Households play a major role in community spread of influenza and are potential targets for mitigation strategies.
We enrolled and followed 328 households with children during the 2010-2011 influenza season; this season was characterized by circulation of influenza A (H3N2), A (H1N1)pdm09 and type B viruses. Specimens were collected from subjects with acute respiratory illnesses and tested for influenza in real-time reverse transcriptase polymerase chain reaction (RT-PCR) assays. Influenza cases were classified as community-acquired or household-acquired, and transmission parameters estimated.
Influenza was introduced to 78 (24%) households and transmission to exposed household members was documented in 23 households. Transmission was more likely in younger households (mean age <22 years) and those not reporting home humidification, but was not associated with household vaccination coverage. The secondary infection risk (overall 9.7%) was highest among young children (<9 years) and varied substantially by influenza type/subtype with the highest risk for influenza A (H3N2). The serial interval (overall 3.2 days) also varied by influenza type and was longest for influenza B. Duration of symptomatic illness was shorter in children compared with adults, and did not differ by influenza vaccination status.
Prospective study of households with children over a single influenza season identified differences in household transmission by influenza type/subtype, subject age, and home humidification, suggesting possible targets for interventions to reduce transmission.
In a randomized controlled trial, we administered seasonal trivalent inactivated influenza vaccine (TIV) or placebo to subjects 6–15 years of age in two consecutive years. Receipt of TIV in year 2 induced seroprotection in most subjects. Among 39 children who received TIV in the second year, receipt of TIV in the first year was associated with lower antibody titer rises in the second year to seasonal influenza A(H1N1) and A(H3N2) strains for which the vaccine strains remained unchanged. Antibody response to a different influenza B strain in the second year was unaffected by receipt of TIV in the first year.
vaccination; influenza; antibody response; children
Observational studies show moderate alcohol use negatively associated with ischemic heart disease (IHD) and cardiovascular disease (CVD). However, healthier attributes among moderate users compared to never users may confound the apparent association. A potentially less biased way to examine the association is Mendelian randomization, using alcohol metabolizing genes which influence alcohol use.
We used instrumental variable analysis with aldehyde dehydrogenase 2 (ALDH2) genotypes (AA/GA/GG) as instrumental variables for alcohol use to examine the association of alcohol use (10 g ethanol/day) with CVD risk factors (blood pressure, lipids and glucose) and morbidity (self-reported IHD and CVD) among men in the Guangzhou Biobank Cohort Study.
ALDH2 genotypes were a credible instrument for alcohol use (F-statistic 74.6). Alcohol was positively associated with HDL-cholesterol (0.05 mmol/L per alcohol unit, 95% confidence interval (CI) 0.02 to 0.08) and diastolic blood pressure (1.15 mmHg, 95% CI 0.23 to 2.07) but not with systolic blood pressure (1.00 mmHg, 95% CI -0.74 to 2.74), LDL-cholesterol (0.03 mmol/L, 95% CI -0.03 to 0.08), log transformed triglycerides (0.03 mmol/L, 95% CI -0.01 to 0.08) or log transformed fasting glucose (0.01 mmol/L, 95% CI -0.006 to 0.03), self-reported CVD (odds ratio (OR) 0.98, 95% CI 0.76 to 1.27) or self-reported IHD (OR 1.10, 95% CI 0.83 to 1.45).
Low to moderate alcohol use among men had the expected effects on most CVD risk factors but not fasting glucose. Larger studies are needed to confirm the null associations with IHD, CVD and fasting glucose.
During the 2009 influenza A(H1N1) pandemic, household transmission studies were implemented to understand better the characteristics of the transmission of the novel virus in a confined setting.
We conducted a systematic review and meta-analysis to assess and summarize the findings of these studies. We identified 27 articles, around half of which reported studies conducted in May and June 2009.
