tetano
Editor, Senior Moderator
Biology (Basel)
. 2020 Jun 17;9(6):E132.
doi: 10.3390/biology9060132.
Unreported Cases for Age Dependent COVID-19 Outbreak in Japan
Quentin Griette[SUP] 1 [/SUP], Pierre Magal[SUP] 1 [/SUP], Ousmane Seydi[SUP] 2 [/SUP]
Affiliations
Abstract
We investigate the age structured data for the COVID-19 outbreak in Japan. We consider a mathematical model for the epidemic with unreported infectious patient with and without age structure. In particular, we build a new mathematical model and a new computational method to fit the data by using age classes dependent exponential growth at the early stage of the epidemic. This allows to take into account differences in the response of patients to the disease according to their age. This model also allows for a heterogeneous response of the population to the social distancing measures taken by the local government. We fit this model to the observed data and obtain a snapshot of the effective transmissions occurring inside the population at different times, which indicates where and among whom the disease propagates after the start of public mitigation measures.
Keywords: age-structured data; coronavirus; epidemic mathematical model; isolation; public closings; quarantine; reported and unreported cases.
. 2020 Jun 17;9(6):E132.
doi: 10.3390/biology9060132.
Unreported Cases for Age Dependent COVID-19 Outbreak in Japan
Quentin Griette[SUP] 1 [/SUP], Pierre Magal[SUP] 1 [/SUP], Ousmane Seydi[SUP] 2 [/SUP]
Affiliations
- PMID: 32560572
- DOI: 10.3390/biology9060132
Abstract
We investigate the age structured data for the COVID-19 outbreak in Japan. We consider a mathematical model for the epidemic with unreported infectious patient with and without age structure. In particular, we build a new mathematical model and a new computational method to fit the data by using age classes dependent exponential growth at the early stage of the epidemic. This allows to take into account differences in the response of patients to the disease according to their age. This model also allows for a heterogeneous response of the population to the social distancing measures taken by the local government. We fit this model to the observed data and obtain a snapshot of the effective transmissions occurring inside the population at different times, which indicates where and among whom the disease propagates after the start of public mitigation measures.
Keywords: age-structured data; coronavirus; epidemic mathematical model; isolation; public closings; quarantine; reported and unreported cases.