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Research Article

Ecology and space in the COVID-19 epidemic diffusion: a multifactorial analysis of Italy’s provinces

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Pages 679-702 | Received 18 Jun 2022, Accepted 28 Jun 2023, Published online: 08 Aug 2023

REFERENCES

  • Adda, J. (2016). Economic activity and the spread of viral diseases: Evidence from high frequency data. The Quarterly Journal of Economics, 131(2), 891–941. https://doi.org/10.1093/qje/qjw005
  • Anselin, L. (2002). Under the hood: Issues in the specification and interpretation of spatial regression models. Agricultural Economics, 27(3), 247–267. https://doi.org/10.1111/j.1574-0862.2002.tb00120.x
  • Balbi, A., & Guerry, A. M. (1830). Statistique comparée de l’état de l’instruction et du nombre des crimes. Jules Renouard.
  • Banfield, E. C. (1958). The moral basis of a backward society. Free Press.
  • Bell, R. M. (1979). Fate and honor, family and village. The University of Chicago Press.
  • Berkessel, J. B., Ebert, T., Gebauer, J. E., Jonsson, T., & Oishi, S. (2022). Pandemics initially spread among people of higher (not lower) social status: Evidence from COVID-19 and the Spanish Flu. Social Psychological and Personality Science, 13(3), 722–733. https://doi.org/10.1177/19485506211039990
  • Biswas, K., & Sen, P. (2020). Space–time dependence of Corona virus (COVID-19) outbreak. arXiv:2003.03149 [physics].
  • Boumahdi, I., Zaoujal, N., & Fadlallah, A. (2021). Is there a relationship between industrial clusters and the prevalence of COVID-19 in the provinces of Morocco? Regional Science Policy & Practice, 13(S1), 138–157. https://doi.org/10.1111/rsp3.12407
  • Bourdin, S., Jeanne, L., Nadou, F., & Noiret, G. (2021). Does lockdown work? A spatial analysis of the spread and concentration of COVID-19 in Italy. Regional Studies, 55(7), 1182–1193. https://doi.org/10.1080/00343404.2021.1887471
  • Buja, A., Paganini, M., Cocchio, S., Scioni, M., Rebba, V., & Baldo, V. (2020). Demographic and socio-economic factors, and healthcare resource indicators associated with the rapid spread of COVID-19 in Northern Italy: An ecological study. PLOS ONE, 15(12), e0244535. https://doi.org/10.1371/journal.pone.0244535
  • Chi, G., & Zhu, J. (2008). Spatial regression models for demographic analysis. Population Research and Policy Review, 27(1), 17–42. https://doi.org/10.1007/s11113-007-9051-8
  • Chi, G., & Zhu, J. (2020). Spatial regression models for the social sciences. Sage.
  • Chowell, G., Erkoreka, A., Viboud, C., & Echeverri-Dávila, B. (2014). Spatial-temporal excess mortality patterns of the 1918–1919 influenza pandemic in Spain. BMC Infectious Diseases, 14(1), 1–12. https://doi.org/10.1186/1471-2334-14-371
  • Cliff, A. D., Haggett, P., Ord, J. K., & Versey, G. R. (1981). Spatial diffusion: An historical geography of epidemics in an island community. Cambridge University Press.
  • Cliff, A. D., Haggett, P., & Smallman-Raynor, M. (2004). World atlas of epidemic diseases. Arnold.
  • Clouston, S. A. P., Natale, G., & Link, B. G. (2021). Socioeconomic inequalities in the spread of coronavirus-19 in the United States: A examination of the emergence of social inequalities. Social Science & Medicine, 268, 113554. https://doi.org/10.1016/j.socscimed.2020.113554
  • Cuebiq. (2020). Real-time location data reveals effect of lockdown on mobility in Italy due to COVID-19. https://www.cuebiq.com/resource-center/resources/real-time-location-data-reveals-effect-of-lockdown-on-mobility-in-italy/.
  • ECDPC (European Centre for Disease Prevention and Control). (2020). Geographic distribution of COVID-19 cases worldwide [WWW Document]. URL https://www.ecdc.europa.eu/sites/default/files/documents/COVID-19-geographic-disbtribution-worldwide.xlsx.
  • Fingleton, B., & Arbia, G. (2008). New spatial econometric techniques and applications in regional science. Papers in Regional Science, 87(3), 311–317. https://doi.org/10.1111/j.1435-5957.2008.00187.x
  • Franch-Pardo, I., Napoletano, B. M., Rosete-Verges, F., & Billa, L. (2020). Spatial analysis and GIS in the study of COVID-19. Science of The Total Environment, 739, 140033. https://doi.org/10.1016/j.scitotenv.2020.140033
  • Gatto, M., Bertuzzo, E., Mari, L., Miccoli, S., Carraro, L., Casagrandi, R., & Rinaldo, A. (2020). Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures. Proceedings of the National Academy of Sciences, 117(19), 10484–10491. https://doi.org/10.1073/pnas.2004978117
  • Gelfand, M. J., Jackson, J. C., Pan, X., Nau, D., Pieper, D., Denison, E., Dagher, M., Van Lange, P. A. M., Chiu, C.-Y., & Wang, M. (2021). The relationship between cultural tightness–looseness and COVID-19 cases and deaths: A global analysis. The Lancet Planetary Health, 5(3), e135–e144. https://doi.org/10.1016/S2542-5196(20)30301-6
  • Giuliani, D., Dickson, M. M., Espa, G., & Santi, F. (2020). Modelling and predicting the spatio-temporal spread of Coronavirus disease 2019 (COVID-19) in Italy. Social Science Research Network.