In 13 of the 27 studies (48%) that collected respiratory specimens from household contacts, point estimates of the risk of secondary infection ranged from 3 to 38%, with substantial heterogeneity. Meta-regression analyses revealed that a part of the heterogeneity reflected varying case ascertainment and study designs. The estimates of symptomatic secondary infection risk, based on 20 studies identifying febrile acute respiratory illness among household contacts, also showed substantial variability, with point estimates ranging from 4% to 37%.
Transmission of the 2009 pandemic virus in households appeared to vary in different countries and settings, with differences in estimates of the secondary infection risk also partly due to differences in study designs.
Influenza A viruses are believed to spread between humans through contact, large respiratory droplets and small particle droplet nuclei (aerosols), but the relative importance of each of these modes of transmission is unclear. Volunteer studies suggest that infections via aerosol transmission may have a higher risk of febrile illness. Here we apply a mathematical model to data from randomized controlled trials of hand hygiene and surgical face masks in Hong Kong and Bangkok households. In these particular environments, inferences on the relative importance of modes of transmission are facilitated by information on the timing of secondary infections and apparent differences in clinical presentation of secondary infections resulting from aerosol transmission. We find that aerosol transmission accounts for approximately half of all transmission events. This implies that measures to reduce transmission by contact or large droplets may not be sufficient to control influenza A virus transmission in households.
We randomized 115 children to trivalent inactivated influenza vaccine (TIV) or placebo. Over the following 9 months, TIV recipients had an increased risk of virologically-confirmed non-influenza infections (relative risk: 4.40; 95% confidence interval: 1.31-14.8). Being protected against influenza, TIV recipients may lack temporary non-specific immunity that protected against other respiratory viruses.
Testosterone therapy is increasingly promoted. No randomized placebo-controlled trial has been implemented to assess the effect of testosterone therapy on cardiovascular events, although very high levels of androgens are thought to promote cardiovascular disease.
A systematic review and meta-analysis was conducted of placebo-controlled randomized trials of testosterone therapy among men lasting 12+ weeks reporting cardiovascular-related events. We searched PubMed through the end of 2012 using “(“testosterone” or “androgen”) and trial and (“random*”)” with the selection limited to studies of men in English, supplemented by a bibliographic search of the World Health Organization trial registry. Two reviewers independently searched, selected and assessed study quality with differences resolved by consensus. Two statisticians independently abstracted and analyzed data, using random or fixed effects models, as appropriate, with inverse variance weighting.
Of 1,882 studies identified 27 trials were eligible including 2,994, mainly older, men who experienced 180 cardiovascular-related events. Testosterone therapy increased the risk of a cardiovascular-related event (odds ratio (OR) 1.54, 95% confidence interval (CI) 1.09 to 2.18). The effect of testosterone therapy varied with source of funding (P-value for interaction 0.03), but not with baseline testosterone level (P-value for interaction 0.70). In trials not funded by the pharmaceutical industry the risk of a cardiovascular-related event on testosterone therapy was greater (OR 2.06, 95% CI 1.34 to 3.17) than in pharmaceutical industry funded trials (OR 0.89, 95% CI 0.50 to 1.60).
The effects of testosterone on cardiovascular-related events varied with source of funding. Nevertheless, overall and particularly in trials not funded by the pharmaceutical industry, exogenous testosterone increased the risk of cardiovascular-related events, with corresponding implications for the use of testosterone therapy.
Testosterone; Cardiovascular; Men; Trial
With economic development and population aging, ischaemic heart disease (IHD) is becoming a leading cause of mortality with widening inequalities in China. To forewarn the trends in China we projected IHD trends in the most economically developed part of China, i.e., Hong Kong.
Based on sex-specific IHD mortality rates from 1976 to 2005, we projected mortality rates by neighborhood-level socio-economic position (i.e., low- or high-income groups) to 2020 in Hong Kong using Poisson age-period-cohort models with autoregressive priors.
