Does climate help modeling COVID-19 risk and to what extent?

Wuhan, China, Bukhari and Jameel [1] reported that 90% of COVID-19 cases were recorded through 22 March 2020 in world areas with colder and less humid late winters and early springs (temperatures of 3–17˚C, and absolute humidity of 4–9 g/m3). As recognized by the authors, these early data were likely to be biased by minimal testing per capita in tropical coun- tries. After over two years into the pandemic, 226 countries across the globe have reported a total of over 500 million confirmed COVID-19 cases [2]. We now have a clearer picture of the global distribution of this disease. There are numerous examples indicating that the cooler sea- son in the northern hemisphere may have favored the spread of the disease, while warmer and more humid weather in late spring and summer has seen a substantial and rapid decline in transmission numbers, once the different containment strategies adopted worldwide are taken into consideration [3, 4]. Prior work on the betacoronavirus genus shows that viruses similar to SARS-CoV-2, such as HCoV-HKU1 and HCoV-OC43, also display seasonal peak trends [5]. The spread of previ- ous coronavirus epidemics, such as SARS-related and the Middle East respiratory syndrome (MERS)-related coronaviruses, have also displayed correlations with seasonal weather changes [6–9]. More specifically, outbreaks of respiratory virus infections are commonly associated with seasonality, with peaks during the winter months. Data from the 1918–19 Flu Pandemic support this correlation. Peak infection/mortality during the 1918–19 Flu Pandemic occurred

in the winter months and waned as solar radiation and absolute humidity increased from late March onward. The resurgence of mortality in the winter of 1919 and its decline with the arrival of spring confirm this trend. These observations are corroborated by US influenza data relative to the last decade where the percentage of patient visits for influenza-like illness consis- tently grows in the winter months. Regression analyses correlating meteorological factors with the spread of SARS-CoV-2 have reported contrasting results. A number of studies have found a negative correlation between temperature and the spread of COVID-19 in China and the US [10–16], Italy [17, 18], Spain [19], Mexico [20], Brazil [21], Latin America and the Caribbean [22], and worldwide [23–27]. By contrast, Xie and Zhu [28] suggest a positive relationship between temperature and the spread of COVID-19 (up to 3˚C), and city-level data from Oslo, Jakarta and, five Brazilian cit- ies show a positive correlation between COVID-19 transmission and higher temperatures, and negative correlation with precipitations [29–31] which typically lead to lower temperatures. Studies on the impact of humidity have also given conflicting results with reports of positive correlation by Jiang et al. [10] for China, and the opposite in studies by Ward et al. [32] for Australia, Qi et al. [11] and Wang et al. [12] for China, Yin et al. [21] in Brazil, and Ju¨ni et al. [33] and Aboura [34] worldwide. Several global analyses and reviews on the impact of climate

on COVID-19 spread [35–39] have also reported conflicting results. Other meteorological factors investigated with reference to COVID-19 transmission include wind and solar radiation. Most studies focusing on the impact of wind speed on the incidence of COVID-19 cases have found a negative correlation [40–42]. Studies focusing on solar radiation in Brazil [43], Australia [44], and worldwide [27, 45, 46] have found that high exposure to solar radiation including UV is negatively correlated with the occurrence of COVID-19 cases. S1 Table provides a summary of the peer-reviewed research on the interrelationship between COVID-19 and meteorological/climatic factors discussed in this section. Overall, there is no conclusive evidence that climate plays a role in the spread of COVID-19 [47–50]. This is probably due to the fact that studies on the impact of climate on COVID-19 transmis- sion have been piecemeal (e.g., limited to country or administrative division-level data), have only taken into account a few climatic parameters, and have not considered the impact of socioeconomic factor, as remarked in Mecenas et al. [4]. The present study addresses these PLOS ONE Does climate help modeling COVID-19 risk and to what extent? PLOS ONE | https://doi.org/10.1371/journal.pone.0273078 September 7, 2022 2 / 27 research, and QNRF encouraged wide dissemination of the study’s results. The study’s results and findings are solely the responsibility of the authors. Competing interests: The authors have declared that no competing interests exist.