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Conference Paper: Optimization of the effects of school closures on mitigating influenza epidemics in Hong Kong

TitleOptimization of the effects of school closures on mitigating influenza epidemics in Hong Kong
Authors
Issue Date2019
PublisherElsevier.
Citation
7th International Conference on Infectious Disease Dynamics (Epidemics7), Charleston, South Carolina, USA, 3-6 December 2019  How to Cite?
AbstractBackground: School closures is often implemented as a non-pharmaceutical interventions to increase social-distancing and reduce influenza transmission in a population, although they can cause serious social disruption. In Hong Kong, school closures have been used to mitigate seasonal influenza in 2008, pandemic influenza A(H1N1)pdm09 in 2009, seasonal influenza B in 2018, and most recently seasonal influenza A(H1N1) in 2019. Methods: We analyzed surveillance data on influenza activity in Hong Kong during these 4 seasons. We estimated transmissibility through the effective reproduction number ( ), assuming the serial interval distribution was a Weibull distribution with mean 3.2 days and standard deviation 1.3 days. We examined changes in transmissibility during the school closure periods. Using multivariate regression model and state-space models, we simulated epidemics with and without school closures to quantify the impact of these closures on peak incidence and overall incidence of infections and hospitalizations. Further we simulated possible counterfactual/experimental scenarios to optimize the timing and duration of the school closures. Results: We estimated a 16% (95% CI: 10%, 26%) to 27% (95% CI: 19%, 36%) reduction in transmissibility for four school closure interventions in Hong Kong. The simulated incidence under the counterfactual scenario of no school closures during the implemented school closure, estimating that closures led to a reduction by 4.2% (95% CI 1.5%, 6.7%) to 13.7% (95% CI 8.6%, 17.9%) in the cumulative incidence of infections. There was considerable variation in the impact of closures depending on the timing of implementation (before/around/after peaks). Conclusions: School closures implemented around the peak had higher impact in reduction overall infections compare to after the epidemic peak. Reductions in incidence of infections should have translated to reduced hospitalisations and deaths by a similar fraction, with the caveat that most infections occur in children while most deaths occur in older adults.
DescriptionSession 10 Non-vacc. interv.- no. O10.5
Persistent Identifierhttp://hdl.handle.net/10722/277168

 

DC FieldValueLanguage
dc.contributor.authorAli, ST-
dc.contributor.authorLau, EHY-
dc.contributor.authorFang, J-
dc.contributor.authorLeung, GM-
dc.contributor.authorCowling, BJ-
dc.date.accessioned2019-09-20T08:45:54Z-
dc.date.available2019-09-20T08:45:54Z-
dc.date.issued2019-
dc.identifier.citation7th International Conference on Infectious Disease Dynamics (Epidemics7), Charleston, South Carolina, USA, 3-6 December 2019 -
dc.identifier.urihttp://hdl.handle.net/10722/277168-
dc.descriptionSession 10 Non-vacc. interv.- no. O10.5-
dc.description.abstractBackground: School closures is often implemented as a non-pharmaceutical interventions to increase social-distancing and reduce influenza transmission in a population, although they can cause serious social disruption. In Hong Kong, school closures have been used to mitigate seasonal influenza in 2008, pandemic influenza A(H1N1)pdm09 in 2009, seasonal influenza B in 2018, and most recently seasonal influenza A(H1N1) in 2019. Methods: We analyzed surveillance data on influenza activity in Hong Kong during these 4 seasons. We estimated transmissibility through the effective reproduction number ( ), assuming the serial interval distribution was a Weibull distribution with mean 3.2 days and standard deviation 1.3 days. We examined changes in transmissibility during the school closure periods. Using multivariate regression model and state-space models, we simulated epidemics with and without school closures to quantify the impact of these closures on peak incidence and overall incidence of infections and hospitalizations. Further we simulated possible counterfactual/experimental scenarios to optimize the timing and duration of the school closures. Results: We estimated a 16% (95% CI: 10%, 26%) to 27% (95% CI: 19%, 36%) reduction in transmissibility for four school closure interventions in Hong Kong. The simulated incidence under the counterfactual scenario of no school closures during the implemented school closure, estimating that closures led to a reduction by 4.2% (95% CI 1.5%, 6.7%) to 13.7% (95% CI 8.6%, 17.9%) in the cumulative incidence of infections. There was considerable variation in the impact of closures depending on the timing of implementation (before/around/after peaks). Conclusions: School closures implemented around the peak had higher impact in reduction overall infections compare to after the epidemic peak. Reductions in incidence of infections should have translated to reduced hospitalisations and deaths by a similar fraction, with the caveat that most infections occur in children while most deaths occur in older adults.-
dc.languageeng-
dc.publisherElsevier. -
dc.relation.ispartof7th International Conference on Infectious Disease Dynamics (Epidemics7), 2019-
dc.titleOptimization of the effects of school closures on mitigating influenza epidemics in Hong Kong-
dc.typeConference_Paper-
dc.identifier.emailAli, ST: alist15@hku.hk-
dc.identifier.emailLau, EHY: ehylau@hku.hk-
dc.identifier.emailFang, J: vickyf@hku.hk-
dc.identifier.emailLeung, GM: gmleung@hku.hk-
dc.identifier.emailCowling, BJ: bcowling@hku.hk-
dc.identifier.authorityLau, EHY=rp01349-
dc.identifier.authorityLeung, GM=rp00460-
dc.identifier.authorityCowling, BJ=rp01326-
dc.identifier.hkuros305370-

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