Spatial disparities in incidence of COVID-19 in relation to economic and socio-demographic factors in the Autonomous Community of Madrid, Spain

Severino Escolano-Utrilla; Andrés Roca-Medina; Diego Barrado-Timón

doi:10.5565/rev/dag.904

Spatial disparities in incidence of COVID-19 in relation to economic and socio-demographic factors in the Autonomous Community of Madrid, Spain

Authors

Severino Escolano-Utrilla University of Zaragoza https://orcid.org/0000-0002-3489-0692
Andrés Roca-Medina Universidad Autónoma de Madrid https://orcid.org/0000-0002-9781-7409
Diego Barrado-Timón Universidad Autónoma de Madrid https://orcid.org/0000-0001-6638-1633

PDF

Abstract

This article models the relationship between the incidence of COVID-19 and several socioeconomic factors during the second period of epidemic (22 June 2020 to 06 December 2020) in the Autonomous Community of Madrid, Spain. Data collected from Basic Health Zones (BHZs) is adjusted using the random forest method, which proves very appropriate for capturing non-linear relationships and obtaining accurate and robust predictions. The results show that the impact of the examined socio-economic variables on rates of incidence of COVID-19 was not uniform, and that levels of mean income by neighborhood exerted stronger influence than population density, proportion of the Spanish population, mean age of the population or average household size. A complex spatial pattern emerges from the combination of impacts, reflecting the relative weights of the different factors in terms of intensity of the pandemic. This information may be considered strategic for the effective future management of health resources.

Keywords

COVID-19, economic factors, random forest method, Autonomous Community of Madrid, socio-demographic factors

References

ALMENDRA, Ricardo; SANTANA, Paula and COSTA, Claudia (2021). “Spatial inequalities of COVID-19 incidence and associated socioeconomic risk factors in Portugal”. Boletín de la Asociación de Geógrafos Españoles, 91. https://doi.org/10.21138/bage.3160 DOI: https://doi.org/10.21138/bage.3160

AMDAOUD, Mounir; ARCURI, Giuseppe; LEVRATTO, Nadine; SUCCURRO, Marianna and CONSTANZO, Damiana (2020). “Geography of COVID-19 outbreak and first policy answers in European regions and cities”. Halshs-03046489. Retrieved from https://halshs.archives-ouvertes.fr/halshs-03046489

AMENGUAL-MORENO, Miquel; CALAFAT-CAULES, Marina; CAROT, Aina; ROSA CORREIA, Ana Rita; RÍO-BERGÉ, Claudia; ROVIRA PLUJÀ, Jana; VALENZUELA PASCUAL, Clàudia and VENTURA-GABARRÓ, Cèlia (2020). “Social determinants of the incidence of Covid-19 in Barcelona: a preliminary ecological study using public data”. Revista española de salud pública, 94. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/32935664

ANSELIN, Luc (2020). Documentation/GeoDa on Github/GeoDa Workbook. Retrieved from https://geodacenter.github.io/documentation.html

ANSELIN, Luc (2021). GeoDa (Tm) (1.20.). Retrieved from https://geodacenter.github.io/

ARAUZO-CAROD, Josep-Maria; DOMÈNECH, Antoni and GUTIÉRREZ, Aaron (2021). “Do local characteristics act in a similar way for the first two waves of COVID-19? Analysis at intraurban level in Barcelona”. Journal of Public Health, 43 (3), 455-461. https://doi.org/10.1093/pubmed/fdaa238 DOI: https://doi.org/10.1093/pubmed/fdaa238

ARROYO-MENÉNDEZ, Millán; BARAÑANO-CID, Margarita and UCEDA-NAVAS, Pedro (2022). “¿Desiguales en la smart city? Segregación espacial y desigualdades digitales en Madrid/Unequal in the Smart City? Spatial Segregation and Digital Inequalities in Madrid”. Revista Española de Investigaciones Sociológicas. https://doi.org/10.5477/cis/reis.180.19 DOI: https://doi.org/10.5477/cis/reis.180.19

ARTIGA, Samantha and HINTO, Elizabeth (2018). Beyond health care: the role of social determinants in promoting health and health equity. KFF.org. Retrieved from https://www.kff.org/racial-equity-and-health-policy/issue-brief/beyond-health-care-the-role-of-social-determinants-in-promoting-health-and-health-equity/

