Abstract
AbstractAs one of the most densely populated countries in the world, Bangladesh have been trying to contain the impact of a pandemic like COVID-19 since March, 2020. Although government announced an array of restricted measures to slow down the diffusion in the beginning of the pandemic, the lockdown has been lifted gradually by reopening all the industries, markets and offices with a notable exception of educational institutes. As the physical geography of Bangladesh is highly variable across the largest delta, the population of different regions and their lifestyle also differ in the country. Thus, to get the real scenario of the current pandemic across Bangladesh, it is essential to analyze the transmission dynamics over the individual districts. In this article, we propose to integrate the Unscented Kalman Filter (UKF) with classic SIRD model to explain the epidemic evolution of individual districts in the country. We show that UKF-SIRD model results in a robust prediction of the transmission dynamics for 1-4 months. Then we apply the robust UKF-SIRD model over different regions in Bangladesh to estimates the course of the epidemic. Our analysis demonstrate that in addition to the densely populated areas, industrial areas and popular tourist spots are in the risk of higher COVID-19 transmission. In the light of these outcomes, we provide a set of suggestions to contain the pandemic in Bangladesh. All the data and relevant codebase is available at https://mjonyh.github.io.HighlightsWe integrate the UKF with classic SIRD model for the better estimation of the COVID-19 diffusion of 64 districts in Bangladesh.Nationwide analysis show the strong correlation between population density and the number of COVID-19 positive cases in the country.Industrial zones and popular tourists spots are at greater risk of spreading the Coronavirus.With the better assessment of the COVID-19 cases dynamics, the Government will find effective policies to contain the current pandemic.
Publisher
Cold Spring Harbor Laboratory
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