SARSCoV-2 disintegration time forecast

At Quarticle, we not only develop software solutions in the field of geoinformation, but we also spend an important time doing research.

Since the covid pandemic is a current problem in everybody’s life, we were thinking about how we can help the community by bringing our GIS know-how and resources to help. That’s why we made a research on how we can predict the virus disintegration rate, based on scientific methods.

Studies conducted by “Homeland Security” in the US (for more details, access this article), show that viruses, especially the SARS-CoV2 virus, have periods of survival in the air that depend very much on weather conditions. Experiments suggest that the SARS-CoV2 virus is sensitive to the following parameters: air temperature, humidity and ultraviolet radiation (UV-B spectrum).

Based on the current weather conditions, a map can be made, in almost real time, with the disintegration times of the virus in the air (HaDEVA). Starting from these scientific data and using Quarticle’s expertise, our team made a variant of atmospheric forecast using a numerical model of atmospheric forecast for a period of 24 hours. We did this by calculating the index represented by the disintegration time of a percentage of viruses in the air depending on the key meteorological parameters.

Our forecast models estimate, based on complex equations, the future states of the atmosphere, based on the initial weather conditions, from the moment the model was initiated on our computing infrastructure. To make the HaDEVA map, we operationally initiate an atmospheric forecasting model (WRF-ARW model), every morning, and calculate, hour by hour, how long 90% of the viruses present in the air are inactivated. The modeling focuses on Romania and its surroundings, at a spatial resolution of 7 km.

The models do not provide an accurate forecast, but rather an estimate of the main atmospheric parameters that may influence the disintegration of the virus in the air. Over a short period (up to 3 days), however, these estimates are highly accurate. Above you can see an example of the HaDEVA model developed by the Quarticle team, which captures the prediction of the disintegration time of 90% of SARS-CoV2 viruses based on these key parameters.