Territorial impact of the COVID-19 pandemic in Galicia (Spain)a geographical approach

  1. Ángel Miramontes Carballada
  2. Jose Balsa-Barreiro
Revista:
BAGE. Boletín de la Asociación Española de Geografía

ISSN: 0212-9426 2605-3322

Ano de publicación: 2021

Título do exemplar: La Geografía frente a la COVID-19. Análisis territoriales y perspectivas multidisciplinares

Número: 91

Tipo: Artigo

DOI: 10.21138/BAGE.3157 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Outras publicacións en: BAGE. Boletín de la Asociación Española de Geografía

Resumo

La pandemia de coronavirus está causando un gran impacto en todo el mundo. Su magnitud real presenta diferencias regionales muy importantes, que son apreciables en el número de infectados y víctimas en los diferentes países. El estallido de la pandemia y el desconocimiento del virus hacen que, aún hoy, existan muchas incógnitas sobre aspectos esenciales relacionados con el mismo. En este sentido, el conocimiento geográfico puede ayudar a responder muchas preguntas a partir del análisis territorial de los datos. El objetivo de este artículo será analizar el comportamiento de la pandemia de coronavirus dentro de la región española de Galicia. Los autores de este estudio proponen un análisis multiescala que permite descifrar los patrones de propagación más comunes. Para ello, contamos con datos de alta resolución espacial que han sido facilitados por la autoridad competente bajo confidencialidad. Los resultados de este trabajo permiten representar e interpretar el impacto territorial de la pandemia, entendiendo en la medida de lo posible su comportamiento, permitiendo predecir dinámicas futuras.

Información de financiamento

This paper was possible because from the Galician Innovation Agency (GAIN) of the Xunta de Galicia, an urgent public competitive call was offered during the month of March 2020, to the entire scientific community (public and private) to propose solutions for "fight? against COVID-19. The project "The risk mapping of COVID-19 in urban and rural areas of Galicia" was selected, which aimed to carry out a series of territorial analysis reports of the pandemic and give them to SERGAS. This project is the basis of this article. Therefore, these data were transmitted to us after the signing of a confidentiality commitment.

