Gis-based vulnerability analysis of the United States to COVID-19 occurrence. (Special Issue: COVID-19 one year on.)
Journal of Risk Research
; 24(3/4):416-431, 2021.
Article
in English
| GIM | ID: covidwho-1747026
ABSTRACT
The outbreak of COVID-19 in the United States has resulted in over 11.2 million cases and over 240 thousand deaths. COVID-19 has affected the society in unprecedented way with its socioeconomic impact yet to be determined. This study aimed at assessing the vulnerability of the US at the county-level to COVID-19 using the pandemic data from January to June of the year 2020. The study considered the following critical factors population density, elderly population, racial/ethnic minority population, diabetics, income, and smoking adults. Pearson's correlation analysis was performed to validate the independence of the factors. Spatial correlations between the COVID-19 occurrence and the factors were examined using Jaccard similarity analysis, which revealed relatively high correlation. A vulnerability to COVID-19 map with a five-level Likert scale was created using Logistic Regression Analysis in ArcGIS. The map showed close agreement in seven representative states, which were selected based on COVID-19 cases including NY, CA, FL, TX, OH, NC, and MT with R2 values between 0.684 and 0.731 with Root Mean Squared Error (RMSE) values between ..0.033 and ..0.057. Furthermore, vulnerability levels from 'High' to 'Very High' were obtained for the top ten counties with the highest COVID-19 cases with residual values less than or equal to 0.04. The method and resulted vulnerability map can aid in COVID-19 response planning, prevention programs and devising strategies for controlling COVID-19 and similar pandemics in the future.
coronavirus disease 2019; pandemics; viral diseases; human diseases; public health; outbreaks; mortality; epidemiology; population density; elderly; ethnicity; minorities; diabetes; income; socioeconomic status; adults; tobacco smoking; spatial distribution; regression analysis; disease distribution; disease incidence; Severe acute respiratory syndrome coronavirus 2; man; USA; New York; California; Florida; Texas; Ohio; North Carolina; Montana; Severe acute respiratory syndrome-related coronavirus; Betacoronavirus; Coronavirinae; Coronaviridae; Nidovirales; positive-sense ssRNA Viruses; ssRNA Viruses; RNA Viruses; viruses; Homo; Hominidae; primates; mammals; vertebrates; Chordata; animals; eukaryotes; APEC countries; high income countries; North America; America; OECD Countries; very high Human Development Index countries; Middle Atlantic States of USA; Northeastern States of USA; Pacific States of USA; Western States of USA; Gulf States of USA; Southern States of USA; South Atlantic States of USA; Southeastern States of USA; Great Plains States of USA; Southern Plains States of USA; West South Central States of USA; Southwestern States of USA; Corn Belt States of USA; North Central States of USA; East North Central States of USA; Appalachian States of USA; Mountain States of USA; SARS-CoV-2; viral infections; United States of America; death rate; aged; elderly people; older adults; senior citizens; ethnic differences
Full text:
Available
Collection:
Databases of international organizations
Database:
GIM
Language:
English
Journal:
Journal of Risk Research
Year:
2021
Document Type:
Article
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