Medical School Professor Drikakis and Associate Professor Dbouk reach quintet of COVID-19 related research. According to their recent paper published in Physics of Fluids on 2 February 2021, temperature, humidity, and wind are typically overlooked key epidemiological parameters
The “second wave” of the coronavirus pandemic has placed much blame on a lack of appropriate safety measures. However, due to the impacts of weather, research suggests two outbreaks per year during a pandemic are inevitable.
In their fifth AIP paper (on Fluid dynamics and epidemiology: Seasonality and transmission dynamics), published in Physics of Fluids, Dr Talib Dbouk and Professor Dimitrios Drikakis, extended their research precisely to ascertain the impacts of weather-based parameters. Though face masks, travel restrictions, and social distancing guidelines are critical in slowing the number of new infections in the short-term, the researchers identified that a lack of climate effects incorporated into epidemiological models presents a glaring hole that can cause long-term effects.
Previous work from this research group showed, among other findings, that droplets of saliva can travel 6 metres in five seconds when an unmasked person coughs, and that repeated coughing seriously degrades face mask efficiency. The authors have been incorporating previous findings into their epidemiological models along the way.
Typical models for predicting the behaviour of an epidemic contain only two basic parameters: transmission rate and recovery rate. These rates tend to be treated as constants, but Dbouk and Drikakis said this is not actually the case. In their view, temperature, relative humidity, and wind speed all play a significant role, in which case, the researchers aimed to modify typical models to account for these climate conditions. They call their new weather-dependent variable the Airborne Infection Rate (AIR) index.
Importantly, when they applied the AIR index to models of Paris, New York City, and Rio de Janeiro, they found it accurately predicted the timing of the second outbreak in each city, suggesting two outbreaks per year is a natural, weather-dependent phenomenon. Further, the behaviour of the virus in Rio de Janeiro was markedly different from the behaviour of the virus in Paris and New York, due to seasonal variations in the northern and southern hemispheres, consistent with real data.
The authors emphasise the importance of accounting for these seasonal variations when designing safety measures. “We propose that epidemiological models must incorporate climate effects through the AIR index”, stressed Drikakis. “National lockdowns or large-scale lockdowns should not be based on short-term prediction models that exclude the effects of weather seasonality”.
Dbouk continued in that vein, noting that government planning should be longer-term in pandemics, during which massive and effective vaccination is not available, by considering weather effects and designing public health and safety guidelines accordingly. “This could help avoid reactive responses in terms of strict lockdowns that adversely affect all aspects of life and the global economy”.
As temperatures rise and humidity falls, Drikakis and Dbouk expect another improvement in infection numbers, though they note that mask and distancing guidelines should continue to be followed with the appropriate weather-based modifications.
Read the full paper here