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Observational studies of the effectiveness of vaccines to prevent COVID-19 are needed to inform real-world use. Such studies are now underway amid the ongoing rollout of SARS-CoV-2 vaccines globally. Although traditional case-control and test-negative design studies feature prominently among strategies used to assess vaccine effectiveness, such studies may encounter important threats to validity. Here, we review the theoretical basis for estimation of vaccine direct effects under traditional case-control and test-negative design frameworks, addressing specific natural history parameters of SARS-CoV-2 infection and COVID-19 relevant to these designs. Bias may be introduced by misclassification of cases and controls, particularly when clinical case criteria include common, nonspecific indicators of COVID-19. When using diagnostic assays with high analytical sensitivity for SARS-CoV-2 detection, individuals testing positive may be counted as cases even if their symptoms are due to other causes. The traditional case-control design may be particularly prone to confounding due to associations of vaccination with healthcare-seeking behavior or risk of infection. The test-negative design reduces but may not eliminate this confounding, for instance, if individuals who receive vaccination seek care or testing for less-severe illness. These circumstances indicate the two study designs cannot be applied naively to datasets gathered through public health surveillance or administrative sources. We suggest practical strategies to reduce bias in vaccine effectiveness estimates at the study design and analysis stages.

BackgroundThe test-negative design is an increasingly popular approach for estimating vaccine effectiveness (VE) due to its efficiency. This review aims to examine published test-negative design studies of VE and to explore similarities and differences in methodological choices for different diseases and vaccines.MethodsWe conducted a systematic search on PubMed, Web of Science, and Medline, for studies reporting the effectiveness of any vaccines using a test-negative design. We screened titles and abstracts and reviewed full texts to identify relevant articles. We created a standardized form for each included article to extract information on the pathogen of interest, vaccine(s) being evaluated, study setting, clinical case definition, choices of cases and controls, and statistical approaches used to estimate VE.ResultsWe identified a total of 348 articles, including studies on VE against influenza virus (n = 253), rotavirus (n = 48), pneumococcus (n = 24), and nine other pathogens. Clinical case definitions used to enroll patients were similar by pathogens of interest but the sets of symptoms that defined them varied substantially. Controls could be those testing negative for the pathogen of interest, those testing positive for nonvaccine type of the pathogen of interest, or a subset of those testing positive for alternative pathogens. Most studies controlled for age, calendar time, and comorbidities.ConclusionsOur review highlights similarities and differences in the application of the test-negative design that deserve further examination. If vaccination reduces disease severity in breakthrough infections, particular care must be taken in interpreting vaccine effectiveness estimates from test-negative design studies.

Test-negative designs are commonplace in assessments of influenza vaccination effectiveness, estimating this value from the exposure odds ratio of vaccination among individuals treated for acute respiratory illness who test positive for influenza virus infection. This approach is widely believed to recover the vaccine direct effect by correcting for differential health-care-seeking behavior among vaccinated and unvaccinated persons. However, the relationship of the measured odds ratio to true vaccine effectiveness is poorly understood. We derived the odds ratio under circumstances of real-world test-negative studies. The odds ratio recovers the vaccine direct effect when 2 conditions are met: 1) Individuals' vaccination decisions are uncorrelated with exposure or susceptibility to the test-positive or test-negative conditions, and 2) vaccination confers "all-or-nothing" protection (whereby certain individuals have no protection while others are perfectly protected). Biased effect-size estimates arise if either condition is unmet. Such bias might suggest misleading associations of vaccine effectiveness with time since vaccination or the force of infection of influenza. The test-negative design could also fail to correct for differential health-care-seeking behavior among vaccinated and unvaccinated persons without stringent criteria for enrollment and testing. Our findings demonstrate a need to reassess how data from test-negative studies can inform policy decisions.

Seroprevalence studies assessing community exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Ghana concluded that population-level immunity remained low as of February 2021. Thus, it is important to demonstrate how increasing vaccine coverage reduces the economic and public health impacts associated with SARS-CoV-2 transmission. To that end, this study used a Susceptible-Exposed-Presymptomatic-Symptomatic-Asymptomatic-Recovered-Dead-Vaccinated compartmental model to simulate coronavirus disease 2019 (COVID-19) transmission and the role of public health interventions in Ghana. The impact of increasing vaccination rates and decline in transmission rates due to nonpharmaceutical interventions (NPIs) on cumulative infections and deaths averted was explored under different scenarios. Latin hypercube sampling-partial rank correlation coefficient (LHS-PRCC) was used to investigate the uncertainty and sensitivity of the outcomes to the parameters. Simulation results suggest that increasing the vaccination rate to achieve 50% coverage was associated with almost 60,000 deaths and 25 million infections averted. In comparison, a 50% decrease in the transmission coefficient was associated with the prevention of about 150,000 deaths and 50 million infections. The LHS-PRCC results indicated that in the context of vaccination rate, cumulative infections and deaths averted were most sensitive to vaccination rate, waning immunity rates from vaccination, and waning immunity from natural infection. This study's findings illustrate the impact of increasing vaccination coverage and/or reducing the transmission rate by NPI adherence in the prevention of COVID-19 infections and deaths in Ghana. [ABSTRACT FROM AUTHOR]

