Independent association of meteorological characteristics with initial spread of Covid-19 in India

Abstract

Whether weather plays a part in the transmissibility of the novel Coronavirus Disease-19 (COVID-19) is still not established. We tested the hypothesis that meteorological factors (air temperature, relative humidity, air pressure, wind speed and rainfall) are independently associated with transmissibility of COVID-19 quantified using the basic reproduction rate (R 0 ). We used publicly available datasets on daily COVID-19 case counts (total n = 108,308), three-hourly meteorological data and community mobility data over a three-month period. Estimated R 0 varied between 1.15 and 1.28. Mean daily air temperature (inversely), wind speed (positively) and countrywide lockdown (inversely) were significantly associated with time dependent R 0 , but the contribution of countrywide lockdown to variability in R 0 was over three times stronger as compared to that of temperature and wind speed combined. Thus, abating temperatures and easing lockdown may concur with increased transmissibility of COVID-19 in India.

Environment and COVID-19 incidence: A critical review

“…Air pressure generally promotes COVID-19 incidence ( Table S2 ). In India, air pressure had a positive correlation with estimates of the time-dependent basic reproduction rate COVID-19 ( Kulkarni et al, 2020 ). In China, a significant positive correlation between air pressure and COVID-19 incidence was reported in a city-level study ( Wu et al, 2021 ).…”

Effects of climate variables on the transmission of COVID-19: a systematic review of 62 ecological studies

“…Geographic factors, such as elevation, are highly associated with the weather type and can indirectly affect air pressure (Zhang et al 2021 ). Furthermore, the sunlight UV radiation dose varies with latitude and season (Tang et al 2021 ), but no statistically significant association was found between any geographic characteristic and the R 0 in India (Kulkarni et al 2021 ). Therefore, the question as to whether latitude and longitude are confounding factors requires further study.…”

“…Malki et al ranked feature importance through a random forest feature selector algorithm and found that temperature and hours of sunlight were important features for infected cases of COVID-19 cases, and climate factors were more important than demographics, such as population, age, and urban percentage, when inspecting mortality (Malki et al 2020 ). Kulkarni et al estimated the proportional reduction in error by using an established approach to quantify the relative contribution of each covariate with the time-dependent R 0 and found that the contributions of air temperature and wind speed to dampening the R 0 estimate were 3–4 times weaker than that in the countrywide lockdown phases 2–4 (Kulkarni et al 2021 ). Hence, governments should take necessary human mobility restrictions and precautionary measures and regard prevention and control of the epidemic as regular.…”

Emergence of SARS-CoV-2 Variants in the World: How Could This Happen?

“…For example, the first large wave of cases in the Northern Hemisphere countries such as China, the US, and Europe during winter and early spring 2020, with a rapid viral expansion and identifying different variants as the months passed. Low temperatures decreased air humidity, and increased air pollution with particulate matter from large cities probably contributed to this process, as well as the survival probabilities of the virus in more temperate climates [114][115][116]. Finally, animal models have been used to evaluate the effect that environmental conditions generate on various tissues, especially the respiratory tract.…”