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Demographic and socio-economic factors, and healthcare resource indicators associated with the rapid spread of COVID-19 in Northern Italy: An ecological study

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Listed:
  • Alessandra Buja
  • Matteo Paganini
  • Silvia Cocchio
  • Manuela Scioni
  • Vincenzo Rebba
  • Vincenzo Baldo

Abstract

Background: COVID-19 rapidly escalated into a pandemic, threatening 213 countries, areas, and territories the world over. We aimed to identify potential province-level socioeconomic determinants of the virus’s dissemination, and explain between-province differences in the speed of its spread, based on data from 36 provinces of Northern Italy. Methods: This is an ecological study. We included all confirmed cases of SARS-CoV-2 reported between February 24th and March 30th, 2020. For each province, we calculated the trend of contagion as the relative increase in the number of individuals infected between two time endpoints, assuming an exponential growth. Pearson’s test was used to correlate the trend of contagion with a set of healthcare-associated, economic, and demographic parameters by province. The virus’s spread was input as a dependent variable in a stepwise OLS regression model to test the association between rate of spread and province-level indicators. Results: Multivariate analysis showed that the spread of COVID-19 was correlated negatively with aging index (p-value = 0.003), and positively with public transportation per capita (p-value = 0.012), the % of private long-term care hospital beds and, to a lesser extent (p-value = 0.070), the % of private acute care hospital beds (p-value = 0.006). Conclusion: Demographic and socioeconomic factors, and healthcare organization variables were found associated with a significant difference in the rate of COVID-19 spread in 36 provinces of Northern Italy. An aging population seemed to naturally contain social contacts. The availability of healthcare resources and their coordination could play an important part in spreading infection.

Suggested Citation

  • Alessandra Buja & Matteo Paganini & Silvia Cocchio & Manuela Scioni & Vincenzo Rebba & Vincenzo Baldo, 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, Public Library of Science, vol. 15(12), pages 1-13, December.
    • Handle: RePEc:plo:pone00:0244535
    DOI: 10.1371/journal.pone.0244535
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    1. Tulio Silveira-Santos & Ana Belén Rodríguez González & Thais Rangel & Rubén Fernández Pozo & Jose Manuel Vassallo & Juan José Vinagre Díaz, 2024. "Were ride-hailing fares affected by the COVID-19 pandemic? Empirical analyses in Atlanta and Boston," Transportation, Springer, vol. 51(3), pages 791-822, June.
    2. Yuxi Heluo & Kexin Wang & Charles W. Robson, 2023. "Do we listen to what we are told? An empirical study on human behaviour during the COVID-19 pandemic: neural networks vs. regression analysis," Papers 2311.13046, arXiv.org.
    3. Hafiz Suliman Munawar & Hina Inam & Fahim Ullah & Siddra Qayyum & Abbas Z. Kouzani & M. A. Parvez Mahmud, 2021. "Towards Smart Healthcare: UAV-Based Optimized Path Planning for Delivering COVID-19 Self-Testing Kits Using Cutting Edge Technologies," Sustainability, MDPI, vol. 13(18), pages 1-21, September.
    4. Borsati, Mattia & Nocera, Silvio & Percoco, Marco, 2022. "Questioning the spatial association between the initial spread of COVID-19 and transit usage in Italy," Research in Transportation Economics, Elsevier, vol. 95(C).
    5. Buja, Alessandra & Paganini, Matteo & Fusinato, Riccardo & Cozzolino, Claudia & Cocchio, Silvia & Scioni, Manuela & Rebba, Vincenzo & Baldo, Vincenzo & Boccuzzo, Giovanna, 2022. "Health and healthcare variables associated with Italy's excess mortality during the first wave of the COVID-19 pandemic: An ecological study," Health Policy, Elsevier, vol. 126(4), pages 294-301.
    6. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2021. "A bibliometric methodology to unveil territorial inequities in the scientific wealth to combat COVID-19," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6601-6624, August.
    7. Kostas Rontos & Maria-Eleni Syrmali & Luca Salvati, 2021. "Unravelling the Role of Socioeconomic Forces in the Early Stage of COVID-19 Pandemic: A Global Analysis," IJERPH, MDPI, vol. 18(12), pages 1-14, June.
    8. Americo Cicchetti & Roberta Laurita & Luca Giorgio, 2022. "L?importanza dell?organizzazione in oncologia: collaborazione e coordinamento. Evidenze da una ricerca intervento sul tumore del polmone," MECOSAN, FrancoAngeli Editore, vol. 2022(124), pages 93-111.
    9. Ehlert, Andree, 2021. "The socio-economic determinants of COVID-19: A spatial analysis of German county level data," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    10. Javier Cifuentes-Faura, 2022. "Is Environmental Pollution Associated with an Increased Number of COVID-19 Cases in Europe?," IJERPH, MDPI, vol. 19(2), pages 1-7, January.
    11. Alipio, Mark & Lantajo, Grace Meroflor, 2021. "Do Socio-Economic Indicators Associate with Covid-2019 Cases? Findings from a Philippine Study," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 1(2), pages 102-107.

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