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1.  Reducing the Impact of the Next Influenza Pandemic Using Household-Based Public Health Interventions 
PLoS Medicine  2006;3(9):e361.
The outbreak of highly pathogenic H5N1 influenza in domestic poultry and wild birds has caused global concern over the possible evolution of a novel human strain [1]. If such a strain emerges, and is not controlled at source [2,3], a pandemic is likely to result. Health policy in most countries will then be focused on reducing morbidity and mortality.
Methods and Findings
We estimate the expected reduction in primary attack rates for different household-based interventions using a mathematical model of influenza transmission within and between households. We show that, for lower transmissibility strains [2,4], the combination of household-based quarantine, isolation of cases outside the household, and targeted prophylactic use of anti-virals will be highly effective and likely feasible across a range of plausible transmission scenarios. For example, for a basic reproductive number (the average number of people infected by a typically infectious individual in an otherwise susceptible population) of 1.8, assuming only 50% compliance, this combination could reduce the infection (symptomatic) attack rate from 74% (49%) to 40% (27%), requiring peak quarantine and isolation levels of 6.2% and 0.8% of the population, respectively, and an overall anti-viral stockpile of 3.9 doses per member of the population. Although contact tracing may be additionally effective, the resources required make it impractical in most scenarios.
National influenza pandemic preparedness plans currently focus on reducing the impact associated with a constant attack rate, rather than on reducing transmission. Our findings suggest that the additional benefits and resource requirements of household-based interventions in reducing average levels of transmission should also be considered, even when expected levels of compliance are only moderate.
Voluntary household-based quarantine and external isolation are likely to be effective in limiting the morbidity and mortality of an influenza pandemic, even if such a pandemic cannot be entirely prevented, and even if compliance with these interventions is moderate.
Editors' Summary
Naturally occurring variation in the influenza virus can lead both to localized annual epidemics and to less frequent global pandemics of catastrophic proportions. The most destructive of the three influenza pandemics of the 20th century, the so-called Spanish flu of 1918–1919, is estimated to have caused 20 million deaths. As evidenced by ongoing tracking efforts and news media coverage of H5N1 avian influenza, contemporary approaches to monitoring and communications can be expected to alert health officials and the general public of the emergence of new, potentially pandemic strains before they spread globally.
Why Was This Study Done?
In order to act most effectively on advance notice of an approaching influenza pandemic, public health workers need to know which available interventions are likely to be most effective. This study was done to estimate the effectiveness of specific preventive measures that communities might implement to reduce the impact of pandemic flu. In particular, the study evaluates methods to reduce person-to-person transmission of influenza, in the likely scenario that complete control cannot be achieved by mass vaccination and anti-viral treatment alone.
What Did the Researchers Do and Find?
The researchers developed a mathematical model—essentially a computer simulation—to simulate the course of pandemic influenza in a hypothetical population at risk for infection at home, through external peer networks such as schools and workplaces, and through general community transmission. Parameters such as the distribution of household sizes, the rate at which individuals develop symptoms from nonpandemic viruses, and the risk of infection within households were derived from demographic and epidemiologic data from Hong Kong, as well as empirical studies of influenza transmission. A model based on these parameters was then used to calculate the effects of interventions including voluntary household quarantine, voluntary individual isolation in a facility outside the home, and contact tracing (that is, asking infectious individuals to identify people whom they may have infected and then warning those people) on the spread of pandemic influenza through the population. The model also took into account the anti-viral treatment of exposed, asymptomatic household members and of individuals in isolation, and assumed that all intervention strategies were put into place before the arrival of individuals infected with the pandemic virus.
  Using this model, the authors predicted that even if only half of the population were to comply with public health interventions, the proportion infected during the first year of an influenza pandemic could be substantially reduced by a combination of household-based quarantine, isolation of actively infected individuals in a location outside the household, and targeted prophylactic treatment of exposed individuals with anti-viral drugs. Based on an influenza-associated mortality rate of 0.5% (as has been estimated for New York City in the 1918–1919 pandemic), the magnitude of the predicted benefit of these interventions is a reduction from 49% to 27% in the proportion of the population who become ill in the first year of the pandemic, which would correspond to 16,000 fewer deaths in a city the size of Hong Kong (6.8 million people). In the model, anti-viral treatment appeared to be about as effective as isolation when each was used in combination with household quarantine, but would require stockpiling 3.9 doses of anti-viral for each member of the population. Contact tracing was predicted to provide a modest additional benefit over quarantine and isolation, but also to increase considerably the proportion of the population in quarantine.
What Do These Findings Mean?
This study predicts that voluntary household-based quarantine and external isolation can be effective in limiting the morbidity and mortality of an influenza pandemic, even if such a pandemic cannot be entirely prevented, and even if compliance with these interventions is far from uniform. These simulations can therefore inform preparedness plans in the absence of data from actual intervention trials, which would be impossible outside (and impractical within) the context of an actual pandemic. Like all mathematical models, however, the one presented in this study relies on a number of assumptions regarding the characteristics and circumstances of the situation that it is intended to represent. For example, the authors found that the efficacy of policies to reduce the rate of infection vary according to the ease with which a given virus spreads from person to person. Because this parameter (known as the basic reproductive ratio, R0) cannot be reliably predicted for a new viral strain based on past epidemics, the authors note that in an actual influenza pandemic rapid determinations of R0 in areas already involved would be necessary to finalize public health responses in threatened areas. Further, the implementation of the interventions that appear beneficial in this model would require devoting attention and resources to practical considerations, such as how to staff isolation centers and provide food and water to those in household quarantine. However accurate the scientific data and predictive models may be, their effectiveness can only be realized through well-coordinated local, as well as international, efforts.
Additional Information.