BAENA-DÍEZ, Jose Miguel; BARROSO, María; CORDEIRO-COELHO, Sara Isabel; DÍAZ, Jorge Luis and GRAU, María (2020). “Impact of COVID-19 outbreak by income: hitting hardest the most deprived”. Journal of Public Health, 42 (4), 698-703. https://doi.org/10.1093/pubmed/fdaa136 DOI: https://doi.org/10.1093/pubmed/fdaa136

BARROS-GUERTON, Javier and EZQUIAGA-DOMÍNGUEZ, José María (2023). “Caer y levantarse: como la ciudad de Madrid ha afrontado el COVID19 de acuerdo con los datos de libre reutilización”. Ciudad y Territorio Estudios Territoriales, 55 (218), 1033-1054. https://doi.org/10.37230/CyTET.2023.218.3 DOI: https://doi.org/10.37230/CyTET.2023.218.3

BENITA, Francisco and GASCA-SANCHEZ, Francisco (2021). “The main factors influencing COVID-19 spread and deaths in Mexico: A comparison between phases I and II”. Applied Geography, 134. https://doi.org/10.1016/J.APGEOG.2021.102523 DOI: https://doi.org/10.1016/j.apgeog.2021.102523

BREIMAN, Leo (2001). “Random Forests”. Machine Learning, 45, 5-32. https://doi.org/10.1023/A:1010933404324 DOI: https://doi.org/10.1023/A:1010933404324

CESTARI, Virna Ribeiro Feitosa; FLORÊNCIO SAMPAIO, Raquel; BEZERRA SOUSA, George Jó; SANTOS GARCES, Tiago; ARAÚJO MARANHÃO, Thatiana; RIBEIRO CASTRO, Révia; LUANA CORDEIRO, Ibiapina; VENTURA DAMASCENO, Lara Lídia; VERA LUCIA, Mendes de Paula Pessoa; DUARTE PEREIRA, Maria Lúcia and MAGALHÃES MOREIRA, Thereza Maria (2021). “Social vulnerability and COVID-19 incidence in a Brazilian metropolis”. Ciencia & saude coletiva, 26 (3), 1023-1033. https://doi.org/10.1590/1413-81232021263.42372020 DOI: https://doi.org/10.1590/1413-81232021263.42372020

COMUNIDAD DE MADRID (n. d.). Covid 19 -TIA Zonas Básicas de Salud - Conjuntos de datos - Datos Abiertos Comunidad de Madrid. Retrieved from https://datos.comunidad.madrid/catalogo/dataset/covid19_tia_zonas_basicas_salud [Accessed: 07 February 2022]

CORDES, Jack and CASTRO, Maria (2020). “Spatial analysis of COVID-19 clusters and contextual factors in New York City”. Spatial and Spatio-temporal Epidemiology, 34, 100355. https://doi.org/10.1016/j.sste.2020.100355 DOI: https://doi.org/10.1016/j.sste.2020.100355

DE COS, Olga; CASTILLO-SALCINES, Valentín and CANTARERO-PRIETO, David (2022). “A geographical information system model to define COVID-19 problem areas with an analysis in the socio-economic context at the regional scale in the North of Spain”. Geospatial Health, 17. https://doi.org/10.4081/gh.2022.1067 DOI: https://doi.org/10.4081/gh.2022.1067

DE MATTOS, Ricardo; RUSSO, Rafael; NETO, Mercedes; GOMES-DEPRET, Davi; COSTA GIL, Adriana; SILVA FONSECA, Mary Hellem and SOUZA-SANTOS, Reinaldo (2020). “Effect of income on the cumulative incidence of COVID-19: an ecological study”. Revista Latino-Americana de Enfermagem, 28. https://doi.org/10.1590/1518-8345.4475.3344 DOI: https://doi.org/10.1590/1518-8345.4475.3344

DE MIGUEL ARRIBAS, Alfonso; ALETA, Alberto and MORENO, Yamir (2023). “Assessing the effectiveness of perimeter lockdowns as a response to epidemics at the urban scale”. Scientific Reports, 13 (1), 4474. https://doi.org/10.1038/s41598-023-31614-8 DOI: https://doi.org/10.1038/s41598-023-31614-8

DEMSAR, Janez; CURK, Tomaž; ERJAVEZ, Aleš; GROUP, Črt; HOCEVAR, Tomaž; MILUTINOVIČ, Mitar; MOŽINA, Martin; POLAJNAR, Matija; TOPLAK, Marko; STARIČ, Anže; ŠTAJDOHAR, Miha; UMEK, Lan; ŽAGAR, Lan; ŽBONTAR, Jure; ŽITNIK, Marinka and ZUPAN, Blaž (2013). “Orange: Data Mining Toolbox in Python”. Journal of Machine Learning Research, 14 (Aug.), 2349-2353. Retrieved from http://jmlr.org/papers/v14/demsar13a.html

