A friend of mine recently quipped that everyone seems to act like probability can be assigned two values 0 or 1. The same sort of logic seems to apply when it comes to talking about the environmental parameters which might affect the progress of COVID-19, such as temperature, humidity, and density. Many people seem to strenuously want to deny there is any plausible evidence that COVID-19 might exhibit seasonality. There is a fair amount of correlational work which suggests that there is an environmental factor shaping the spread and depth of COVID-19. And, we know three out of the four previous coronaviruses exhibit seasonality.
Well, I noticed this note on medRxiv today, Stability of SARS-CoV-2 in different environmental conditions. It’s a very short write-up of their experimental results. I don’t really know much about virology so I can’t evaluate it well, but you can see the figure above. As you increase the temperature the virus titer seems to drop much faster. At a very high temperature of 70 Celsius, they basically can’t detect anything after 1 minute.
Here is one of the better correlational analyses, using some sophisticated techniques, Causal empirical estimates suggest COVID-19 transmission rates are highly seasonal:
Nearly every country is now combating the 2019 novel coronavirus (COVID-19). It has been hypothesized that if COVID-19 exhibits seasonality, changing temperatures in the coming months will shift transmission patterns around the world. Such projections, however, require an estimate of the relationship between COVID-19 and temperature at a global scale, and one that isolates the role of temperature from confounding factors, such as public health capacity. This paper provides the first plausibly causal estimates of the relationship between COVID-19 transmission and local temperature using a global sample comprising of 166,686 confirmed new COVID-19 cases from 134 countries from January 22, 2020 to March 15, 2020. We find robust statistical evidence that a 1◦C increase in local temperature reduces transmission by 13% [-21%, -4%, 95%CI]. In contrast, we do not find that specific humidity or precipitation influence transmission. Our statistical approach separates effects of climate variation on COVID-19 transmission from other potentially correlated factors, such as differences in public health responses across countries and heterogeneous population densities. Using constructions of expected seasonal temperatures, we project that changing temperatures between March 2020 and July 2020 will cause COVID-19 transmission to fall by 43% on average for Northern Hemisphere countries and to rise by 71% on average for Southern Hemisphere countries. However, these patterns reverse as the boreal winter approaches, with seasonal temperatures in January 2021 increasing average COVID-19 transmission by 59% relative to March 2020 in northern countries and lowering transmission by 2% in southern countries. These findings suggest that Southern Hemisphere countries should expect greater transmission in the coming months. Moreover, Northern Hemisphere countries face a crucial window of opportunity: if contagion-containing policy interventions can dramatically reduce COVID-19 cases with the aid of the approaching warmer months, it may be possible to avoid a second wave of COVID-19 next winter.
To be clear. Does this mean weather/climate determine whether COVID-19 will spread or not? No. Rather, I think that weather/climate has some effect on the margin on the R0. I am not sure of the exact reason, but if the virus degrades much faster in hot climates, that could be one explanation of why spreading is more limited. It also does not seem to be the case that tropical countries are going to avoid mass healthcare crises. Rather, as these countries formulate policies to decrease R0, it may not be as long of a haul.
I believe that many are worried that if there is some relationship between temperature and COVID-19, people will think they are safe in a particular climate. The way to deal with this is not to ratchet up skepticism to an inordinately high extent. Rather, it is to be more clear and careful in how one presents the data.
Similarly, I think density has some impact. But, South Korea, Japan, and Taiwan show that density does not seal one’s fate.