Abstract Weather variables are one of the crucial factors affecting respiratory infectious diseases; however, the effect of weather variables on the coronavirus disease 2019 (COVID-19) is still inconclusive and varies in different regions. The present study investigated the effects of weather variables (maximum temperature, MT; relative humidity, RH; wind speed, WS; precipitation, PR; and dew point, DP) on daily infection and death cases in three lockdown phases in Asia as of November 1, 2020. Generalized additive lag model was used to analyze the risk associated with weather variables, with confounders like median age of the national population, population density, country and lockdown phases. Our findings revealed that during lockdown phases all five weather variables show association with daily confirmed,?and death cases. On the other hand, PR (pre-lockdown phase) and DP (lockdown phase) showed positive association with both daily?confirmed? and death cases. Throughout the three lockdown phases MT, RH and PR showed strong positive associations with daily confimed/death cases.?A lag period of 0–4-days possess higher risk of infection and death due to the varied ratios of different weather variables. The?relative risk indicated that the infection and mortality risk was higher in?India as compared to the rest of the countries. Here, unique combination of weather variables together with higher population density makes this region as one of the hotspots for COVID-19. This shows that the COVID-19 pandemic may be suppressed or enhanced with combination of different weather conditions together with factors like population density and median age of the country, which shall be useful for better implementation of health policies and further preparedness in Asia.
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