A SARS-CoV-2 Omicron BA.5 outbreak occurred in Macau from mid-June through July 2022. Out of >1,800 laboratory-confirmed cases, most were mild or asymptomatic; only 6 deaths were recorded. The outbreak was controlled through stringent public health and social measures, such as repeated universal testing and a stay-athome order lasting 2 weeks. [ABSTRACT FROM AUTHOR]

Author(s): Joseph T. Wu [sup.1], Kathy Leung [sup.1], Mary Bushman [sup.2], Nishant Kishore [sup.2], Rene Niehus [sup.2], Pablo M. de Salazar [sup.2], Benjamin J. Cowling [sup.1], Marc Lipsitch [sup.2], Gabriel [...]

We conducted a scoping review of the epidemiological literature from the past 50 years to document the contribution of influenza virus infection to extrapulmonary clinical outcomes. We identified 99 publications reporting 243 associations using many study designs, exposure and outcome definitions, and methods. Laboratory confirmation of influenza was used in only 28 (12%) estimates, mostly in case-control and self-controlled case series study designs. We identified 50 individual clinical conditions associated with influenza. The most numerous estimates were of cardiocirculatory diseases, neurological/neuromuscular diseases, and fetal/newborn disorders, with myocardial infarction the most common individual outcome. Due to heterogeneity, we could not generate summary estimates of effect size, but of 130 relative effect estimates, 105 (81%) indicated an elevated risk of extrapulmonary outcome with influenza exposure. The literature is indicative of systemic complications of influenza virus infection, the requirement for more effective influenza control, and a need for robust confirmatory studies. [ABSTRACT FROM AUTHOR]

Background: Influenza is the most common vaccine-preventable disease in Australia, causing significant morbidity and mortality. We assessed the burden of influenza across all ages in terms of influenza-associated mortality and hospitalizations using national mortality, hospital-discharge and influenza surveillance data.Methods: Influenza-associated excess respiratory mortality and hospitalization rates from 2007 to 2015 were estimated using generalized additive models with a proxy of influenza activity based on syndromic and laboratory surveillance data. Estimates were made for each age group and year.Results: The estimated mean annual influenza-associated excess respiratory mortality was 2.6 per 100 000 population [95% confidence interval (CI): 1.8, 3.4 per 100 000 population]. The excess annual respiratory hospitalization rate was 57.4 per 100 000 population (95% CI: 32.5, 82.2 per 100 000 population). The highest mortality rates were observed among those aged ≥75 years (35.11 per 100 000 population; 95% CI: 19.93, 50.29 per 100 000 population) and hospitalization rates were also highest among older adults aged ≥75 years (302.95 per 100 000 population; 95% CI: 144.71, 461.19 per 100 000 population), as well as children aged <6 months (164.02 per 100 000 population; 95% CI: -34.84, 362.88 per 100 000 population). Annual variation was apparent, ranging from 1.0 to 3.9 per 100 000 population for mortality and 24.2 to 94.28 per 100 000 population for hospitalizations. Influenza A contributed to almost 80% of the average excess respiratory hospitalizations and 60% of the average excess respiratory deaths.Conclusions: Influenza causes considerable burden to all Australians. Expected variation was observed among age groups, years and influenza type, with the greatest burden falling to older adults and young children. Understanding the current burden is useful for understanding the potential impact of mitigation strategies, such as vaccination. [ABSTRACT FROM AUTHOR]