EUROSTAT (n. d.). Eurostat Metropolitan Region Database. Retrieved from https://ec.europa.eu/eurostat/web/metropolitan-regions/database [Accessed: 15 November 2023]

FLORIDA, Richard and MELLANDER, Charlotta (2022). “The geography of COVID-19 in Sweden”. The Annals of Regional Science, 68, 125-150. https://doi.org/10.1007/s00168-021-01071-0 DOI: https://doi.org/10.1007/s00168-021-01071-0

FLORIDA, Richard; RODRÍGUEZ-POSE, Andrés and STORPER, Michael (2021). “Cities in a post-COVID world”. Urban Studies. https://doi.org/10.1177/00420980211018072 DOI: https://doi.org/10.1177/00420980211018072

FONTÁN-VELA, Mario; GULLÓN, Pedro and PADILLA-BERNÁLDEZ, Javier (2021). “Selective perimeter lockdowns in Madrid: a way to bend the COVID-19 curve?”. European Journal of Public Health, 31 (5), 1102-1104. https://doi.org/10.1093/eurpub/ckab061 DOI: https://doi.org/10.1093/eurpub/ckab061

FRANCH-PARDO, Ivan; DESJARDINS, Michael; BAREA-NAVARRO, Isabel and CERDÀ, Artemi. (2021). “A review of GIS methodologies to analyze the dynamics of COVID-19 in the second half of 2020”. Transactions in GIS, 25 (5), 2191-2239. https://doi.org/10.1111/tgis.12792 DOI: https://doi.org/10.1111/tgis.12792

FRANCH-PARDO, Ivan; NAPOLETANO, Brian; ROSETE-VERGES, Fernando and BILLA, Lawal (2020). “Spatial analysis and GIS in the study of COVID-19. A review”. Science of The Total Environment, 739, 140033. https://doi.org/10.1016/j.scitotenv.2020.140033 DOI: https://doi.org/10.1016/j.scitotenv.2020.140033

GARCÍA-GARCÍA, David; HERRANZ-HERNÁNDEZ, Rafael; ROJAS-BENEDICTO, Ayelen; LEÓN-GÓMEZ, Inmaculada; LARRAURI, Amparo; PEÑUELAS, Marina; GUERRERO-VADILLO, María; RAMIS, Rebeca and GÓMEZ-BARROSO, Diana (2022). “Perimeter confinements of basic health zones and COVID-19 incidence in Madrid, Spain”. BMC Public Health, 22 (1), 216. https://doi.org/10.1186/s12889-022-12626-x DOI: https://doi.org/10.1186/s12889-022-12626-x

GAYNOR, Tia Sherèe and WILSON, Meghan (2020). “Social Vulnerability and Equity: The Disproportionate Impact of COVID”. Public Administration Review, 80 (5), 832-838. https://doi.org/10.1111/puar.13264 DOI: https://doi.org/10.1111/puar.13264

GONZÁLEZ PÉREZ, Jesús and PIÑEIRA MANTIÑÁN, María José (2020). “La ciudad desigual en Palma (Mallorca): geografía del confinamiento durante la pandemia de la COVID-19”. Boletín de la Asociación de Geógrafos Españoles, 87. https://doi.org/10.21138/bage.2998 DOI: https://doi.org/10.21138/bage.2998

HAMIDI, Shima; SABOURI, Sadegh and EWING, Reid (2020). “Does Density Aggravate the COVID-19 Pandemic?” Journal of the American Planning Association, 86 (4), 495-509. https://doi.org/10.1080/01944363.2020.1777891 DOI: https://doi.org/10.1080/01944363.2020.1777891

HIERRO, María and MAZA, Alfonso (2023). “Spatial contagion during the first wave of the COVID‐19 pandemic: Some lessons from the case of Madrid, Spain”. Regional Science Policy & Practice, 15 (3), 474-492. https://doi.org/10.1111/rsp3.12522 DOI: https://doi.org/10.1111/rsp3.12522

