tetano
Editor, Senior Moderator
Bull Math Biol
. 2026 Feb 9;88(3):37.
doi: 10.1007/s11538-026-01600-y.
The Impact of Vacations on the Transmission Dynamics of Influenza A (H1N1)
Zihan Wang[SUP] #[/SUP][SUP] 1 [/SUP], Yu Jin[SUP] #[/SUP][SUP] 2 [/SUP], Xujun Dong[SUP] 1 [/SUP], Yong Zhang[SUP] 3 [/SUP]
Affiliations
The 2009 influenza A (H1N1) epidemic in China provided a unique natural experiment to evaluate school closures, as it overlapped with two school vacations. Utilizing the epidemiological data from this outbreak, our study specifically assesses the impact of holidays and systematically evaluates the efficacy of school-specific prevention measures in curbing influenza transmission. By using the enhanced piecewise linear representation model and calculating the effective reproduction number R[SUB]t[/SUB], we divided the entire pandemic period into six stages. We employed the Susceptible-Exposed-Infective-Removed model with quarantine compartments to align with the prevention and control policy. We quantified the effectiveness of holidays and school-specific prevention strategies using parameter estimation results. Moreover, we explored several comparative scenarios, including holiday cancellations or extensions, to further demonstrate the impact of school closure and policies. The comparison of different transmission phases revealed a 14.0% and 16.5% reduction in the mean of R[SUB]t[/SUB] during the summer vacation and the National Day holiday, respectively. Furthermore, the relaxation of school-specific preventive measures could potentially lead to a doubling of the accumulated case count within several months. In contrast, the extension of holiday periods demonstrated a notable mitigating impact on the epidemic curve. School-specific prevention strategies and school holidays exert a beneficial and significant influence on mitigating the spread of the influenza A (H1N1) epidemic. Our research findings and methods can provide insights for implementing school closure strategies to mitigate similar emerging infectious diseases.
Keywords: Influenza A (H1N1); PLR algorithm; Reproduction number; School closure.
. 2026 Feb 9;88(3):37.
doi: 10.1007/s11538-026-01600-y.
The Impact of Vacations on the Transmission Dynamics of Influenza A (H1N1)
Zihan Wang[SUP] #[/SUP][SUP] 1 [/SUP], Yu Jin[SUP] #[/SUP][SUP] 2 [/SUP], Xujun Dong[SUP] 1 [/SUP], Yong Zhang[SUP] 3 [/SUP]
Affiliations
- PMID: 41661395
- DOI: 10.1007/s11538-026-01600-y
The 2009 influenza A (H1N1) epidemic in China provided a unique natural experiment to evaluate school closures, as it overlapped with two school vacations. Utilizing the epidemiological data from this outbreak, our study specifically assesses the impact of holidays and systematically evaluates the efficacy of school-specific prevention measures in curbing influenza transmission. By using the enhanced piecewise linear representation model and calculating the effective reproduction number R[SUB]t[/SUB], we divided the entire pandemic period into six stages. We employed the Susceptible-Exposed-Infective-Removed model with quarantine compartments to align with the prevention and control policy. We quantified the effectiveness of holidays and school-specific prevention strategies using parameter estimation results. Moreover, we explored several comparative scenarios, including holiday cancellations or extensions, to further demonstrate the impact of school closure and policies. The comparison of different transmission phases revealed a 14.0% and 16.5% reduction in the mean of R[SUB]t[/SUB] during the summer vacation and the National Day holiday, respectively. Furthermore, the relaxation of school-specific preventive measures could potentially lead to a doubling of the accumulated case count within several months. In contrast, the extension of holiday periods demonstrated a notable mitigating impact on the epidemic curve. School-specific prevention strategies and school holidays exert a beneficial and significant influence on mitigating the spread of the influenza A (H1N1) epidemic. Our research findings and methods can provide insights for implementing school closure strategies to mitigate similar emerging infectious diseases.
Keywords: Influenza A (H1N1); PLR algorithm; Reproduction number; School closure.