Lessons from the pandemic. Usefulness of datathons and open bases in the analysis of Covid-19

dc.contributor.authorReynoso-García, Jelissa
dc.contributor.authorFernández, Ariel Leonardo
dc.contributor.authorOrdoñez, Patricia
dc.contributor.authorVillanueva, Cleva
dc.date.accessioned2023-09-05T18:37:40Z
dc.date.available2023-09-05T18:37:40Z
dc.date.issued2023-07
dc.description21st LACCEI International Multi-Conference for Engineering, Education, and Technology: “Leadership in Education and Innovation in Engineering in the Framework of Global Transformations: Integration and Alliances for Integral Development”, Hybrid Event, Buenos Aires - ARGENTINA, July 17 - 21, 2023.en_US
dc.description.abstractCovid-19 Latam Datathon was the origin of the present study. Analyzing open databases, it was detected that in Chile the deaths of confirmed Covid-19 cases were concentrated in regions with greatest access to hospitals, which was the opposite of what was detected in other countries of Latin America. The objective was to determine the relationship between the distribution of hospitals and mortality from COVID -19 in Chile. The percentage of confirmed cases from March 2020 to August 2021 was analyzed by regions of the country. The analysis was based on the open database of the Chilean Ministry of Health. Geolocation was used to analyze the distribution of health establishments, confirmed cases and deaths. A positive correlation was observed between mortality and the number of hospitals (R = 0.54, p=0.02). It is known that in large cities there are factors such as the segregation of vulnerable groups and environmental contamination that determine the higher mortality from infectious-contagious diseases. However, in the analyzed database it was not possible to find regional information that would help in the interpretation of the results. The datathon allowed us to glimpse the global need to have open, complete, updated databases, which would make it possible to analyze the variables that determine the causes and prevent the consequences of natural disasters or pandemics such as COVID-19. This will help in the future to reduce analysis biases and to help governments to act promptly in the most vulnerable sites to reduce mortality and economic consequences.en_US
dc.description.sponsorshipGrant NIH. Increasing diversity in interdisciplinary BD2K (IDI-BD2K). Grant CONACYT-México 311866.en_US
dc.description.urihttps://laccei.org/LACCEI2023-BuenosAires/table-of-content.htmlen_US
dc.format.extent8 pagesen_US
dc.genreconference papers and proceedingsen_US
dc.genrepreprintsen_US
dc.identifierdoi:10.13016/m2n72i-obuq
dc.identifier.urihttp://hdl.handle.net/11603/29538
dc.language.isoesen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.en_US
dc.titleLessons from the pandemic. Usefulness of datathons and open bases in the analysis of Covid-19en_US
dc.typeTexten_US

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