ABSTRACT
We model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.
Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Models, Biological , Pandemics , Pneumonia, Viral/epidemiology , Asymptomatic Infections/epidemiology , Basic Reproduction Number/statistics & numerical data , COVID-19 , China/epidemiology , Computer Simulation , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Epidemics/prevention & control , Epidemics/statistics & numerical data , Humans , Mathematical Concepts , Pandemics/prevention & control , Pandemics/statistics & numerical data , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , Quarantine/statistics & numerical data , SARS-CoV-2 , Time FactorsABSTRACT
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.
ABSTRACT
We develop a mathematical model to provide epidemic predictions for the COVID-19 epidemic in Wuhan, China. We use reported case data up to 31 January 2020 from the Chinese Center for Disease Control and Prevention and the Wuhan Municipal Health Commission to parameterize the model. From the parameterized model, we identify the number of unreported cases. We then use the model to project the epidemic forward with varying levels of public health interventions. The model predictions emphasize the importance of major public health interventions in controlling COVID-19 epidemics.