Household transmission of pandemic (H1N1) 2009, San Antonio, Texas, USA, April-May 2009

A method to estimate the serial interval distribution under partially-sampled data

The serial interval of an infectious disease is an important variable in epidemiology. It is defined as the period of time between the symptom onset times of the infector and infectee in a direct transmission pair. Under partially sampled data, purported infector-infectee pairs may actually be separated by one or more unsampled cases in between. Misunderstanding such pairs as direct transmissions will result in overestimating the length of serial intervals. On the other hand, two cases that are infected by an unseen third case (known as coprimary transmission) may be classified as a direct transmission pair, leading to an underestimation of the serial interval. Here, we introduce a method to jointly estimate the distribution of serial intervals factoring in these two sources of error. We simultaneously estimate the distribution of the number of unsampled intermediate cases between purported infector-infectee pairs, as well as the fraction of such pairs that are coprimary. We also extend our method to situations where each infectee has multiple possible infectors, and show how to factor this additional source of uncertainty into our estimates. We assess our method's performance on simulated data sets and find that our method provides consistent and robust estimates. We also apply our method to data from real-life outbreaks of four infectious diseases and compare our results with published results. With similar accuracy, our method of estimating serial interval distribution provides unique advantages, allowing its application in settings of low sampling rates and large population sizes, such as widespread community transmission tracked by routine public health surveillance.

Impact of Nonpharmacological Interventions on Severe Acute Respiratory Infections in Children: From the National Surveillance Database

BACKGROUND

Nonpharmacological interventions (NPIs) reduce the incidence of respiratory infections. After NPIs imposed during the coronavirus disease 2019 pandemic ceased, respiratory infections gradually increased worldwide. However, few studies have been conducted on severe respiratory infections requiring hospitalization in pediatric patients. This study compares epidemiological changes in severe respiratory infections during pre-NPI, NPI, and post-NPI periods in order to evaluate the effect of that NPI on severe respiratory infections in children.

METHODS

We retrospectively studied data collected at 13 Korean sentinel sites from January 2018 to October 2022 that were lodged in the national Severe Acute Respiratory Infections (SARIs) surveillance database.

RESULTS

A total of 9,631 pediatric patients were admitted with SARIs during the pre-NPI period, 579 during the NPI period, and 1,580 during the post-NPI period. During the NPI period, the number of pediatric patients hospitalized with severe respiratory infections decreased dramatically, thus from 72.1 per 1,000 to 6.6 per 1,000. However, after NPIs ceased, the number increased to 22.8 per 1,000. During the post-NPI period, the positive test rate increased to the level noted before the pandemic.

CONCLUSION

Strict NPIs including school and daycare center closures effectively reduced severe respiratory infections requiring hospitalization of children. However, childcare was severely compromised. To prepare for future respiratory infections, there is a need to develop a social consensus on NPIs that are appropriate for children.

Household transmission of influenza A and B within a prospective cohort during the 2013-2014 and 2014-2015 seasons

People living within the same household as someone ill with influenza are at increased risk of infection. Here, we use Markov chain Monte Carlo methods to partition the hazard of influenza illness within a cohort into the hazard from the community and the hazard from the household. During the 2013‐2014 influenza season, 49 (4.7%) of the 1044 people enrolled in a community surveillance cohort had an acute respiratory illness (ARI) attributable to influenza. During the 2014‐2015 influenza season, 50 (4.7%) of the 1063 people in the cohort had an ARI attributable to influenza. The secondary attack rate from a household member was 2.3% for influenza A (H1) during 2013‐2014, 5.3% for influenza B during 2013‐2014, and 7.6% for influenza A (H3) during 2014‐2015. Living in a household with a person ill with influenza increased the risk of an ARI attributable to influenza up to 350%, depending on the season and the influenza virus circulating within the household.

Estimating and interpreting secondary attack risk: Binomial considered biased

The household secondary attack risk (SAR), often called the secondary attack rate or secondary infection risk, is the probability of infectious contact from an infectious household member A to a given household member B, where we define infectious contact to be a contact sufficient to infect B if he or she is susceptible. Estimation of the SAR is an important part of understanding and controlling the transmission of infectious diseases. In practice, it is most often estimated using binomial models such as logistic regression, which implicitly attribute all secondary infections in a household to the primary case. In the simplest case, the number of secondary infections in a household with m susceptibles and a single primary case is modeled as a binomial(m, p) random variable where p is the SAR. Although it has long been understood that transmission within households is not binomial, it is thought that multiple generations of transmission can be neglected safely when p is small. We use probability generating functions and simulations to show that this is a mistake. The proportion of susceptible household members infected can be substantially larger than the SAR even when p is small. As a result, binomial estimates of the SAR are biased upward and their confidence intervals have poor coverage probabilities even if adjusted for clustering. Accurate point and interval estimates of the SAR can be obtained using longitudinal chain binomial models or pairwise survival analysis, which account for multiple generations of transmission within households, the ongoing risk of infection from outside the household, and incomplete follow-up. We illustrate the practical implications of these results in an analysis of household surveillance data collected by the Los Angeles County Department of Public Health during the 2009 influenza A (H1N1) pandemic.

The household secondary attack risk (SAR), often called the secondary attack rate or secondary infection risk, is the probability of infectious contact from an infectious household member A to a given household member B, where we define infectious contact to be a contact sufficient to infect B if he or she is susceptible. The most common statistical models used to estimate the SAR are binomial models such as logistic regression, which implicitly assume that all secondary infections in a household are infected by the primary case. Here, we use analytical calculations and simulations to show that estimation of the SAR must account for multiple generations of transmission within households. As an example, we show that binomial models and statistical models that account for multiple generations of within-household transmission reach different conclusions about the household SAR for 2009 influenza A (H1N1) in Los Angeles County, with the latter models fitting the data better. In an epidemic, accurate estimation of the SAR allows rigorous evaluation of the effectiveness of public health interventions such as social distancing, prophylaxis or treatment, and vaccination.

Improved inference of time-varying reproduction numbers during infectious disease outbreaks

Accurate estimation of the parameters characterising infectious disease transmission is vital for optimising control interventions during epidemics. A valuable metric for assessing the current threat posed by an outbreak is the time-dependent reproduction number, i.e. the expected number of secondary cases caused by each infected individual. This quantity can be estimated using data on the numbers of observed new cases at successive times during an epidemic and the distribution of the serial interval (the time between symptomatic cases in a transmission chain). Some methods for estimating the reproduction number rely on pre-existing estimates of the serial interval distribution and assume that the entire outbreak is driven by local transmission. Here we show that accurate inference of current transmissibility, and the uncertainty associated with this estimate, requires: (i) up-to-date observations of the serial interval to be included, and; (ii) cases arising from local transmission to be distinguished from those imported from elsewhere. We demonstrate how pathogen transmissibility can be inferred appropriately using datasets from outbreaks of H1N1 influenza, Ebola virus disease and Middle-East Respiratory Syndrome. We present a tool for estimating the reproduction number in real-time during infectious disease outbreaks accurately, which is available as an R software package (EpiEstim 2.2). It is also accessible as an interactive, user-friendly online interface (EpiEstim App), permitting its use by non-specialists. Our tool is easy to apply for assessing the transmission potential, and hence informing control, during future outbreaks of a wide range of invading pathogens.

