Modelización compartimental y multivariante de enfermedades respiratorias en Guayaquil mediante enfoque poblacional

Abstract

Over the past five years, certain viral agents associated with severe acute respiratory infections such as COVID-19, Respiratory Syncytial Virus, Influenza AH1N1, Influenza AH3N2, and Influenza B have been resurging, affecting the health of Ecuadorians. This project aims to apply spatial geoprocessing tools and an epidemiological compartmental model to visualize the spread of these diseases in Guayaquil and their infection hotspots. To this end, the Quantum Geographic Information System (QGIS) was used to illustrate the urban map with the distribution of districts and circuits in Guayaquil, as well as the set of registered cases of these diseases together with the city’s hospital units. In addition, the RStudio integrated development environment was used for database processing and the Susceptible-Exposed-Infected-Removed (SEIR) epidemiological model was used to observe the spread of infected individuals over time. The study showed that the El Fortín, Sauces 3, and Socio Vivienda 1 health units recorded the highest number of cases, as did the densely populated areas of Guayaquil, such as Urdaneta, Cristo del Consuelo, and the areas surrounding the port terminal. It is concerning to note that relatively small districts (such as 09D04, 09D06, and 09D08) showed a higher concentration of cases than larger districts, thus reaffirming their role as critical points of infection and reinforcing the idea of increasing the number of hospital units in these districts. Keywords: Clustering, DBSCAN, OpenStreetMap, Geographic Information System, SEIR model, RStudio, Respiratory Syncytial Virus, pathogens, mortality, infection rate.