INSTITUTO DE SALUD CARLOS III (ISCIII). Informe n.o 173. Situación de COVID-19 en España. Retrieved from https://www.isciii.es/QueHacemos/Servicios/VigilanciaSaludPublicaRENAVE/EnfermedadesTransmisibles/Paginas/-COVID-19.-Informes-previos.aspx [Accessed: 03 April 2023]

INSTITUTO NACIONAL DE ESTADÍSTICA (2021). Estadística experimental. Atlas de la distribución de renta de los hogares. Retrieved from https://www.ine.es/experimental/atlas/experimental_atlas.htm [Accessed: 24 July 2021]

KARAYE, Ibraheem and HORNEY, Jennifer (2020). “The Impact of Social Vulnerability on COVID-19 in the U.S.: An Analysis of Spatially Varying Relationships”. American Journal of Preventive Medicine, 59 (3), 317-325. https://doi.org/10.1016/j.amepre.2020.06.006 DOI: https://doi.org/10.1016/j.amepre.2020.06.006

KLING, Samuel (2020). “Is the City Itself the Problem? The Long History of Demonizing Urban Density”. Bloomberg City Lab. Retrieved from https://www.bloomberg.com/news/articles/2020-04-20/the-long-history-of-demonizing-urban-density

KOLAK, Marinya; BHATT, Jay; HONG PARK, Yoon; PADRÓN, Norma and MOLEFE, Ayrin (2020). “Quantification of Neighborhood-Level Social Determinants of Health in the Continental United States”. JAMA Network Open, 3 (1), 1919928. https://doi.org/10.1001/jamanetworkopen.2019.19928 DOI: https://doi.org/10.1001/jamanetworkopen.2019.19928

KONSTANTINOUDIS, Garyfallos; CAMELETTI, Michela; GÓMEZ-RUBIO, Virgilio; LEÓN GÓMEZ, Inmaculada; PIRANI, Mónica; BAIO, Gianluca; LARRAURI, Amparo; RIOU, Julien; EGGER, Matthias; VINEIS, Paolo and BLANGIARDO, Marta (2022). “Regional excess mortality during the 2020 COVID-19 pandemic in five European countries”. Nature Communications, 13 (1), 482. https://doi.org/10.1038/s41467-022-28157-3 DOI: https://doi.org/10.1038/s41467-022-28157-3

LI, Yige; UNDURRAGA, Eduardo and ZUBIZARRETA, José (2022). “Effectiveness of Localized Lockdowns in the COVID-19 Pandemic”. American Journal of Epidemiology, 191 (5), 812-824. https://doi.org/10.1093/aje/kwac008 DOI: https://doi.org/10.1093/aje/kwac008

LÓPEZ-GAY, Antonio; SPIJKER, Jeroen; COLE, Helen; MARQUES, Antonio; TRIGUERO-MAS, Margarita; ANGUELOVSKI, Isabelle; MARÍ-DELL’OLMO, Marc; MÓDENES, Juan; ÁLAMO-JUNQUERA, Dolores; LÓPEZ-GALLEGO, Fernando and BORRELL, Carme (2022). “Sociodemographic determinants of intraurban variations in COVID-19 incidence: the case of Barcelona”. Journal of Epidemiology and Community Health, 76 (1), 1-7. https://doi.org/10.1136/jech-2020-216325 DOI: https://doi.org/10.1136/jech-2020-216325

MARÍ-DELL’OLMO, Marc; GOTSENS, Mercè; PASARÍN, María Isabel; RODRÍGUEZ-SANZ, Maica; ARTAZCOZ, Lucía; GARCIA DE OLALLA, Patricia; RIUS, Cristina and BORRELL, Carme (2021). “Socioeconomic Inequalities in COVID-19 in a European Urban Area: Two Waves, Two Patterns”. International Journal of Environmental Research and Public Health, 18 (3), 1256. https://doi.org/10.3390/ijerph18031256 DOI: https://doi.org/10.3390/ijerph18031256

MAZA, Adolfo and HIERRO, María (2021). “Modelling changing patterns in the COVID‐19 geographical distribution: Madrid’s case”. Geographical Research, 60 (2), 218-231. https://doi.org/10.1111/1745-5871.12521 DOI: https://doi.org/10.1111/1745-5871.12521

MENA, Gonzalo; MARTINEZ, Pamela; MAHMUD, Ayesha; MARQUET, Pablo; BUCKEE, Caroline and SANTILLANA, Mauricio (2021). “Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile”. Science, 372 (6545). https://doi.org/10.1126/science.abg5298 DOI: https://doi.org/10.1126/science.abg5298

