How do environmental, economic and health factors influence regional vulnerability to COVID-19?

Pejman Tahmasebi; Salome M.S. Shokri-Kuehni; Muhammad Sahimi; Nima Shokri

is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.09.20059659 doi: medRxiv preprint (a) (b) (c) Fig. 1. Top row (a, b) : Prevalence of obesity among adults, BMI ≥ 30, age-standardized in 2016 labelled as "Obesity (%)," cancer data age-standardized incidence rates per 10,000 labelled as "Cancer per 10,000," prevalence of insufficient physical activity among adults aged 18+ years in 2016 labelled as "Ins. PA (%)," population aged 15-64 labelled as "Ages 15-64 (%)," high total cholesterol (>= 5.0 mmol/L) (age-standardized estimate) in 2008 labelled as "Raised TC 25+," gross national income in 2018 labelled as "GNI (in $thousands)," diabetes % of total population in 2016 labelled as "Diabetes (%)," prevalence of smoking in 2016 labelled as "Smoking (%)," raised blood pressure (SBP ≥ 140 or DBP ≥ 90), age-standardized (%) labelled as "Raised BP (%)," CO 2 per capita emissions in 2018 labelled as "CO 2 emission," gross domestic product in 2018 labelled as "GDP (in $trillions)", and population aged 65 and older labelled as "Ages 65+" in each country. The data for obesity, diabetes, raised blood pressure, raised total cholesterol, insufficient physical activity are from the World Health Organization, those for age population, prevalence of smoking, GDP and GNI from the World Bank, while the data for CO 2 per capita emissions are from Emission Database for Global Atmospheric Research (EDGAR) of the European Commission. (c) The daily death due to COVID-19 in each country. The colors represent the 3-day average total number of deaths. . CC-BY-NC 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.