tetano
Editor, Senior Moderator
J Theor Biol. 2019 Nov 4:110070. doi: 10.1016/j.jtbi.2019.110070. [Epub ahead of print] [h=1]Mechanistic Modelling of Multiple Waves in an Influenza Epidemic or Pandemic.[/h]
Xu B[SUP]1[/SUP], Cai J[SUP]2[/SUP], He D[SUP]3[/SUP], Chowell G[SUP]4[/SUP], Xu B[SUP]5[/SUP].
[h=3]Author information[/h] 1 Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Joint Center for Global Change Studies, Beijing 100875, China. Electronic address: xu-b15@mails.tsinghua.edu.cn. 2 Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Joint Center for Global Change Studies, Beijing 100875, China. Electronic address: cai-j12@mails.tsinghua.edu.cn. 3 Department of Applied Mathematics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (SAR), China. Electronic address: daihai.he@polyu.edu.hk. 4 Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia 30303, United States; Division of Inwternational Epidemiology and Population Studies, Fogarty International Center, National Institute of Health, Bethesda, Maryland 20892, United States. Electronic address: gchowell@gsu.edu. 5 Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Joint Center for Global Change Studies, Beijing 100875, China. Electronic address: bingxu@tsinghua.edu.cn.
[h=3]Abstract[/h] Multiple-wave outbreaks have been documented for influenza pandemics particularly in the temperate zone, and occasionally for seasonal influenza epidemics in the tropical zone. The mechanisms shaping multiple-wave influenza outbreaks are diverse but are yet to be summarized in a systematic fashion. For this purpose, we described 12 distinct mechanistic models, among which five models were proposed for the first time, that support two waves of infection in a single influenza season, and classified them into five categories according to heterogeneities in host, pathogen, space, time and their combinations, respectively. To quantify the number of infection waves, we proposed three metrics that provide robust and intuitive results for real epidemics. Further, we performed sensitivity analyses on key parameters in each model and found that reducing the basic reproduction number or the transmission rate, limiting the addition of susceptible people who are to get the primary infection to infected areas, and limiting the probability of replenishment of people who are to be reinfected in the short term, could decrease the number of infection waves and clinical attack rate. Finally, we introduced a modelling framework to infer the mechanisms driving two-wave outbreaks. A better understanding of two-wave mechanisms could guide public health authorities to develop and implement preparedness plans and deploy control strategies.
Copyright ? 2019. Published by Elsevier Ltd.
[h=4]KEYWORDS:[/h] Influenza outbreak; Mechanistic model; Modelling framework; Multiple waves; Number of infection waves
PMID: 31697940 DOI: 10.1016/j.jtbi.2019.110070
Xu B[SUP]1[/SUP], Cai J[SUP]2[/SUP], He D[SUP]3[/SUP], Chowell G[SUP]4[/SUP], Xu B[SUP]5[/SUP].
[h=3]Author information[/h] 1 Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Joint Center for Global Change Studies, Beijing 100875, China. Electronic address: xu-b15@mails.tsinghua.edu.cn. 2 Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Joint Center for Global Change Studies, Beijing 100875, China. Electronic address: cai-j12@mails.tsinghua.edu.cn. 3 Department of Applied Mathematics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (SAR), China. Electronic address: daihai.he@polyu.edu.hk. 4 Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia 30303, United States; Division of Inwternational Epidemiology and Population Studies, Fogarty International Center, National Institute of Health, Bethesda, Maryland 20892, United States. Electronic address: gchowell@gsu.edu. 5 Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Joint Center for Global Change Studies, Beijing 100875, China. Electronic address: bingxu@tsinghua.edu.cn.
[h=3]Abstract[/h] Multiple-wave outbreaks have been documented for influenza pandemics particularly in the temperate zone, and occasionally for seasonal influenza epidemics in the tropical zone. The mechanisms shaping multiple-wave influenza outbreaks are diverse but are yet to be summarized in a systematic fashion. For this purpose, we described 12 distinct mechanistic models, among which five models were proposed for the first time, that support two waves of infection in a single influenza season, and classified them into five categories according to heterogeneities in host, pathogen, space, time and their combinations, respectively. To quantify the number of infection waves, we proposed three metrics that provide robust and intuitive results for real epidemics. Further, we performed sensitivity analyses on key parameters in each model and found that reducing the basic reproduction number or the transmission rate, limiting the addition of susceptible people who are to get the primary infection to infected areas, and limiting the probability of replenishment of people who are to be reinfected in the short term, could decrease the number of infection waves and clinical attack rate. Finally, we introduced a modelling framework to infer the mechanisms driving two-wave outbreaks. A better understanding of two-wave mechanisms could guide public health authorities to develop and implement preparedness plans and deploy control strategies.
Copyright ? 2019. Published by Elsevier Ltd.
[h=4]KEYWORDS:[/h] Influenza outbreak; Mechanistic model; Modelling framework; Multiple waves; Number of infection waves
PMID: 31697940 DOI: 10.1016/j.jtbi.2019.110070