Temperature dependence of COVID-19 transmission

Abstract

The recent coronavirus pandemic follows in its early stages an almost exponential growth, with the number of cases quite well fit in time by $N(t)\propto e^{\alpha t}$, in many countries. We analyze the rate $\alpha$ for each country, starting from a threshold of 30 total cases and using the next 12 days, capturing thus the early growth homogeneously. We look for a link between $\alpha$ and the average temperature $T$ of each country, in the month of the epidemic growth. We analyze a {\it base} set of 42 countries, which developed the epidemic earlier, an {\it intermediate} set of 88 countries and an {\it extended} set of 125 countries, which developed the epidemic more recently. Applying a linear fit $\alpha (T)$, we find increasing evidence for a decreasing $\alpha$ as a function of $T$, at $99.66\%$C.L., $99.86\%$C.L. and $99.99995\%$ C.L. ($p$-value $5\cdot 10^{-7}$, or 5$\sigma$ detection) in the {\it base}, {\it intermediate} and {\it extended} dataset, respectively. The doubling time is expected to increase by $40\%\sim 50\%$, going from $5^{\circ }$ C to $25^{\circ }$ C. In the {\it base} set, going beyond a linear model, a peak at $(7.7\pm 3.6{)}^{\circ }C$ seems to be present, but its evidence disappears for the larger datasets. We also analyzed a possible bias: poor countries, often located in warm regions, might have less intense testing. By excluding countries below a given GDP per capita, we find that our conclusions are only slightly affected and only for the {\it extended} dataset. The significance remains high, with a $p$-value of $10^{-3}-10^{-4}$ or less. Our findings give hope that, for northern hemisphere countries, the growth rate should significantly decrease as a result of both warmer weather and lockdown policies. In general the propagation should be hopefully stopped by strong lockdown, testing and tracking policies, before the arrival of the cold season.

5 pages, 5 figures. Updated with improved analysis, leading to higher significance. Analysis with extended dataset added

References in corpus (1)

• Inferring change points in the COVID-19 spreading reveals the effectiveness of interventions

Cited by in corpus (8)

• Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts
• Neural Networks Fail to Learn Periodic Functions and How to Fix It
• Investigation of superspreading COVID-19 outbreaks events in meat and poultry processing plants in Germany: A cross-sectional study
• PM${}_{2.5}$ as a major predictor of COVID-19 basic reproduction number in the USA
• Effect of Mitigation Measures on the Spreading of COVID-19 in Hard-Hit States
• Correlations Between COVID-19 and Dengue
• Inferring the main drivers of SARS-CoV-2 global transmissibility by feature selection methods
• Weather impact on daily cases of COVID-19 in Saudi Arabia using machine learning