Please access these Web sites via the online version of this summary at
• World Health Organization influenza pandemic preparedness page
• US Department of Health and Human Services avian and pandemic flu information site
• Pandemic influenza page from the Public Health Agency of Canada
• Emergency planning page on pandemic flu from the England Department of Health
• Wikipedia entry on pandemic influenza with links to individual country resources (note: Wikipedia is a free Internet encyclopedia that anyone can edit)
PMCID: PMC1526768  PMID: 16881729
2.  Was Mandatory Quarantine Necessary in China for Controlling the 2009 H1N1 Pandemic? 
The Chinese government enforced mandatory quarantine for 60 days (from 10 May to 8 July 2009) as a preventative strategy to control the spread of the 2009 H1N1 pandemic. Such a prevention strategy was stricter than other non-pharmaceutical interventions that were carried out in many other countries. We evaluated the effectiveness of the mandatory quarantine and provide suggestions for interventions against possible future influenza pandemics. We selected one city, Beijing, as the analysis target. We reviewed the epidemiologic dynamics of the 2009 H1N1 pandemic and the implementation of quarantine measures in Beijing. The infectious population was simulated under two scenarios (quarantined and not quarantined) using a deterministic Susceptible-Exposed-Infectious-Recovered (SEIR) model. The basic reproduction number R0 was adjusted to match the epidemic wave in Beijing. We found that mandatory quarantine served to postpone the spread of the 2009 H1N1 pandemic in Beijing by one and a half months. If mandatory quarantine was not enforced in Beijing, the infectious population could have reached 1,553 by 21 October, i.e., 5.6 times higher than the observed number. When the cost of quarantine is taken into account, mandatory quarantine was not an economically effective intervention approach against the 2009 H1N1 pandemic. We suggest adopting mitigation methods for an influenza pandemic with low mortality and morbidity.
PMCID: PMC3823329  PMID: 24084677
China; 2009 H1N1 pandemic; prevention policy; quarantine
3.  Assessment of Border Control Measures and Community Containment Measures Used in Japan during the Early Stages of Pandemic (H1N1) 2009 
PLoS ONE  2012;7(2):e31289.
In the early stages of Pandemic (H1N1) 2009, border control measures were taken by quarantine stations to block the entry of infected individuals into Japan and community containment measures were implemented to prevent the spreading. The objectives of this study were to describe these measures and the characteristics of infected individuals, and to assess the measures' effectiveness.
Methodology/Principal Findings
Border control and community containment measures implemented from April to June (Period I: April 28–May 21, Period II: May 22–June 18) 2009 were described. Number of individuals identified and disease characteristics were analyzed. For entry screening, a health declaration form and an infrared thermoscanner were used to detect symptomatic passengers. Passengers indicated for the rapid influenza test underwent the test followed by RT-PCR. Patients positive for H1N1 were isolated, and close contacts were quarantined. Entry cards were handed out to all asymptomatic passengers informing them about how to contact a health center in case they developed symptoms. Nine individuals were identified by entry screening and 1 during quarantine to have Pandemic (H1N1) 2009. Health monitoring by health centers was performed in period I for passengers arriving from affected countries and in period II for those who had come into contact with the individuals identified by entry screening. Health monitoring identified 3 infected individuals among 129,546 in Period I and 5 among 746 in Period II. Enhanced surveillance, which included mandatory reporting of details of the infected individuals, identified 812 individuals, 141 (18%) of whom had a history of international travel. Twenty-four of these 141 passengers picked up by enhanced surveillance had been developing symptoms on entry and were missed at screening.
Symptomatic passengers were detected by the various entry screening measures put in place. Enhanced surveillance provided data for the improvement of public health measures in future pandemics.
PMCID: PMC3280294  PMID: 22355354
4.  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.
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.
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
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
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, 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)
PMCID: PMC2872648  PMID: 20502525
5.  Analysis of CDC social control measures using an agent-based simulation of an influenza epidemic in a city 
BMC Infectious Diseases  2011;11:199.
The transmission of infectious disease amongst the human population is a complex process which requires advanced, often individual-based, models to capture the space-time details observed in reality.
An Individual Space-Time Activity-based Model (ISTAM) was applied to simulate the effectiveness of non-pharmaceutical control measures including: (1) refraining from social activities, (2) school closure and (3) household quarantine, for a hypothetical influenza outbreak in an urban area.
Amongst the set of control measures tested, refraining from social activities with various compliance levels was relatively ineffective. Household quarantine was very effective, especially for the peak number of cases and total number of cases, with large differences between compliance levels. Household quarantine resulted in a decrease in the peak number of cases from more than 300 to around 158 for a 100% compliance level, a decrease of about 48.7%. The delay in the outbreak peak was about 3 to 17 days. The total number of cases decreased to a range of 3635-5403, that is, 63.7%-94.7% of the baseline value.
When coupling control measures, household quarantine together with school closure was the most effective strategy. The resulting space-time distribution of infection in different classes of activity bundles (AB) suggests that the epidemic outbreak is strengthened amongst children and then spread to adults. By sensitivity analysis, this study demonstrated that earlier implementation of control measures leads to greater efficacy. Also, for infectious diseases with larger basic reproduction number, the effectiveness of non-pharmaceutical measures was shown to be limited.
Simulated results showed that household quarantine was the most effective control measure, while school closure and household quarantine implemented together achieved the greatest benefit. Agent-based models should be applied in the future to evaluate the efficacy of control measures for a range of disease outbreaks in a range of settings given sufficient information about the given case and knowledge about the transmission processes at a fine scale.
PMCID: PMC3151229  PMID: 21767379
6.  Risk assessment and cost-effectiveness of animal health certification methods for livestock export in Somalia 
Preventive Veterinary Medicine  2014;113(4):469-483.
Livestock export is vital to the Somali economy. To protect Somali livestock exports from costly import bans used to control the international spread of disease, better certification of livestock health status is required. We performed quantitative risk assessment and cost-effectiveness analysis on different health certification protocols for Somali livestock exports for six transboundary diseases.
Examining stock at regional markets alone without port inspection and quarantine was inexpensive but was ineffective for all but contagious bovine pleuropneumonia, contagious caprine pleuropneumonia and peste des petits ruminants. While extended pre-export quarantine improves detection of infections that cause clinical disease, if biosecurity is suboptimal quarantine provides an opportunity for transmission and increased risk. Clinical examination, laboratory screening and vaccination of animals for key diseases before entry to the quarantine station reduced the risk of an exported animal being infected. If vaccination could be reliably performed weeks before arrival at quarantine its effect would be greatly enhanced.
The optimal certification method depends on the disease. Laboratory diagnostic testing was particularly important for detecting infections with limited clinical signs in male animals (only males are exported); for Rift Valley fever (RVF) the probability of detection was 99% or 0% with and without testing.
Based on our findings animal inspection and certification at regional markets combined with quarantine inspection and certification would reduce the risk of exporting infected animals and enhance disease control at the regional level. This is especially so for key priority diseases, that is RVF, foot-and-mouth disease and Brucellosis. Increased data collection and testing should be applied at point of production and export.