MOLLALO, Abolfazl; VAHEDI, Behzad and RIVERA, Kiara M. (2020). “GIS-based spatial modeling of COVID-19 incidence rate in the continental United States”. Science of The Total Environment, 728, (138884). https://doi.org/10.1016/j.scitotenv.2020.138884 DOI: https://doi.org/10.1016/j.scitotenv.2020.138884

MOLNAR, Christoph (2019). Interpretable machine learning. A Guide for Making Black Box Models Explainable. Retrieved from https://christophm.github.io/interpretable-ml-book/

MUSTERD, Sako; MARCINCZAK, Szymon; VAN HAM, Maarten and TAMMARU, Tiit (2017). “Socioeconomic segregation in European capital cities. Increasing separation between poor and rich”. Urban Geography, 38 (7), 1062-1083. https://doi.org/10.1080/02723638.2016.1228371 DOI: https://doi.org/10.1080/02723638.2016.1228371

NIU, Xinyi; YUE, Yufeng; ZHOU, Xingang and ZHANG, Xiaohu (2020). “How Urban Factors Affect the Spatiotemporal Distribution of Infectious Diseases in Addition to Intercity Population Movement in China”. International Journal of Geo-Information, 9 (11), 615. https://doi.org/10.3390/ijgi9110615 DOI: https://doi.org/10.3390/ijgi9110615

OMS (n.d.). WHO Coronavirus (COVID-19) Dashboard. Retrieved from https://covid19.who.int/table

RAYMUNDO, Carlos Eduardo; CINI OLIVEIRA, Marcella; DE ARAÚJO ELEUTERIO, Tatiana; ANDRÉ, Suzana Rosa; GONÇALVES DA SILVA, Marcele; DA SILVA QUEIROZ, Eny Regina and DE ANDRADE MEDRONHO, Roberto (2021). “Spatial analysis of COVID-19 incidence and the sociodemographic context in Brazil”. PLOS ONE, 16 (3), e0247794. https://doi.org/10.1371/journal.pone.0247794 DOI: https://doi.org/10.1371/journal.pone.0247794

RODRÍGUEZ‐POSE, Andrés and BURLINA, Chiara (2021). “Institutions and the uneven geography of the first wave of the COVID‐19 pandemic”. Journal of Regional Science, 61 (4), 728-752. https://doi.org/10.1111/jors.12541 DOI: https://doi.org/10.1111/jors.12541

ROMERO STARKE, Karla; REISSIG, David; PETEREIT-HAACK, Gabriela; SCHMAUDER, Stefanie; NIENHAUS, Albert and SEIDLER, Andreas (2021). “The isolated effect of age on the risk of COVID-19 severe outcomes: a systematic review with meta-analysis”. BMJ Global Health, 6 (12), e006434. https://doi.org/10.1136/bmjgh-2021-006434 DOI: https://doi.org/10.1136/bmjgh-2021-006434

RUIZ-PÉREZ, Maurici; MORAGUES, Alexandre; SEGUÍ-PONS, Joana Maria; MUNCUNILL, Josep; POU GOYANES, Albert and COLOM FERNÁNDEZ, Antoni (2023). “Geographical Distribution and Social Justice of the COVID-19 Pandemic: The Case of Palma (Balearic Islands)”. GeoHealth, 7 (2). https://doi.org/10.1029/2022GH000733 DOI: https://doi.org/10.1029/2022GH000733

SALMON, Charleen; FLANAGAN, Jordyn; FARKAS, Brenlea; MASTHIKINA, Liza; EGUNSOLA, Oluwaseun; SAXINGER, Lynora; SKIDMORE, Becky and CLEMENT, Fiona (2021). “Transmissibility of COVID-19 among vaccinated individuals”. Retrieved from https://sporevidencealliance.ca/wp-content/uploads/2021/10/Transmissibility-of-COVID-Vaccinated-Individuals_Final-Report_2021.09.24.pdf

SANTESMASSES, Didac; CASTRO, Jose Pedro; ZENIN, Alexandr; SHINDYAPINA, Anastasia; GERASHCHENKO, Maxim; ZHANG, Bohan; KEREPESI, Csaba; YIM, Sun Hee; FEDICHEV, Peter and GLADYSHEV, Vadim (2020). “COVID‐19 is an emergent disease of aging”. Aging Cell, 19 (10). https://doi.org/10.1111/acel.13230 DOI: https://doi.org/10.1111/acel.13230

