Influence of temperature, and of relative and absolute humidity on COVID-19 incidence in England - A multi-city time-series study

Abstract

Background SARS-CoV-2 caused the COVID-19 pandemic in 2020. The virus is likely to show seasonal dynamics in European climates as this is often the case for respiratory viruses and for coronaviruses. Analysing the association with meteorological factors will be helpful to anticipate how cases will develop with changing seasons. Methods Routinely measured ambient daily mean temperature, absolute humidity, and relative humidity were the explanatory variables. Test-positive COVID-19 cases represented the outcome variable. The analysis included 54 English cities. A two-stage meta-regression was conducted using a quasi-Poisson-distributed generalised linear modelling approach at first stage including distributed lag non-linear model elements. Thereby, the authors investigate the explanatory variables’ non-linear effects as well as the non-linear effects across lags. Results This study found a non-linear association of COVID-19 cases with temperature. At 11.9°C there was 1.62-times (95%-CI: 1.44; 1.81) the risk of cases compared to the temperature-level with the smallest risk (21.8°C). Absolute humidity exhibited a 1.61-times (95%-CI: 1.41; 1.83) elevated risk at 6.6 g/m 3 compared to the centering at 15.1 g/m 3 . When adjusting for temperature RH shows a 1.41-fold increase in risk of COVID-19 incidence (95%-CI: 1.09; 1.81) at 60.7% in respect to 87.6%. Conclusion The analysis suggests that in England meteorological variables likely influence COVID-19 case development. These results reinforce the importance of non-pharmaceutical interventions (e.g., social distancing and mask use) during all seasons, especially with cold and dry weather conditions.

Prominent Spatiotemporal Waves of COVID-19 Incidence in the United States: Implications for Causality, Forecasting, and Control

“…Paradoxically, increased epidemic intensity in wave 2 first emerged in states in southern latitudes and with low altitudes, in the hottest states in the hottest time of the year. Studies identified the range of 5-15°C as a significant temperature zone for high incidence of COVID-19 cases (14)(15)(16). Outside this temperature range, COVID-19's temperature response becomes unclear (14,16,17).…”

Exposure-lag Response of Air Temperature on COVID-19 Incidence in Italy

“…In the second stage, coefficients and covariance matrices from the first stage models were pooled using meta-analysis. This approach controls for city-level confounders, relaxes the strong assumption that the exposure-1 lag response is not city-specific and has been deployed in a recent similar study (Nottmeyer and Sera 2021).…”

“…, denotes a crossbasis for temperature on day t considering lag l, constructed using natural splines with 3 prespecified degrees of freedom for both the exposure and lag bases (Nottmeyer and Sera 2021 found that larger values for the degrees of freedom incurred a loss of precision for the estimates) with 1 the corresponding vector of coefficients. We considered lag range 0 through 10 days inclusive as in recent studies (Lauer et al, 2020;Nottmeyer and Sera 2021). dow denotes the day of week fitted as dummy variables, with the corresponding vector of coefficients.…”

“…Parameters were estimated using quasi-restricted maximum likelihood (REML) 4 (McCullagh and Nelder, 1989). We performed a sensitivity analysis by altering the lag period to 0-5 and 0-15 days respectively as in Nottmeyer and Sera (2021).…”

Does Environment has any role in recovery from COVID-19 pandemic? A case study from India.

“…A few researchers have already exhorted about signi cant association of environmental parameters to COVID-19 transmission (Azuma et al, 2020;Bherwani et al, 2020;Eslami and Jalili, 2020;Gupta and Pradhan, 2020a;Kifer et al, 2021;Rume and Islam, 2020;Saadat et al, 2020;Shakil et al, 2020). There are also a few global as well as regional studies that had been carried out in the context of China, USA, England, Germany, Spain, Italy, Indonesia, Iran, Pakistan, Bangladesh, India, and found signi cant correlation between weather parameters and the COVID-19 cases (Ahmadi et al, 2020;Fadli et al, 2020;Ficetola and Rubolini, 2021;Gupta and Pradhan, 2020b;Liu et al, 2020b;Ma et al, 2020;Mehmood et al, 2021;Nottmeyer and Sera, 2021;Qi et al, 2020;Tosepu et al, 2020). Studies carried out by Bochenek et al, 2021;Borah et al, 2020;Briz-Redón and Serrano-Aroca, 2020;Emediegwu, 2021;Guo et al, 2021;Mecenas et al, 2020;Runkle et al, 2020;Şahin, 2020;Sil and Kumar, 2020 suggested that warm and humid condition days incubation period, lower the number of cases (Şahin, 2020).…”