Background Estimates of the serial interval distribution contribute to our understanding of the transmission dynamics of coronavirus disease 2019 (COVID-19). Here, we aimed to summarize the existing evidence on serial interval distributions and delays in case isolation for COVID-19. Methods We conducted a systematic review of the published literature and preprints in PubMed on 2 epidemiological parameters, namely, serial intervals and delay intervals relating to isolation of cases for COVID-19 from 1 January 2020 to 22 October 2020 following predefined eligibility criteria. We assessed the variation in these parameter estimates using correlation and regression analysis. Results Of 103 unique studies on serial intervals of COVID-19, 56 were included, providing 129 estimates. Of 451 unique studies on isolation delays, 18 were included, providing 74 estimates. Serial interval estimates from 56 included studies varied from 1.0 to 9.9 days, while case isolation delays from 18 included studies varied from 1.0 to 12.5 days, which were associated with spatial, methodological, and temporal factors. In mainland China, the pooled mean serial interval was 6.2 days (range, 5.1–7.8) before the epidemic peak and reduced to 4.9 days (range, 1.9–6.5) after the epidemic peak. Similarly, the pooled mean isolation delay related intervals were 6.0 days (range, 2.9–12.5) and 2.4 days (range, 2.0–2.7) before and after the epidemic peak, respectively. There was a positive association between serial interval and case isolation delay. Conclusions Temporal factors, such as different control measures and case isolation in particular, led to shorter serial interval estimates over time. Correcting transmissibility estimates for these time-varying distributions could aid mitigation efforts. [ABSTRACT FROM AUTHOR]

Hong Kong employed a strategy of intermittent public health and social measures alongside increasingly stringent travel regulations to eliminate domestic SARS-CoV-2 transmission. By analyzing 1899 genome sequences (>18% of confirmed cases) from 23-January-2020 to 26-January-2021, we reveal the effects of fluctuating control measures on the evolution and epidemiology of SARS-CoV-2 lineages in Hong Kong. Despite numerous importations, only three introductions were responsible for 90% of locally-acquired cases. Community outbreaks were caused by novel introductions rather than a resurgence of circulating strains. Thus, local outbreak prevention requires strong border control and community surveillance, especially during periods of less stringent social restriction. Non-adherence to prolonged preventative measures may explain sustained local transmission observed during wave four in late 2020 and early 2021. We also found that, due to a tight transmission bottleneck, transmission of low-frequency single nucleotide variants between hosts is rare. Hong Kong has used an elimination strategy to control SARS-CoV-2 with stringent measures including traveller quarantine. Here, the authors show that the majority of community-acquired cases until January 2021 resulted from three importations, and that increased transmission followed prolonged periods of restrictions, likely due to adherence fatigue. [ABSTRACT FROM AUTHOR]

Background: After relaxing social distancing measures, South Korea experienced a resurgent second epidemic wave of coronavirus disease 2019 (COVID-19). In this study, we aimed to identify the transmission dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and assess the impact of COVID-19 case finding and contact tracing in each epidemic wave. Methods: We collected data on COVID-19 cases published by local public health authorities in South Korea and divided the study into two epidemic periods (19 January–19 April 2020 for the first epidemic wave and 20 April–11 August 2020 for the second epidemic wave). To identify changes in the transmissibility of SARS-CoV-2, the daily effective reproductive number (Rt) was estimated using the illness onset of the cases. Furthermore, to identify the characteristics of each epidemic wave, frequencies of cluster types were measured, and age-specific transmission probability matrices and serial intervals were estimated. The proportion of asymptomatic cases and cases with unknown sources of infection were also estimated to assess the changes of infections identified as cases in each wave. Results: In early May 2020, within 2-weeks of a relaxation in strict social distancing measures, Rt increased rapidly from 0.2 to 1.8 within a week and was around 1 until early July 2020. In both epidemic waves, the most frequent cluster types were religious-related activities and transmissions among the same age were more common. Furthermore, children were rarely infectors or infectees, and the mean serial intervals were similar (~ 3 days) in both waves. The proportion of asymptomatic cases at presentation increased from 22% (in the first wave) to 27% (in the second wave), while the cases with unknown sources of infection were similar in both waves (22 and 25%, respectively). Conclusions: Our study shows that relaxing social distancing measures was associated with increased SARS-CoV-2 transmission despite rigorous case findings in South Korea. Along with social distancing measures, the enhanced contact tracing including asymptomatic cases could be an efficient approach to control further epidemic waves. [ABSTRACT FROM AUTHOR]