SASSON, Isaac (2021). “Age and COVID-19 mortality: A comparison of Gompertz doubling time across countries and causes of death”. Demographic Research, 44, 379-396. https://doi.org/10.4054/DemRes.2021.44.16 DOI: https://doi.org/10.4054/DemRes.2021.44.16

SCHELLEKENS, Philip and SOURROUILLE, Diego (2020). The unreal dichotomy in COVID-19 mortality between high-income and developing countries. Retrieved from https://www.brookings.edu/blog/future-development/2020/05/05/the-unreal-dichotomy-in-covid-19-mortality-between-high-income-and-developing-countries/ [Accessed: 02/05/2023]

SIGLER, Thomas; MAHMUDA, Sirat; KIMPTON, Anthony; LOGINOVA, Julia; WOHLAND-JAKHAR, Pia; CHARLES-EDWARDS, Elin and CORCORAN, Jonathan (2020). “The Socio-Spatial Determinants of COVID-19 Diffusion: The Impact of Globalisation, Settlement Characteristics and Population”. Research Square, preprint. https://doi.org/10.21203/rs.3.rs-33615/v1 DOI: https://doi.org/10.21203/rs.3.rs-33615/v1

SORANDO, Daniel and LEAL, Jesús (2019). “Distantes y desiguales: el declive de la mezcla social en Barcelona y Madrid/Distant and Unequal: The Decline of Social Mixing in Barcelona and Madrid”. Revista Española de Investigaciones Sociológicas, 167, 125-148. https://doi.org/10.5477/cis/reis.167.125 DOI: https://doi.org/10.5477/cis/reis.167.125

SOURIS, Marc (2019). Épidémiologie et géographie, principes, méthodes et outils de l´analyse spatiales. London: ISTE Editions Ltd. DOI: https://doi.org/10.51926/ISTE.9781784055738

TCHICAYA, Anastase; LORENTZ, Nathalie; LEDUC, Kristell and DE LANCHY, Gaetan (2021). “COVID-19 mortality with regard to healthcare services availability, health risks, and socio-spatial factors at department level in France: A spatial cross-sectional analysis”. PloS One, 16 (9), e0256857. https://doi.org/10.1371/journal.pone.0256857 DOI: https://doi.org/10.1371/journal.pone.0256857

TEPE, Emre (2023). “The impact of built and socio-economic environment factors on Covid-19 transmission at the ZIP-code level in Florida”. Journal of Environmental Management, 326, 116806. https://doi.org/10.1016/j.jenvman.2022.116806 DOI: https://doi.org/10.1016/j.jenvman.2022.116806

TOKEY, Ahmad Ilderim (2021). “Spatial association of mobility and COVID-19 infection rate in the USA: A county-level study using mobile phone location data”. Journal of Transport & Health, 22, 101135. https://doi.org/10.1016/j.jth.2021.101135 DOI: https://doi.org/10.1016/j.jth.2021.101135

WANG, Haidong; PAULSON, Katherin; PEASE, Spencer; WATSON, Stefanie; COMFORT, Haley; ZHENG, Peng; ARAVKIN, Aleksandr; BISIGNANO, Catherin; BARBER, Ryan; ALAM, Tahiya; FULLER, John; MAY, Erin; JONES, Darwin Phan; FRISCH, Meghan; ABBAFATI, Cristiana; ADOLPH, Christopher; ALLORANT, Adrien; AMLAG, Joanne; BANG-JENSEN, Bree; … MURRAY, Christopher (2022). “Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21”. The Lancet, 399 (10334), 1513-1536. https://doi.org/10.1016/S0140-6736(21)02796-3 DOI: https://doi.org/10.1016/S0140-6736(21)02796-3

YOU, Heyuan; WU, Xin and GUO, Xuxu (2020). “Distribution of COVID-19 Morbidity Rate in Association with Social and Economic Factors in Wuhan, China: Implications for Urban Development”. International Journal of Environmental Research and Public Health, 17 (10). https://doi.org/10.3390/ijerph17103417 DOI: https://doi.org/10.3390/ijerph17103417

ZHANG, Xinxuan; MAGGIONI, Viviana; HOUSER, Paul; XUE, Yuan and MEI, Yiwen (2022). “The impact of weather condition and social activity on COVID-19 transmission in the United States”. Journal of Environmental Management, 302, 114085. https://doi.org/10.1016/j.jenvman.2021.114085 DOI: https://doi.org/10.1016/j.jenvman.2021.114085