Improved inference of time-varying reproduction numbers during infectious disease outbreaks

Accurate estimation of the parameters characterising infectious disease transmission is vital for optimising control interventions during epidemics. A valuable metric for assessing the current threat posed by an outbreak is the time-dependent reproduction number, i.e. the expected number of secondary cases caused by each infected individual. This quantity can be estimated using data on the numbers of observed new cases at successive times during an epidemic and the distribution of the serial interval (the time between symptomatic cases in a transmission chain). Some methods for estimating the reproduction number rely on pre-existing estimates of the serial interval distribution and assume that the entire outbreak is driven by local transmission. Here we show that accurate inference of current transmissibility, and the uncertainty associated with this estimate, requires: (i) up-to-date observations of the serial interval to be included, and; (ii) cases arising from local transmission to be distinguished from those imported from elsewhere. We demonstrate how pathogen transmissibility can be inferred appropriately using datasets from outbreaks of H1N1 influenza, Ebola virus disease and Middle-East Respiratory Syndrome. We present a tool for estimating the reproduction number in real-time during infectious disease outbreaks accurately, which is available as an R software package (EpiEstim 2.2). It is also accessible as an interactive, user-friendly online interface (EpiEstim App), permitting its use by non-specialists. Our tool is easy to apply for assessing the transmission potential, and hence informing control, during future outbreaks of a wide range of invading pathogens.

Assessing the reporting quality of influenza outbreaks in the community

BACKGROUND

High-quality reporting of outbreak characteristics is fundamental to understand the behaviour of various strains of influenza virus and the impact of outbreak management strategies. However, few studies have systematically evaluated the quality of outbreak reporting.

OBJECTIVES

To conduct a systematic analysis and assessment for reporting quality of influenza outbreaks based on a modified version of the STROBE statement, and to examine characteristics associated with reporting quality.

METHODS

A literature search was conducted across 3 online databases (PubMed, Web of Science, MEDLINE) for reports of influenza outbreaks (pandemic H1N1, avian, seasonal). The quality of reports meeting our eligibility criteria was assessed using the Modified STROBE criteria and assigned a score of 30. Mean differences (MD) and 95% confidence intervals (CI) were reported for comparisons of study characteristics.

RESULTS

Sixty-four outbreak reports were available for analyses. The average Modified STROBE score was 20/30. Peer-reviewed articles were associated with a better quality of reporting (MD 2.79, 95% CI 0.79-4.78). Likewise, reports from authors affiliated with public health agencies were associated with better quality than those from academic institutions (MD 1.65, 95% CI-0.27-3.56).

CONCLUSIONS

The development of explicit reporting guidelines specifically geared towards reporting of outbreak investigations proved to be useful. Providing information on patient characteristics, investigation details in introduction and results, as well as addressing limitations that could have biased the findings, were frequently missing in the published reports.

Household-level risk factors for secondary influenza-like illness in a rural area of Bangladesh

Objective

To describe household‐level risk factors for secondary influenza‐like illness (ILI), an important public health concern in the low‐income population of Bangladesh.

Methods

Secondary analysis of control participants in a randomised controlled trial evaluating the effect of handwashing to prevent household ILI transmission. We recruited index‐case patients with ILI – fever (<5 years); fever, cough or sore throat (≥5 years) – from health facilities, collected information on household factors and conducted syndromic surveillance among household contacts for 10 days after resolution of index‐case patients’ symptoms. We evaluated the associations between household factors at baseline and secondary ILI among household contacts using negative binomial regression, accounting for clustering by household.

Results

Our sample was 1491 household contacts of 184 index‐case patients. Seventy‐one percentage reported that smoking occurred in their home, 27% shared a latrine with one other household and 36% shared a latrine with >1 other household. A total of 114 household contacts (7.6%) had symptoms of ILI during follow‐up. Smoking in the home (RR_adj 1.9, 95% CI: 1.2, 3.0) and sharing a latrine with one household (RR_adj 2.1, 95% CI: 1.2, 3.6) or >1 household (RR_adj 3.1, 95% CI: 1.8–5.2) were independently associated with increased risk of secondary ILI.

Conclusion

Tobacco use in homes could increase respiratory illness in Bangladesh. The mechanism between use of shared latrines and household ILI transmission is not clear. It is possible that respiratory pathogens could be transmitted through faecal contact or contaminated fomites in shared latrines.

Influenza-like Illness in Households with Children of Preschool Age

BACKGROUND

Influenza-like illness (ILI) is the leading cause of medical consultation amongst preschool children, who may contribute to spreading ILI-causing agents within the household. We aimed to determine the societal burden (incidence, health-care consumption and productivity loss) and correlates of ILI in households with preschool children.

METHODS

A survey was performed in the Netherlands during October 2012 to October 2014. Monthly, 2000 households with children younger than 4 years were invited to report their symptoms and related medical care, productivity loss and putative risk exposures for 1 preschool child and 1 parent.

RESULTS

Eight thousand seven hundred and sixty-eight child-parent pairs were enrolled. ILI incidence was 2.81 episodes/child-year and 1.72 episodes/parent-year. Amongst those with ILI, health-care utilization was 35.7% (children) and 17.7% (parents). Work absenteeism was 45.7% (median 2 workdays lost) and day-care absenteeism was 22.8% (median 1 day missed). Chronic respiratory conditions, developmental disabilities, parental occupation in health care/child care, having a sibling and attending day care for ≤12 months increased childhood ILI risk. Parental ILI risk increased with having chronic respiratory conditions, developmentally disabled day-care-attending children and female gender in interaction with unemployment and multiple day-care-attending children. Breastfeeding infants 6-month-old or younger and attending day care for >24 months decreased childhood ILI risk. Pregnancy, occupation in health care and having ≥3 children decreased parental ILI risk. Parents of ILI-affected children had a concurrent 4-fold higher ILI risk.

CONCLUSION

ILI in households with preschool children has a considerable societal impact. Risk-mitigating initiatives seem justified for day-care attendees, mothers, people with chronic respiratory conditions, and children with developmental disabilities. Children attending day care for >2 years acquire some protection to ILI.

Household Transmission of Influenza Virus

Human influenza viruses cause regular epidemics and occasional pandemics with a substantial public health burden. Household transmission studies have provided valuable information on the dynamics of influenza transmission. We reviewed published studies and found that once one household member is infected with influenza, the risk of infection in a household contact can be up to 38%, and the delay between onset in index and secondary cases is around 3 days. Younger age was associated with higher susceptibility. In the future, household transmission studies will provide information on transmission dynamics, including the correlation of virus shedding and symptoms with transmission, and the correlation of new measures of immunity with protection against infection.

Historically, household cohort studies have provided valuable information on the incidence of respiratory infections and risk factors for infection. However, these studies require substantial resources and can provide limited information on transmission dynamics.

Household transmission studies provide an efficient approach to describing the risk of influenza transmission and factors affecting transmission. In these studies, households with at least one member infected by influenza are eligible and are followed intensively for 1–2 weeks to observe secondary transmission within the household.

Transmission studies also provide a model for evaluation of interventions in randomized controlled trials, and have been used to determine the efficacy of antiviral drugs for treatment and prophylaxis, and nonpharmaceutical interventions such as face masks and hand hygiene.

Case-ascertained study of household transmission of seasonal influenza - South Africa, 2013

OBJECTIVES

The household is important in influenza transmission due to intensity of contact. Previous studies reported secondary attack rates (SAR) of 4-10% for laboratory-confirmed influenza in the household. Few have been conducted in middle-income countries.

METHODS

We performed a case-ascertained household transmission study during May-October 2013. Index cases were patients with influenza-like-illness (cough and self-reported or measured fever (≥38 °C)) with onset in the last 3 days and no sick household contacts, at clinics in South Africa. Household contacts of index cases with laboratory-confirmed influenza were followed for 12 days.

