Abstract

Significance. There are many studies on the influence of climate on the spread of coronavirus, however, the effect of low temperatures on the development of the COVID-19 epidemic is yet to be determined. Purpose: to evaluate impact of low temperatures on the spread of the new coronavirus infection. Material and methods. Dynamics in newly detected cases of SARS-CoV-2 infection for the period from November 1 to December 31 in 85 regions of the Russian Federation has been analyzed. Based on discrepancies in the projected course of the COVID-19 epidemic according to data for the periods from November 1 - December 7 and November 1 - December 20, groups of the regions have been formed. Mean values of risk factors for SARS-CoV-2 have been compared across these groups. The extrapolation method was used for forecasting with analytical alignment of the temporal series. The procedure has then been repeated for the periods from November 1 - December 20 and December 16-31. Results. In the second part of December, deterioration of the epidemic situation was projected in two groups, while improvement of the epidemic situation was projected in two groups, and an unchanged level of detection of new cases of infection was projected in one group. The average monthly temperatures in December in the groups with the projected rise in the number of infections were significantly higher than in other groups. The tendency towards improvements in the forecast of the epidemic situation as the risk factors change is disrupted by the group with stabilization in the number of cases after the increasing trend. In this group, the average monthly temperature (-6.4°C [-7.8 — -5.0]) is higher than in the group with the unchanged epidemic situation (-8.5°C [-9.4 — -7.5]), where the influence of low temperatures was likely to manifest by the beginning of December. In the group with the decreased number of cases, the average temperature was (-18.3°C [-20.8 — -15.9]. With changes in trends in the third part of December, significant differences between subgroups were registered only in terms of the mean monthly temperature with the rest of the risk factors being identified in some cases only. In general, no correlation between the COVID-19 infection and the average monthly temperature was identified in the country. There is a correlation between the prevalence and the number of doctors (r = 0.33) and population density (r = 0.37), but the trend towards better forecasts in the regions does not agree with the last risk factor. Conclusion. The study results support the hypothesis that low air temperatures reduce the SARS-COV-2 transmission. Their influence is manifested in the regions with a fairly high level of the infection prevalence.

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