In the low-income group, age-standardized IHD mortality rates among women declined from 33.3 deaths in 1976–1980 to 19.7 per 100,000 in 2016–2020 (from 55.5 deaths to 34.2 per 100,000 among men). The rates in the high-income group were initially higher in both sexes, particularly among men, but this had reversed by the end of the study periods. The rates declined faster for the high-income group than for the low-income group in both sexes. The rates were projected to decline faster in the high-income group, such that by the end of the projection period the high-income group would have lower IHD mortality rates, particularly for women. Birth cohort effects varied with sex, with a marked upturn in IHD mortality around 1945, i.e., for the first generation of men to grow up in a more economically developed environment. There was no such upturn in women. Birth cohort effects were the main drivers of change in IHD mortality rates.
IHD mortality rates are declining in Hong Kong and are projected to continue to do so, even taking into account greater vulnerability for the first generation of men born into a more developed environment. At the same time social disparities in IHD have reversed and are widening, partly as a result of a cohort effect, with corresponding implications for prevention.
This paper describes the potential use of multiple influenza surveillance data to forecast hospital admissions for respiratory diseases.
A sudden surge in hospital admissions in public hospital during influenza peak season has been a challenge to healthcare and manpower planning. In Hong Kong, the timing of influenza peak seasons are variable and early short-term indication of possible surge may facilitate preparedness which could be translated into strategies such as early discharge or reallocation of extra hospital beds. In this study we explore the potential use of multiple routinely collected syndromic data in the forecast of hospital admissions.
A multivariate dynamic linear time series model was fitted to multiple syndromic data including influenza-like illness (ILI) rates among networks of public and private general practitioners (GP), and school absenteeism rates, plus drop-in fever count data from designated flu clinics (DFC) that were created during the pandemic. The latent process derived from the model has been used as a measure of the influenza activity . We compare the cross-correlations between estimated influenza level based on multiple surveillance data and GP ILI data, versus accident and emergency hospital admissions with principal diagnoses of respiratory diseases and pneumonia & influenza (P&I).
The estimated influenza activity has higher cross-correlation with respiratory and P&I admissions (ρ=0.66 and 0.73 respectively) compared to that of GP ILI rates (Table 1). Cross correlations drop distinctly after lag 2 for both estimated influenza activity and GP ILI rates.
The use of a multivariate method to integrate information from multiple sources of influenza surveillance data may have the potential to improve forecasting of admission surge of respiratory diseases.
influenza; surveillance; admission; respiratory
The CDC recommends that healthcare settings provide influenza patients with facemasks as a means of reducing transmission to staff and other patients, and a recent report suggested that surgical masks can capture influenza virus in large droplet spray. However, there is minimal data on influenza virus aerosol shedding, the infectiousness of exhaled aerosols, and none on the impact of facemasks on viral aerosol shedding from patients with seasonal influenza.
We collected samples of exhaled particles (one with and one without a facemask) in two size fractions (“coarse”>5 µm, “fine”≤5 µm) from 37 volunteers within 5 days of seasonal influenza onset, measured viral copy number using quantitative RT-PCR, and tested the fine-particle fraction for culturable virus.
Fine particles contained 8.8 (95% CI 4.1 to 19) fold more viral copies than did coarse particles. Surgical masks reduced viral copy numbers in the fine fraction by 2.8 fold (95% CI 1.5 to 5.2) and in the coarse fraction by 25 fold (95% CI 3.5 to 180). Overall, masks produced a 3.4 fold (95% CI 1.8 to 6.3) reduction in viral aerosol shedding. Correlations between nasopharyngeal swab and the aerosol fraction copy numbers were weak (r = 0.17, coarse; r = 0.29, fine fraction). Copy numbers in exhaled breath declined rapidly with day after onset of illness. Two subjects with the highest copy numbers gave culture positive fine particle samples.
Surgical masks worn by patients reduce aerosols shedding of virus. The abundance of viral copies in fine particle aerosols and evidence for their infectiousness suggests an important role in seasonal influenza transmission. Monitoring exhaled virus aerosols will be important for validation of experimental transmission studies in humans.