Referencias bibliográficas

  • Arab-Mazar, Z, Sah, R., Rabaan, A.A., Dhama, K., & Rodriguez-Morales, A.J. (2020). Mapping the incidence of the COVID-19 hotspot in Iran – implications for travellers Travel Medicine Infectious Disease, 34, 101630. https://doi.org/10.1016/j.tmaid.2020.101630
  • Balsa-Barreiro, J., & Landsperger, S. (2015). A Costa da Morte (Galicia, España): un modelo demográfico antagónico al español. Análisis de su evolución demográfica en el siglo XXI. Journal of Iberian and Latin American Research, 21(1), 63-86. https://doi.org/10.1080/13260219.2015.1041198
  • Balsa-Barreiro, J. (2013). Insostenibilidad de modelos territoriales desde un punto de vista demográfico: El caso de Costa da Morte (Galicia, España). Papeles de población, 19(78), 167-206. https://www.redalyc.org/articulo.oa?id=11229719007
  • Balsa-Barreiro, J., Ambühl, L., Menendez, M., &Pentland A.S. (2019). Mapping time-varying accessibility and territorial cohesion with time-distorted maps. IEEE Access, 7, 41702-41714. https://dspace.mit.edu/bitstream/handle/1721.1/134793/08675273.pdf?sequence=2&isAllowed=y
  • Balsa-Barreiro, J., Morales, A., & Lois-González, RC (2021). Mapping population dynamics at local scales using spatial networks. Complexity, 2021, ID 8632086. https://doi.org/10.1155/2021/8632086
  • BBC News (2020, March 30). Coronavirus: A visual Guide to the Pandemic. BBC news. https://www.bbc.co.uk/news/world-51235105
  • Boulos, K., & Geraghty E.M (2020). Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbreaks and epidemics. International Journal Health Geographics, 19, 8. https://doi.org/10.1186/s12942-020-00202-8
  • Buzai, G.D. (2020). De Wuhan a Luján. Evolución espacial del COVID-19. Posición, 3, 2683-8915. https://ri.unlu.edu.ar/xmlui/bitstream/handle/rediunlu/683/Buzai_Gustavo_COVID-19.pdf?sequence=1&isAllowed=y
  • Bynum, P., Raja R.A.I., & Olbina, S. (2013). Building information modelling in support of sustainable design and construction. Journal of Construction Engineering and Management, 139, 24-34. http:://dx.doi.org/10.1061/(ASCE)CO.1943-7862.0000560
  • Buckee, C.O., Balsari, S., Chan, J., Crosas, M., Dominici, F., Gasser, U., & Lipsitch, M. (2020). Aggregated mobility data could help fight COVID-19. Science, 368(6487), 145-146. https://doi.org/10.1126/science.abb8021
  • Carballada, A.M., & Balsa-Barreiro, J. (2021) Geospatial Analysis and Mapping Strategies for Fine-Grained and Detailed COVID-19 Data with GIS. ISPRS International Journay Geo-Information, 10(9), 602. https://doi.org/10.3390/ijgi10090602
  • Cattarino, L., Rodriguez-Barraquer, I., Imai, N., Cummings, D.A.T., & Ferguson, N.M. (2020). Mapping global variation in dengue 690 transmission intensity. Science Translational Medicine, 12(528). https://doi.org/10.1126/scitranslmed.aax4144
  • Centro Nacional de Epidemiología, Instituto de Salud Carlos III (2020). https://www.isciii.es/Paginas/Inicio.aspx
  • Chang, S.L., Harding, N., & Zachreson, C. (2020). Modelling transmission and control of the COVID-19 pandemic in Australia. Nature Communications, 11, 5710. https://doi.org/10.1038/s41467-020-19393-6
  • Chen, S., Li, Q., Gao, S., Kang, Y., & Shi, X. (2020a). Mitigating COVID-19 outbreak via high testing capacity and strong transmission-intervention in the United States. medRxiv https://www.medrxiv.org/content/10.1101/2020.04.03.20052720v1
  • Chen, S., Zhang, Q., Lu, Y., Guo, Z.M., Zhang, X., Zhang, W.J., & Lu, J.H. (2020b). Distribution of the COVID-19 epidemic and correlation with population emigration from Wuhan, China. Chinese Medical Journal, 133(9), 1044-1050. https://dx.doi.org/10.1097%2FCM9.0000000000000782
  • Cicalò, E., & Valentino, M. (2019). Mapping and visualisation of health data. The contribution of the graphic sciences to medical re-626 search from New York yellow fever to China coronavirus. Disegnarecon, 12(23), 12-21. https://doi.org/10.20365/disegnarecon.23.2019.12
  • Dagnino, R., Weber, E.J., & Panitz, L.M. (2020). Monitoramento do Coronavírus (Covid-19) nos municípios do Rio Grande do Sul, Brasil. SocArXiv. https://doi.org/10.31235/osf.io/3uqn5