PMCID: PMC3989042  PMID: 24462194
Risk assessment; Cost-effectiveness; Somalia; RVF; FMD; Brucellosis; PPR; CCPP; CBPP
7.  Modeling the Worldwide Spread of Pandemic Influenza: Baseline Case and Containment Interventions 
PLoS Medicine  2007;4(1):e13.
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.
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
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
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
PMCID: PMC1779816  PMID: 17253899
8.  Human Monoclonal Antibody Combination against SARS Coronavirus: Synergy and Coverage of Escape Mutants 
PLoS Medicine  2006;3(7):e237.
Experimental animal data show that protection against severe acute respiratory syndrome coronavirus (SARS-CoV) infection with human monoclonal antibodies (mAbs) is feasible. For an effective immune prophylaxis in humans, broad coverage of different strains of SARS-CoV and control of potential neutralization escape variants will be required. Combinations of virus-neutralizing, noncompeting mAbs may have these properties.
Methods and Findings
Human mAb CR3014 has been shown to completely prevent lung pathology and abolish pharyngeal shedding of SARS-CoV in infected ferrets. We generated in vitro SARS-CoV variants escaping neutralization by CR3014, which all had a single P462L mutation in the glycoprotein spike (S) of the escape virus. In vitro experiments confirmed that binding of CR3014 to a recombinant S fragment (amino acid residues 318–510) harboring this mutation was abolished. We therefore screened an antibody-phage library derived from blood of a convalescent SARS patient for antibodies complementary to CR3014. A novel mAb, CR3022, was identified that neutralized CR3014 escape viruses, did not compete with CR3014 for binding to recombinant S1 fragments, and bound to S1 fragments derived from the civet cat SARS-CoV-like strain SZ3. No escape variants could be generated with CR3022. The mixture of both mAbs showed neutralization of SARS-CoV in a synergistic fashion by recognizing different epitopes on the receptor-binding domain. Dose reduction indices of 4.5 and 20.5 were observed for CR3014 and CR3022, respectively, at 100% neutralization. Because enhancement of SARS-CoV infection by subneutralizing antibody concentrations is of concern, we show here that anti-SARS-CoV antibodies do not convert the abortive infection of primary human macrophages by SARS-CoV into a productive one.
The combination of two noncompeting human mAbs CR3014 and CR3022 potentially controls immune escape and extends the breadth of protection. At the same time, synergy between CR3014 and CR3022 may allow for a lower total antibody dose to be administered for passive immune prophylaxis of SARS-CoV infection.
Editors' Summary
Late in 2002, severe acute respiratory syndrome (SARS) emerged in the Guangdong province of China. In February 2003, an infected doctor from the province carried this new viral threat to human health to Hong Kong. Here, people staying in the same hotel caught the disease and took it to other countries. SARS was on the move, hitching lifts with international travellers. Because the virus responsible for SARS—SARS-CoV—spread by close person-to-person contact and killed 10% of the people it infected, health experts feared a world-wide epidemic. This was avoided by the World Health Organization issuing a global alert and warning against unnecessary travel to affected areas and by public-health officials isolating patients and their close contacts. By July 2003, the first SARS epidemic was over. 8,098 people had been infected; 774 people had died. Since then, sporadic cases of SARS have been contained locally.
Why Was This Study Done?
The first epidemic of SARS was caused by an animal virus that became adapted to spread between people. There is no reason this process won't be repeated. If it is, stringent quarantine measures could again prevent a global epidemic, but at considerable economic cost. What is needed is a way to prevent SARS developing in healthy people who have been exposed to SARS-CoV and to treat sick people so that they are less infectious and can fight the virus. In this study, researchers have been investigating “passive immunization” as a way to limit SARS epidemics. In passive immunization, short-term protection against illness is achieved by injecting antibodies—proteins that recognize specific molecules (called antigens) on foreign organisms such as bacteria and viruses and prevent those organisms from causing disease. Antibodies for passive immunization can be isolated from blood taken from people who have had SARS, or they can be manufactured as so-called “human monoclonal antibodies” in a laboratory. One of these human monoclonal antibodies—CR3014—had been previously made and shown to prevent lung damage in ferrets infected with SARS-CoV and to stop the infected animals from infecting others. But for effective disease prevention in people, a single monoclonal antibody might not be enough. There are strains of SARS-CoV that CR3014 does not recognize and therefore cannot act against. Also, the virus can alter the antigen recognized by CR3014 when it is grown at a low antibody concentration, producing so-called escape variants; if this happens CR3014 can no longer prevent these escape variants from killing human cells.
What Did the Researchers Do and Find?
The researchers tested how well a combination of two monoclonal antibodies controlled SARS-CoV killing of human cells. First, they showed that CR3014 escape variants all had the same small change in a part of the virus surface that interacts with human cells. CR3014 blocked this interaction in the parent SARS-CoV strain but not in the escape variants. They then made a new monoclonal antibody—CR3022—that prevented both the parent SARS-CoV stain and the CR3014 escape viruses from killing human cells. The two antibodies bound to neighboring parts of the virus surface, and both of them could bind at the same time. CR3022 also bound to surfaces of SARS-CoV strains to which CR3014 does not bind. And when they tried, the researchers could not generate any viral escape variants to which CR3022 was unable to bind. Finally, the effect of the two antibodies together on inhibition of SARS-CoV killing of human cells was more than the sum of their individual effects.
What Do These Findings Mean?
A combination of two (or more) human monoclonal antibodies that recognize different parts of the SARS-CoV surface that interacts with human cells might be a good way to immunize people passively against SARS-CoV. It might minimize the possibility of escape variants arising, broaden the range of virus strains against which protection is provided, and reduce the amount of antibody needed for effective protection. Before the approach is tried in people, it will have to be tested in animals—results from experiments done on human cells in dishes are not always replicated in whole animals or people. If the approach passes further tests, the hope is that passive immunization of people with SARS and their close contacts might reduce disease severity in infected people and reduce viral spread as effectively as dramatic quarantine measures
Additional Information.
Please access these websites via the online version of this summary at
• Medline Plus pages on SARS
• US Centers for Disease Control and Prevention information on SARS
• US National Institute of Allergy and Infectious Diseases factsheet about research on SARS
• Wikipedia page on SARS and monoclonal antibodies (note: Wikipedia is a free online encyclopedia that anyone can edit)
Two human monoclonal antibodies that bind to different parts of the viral glycoprotein spike show synergistic effects in virus neutralization and suppress the emergence of resistant virus in vitro.
