Investigating the association between PM2.5, Climate variables, and COVID-19 daily reported cases from March 2020 to November 2021 in El Paso County, Texas: A Time-Series Analysis

This study aims to examine the relation between daily maximum exposure to Particulate Matter (PM2.5), high wind speed, and minimum visibility, and COVID-19 cases in El Paso County, Texas, a dust-prone region. A time-series analysis using a generalized linear model with a Poisson model was employed to analyze relative risks of COVID-19 cases in El Paso (March 2020 to November 2021). A total of 156,299 cases were diagnosed during the study period. A 10 μg/m³ increase in PM2.5 levels was linked with higher risk ratio (RR) of COVID-19 (Lag Days 1 to 3) [lag1: RR = 1.004; 95% CI: (1.003-1.005), lag2: RR = 1.006; 95% CI: (1.005-1.007), & lag 3: RR = 1.004; 95% CI: (1.003-1.005)], followed by a decrease in cases. Similarly, a 4.47 m/s rise in maximum wind speed was associated with an elevated RR of cases on Lag Day 4 [lag4: RR = 1.009; 95% CI: (1.003-1.014)], after which numbers begin to drop. Finally, a 4.83 km decrease in minimum daily visibility was correlated with an increased RR of cases on Lag Days 1 and 2 [lag1: RR = 1.031; 95% CI: (1.023-1.039), & lag2: RR = 1.018; 95% CI: (1.011-1.024)], with a decrease on Lag days 3, 4 and 5 and resurgence on Lag days 6 and 7 [lag6: RR = 1.028; 95% CI: (1.021-1.036), & lag7: RR = 1.046; 95% CI: (1.038-1.055)]. PM2.5, wind speed, and visibility influencing COVID-19 cases in El Paso highlight the need for evidence-based interventions, including information, education, and communication programs, early-warning systems, cross-border air-quality management, real-time monitoring, and stricter emission controls.