  • Grasselli, G., Zangrillo, A., Zanella, A., Antonelli, M., Cabrini, L., Castelli, A., Cereda, D., Coluccello, A., Foti, G., Fumagalli, R., Iotti, G., Latronico, N., Lorini, L., Merler, S., Natalini, G., Piatti, A., Ranieri, M. V., Scandroglio, A. M., Storti, E., … Pesenti, A. (2020). Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA, 323(16), 1574–1581. https://doi.org/10.1001/jama.2020.5394
  • Herrera, M., Mur, J., & Ruiz, M. (2019). A comparison study on criteria to select the most adequate weighting matrix. Entropy, 21, 1–29. https://doi.org/10.3390/e21020160
  • Hunter, P. R., Colón-González, F. J., Brainard, J., Majuru, B., Pedrazzoli, D., Abubakar, I., Dinsa, G., Suhrcke, M., Stuckler, D., Lim, T.-A., & Semenza, J. C. (2020). Can economic indicators predict infectious disease spread? A cross-country panel analysis of 13 European countries. Scandinavian Journal of Public Health, 48(4), 351–361. https://doi.org/10.1177/1403494819852830
  • Iacus, S. M., Santamaria, C., Sermi, F., Spyratos, S., Tarchi, D., & Vespe, M. (2020). Human mobility and COVID-19 initial dynamics. Nonlinear Dynamics, 101(3), 1901–1919. https://doi.org/10.1007/s11071-020-05854-6
  • Istat. (2021). Commuting for studying or working 2019. https://www.istat.it/it/archivio/257621
  • Italy. Ministero della Salute. (2020). Nuovo coronavirus [WWW Document]. URL http://www.salute.gov.it/portale/nuovocoronavirus/dettaglioContenutiNuovoCoronavirus.jsp?area = nuovoCoronavirus&id = 5351&lingua = italiano&menu = vuoto.
  • Jacquez, G. M. (2000). Spatial analysis in epidemiology: Nascent science or a failure of GIS? Journal of Geographical Systems, 2(1), 91–97. https://doi.org/10.1007/s101090050035
  • Kraemer, M. U. G., Sadilek, A., Zhang, Q., Marchal, N. A., Tuli, G., Cohn, E. L., Hswen, Y., Perkins, T. A., Smith, D. L., Reiner, R. C., & Brownstein, J. S. (2020). Mapping global variation in human mobility. Nature Human Behaviour, 4(8), 800–810. https://doi.org/10.1038/s41562-020-0875-0
  • Kuznets, S. (1973). Modern economic growth: Findings and reflections. The American Economic Review, 63, 247–258. http://www.jstor.org/stable/1914358
  • LeSage, J. P. (2008). An introduction to spatial econometrics. Revue d’Économie Industrielle, 123, 19–44. https://doi.org/10.4000/rei.3887
  • LeSage, J. P., & Pace, R. K. (2014). The biggest myth in spatial econometrics. Econometrics, 2(4), 217–249. https://doi.org/10.3390/econometrics2040217
  • Li, R., Wang, W., & Di, Z. (2017). Effects of human dynamics on epidemic spreading in Côte d’Ivoire. Physica A: Statistical Mechanics and its Applications, 467, 30–40. https://doi.org/10.1016/j.physa.2016.09.059
  • Link, B. G., & Phelan, J. (1995). Social conditions as fundamental causes of disease. Journal of Health and Social Behavior, 80–94. https://doi.org/10.2307/2626958
  • Mollalo, A., Vahedi, B., & Rivera, K. 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
  • Moore, D. A., & Carpenter, T. E. (1999). Spatial analytical methods and geographic information systems: Use in health research and epidemiology. Epidemiologic Reviews, 21(2), 143–161. https://doi.org/10.1093/oxfordjournals.epirev.a017993
  • Nikolai, L. A., Meyer, C. G., Kremsner, P. G., & Velavan, T. P. (2020). Asymptomatic SARS Coronavirus 2 infection: Invisible yet invincible. International Journal of Infectious Diseases, 100, 112–116. https://doi.org/10.1016/j.ijid.2020.08.076
  • Orea, L., & Álvarez, I. C. (2022). How effective has the Spanish lockdown been to battle COVID-19? A spatial analysis of the coronavirus propagation across provinces. Health Economics, 31, 154–173. https://doi.org/10.1002/hec.4437
  • Paez, A., Lopez, F. A., Menezes, T., Cavalcanti, R., & Pitta, M. G. d. R. (2021). A spatio-temporal analysis of the environmental correlates of COVID-19 incidence in Spain. Geographical Analysis, 53(3), 397–421. https://doi.org/10.1111/gean.12241
  • Pan, A., Liu, L., Wang, C., Guo, H., Hao, X., Wang, Q., Huang, J., He, N., Yu, H., Lin, X., Wei, S., & Wu, T. (2020). Association of public health interventions with the epidemiology of the COVID-19 outbreak in Wuhan, China. JAMA, 323(19), 1915–1923. https://doi.org/10.1001/jama.2020.6130
  • Pepe, E., Bajardi, P., Gauvin, L., Privitera, F., Lake, B., Cattuto, C., & Tizzoni, M. (2020). COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown. Scientific Data, 7(1), 230. https://doi.org/10.1038/s41597-020-00575-2
  • Putnam, R. D. (1993). Making democracy work: Civic traditions in modern Italy. Princeton University Press.
