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. 2021 Jan 7:149:e16.
doi: 10.1017/S0950268821000029.

Impact of population density and weather on COVID-19 pandemic and SARS-CoV-2 mutation frequency in Bangladesh

Nadim Sharif  1 , Shuvra Kanti Dey  1
Affiliations

Impact of population density and weather on COVID-19 pandemic and SARS-CoV-2 mutation frequency in Bangladesh

Nadim Sharif et al. Epidemiol Infect. .

Abstract

Coronavirus disease-2019 (COVID-19) has caused the recent pandemic worldwide. Research studies are focused on various factors affecting the pandemic to find effective vaccine or therapeutics against COVID-19. Environmental factors are the important regulators of COVID-19 pandemic. This study aims to determine the impact of weather on the COVID-19 cases, fatalities and frequency of mutations in Bangladesh. The impacts were determined on 1, 7 and 14 days of the case. The study was conducted based on Spearman's correlation coefficients. The highest correlation was found between population density and cases (rs = 0.712). Among metrological parameters, average temperature had the strongest correlation (rs = -0.675) with the cases. About 82% of Bangladeshi isolates had D614G at spike protein. Both temperature and UV index had strong effects on the frequency of mutations. Among host factors, coinfection is highly associated with frequency of different mutations. This study will give a complete picture of the effects of metrological parameters on COVID-19 cases, fatalities and mutation frequency that will help the authorities to take proper decisions.

Keywords: Bangladesh; COVID-19; UV index; mutation frequency; population density; temperature.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1.
Fig. 1.
Total COVID-19 cases and fatalities in Bangladesh.
Fig. 2.
Fig. 2.
Map of the distribution of COVID-19 cases in eight different cities in Bangladesh
Fig. 3.
Fig. 3.
Weekly distribution of minimum temperature, maximum temperature and average temperature in Dhaka in Bangladesh.
Fig. 4.
Fig. 4.
Average relative humidity of the cities per week in Bangladesh.
Fig. 5.
Fig. 5.
Weekly distribution of average UV index in the cities.
Fig. 6.
Fig. 6.
Weekly distribution of average wind speed in the cities.
Fig. 7.
Fig. 7.
Frequency of mutations at different site in the Bangladeshi novel coronavirus genome.
Fig. 8.
Fig. 8.
Age and gender distribution of the COVID-19 patients in Bangladesh.
See this image and copyright information in PMC

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