Objectives: mask-wearing outside the home has been almost universal in Hong Kong since late January 2020 with very high compliance. Nevertheless, community spread of COVID-19 has still occurred. We aimed to assess the settings where COVID-19 transmission occurred and determine the fraction of transmission events that occurred in settings where masks are not usually worn.Methods: we reviewed detailed information provided by the Hong Kong Department of Health on local COVID-19 cases diagnosed up to 30 September 2020 to determine the most likely settings in which transmission occurred. We classified them in probably mask-on or mask-of and compared the prevalence of asymptomatic infections in these settings.Results: among the 2425 cases (65.3%, 2425/3711) with information on transmission setting, 77.6% of the transmission occurred in household and social settings where face masks are not usually worn. Infections that occurred in mask-on settings were more likely to be asymptomatic (adjusted odds ratio 1.33; 95% confidence interval: 1.04, 1.68).Conclusions: we conclude that universal mask-wearing can reduce transmission, but transmission can continue to occur in settings where face masks are not usually worn. The higher proportion of asymptomatic cases in mask-on settings could be related to a milder disease presentation or earlier case detection. [ABSTRACT FROM AUTHOR]

To inform seroepidemiological studies, we characterized the IgG‐ responses in COVID‐19 patients against the two major SARS‐CoV‐2 viral proteins, spike (S) and nucleocapsid (N). We tested 70 COVID‐19 sera collected up to 85 days post‐symptom onset and 230 non‐COVID‐19 sera, including 27 SARS sera from 2003. Although the average SARS‐CoV‐2 S and N‐IgG titers were comparable, N‐responses were more variable among individuals. S‐ and N‐assay specificity tested with non‐COVID‐19 sera were comparable at 97.5% and 97.0%, respectively. Therefore, S will make a better target due to its lower cross‐reactive potential and its' more consistent frequency of detection compared to N. [ABSTRACT FROM AUTHOR]

During the coronavirus disease pandemic, international travel controls have been widely adopted. To determine the effectiveness of these measures, we analyzed data from 165 countries and found that early implementation of international travel controls led to a mean delay of 5 weeks in the first epidemic peak of cases. [ABSTRACT FROM AUTHOR]

On January 23, 2020, China quarantined Wuhan to contain coronavirus disease (COVID-19). We estimated the probability of transportation of COVID-19 from Wuhan to 369 other cities in China before the quarantine. Expected COVID-19 risk is >50% in 130 (95% CI 89-190) cities and >99% in the 4 largest metropolitan areas. [ABSTRACT FROM AUTHOR]

There is increasing attention to the need to identify new immune markers for the evaluation of existing and new influenza vaccines. Immune markers that could predict individual protection against infection and disease, commonly called correlates of protection (CoPs), play an important role in vaccine development and licensing. Here, we discuss the epidemiologic considerations when evaluating immune markers as potential CoPs for influenza vaccines and emphasize the distinction between correlation and causation. While an immune marker that correlates well with protection from infection can be used as a predictor of vaccine efficacy, it should be distinguished from an immune marker that plays a mechanistic role in conferring protection against a clinical endpoint—the latter might be a more reliable predictor of vaccine efficacy and a more appropriate target for rational vaccine design. To clearly distinguish mechanistic and nonmechanistic CoPs, we suggest using the term "correlates of protection" for nonmechanistic CoPs, and "mediators of protection" for mechanistic CoPs. Furthermore, because the interactions among and relative importance of correlates or mediators of protection can vary according to age or prior vaccine experience, the effect sizes and thresholds for protective effects for CoPs could also vary in different segments of the population. [ABSTRACT FROM AUTHOR]

A fast-spreading severe acute respiratory syndrome coronavirus 2 variant identified in the United Kingdom in December 2020 has raised international alarm. We analyzed data from 15 countries and estimated that the chance that this variant was imported into these countries by travelers from the United Kingdom by December 7 is >50%. [ABSTRACT FROM AUTHOR]

Cities across China implemented stringent social distancing measures in early 2020 to curb coronavirus disease outbreaks. We estimated the speed with which these measures contained transmission in cities. A 1-day delay in implementing social distancing resulted in a containment delay of 2.41 (95% CI 0.97-3.86) days. [ABSTRACT FROM AUTHOR]

We estimate the distribution of serial intervals for 468 confirmed cases of coronavirus disease reported in China as of February 8, 2020. The mean interval was 3.96 days (95% CI 3.53-4.39 days), SD 4.75 days (95% CI 4.46-5.07 days); 12.6% of case reports indicated presymptomatic transmission. [ABSTRACT FROM AUTHOR]

We used national sentinel surveillance data in China for 2005-2016 to examine the lineage-specific epidemiology of influenza B. Influenza B viruses circulated every year with relatively lower activity than influenza A. B/Yamagata was more frequently detected in adults than in children. [ABSTRACT FROM AUTHOR]