RESULTS

Thirty index cases in 30 households and 107/110 (97%) eligible household contacts were enrolled. Assuming those not enrolled were influenza negative, 21/110 household contacts had laboratory-confirmed influenza (SAR 19%); the mean serial interval was 2.1 days (SD = 0.35, range 2-3 days). Most (62/82; 76%) household contacts who completed the risk factor questionnaire never avoided contact and 43/82 (52%) continued to share a bed with the index case after illness onset.

CONCLUSION

SAR for laboratory-confirmed influenza in South Africa was higher than previously reported SARs. Household contacts did not report changing behaviors to prevent transmission. These results can be used to understand and predict influenza transmission in similar middle-income settings.

Serial intervals of respiratory infectious diseases: a systematic review and analysis

The serial interval of an infectious disease represents the duration between symptom onset of a primary case and symptom onset of its secondary cases. A good evidence base for such values is essential, because they allow investigators to identify epidemiologic links between cases and serve as an important parameter in epidemic transmission models used to design infection control strategies. We reviewed the literature for available data sets containing serial intervals and for reported values of serial intervals. We were able to collect data on outbreaks within households, which we reanalyzed to infer a mean serial interval using a common statistical method. We estimated the mean serial intervals for influenza A(H3N2) (2.2 days), pandemic influenza A(H1N1)pdm09 (2.8 days), respiratory syncytial virus (7.5 days), measles (11.7 days), varicella (14.0 days), smallpox (17.7 days), mumps (18.0 days), rubella (18.3 days), and pertussis (22.8 days). For varicella, we found an evidence-based value that deviates substantially from the 21 days commonly used in transmission models. This value of the serial interval for pertussis is, to the best of our knowledge, the first that is based on observations. Our review reveals that, for most infectious diseases, there is very limited evidence to support the serial intervals that are often cited.

High rate of A(H1N1)pdm09 infections among rural Thai villagers, 2009-2010

Background

Pandemic influenza A(H1N1)pdm09 emerged in Thailand in 2009. A prospective longitudinal adult cohort and household transmission study of influenza-like illness (ILI) was ongoing in rural Thailand at the time of emergence. Symptomatic and subclinical A(H1N1)pdm09 infection rates in the cohort and among household members were evaluated.

Methods

A cohort of 800 Thai adults underwent active community-based surveillance for ILI from 2008–2010. Acute respiratory samples from ILI episodes were tested for A(H1N1)pdm09 by qRT-PCR; acute and 60-day convalescent blood samples were tested by A(H1N1)pdm09 hemagglutination inhibition assay (HI). Enrollment, 12-month and 24-month follow-up blood samples were tested for A(H1N1)pdm09 seroconversion by HI. Household members of influenza A-infected cohort subjects with ILI were enrolled in household transmission investigations in which day 0 and 60 blood samples and acute respiratory samples were tested by either qRT-PCR or HI for A(H1N1)pdm09. Seroconversion between annual blood samples without A(H1N1)pdm09-positive ILI was considered as subclinical infection.

Results

The 2-yr cumulative incidence of A(H1N1)pdm09 infection in the cohort in 2009/2010 was 10.8% (84/781) with an annual incidence of 1.2% in 2009 and 9.7% in 2010; 83.3% of infections were subclinical (50% in 2009 and 85.9% in 2010). The 2-yr cumulative incidence was lowest (5%) in adults born ≤1957. The A(H1N1)pdm09 secondary attack rate among household contacts was 47.2% (17/36); 47.1% of these infections were subclinical. The highest A(H1N1)pdm09 secondary attack rate among household contacts (70.6%, 12/17) occurred among children born between 1990 and 2003.

Conclusion

Subclinical A(H1N1)pdm09 infections in Thai adults occurred frequently and accounted for a greater proportion of all A(H1N1)pdm09 infections than previously estimated. The role of subclinical infections in A(H1N1)pdm09 transmission has important implications in formulating strategies to predict and prevent the spread of A(H1N1)pdm09 and other influenza virus strains.

Animal models for influenza virus pathogenesis, transmission, and immunology

In humans, infection with an influenza A or B virus manifests typically as an acute and self-limited upper respiratory tract illness characterized by fever, cough, sore throat, and malaise. However, influenza can present along a broad spectrum of disease, ranging from sub-clinical or even asymptomatic infection to a severe primary viral pneumonia requiring advanced medical supportive care. Disease severity depends upon the virulence of the influenza virus strain and the immune competence and previous influenza exposures of the patient. Animal models are used in influenza research not only to elucidate the viral and host factors that affect influenza disease outcomes in and spread among susceptible hosts, but also to evaluate interventions designed to prevent or reduce influenza morbidity and mortality in man. This review will focus on the three animal models currently used most frequently in influenza virus research - mice, ferrets, and guinea pigs - and discuss the advantages and disadvantages of each.

Pandemic H1N1 virus transmission and shedding dynamics in index case households of a prospective Vietnamese cohort

Objectives

Influenza household transmission studies are required to guide prevention strategies but most passively recruit index cases that seek healthcare. We investigated A(H1N1)pdm09 transmission in a household-based cohort during 2009.

Methods

Health-workers visited 270 households weekly, and collected swabs from influenza-like-illness cases. If A(H1N1)pdm09 was RT-PCR-confirmed, all household members had symptoms assessed and swabs collected daily for 10–15 days. Viral RNA was quantified and sequenced and serology performed on pre-pandemic sera.

Results

Index cases were detected in 20 households containing 81 people. 98.5% lacked A(H1N1)pdm09 neutralizing antibodies in pre-pandemic sera. Eleven (18.6%, 95% CI 10.7–30.4%) of 59 contacts were infected. Virus genetic diversity within households was negligible and less than between households. Index and secondary cases were distributed between mothers, daughters and sons, and had similar virus-RNA shedding and symptom dynamics. Fathers were rarely infected. Five secondary cases (45%) had no apparent symptoms and three shed virus before symptoms. Secondary infection was associated with index case wet cough (OR 1.56, 95% CI 1.22–1.99).

Conclusions

In this cohort of A(H1N1)pdm09 susceptible persons, virus sequencing was capable of discriminating household from community transmission. Household transmission involved mothers and children but rarely fathers. Asymptomatic or pre-symptomatic shedding was common.

Optimal design of studies of influenza transmission in households. II: comparison between cohort and case-ascertained studies

Both case-ascertained household studies, in which households are recruited after an 'index case' is identified, and household cohort studies, where a household is enrolled before the start of the epidemic, may be used to test and estimate the protective effect of interventions used to prevent influenza transmission. A simulation approach parameterized with empirical data from household studies was used to evaluate and compare the statistical power of four study designs: a cohort study with routine virological testing of household contacts of infected index case, a cohort study where only household contacts with acute respiratory illness (ARI) are sampled for virological testing, a case-ascertained study with routine virological testing of household contacts, and a case-ascertained study where only household contacts with ARI are sampled for virological testing. We found that a case-ascertained study with ARI-triggered testing would be the most powerful design while a cohort design only testing household contacts with ARI was the least powerful. Sensitivity analysis demonstrated that these conclusions varied by model parameters including the serial interval and the risk of influenza virus infection from outside the household.

Novel framework for assessing epidemiologic effects of influenza epidemics and pandemics

Organizing and prioritizing data collection may lead to informed assessment and guide decision making.