PMCID: PMC1483912  PMID: 16796401
9.  Bayesian Contact Tracing for Communicable Respiratory Disease 
The purpose of our work is to develop a system for automatic contact tracing with the goal of identifying individuals who are most likely infected, even if we do not have direct diagnostic information on their health status. Control of the spread of respiratory pathogens (e.g. novel influenza viruses) in the population using vaccination is a challenging problem that requires quick identification of the infectious agent followed by large-scale production and administration of a vaccine. This takes a significant amount of time. A complementary approach to control transmission is contact tracing and quarantining, which are currently applied to sexually transmitted diseases (STDs). For STDs, identifying the contacts that might have led to disease transmission is relatively easy; however, for respiratory pathogens, the contacts that can lead to transmission include a huge number of face-to-face daily social interactions that are impossible to trace manually.
The evolution of novel influenza viruses in humans is a biological phenomenon that can not be stopped. All existing data suggest that vaccination against the morbidity and mortality of the novel influenza viruses is our best line of defence. Unfortunately, vaccination requires that the infectious agent to be quickly identified and a safe vaccine in large quantities is produced and administered. As was witnessed with the 2009 H1N1 influenza pandemic, these steps took a frustratingly long period during which the novel influenza virus continued its unstoppable and rapid global spreading.
In addition to the different vaccination strategies (e.g. random mass vaccination, age structured vaccination), isolation and quarantining of infected individuals is another effective method used by the public health agencies to control the spreading of infectious diseases. Isolation is effective against any infectious disease, however it can be very hard to detect infectious individuals in the population when: Symptoms are ambiguous or easily misdiagnosed (e.g. 2009 H1N1 influenza outbreak shared many symptoms with many other influenza like illnesses)When the symptoms emerge after the individual become infectious.
We developed a dynamic Bayesian network model to process sensor information from users’ cellphones together with (possibly incomplete) diagnosis information to track the spread of disease in a population. Our model tracks real-time proximity contacts and can provide public health agencies with the probability of infection for each individual in the model.
For testing our algorithm, we used a real-world mobile sensor dataset with 120 individuals collected over a period of 9 months, and we simulated an outbreak.
We ran several experiments where different sub-populations were “infected” and “diagnosed.” By using the contact information, our model was able to automatically identify individuals in the population who were likely to be infected even though they were not directly “diagnosed” with an illness.
Automatic contact tracing for respiratory pathogens is a powerful idea, however we have identified several implementation challenges. The first challenge is scalability: we note that a contact tracing system with a hundred thousand individuals requires a Bayesian model with a billion nodes. Bayesian inference on models of this scale is an open problem and an active area of research. The second challenge is privacy protection: although the test data were collected in an academic setting, deploying any system will require appropriate safeguards for user privacy. Nonetheless, our work llustrates the potential for broader use of contact tracing for modeling and controlling disease transmission.
PMCID: PMC3692863
Outbreak Detection; Syndromic Surveillance; Mobile; Contact Tracing; Bayesian Algorithms
10.  Quantifying the impact of community quarantine on SARS transmission in Ontario: estimation of secondary case count difference and number needed to quarantine 
BMC Public Health  2009;9:488.
Community quarantine is controversial, and the decision to use and prepare for it should be informed by specific quantitative evidence of benefit. Case-study reports on 2002-2004 SARS outbreaks have discussed the role of quarantine in the community in transmission. However, this literature has not yielded quantitative estimates of the reduction in secondary cases attributable to quarantine as would be seen in other areas of health policy and cost-effectiveness analysis.
Using data from the 2003 Ontario, Canada, SARS outbreak, two novel expressions for the impact of quarantine are presented. Secondary Case Count Difference (SCCD) reflects reduction in the average number of transmissions arising from a SARS case in quarantine, relative to not in quarantine, at onset of symptoms. SCCD was estimated using Poisson and negative binomial regression models (with identity link function) comparing the number of secondary cases to each index case for quarantine relative to non-quarantined index cases. The inverse of this statistic is proposed as the number needed to quarantine (NNQ) to prevent one additional secondary transmission.
Our estimated SCCD was 0.133 fewer secondary cases per quarantined versus non-quarantined index case; and a NNQ of 7.5 exposed individuals to be placed in community quarantine to prevent one additional case of transmission in the community. This analysis suggests quarantine can be an effective preventive measure, although these estimates lack statistical precision.
Relative to other health policy areas, literature on quarantine tends to lack in quantitative expressions of effectiveness, or agreement on how best to report differences in outcomes attributable to control measure. We hope to further this discussion through presentation of means to calculate and express the impact of population control measures. The study of quarantine effectiveness presents several methodological and statistical challenges. Further research and discussion are needed to understand the costs and benefits of enacting quarantine, and this includes a discussion of how quantitative benefit should be communicated to decision-makers and the public, and evaluated.
PMCID: PMC2808319  PMID: 20034405
11.  Implementation of an Intersectoral Program to Eliminate Human and Canine Rabies: The Bohol Rabies Prevention and Elimination Project 
The province of Bohol, located in the Visayas islands region in the Philippines has a human population of 1.13 million and was the 4th highest region for human rabies deaths in the country, averaging 10 per year, prior to the initiation of the Bohol Rabies Prevention and Elimination Project (BRPEP).
The BRPEP was initiated in 2007 with the goal of building a sustainable program that would prevent human rabies by eliminating rabies at its source, in dogs, by 2010. This goal was in line with the Philippine National Rabies Program whose objective is to eliminate rabies by 2020.
The intersectoral BRPEP was launched in 2007 and integrated the expertise and resources from the sectors of agriculture, public health and safety, education, environment, legal affairs, interior and local government. The program included: increasing local community involvement; implementing dog population control; conducting mass dog vaccination; improving dog bite management; instituting veterinary quarantine; and improving diagnostic capability, surveillance and monitoring. Funding was secured from the national government, provincial, municipal and village units, dog owners, NGOs, the regional office of the WHO, the UBS Optimus Foundation, and the Global Alliance for Rabies Control. The BRPEP was managed by the Bohol Rabies Prevention and Eradication Council (BRPEC) under the jurisdiction of the Governor of Bohol. Parallel organizations were created at the municipal level and village level. Community volunteers facilitated the institution of the program. Dog population surveys were conducted to plan for sufficient resources to vaccinate the required 70% of the dogs living in the province. Two island-wide mass vaccination campaigns were conducted followed by “catch up” vaccination campaigns. Registration of dogs was implemented including a small fee that was rolled back into the program to maintain sustainability. Children were educated by introducing rabies prevention modules into all elementary schools in Bohol. Existing public health legislation at the national, provincial, and municipal level strengthened the enforcement of activities. A Knowledge, Attitude and Practices (KAP) survey was conducted in 2009 to evaluate the educational knowledge of the population. Increased surveillance was instituted to ensure that dogs traveling into and out of the province were vaccinated against rabies. Human and animal cases of rabies were reported to provincial and national authorities.
