COVID-19 trend analysis in mexican states and cities
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNIFESP |
Texto Completo: | https://repositorio.unifesp.br/xmlui/handle/11600/62486 http://dx.doi.org/10.1109/EMBC46164.2021.9630001 |
Resumo: | This paper presents a trend analysis of the COVID-19 pandemics in Mexico. The studies were run in a subnational basis because they are more useful that way, providing important information about the pandemic to local authorities. Unlike classic approaches in the literature, the trend analysis presented here is not based on the variations in the number of infections along time, but rather on the predicted value of the final number of infections, which is updated every day employing new data. Results for four states and four cities, selected among the most populated in Mexico, are presented. The model was able to suitably fit the local data for the selected regions under evaluation. Moreover, the trend analysis enabled one to assess the accuracy of the forecasts. |
id |
UFSP_614cfee33103ed6ca8d6c8169792fc5a |
---|---|
oai_identifier_str |
oai:repositorio.unifesp.br:11600/62486 |
network_acronym_str |
UFSP |
network_name_str |
Repositório Institucional da UNIFESP |
repository_id_str |
3465 |
spelling |
Paiva, Henrique Mohallem [UNIFESP]Afonso, Rubens Junqueira MagalhãesSanches, Davi Gonçalves [UNIFESP]Pelogia, Frederico José Ribeiro [UNIFESP]http://lattes.cnpq.br/6901974057937430Mexico2022-01-03T11:26:07Z2022-01-03T11:26:07Z2021-12-092694-0604https://repositorio.unifesp.br/xmlui/handle/11600/62486http://dx.doi.org/10.1109/EMBC46164.2021.9630001This paper presents a trend analysis of the COVID-19 pandemics in Mexico. The studies were run in a subnational basis because they are more useful that way, providing important information about the pandemic to local authorities. Unlike classic approaches in the literature, the trend analysis presented here is not based on the variations in the number of infections along time, but rather on the predicted value of the final number of infections, which is updated every day employing new data. Results for four states and four cities, selected among the most populated in Mexico, are presented. The model was able to suitably fit the local data for the selected regions under evaluation. Moreover, the trend analysis enabled one to assess the accuracy of the forecasts.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)2020/14357-11820-1823engInstitute of Electrical and Electronics Engineers (IEEE)2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)epidemiology, mathematical model, trend analysis, COVID-19, SARS-CoV-2COVID-19 trend analysis in mexican states and citiesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UNIFESPinstname:Universidade Federal de São Paulo (UNIFESP)instacron:UNIFESPInstituto de Ciência e Tecnologia (ICT)Engenharia BiomédicaOutraModelos Matemáticos descritivos da pandemia de COVID-19Ciência e TecnologiaNão se aplicaORIGINAL2021_IEEE_EMBC_Covid_preprint.pdf2021_IEEE_EMBC_Covid_preprint.pdfapplication/pdf1199364${dspace.ui.url}/bitstream/11600/62486/1/2021_IEEE_EMBC_Covid_preprint.pdfa25acb96057df17c80da0958230318e6MD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-85799${dspace.ui.url}/bitstream/11600/62486/2/license.txtab7bcca84d084ecb0e4e1f2025335c5dMD52open accessTEXT2021_IEEE_EMBC_Covid_preprint.pdf.txt2021_IEEE_EMBC_Covid_preprint.pdf.txtExtracted texttext/plain17939${dspace.ui.url}/bitstream/11600/62486/15/2021_IEEE_EMBC_Covid_preprint.pdf.txtb75e476e947f15674a8dff71b1ffd972MD515open accessTHUMBNAIL2021_IEEE_EMBC_Covid_preprint.pdf.jpg2021_IEEE_EMBC_Covid_preprint.pdf.jpgIM Thumbnailimage/jpeg6190${dspace.ui.url}/bitstream/11600/62486/17/2021_IEEE_EMBC_Covid_preprint.pdf.jpg4ac4b4f475b310353eacfacba7929760MD517open access11600/624862023-06-05 19:09:28.288open accessoai:repositorio.unifesp.br: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ório InstitucionalPUBhttp://www.repositorio.unifesp.br/oai/requestopendoar:34652023-06-05T22:09:28Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP)false |