The effects of influenza on a population are attributable to the clinical severity of illness and the number of persons infected, which can vary greatly between seasons or pandemics. To create a systematic framework for assessing the public health effects of an emerging pandemic, we reviewed data from past influenza seasons and pandemics to characterize severity and transmissibility (based on ranges of these measures in the United States) and outlined a formal assessment of the potential effects of a novel virus. The assessment was divided into 2 periods. Because early in a pandemic, measurement of severity and transmissibility is uncertain, we used a broad dichotomous scale in the initial assessment to divide the range of historic values. In the refined assessment, as more data became available, we categorized those values more precisely. By organizing and prioritizing data collection, this approach may inform an evidence-based assessment of pandemic effects and guide decision making.

Impact of the availability of an influenza virus rapid antigen test on diagnostic decision making in a pediatric emergency department

OBJECTIVES

Fever is one of the most commonly seen symptoms in the pediatric emergency department. The objective of this study was to observe how the rapid testing for influenza virus impacts on the management of children with fever.

METHODS

We performed a review of our pediatric emergency department records during the 2008/2009 annual influenza season. The BinaxNow Influenza A+B test was performed on patients with the following criteria: age 1.0 to 16.0 years, fever greater than 38.5 °C, fever of less than 96 hours' duration after the onset of clinical illness, clinical signs compatible with acute influenza, and nontoxic appearance. Additional laboratory tests were performed at the treating physician's discretion.

RESULTS

The influenza rapid antigen test was performed in 192 children. One hundred nine (57%) were influenza positive, with the largest fraction (101 patients) positive for influenza A. The age distribution did not differ between children with negative and positive test results (mean, 5.3 vs. 5.1 years, not statistically significant). A larger number of diagnostic tests were performed in the group of influenza-negative patients. Twice as many complete blood counts, C-reactive protein determinations, lumbar punctures, and urinalyses were ordered in the latter group.

CONCLUSIONS

Rapid diagnosis of influenza in the pediatric emergency department affects the management of febrile children as the confirmation of influenza virus infection decreases additional diagnostic tests ordered.

Factors associated with post-seasonal serological titer and risk factors for infection with the pandemic A/H1N1 virus in the French general population

The CoPanFlu-France cohort of households was set up in 2009 to study the risk factors for infection by the pandemic influenza virus (H1N1pdm) in the French general population. The authors developed an integrative data-driven approach to identify individual, collective and environmental factors associated with the post-seasonal serological H1N1pdm geometric mean titer, and derived a nested case-control analysis to identify risk factors for infection during the first season. This analysis included 1377 subjects (601 households). The GMT for the general population was 47.1 (95% confidence interval (CI): 45.1, 49.2). According to a multivariable analysis, pandemic vaccination, seasonal vaccination in 2009, recent history of influenza-like illness, asthma, chronic obstructive pulmonary disease, social contacts at school and use of public transports by the local population were associated with a higher GMT, whereas history of smoking was associated with a lower GMT. Additionally, young age at inclusion and risk perception of exposure to the virus at work were identified as possible risk factors, whereas presence of an air humidifier in the living room was a possible protective factor. These findings will be interpreted in light of the longitudinal analyses of this ongoing cohort.

Influenza A(H1N1)pdm09 during air travel

The global spread of the influenza A(H1N1)pdm09 virus (pH1N1) associated with travelers from North America during the onset of the 2009 pandemic demonstrates the central role of international air travel in virus migration. To characterize risk factors for pH1N1 transmission during air travel, we investigated travelers and airline employees from four North American flights carrying ill travelers with confirmed pH1N1 infection. Of 392 passengers and crew identified, information was available for 290 (74%) passengers were interviewed. Overall attack rates for acute respiratory infection and influenza-like illness 1-7 days after travel were 5.2% and 2.4% respectively. Of 43 individuals that provided sera, 4 (9.3%) tested positive for pH1N1 antibodies, including 3 with serologic evidence of asymptomatic infection. Investigation of novel influenza aboard aircraft may be instructive. However, beyond the initial outbreak phase, it may compete with community-based mitigation activities, and interpretation of findings will be difficult in the context of established community transmission.

Effectiveness of antiviral prophylaxis coupled with contact tracing in reducing the transmission of the influenza A (H1N1-2009): a systematic review

BACKGROUND

During the very early stage of the 2009 pandemic, mass chemoprophylaxis was implemented as part of containment measure. The purposes of the present study were to systematically review the retrospective studies that investigated the effectiveness of antiviral prophylaxis during the 2009 pandemic, and to explicitly estimate the effectiveness by employing a mathematical model.

METHODS

A systematic review identified 17 articles that clearly defined the cases and identified exposed individuals based on contact tracing. Analysing a specific school-driven outbreak, we estimated the effectiveness of antiviral prophylaxis using a renewal equation model. Other parameters, including the reproduction number and the effectiveness of antiviral treatment and school closure, were jointly estimated.

RESULTS

Based on the systematic review, median secondary infection risks (SIRs) among exposed individuals with and without prophylaxis were estimated at 2.1% (quartile: 0, 12.2) and 16.6% (quartile: 8.4, 32.4), respectively. A very high heterogeneity in the SIR was identified with an estimated I2 statistic at 71.8%. From the outbreak data in Madagascar, the effectiveness of mass chemoprophylaxis in reducing secondary transmissions was estimated to range from 92.8% to 95.4% according to different model assumptions and likelihood functions, not varying substantially as compared to other parameters.

CONCLUSIONS

Only based on the meta-analysis of retrospective studies with different study designs and exposure settings, it was not feasible to estimate the effectiveness of antiviral prophylaxis in reducing transmission. However, modelling analysis of a single outbreak successfully yielded an estimate of the effectiveness that appeared to be robust to model assumptions. Future studies should fill the data gap that has existed in observational studies and allow mathematical models to be used for the analysis of meta-data.

Household transmission of respiratory viruses - assessment of viral, individual and household characteristics in a population study of healthy Australian adults

Background

Household transmission of influenza-like illness (ILI) may vary with viral and demographic characteristics. We examined the effect of these factors in a population-based sample of adults with ILI.

Methods

We conducted a prospective cohort study in community-dwelling Australian adults nested within an influenza vaccine effectiveness trial. On presentation with ILI, participants were swabbed for a range of respiratory viruses and asked to return a questionnaire collecting details of household members with or without similar symptoms. We used logistic and Poisson regression to assess the key characteristics of household transmission.

Results

258 participants from multi-occupancy households experienced 279 ILI episodes and returned a questionnaire. Of these, 183 were the primary case in the household allowing assessment of factors associated with transmission. Transmission was significantly associated in univariate analyses with female sex (27% vs. 13%, risk ratio (RR) = 2.13 (1.08, 4.21)) and the presence of a child in the house (33% vs. 17%, RR = 1.90 (1.11, 3.26)). The secondary household attack proportion (SHAP) was 0.14, higher if influenza was isolated (RR = 2.1 (1.0, 4.5)). Vaccinated participants who nonetheless became infected with influenza had a higher SHAP (Incidence RR = 5.24 (2.17, 12.6)).

Conclusions

The increased SHAP in households of vaccinated participants who nonetheless had confirmed influenza infection supports the hypothesis that in years of vaccine mismatch, not only is influenza vaccine less protective for the vaccine recipient, but that the population’s immunity is also lower.

Attack rates assessment of the 2009 pandemic H1N1 influenza A in children and their contacts: a systematic review and meta-analysis

BACKGROUND

The recent H1N1 influenza A pandemic was marked by multiple reports of illness and hospitalization in children, suggesting that children may have played a major role in the propagation of the virus. A comprehensive detailed analysis of the attack rates among children as compared with their contacts in various settings is of great importance for understanding their unique role in influenza pandemics.