The relative importance of direct and indirect contact, large droplet spray, and aerosols as modes of influenza transmission is not known but is important in devising effective interventions. Surgical facemasks worn by patients are recommended by the CDC as a means of reducing the spread of influenza in healthcare facilities. We sought to determine the total number of viral RNA copies present in exhaled breath and cough aerosols, whether the RNA copies in fine particle aerosols represent infectious virus, and whether surgical facemasks reduce the amount of virus shed into aerosols by people infected with seasonal influenza viruses. We found that total viral copies detected by molecular methods were 8.8 times more numerous in fine (≤5 µm) than in coarse (>5 µm) aerosol particles and that the fine particles from cases with the highest total number of viral RNA copies contained infectious virus. Surgical masks reduced the overall number of RNA copies by 3.4 fold. These results suggest an important role for aerosols in transmission of influenza virus and that surgical facemasks worn by infected persons are potentially an effective means of limiting the spread of influenza.
Statins are extensively used for cardiovascular disease prevention. Statins reduce mortality rates more than other lipid-modulating drugs, although evidence from randomized controlled trials also suggests that statins unexpectedly increase the risk of diabetes and improve immune function. Physiologically, statins would be expected to lower androgens because statins inhibit production of the substrate for the local synthesis of androgens and statins' pleiotropic effects are somewhat similar to the physiological effects of lowering testosterone, so we hypothesized that statins lower testosterone.
A meta-analysis of placebo-controlled randomized trials of statins to test the a priori hypothesis that statins lower testosterone. We searched the PubMed, Medline and ISI Web of Science databases until the end of 2011, using '(Testosterone OR androgen) AND (CS-514 OR statin OR simvastatin OR atorvastatin OR fluvastatin OR lovastatin OR rosuvastatin OR pravastatin)' restricted to randomized controlled trials in English, supplemented by a bibliographic search. We included studies with durations of 2+ weeks reporting changes in testosterone. Two reviewers independently searched, selected and assessed study quality. Two statisticians independently abstracted and analyzed data, using random or fixed effects models, as appropriate, with inverse variance weighting.
Of the 29 studies identified 11 were eligible. In 5 homogenous trials of 501 men, mainly middle aged with hypercholesterolemia, statins lowered testosterone by -0.66 nmol/l (95% confidence interval (CI) -0.14 to -1.18). In 6 heterogeneous trials of 368 young women with polycystic ovary syndrome, statins lowered testosterone by -0.40 nmol/l (95% CI -0.05 to -0.75). Overall statins lowered testosterone by -0.44 nmol/l (95% CI -0.75 to -0.13).
Statins may partially operate by lowering testosterone. Whether this is a detrimental side effect or mode of action warrants investigation given the potential implications for drug development and prevention of non-communicable chronic diseases.
See commentary article here http://www.biomedcentral.com/1741-7015/11/58
androgen; cardiovascular; cholesterol; diabetes; inflammation; statins; testosterone
Few studies have investigated the validity of self-collected nose and throat swabs for influenza confirmation in community settings. We followed outpatients with confirmed influenza with sequential measurement of viral loads and applied log-linear regression models to the viral shedding patterns. Among 176 outpatients with confirmed influenza, the detection of virus and quantitative viral loads obtained from self-swabs was consistent with statistical predictions based on earlier and later measurements, suggesting that self-collected nose and throat swabs can be a valid alternative for virologic confirmation of influenza A or B infection in a community setting.
Estimates of the clinical-onset serial interval of human influenza infection (time between onset of symptoms in an index case and a secondary case) are used to inform public health policy and to construct mathematical models of influenza transmission. We estimate the serial interval of laboratory-confirmed influenza transmission in households.
Index cases were recruited after reporting to a primary healthcare center with symptoms. Members of their households were followed up with repeated home visits.
Assuming a Weibull model and accounting for selection bias inherent in our field study design, we used symptom-onset times from 14 pairs of infector/infectee to estimate a mean serial interval of 3.6 days (95% confidence interval = 2.9–4.3 days), with standard deviation 1.6 days.
The household serial interval of influenza may be longer than previously estimated. Studies of the complete serial interval, based on transmission in all community contexts, are a priority.