Background: Many serologic studies were done during and after the 2009 influenza pandemic, to estimate the cumulative incidence of influenza A(H1N1)pdm09 virus infections, but there are few comparative estimates of the incidence of influenza A(H3N2) virus infections during epidemics. Methods: We conducted a longitudinal serologic study in Hong Kong. We collected sera annually and tested samples from 2009–13 by HAI against the A/Perth/16/2009(H3N2) virus, and samples from 2013–15 against the A/Victoria/361/2011(H3N2) virus using the hemagglutination inhibition (HAI) assay. We estimated the cumulative incidence of infections based on 4-fold or greater rises in HAI titers in consecutive sera. Results: There were four major H3N2 epidemics: (1) Aug-Oct 2010; (2) Mar-Jun 2012; (3) Jul-Oct 2013; and (4) Jun-Jul 2014. Between 516 and 619 relevant pairs of sera were available for each epidemic. We estimated that 9%, 19%, 7% and 7% of the population were infected in each epidemic, respectively, with higher incidence in children in epidemics 1 and 4. Conclusions: We found that re-infections in each of the four H3N2 epidemics that occurred from 2010 through 2014 were rare. The largest H3N2 epidemic occurred with the lowest level of pre-epidemic immunity. [ABSTRACT FROM AUTHOR]

Annual incidence of scarlet fever in Hong Kong remained elevated after an upsurge in 2011. Incidence increased from 3.3/10,000 children <5 years of age during 2005-2010 to 18.1/10,000 during 2012-2015. Incidence was higher among boys and was 32%-42% lower in the week following school holidays. [ABSTRACT FROM AUTHOR]

Background. Influenza virus infections are associated with a wide spectrum of disease. However, few studies have investigated in detail the epidemiological and virological characteristics of asymptomatic and mild illness with influenza virus infections. Methods. In a community-based study in Hong Kong from 2008 to 2014, we followed up initially healthy individuals who were household contacts of symptomatic persons with laboratory-confirmed influenza, to identify secondary infections. Information from daily symptom diaries was used to classify infections as symptomatic (=2 signs/symptoms, including fever =37.8°C, headache, myalgia, cough, sore throat, runny nose and sputum), paucisymptomatic (1 symptom only), or asymptomatic (none of these symptoms). We compared the patterns of influenza viral shedding between these groups. Results. We identified 235 virologically confirmed secondary cases of influenza virus infection in the household setting, including 31 (13%) paucisymptomatic and 25 (11%) asymptomatic cases. The duration of viral RNA shedding was shorter and declined more rapidly in paucisymptomatic and asymptomatic than in symptomatic cases. The mean levels of influenza viral RNA shedding in asymptomatic and paucisymptomatic cases were approximately 1-2 log10 copies lower than in symptomatic cases. Conclusions. The presence of influenza viral shedding in patients with influenza who have very few or no symptoms reflects their potential for transmitting the virus to close contacts. These findings suggest that further research is needed to investigate the contribution of persons with asymptomatic or clinically mild influenza virus infections to influenza virus transmission in household, institutional, and community settings. [ABSTRACT FROM AUTHOR]

Background: This study was performed to investigate the disease burden of seasonal influenza in adults ≥20 years of age in Korea, based on surveillance data from the Hospital-based Influenza Morbidity & Mortality Surveillance (HIMM) network. Materials and methods: The HIMM network is composed of two surveillance systems: emergency room-based and inpatients-based surveillance. A total of ten university hospitals all over the country are included in the surveillance network. The adult catchment population of the HIMM network was calculated by using the data of each hospital and the database of the Health Insurance Review and Assessment Service (HIRA) of Korea. The incidence rates of laboratory-confirmed medically-attended influenza, laboratory-confirmed influenza-related admission and laboratory-confirmed influenza-related death were calculated based on the catchment population. The socioeconomic burden of influenza was estimated using the human capital approach. Results: During the 2013–2014 influenza season, the calculated adult catchment population of the HIMM network was 1,380,000. The incidence of medically-attended laboratory-confirmed influenza infection was 242.8 per 100,000 adults. The incidence of laboratory-confirmed influenza-related admission was 57.9 per 100,000 adults. The incidence of laboratory-confirmed influenza-related death was 3.1 per 100,000 adults. The total socioeconomic cost of 2013–2014 seasonal influenza in Korean adult population was estimated as 125 million USD (1 USD = 1,100 KRW). Conclusion: The disease burden of 2013–2014 seasonal influenza in Korean adult population is very high and indicates that more active prevention and control policies will be needed to decrease the burden. Additional researches will be needed to assess the burden of seasonal influenza in the Korean child population. [ABSTRACT FROM AUTHOR]