METHODOLOGY/PRINCIPAL FINDINGS

We searched MEDLINE (PubMed) and Embase for published studies reporting outbreak investigations with direct measurements of attack rates of the 2009 pandemic H1N1 influenza A among children, and quantified how these compare with those of their contacts. We identified 50 articles suitable for review, which reported school, household, travel and social events. The selected reports and our meta-analysis indicated that children had significantly higher attack rates as compared to adults, and that this phenomenon was observed for both virologically confirmed and clinical cases, in various settings and locations around the world. The review also provided insight into some characteristics of transmission between children and their contacts in the various settings.

CONCLUSION/SIGNIFICANCE

The consistently higher attack rates of the 2009 pandemic H1N1 influenza A among children, as compared to adults, as well as the magnitude of the difference is important for understanding the contribution of children to disease burden, for implementation of mitigation strategies directed towards children, as well as more precise mathematical modeling and simulation of future influenza pandemics.

Reproductive number and serial interval of the first wave of influenza A(H1N1)pdm09 virus in South Africa

Background/Objective

Describing transmissibility parameters of past pandemics from diverse geographic sites remains critical to planning responses to future outbreaks. We characterize the transmissibility of influenza A(H1N1)pdm09 (hereafter pH1N1) in South Africa during 2009 by estimating the serial interval (SI), the initial effective reproductive number (initial R_t) and the temporal variation of R_t.

Methods

We make use of data from a central registry of all pH1N1 laboratory-confirmed cases detected throughout South Africa. Whenever date of symptom onset is missing, we estimate it from the date of specimen collection using a multiple imputation approach repeated 100 times for each missing value. We apply a likelihood-based method (method 1) for simultaneous estimation of initial R_t and the SI; estimate initial R_t from SI distributions established from prior field studies (method 2); and the Wallinga and Teunis method (method 3) to model the temporal variation of R_t.

Results

12,360 confirmed pH1N1 cases were reported in the central registry. During the period of exponential growth of the epidemic (June 21 to August 3, 2009), we simultaneously estimate a mean R_t of 1.47 (95% CI: 1.30–1.72) and mean SI of 2.78 days (95% CI: 1.80–3.75) (method 1). Field studies found a mean SI of 2.3 days between primary cases and laboratory-confirmed secondary cases, and 2.7 days when considering both suspected and confirmed secondary cases. Incorporating the SI estimate from field studies using laboratory-confirmed cases, we found an initial R_t of 1.43 (95% CI: 1.38–1.49) (method 2). The mean R_t peaked at 2.91 (95% CI: 0.85–2.91) on June 21, as the epidemic commenced, and R_t>1 was sustained until August 22 (method 3).

Conclusions

Transmissibility characteristics of pH1N1 in South Africa are similar to estimates reported by countries outside of Africa. Estimations using the likelihood-based method are in agreement with field findings.

Nonparametric survival analysis of infectious disease data

This paper develops nonparametric methods based on contact intervals for the analysis of infectious disease data. The contact interval from person i to person j is the time between the onset of infectiousness in i and infectious contact from i to j, where we define infectious contact as a contact sufficient to infect a susceptible individual. The hazard function of the contact interval distribution equals the hazard of infectious contact from i to j, so it provides a summary of the evolution of infectiousness over time. When who-infects-whom is observed, the Nelson-Aalen estimator produces an unbiased estimate of the cumulative hazard function of the contact interval distribution. When who-infects-whom is not observed, we use an EM algorithm to average the Nelson-Aalen estimates from all possible combinations of who-infected-whom consistent with the observed data. This converges to a nonparametric maximum likelihood estimate of the cumulative hazard function that we call the marginal Nelson-Aalen estimate. We study the behavior of these methods in simulations and use them to analyze household surveillance data from the 2009 influenza A(H1N1) pandemic.

Household transmission of 2009 pandemic influenza A (H1N1): a systematic review and meta-analysis

BACKGROUND

During the 2009 influenza A (H1N1) pandemic, household transmission studies were implemented to better understand the characteristics of the transmission of the novel virus in a confined setting.

METHODS

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.

RESULTS

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%.

CONCLUSIONS

Transmission of the 2009 pandemic virus in households appeared to vary among countries and settings, with differences in estimates of the secondary infection risk also partly due to differences in study designs.

Survival of influenza virus on hands and fomites in community and laboratory settings

BACKGROUND

Transmission dynamics modeling provides a practical method for virtual evaluation of the impact of public health interventions in response to prospective influenza pandemics and also may help determine the relative contribution of different modes of transmission to overall infection rates. Accurate estimates of longevity for all forms of viral particles are needed for such models to be useful.

METHODS

We conducted a time course study to determine the viability and longevity of H1N1 virus on naturally contaminated hands and household surfaces of 20 individuals with laboratory-confirmed infection. Participants coughed or sneezed into their hands, which were sampled immediately and again after 5, 10, and 30 minutes. Samples also were obtained from household surfaces handled by the participants immediately after coughing/sneezing. Clinically obtained H1N1 isolates were used to assess the viability and longevity of the virus on various artificially inoculated common household surfaces and human hands in a controlled laboratory setting. Viral detection was achieved by culture and real-time reverse-transcriptase polymerase chain reaction.

RESULTS

The results suggest that H1N1 does not survive long on naturally contaminated skin and fomites, and that secretions deposited on hands by coughing or sneezing have a concentration of <2.15 × 10 to 2.94 × 10 TCID(50)/mL.

CONCLUSIONS

These data can be used to estimate the relative contribution of direct and indirect contact transmission on overall infection rates.

Preventable and non-preventable risk factors for influenza transmission and hygiene behavior in German influenza households, pandemic season (H1N1) 2009/2010

BACKGROUND

To date, little is known about the role of behavioral risk factors for influenza transmission as well as hygiene behavior in the household setting during the influenza pandemic (H1N1) 2009. In a household-based study conducted during 2008/2009, we identified several behavioral risk factors for influenza transmission; 30% of index patients and 30% of household contacts reported increased hand cleaning frequency in the week after symptom onset of the index patient. We conducted another household-based study during the pandemic season 2009/2010.

METHODS

We identified index patients with laboratory confirmed influenza infection and interviewed household members after illness day 8 of the index patient. Outcome was influenza-like illness (ILI) in a household contact.

RESULTS

We included 108 households. Overall secondary attack rate was 10·1% (27/267) and decreased with increasing age. Apart from being in close daily proximity with the index patient for at least 9 hours, no other behavioral risk factor was associated with secondary ILI. Of all index patients and household contacts, 49% and 55%, respectively, cleaned their hands more often in the week after symptom onset of the index patient (in comparison with 2008/2009 P-value for both <0·01).

CONCLUSIONS

While the study was hampered by its relatively limited size, data suggest that a significantly larger proportion of influenza households practiced good hand hygiene compared to the last pre-pandemic season. This may have led to a different risk factor profile and a delay of the time threshold necessary for transmission among household members with close contact.

Secondary household transmission of 2009 pandemic influenza A (H1N1) virus among an urban and rural population in Kenya, 2009-2010

Background

In Kenya, >1,200 laboratory-confirmed 2009 pandemic influenza A (H1N1) (pH1N1) cases occurred since June 2009. We used population-based infectious disease surveillance (PBIDS) data to assess household transmission of pH1N1 in urban Nairobi (Kibera) and rural Lwak.