Animal transmission studies can provide important insights into host, viral and environmental factors affecting transmission of viruses including influenza A. The basic unit of analysis in typical animal transmission experiments is the presence or absence of transmission from an infectious animal to a susceptible animal. In studies comparing two groups (e.g. two host genetic variants, two virus strains, or two arrangements of animal cages), differences between groups are evaluated by comparing the proportion of pairs with successful transmission in each group. The present study aimed to discuss the significance and power to estimate transmissibility and identify differences in the transmissibility based on one-to-one trials. The analyses are illustrated on transmission studies of influenza A viruses in the ferret model.
Employing the stochastic general epidemic model, the basic reproduction number, R0, is derived from the final state of an epidemic and is related to the probability of successful transmission during each one-to-one trial. In studies to estimate transmissibility, we show that 3 pairs of infectious/susceptible animals cannot demonstrate a significantly higher transmissibility than R0 = 1, even if infection occurs in all three pairs. In comparisons between two groups, at least 4 pairs of infectious/susceptible animals are required in each group to ensure high power to identify significant differences in transmissibility between the groups.
These results inform the appropriate sample sizes for animal transmission experiments, while relating the observed proportion of infected pairs to R0, an interpretable epidemiological measure of transmissibility. In addition to the hypothesis testing results, the wide confidence intervals of R0 with small sample sizes also imply that the objective demonstration of difference or similarity should rest on firmly calculated sample size.
Many novel vaccines can cover only a fraction of all antigenic types of a pathogen. Vaccine effectiveness (VE) in the presence of interactions between vaccine strains and others is complicated by the interacting transmission dynamics among all strains. The present study investigated how the VE estimates measured in the field, based on estimated odds ratio or relative risks, are scaled by vaccination coverage and the transmission dynamics in the presence of cross-protective immunity between two strains, i.e. vaccine and non-vaccine strains.
Two different types of epidemiological models, i.e. with and without re-infection by the same antigenic type, were investigated. We computed the relative risk of infection and the odds ratio of vaccination, the latter of which has been measured by indirect cohort method as applied to vaccine effectiveness study of Streptococcus pneumoniae. The VE based on the relative risk was less sensitive to epidemiological dynamics such as cross-protective immunity and vaccination coverage than the VE calculated from the odds ratio, and this was especially the case for the model without re-infection. Vaccine-induced (cross-protective) immunity against a non-vaccine strain appeared to yield the highest impact on the VE estimate calculated from the odds ratio of vaccination.
It is essential to understand the transmission dynamics of non-vaccine strains so that epidemiological methods can appropriately measure both the direct and indirect population impact of vaccination. For pathogens with interacting antigenic types, the most valid estimates of VE, that are unlikely to be biased by the transmission dynamics, may be obtained from longitudinal prospective studies that permit estimation of the VE based on the relative risk of infection among vaccinated compared to unvaccinated individuals.
The household secondary attack proportion is commonly used to measure the transmissibility of an infectious disease.
We analyzed the final outbreak distributions of pandemic A(H1N1), seasonal A(H1N1) and A(H3N2) infections identified in paired sera collected from members of 117 Hong Kong households in April and August-October 2009.
The estimated community probability of infection overall was higher for children than adults; the probability was similar for pandemic A(H1N1) and seasonal A(H3N2) influenza. The household secondary attack proportion for pandemic A(H1N1) was higher in children than adults, whereas for seasonal A(H3N2) it was similar in children and adults. The estimated secondary attack proportions were similar for seasonal A(H3N2) and pandemic A(H1N1) after excluding persons with higher baseline antibody titers from analysis.
Pandemic and seasonal influenza A viruses had similar age-specific transmissibility in a cohort of initially uninfected households after adjustment for baseline immunity.
Although the harms of smoking are well established, it is unclear how they extend into old age in the Chinese.
To examine the relationship of smoking with all‐cause and major cause‐specific mortality in elderly Chinese men and women, respectively, in Hong Kong.