The fourth roundtable meeting of the Global Influenza Initiative (GII) was held in Hong Kong, China, in July 2015. An objective of this meeting was to gain a broader understanding of the epidemiology, surveillance, vaccination policies and programs, and obstacles to vaccination of influenza in the Asia-Pacific region through presentations of data from Australia, Hong Kong, India, Indonesia, Malaysia, New Zealand, the Philippines, Taiwan, Thailand, and Vietnam. As well as a need for improved levels of surveillance in some areas, a range of factors were identified that act as barriers to vaccination in some countries, including differences in climate and geography, logistical challenges, funding, lack of vaccine awareness and education, safety concerns, perceived lack of vaccine effectiveness, and lack of inclusion in national guidelines. From the presentations at the meeting, the GII discussed a number of recommendations for easing the burden of influenza and overcoming the current challenges in the Asia-Pacific region. These recommendations encompass the need to improve surveillance and availability of epidemiological data; the development and publication of national guidelines, where not currently available and/or that are in line with those proposed by the World Health Organization; the requirement for optimal timing of vaccination programs according to local or country-specific epidemiology; and calls for advocacy and government support of vaccination programs in order to improve availability and uptake and coverage. In conclusion, in addition to the varied epidemiology of seasonal influenza across this diverse region, there are a number of logistical and resourcing issues that present a challenge to the development of optimally effective vaccination strategies and that need to be overcome to improve access to and uptake of seasonal influenza vaccines. The GII has developed a number of recommendations to address these challenges and improve the control of influenza. [ABSTRACT FROM AUTHOR]

We compared the epidemiology of hepatitis A and hepatitis E cases in China from 1990-2014 to better inform policy and prevention efforts. The incidence of hepatitis A cases declined dramatically, while hepatitis E incidence increased. During 2004-2014, hepatitis E mortality rates surpassed those of hepatitis A. [ABSTRACT FROM AUTHOR]

Background Population-based serologic studies are a vital tool for understanding the epidemiology of influenza and other respiratory viruses, including the early assessment of the transmissibility and severity of the 2009 influenza pandemic, and Middle East respiratory syndrome coronavirus. However, interpretation of the results of serologic studies has been hampered by the diversity of approaches and the lack of standardized methods and reporting. Objective The objective of the CONSISE ROSES -I statement was to improve the quality and transparency of reporting of influenza seroepidemiologic studies and facilitate the assessment of the validity and generalizability of published results. Methods The ROSES-I statement was developed as an expert consensus of the CONSISE epidemiology and laboratory working groups. The recommendations are presented in the familiar format of a reporting guideline. Because seroepidemiologic studies are a specific type of observational epidemiology study, the ROSES-I statement is built upon the STROBE guidelines. As such, the ROSES-I statement should be seen as an extension of the STROBE guidelines. Results The ROSES -I statement presents 42 items that can be used as a checklist of the information that should be included in the results of published seroepidemiologic studies, and which can also serve as a guide to the items that need to be considered during study design and implementation. Conclusions We hope that the ROSES-I statement will contribute to improving the quality of reporting of seroepidemiologic studies. [ABSTRACT FROM AUTHOR]

Emerging diseases may spread rapidly through dense and large urban contact networks, especially they are transmitted by the airborne route, before new vaccines can be made available. Airborne diseases may spread rapidly as people visit different indoor environments and are in frequent contact with others. We constructed a simple indoor contact model for an ideal city with 7 million people and 3 million indoor spaces, and estimated the probability and duration of contact between any two individuals during one day. To do this, we used data from actual censuses, social behavior surveys, building surveys, and ventilation measurements in Hong Kong to define eight population groups and seven indoor location groups. Our indoor contact model was integrated with an existing epidemiological Susceptible, Exposed, Infectious, and Recovered (SEIR) model to estimate disease spread and with the Wells-Riley equation to calculate local infection risks, resulting in an integrated indoor transmission network model. This model was used to estimate the probability of an infected individual infecting others in the city and to study the disease transmission dynamics. We predicted the infection probability of each sub-population under different ventilation systems in each location type in the case of a hypothetical airborne disease outbreak, which is assumed to have the same natural history and infectiousness as smallpox. We compared the effectiveness of controlling ventilation in each location type with other intervention strategies. We conclude that increasing building ventilation rates using methods such as natural ventilation in classrooms, offices, and homes is a relatively effective strategy for airborne diseases in a large city. [ABSTRACT FROM AUTHOR]