  • Deka, M.A., & Morshed N. (2018). Mapping disease transmission risk of Nipah virus in South and Southeast Asia. Tropical Medicine and Infectious Disease, 3(2), 57. https://doi.org/10.3390/tropicalmed3020057
  • De Kadt J., Gotz G., Hamann C., Maree G., Parker A., & Gauteng City-Region Observatory; (2020). Mapping Vulnerability to COVID-19 in Gauteng. GCRO Map of the Month https://gcro.ac.za/outputs/map-of-the-month/detail/mapping-vulnerability-to-covid-19/
  • Desjardins, M.R., Hohl, A., & 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. Applied Geography, 118(102202), 102-202. https://doi.org/10.1016/j.apgeog.2020.102202
  • Dong, E., Du, H., & Gardner, L. (2020). An interactive web-based dashboard to track COVID-19 in real time. Lancet Infectious Diseases, 20, 533-534. https://doi.org/10.1016/S1473-3099(20)30120-1
  • Dudley, J. (2008). Public Health and Epidemiological Considerations for Avian Influenza Risk Mapping and Risk Assessment. Ecology and Society, 13(2). http://www.ecologyandsociety.org/vol13/iss2/art21/
  • Franch-Pardo, I., Napoletano, B.M., Rosete-Verges F., & Billa L. (2020). Spatial analysis and GIS in the study of COVID-19. A review. The Science of the Total Environment. http://doi.org/10.1016/j.scitotenv.2020.140033
  • Gesler, W. & Kearns, R. (2002). Culture/Place/Health. https://doi.org/10.4324/9780203996317
  • Gibson, L., & Rush, D. (2020). Novel coronavirus in Cape Town informal settlements: feasibility of using informal dwelling outlines to identify high risk areas for COVID-19 transmission from a social distancing perspective. JMIR Public Health Surveillance, 6(2), e18844. https://doi.org/10.2196/18844
  • Giuliani, D., Dickson, M.M., Espa, G., & Santi, F. (2020). Modelling and predicting the spatio-temporal spread of COVID-19 in Italy. BMC Infectious Disease, 20(700). https://doi.org/10.1186/s12879-020-05415-7
  • Graham, H. (2000). Understanding health inequalities. Open University Press.
  • Gross, B., Zheng, Z., Liu, S., Chen, X., Sela, A., Li, J., & Havlin, S. (2020). Spatio-temporal propagation of COVID-19 pandemics. MedRxiv https://doi.org/10.1101/2020.03.23.20041517
  • Guan W.J., Ni Z.Y., Hu Y., Liang W.H., Ou C.Q., He J.X., & Du B. (2020). Clinical characteristics of coronavirus disease 2019 in China. New England Journal of Medicine, 382(18):1708–1720. https://doi.org/10.1056/NEJMoa2002032
  • Huang H., Wang Y., Wang Z., Liang Z., Qu S., Ma S., & Liu X. (2020). Epidemic Features and Control of 2019 Novel Coronavirus Pneumonia in Wenzhou, China (3/3/2020). http://dx.doi.org/10.2139/ssrn.3550007
  • National Institute of Statistics (2021). [Website] https://www.ine.es
  • Kearns, R., & Moon, G. (2002). From medical to health geography: novelty, place and theory after a decade of change. Progress Human Geography, 26(5), 605-625. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.137.3695&rep=rep1&type=pdf
  • Koch, T. (2005). Cartographies of Disease: Maps, Mapping, and Medicine. ESRI Press.
  • Kuupiel, D., Adu, K.M., Bawontuo, V., Adogboba, D.A., Drain, P.K., Moshabela, M., & Mashamba Thompson, T.P. (2020). Geographical accessibility to glucose-6-phosphate dioxygenase deficiency point-of-care testing for antenatal care in Ghana. Diagnostics, 10(4), 229. https://dx.doi.org/10.3390%2Fdiagnostics10040229
  • Lee, J.G., & Kang, M. (2015). Geospatial big data: challenges and opportunities. Big Data Research, 2(2), 74-81 https://doi.org/10.1016/j.bdr.2015.01.003
  • Lenzen, M., Li, M., Malik, A., Pomponi, F., Sun, Y., Wiedmann, T., Faturay, F., Fry, J., Gallego, B., Geschke, A., Gómez-Paredes, J., Kanemoto, K., Kenway, S., Nansai, K., Prokopenko, M., Wakiyama, T., Wang, Y., & Yousefzadeh, M. (2020). Global socio-economic losses and environmental gains from the Coronavirus pandemic. PLOS ONE, 15, 1.13. https://doi.org/10.1371/journal.pone.0235654
  • Lois-González, R. (2004). A model of Spanish-Portuguese urban growth: the Atlantic axis. Dela, (21), 281-294. https://doi.org/10.4312/dela.21.281-294