Key Results
Within the first 18 months of the BRPEP, human rabies deaths had decreased annually from 0.77 to 0.37 to zero per 100,000 population from 2007–2009. Between October 2008 and November 2010 no human and animal cases were detected. Increased surveillance on the island detected one suspected human rabies case in November 2010 and one confirmed case of canine rabies in April 2011. Two mass vaccination campaigns conducted in 2007 and 2008 successfully registered and vaccinated 44% and 70% of the dogs on the island. The additional surveillance activities enabled a mobilization of mop up vaccination activities in the region where the human and canine case was located. Due to the increased effective and continuous surveillance activities, rabies was stopped before it could spread to other areas on the island. The program costs totaled USD 450,000. Registration fees collected to maintain the program amounted to USD 105,740 and were re-allocated back into the community to sustain the program.
Author Summary
The Province of Bohol, Philippines has eliminated dog and human rabies in less than three years by empowering the community and implementing an intersectoral strategy. In 2006, Bohol ranked 4th highest in the Philippines for human rabies, averaging 10 deaths per year. Launched in 2007, the program utilized a social awareness campaign, dog population control, mass dog vaccination campaigns, improved dog bite management and veterinary quarantine, a new diagnostic laboratory, expanded surveillance, and the inclusion of education modules into the school curriculum. Improving community compliance to existing national and provincial rabies laws and engaging volunteers to help conduct the project was a key to success. The program, led by the Governor of Bohol, was administered through a group of departments working together at a provincial and local level, and supervised through the Office of the Provincial Veterinarian. Financial support came through the Governor and several NGOs including the Global Alliance for Rabies Control. The program is self-sustaining, through a small dog registration fee fed back into the program, through the continuing education of children in their classrooms, and through the dedicated efforts of over 15,000 staff and volunteers throughout the island.
PMCID: PMC3516573  PMID: 23236525
12.  Small islands and pandemic influenza: Potential benefits and limitations of travel volume reduction as a border control measure 
Some island nations have explicit components of their influenza pandemic plans for providing travel warnings and restricting incoming travellers. But the potential value of such restrictions has not been quantified.
We developed a probabilistic model and used parameters from a published model (i.e., InfluSim) and travel data from Pacific Island Countries and Territories (PICTs).
The results indicate that of the 17 PICTs with travel data, only six would be likely to escape a major pandemic with a viral strain of relatively low contagiousness (i.e., for R0 = 1.5) even when imposing very tight travel volume reductions of 99% throughout the course of the pandemic. For a more contagious viral strain (R0 = 2.25) only five PICTs would have a probability of over 50% to escape. The total number of travellers during the pandemic must not exceed 115 (for R0 = 3.0) or 380 (for R0 = 1.5) if a PICT aims to keep the probability of pandemic arrival below 50%.
These results suggest that relatively few island nations could successfully rely on intensive travel volume restrictions alone to avoid the arrival of pandemic influenza (or subsequent waves). Therefore most island nations may need to plan for multiple additional interventions (e.g., screening and quarantine) to raise the probability of remaining pandemic free or achieving substantial delay in pandemic arrival.
PMCID: PMC2761921  PMID: 19788751
13.  Modelling strategies for controlling SARS outbreaks. 
Severe acute respiratory syndrome (SARS), a new, highly contagious, viral disease, emerged in China late in 2002 and quickly spread to 32 countries and regions causing in excess of 774 deaths and 8098 infections worldwide. In the absence of a rapid diagnostic test, therapy or vaccine, isolation of individuals diagnosed with SARS and quarantine of individuals feared exposed to SARS virus were used to control the spread of infection. We examine mathematically the impact of isolation and quarantine on the control of SARS during the outbreaks in Toronto, Hong Kong, Singapore and Beijing using a deterministic model that closely mimics the data for cumulative infected cases and SARS-related deaths in the first three regions but not in Beijing until mid-April, when China started to report data more accurately. The results reveal that achieving a reduction in the contact rate between susceptible and diseased individuals by isolating the latter is a critically important strategy that can control SARS outbreaks with or without quarantine. An optimal isolation programme entails timely implementation under stringent hygienic precautions defined by a critical threshold value. Values below this threshold lead to control, but those above are associated with the incidence of new community outbreaks or nosocomial infections, a known cause for the spread of SARS in each region. Allocation of resources to implement optimal isolation is more effective than to implement sub-optimal isolation and quarantine together. A community-wide eradication of SARS is feasible if optimal isolation is combined with a highly effective screening programme at the points of entry.
PMCID: PMC1691853  PMID: 15539347
14.  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.
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.
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
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
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)
PMCID: PMC2680070  PMID: 19440354
15.  Influence of Stress Connected with Moving to a New Farm on Potentially MAP-Infected Mouflons 
ISRN Microbiology  2014;2014:450130.
There is no European legislation concerning paratuberculosis that requires that imported animals be kept in quarantine and commonly they are directly released into areas with other animals. In this study, detection of latent infection of paratuberculosis in healthy mouflons previously diagnosed as paratuberculosis-free, but originating from a real time quantitative PCR- (qPCR-) positive herd, occurred after their transport to a new farm. During a twelve-day quarantine period, all mouflons irregularly shed Mycobacterium avium subsp. paratuberculosis (MAP) in faeces, and in a small number of cases also in milk. After the animals were released from quarantine, MAP was detected for a further two days, after which, testing was negative, except in one case. Therefore, the stress connected with transport, novel environment, dietary change, or limited area with high density of animals might have contributed to the induction of paratuberculosis and the shedding of MAP from the animals, previously diagnosed as MAP-negative. According to these results, the keeping of imported animals in quarantine and their examination for MAP presence not only before the transport but also afterwards should be recommended. The designation of a particular area of a farm as a quarantine enclosure could help to mitigate the impact of stress caused by a confined space with a high density of animals.
