ArticlePLoS medicine2011
Estimating infection attack rates and severity in real time during an influenza pandemic: analysis of serial cross-sectional serologic surveillance data.
Article in PLoS medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 4 of them syntheses that pooled it.
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Who cites it
49 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- A systematic review of early modelling studies of Ebola virus disease in West Africa.Epidemiology and infection · 2017Pooled it
- CONSISE statement on the reporting of Seroepidemiologic Studies for influenza (ROSES-I statement): an extension of the STROBE statement.Influenza and other respiratory viruses · 2017Guideline
- Case fatality risk of influenza A (H1N1pdm09): a systematic review.Epidemiology (Cambridge, Mass.) · 2013Pooled it
- Estimating age-specific cumulative incidence for the 2009 influenza pandemic: a meta-analysis of A(H1N1)pdm09 serological studies from 19 countries.Influenza and other respiratory viruses · 2013Pooled it
- Quantifying Protection Against Influenza Virus Infection Measured by Hemagglutination-inhibition Assays in Vaccine Trials.Epidemiology (Cambridge, Mass.) · 2016Trial
- Inferring influenza infection attack rate from seroprevalence data.PLoS pathogens · 2014Trial
- Undetected circulation of monkeypox virus in Portugal: Evidence for a 50-day gap before first detection.Global epidemiology · 2026Article
- Reconstructed influenza A/H3N2 infection histories reveal variation in incidence and antibody dynamics over the life course.PLoS biology · 2024Article
- Reconstructed influenza A/H3N2 infection histories reveal variation in incidence and antibody dynamics over the life course.medRxiv : the preprint server for health sciences · 2024Article
- Avian Influenza A(H5N1) Neuraminidase Inhibition Antibodies in Healthy Adults after Exposure to Influenza A(H1N1)pdm09.Emerging infectious diseases · 2024Article
- Human Influenza Epidemiology.Cold Spring Harbor perspectives in medicine · 2021Review
- Effect of Adjustment for Case Misclassification and Infection Date Uncertainty on Estimates of COVID-19 Effective Reproduction Number.Epidemiology (Cambridge, Mass.) · 2021Article
- Real-time tracking and prediction of COVID-19 infection using digital proxies of population mobility and mixing.Nature communications · 2021Article
- Nowcasting (Short-Term Forecasting) of Influenza Epidemics in Local Settings, Sweden, 2008-2019.Emerging infectious diseases · 2020Article
- A Comparison of Case Fatality Risk of COVID-19 between Singapore and Japan.Journal of clinical medicine · 2020Article
- Seroepidemiologic Study Designs for Determining SARS-COV-2 Transmission and Immunity.Emerging infectious diseases · 2020Article
- An open source tool to infer epidemiological and immunological dynamics from serological data: serosolver.PLoS computational biology · 2020Article
- Real-time estimation of the influenza-associated excess mortality in Hong Kong.Epidemiology and infection · 2019Article
- Incidence of influenza A(H3N2) virus infections in Hong Kong in a longitudinal sero-epidemiological study, 2009-2015.PloS one · 2018Article
- Rethinking thresholds for serological evidence of influenza virus infection.Influenza and other respiratory viruses · 2017Article
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Authors and funding
15 authors.
Funding
Abstract
backgroundIn an emerging influenza pandemic, estimating severity (the probability of a severe outcome, such as hospitalization, if infected) is a public health priority. As many influenza infections are subclinical, sero-surveillance is needed to allow reliable real-time estimates of infection attack rate (IAR) and severity. METHODS AND
findingsWe tested 14,766 sera collected during the first wave of the 2009 pandemic in Hong Kong using viral microneutralization. We estimated IAR and infection-hospitalization probability (IHP) from the serial cross-sectional serologic data and hospitalization data. Had our serologic data been available weekly in real time, we would have obtained reliable IHP estimates 1 wk after, 1-2 wk before, and 3 wk after epidemic peak for individuals aged 5-14 y, 15-29 y, and 30-59 y. The ratio of IAR to pre-existing seroprevalence, which decreased with age, was a major determinant for the timeliness of reliable estimates. If we began sero-surveillance 3 wk after community transmission was confirmed, with 150, 350, and 500 specimens per week for individuals aged 5-14 y, 15-19 y, and 20-29 y, respectively, we would have obtained reliable IHP estimates for these age groups 4 wk before the peak. For 30-59 y olds, even 800 specimens per week would not have generated reliable estimates until the peak because the ratio of IAR to pre-existing seroprevalence for this age group was low. The performance of serial cross-sectional sero-surveillance substantially deteriorates if test specificity is not near 100% or pre-existing seroprevalence is not near zero. These potential limitations could be mitigated by choosing a higher titer cutoff for seropositivity. If the epidemic doubling time is longer than 6 d, then serial cross-sectional sero-surveillance with 300 specimens per week would yield reliable estimates when IAR reaches around 6%-10%.
conclusionsSerial cross-sectional serologic data together with clinical surveillance data can allow reliable real-time estimates of IAR and severity in an emerging pandemic. Sero-surveillance for pandemics should be considered.
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