Influenza viruses undergo frequent antigenic changes. As a result, the viruses circulating change within and between seasons, and the composition of the influenza vaccine is updated annually. Thus, estimation of the vaccine's effectiveness is not constant across seasons. In order to provide annual estimates of the influenza vaccine's effectiveness, health departments have increasingly adopted the "test-negative design," using enhanced data from routine surveillance systems. In this design, patients presenting to participating general practitioners with influenza-like illness are swabbed for laboratory testing; those testing positive for influenza virus are defined as cases, and those testing negative form the comparison group. Data on patients' vaccination histories and confounder profiles are also collected. Vaccine effectiveness is estimated from the odds ratio comparing the odds of testing positive for influenza among vaccinated patients and unvaccinated patients, adjusting for confounders. The test-negative design is purported to reduce bias associated with confounding by health-care-seeking behavior and misclassification of cases. In this paper, we use directed acyclic graphs to characterize potential biases in studies of influenza vaccine effectiveness using the test-negative design. We show how studies using this design can avoid or minimize bias and where bias may be introduced with particular study design variations. [ABSTRACT FROM AUTHOR]

The Global Influenza Hospital Surveillance Network (GIHSN) has established a prospective, active surveillance, hospital-based epidemiological study to collect epidemiological and virological data for the Northern and Southern Hemispheres over several consecutive seasons. It focuses exclusively on severe cases of influenza requiring hospitalization. A standard protocol is shared between sites allowing comparison and pooling of results. During the 2014-2015 influenza season, the GIHSN included seven coordinating sites from six countries (St. Petersburg and Moscow, Russian Federation; Prague, Czech Republic; Istanbul, Turkey; Beijing, China; Valencia, Spain; and Rio de Janeiro, Brazil). Here, we present the detailed epidemiological and influenza vaccine effectiveness findings for the Northern Hemisphere 2014-2015 influenza season. [ABSTRACT FROM AUTHOR]

Since March 2013, a novel influenza A(H7N9) virus has caused 3 epidemic waves of human infection in mainland China. We analyzed data from patients with laboratory-confirmed influenza A(H7N9) virus infection to estimate the risks for severe outcomes after hospitalization across the 3 waves. We found that hospitalized patients with confirmed infections in waves 2 and 3 were younger and more likely to be residing in small cities and rural areas than were patients in wave 1; they also had a higher risk for death, after adjustment for age and underlying medical conditions. Risk for death among hospitalized patients during waves 2 and 3 was lower in Jiangxi and Fujian Provinces than in eastern and southern provinces. The variation in risk for death among hospitalized case-patients in different areas across 3 epidemic waves might be associated with differences in case ascertainment, changes in clinical management, or virus genetic diversity. [ABSTRACT FROM AUTHOR]

Background: The Global Influenza Hospital Surveillance Network was established in 2012 to obtain valid epidemiologic data on hospital admissions with influenza-like illness. Here we describe the epidemiology of admissions with influenza within the Northern Hemisphere sites during the 2013/2014 influenza season, identify risk factors for severe outcomes and complications, and assess the impact of different influenza viruses on clinically relevant outcomes in at-risk populations. Methods: Eligible consecutive admissions were screened for inclusion at 19 hospitals in Russia, Turkey, China, and Spain using a prospective, active surveillance approach. Patients that fulfilled a common case definition were enrolled and epidemiological data were collected. Risk factors for hospitalization with laboratory-confirmed influenza were identified by multivariable logistic regression. Findings: 5303 of 9507 consecutive admissions were included in the analysis. Of these, 1086 were influenza positive (534 A(H3N2), 362 A(H1N1), 130 B/Yamagata lineage, 3 B/Victoria lineage, 40 untyped A, and 18 untyped B). The risk of hospitalization with influenza (adjusted odds ratio [95% confidence interval]) was elevated for patients with cardiovascular disease (1.63 [1.33–2.02]), asthma (2.25 [1.67–3.03]), immunosuppression (2.25 [1.23–4.11]), renal disease (2.11 [1.48–3.01]), liver disease (1.94 [1.18–3.19], autoimmune disease (2.97 [1.58–5.59]), and pregnancy (3.84 [2.48–5.94]). Patients without comorbidities accounted for 60% of admissions with influenza. The need for intensive care or in-hospital death was not significantly different between patients with or without influenza. Influenza vaccination was associated with a lower risk of confirmed influenza (adjusted odds ratio = 0.61 [0.48–0.77]). Conclusions: Influenza infection was detected among hospital admissions with and without known risk factors. Pregnancy and underlying comorbidity increased the risk of detecting influenza virus in patients hospitalized with influenza-like illness. Our results support influenza vaccination as a measure for reducing the risk of influenza-associated hospital admission. [ABSTRACT FROM AUTHOR]