PMCID: PMC3960726  PMID: 24729908
16.  Quarantine Plasma: Quo vadis? 
Upon the introduction of mandatory nucleic acid amplification technology (NAT) testing in Germany for HCV, quarantining of fresh frozen plasma (FFP) was reduced in 2002 from 6 to 4 months. In 2004 HIV-1 NAT and in 2005 anti-HBc testing were introduced to further reduce the residual transmission risks for transfusion relevant viruses. After testing more than 40 million donations by HCV NAT it became obvious that NAT testing has a very significant impact on viral blood safety by reducing the residual risk by a factor of 10. Only one documented HCV transmission occurred during more than 10 years of NAT testing in Germany, indicating that the remaining risk is marginal. Similar data were obtained for HIV-1. The question arises whether we could discontinue quarantining of FFP or further reduce the quarantining interval for retesting of the donor. This could facilitate logistics and reduce losses as quarantine FFP can be released earlier after donation and at regular donation intervals. Essential parameters for estimating the remaining infectious risks are the minimal infectious dose and replication kinetics of the viruses involved, the detection limits of the NAT tests applied, and the volume of plasma transfused. In essence it can be assumed that discontinuation of quarantining would only marginally increase the residual risk and that the reduction of the quarantine period to only 4 weeks would add an additional benefit to the viral safety of quarantine FFP.
PMCID: PMC2889627  PMID: 20577600
HBsAg; HBV; HCV; HIV; NAT; Plasma; Quarantine; Transfusion-associated infections; Virus transmission; Quarantine period reduction
17.  Clinical and Epidemiologic Characteristics of 3 Early Cases of Influenza A Pandemic (H1N1) 2009 Virus Infection, People’s Republic of China, 2009 
Emerging Infectious Diseases  2009;15(9):1418-1422.
A national network is essential for controlling this infection.
On May 7, 2009, a national network was organized in the People’s Republic of China for the surveillance, reporting, diagnosis, and treatment of influenza A pandemic (H1N1) 2009 virus infection (pandemic [H1N1] 2009). Persons with suspected cases are required to report to the Chinese Center for Disease Control and Prevention and the Ministry of Health within 24 hours; the patient’s close contacts are then traced and placed in quarantine for 7 days. We report 3 confirmed early cases of pandemic (H1N1) 2009. Two cases were imported from United States; the other was imported from Canada. The patients exhibited fever and signs and other symptoms that were indistinguishable from those of seasonal influenza. Serial virologic monitoring of pharyngeal swabs showed that they were negative for pandemic (H1N1) 2009 virus by real-time reverse transcription–PCR 4–6 days after onset of illness. One close contact whose sample tested positive for pandemic (H1N1) 2009 virus had no symptoms during quarantine. A national network is essential for controlling pandemic (H1N1) 2009.
PMCID: PMC2819857  PMID: 19788809
influenza; influenza A pandemic (H1N1) 2009 virus; viruses; China; research; expedited; podcast
18.  Containing the accidental laboratory escape of potential pandemic influenza viruses 
BMC Medicine  2013;11:252.
The recent work on the modified H5N1 has stirred an intense debate on the risk associated with the accidental release from biosafety laboratory of potential pandemic pathogens. Here, we assess the risk that the accidental escape of a novel transmissible influenza strain would not be contained in the local community.
We develop here a detailed agent-based model that specifically considers laboratory workers and their contacts in microsimulations of the epidemic onset. We consider the following non-pharmaceutical interventions: isolation of the laboratory, laboratory workers’ household quarantine, contact tracing of cases and subsequent household quarantine of identified secondary cases, and school and workplace closure both preventive and reactive.
Model simulations suggest that there is a non-negligible probability (5% to 15%), strongly dependent on reproduction number and probability of developing clinical symptoms, that the escape event is not detected at all. We find that the containment depends on the timely implementation of non-pharmaceutical interventions and contact tracing and it may be effective (>90% probability per event) only for pathogens with moderate transmissibility (reproductive number no larger than R0 = 1.5). Containment depends on population density and structure as well, with a probability of giving rise to a global event that is three to five times lower in rural areas.
Results suggest that controllability of escape events is not guaranteed and, given the rapid increase of biosafety laboratories worldwide, this poses a serious threat to human health. Our findings may be relevant to policy makers when designing adequate preparedness plans and may have important implications for determining the location of new biosafety laboratories worldwide.
PMCID: PMC4220800  PMID: 24283203
BSL Laboratory; Influenza; Agent-based model; Outbreak containment; Contact tracing
19.  Sources, perceived usefulness and understanding of information disseminated to families who entered home quarantine during the H1N1 pandemic in Victoria, Australia: a cross-sectional study 
Voluntary home quarantine of cases and close contacts was the main non-pharmaceutical intervention used to limit transmission of pandemic (H1N1) 2009 influenza (pH1N1) in the initial response to the outbreak of the disease in Australia. The effectiveness of voluntary quarantine logically depends on affected families having a clear understanding of what they are being asked to do. Information may come from many sources, including the media, health officials, family and friends, schools, and health professionals. We report the extent to which families who entered home quarantine received and used information on what they were supposed to do. Specifically, we outline their sources of information; the perceived usefulness of each source; and associations between understanding of recommendations and compliance.
Cross-sectional survey administered via the internet and computer assisted telephone interview to families whose school children were recommended to go into home quarantine because they were diagnosed with H1N1 or were a close contact of a case. The sample included 314 of 1157 potentially eligible households (27% response rate) from 33 schools in metropolitan Melbourne. Adjusting for clustering within schools, we describe self-reported 'understanding of what they were meant to do during the quarantine period'; source of information (e.g. health department) and usefulness of information. Using logistic regression we examine whether compliance with quarantine recommendations was associated with understanding and the type of information source used.
Ninety per cent understood what they were meant to do during the quarantine period with levels of understanding higher in households with cases (98%, 95% CI 93%-99% vs 88%, 95% CI 84%-91%, P = 0.006). Over 87% of parents received information about quarantine from the school, 63% from the health department and 44% from the media. 53% of households were fully compliant and there was increased compliance in households that reported that they understood what they were meant to do (Odds Ratio 2.27, 95% CI 1.35-3.80).
It is critical that public health officials work closely with other government departments and media to provide clear, consistent and simple information about what to do during quarantine as high levels of understanding will maximise compliance in the quarantined population.