  • Lyseen, A. K., Nøhr, C., Sørensen, E. M., Gudes, O., Geraghty, E. M., Shaw, N. T., Bivona-Tellez, C., & IMIA Health GIS Working Group (2014). A Review and Framework for Categorizing Current Research and Development in Health Related Geographical Information Systems (GIS) Studies. Yearbook of medical informatics, 9(1), 110-124. https://doi.org/10.15265/IY-2014-0008
  • Meade, M.S. (2014). Medical geography. In The Wiley Blackwell Encyclopedia of Health, Illness, Behavior, and Society (pp. 1375-1381). https://doi.org/10.1002/9781118410868.wbehibs204
  • Messina, J., Kraemer, M.U., Brady, O.J., Pigott, D.M., Shearer, F.M., Weiss, D.J., Golding, N., Ruktanonchai, C.W., Gething, P.W., Cohn, E., Brownstein, J.S., Khan, K., Tatem, A.J., Jaenisch, T., Murray, C.J., Marinho, F., Scott, T.W., & Hay, S.I. (2016). Mapping global environmental 695 suitability for Zika virus. Elife, 19(5),e15272. https://doi.org/10.7554/eLife.15272
  • Messina, J., Brady, O., & Pigott, D. (2014). A global compendium of human dengue virus occurrence. Sciencie Data 1, 140004. https://doi.org/10.1038/sdata.2014.4
  • MoMo dashboard (n.d.). Instituto de Salud Carlos III (Spain). https://momo.isciii.es/public/momo/dashboard/momo_dash-738 board.html
  • National Health Commission (NHC) of the People’s Republic of China (2020). NHC daily reports. http://www.nhc.gov.cn/yjb/pzhgli/new_list.shtml
  • Orea, L., & Álvarez. I. C. (2020). How Effective Has the Spanish Lockdown Been to Battle COVID-19? A Spatial Analysis of the Coronavirus Propagation across Provinces (Working Paper). FEDEA, Universidad de Oviedo. https://documentos.fedea.net/pubs/dt/2020/dt2020-03.pdf
  • Pattison, W.D. (1964) The four traditions of geography. Journal Geography, 63, 211-216. https://doi.org/10.1080/00221346408985265
  • Pazos Otón, M. (2003). El estudio geográfico de la movilidad: un análisis histórico-evolutivo. In Xeográfic (pp. 101-119). Universidade de Santiago de Compostela.
  • Pham, Q., Nguyen, D.C., Huynh-The, T., Hwang W., & Pathirana, P.N. (2020). Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts. IEEE Access, 8, 130820-130839. https://doi.org/10.1109/ACCESS.2020.3009328
  • Pigott, D.M., Golding, N., Mylne, A., Huang, Z., Henry, A.J., Weiss, D.J., Brady, O.J., Kraemer, M.U., Smith, D.L., Moyes, C.L., Bhatt, S., Gething, P.W., Horby, P.W., Bogoch, I.I., Brownstein, J.S., Mekaru, S.R., Tatem, A.J., Khan, K., & Hay, S.I. (2014). Mapping the zoonotic niche of Ebola virus disease in Africa. Elife, 3, e04395. https://doi.org/10.7554/eLife.04395
  • Pollán, M., Pérez-Gómez, B., Pastor-Barriuso, R., Oteo, J., Hernán, M. A., Pérez-Olmeda, M., Sanmartín, J.L., Fernández-García, A., Cruz, I., Fernández de Larrea, N., Molina, M., Rodríguez-Cabrera, F., Martín, M., Merino-Amador, P., Paniagua, J.L., Muñoz-Montalvo, J.F. Blanco, F., & Yotti, R. (2020). Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study. The Lancet, 396(10250), 535-544. https://doi.org/10.1016/S0140-6736(20)31483-5
  • Rezaei, M., Nouri, A.A., Park, G.S., & Kim, D.H. (2020). Application of geographic information system in monitoring and detecting the COVID-19 outbreak Iran Journal Public Health, 49, 114-116. https://doi.org/10.18502/ijph.v49iS1.3679
  • Rodriguez-Morales, A.J., Galindo-Marquez, M.L., García-Loaiza, C.J., Sabogal-Roman, J.A., Marin-Loaiza, S., Ayala, A.F., Lagos-Grisales, G.J., Lozada-Riascos, C.O., Parra-Valencia, E., Rojas-Palacios, J.H., López, E., López, P., & Grobusch, M.P. (2017). Mapping Zika virus disease incidence in Valle del Cauca. Infection, 45(1), 93-102. https://doi.org/10.1007/s15010-016-0948-1
  • Romero JM. (2020). Los muertos de la pandemia en España: 44.868. El País. https://elpais.com/sociedad/2020-07-25/las-44868-muertes-de-la-pandemia-en-espana.html
  • Rosenkrantz, L., Schuurman, N., Bell, N., & Amram, O., (2021). The need for GIScience in mapping COVID-19. Health & Place, 67, 102389. https://doi.org/10.1016/j.healthplace.2020.102389
  • Rossman, H., Keshet, A., Shilo, S., Gavrieli, A., Bauman, T., Cohen, O., & Segal, E. (2020). A framework for identifying regional outbreak and spread of COVID-19 from one-minute population-wide surveys. Nature Medicine, 26, 634-638. https://doi.org/10.1038/s41591-020-0857-9
