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Role of the Health System in Combating Covid-19: Cross-Section Analysis and Artificial Neural Network Simulation for 124 Country Cases

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dc.contributor.authorBayraktar, Yüksel
dc.contributor.authorÖzyılmaz, Ayfer
dc.contributor.authorToprak, Metin
dc.contributor.authorIşık, Esme
dc.contributor.authorBüyükakın, Figen
dc.contributor.authorOlgun, Mehmet Fırat
dc.date.accessioned2026-01-04T14:51:09Z
dc.date.issued2020-12-28
dc.description.abstractIn the fight against Covid-19, developed countries and developing countries diverge in success. This drew attention to the discussion of how different health systems and different levels of health spending are effective in combating Covid-19. In this study, the role of the health system in the fight against Covid-19 is discussed. In this context, the number of hospital beds, the number of doctors, life expectancy at 60, universal health service and the share of health expenditures in GDP were used as health indicators. In the study, firstly 2020 data was estimated by using the Artificial Neural Networks simulation method and this year was used in the analysis. The model, with the data of 124 countries, was estimated using the cross-sectional OLS regression method. The estimation results show that the number of hospital beds, number of doctors and life expectancy at the age of 60 have statistically significant and positive effects on the ratio of Covid-19 recovered/cases. Universal health service and share of health expenditures in GDP are not significant statistically on the cases and recovered. Hospital bed capacity is the most effective variable on the recovered/case ratio.
dc.description.urihttps://doi.org/10.1080/19371918.2020.1856750
dc.description.urihttps://www.tandfonline.com/doi/pdf/10.1080/19371918.2020.1856750?needAccess=true
dc.description.urihttps://pubmed.ncbi.nlm.nih.gov/33369535
dc.description.urihttps://dx.doi.org/10.1080/19371918.2020.1856750
dc.description.urihttps://avesis.kocaeli.edu.tr/publication/details/5629db35-87a0-474f-a856-c20a12775c19/oai
dc.description.urihttps://hdl.handle.net/20.500.12899/726
dc.description.urihttps://hdl.handle.net/20.500.12436/3151
dc.description.urihttp://dx.doi.org/10.1080/19371918.2020.1856750
dc.identifier.doi10.1080/19371918.2020.1856750
dc.identifier.eissn1937-190X
dc.identifier.endpage193
dc.identifier.issn1937-1918
dc.identifier.openairedoi_dedup___::9695b0b3fbb324dbd0ee1b769bcf0a80
dc.identifier.orcid0000-0002-3499-4571
dc.identifier.orcid0000-0001-9201-2508
dc.identifier.orcid0000-0001-9217-6318
dc.identifier.orcid0000-0002-6179-5746
dc.identifier.orcid0000-0002-0226-7265
dc.identifier.orcid0000-0002-2728-0714
dc.identifier.pubmed33369535
dc.identifier.scopus2-s2.0-85098479390
dc.identifier.startpage178
dc.identifier.urihttps://hdl.handle.net/20.500.12597/38431
dc.identifier.volume36
dc.identifier.wos000603847300001
dc.language.isoeng
dc.publisherInforma UK Limited
dc.relation.ispartofSocial Work in Public Health
dc.rightsOPEN
dc.subjectSARS-CoV-2
dc.subjectHealth Policy
dc.subjectPublic Health, Environmental and Occupational Health
dc.subjectglobal health
dc.subjectCOVID-19
dc.subjecthealthcare system
dc.subjectGlobal Health
dc.subjectHealth(social science)
dc.subjectCross-Sectional Studies
dc.subjectLife Expectancy
dc.subjectHospital Bed Capacity
dc.subjectNovel Coronavirus
dc.subjectPhysicians
dc.subjectHumans
dc.subjectRegression Analysis
dc.subjectComputer Simulation
dc.subjectNeural Networks, Computer
dc.subjectHealth Expenditures
dc.subjectCovid-19
dc.subjectDelivery of Health Care
dc.subject.sdg1. No poverty
dc.subject.sdg3. Good health
dc.titleRole of the Health System in Combating Covid-19: Cross-Section Analysis and Artificial Neural Network Simulation for 124 Country Cases
dc.typeArticle
dspace.entity.typePublication
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