Methods

We defined a pH1N1 patient as laboratory-confirmed pH1N1 infection among PBIDS participants during August 1, 2009–February 5, 2010, in Kibera, or August 1, 2009–January 20, 2010, in Lwak, and a case household as a household with a laboratory-confirmed pH1N1 patient. Community interviewers visited PBIDS-participating households to inquire about illnesses among household members. We randomly selected 4 comparison households per case household matched by number of children aged <5. Comparison households had a household visit 10 days before or after the matched patient symptom onset date. We defined influenza-like illnesses (ILI) as self-reported cough or sore throat, and a self-reported fever ≤8 days after the pH1N1 patient's symptom onset in case households and ≤8 days before selected household visit in comparison households. We used the Cochran-Mantel-Haenszel test to compare proportions of ILIs among case and comparison households, and log binomial-model to compare that of Kibera and Lwak.

Results

Among household contacts of patients with confirmed pH1N1 in Kibera, 4.6% had ILI compared with 8.2% in Lwak (risk ratio [RR], 0.5; 95% confidence interval [CI], 0.3–0.9). Household contacts of patients were more likely to have ILIs than comparison-household members in both Kibera (RR, 1.8; 95% CI, 1.1–2.8) and Lwak (RR, 2.6; 95% CI, 1.6–4.3). Overall, ILI was not associated with patient age. However, ILI rates among household contacts were higher among children aged <5 years than persons aged ≥5 years in Lwak, but not Kibera.

Conclusions

Substantial pH1N1 household transmission occurred in urban and rural Kenya. Household transmission rates were higher in the rural area.

Integrative study of pandemic A/H1N1 influenza infections: design and methods of the CoPanFlu-France cohort

BACKGROUND

The risk of influenza infection depends on biological characteristics, individual or collective behaviors and the environmental context. The Cohorts for Pandemic Influenza (CoPanFlu) France study was set up in 2009 after the identification of the novel swine-origin A/H1N1 pandemic influenza virus. This cohort of 601 households (1450 subjects) representative for the general population aims at using an integrative approach to study the risk and characteristics of influenza infection as a complex combination of data collected from questionnaires regarding sociodemographic, medical, behavioral characteristics of subjects and indoor environment, using biological samples or environmental databases.

METHODS/DESIGN

Households were included between December 2009 and July 2010. The design of this study relies on systematic follow-up visits between influenza seasons and additional visits during influenza seasons, when an influenza-like illness is detected in a household via an active surveillance system. During systematic visits, a nurse collects individual and environmental data on questionnaires and obtains blood samples from all members of the household. When an influenza-like-illness is detected, a nurse visits the household three times during the 12 following days, and collects data on questionnaires regarding exposure and symptoms, and biological samples (including nasal swabs) from all subjects in the household. The end of the follow-up period is expected in fall 2012.

DISCUSSION

The large amount of data collected throughout the follow-up will permit a multidisciplinary study of influenza infections. Additional data is being collected and analyzed in this ongoing cohort. The longitudinal analysis of these households will permit integrative analyses of complex phenomena such as individual, collective and environmental risk factors of infection, routes of transmission, or determinants of the immune response to infection or vaccination.

Household transmission of 2009 H1N1 influenza virus in Yazd, Iran

OBJECTIVES

The 2009 pandemic influenza A (H1N1) virus is a public health challenge. Notably, laboratory-confirmed cases do not represent the age group most susceptible to infection. To characterize the age distribution of all cases of H1N1 influenza, we studied the personal contacts of confirmed cases to identify the age group at the highest risk.

METHODS

We investigated the family members of 162 laboratory-confirmed cases of 2009 H1N1 in Yazd, Iran. Family members were retrospectively asked whether they had ≥2 respiratory symptoms within 7days of the last contact with the associated index cases. The ages and symptoms of the patients as well as the interval between diagnosis and the onset of symptoms among household contacts were determined using a questionnaire.

RESULTS

We identified 596 family members of index cases, 83 (13.9%) of whom developed acute respiratory illness. No acute respiratory illness was found in 104 families (64%); however, there were 2 cases in 15 families (9.3%) and ≥3 cases in 4 families (24%). Household contacts from 5 to 18years old were more susceptible to acute respiratory illness than those who were ≥51years old (RR=3.174, 95% CI 1.313-7.675 P-value=0.01).

CONCLUSION

Individuals ≤18years old were most susceptible to infection by the H1N1 virus. Therefore, in low-income populations, prevention of the spread of H1N1 to this age group should be emphasized.

Two years after pandemic influenza A/2009/H1N1: what have we learned?

The world had been anticipating another influenza pandemic since the last one in 1968. The pandemic influenza A H1N1 2009 virus (A/2009/H1N1) finally arrived, causing the first pandemic influenza of the new millennium, which has affected over 214 countries and caused over 18,449 deaths. Because of the persistent threat from the A/H5N1 virus since 1997 and the outbreak of the severe acute respiratory syndrome (SARS) coronavirus in 2003, medical and scientific communities have been more prepared in mindset and infrastructure. This preparedness has allowed for rapid and effective research on the epidemiological, clinical, pathological, immunological, virological, and other basic scientific aspects of the disease, with impacts on its control. A PubMed search using the keywords "pandemic influenza virus H1N1 2009" yielded over 2,500 publications, which markedly exceeded the number published on previous pandemics. Only representative works with relevance to clinical microbiology and infectious diseases are reviewed in this article. A significant increase in the understanding of this virus and the disease within such a short amount of time has allowed for the timely development of diagnostic tests, treatments, and preventive measures. These findings could prove useful for future randomized controlled clinical trials and the epidemiological control of future pandemics.

Serologically confirmed household transmission of 2009 pandemic influenza A (H1N1) virus during the first pandemic wave--New York City, April-May 2009

BACKGROUND

Understanding transmissibility of influenza viruses within households is critical for guiding public health response to pandemics. We studied serologically confirmed infection and disease among household contacts of index case patients with 2009 pandemic influenza A (H1N1) virus (pH1N1) infection in a setting of minimal community pH1N1 transmission.

METHODS

We defined index case patients as students and staff of a New York City high school with laboratory-confirmed pH1N1 infection during the earliest phase of the pH1N1 outbreak in April 2009. We visited households of index case patients twice, once in early May and again in June/July 2009. At each visit, household members (both index case patents and household contacts) provided serum samples and completed questionnaires about illness and possible risk factors. Serologic testing was performed using microneutralization and hemagglutination-inhibition assays.

RESULTS

Of 79 eligible household contacts in 28 households, 19% had serologically confirmed pH1N1 infection, and 28% of those infected were asymptomatic. Serologically confirmed infection varied by age among household contacts: 36% of contacts younger than 10 years were infected, compared with 46% of contacts age 10-18 years, 8% of contacts aged 19-54 years, and 22% of contacts aged 55 years and older.

CONCLUSIONS

Infection rates were high for household contacts of persons with confirmed pH1N1, particularly for contacts aged 10-18 years, and asymptomatic infection was common. Efforts to reduce household transmission during influenza pandemics are important adjuncts to strategies to reduce community illness.

Influenza transmission in a community during a seasonal influenza A(H3N2) outbreak (2010-2011) in Mongolia: a community-based prospective cohort study

Background

Knowledge of how influenza viruses spread in a community is important for planning and implementation of effective interventions, including social distancing measures. Households and schools are implicated as the major sites for influenza virus transmission. However, the overall picture of community transmission is not well defined during actual outbreaks. We conducted a community-based prospective cohort study to describe the transmission characteristics of influenza in Mongolia.