Mortality by smoking status was examined in a prospective cohort study of 56 167 (18 749 men, 37 416 women) Chinese aged ⩾65 years enrolled from 1998 to 2000 at all the 18 elderly health centres of the Hong Kong Government Department of Health.
After a mean follow‐up of 4.1 years, 1848 male and 2035 female deaths occured among 54 214 subjects (96.5% successful follow‐up). At baseline, more men than women were current smokers (20.3% vs 4.0%) and former smokers (40.8% vs 7.9%). The adjusted RRs (95% CI) for all‐cause mortality in former and current smokers, compared with never smokers, were 1.39 (1.23 to 1.56) and 1.75 (1.53 to 2.00) in men and 1.43 (1.25 to 1.64) and 1.38 (1.14 to 1.68) in women, respectively. For current smokers, the RRs (95% CI) for all‐cause mortality were 1.59 (1.39 to 1.82), 1.72 (1.48 to 2.00) and 1.84 (1.43 to 2.35) for daily consumption of 1–9, 10–20 and >21 cigarettes, respectively (p for trend <0.001). RRs (95% CI) were 1.49 (1.30 to 1.72) and 2.20 (1.88 to 2.57) in former and current smokers for all deaths from cancer, and 1.24 (1.04 to 1.47) and 1.57 (1.28 to 1.94) for all cardiovascular deaths, respectively. Quitters had significantly lower risks of death than current smokers from all causes, lung cancer, all cancers, stroke and all cardiovascular diseases.
In old age, smoking continues to be a major cause of death, and quitting is beneficial. Smoking cessation is urgently needed in rapidly ageing populations in the East.
There are few data in the literature on viral sequence variation between host generations/successive transmission events. Relatively little is known about the sequence heterogeneity of the influenza viruses transmitted within families.
To study the molecular epidemiology of influenza virus and to determine the sequence variation within an individual, a household and a community during the first wave of influenza pandemic in 2009.
A prospective study of household transmission of influenza A in Hong Kong was conducted during the pandemic in 2009. The HA and NA sequences of pandemic and seasonal influenza A viral isolates identified in this household transmission study were sequences and analyzed.
Our results indicated that there were multiple introductions of influenza viruses into Hong Kong. Sequence analysis of these isolates suggested that members of these family clusters acquired the infection by household transmissions. Interestingly, unlike those concluded from previous household transmission studies, we observed sequence variations between sequential samples from the same person and also within the same household.
Family clusters of influenza A viral infection are predominantly the result of secondary transmission within a household. Our results also suggested that the intra-host viral sequence variation might be more common that than previously thought.
scarlet fever; group A streptococcus; bacteria; Hong Kong; China; outbreak
Although some studies have suggested that low preoperative 25-hydroxyvitamin D (25-OHD) levels may increase the risk of hypocalcemia and decrease the accuracy of single quick parathyroid hormone in predicting hypocalcemia after total thyroidectomy, the literature remains scarce and inconsistent. Our study aimed to address these issues.
Of the 281 consecutive patients who underwent a total/completion total thyroidectomy, 244 (86.8 %) did not require any oral calcium and/or calcitriol supplements (group 1), while 37 (13.2 %) did (group 2) at hospital discharge. 25-OHD level was checked 1 day before surgery, and postoperative quick parathyroid hormone (PTH) was checked at skin closure (PTH-SC). Postoperative serum calcium was checked regularly. Hypocalcemia was defined by the presence of symptoms or adjusted calcium of <1.90 mmol/L. Significant factors for hypocalcemia were determined by univariate and multivariate analyses. The accuracy of PTH-SC in predicting hypocalcemia was measured by area under a receiver operating characteristic curve (AUC), and the AUC of PTH-SC was compared between patients with preoperative 25-OHD <15 and ≥15 ng/mL via bootstrapping.