dc.title.pt_BR.fl_str_mv |
COVID-19 trend analysis in mexican states and cities |
title |
COVID-19 trend analysis in mexican states and cities |
spellingShingle |
COVID-19 trend analysis in mexican states and cities Paiva, Henrique Mohallem [UNIFESP] epidemiology, mathematical model, trend analysis, COVID-19, SARS-CoV-2 |
title_short |
COVID-19 trend analysis in mexican states and cities |
title_full |
COVID-19 trend analysis in mexican states and cities |
title_fullStr |
COVID-19 trend analysis in mexican states and cities |
title_full_unstemmed |
COVID-19 trend analysis in mexican states and cities |
title_sort |
COVID-19 trend analysis in mexican states and cities |
author |
Paiva, Henrique Mohallem [UNIFESP] |
author_facet |
Paiva, Henrique Mohallem [UNIFESP] Afonso, Rubens Junqueira Magalhães Sanches, Davi Gonçalves [UNIFESP] Pelogia, Frederico José Ribeiro [UNIFESP] |
author_role |
author |
author2 |
Afonso, Rubens Junqueira Magalhães Sanches, Davi Gonçalves [UNIFESP] Pelogia, Frederico José Ribeiro [UNIFESP] |
author2_role |
author author author |
dc.contributor.authorLattes.pt_BR.fl_str_mv |
http://lattes.cnpq.br/6901974057937430 |
dc.contributor.author.fl_str_mv |
Paiva, Henrique Mohallem [UNIFESP] Afonso, Rubens Junqueira Magalhães Sanches, Davi Gonçalves [UNIFESP] Pelogia, Frederico José Ribeiro [UNIFESP] |
dc.subject.por.fl_str_mv |
epidemiology, mathematical model, trend analysis, COVID-19, SARS-CoV-2 |
topic |
epidemiology, mathematical model, trend analysis, COVID-19, SARS-CoV-2 |
description |
This paper presents a trend analysis of the COVID-19 pandemics in Mexico. The studies were run in a subnational basis because they are more useful that way, providing important information about the pandemic to local authorities. Unlike classic approaches in the literature, the trend analysis presented here is not based on the variations in the number of infections along time, but rather on the predicted value of the final number of infections, which is updated every day employing new data. Results for four states and four cities, selected among the most populated in Mexico, are presented. The model was able to suitably fit the local data for the selected regions under evaluation. Moreover, the trend analysis enabled one to assess the accuracy of the forecasts. |
publishDate |
2021 |
dc.date.issued.fl_str_mv |
2021-12-09 |
dc.date.accessioned.fl_str_mv |
2022-01-03T11:26:07Z |
dc.date.available.fl_str_mv |
2022-01-03T11:26:07Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://repositorio.unifesp.br/xmlui/handle/11600/62486 |
dc.identifier.issn.pt_BR.fl_str_mv |
2694-0604 |
dc.identifier.doi.pt_BR.fl_str_mv |
http://dx.doi.org/10.1109/EMBC46164.2021.9630001 |
identifier_str_mv |
2694-0604 |
url |
https://repositorio.unifesp.br/xmlui/handle/11600/62486 http://dx.doi.org/10.1109/EMBC46164.2021.9630001 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
1820-1823 |
dc.coverage.spatial.pt_BR.fl_str_mv |
Mexico |
dc.publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers (IEEE) |
publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers (IEEE) |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UNIFESP instname:Universidade Federal de São Paulo (UNIFESP) instacron:UNIFESP |
instname_str |
Universidade Federal de São Paulo (UNIFESP) |
instacron_str |
UNIFESP |
institution |
UNIFESP |
reponame_str |
Repositório Institucional da UNIFESP |
collection |
Repositório Institucional da UNIFESP |
bitstream.url.fl_str_mv |
${dspace.ui.url}/bitstream/11600/62486/1/2021_IEEE_EMBC_Covid_preprint.pdf ${dspace.ui.url}/bitstream/11600/62486/2/license.txt ${dspace.ui.url}/bitstream/11600/62486/15/2021_IEEE_EMBC_Covid_preprint.pdf.txt ${dspace.ui.url}/bitstream/11600/62486/17/2021_IEEE_EMBC_Covid_preprint.pdf.jpg |
bitstream.checksum.fl_str_mv |
a25acb96057df17c80da0958230318e6 ab7bcca84d084ecb0e4e1f2025335c5d b75e476e947f15674a8dff71b1ffd972 4ac4b4f475b310353eacfacba7929760 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP) |
repository.mail.fl_str_mv |
|
_version_ |
1802764247085613056 |