ABSTRACT
The pandemic nature of the new SARS-CoV-2 coronavirus requires extraordinary efforts in all areas of management and the formulation of public health policies to contain the number of contagion cases and deaths inflicted on the world population. However, it is possible to develop and encourage follow-up practices that can help reduce the number of contagion cases. This work aims to collect sociodemographic indicators associated by the scientific literature with the spatial distribution of COVID-19. Methodologically, it is a case study that aims to build a knowledge management model based on sociodemographic data collection. Their comparison with the viral RNA measurements in wastewater obtained at different points would allow managers to predict the possibility of an early warning of the onset of the disease, the future increase or decrease in the number of cases or the end of the pandemic in location. Regarding government action, associating the information related to the virus with the sociodemographic indicators of the region where the wastewater is collected, its managers can design preventive measures with greater precision and accuracy.