This study evaluates the distribution of COVID-19 cases and mass vaccination campaigns from January 2020 to April 2023. There are over 235,000 COVID-19 cases and over 733,000 vaccinations across the 159 counties in the state of Georgia. Data on COVID-19 was acquired from usafact.org while the vaccination records were obtained from COVID-19 vaccination tracker. The spatial patterns across the counties were analyzed using spatial statistical techniques which include both global and local spatial autocorrelation. The study further evaluates the effect of vaccination and selected socio-economic predictors on COVID-19 cases across the study area. The result of hotspot analysis reveals that the epicenters of COVID-19 are distributed across Cobb, Fulton, Gwinnett, and DeKalb counties. It was also affirmed that the vaccination records followed the same pattern as COVID-19 cases’ epicenters. The result of the spatial error model performed well and accounted for a considerable percentage of the regression with an adjusted R squared of 0.68, Akaike Information Criterion (AIC) 387.682 and Breusch-Pagan of 9.8091. ESDA was employed to select the main explanatory variables. The selected variables include vaccination, population density, percentage of people that do not have health insurance, black race, Hispanic and these variables accounted for 68% of the number of COVID-19 cases in the state of Georgia during the study period. The study concludes that both COVID-19 cases and vaccinated individuals have spatial peculiarities across counties in Georgia state. Lastly, socio-economic variables and vaccination are very important to reduce the vulnerability of individuals to COVID-19 disease.
References
[1]
Mollalo, A., Vahedi, B. and Rivera, K.M. (2020) GIS-Based Spatial Modeling of COVID-19 Incidence Rate in the Continental United States. ScienceoftheTotalEnvironment, 728, Article ID: 138884. https://doi.org/10.1016/j.scitotenv.2020.138884
[2]
Oluwafemi, O. and Oladepo, O. (2021) Modeling Severe Acute Respiratory Syndrome Coronavirus 2019 (SARS-CoV-19) Incidence across Conterminous US Counties: A Spatial Perspective. ProceedingsoftheICA,Vol. 4, 79. https://doi.org/10.5194/ica-proc-4-79-2021
[3]
US COVID-19 Cases and Deaths by State. https://usafacts.org/visualizations/coronavirus-covid-19-spread-map/
[4]
Bloom, J.D., Chan, Y.A., Baric, R.S., Bjorkman, P.J., Cobey, S., Deverman, B.E. and Relman, D.A. (2021) Investigate the Origins of COVID-19. Science, 372, 694-694. https://doi.org/10.1126/science.abj0016
[5]
Riccardo, F., Ajelli, M., Andrianou, X.D., Bella, A., Del Manso, M., Fabiani, M. and COVID-19 Working Group (2020) Epidemiological Characteristics of COVID-19 Cases and Estimates of the Reproductive Numbers 1 Month into the Epidemic, Italy, 28 January to 31 March 2020. Eurosurveillance, 25, Article ID: 2000790. https://doi.org/10.2807/1560-7917.ES.2020.25.49.2000790
[6]
Akinwumiju, A.S., Oluwafemi, O., Mohammed, Y.D. and Mobolaji, J.W. (2022) Geospatial Evaluation of COVID-19 Mortality: Influence of Socio-Economic Status and Underlying Health Conditions in Contiguous USA. AppliedGeography, 141, Article ID: 102671. https://doi.org/10.1016/j.apgeog.2022.102671
[7]