Methods and Findings

A total of 5,655 residents in 1,343 households were included in this cohort study. An active search for cases of influenza-like illness (ILI) was performed between October 2010 and April 2011. Data collected during a community outbreak of influenza A(H3N2) were analyzed. Total 282 ILI cases occurred during this period, and 73% of the subjects were aged <15 years. The highest attack rate (20.4%) was in those aged 1–4 years, whereas the attack rate in those aged 5–9 years was 10.8%. Fifty-one secondary cases occurred among 900 household contacts from 43 households (43 index cases), giving an overall crude household secondary attack rate (SAR) of 5.7%. SAR was significantly higher in younger household contacts (relative risk for those aged <1 year: 9.90, 1–4 years: 5.59, and 5–9 years: 6.43). We analyzed the transmission patterns among households and a community and repeated transmissions were detected between households, preschools, and schools. Children aged 1–4 years played an important role in influenza transmission in households and in the community at large. Working-age adults were also a source of influenza in households, whereas elderly cases (aged ≥65 years) had no link with household transmission.

Conclusions

Repeated transmissions between households, preschools, and schools were observed during an influenza A(H3N2) outbreak period in Mongolia, where subjects aged 1–4 years played an important role in influenza transmission.

Transmission dynamics and risk factors for pandemic H1N1-related illness: outbreak investigation in a rural community of British Columbia, Canada

OBJECTIVE

To characterize the first-wave epidemiologic features of influenza-like illness (ILI) associated with the novel pandemic A/H1N1 [A(H1N1)pdm09] virus.

METHODS

We used generalized linear mixed models (GLMM) to assess risk factors and non-parametric and/or parametric distributions to estimate attack rates, secondary attack rates (SAR), duration of illness, and serial interval during a laboratory-confirmed community outbreak of A(H1N1)pdm09 clustered around on-reserve residents and households of an elementary school in rural British Columbia, Canada, in late April/early May 2009. ILI details were collected as part of outbreak investigation by community telephone survey in early June 2009.

RESULTS

Overall, 92/408 (23%) of participants developed ILI and 36/408 (9%) experienced medically attended ILI (MAILI). The overall SAR in households was 22%: highest among participants 1-4 years of age (yoa) (50%) followed by < 1 yoa (38%), 5-8 yoa (20%), 10-19 yoa (13%), 20-49 yoa (20%), and 50-64 yoa (0%). The median serial interval was estimated at 3·5 days (95% CI: 2·1-5·1). In multivariable GLMM analysis, having a chronic condition (OR: 2·58; 95% CI: 1·1-6·04), younger age [1-8 yoa: OR: 4·63; 95% CI: 2·25-9·52; 9-19 yoa: OR: 1·95; 95% CI: 0·97-3·9 (referent: ≥ 20 yoa)] and receipt of 2008-2009 influenza vaccine (OR: 2·68; 95% CI: 1·37-5·25) were associated with increased risk of ILI. Median duration of illness was 9 days, longer among those with chronic conditions (21 days). Median time to seeking care after developing illness was 4·5 days. On-reserve participants had higher chronic conditions, household density, ILI, MAILI, and SAR.

CONCLUSIONS

During a community outbreak of A(H1N1)pdm09-related illness, we identified substantial clinical ILI attack rates exceeding 20% with secondary household attack rates as high as 50% in young children. The serial interval was short suggesting a narrow period to prevent transmission.

Intrahousehold transmission of pandemic (H1N1) 2009 virus, Victoria, Australia

To examine intrahousehold secondary transmission of pandemic (H1N1) 2009 virus in households in Victoria, Australia, we conducted a retrospective cross-sectional study in late 2009. We randomly selected case-patients reported during May-June 2009 and their household contacts. Information collected included household characteristics, use of prevention and control measures, and signs and symptoms. Secondary cases were defined as influenza-like illness in household contacts within the specified period. Secondary transmission was identified for 18 of 122 susceptible household contacts. To identify independent predictors of secondary transmission, we developed a model. Risk factors were concurrent quarantine with the household index case-patient, and a protective factor was antiviral prophylaxis. These findings show that timely provision of antiviral prophylaxis to household contacts, particularly when household members are concurrently quarantined during implementation of pandemic management strategies, delays or contains community transmission of pandemic (H1N1) 2009 virus.

The role of facemasks and hand hygiene in the prevention of influenza transmission in households: results from a cluster randomised trial; Berlin, Germany, 2009-2011

Background

Previous controlled studies on the effect of non-pharmaceutical interventions (NPI) - namely the use of facemasks and intensified hand hygiene - in preventing household transmission of influenza have not produced definitive results. We aimed to investigate efficacy, acceptability, and tolerability of NPI in households with influenza index patients.

Methods

We conducted a cluster randomized controlled trial during the pandemic season 2009/10 and the ensuing influenza season 2010/11. We included households with an influenza positive index case in the absence of further respiratory illness within the preceding 14 days. Study arms were wearing a facemask and practicing intensified hand hygiene (MH group), wearing facemasks only (M group) and none of the two (control group). Main outcome measure was laboratory confirmed influenza infection in a household contact. We used daily questionnaires to examine adherence and tolerability of the interventions.

Results

We recruited 84 households (30 control, 26 M and 28 MH households) with 82, 69 and 67 household contacts, respectively. In 2009/10 all 41 index cases had a influenza A (H1N1) pdm09 infection, in 2010/11 24 had an A (H1N1) pdm09 and 20 had a B infection. The total secondary attack rate was 16% (35/218). In intention-to-treat analysis there was no statistically significant effect of the M and MH interventions on secondary infections. When analysing only households where intervention was implemented within 36 h after symptom onset of the index case, secondary infection in the pooled M and MH groups was significantly lower compared to the control group (adjusted odds ratio 0.16, 95% CI, 0.03-0.92). In a per-protocol analysis odds ratios were significantly reduced among participants of the M group (adjusted odds ratio, 0.30, 95% CI, 0.10-0.94). With the exception of MH index cases in 2010/11 adherence was good for adults and children, contacts and index cases.

Conclusions

Results suggest that household transmission of influenza can be reduced by the use of NPI, such as facemasks and intensified hand hygiene, when implemented early and used diligently. Concerns about acceptability and tolerability of the interventions should not be a reason against their recommendation.

Trial registration

The study was registered with ClinicalTrials.gov (Identifier NCT00833885).

Pandemic influenza A(H1N1) outbreak among a group of medical students who traveled to the Dominican Republic

BACKGROUND

From the beginning of the influenza pandemic until the time the outbreak described here was detected, 77,201 cases of pandemic influenza A(H1N1) with 332 deaths had been reported worldwide, mostly in the United States and Mexico. All of the cases reported in Spain until then had a recent history of travel to Mexico, the Dominican Republic, or Chile. We describe an outbreak of influenza among medical students who traveled from Spain to the Dominican Republic in June 2009.

METHODS

We collected diagnostic samples and clinical histories from consenting medical students who had traveled to the Dominican Republic and from their household contacts after their return to Spain.

RESULTS

Of 113 students on the trip, 62 (55%) developed symptoms; 39 (45%) of 86 students tested had laboratory evidence of influenza A(H1N1) infection. Most students developed symptoms either just before departure from the Dominican Republic or within days of returning to Spain. The estimated secondary attack rate of influenza-like illness among residential contacts of ill students after return to Spain was 2.1%.

CONCLUSIONS

The attack rate of influenza A(H1N1) can vary widely depending on the circumstances of exposure. We report a high attack rate among a group of traveling medical students but a much lower secondary attack rate among their contacts after return from the trip. These findings may aid the development of recommendations to prevent influenza.

Use of antiviral drugs to reduce household transmission of pandemic (H1N1) 2009, United Kingdom

TOC Summary: Early treatment of primary case-patients and prophylaxis of household contacts provides effective protection.

