Distribution of the environmental and socioeconomic risk factors on COVID-19 death rate across continental United States: A spatial nonlinear analysis

doi:10.21203/rs.3.rs-61369/v1

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Distribution of the environmental and socioeconomic risk factors on COVID-19 death rate across continental United States: A spatial nonlinear analysis

https://doi.org/10.21203/rs.3.rs-61369/v1

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The COVID-19 outbreak has become a global pandemic. Spatial variation in the environmental, health, socioeconomic, and demographic risk factors of COVID-19 death rate is not well understood. Global models and local linear models were used to estimate the impact of risk factors of the COVID-19, but these do not account for the nonlinear relationships between the risk factors and the COVID-19 death rate at various geographical locations. We proposed a local nonlinear nonparametric regression model named geographically weighted random forest (GW-RF) to estimate the nonlinear relationship between COVID-19 death rate and 47 risk factors derived from US Environmental Protection Agency, National Center for Environmental Information, Centers for Disease Control and the US census. The COVID-19 data were employed to a global regression model random forest (RF) and a local model GW-RF. The adjusted R²of the RF is 0.69. The adjusted R² of the proposed GW-RF is 0.78. The result of GW-RF showed that the risk factors (i.e. going to work by walking, airborne benzene concentration, householder with a mortgage, unemployment, airborne PM_2.5concentration and percent of the black or African American) have a high correlation with the spatial distribution of the COVID-19 death rate and these key factors driven from the GW-RF were mapped, which could provide useful implications for controlling the spread of COVID-19 pandemic.

Geographic Information Systems

COVID-19 death rate

environment

socioeconomic

health

local nonlinear model

spatial variation

Table 1. Definitions of indicators and sources

Theme	Indicators	Indicator meaning	Source
Atmosphere	Airborne PM_2.5 concentration	Annual average ambient concentrations of PM_2.5 in micrograms per cubic meter	United States Environmental Protection Agency (https://www.epa.gov/) and Centers for Diseases Control and Prevention (https://www.cdc.gov/)
	Airborne benzene concentration	Annual average concentration of benzene estimates in microgram per cubic meter
	Airborne formaldehyde concentration	Annual average air concentration of formaldehyde estimates in microgram per cubic meter
	Airborne acetaldehyde concentration	Annual average air concentration of acetaldehyde estimates in microgram per cubic meter
	Airborne carbon tetrachloride concentration	Annual average air concentration of carbon tetrachloride estimates in microgram per cubic meter
Climate	Air temperature	Average Daily Max Air Temperature ( )	National Center for Environmental Information (https://www.ncei.noaa.gov/)
	Precipitation	Average Daily Precipitation ( )
	Sunlight exposure	Annual average sunlight exposure measured by solar irradiance ( )	Centers for Diseases Control and Prevention (https://www.cdc.gov/)
	UV radiation exposure	Annual average daily dose of UV irradiance ( )
Landcover	Landcover with water	Percent of land covered by water
Landcover	Land cover with forest	Percent of land covered by forest
Disaster	Drought	Number of weeks of moderate drought or worse per year
Disaster	Flood	Percentage of people within fema designated flood hazard area
Health status	Disability	Percentage of population aged 5 years and over with a disability
	Asthma	Percent of adults diagnosed with asthma
	Obese	Percentage of adults aged 18 years and over who were obese
	Overweight	Percentage of adults aged 18 years and over who were overweight
	Cancer	Number of people with lung and brouchus cancer per 1000000 population
Commuting to work	Go to work by private transportation	Percentage of workers 16 years and over who drove alone (car, truck, or van)	United States Census Bureau (https://www.census.gov/en.html)
	Go to work by public transportation	Percentage of workers 16 years and over who go to work by public transportation (excluding taxicab)
	Go to work by walking	Percentage of workers 16 years and over who go to work by walking
	Work at home	Percentage of workers 16 years and over who worked at home
	Mean travel time to work	Mean travel time to work (minutes) of the workers 16 years and over
Socioeconomic	Health insurance	Percentage of population without health insurance
	Householder with a mortgage	Percentage of household with a mortgage
	Poverty	Percentage of population whose income is below the poverty level
	Service occupations	Percentage of employed population 16 years and over with service occupations
	Unemployment	Percentage of population 16 years and over unemployed
	Hospital	Number of hospitals	Centers for Diseases Control and Prevention (https://www.cdc.gov/)
	Hospital beds	Number of hospital beds per 10000 population
	People living in group quarter	Percentage of population living in group quarter	United States Census Bureau (https://www.census.gov/en.html)
	People living near a park	Percentage of population living within a half mile of a park
	Householder with no internet access	Percentage of households with no internet access
	Median household income
	Mean household retirement income
	Mean household cash public assistance income
	Mean household Supplemental Security Income
Demographic	Percent of males
	Median age
	Percent of people under 18 years
	Percent of people 65 years and over
	Percent of the white race
	Percent of the black or African American
	Percent of American Indian and Alaska Native
	Percent of Asian
	Percent of native Hawaiian and other Pacific islander
	Percent of Hispanic or Latino

Table 2. The statistic of local R² of the GW-RF in modelling COVID-19 death rate, we calculated the average value of local R² and the percentage of counties in five local R² range (≤0.2, (0.2, 04], (0.4, 06], (0.6, 08], >0.8)

The value of local	GW-RF
Average value	0.59
≤0.2	1.1%
(0.2, 04]	9.5%
(0.4, 06]	38.9%
(0.6, 08]	44.8%
>0.8	5.7%

Table 3. The proportion of counties with local primary risk factor (the risk fator with the highest value of local variable importance) on COVID-19 death rate at county level in the GW-RF.

Local primary risk factor	Proportion of counties
Go to work by walking	35%
Airborne benzene concentration	25%
Householder with a mortgage	13%
Unemployment	12%
Other risk factors	16%

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Distribution of the environmental and socioeconomic risk factors on COVID-19 death rate across continental United States: A spatial nonlinear analysis

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