As COVID-19 swept country after country, cities and nations have instituted quarantine regulations to prevent the further spread of the virus. Lives have been lost, economies have crippled, jobs have been cut, and citizens have isolated themselves for weeks and even months. People across the globe living in anxiety, financial setbacks, and depression because of the COVID-19 outbreak wonder when it will end. Gatherings have been observed disregarding local, state, and federal advisory notices from impatiently waiting for the curve to flatten indicating the spread of the disease has slowed.
How does the weather affect the risk of spreading COVID-19?
In an early February 2020 study, researchers collected data from all cities and regions with confirmed cases of COVID-19 between January 20th and February 4th. These cases totaling in 24,129, were made up of a vast majority of data points from in regions of China and only 26 confirmed cases in overseas countries. Information from these cases were analyzed for the relationship between number of cases and temperature change in average maximum and minimum temperatures for the region within the time span. The results determined that in lower temperatures, as temperatures increase the number of cases increase. The results also showed that in higher temperatures, as the temperature increases the number of cases decrease. This led scientist to believe that there is a most productive temperature range for the virus that causes COVID-19. This also provides evidence used to implement and enforce stricter risk management protocols in regions with lower temperatures. This conclusion gave hopes to analyst around the globe making predictive models for the upcoming spring summer months for flattening the curve, but then as the virus continues to proliferate regionally new questions arise.
· Does temperature factor into the reasoning African countries remain largely unaffected?
· Did weather modeling predict the transmission of COVID-19?
· And how does humidity factor into the findings that the virus might have an ideal temperature range?
These questions were further explored in two March studies analyzing temperature, humidity, and data points from confirmed cases in China between January 21st and 23rd. Modelling from statistical analysis with influenza, researchers calculated the severity of infectiveness (R) for the COVID-19 SARS virus. Using a 5-day incubation estimate from John Hopkins University, researchers ran a 3 to 5-day average temperature and humidity calculation to formulate a relationship between both temperature and humidity to R. The results determined a strong negative relationship meaning, high temperature and high humidity can possibly reduce the transmission of COVID-19.
There are many reasons why they data may show such promising results:
“First, the influenza virus is more stable in cold temperature, and respiratory droplets, as containers of viruses, remain airborne longer in dry air. Second, cold and dry weather can also weaken the hosts’ immunity and make them more susceptible to the virus. These mechanisms are also likely to apply to the COVID-19 transmission.” (Wang, J. et. al, 2020)
Another study analyzed the relationship between weather patterns, geographical movement of COVID-19, and significance of regional spread of COVID-19. The study determined that there is a significant pattern in weather conditions such as temperature and humidity and the significance of COVID-19 in cities that have been majorly impacted. In addition, these regions have factors such as international travel and population proximity that could correspond to the trends observed. Weather modeling shows promise of predicting regions of higher risk for the spread of COVID-19 allowing public health officials to use this data to monitor and contain the epidemic.
However, as promising as the data looks, the temperature and humidity ranges for this study were small, so the estimations may not be relevant to regions with extreme high or low temperatures and humidity indices. All local, state, and federal leaders are strongly advised to implement risk management protocols to last throughout the summer.
Gutierrez, R. (2019). Coronavirus Disease 2019 Rotator Graphic for af.mil [Photograph]. U.S. Air Force Graphic. https://www.919sow.afrc.af.mil/News/Art/igphoto/2002264666/
Wang, M., Jiang, A., Gong, L., Luo, L., Guo, W., Li, C., Zheng, C., Li, C., Yang, B. Zeng, J., Chen, Y., Ke Zheng, K., Li, H. (2020). Temperature significant change COVID-19 Transmission in 429 cities. Sourced from https://www.medrxiv.org/content/10.1101/2020.02.22.20025791v1.full.pdf
Wang, J.,Tang, K., Feng, K., & Lv, W. (2020). High Temperature and High Humidity Reduce the Transmission of COVID-19. Available at SSRN: https://ssrn.com/abstract=3551767 or http://dx.doi.org/10.2139/ssrn.3551767
Sajadi, Mohammad M., Habibzadeh, P., Vintzileos, A., Shokouhi, S., Miralles-Wilhelm, F., & Amoroso, A. (2020). Temperature, Humidity and Latitude Analysis to Predict Potential Spread and Seasonality for COVID-19. Available at SSRN: https://ssrn.com/abstract=3550308 or http://dx.doi.org/10.2139/ssrn.3550308