PMCID: PMC3025855  PMID: 21199583
20.  Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies 
BMC Medicine  2009;7:76.
Individual strategies in pandemic preparedness plans may not reduce the impact of an influenza pandemic.
We searched modeling publications through PubMed and associated references from 1990 to 30 September 2009. Inclusion criteria were modeling papers quantifying the effectiveness of combination strategies, both pharmaceutical and non-pharmaceutical.
Nineteen modeling papers on combination strategies were selected. Four studies examined combination strategies on a global scale, 14 on single countries, and one on a small community. Stochastic individual-based modeling was used in nine studies, stochastic meta-population modeling in five, and deterministic compartmental modeling in another five. As part of combination strategies, vaccination was explored in eight studies, antiviral prophylaxis and/or treatment in 16, area or household quarantine in eight, case isolation in six, social distancing measures in 10 and air travel restriction in six studies. Two studies suggested a high probability of successful influenza epicenter containment with combination strategies under favorable conditions. During a pandemic, combination strategies delayed spread, reduced overall number of cases, and delayed and reduced peak attack rate more than individual strategies. Combination strategies remained effective at high reproductive numbers compared with single strategy. Global cooperative strategies, including redistribution of antiviral drugs, were effective in reducing the global impact and attack rates of pandemic influenza.
Combination strategies increase the effectiveness of individual strategies. They include pharmaceutical (antiviral agents, antibiotics and vaccines) and non-pharmaceutical interventions (case isolation, quarantine, personal hygiene measures, social distancing and travel restriction). Local epidemiological and modeling studies are needed to validate efficacy and feasibility.
PMCID: PMC2797001  PMID: 20003249
21.  An Epidemiological Network Model for Disease Outbreak Detection 
PLoS Medicine  2007;4(6):e210.
Advanced disease-surveillance systems have been deployed worldwide to provide early detection of infectious disease outbreaks and bioterrorist attacks. New methods that improve the overall detection capabilities of these systems can have a broad practical impact. Furthermore, most current generation surveillance systems are vulnerable to dramatic and unpredictable shifts in the health-care data that they monitor. These shifts can occur during major public events, such as the Olympics, as a result of population surges and public closures. Shifts can also occur during epidemics and pandemics as a result of quarantines, the worried-well flooding emergency departments or, conversely, the public staying away from hospitals for fear of nosocomial infection. Most surveillance systems are not robust to such shifts in health-care utilization, either because they do not adjust baselines and alert-thresholds to new utilization levels, or because the utilization shifts themselves may trigger an alarm. As a result, public-health crises and major public events threaten to undermine health-surveillance systems at the very times they are needed most.
Methods and Findings
To address this challenge, we introduce a class of epidemiological network models that monitor the relationships among different health-care data streams instead of monitoring the data streams themselves. By extracting the extra information present in the relationships between the data streams, these models have the potential to improve the detection capabilities of a system. Furthermore, the models' relational nature has the potential to increase a system's robustness to unpredictable baseline shifts. We implemented these models and evaluated their effectiveness using historical emergency department data from five hospitals in a single metropolitan area, recorded over a period of 4.5 y by the Automated Epidemiological Geotemporal Integrated Surveillance real-time public health–surveillance system, developed by the Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology on behalf of the Massachusetts Department of Public Health. We performed experiments with semi-synthetic outbreaks of different magnitudes and simulated baseline shifts of different types and magnitudes. The results show that the network models provide better detection of localized outbreaks, and greater robustness to unpredictable shifts than a reference time-series modeling approach.
The integrated network models of epidemiological data streams and their interrelationships have the potential to improve current surveillance efforts, providing better localized outbreak detection under normal circumstances, as well as more robust performance in the face of shifts in health-care utilization during epidemics and major public events.
Most surveillance systems are not robust to shifts in health care utilization. Ben Reis and colleagues developed network models that detected localized outbreaks better and were more robust to unpredictable shifts.
Editors' Summary
The main task of public-health officials is to promote health in communities around the world. To do this, they need to monitor human health continually, so that any outbreaks (epidemics) of infectious diseases (particularly global epidemics or pandemics) or any bioterrorist attacks can be detected and dealt with quickly. In recent years, advanced disease-surveillance systems have been introduced that analyze data on hospital visits, purchases of drugs, and the use of laboratory tests to look for tell-tale signs of disease outbreaks. These surveillance systems work by comparing current data on the use of health-care resources with historical data or by identifying sudden increases in the use of these resources. So, for example, more doctors asking for tests for salmonella than in the past might presage an outbreak of food poisoning, and a sudden rise in people buying over-the-counter flu remedies might indicate the start of an influenza pandemic.
Why Was This Study Done?
Existing disease-surveillance systems don't always detect disease outbreaks, particularly in situations where there are shifts in the baseline patterns of health-care use. For example, during an epidemic, people might stay away from hospitals because of the fear of becoming infected, whereas after a suspected bioterrorist attack with an infectious agent, hospitals might be flooded with “worried well” (healthy people who think they have been exposed to the agent). Baseline shifts like these might prevent the detection of increased illness caused by the epidemic or the bioterrorist attack. Localized population surges associated with major public events (for example, the Olympics) are also likely to reduce the ability of existing surveillance systems to detect infectious disease outbreaks. In this study, the researchers developed a new class of surveillance systems called “epidemiological network models.” These systems aim to improve the detection of disease outbreaks by monitoring fluctuations in the relationships between information detailing the use of various health-care resources over time (data streams).
What Did the Researchers Do and Find?
The researchers used data collected over a 3-y period from five Boston hospitals on visits for respiratory (breathing) problems and for gastrointestinal (stomach and gut) problems, and on total visits (15 data streams in total), to construct a network model that included all the possible pair-wise comparisons between the data streams. They tested this model by comparing its ability to detect simulated disease outbreaks implanted into data collected over an additional year with that of a reference model based on individual data streams. The network approach, they report, was better at detecting localized outbreaks of respiratory and gastrointestinal disease than the reference approach. To investigate how well the network model dealt with baseline shifts in the use of health-care resources, the researchers then added in a large population surge. The detection performance of the reference model decreased in this test, but the performance of the complete network model and of models that included relationships between only some of the data streams remained stable. Finally, the researchers tested what would happen in a situation where there were large numbers of “worried well.” Again, the network models detected disease outbreaks consistently better than the reference model.
What Do These Findings Mean?