Background: Hand, foot, and mouth disease (HFMD) is a common childhood illness caused by serotypes of the Enterovirus A species in the genus Enterovirus of the Picornaviridae family. The disease has had a substantial burden throughout East and Southeast Asia over the past 15 y. China reported 9 million cases of HFMD between 2008 and 2013, with the two serotypes Enterovirus A71 (EV-A71) and Coxsackievirus A16 (CV-A16) being responsible for the majority of these cases. Three recent phase 3 clinical trials showed that inactivated monovalent EV-A71 vaccines manufactured in China were highly efficacious against HFMD associated with EV-A71, but offered no protection against HFMD caused by CV-A16. To better inform vaccination policy, we used mathematical models to evaluate the effect of prospective vaccination against EV-A71-associated HFMD and the potential risk of serotype replacement by CV-A16. We also extended the model to address the co-circulation, and implications for vaccination, of additional non-EV-A71, non-CV-A16 serotypes of enterovirus.Methods and Findings: Weekly reports of HFMD incidence from 31 provinces in Mainland China from 1 January 2009 to 31 December 2013 were used to fit multi-serotype time series susceptible-infected-recovered (TSIR) epidemic models. We obtained good model fit for the two-serotype TSIR with cross-protection, capturing the seasonality and geographic heterogeneity of province-level transmission, with strong correlation between the observed and simulated epidemic series. The national estimate of the basic reproduction number, R0, weighted by provincial population size, was 26.63 for EV-A71 (interquartile range [IQR]: 23.14, 30.40) and 27.13 for CV-A16 (IQR: 23.15, 31.34), with considerable variation between provinces (however, predictions about the overall impact of vaccination were robust to this variation). EV-A71 incidence was projected to decrease monotonically with higher coverage rates of EV-A71 vaccination. Across provinces, CV-A16 incidence in the post-EV-A71-vaccination period remained either comparable to or only slightly increased from levels prior to vaccination. The duration and strength of cross-protection following infection with EV-A71 or CV-A16 was estimated to be 9.95 wk (95% confidence interval [CI]: 3.31, 23.40) in 68% of the population (95% CI: 37%, 96%). Our predictions are limited by the necessarily short and under-sampled time series and the possible circulation of unidentified serotypes, but, nonetheless, sensitivity analyses indicate that our results are robust in predicting that the vaccine should drastically reduce incidence of EV-A71 without a substantial competitive release of CV-A16.Conclusions: The ability of our models to capture the observed epidemic cycles suggests that herd immunity is driving the epidemic dynamics caused by the multiple serotypes of enterovirus. Our results predict that the EV-A71 and CV-A16 serotypes provide a temporary immunizing effect against each other. Achieving high coverage rates of EV-A71 vaccination would be necessary to eliminate the ongoing transmission of EV-A71, but serotype replacement by CV-A16 following EV-A71 vaccination is likely to be transient and minor compared to the corresponding reduction in the burden of EV-A71-associated HFMD. Therefore, a mass EV-A71 vaccination program of infants and young children should provide significant benefits in terms of a reduction in overall HFMD burden. [ABSTRACT FROM AUTHOR]

Background Influenza is a global public health problem. However, severe influenza only recently has been addressed in routine surveillance. Objectives The Global Influenza Hospital Surveillance Network ( GIHSN) was established to study the epidemiology of severe influenza in consecutive seasons in different countries. Our objective is to describe the GIHSN approach and methods. Methods The GIHSN uses prospective active surveillance to identify consecutive influenza admissions in permanent residents of well-defined geographic areas in sites around the world. A core common protocol is followed. After consent, data are collected on patient characteristics and clinical outcomes, respiratory swabs are obtained, and the presence of influenza virus and subtype or lineage is ascertained by polymerase chain reaction. Data are collated and analyzed at the GIHSN coordination center. Results The GIHSN has run its activities for two consecutive influenza seasons, 2012-2013 and 2013-2014, and hospitals in Brazil, China, France, Russian Federation, Turkey, and Spain have been involved in one or both seasons. Consistency on the application of the protocol and heterogeneity for the first season have been addressed in two previous publications. During both seasons, 19 677 eligible admissions were recorded; 11 843 (60%) were included and tested, and 2713 (23%) were positive for influenza: 991 (37%) A(H1N1); 807 (30%) A(H3N2); 583 (21%) B/Yamagata; 56 (2%) B/Victoria and 151 (6%) influenza A; and 125 (5%) influenza B were not characterized. Conclusions The GIHSN is a platform that provides information on severe influenza worldwide, applying a common core protocol and a consistent case definition. [ABSTRACT FROM AUTHOR]