Objective This study retrospectively examined the health and social determinants of the COVID-19 outbreak in 175 countries from a spatial epidemiological approach. Methods We used spatial analysis to examine the cross-national determinants of confirmed cases of COVID-19 based on the World Health Organization official COVID-19 data and the World Bank Indicators of Interest to the COVID-19 outbreak. All models controlled for COVID-19 government measures. Results The percentage of the population age between 15-64 years (Age15-64), percentage smokers (SmokTot.), and out-of-pocket expenditure (OOPExp) significantly explained global variation in the current COVID-19 outbreak in 175 countries. The percentage population age group 15-64 and out of pocket expenditure were positively associated with COVID-19. Conversely, the percentage of the total population who smoke was inversely associated with COVID-19 at the global level. Conclusions This study is timely and could serve as a potential geospatial guide to developing public health and epidemiological surveillance programs for the outbreak in multiple countries. Removal of catastrophic medical expenditure, smoking cessation, and observing public health guidelines will not only reduce illness related to COVID-19 but also prevent unecessary deaths.

The coronavirus disease 2019 (COVID-19) pandemic has affected people from every part of the world, with the elderly and minority groups being at a higher risk owing to the high prevalence of underlying health conditions such as atherosclerosis among these groups. This study discusses numerous implications of the COVID-19 pandemic on people consuming more unhealthy foods due to restricted access to stores and stores closing early. A lot of people currently live a sedentary lifestyle because of the strenuous quarantine measures. COVID-19 impacts the nutritional status of people leaving them at risk of atherosclerosis and worsens the health condition of individuals suffering from it. Also, the use of COVID-19 medications has been observed to have side effects in patients with atherosclerosis. Thus, we review the nutritional impact of COVID-19 and its implications on atherosclerosis at length and make recommendations for reducing future implications. This study would serve as a foundation for further research on COVID-19 and its implications on atherosclerosis as only a limited number of studies have addressed it.

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Among existing research on social vulnerability, virtually no studies have considered homelessness as a variable in their vulnerability assessments. This study identified the relevance of homelessness as a key index in social vulnerability assessment to inform the public, policymakers and the broader body of literature of its impacts on shaping vulnerability patterns in cities. In this study, the 2018 Homeless data for Austin was disaggregated from the council district level to block group level using dasymetric mapping in Geographic Information System (GIS). Principal Component Analysis (PCA) was used to group highly correlated demographic and socioeconomic variables into factors, which were normalized and summed to model social vulnerability with homeless index (SOVI_H) and without homeless index (SOVI) for each Austin Blockgroup. The result revealed significant differences in geographic patterns between SOVI_H and SOVI. SOVI_H showed hotspots of vulnerabilities in Downtown and East-Austin neighborhoods, depicting a slight shift of social vulnerability westwards of the city. This finding differs from past results of social vulnerabilities in Austin where it used to be predominant in the East. This study showed that incorporating homelessness in identifying social vulnerability can help researchers and other associated organizations identify the most vulnerable groups when conducting social vulnerability assessments.