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

Abstract

The new severe acute respiratory syndrome coronavirus 2 was initially discovered at the end of 2019 in Wuhan City in China and has caused one of the most serious global public health crises. A collection and analysis of studies related to the association between COVID-19 (coronavirus disease 2019) transmission and meteorological factors, such as humidity, is vital and indispensable for disease prevention and control. A comprehensive literature search using various databases, including Web of Science, PubMed, and Chinese National Knowledge Infrastructure, was systematically performed to identify eligible studies from Dec 2019 to Feb 1, 2021. We also established six criteria to screen the literature to obtain high-quality literature with consistent research purposes. This systematic review included a total of 62 publications. The study period ranged from 1 to 8 months, with 6 papers considering incubation, and the lag effect of climate factors on COVID-19 activity being taken into account in 22 studies. After quality assessment, no study was found to have a high risk of bias, 30 studies were scored as having moderate risks of bias, and 32 studies were classified as having low risks of bias. The certainty of evidence was also graded as being low. When considering the existing scientific evidence, higher temperatures may slow the progression of the COVID-19 epidemic. However, during the course of the epidemic, these climate variables alone could not account for most of the variability. Therefore, countries should focus more on health policies while also taking into account the influence of weather. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-021-15929-5.

A data-driven interpretable ensemble framework based on tree models for forecasting the occurrence of COVID-19 in the USA

“…This research was based on the USA, a whole country with a very large geographical area and various weather environments and landforms. Thus, it is difficult for us to find a suitable meteorological index or air pollution index to exactly describe the characteristics of this geographical environment, although meteorological factors and air quality can affect the spread of COVID-19 (Copat et al 2020 ; Zheng et al 2021a , b ). In fact, the occurrence of COVID-19 should be impacted by the spatiotemporal variations especially in large areas.…”

“…XGBoost has also been used in other diseases for disease prediction and risk factor analysis, such as smoking-induced noncommunicable disease (Davagdorj et al 2020 ) and kidney disease (Chen et al 2019 ). The Light Gradient Boosting Machine (LightGBM) model showed better discrimination ability than the traditional model in predicting the all-cause mortality of patients (Zheng et al 2021a , b ), but it has not been used in COVID-19 prediction. To date, none of these three methods has been used to forecast daily cases of COVID-19 in the USA, which is one of the innovations in our research.…”

Epidemiology of COVID-19: What changed in one year?

“…Newly discovered SARS-CoV and SARS-CoV-2 infections also started in winter months. In addition, some reports support the seasonal nature of SARS-CoV-2 [46,47]. However, it cannot be pointed out that climatic parameters such as temperature or humidity alone play a central role during the pandemic [48].…”

Exploring meteorological impacts based on Köppen-Geiger climate classification after reviewing China's response to COVID-19

“…Therefore, this study focused on whether measurable risk variables could be found through global COVID-19 data in order to implement epidemic control more efficiently in China. Previous studies [12] , [13] , [14] , [15] , [16] about the association between COVID-19 transmission and meteorological conditions have been published over the last years. However, diversity of selected regions, data sets, and mathematical methods might contribute to specific results, leading to significantly different from each other [17] , [18] .…”