The United Kingdom implemented a containment strategy for pandemic (H1N1) 2009 through administering antiviral agents (AVs) to patients and their close contacts. This observational household cohort study describes the effect of AVs on household transmission. We followed 285 confirmed primary cases in 259 households with 761 contacts. At 2 weeks, the confirmed secondary attack rate (SAR) was 8.1% (62/761) and significantly higher in persons <16 years of age than in those >50 years of age (18.9% vs. 1.2%, p<0.001). Early (<48 hours) treatment of primary case-patients reduced SAR (4.5% vs. 10.6%, p = 0.003). The SAR in child contacts was 33.3% (10/30) when the primary contact was a woman and 2.9% (1/34) when the primary contact was a man (p = 0.010). Of 53 confirmed secondary case-patients, 45 had not received AV prophylaxis. The effectiveness of AV prophylaxis in preventing infection was 92%.

Household transmission of influenza (H1N1-2009) in Japan: age-specificity and reduction of household transmission risk by zanamivir treatment

This study investigated household transmission data for influenza (H1N1-2009) in Japan in order to quantify the age-specific risk of infection and estimate the impact of antiviral treatment on the risk of household transmission. Among a total of 1547 households, involving 4609 household contacts, the secondary attack ratio (SAR) was estimated to be 11.4%. School children aged 5 - 18 years dominated the index cases. Age-specific infectiousness and susceptibility were highest among 0 - 4-year olds, with SAR estimated at 19.4% and 29.6%, respectively. Zanamivir treatment within 24 and 24 - 48 h of illness onset in index cases, respectively, reduced the risk of household transmission to 0.57 (95% CI 0.44, 0.73) and 0.58 (95% CI 0.38, 0.86) times that among those receiving the same treatment at > 48 h and those not receiving treatment. The preventive performance of antiviral treatment and prophylaxis should be further examined in randomized controlled trials.

The effect of age on transmission of 2009 pandemic influenza A (H1N1) in a camp and associated households

BACKGROUND

A major portion of influenza disease burden during the 2009 pandemic was observed among young people.

METHODS

We examined the effect of age on the transmission of influenza-like illness associated with the 2009 pandemic influenza A (H1N1) virus (pH1N1) for an April-May 2009 outbreak among youth-camp participants and household contacts in Washington State.

RESULTS

An influenza-like illness attack rate of 51% was found among 96 camp participants. We observed a cabin secondary attack rate of 42% (95% confidence interval = 21%-66%) and a camp local reproductive number of 2.7 (1.7-4.1) for influenza-like illness among children (less than 18 years old). Among the 136 contacts in the 41 households with an influenza-like illness index case who attended the camp, the influenza-like illness secondary attack rate was 11% for children (5%-21%) and 4% for adults (2%-8%). The odds ratio for influenza-like illness among children versus adults was 3.1 (1.3-7.3).

CONCLUSIONS

The strong age effect, combined with the low number of susceptible children per household (1.2), plausibly explains the lower-than-expected household secondary attack rate for influenza-like illness, illustrating the importance of other venues where children congregate for sustaining community transmission. Quantifying the effects of age on pH1N1 transmission is important for informing effective intervention strategies.

Serial intervals and the temporal distribution of secondary infections within households of 2009 pandemic influenza A (H1N1): implications for influenza control recommendations

A critical issue during the 2009 influenza A (H1N1) pandemic was determining the appropriate duration of time individuals with influenza-like illness (ILI) should remain isolated to reduce onward transmission while limiting societal disruption. Ideally this is based on knowledge of the relative infectiousness of ill individuals at each point during the course of the infection. Data on 261 clinically apparent pH1N1 infector-infectee pairs in households, from 7 epidemiological studies conducted in the United States early in 2009, were analyzed to estimate the distribution of times from symptom onset in an infector to symptom onset in the household contacts they infect (mean, 2.9 days, not correcting for tertiary transmission). Only 5% of transmission events were estimated to take place >3 days after the onset of clinical symptoms among those ill with pH1N1 virus. These results will inform future recommendations on duration of isolation of individuals with ILI.

Epidemiology of 2009 pandemic influenza A (H1N1) in the United States

In April 2009, the Centers for Disease Control and Prevention confirmed 2 cases of 2009 pandemic influenza A (H1N1) virus infection in children from southern California, marking the beginning of what would be the first influenza pandemic of the twenty-first century. This report describes the epidemiology of the 2009 H1N1 pandemic in the United States, including characterization of cases, fluctuations of disease burden over the course of a year, the age distribution of illness and severe outcomes, and estimation of the overall burden of disease.

Assessing secondary attack rates among household contacts at the beginning of the influenza A (H1N1) pandemic in Ontario, Canada, April-June 2009: a prospective, observational study

BACKGROUND

Understanding transmission dynamics of the pandemic influenza A (H1N1) virus in various exposure settings and determining whether transmissibility differed from seasonal influenza viruses was a priority for decision making on mitigation strategies at the beginning of the pandemic. The objective of this study was to estimate household secondary attack rates for pandemic influenza in a susceptible population where control measures had yet to be implemented.

METHODS

All Ontario local health units were invited to participate; seven health units volunteered. For all laboratory-confirmed cases reported between April 24 and June 18, 2009, participating health units performed contact tracing to detect secondary cases among household contacts. In total, 87 cases and 266 household contacts were included in this study. Secondary cases were defined as any household member with new onset of acute respiratory illness (fever or two or more respiratory symptoms) or influenza-like illness (fever plus one additional respiratory symptom). Attack rates were estimated using both case definitions.

RESULTS

Secondary attack rates were estimated at 10.3% (95% CI 6.8-14.7) for secondary cases with influenza-like illness and 20.2% (95% CI 15.4-25.6) for secondary cases with acute respiratory illness. For both case definitions, attack rates were significantly higher in children under 16 years than adults (25.4% and 42.4% compared to 7.6% and 17.2%). The median time between symptom onset in the primary case and the secondary case was estimated at 3.0 days.

CONCLUSIONS

Secondary attack rates for pandemic influenza A (H1N1) were comparable to seasonal influenza estimates suggesting similarities in transmission. High secondary attack rates in children provide additional support for increased susceptibility to infection.

Transmission parameters of the A/H1N1 (2009) influenza virus pandemic: a review

Please cite this paper as: Boëlle P‐Y et al. (2011) Transmission parameters of the A/H1N1 (2009) influenza virus pandemic: a review. Influenza and Other Respiratory Viruses 5(5), 306–316.

Background  The new influenza virus A/H1N1 (2009), identified in mid‐2009, rapidly spread over the world. Estimating the transmissibility of this new virus was a public health priority.

Methods  We reviewed all studies presenting estimates of the serial interval or generation time and the reproduction number of the A/H1N1 (2009) virus infection.

Results  Thirteen studies documented the serial interval from household or close‐contact studies, with overall mean 3 days (95% CI: 2·4, 3·6); taking into account tertiary transmission reduced this estimate to 2·6 days. Model‐based estimates were more variable, from 1·9 to 6 days. Twenty‐four studies reported reproduction numbers for community‐based epidemics at the town or country level. The range was 1·2–3·1, with larger estimates reported at the beginning of the pandemic. Accounting for under‐reporting in the early period of the pandemic and limiting variation because of the choice of the generation time interval, the reproduction number was between 1·2 and 2·3 with median 1·5.

Discussion  The serial interval of A/H1N1 (2009) flu was typically short, with mean value similar to the seasonal flu. The estimates of the reproduction number were more variable. Compared with past influenza pandemics, the median reproduction number was similar (1968) or slightly smaller (1889, 1918, 1957).