  • Saha, A., Gupta, K., & Patil, M. (2020). Monitoring and Epidemiological Trends of Coronavirus Disease (COVID-19) around the World. Osfpreprints. https://osf.io/2mwky
  • Santana, P. (2005). Geografias da Saúde e do Desenvolvimento. Evolução e Tendências em Portugal, Coimbra. Ed. Almedina.
  • Santana Juárez, M.V. (2020). COVID-19 en México: comportamiento espacio temporal y condicionantes socioespaciales, febrero y marzo de 2020. Posición, 3, 2683-8915.
  • Sarwar, S., Waheedab, R., Sarwar, S., & Khand, A. (2020). COVID-19 challenges to Pakistan: is GIS analysis useful to draw solutions? Science Total Environment, https://doi.org/10.1016/j.scitotenv.2020.139089
  • Schnaiberg, A., & Gould, K. (1994). Environment and Society: The Enduring Conflict. St. Martin’s Press.
  • Trias-Llimós, S., Alustiza, A., Prats, C., Tobias, A., & Riffe, T. (2020). The need for detailed COVID-19 data in Spain, The Lancet Public Health, 5(11), e576. https://doi.org/10.1016/S2468-2667(20)30234-6
  • Smith, D., Lapedes, A., Jong, J.D., Bestebroer, T., Rimmelzwaan, G., Osterhaus, A., & Fouchier, R. (2004). Mapping the Antigenic and Genetic Evolution of Influenza Virus. Science, 305, 371-376.
  • Su, L., Hong, N., Zhou, X., He, J., Ma, Y., Jiang, H., Han, L., Chang, F., Shan, G., Zhu, W., & Long, Y. (2020). Evaluation of the Secondary Transmission Pattern and Epidemic Prediction of COVID-19 in the Four Metropolitan Areas of China. Frontiers in medicine, 7, 171. https://doi.org/10.3389/fmed.2020.00171
  • Tang W, Liao H, Marley G, Wang Z, Cheng W, Wu D, Yu R. (2020). The Changing Patterns of Coronavirus Disease 2019 (COVID-19) in China: A Tempogeographic Analysis of the Severe Acute Respiratory Syndrome Coronavirus 2. Clinical Infectious Diseases, 71(15), 818-824. https://doi.org/10.1093/cid/ciaa423
  • The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team (2020). Vital Surveillances: The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19) — China, 2020. China CDC Weekly, 2(8), 113-122. https://doi.org/10.46234/ccdcw2020.032
  • The Lancet Public Health, COVID-19 in Spain: a predictable storm?, The Lancet Public Health, 5(11), e568. https://doi.org/10.1016/S2468-2667(20)30239-5
  • Tobaiqy, M., Qashqary, M., Al-Dahery, S., Mujallad, A., Hershan, A. A., Kamal, M. A., & Helmi, N. (2020). Therapeutic management of patients with COVID-19: a systematic review. Infection Prevention in Practice, 2(3), 100061. https://doi.org/10.1016/j.infpip.2020.100061
  • Turner, B.L. (2002). Contested identities: human-environment geography and disciplinary implications in a restructuring academy. Annals Association American Geographers, 92(1), 52-74.
  • Wang, C., Horby, P. W., Hayden, F. G., & Gao, G. F. (2020). A novel coronavirus outbreak of global health concern. Lancet, 395, 470-473.
  • World Health Organization (2020a). Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). https://www.who.int/docs/default-source/coronaviruse/who-china-joint-mission-on-covid-19-final-report.pdf
  • World Health Organization (2020b). WHO Director-General’s opening remarks at the media briefing on COVID-19—11 March 2020. https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020
  • Wilkinson, R. (1996). Unhealthy socities: the afflictions of inequality. Routledge https://doi.org/10.1111/1467-9566.ep10938939
  • Xiong, Y., Wang, Y., Chen, F., & Zhu, M. (2020). Spatial statistics and influencing factors of the novel coronavirus pneumonia 2019 epidemic in Hubei Province, China. International Journal of Environmental Research and Public Health, 17(11), 3903. https://doi.org/10.3390/ijerph17113903
  • Zhang, X., Rao, H.X., Wu, Y., Huang, Y., & Dai, H. (2020). Comparison of the spatiotemporal characteristics of the COVID-19 and SARS outbreaks in mainland China. BMC Infectious Diseases, 20, 805. https://doi.org/10.1186/s12879-020-05537-y
  • Zhou, C., Su, F., Pei, T., Zhang, A., Du, Y., Luo, B., & Song, C. (2020). COVID-19: challenges to GIS with big data. Geography and Sustainability, 1(1), 77-87. https://doi.org/10.1016/j.geosus.2020.03.005