Abstract
SARS-CoV-2 is a new pathogen responsible for the coronavirus disease 2019 (COVID-19) outbreak. Southeast Asia was the first region to be affected outside China, and although COVID-19 cases have been reported in all countries of Southeast Asia, both the policies and epidemic trajectories differ substantially, potentially due to marked differences in social distancing measures that have been implemented by governments in the region. This paper studies the across-country relationships between social distancing and each population’s response to policy, the subsequent effects of these responses to the transmissibility and epidemic trajectories of SARS-CoV-2. The analysis couples COVID-19 case counts with real-time mobility data across Southeast Asia to estimate the effects of host population response to social distancing policy and the subsequent effects on the transmissibility and epidemic trajectories of SARS-CoV-2. A novel inference strategy for the time-varying reproduction number is developed to allow explicit inference of the effects of social distancing on the transmissibility of SARS-CoV-2 through a regression structure. This framework replicates the observed epidemic trajectories across most Southeast Asian countries, provides estimates of the effects of social distancing on the transmissibility of disease and can simulate epidemic histories conditional on changes in the degree of intervention scenarios and compliance within Southeast Asia.
Highlights
The politically and economically diverse region of Southeast Asia was the first region outside China to be affected by the coronavirus disease 2019 (COVID19) pandemic, with early importations from Wuhan into Bangkok [1] and Singapore [2]
It is able to simulate alternative epidemic histories conditional on changes in the degree of intervention scenarios and/or compliance within each population. Using this new estimation methodology, we found significant between-country variations in the host population response to social distancing policy, variations in the effects of social distancing policy on the time-varying reproduction number and overall epidemic trends and lastly differences in the ability for even greater degrees of intervention within each country to stem the spread of SARS-CoV-2
To prevent collinearities obfuscating the signal, we focus on the change in time spent at home, using this feature in the model to estimate the effect of time-varying degrees of social distancing on the infection potential and time-varying reproduction number of SARS-CoV-2 across countries
Summary
The politically and economically diverse region of Southeast Asia was the first region outside China to be affected by the coronavirus disease 2019 (COVID19) pandemic, with early importations from Wuhan into Bangkok [1] and Singapore [2]. We use publicly available reported COVID-19 case counts across nine Southeast Asian countries together with Google mobility data to infer the response of populations to social distancing policy and its subsequent effects on the transmissibility of SARS-CoV-2 and epidemic trajectories of COVID-19. It is able to simulate alternative epidemic histories conditional on changes in the degree of intervention scenarios and/or compliance within each population Using this new estimation methodology, we found significant between-country variations in the host population response to social distancing policy, variations in the effects of social distancing policy on the time-varying reproduction number and overall epidemic trends and lastly differences in the ability for even greater degrees of intervention within each country to stem the spread of SARS-CoV-2
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
