ArticleEpidemiology and infection2015
Modelling the epidemic spread of an H1N1 influenza outbreak in a rural university town.
Article in Epidemiology and infection, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 19 citations in OpenAlex.
- Estimating transmission parameters from stochastic epidemic models using survival analysis techniques.Statistical methods in medical research · 2026Article
- Impact of Shifting University Policies During the COVID-19 Pandemic on Self-Reported Employee Social Networks.medRxiv : the preprint server for health sciences · 2024Article
- Use of the Hayami diffusive wave equation to model the relationship infected-recoveries-deaths of Covid-19 pandemic.Epidemiology and infection · 2021Article
- Global dynamics and control strategies of an epidemic model having logistic growth, non-monotone incidence with the impact of limited hospital beds.Nonlinear dynamics · 2021Article
- Forecasting COVID-19-Associated Hospitalizations under Different Levels of Social Distancing in Lombardy and Emilia-Romagna, Northern Italy: Results from an Extended SEIR Compartmental Model.Journal of clinical medicine · 2020Article
- Survival dynamical systems: individual-level survival analysis from population-level epidemic models.Interface focus · 2020Article
- Modeling Zika Virus Transmission Dynamics: Parameter Estimates, Disease Characteristics, and Prevention.Scientific reports · 2019Article
- Pandemic 2009 H1N1 influenza in two settings in a small community: the workplace and the university campus.Epidemiology and infection · 2015Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Knowledge of mechanisms of infection in vulnerable populations is needed in order to prepare for future outbreaks. Here, using a unique dataset collected during a 2009 outbreak of influenza A(H1N1)pdm09 in a university town, we evaluated mechanisms of infection and identified that an epidemiological model containing partial protection of susceptibles best describes H1N1 dynamics in a rural university environment. We found that the protected group was over 14 times less susceptible to H1N1 infection than unprotected susceptibles. Our estimates show that the basic reproductive rate, R 0, was 5·96 (95% confidence interval 5·83-6·61), and, importantly, R 0 could be decreased to below 1 and similar epidemics could be avoided by increasing the proportion of the initial protected group. Moreover, several weeks into the epidemic, this protected group generated more new infections than the unprotected susceptible group, and thus, such protected groups should be taken into account while studying influenza epidemics in similar settings.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.