Preoperative 25-OHD level was not significantly different between groups 1 and 2 (13.1 vs. 12.5 ng/mL, p = 0.175). After adjusting for other significant factors, PTH-SC (odds ratio 2.49, 95 % confidence interval 1.52–4.07, p < 0.001) and parathyroid autotransplantation (odds ratio 3.23, 95 % confidence interval 1.22–8.60, p = 0.019) were the two independent factors for hypocalcemia. The AUC of PTH-SC was similar between those with 25-OHD <15 and ≥15 ng/mL (0.880 vs. 0.850, p = 0.61)
Low 25-OHD was not a significant factor for hypocalcemia and did not lower the accuracy of quick PTH in predicting postthyroidectomy hypocalcemia.
We applied time-series methods to multivariate sentinel surveillance data recorded in Hong Kong during 1998–2007. Our study demonstrates that simultaneous monitoring of multiple streams of influenza surveillance data can improve the accuracy and timeliness of alerts compared with monitoring of aggregate data or of any single stream alone.
Sentinel surveillance; influenza; multivariate analysis; dispatch
During the 2009 H1N1 pandemic (pH1N1), morbidity and mortality sparing was observed among the elderly population; it was hypothesized that this age group benefited from immunity to pH1N1 due to cross-reactive antibodies generated from prior infection with antigenically similar influenza viruses. Evidence from serologic studies and genetic similarities between pH1N1 and historical influenza viruses suggest that the incidence of pH1N1 cases should drop markedly in age cohorts born prior to the disappearance of H1N1 in 1957, namely those at least 52–53 years old in 2009, but the precise range of ages affected has not been delineated.
Methods and Findings
To test for any age-associated discontinuities in pH1N1 incidence, we aggregated laboratory-confirmed pH1N1 case data from 8 jurisdictions in 7 countries, stratified by single year of age, sex (when available), and hospitalization status. Using single year of age population denominators, we generated smoothed curves of the weighted risk ratio of pH1N1 incidence, and looked for sharp drops at varying age bandwidths, defined as a significantly negative second derivative. Analyses stratified by hospitalization status and sex were used to test alternative explanations for observed discontinuities. We found that the risk of laboratory-confirmed infection with pH1N1 declines with age, but that there was a statistically significant leveling off or increase in risk from about 45 to 50 years of age, after which a sharp drop in risk occurs until the late fifties. This trend was more pronounced in hospitalized cases and in women and was independent of the choice in smoothing parameters. The age range at which the decline in risk accelerates corresponds to the cohort born between 1951–1959 (hospitalized) and 1953–1960 (not hospitalized).
The reduced incidence of pH1N1 disease in older individuals shows a detailed age-specific pattern consistent with protection conferred by exposure to influenza A/H1N1 viruses circulating before 1957.
Influenza pandemics have occurred throughout history and were associated with substantial excess mortality and morbidity. Mathematical models of infectious diseases permit quantitative description of epidemic processes based on the underlying biological mechanisms. Mathematical models have been widely used in the past decade to aid pandemic planning by allowing detailed predictions of the speed of spread of an influenza pandemic and the likely effectiveness of alternative control strategies. During the initial waves of the 2009 influenza pandemic, mathematical models were used to track the spread of the virus, predict the time course of the pandemic and assess the likely impact of large-scale vaccination. While mathematical modeling has made substantial contributions to influenza pandemic preparedness, its use as a real-time tool for pandemic control is currently limited by the lack of essential surveillance information such as serologic data. Mathematical modeling provided a useful framework for analyzing and interpreting surveillance data during the 2009 influenza pandemic, for highlighting limitations in existing pandemic surveillance systems, and for guiding how these systems should be strengthened in order to cope with future epidemics of influenza or other emerging infectious diseases.
(See the editorial commentary by Drumright and Holmes, on pages 284–286.)
Reporting of confirmed pandemic influenza A virus (pH1N1) 2009 infection was mandatory among health care workers in Hong Kong. Among 1158 confirmed infections, there was no significant difference in incidence among clinical versus nonclinical staff (relative risk, 0.98; 95% confidence interval, 0.78–1.20). Reported community exposure to pH1N1 was common and was similar in both groups.