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article imageHumidity levels could be key to coronavirus control

By Tim Sandle     Sep 28, 2020 in Health
To what extent can weather and climate affect COVID-19 infection risks? The answer rests on a predictive model, one that could enable buildings to be modified to lower infection.
In terms of the climate, one research group maintain that as COVID-19 cases increase, understanding how climate affects the spread of the coronavirus is necessary.
Aerosol of respiratory droplet transmission is well-known to be a primary vehicle for the rapid spread and continued circulation of viruses in humans. There is also strong support that environmental conditions will affect rates of virus transmission. With the SARS-CoV-2 virus, medical data has consistently detected the virus in the saliva of infected people.
This is particularly so as winter virus infections are generally more common (and those of use based in the northern hemisphere) will experience cooler temperatures.
To this end, scientists have studied the impact of relative humidity, environmental temperature, and wind speed in relation to the human respiratory cloud and also with virus viability.
The key aspect from the research relates to a critical factor for the transmission of the infectious particles or virions (especially when they are immersed in respiratory clouds of saliva droplets). This is the rate of evaporation. The importance of this is the way by which heat and mass transfer around and within respiratory droplets, affect the chance of infection, especially within a closed environment.
The optimal conditions to reduce the chance of infection from coronavirus are environments with high temperature and low relative humidity. This is because such environs lead to high evaporation rates of saliva-contaminated droplets, and this is critical for reducing the virus viability.
The researchers call this factors the saliva liquid carrier-droplet evaporation rate. However, even under these optimal conditions the virus can still spread. This arises due to another factor: wind speed. This means the wind outdoors or air movement through air changes when indoors. Understanding the aerodynamics could influence social distancing guidelines.
The significance of this research could be towards a better understanding of the evaporation and how this connects with climate effects. This could become the basis to a model that would enable scientists to better predict coronavirus concentration and hence to assess the viability of the virus or at least the potential for virus survival.
Such a model could be possible through the use of a computational fluid dynamics platform. The researchers used a very specific model, called the three-dimensional multiphase Eulerian–Lagrangian computational fluid dynamics solver.
This requires an understanding of the steady-state of heat and mass transfer in relation to flowing spherical particles, as viral particles would be in a stream of ejected saliva – such as when we talk, cough or spit.
The video below expands on some of these points:
What was most complicated with the model was assessing the vapor film of thickness that forms around the droplet containing viral particles.
Such a model cannot predict if someone will become infected as that depends on the viral load and the individual, accounting for factors like age, gender, underlying medical conditions, and, possibly, genetics and so on.
But what the model can do is assist with building design and social distancing indoors and outdoors, and provide advice for optimal environments to help lower transmission. The model shows how social distancing remains important both in the streamwise (wind direction) and spanwise direction – it’s not just a linear concept.
Of concern for those living in the northern hemisphere as winter approaches are the combination of low temperatures and high wind speeds , which are set to increase airborne virus survival and transmission – at least based on the new research.
The study has been published in the Physics of Fluids and it is titled “Weather impact on airborne coronavirus survival.”
Predictive analytics
In related predictive analytics news, researchers have taken as series of factors to create a model that can assess how series the coronavirus infection is likely to be for a given person. The factors used were: patient's age, body mass index (BMI), lung health and chronic disease, as well as vital signs and the severity of a patient's COVID-19 symptoms at the time of admission.
This has led to a computer-based program called the ‘COVID Inpatient Risk Calculator’, and this is free online for medics from around the world to access.
More about coronavirus, Weather, humidity, Covid19
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