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.

arXiv comment5 pages, 5 figures. Updated with improved analysis, leading to higher significance. Analysis with extended dataset added

References in corpus (1)

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