions per 100,000 inhabitants was more than three times higher in 2007 (2.6/100,000, 95% CI 2.0 to 3.1) than the pandemic year, 2009 (0.76/100,000, 95% CI 0.04 to 1.48). In 2009, the highest excess respiratory ICU admission rate was in 17 to 64 year olds (2.9/100,000, 95% CI 2.2 to 3.6), while in 2007, the highest excess rate was in those aged 65 years or older (9.5/100,000, 95% CI 6.2 to 12.8). In 2009, the excess rate was 17/100,000 (95% CI 14 to 20) in Aboriginal people and 14/100,000 (95% CI 13 to 16) in pregnant women.
Conclusion
While influenza was diagnosed more frequently and peak use of intensive care was higher during the epidemic of pandemic influenza in 2009, overall excess admissions to intensive care for respiratory illness was much greater during the influenza season in 2007. Thus, the impact of seasonal influenza on intensive care use may have previously been under-recognised. In 2009, high ICU use among young to middle aged adults was offset by relatively low use among older adults, and Aboriginal people and pregnant women were substantially over-represented in ICUs. Greater emphasis on prevention of serious illness in Aboriginal people and pregnant women should be a priority in pandemic planning.
doi:10.1186/1471-2458-12-869
PMCID: PMC3539885  PMID: 23061747
Intensive care; Influenza; Respiratory illness; Hospitalisations; H1N1; Australia; Pandemic; Demand; Indigenous; Pregnancy
25.  Epidemiology of Human Infection with the Novel Virus Influenza A (H1H1) in the Hospital das Clínicas, São Paulo, Brazil – June–September 2009 
Clinics (Sao Paulo, Brazil)  2009;64(10):1025-1030.
The pandemic novel influenza A (H1N1) infection was considered widespread in Brazil on July 16, 2009. Since then, 46,810 cases of acute respiratory syndrome have been reported in Brazil, most of them concentrated in São Paulo. Through September 16, we have confirmed 9,249 cases of novel influenza A H1N1in Brazil, including 699 deaths. The mortality rate observed in Brazil is 0.47/100,000 inhabitants and varies according to region. In this period, São Paulo registered 3733 cases (40.3% of the total) of novel influenza A (H1N1) infection and 327 deaths, reflecting a mortality rate of 0.79/100,000 inhabitants.
The Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HC) is a reference center for H1N1 cases in São Paulo. During the winter of 2009, 472 patients in this hospital were diagnosed with H1N1 infection; of these, 210 were admitted, and 16 died. To control this pandemic and to provide adequate care for these patients, the Hospital das Clínicas implemented “bundles” including prevention strategies, an epidemiologic surveillance service, availability of fast diagnosis, antiviral treatment and training of staff.
The purpose of this manuscript is to describe the epidemiologic features of novel human influenza A (H1N1) infection in the Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo during the winter period of the 2009 pandemic.
doi:10.1590/S1807-59322009001000014
PMCID: PMC2763062  PMID: 19841711
Epidemiology; H1N1 infection; Hospital das Clínicas; Pandemic

Results 1-25 (1483150)