Assessing temporal correlation in environmental risk factors to design efficient area-specific COVID-19 regulations: Delhi based case study
Vishal Chaudhary, Pradeep Bhadola, Ajeet Kaushik, Mohammad Khalid, Hidemitsu Furukawa, Ajit Khosla
Abstract
Abstract Amid ongoing devastation due to Serve-Acute-Respiratory-Coronavirus2 (SARS-CoV-2), the global spatial and temporal variation in the pandemic spread has strongly anticipated the requirement of designing area-specific preventive strategies based on geographic and meteorological state-of-affairs. Epidemiological and regression models have strongly projected particulate matter (PM) as leading environmental-risk factor for the COVID-19 outbreak. Understanding the role of secondary environmental-factors like ammonia (NH 3 ) and relative humidity (RH), latency of missing data structuring, monotonous correlation remains obstacles to scheme conclusive outcomes. We mapped hotspots of airborne PM 2.5 , PM 10 , NH 3 , and RH concentrations, and COVID-19 cases and mortalities for January, 2021-July,2021 from combined data of 17 ground-monitoring stations across Delhi. Spearmen and Pearson coefficient correlation show strong association (p-value < 0.001) of COVID-19 cases and mortalities with PM 2.5 (r > 0.60) and PM 10 (r > 0.40), respectively. Interestingly, the COVID-19 spread shows significant dependence on RH (r > 0.5) and NH 3 (r = 0.4), anticipating their potential role in SARS-CoV-2 outbreak. We found systematic lockdown as a successful measure in combatting SARS-CoV-2 outbreak. These outcomes strongly demonstrate regional and temporal differences in COVID-19 severity with environmental-risk factors. The study lays the groundwork for designing and implementing regulatory strategies, and proper urban and transportation planning based on area-specific environmental conditions to control future infectious public health emergencies.