COVID‐19 in Chihuahua, Mexico: Assessing its spatial behaviour through the inverse distance weighted interpolation technique

Abstract

AbstractThis study focused on the spatial evolution of COVID‐19 in the state of Chihuahua, Mexico. Data were retrieved from governmental databases and analyzed by means of GIS, applying the inverse distance weighted (IDW) method. The period of December 2019 through November 2021 was split into eight seasons. The root mean square error (RMSE) was used to assess the reliability of the interpolations, showing acceptable values (RSME < 25). During the period, the municipalities of Juarez and Chihuahua reached the highest number of confirmed cases and deaths, Juarez being the main hotspot of contagion (37.2% of confirmed cases; 46.9% of deaths). Four waves of contagion were identified during the evaluated period, with Fall 2020 being the strongest season. Since Fall 2020, the spread of the disease was more often observed in municipalities with the highest human mobility. Although the spread of COVID‐19 decreased after Spring 2021, in Fall 2021 records indicated a continuous increase in cases in the state. That could be due to a relaxation of the implementation of sanitary measures, as well as to the propagation of novel COVID‐19 variants having an elevated infectious level. Geospatial techniques allowed for an understanding of the spatial spread of COVID‐19 and could be useful for its control.