key: cord-0856798-jjcrnvc8 authors: Sarkodie, Samuel Asumadu; Owusu, Phebe Asantewaa title: Global effect of city-to-city air pollution, health conditions, climatic & socio-economic factors on COVID-19 pandemic date: 2021-03-12 journal: Sci Total Environ DOI: 10.1016/j.scitotenv.2021.146394 sha: a5df8a24b048dd875364deb4af3228700c026338 doc_id: 856798 cord_uid: jjcrnvc8 The rate of spread of the global pandemic calls for much attention from the empirical literature. The limitation of extant literature in assessing a comprehensive COVID-19 portfolio that accounts for complexities in the spread and containment of the virus underscores this study. We investigate the effect of city-to-city air pollutant species, meteorological conditions, underlying health conditions, socio-economic and demographic factors on COVID-19 health outcomes. We utilize a panel estimation of 615 cities in 6 continents from January 1 to June 11, 2020. While social distancing measures, movement restrictions and lockdown are reported to have improved environmental quality, we show that ambient PM2.5 remains unhealthy and above the acceptable threshold in several countries. Our empirical assessment shows that while ambient PM2.5, nitrogen dioxide, ozone, pressure, dew, Windgust, and windspeed increase the spread of COVID-19, high relative humidity and ambient temperature have mitigation effect on COVID-19, hence, decreases the number of confirmed cases. We report 66.3% of countries projected to experience a second wave of COVID-19 if government stringency and safety protocols are not enhanced. By extension, our assessments demonstrate that several factors namely underlying health conditions, meteorological, air pollution, health system quality, socio-economic and demographics spur the reproduction effect of COVID-19 across countries. Our study highlights the importance of government stringency in containing the spread of COVID-19 and its impacts. The confirmed cases of COVID-19 global pandemic have surpassed 14 million as of July, 2020, with corresponding 602,656 cases of deaths (4.3% death rate), and 7,894,890 recovery cases (Lauren, 2020) . Top 10 countries of confirmed cases include the US (3,647,715), Brazil (2,046,328), India To contain the spread and reduce fatalities from COVID-19, there are several Government responses instituted across countries ranging from public health system, economic Response, closure and containment (ACAPS, 2020). Public health system responses toward improving health system quality include public information campaigns, testing policy, contact tracing, emergency investment in healthcare, and investment in vaccines. The economic response towards the alleviation of economic burden comprises income support, debt contract relief, fiscal measures, and Contrary to the extant literature, we present a comprehensive empirical assessment of COVID-19 pandemic by controlling for underlying health conditions, government response, socio-economic and demographic factors, climatic and environmental conditions from 615 cities in 6 continents. The statistical hypotheses tested in this study include: First, H 0 : Climatic factors have no effect on COVID-19 cases. Second, H 0 : Socio-economic and demographic factors have no effect on COVID-19 deaths. Third, H 0 : Underlying health conditions have no effect on COVID-19 health outcomes. Fourth, H 0 : Stringency and availability of beds have no effect on COVID-19 cases. H 1 : Stringency and availability of beds have negative effect on COVID-19 cases. Finally, H 0 : Concentrations of air pollutants have no effect on COVID-19 cases. H 1 : Concentration of air pollutants have positive effect on COVID-19 cases. matter 2.5 (PM 2.5 -µg/m 3 ), ozone (O 3 -µg/m 3 ), nitrogen dioxide (NO 2 -µg/m 3 ), dew (°C), relative humidity (%), pressure (hPa), wind gust (m/s), wind speed (m/s), ambient temperature (°C) were extracted from World Air Quality Index project (WAQI, 2020), whereas reproduction rates were obtained from EpiForecasts (Abbott et al., 2020) . Data on cardiovascular diseases, prevalence of diabetes, male and female Smokers, total tests conducted across cities, Government stringency in containing the spread of the virus, total number of hospital beds per thousand population, total number of COVID-19 deaths reported, population, Aged older than 65, GDP per capita-a proxy for income level and extreme poverty were obtained from Our World in Data (OWID, 2020). The selection of data series with specific characteristics is due to the complexity of coronaviruses. Climate change disrupts weather patterns by changing the frequency of temperature, precipitation, humidity, wind speed, dew and pressure. These changes in weather patterns affect the concentrations of atmospheric pollutants such as PM 2.5 , O 3 , and NO 2 . Hence, the interaction between weather conditions and concentrations of atmospheric pollutants affects human immune response to morbidities (De Sario et al., 2013) . Thus, confounding factors such age, existing lifestyle (smoking), health conditions (CVD, diabetes), and health quality (hospital beds, testing) underpin health outcomes. This implies that several socio-economic, political and climatic factors affect the spread of coronaviruses. Figures 1-4 were constructed using visualization tools provided by Knoema (Knoema, 2020) . The corresponding statistical analysis of the data series is presented in Table 1 . Our initial dataset comprises 615 cities and 98,480 observations. Jarque-Bera test presented in Table 1 Where ∑ is the city-by-city covariance matrix with identity matrix . The model specification of equation (1) can be presented as: Model 1: Where is the total number of COVID-19 confirmed cases, denotes temperature, represents pressure, signifies humidity, means dew, and is wind gust. In Model 1, we hypothesize that meteorological factors affect the spread of COVID-19 cases across cities. Model 2: Where is particulate matter 2.5, is ozone, denotes nitrogen dioxide, and is the wind speed. In Model 2, we test the hypothesis that climatic conditions alter the spread of COVID-19 cases across cities. Model 3: Where is the rate of cardiovascular diseases, represents the prevalence of diabetes, and denotes smokers. In Model 3, we ascertain the impact of underlying health conditions on COVID-19 cases. Where is the total tests conducted across cities, represents Government stringency in containing the spread of the virus, is the total number of hospital beds per thousand population. In Model 4, we test the hypothesis that testing, stringency and availability of beds affect the cases of COVID-19. Model 5: Where is the total number of COVID-19 deaths reported, is the rate of cardiovascular diseases, represents the prevalence of diabetes, and denotes smokers. In Model 5, we hypothesize that underlying health conditions escalate COVID-19 deaths. Model 6: Where denotes population, represents the aged older than 65, is GDP per capita-used as a proxy for income level, and denotes extreme poverty. In Model 6, we test socio-economic and demographic factors affect reported cases of COVID-19 deaths. The implementation of social distancing measures is reported to have improved air quality. In Our empirical estimation began by testing for heterogeneous effects using the modified Wald test statistic for heteroskedasticity. We observe in Table 2 that the null hypothesis of homogeneity is rejected at p-value<0.01 -confirming the city-level heterogeneity and justifying the application of panel standard error corrected estimation technique to control heteroskedastic errors across cities. We validated the estimated model using the conditional marginal effects with the heteroskedastic- Table 2 are statistically significant at 1% level with predictive power between 0.33-1.00 -implying that the regressors explain 33%-100% variations in COVID-19 health outcomes. We hypothesized via the empirical analysis that meteorological factors affect the spread of COVID-19 cases across cities. We observe in We tested the hypothesis that air pollutant conditions alter the spread of COVID-19 cases across cities. 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Open Access funding provided by Nord University is well appreciated.