Spatial epidemiology of COVID-19 infection through the first outbreak (March-May 2020) in the city of Mashhad, Iran

Abstract

Background: Since December 2019, SARS-CoV-2 infection has converted to a severe threat to global health. It is now considered as the fifth worldwide pandemic problem. This study aims to explore spatial-time distribution of COVID-19 in the first outbreak of COVID-19 in the second major city of Iran (Mashhad). The results will pave the way for better tracking of COVID-19.Methods: Data were collected from two tertiary hospitals in Mashhad in June 2020. They included demographic findings and residential address of the patients with confirmed COVID-19 disease by polymerase chain reaction test. The univariate logistic regression model was used to assess the influence of age and sex on mortality. For spatial-time analysis, after calculating empirical Bayesian rate for every neighborhood, the local Moran's I statistic was used to quantify spatial autocorrelation of COVID-19 frequency at the city neighborhood level.Results: Of 1,535 confirmed cases of COVID-19 included in this study, 951 (62%) were male. Odds of death for patients over 60 years of age was more than three times higher (odds ratio [OR]: 3.7, CI [2.8-4.8]) than for those under the 60 years. In addition, the ratio of relative mortality for male patients was significantly higher than the female (OR: 1.58, CI [1.2-2]). The univariate regression model also revealed that odds of death increased along with increase in duration of hospitalization secondary to COVID-19 disease (OR: 1.02, IQR [1.01-1.02]). The downtown area had a significant high-high cluster throughout much of the study period (March-May 2020). Conclusions: Collection of geographic information system (GIS) map data on SARS-CoV-2 provides insight into clusters of infection and high risk places for COVID-19 transmission. GIS-