These findings suggest that epidemiological network systems that monitor the relationships between health-care resource-utilization data streams might detect disease outbreaks better than current systems under normal conditions and might be less affected by unpredictable shifts in the baseline data. However, because the tests of the new class of surveillance system reported here used simulated infectious disease outbreaks and baseline shifts, the network models may behave differently in real-life situations or if built using data from other hospitals. Nevertheless, these findings strongly suggest that public-health officials, provided they have sufficient computer power at their disposal, might improve their ability to detect disease outbreaks by using epidemiological network systems alongside their current disease-surveillance systems.
Additional Information.
Please access these Web sites via the online version of this summary at
Wikipedia pages on public health (note that Wikipedia is a free online encyclopedia that anyone can edit, and is available in several languages)
A brief description from the World Health Organization of public-health surveillance (in English, French, Spanish, Russian, Arabic, and Chinese)
A detailed report from the US Centers for Disease Control and Prevention called “Framework for Evaluating Public Health Surveillance Systems for the Early Detection of Outbreaks”
The International Society for Disease Surveillance Web site
PMCID: PMC1896205  PMID: 17593895
22.  Modeling potential responses to smallpox as a bioterrorist weapon. 
Emerging Infectious Diseases  2001;7(6):959-969.
We constructed a mathematical model to describe the spread of smallpox after a deliberate release of the virus. Assuming 100 persons initially infected and 3 persons infected per infectious person, quarantine alone could stop disease transmission but would require a minimum daily removal rate of 50% of those with overt symptoms. Vaccination would stop the outbreak within 365 days after release only if disease transmission were reduced to <0.85 persons infected per infectious person. A combined vaccination and quarantine campaign could stop an outbreak if a daily quarantine rate of 25% were achieved and vaccination reduced smallpox transmission by > or = 33%. In such a scenario, approximately 4,200 cases would occur and 365 days would be needed to stop the outbreak. Historical data indicate that a median of 2,155 smallpox vaccine doses per case were given to stop outbreaks, implying that a stockpile of 40 million doses should be adequate.
PMCID: PMC2631899  PMID: 11747722
23.  Calculating the potential for within-flight transmission of influenza A (H1N1) 
BMC Medicine  2009;7:81.
Clearly air travel, by transporting infectious individuals from one geographic location to another, significantly affects the rate of spread of influenza A (H1N1). However, the possibility of within-flight transmission of H1N1 has not been evaluated; although it is known that smallpox, measles, tuberculosis, SARS and seasonal influenza can be transmitted during commercial flights. Here we present the first quantitative risk assessment to assess the potential for within-flight transmission of H1N1.
We model airborne transmission of infectious viral particles of H1N1 within a Boeing 747 using methodology from the field of quantitative microbial risk assessment.
The risk of catching H1N1 will essentially be confined to passengers travelling in the same cabin as the source case. Not surprisingly, we find that the longer the flight the greater the number of infections that can be expected. We calculate that H1N1, even during long flights, poses a low to moderate within-flight transmission risk if the source case travels First Class. Specifically, 0-1 infections could occur during a 5 hour flight, 1-3 during an 11 hour flight and 2-5 during a 17 hour flight. However, within-flight transmission could be significant, particularly during long flights, if the source case travels in Economy Class. Specifically, two to five infections could occur during a 5 hour flight, 5-10 during an 11 hour flight and 7-17 during a 17 hour flight. If the aircraft is only partially loaded, under certain conditions more infections could occur in First Class than in Economy Class. During a 17 hour flight, a greater number of infections would occur in First Class than in Economy if the First Class Cabin is fully occupied, but Economy class is less than 30% full.
Our results provide insights into the potential utility of air travel restrictions on controlling influenza pandemics in the winter of 2009/2010. They show travel by one infectious individual, rather than causing a single outbreak of H1N1, could cause several simultaneous outbreaks. These results imply that, during a pandemic, quarantining passengers who travel in Economy on long-haul flights could potentially be an important control strategy. Notably, our results show that quarantining passengers who travel First Class would be unlikely to be an effective control strategy.
PMCID: PMC2813231  PMID: 20034378
24.  Nonpharmaceutical Interventions for Pandemic Influenza, International Measures 
Emerging Infectious Diseases  2006;12(1):81-87.
Closing international borders was usually ineffective in past pandemics and would be less effective today.
Since global availability of vaccine and antiviral agents against influenza caused by novel human subtypes is insufficient, the World Health Organization (WHO) recommends nonpharmaceutical public health interventions to contain infection, delay spread, and reduce the impact of pandemic disease. Virus transmission characteristics will not be completely known in advance, but difficulties in influenza control typically include peak infectivity early in illness, a short interval between cases, and to a lesser extent, transmission from persons with incubating or asymptomatic infection. Screening and quarantining entering travelers at international borders did not substantially delay virus introduction in past pandemics, except in some island countries, and will likely be even less effective in the modern era. Instead, WHO recommends providing information to international travelers and possibly screening travelers departing countries with transmissible human infection. The principal focus of interventions against pandemic influenza spread should be at national and community levels rather than international borders.
PMCID: PMC3291414  PMID: 16494722
influenza; World Health Organization; quarantine
25.  Lessons from the History of Quarantine, from Plague to Influenza A 
Emerging Infectious Diseases  2013;19(2):254-259.
The complex and controversial history of this centuries-old public health strategy offers guidance for its future use.
In the new millennium, the centuries-old strategy of quarantine is becoming a powerful component of the public health response to emerging and reemerging infectious diseases. During the 2003 pandemic of severe acute respiratory syndrome, the use of quarantine, border controls, contact tracing, and surveillance proved effective in containing the global threat in just over 3 months. For centuries, these practices have been the cornerstone of organized responses to infectious disease outbreaks. However, the use of quarantine and other measures for controlling epidemic diseases has always been controversial because such strategies raise political, ethical, and socioeconomic issues and require a careful balance between public interest and individual rights. In a globalized world that is becoming ever more vulnerable to communicable diseases, a historical perspective can help clarify the use and implications of a still-valid public health strategy.
PMCID: PMC3559034  PMID: 23343512
infectious diseases; epidemics; public health measures; quarantine; isolation; maritime quarantine; sanitary cordons; lazarettos; public health emergencies; political issues; economic issues; social issues; ethical issues; viruses; bacteria; discrimination; stigmatization; prejudice; border controls; communicable diseases; influenza; cholera; Black Death; SARS; severe acute respiratory syndrome

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