Spatial associations of long-term exposure to diesel particulate matter with seasonal and annual mortality due to COVID-19 in the contiguous United States

Abstract

Abstract Background People with certain underlying respiratory and cardiovascular conditions might be at an increased risk for severe illness from COVID-19. Diesel Particulate Matter (DPM) exposure may affect the pulmonary and cardiovascular systems. The study aims to assess if DPM was spatially associated with COVID-19 mortality rates across three waves of the disease and throughout 2020. Methods We tested an ordinary least squares (OLS) model, then two global models, a spatial lag model (SLM) and a spatial error model (SEM) designed to explore spatial dependence, and a geographically weighted regression (GWR) model designed to explore local associations between COVID-19 mortality rates and DPM exposure, using data from the 2018 AirToxScreen database. Results The GWR model found that associations between COVID-19 mortality rate and DPM concentrations may increase up to 77 deaths per 100,000 people in some US counties for every interquartile range (0.21 μg/m3) increase in DPM concentration. Significant positive associations between mortality rate and DPM were observed in New York, New Jersey, eastern Pennsylvania, and western Connecticut for the wave from January to May, and in southern Florida and southern Texas for June to September. The period from October to December exhibited a negative association in most parts of the US, which seems to have influenced the year-long relationship due to the large number of deaths during that wave of the disease. Conclusions Our models provided a picture in which long-term DPM exposure may have influenced COVID-19 mortality during the early stages of the disease. That influence appears to have waned over time as transmission patterns evolved.

Keywords

• Diesel Particulate Matter
• COVID-19 mortality
• Global models
• Geographically weighted regression
• Spatial pattern
• Seasonal effects