A convincing argument that weather influences COVID-19 can be formulated in three parts: (1) experimental data suggest SARS-CoV-2 persistence on surfaces or in the air is sensitive to temperature, humidity, and ultraviolet light; (2) other environmentally sensitive respiratory viruses are seasonal, and more common in winter; and therefore, (3) climatic effects could be protective over space (hot, dry places might have less transmission) and time (summer might see reduced transmission compared to winter). All three are plausible and are generally consistent, but in many places (including, and especially, on social media), the basic premise of each has been communicated to the public, and policymakers, in a way that obscures key nuance and creates false confidence.
Experimental evidence shows that SARS-CoV-2 is environmentally sensitive
Like other viruses with a lipid envelope, SARS-CoV-2 is probably sensitive to temperature, humidity, and solar radiation; this affects its ability to persist on surfaces and in air, and might have subtle impacts on transmission. But the finer details of microbiology are often lost, leading to false confidence in how lab studies could scale up to the real world. For example, studies showing that germicidal ultraviolet radiation in hospitals and laboratories (ultraviolet C (UV-C) wavelengths) kills the virus have been misconstrued as evidence that sunlight (a mix of UV-A and UV-B) would effectively neutralize the virus in outdoor public spaces, possibly at a scale detectable from case data1. Newer experimental evidence supports the hypothesis that sunlight might also have an effect on SARS-CoV-22, although a global study found only a 1% reduction in transmission linked to environmental UV radiation3. In the real world, these effects will be slight, and unlikely to set hard limits on transmission anywhere in the world4.
Other upper respiratory tract infections are seasonal, with declines in warmer months
Influenza, the common cold, and other respiratory infections show seasonal transmission that coincides with changes in temperature, humidity, and solar radiation. But seasonal epidemics are also a product of the transmissibility of a virus, the initial susceptibility of a population, and the degree and nature of immunity conferred by infections. In basic epidemiological models, stable “oscillations” like seasonal epidemic waves usually require some degree of immunity5,6; at the start of a pandemic, when transmissibility is high and immunity is low, even strong environmental drivers are unlikely to curb transmission. Previous influenza pandemics show the importance of this nuance7. “Seasonal” versus “pandemic” influenza refers not just to different epidemic phases, but entirely different viral strains, and population susceptibility to pandemic strains starts high enough for rapid spread regardless of the season. During the first wave of the 2009 A/H1N1 pandemic, epidemic growth was still possible in August, the most environmentally unfavorable point in the year, with immunity under 20%; months later, immunity—and consequently environmental sensitivity—may eventually have been high enough to lead to a winter-driven third wave8. Scientists anticipate a similar pattern for COVID-19: while the virus could develop seasonal oscillations if it becomes endemic9 (i.e., if pandemic control fails in the long term), current susceptibility to SARS-CoV-2 is high enough that summer weather is unlikely to be protective10.
Environmental drivers could plausibly create seasonal or geographic differences in COVID-19 outbreak intensity
But those drivers’ impacts are heavily confounded by immunity, interventions, human behavior, and other details that are usually left out of models, leading to potentially spurious conclusions. For example, most available contact tracing data indicate that the proportion of indoor transmission is high11,12, a pattern likely caused by a combination of social contact patterns (including both number, intensity, and duration of contacts), air circulation, and potential weather drivers like sunlight or humidity. However, when studies attempt to model links between temperature and transmission, they almost always use gridded climate data or local weather data that represents the outdoors, and is unrepresentative of indoor conditions a virus particle or aerosolized cloud would actually experience in most transmission events.
Perhaps the biggest confounder, social behavior is environmentally driven and seasonal, but is rarely weighed alongside environmental and immunity drivers as a hypothesis for why infectious diseases show seasonality13,14. For example, school terms are seasonal and have a marked influence on social mixing patterns relevant to influenza transmission, even in pandemics15,16,17. Without individual-level transmission data, it can be difficult to distinguish direct biological impacts of weather from behaviorally mediated seasonality, and in some cases, the two are blurred (e.g., vitamin D levels are driven by both weather and seasonal behavior). Confusing the two could easily lead to spurious predictions. If behavioral patterns become unpredictable—either because of externalities like social distancing restrictions or a feedback loop between science and public risk perceptions around seasonality—attempts at forecasting the pandemic based on environmental seasonality will only become more unreliable.
Source: Ecology - nature.com