Faria, C.G.F., Matos, U.M.A.D., Llado-Medina, L., Pereira-Sanchez, V., Freire, R. and Nardi, A.E. (2022) Understanding and Addressing COVID-19 Vaccine Hesitancy in Low and Middle Income Countries and in People with Severe Mental Illness: Overview and Recommendations for Latin America and the Caribbean. FrontiersinPsychiatry, 13, Article ID: 910410. https://doi.org/10.3389/fpsyt.2022.910410
[8]
Mohammadi, A., Mollalo, A., Bergquist, R. and Kiani, B. (2021) Measuring COVID-19 Vaccination Coverage: An Enhanced Age-Adjusted Two-Step Floating Catchment Area Model. InfectiousDiseasesofPoverty, 10, 1-13. https://doi.org/10.1186/s40249-021-00904-6
[9]
Penchansky, R. and Thomas, J.W. (1981) The Concept of Access: Definition and Relationship to Consumer Satisfaction. MedicalCare, 19, 127-140. https://doi.org/10.1097/00005650-198102000-00001
[10]
Rader, B., Astley, C.M., Sewalk, K., Delamater, P.L., Cordiano, K., Wronski, L. and Brownstein, J.S. (2022) Spatial Modeling of Vaccine Deserts as Barriers to Controlling SARS-CoV-2. CommunicationsMedicine, 2, 141. https://doi.org/10.1038/s43856-022-00183-8
[11]
Sobral, M.F.F., Duarte, G.B., da Penha Sobral, A.I.G., Marinho, M.L.M. and de Souza Melo, A. (2020) Association between Climate Variables and Global Transmission of SARS-CoV-2. ScienceoftheTotalEnvironment, 729, Article ID: 138997. https://doi.org/10.1016/j.scitotenv.2020.138997
[12]
Desjardins, M.R., Hohl, A. and Delmelle, E.M. (2020) Rapid Surveillance of COVID-19 in the United States Using a Prospective Space-Time Scan Statistic: Detecting and Evaluating Emerging Clusters. AppliedGeography, 118, Article ID: 102202. https://doi.org/10.1016/j.apgeog.2020.102202
[13]
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y. and Cao, B. (2020) Clinical Features of Patients Infected with 2019 Novel Coronavirus in Wuhan, China. TheLancet, 395, 497-506. https://doi.org/10.1016/S0140-6736(20)30183-5
[14]
Koets, L., van Leeuwen, K., Derlagen, M., van Wijk, J., Keijzer, N., Feenstra, J.D. and Koppelman, M.H. (2023) Efficient SARS-CoV-2 Surveillance during the Pandemic-Endemic Transition Using PCR-Based Genotyping Assays. MicrobiologySpectrum, 11, e03450-22. https://doi.org/10.1128/spectrum.03450-22
[15]
United States Bureau of the Census, United States Economics and Statistics Administration (2011) Statistical Abstract of the United States 2011. US Government Printing Office, Washington DC.
[16]
Yarbrough, R.A. (2010) Becoming “Hispanic” in the “New South”: Central American Immigrants’ Racialization Experiences in Atlanta, GA, USA. GeoJournal, 75, 249-260. https://doi.org/10.1007/s10708-009-9304-7
[17]
Zúñiga, V. and Hernández-León, R. (2022) An Ambivalent Embrace: The Reception of Children of Mexican Immigrants in the Schools of Georgia. CONfines, 25, 81-104.
[18]
Binita, K.C., Shepherd, J.M. and Gaither, C.J. (2015) Climate Change Vulnerability Assessment in Georgia. AppliedGeography, 62, 62-74. https://doi.org/10.1016/j.apgeog.2015.04.007
[19]
Georgia Department of Transportation, Office of Transportation Data, December 2012.
[20]
Tobler, W. (2004) On the First Law of Geography: A Reply. AnnalsoftheAssociationofAmericanGeographers, 94, 304-310. https://doi.org/10.1111/j.1467-8306.2004.09402009.x
[21]
Oluwafemi, O.A., Babatimehin, O.I., Oluwadare, T.S. and Mahmud, U.M. (2013) Mapping Malaria Case Event and Factors of Vulnerability to Malaria in Ile-Ife, Southwestern Nigeria: Using GIS. EthiopianJournalofEnvironmentalStudiesandManagement, 6, 365-375. https://doi.org/10.4314/ejesm.v6i4.4
