ArticlePLoS computational biology2016
Revealing the True Incidence of Pandemic A(H1N1)pdm09 Influenza in Finland during the First Two Seasons - An Analysis Based on a Dynamic Transmission Model.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Mathematical Modeling of Influenza Dynamics: Integrating Seasonality and Gradual Waning Immunity.Bulletin of mathematical biology · 2025Article
- The immunopathogenesis of narcolepsy type 1.Nature reviews. Immunology · 2024Review
- Cross-sectional telephone surveys as a tool to study epidemiological factors and monitor seasonal influenza activity in Malta.BMC public health · 2021Article
- Conditional particle filters with diffuse initial distributions.Statistics and computing · 2021Article
- Efficient Real-Time Monitoring of an Emerging Influenza Pandemic: How Feasible?The annals of applied statistics · 2020Article
- An artificially simulated outbreak of a respiratory infectious disease.BMC public health · 2020Article
- Joining and splitting models with Markov melding.Bayesian analysis · 2019Article
- Exploiting routinely collected severe case data to monitor and predict influenza outbreaks.BMC public health · 2018Article
- Evidence Synthesis for Stochastic Epidemic Models.Statistical science : a review journal of the Institute of Mathematical Statistics · 2018Article
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Authors and funding
4 authors.
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Abstract
The threat of the new pandemic influenza A(H1N1)pdm09 imposed a heavy burden on the public health system in Finland in 2009-2010. An extensive vaccination campaign was set up in the middle of the first pandemic season. However, the true number of infected individuals remains uncertain as the surveillance missed a large portion of mild infections. We constructed a transmission model to simulate the spread of influenza in the Finnish population. We used the model to analyse the two first years (2009-2011) of A(H1N1)pdm09 in Finland. Using data from the national surveillance of influenza and data on close person-to-person (social) contacts in the population, we estimated that 6% (90% credible interval 5.1 - 6.7%) of the population was infected with A(H1N1)pdm09 in the first pandemic season (2009/2010) and an additional 3% (2.5 - 3.5%) in the second season (2010/2011). Vaccination had a substantial impact in mitigating the second season. The dynamic approach allowed us to discover how the proportion of detected cases changed over the course of the epidemic. The role of time-varying reproduction number, capturing the effects of weather and changes in behaviour, was important in shaping the epidemic.
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