  • Qiu, Y., Chen, X., & Shi, W. (2020). Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China. Journal of Population Economics, 33(4), 1127–1172. https://doi.org/10.1007/s00148-020-00778-2
  • Rodríguez-Pose, A., & Burlina, C. (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
  • Sannigrahi, S., Pilla, F., Basu, B., & Basu, A. S. (2020). The overall mortality caused by COVID-19 in the European region is highly associated with demographic composition: A spatial regression-based approach. arXiv:2005.04029.
  • Sebastiani, G., Massa, M., & Riboli, E. (2020). COVID-19 epidemic in Italy: Evolution, projections and impact of government measures. European Journal of Epidemiology, 35(4), 341–345. https://doi.org/10.1007/s10654-020-00631-6
  • Semenza, J. C., & Giesecke, J. (2008). Intervening to reduce inequalities in infections in Europe. American Journal of Public Health, 98(5), 787–792. https://doi.org/10.2105/AJPH.2007.120329
  • Siddique, A. B., Haynes, K. E., Kulkarni, R., & Li, M.-H. (2020). Impact of poverty on COVID-19 infections and fatalities: A regional perspective. Social Science Research Network.
  • Smith, C. M., Le Comber, S. C., Fry, H., Bull, M., Leach, S., & Hayward, A. C. (2015). Spatial methods for infectious disease outbreak investigations: Systematic literature review. Eurosurveillance, 20(39), 1–21. https://doi.org/10.2807/1560-7917.ES.2015.20.39.30026
  • Stakhovych, S., & Bijmolt, T. H. A. (2009). Specification of spatial models: A simulation study on weights matrices. Papers in Regional Science, 88(2), 389–408. https://doi.org/10.1111/j.1435-5957.2008.00213.x
  • Thomson, R., Yuki, M., Talhelm, T., Schug, J., Kito, M., Ayanian, A. H., Becker, J. C., Becker, M., Chiu, C., Choi, H.-S., Ferreira, C. M., Fülöp, M., Gul, P., Houghton-Illera, A. M., Joasoo, M., Jong, J., Kavanagh, C. M., Khutkyy, D., Manzi, C., … Visserman, M. L. (2018). Relational mobility predicts social behaviors in 39 countries and is tied to historical farming and threat. Proceedings of the National Academy of Sciences, 115(29), 7521–7526. https://doi.org/10.1073/pnas.1713191115
  • Varkey, R. S., Joy, J., Sarmah, G., & Panda, P. K. (2020). Socioeconomic determinants of COVID-19 in Asian countries: An empirical analysis. Journal of Public Affairs, 21, e2532. https://doi.org/10.1002/pa.2532
  • Wang, J., Tang, K., Feng, K., Lin, X., Lv, W., Chen, K., & Wang, F. (2020). High temperature and high humidity reduce the transmission of COVID-19. Social Science Research Network.
  • Xing, G.-R., Li, M.-T., Li, L., & Sun, G.-Q. (2020). The impact of population migration on the spread of COVID-19: A case study of Guangdong province and Hunan province in China. Frontiers in Physics, 8, 488. https://doi.org/10.3389/fphy.2020.587483
  • Zare-Zardini, H., Soltaninejad, H., Ferdosian, F., Hamidieh, A. A., & Memarpoor-Yazdi, M. (2020). Coronavirus disease 2019 (COVID-19) in children: Prevalence, diagnosis, clinical symptoms, and treatment. International Journal of General Medicine, 13, 477–482. https://doi.org/10.2147/IJGM.S262098
  • Zemtsov, S. P., & Baburin, V. L. (2020). COVID-19: Spatial dynamics and diffusion factors across Russian regions. Regional Research of Russia, 10(3), 273–290. https://doi.org/10.1134/S2079970520030156
  • Zhang, C. H., & Schwartz, G. G. (2020). Spatial disparities in coronavirus incidence and mortality in the United States: An ecological analysis as of May 2020. The Journal of Rural Health, 36(3), 433–445. doi:10.1111/jrh.12476