The SARS-CoV-2 virus, responsible for the COVID-19 disease, has caused a global pandemic resulting in numerous deaths and significant impacts on the global economy and daily life. At the beginning of the pandemic there were no vaccines available to prevent COVID-19, so the non-pharmaceutical interventions, such as reducing person-to-person contact, were crucial in preventing the spread of the virus. Because of this, It is essential to develop strategies to control the disease's spread while preserving people's well-being, preventing job losses, and minimizing the economic impact.
A solution to the problem of controlling the spread of the SARS-CoV-2 virus is to use a meta-population model. This model takes into account the mobility of people and includes parameters to modulate their behavior based on real-world factors such as changes in social behavior, quarantines, and lockdowns. This model significantly expands traditional SEIR models and allows for more accurate forecasting of the pandemic's impact on both the population and the healthcare system. By understanding the propagation dynamics of the virus and identifying areas that contribute more to its spread, large-scale mitigation strategies can be developed to control its spread while preserving people's well-being, preventing job losses, and minimizing the economic impact.
The objective of this project, funded by the US Air Force Office of Research (AFOSR), is to develop tools that allow us to understand the current situation of the pandemic (nowcasting) and its projected impact (forecasting), both in the population and in the health system, through a georeferenced model to study the spread of the SARS-CoV-2 virus.