The Impact of Temperature on the Risk of COVID-19: A Multinational Study

Abstract

The current understanding of ambient temperature and its link to the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unclear. The objective of this study was to explore the environmental and climatic risk factors for SARS-CoV-2. For this study, we analyzed the data at the beginning of the outbreak (from 20 January to 31 March 2020) to avoid the influence of preventive or control measures. We obtained the number of cases and deaths due to SARS-CoV-2, international tourism, population age, universal health coverage, regional factors, the SARS-CoV-2 testing rate, and population density of a country. A total of 154 countries were included in this study. There were high incidence rates and mortality risks in the countries that had an average ambient temperature between 0 and 10 °C. The adjusted incidence rate for temperatures between 0 and 10 °C was 2.91 (95% CI 2.87-2.95). We randomly divided the data into a training set (80% of data) for model derivation and a test set (20% of data) for validation. Using a random forest statistical model, the model had high accuracy for predicting the high epidemic status of a country (ROC = 95.5%, 95% CI 87.9-100.0%) in the test set. Population age, temperature, and international tourism were the most important factors affecting the risk of SARS-CoV-2 in a country. An understanding the determinants of the SARS-CoV-2 outbreak can help to design better strategies for disease control. This study highlights the need to consider thermal effect in the prevention of emerging infectious diseases.

Keywords: SARS-CoV-2; elder; international tourism; temperature; universal health coverage.

Figure 1

Scatterplot showing the relationship between average annual temperature (°C) and (a) incidence (per million) and (b) mortality (per million) of SARS-CoV-2.

Figure 2

The Pearson correlation matrix of the ambient temperature (temperature), population age (age), universal health coverage (UHC), incidence rate (incidence), the mortality rate (mortality), the proportion of international tourism (tourism), and the SARS-CoV-2 testing rate (tests).

Figure 3

The nonlinear regression line of the average temperature and the (a) incidence rate and (b) mortality rate of SARS-CoV-2 in 36 OECD countries.

Figure 4

The incidence rates of four temperature groups.

Figure 5

(a) Important variables for the incidence risk of severe acute respiratory syndrome coronavirus 2 modeled by random forest; (b) the accuracy of the prediction model, which is validated in the test set. The 95% confidence interval of receiver operating characteristic using bootstrap resampling for 2000 replicates was shown.