{"title":"[在IMSS中对COVID-19爆发进行早期预警以制定应对计划]。","authors":"José Esteban Fernández-Gárate, Aide Jazmín González-Cruz, Jorge Zenil-Pérez, Ismael Seth Medina-Reyes, Humberto Frances-Salgado, Xóchitl Refugio Romero-Guerrero","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>The Instituto Mexicano del Seguro Social (IMSS) developed and implemented epidemic monitoring and modeling tools to support the organization and planning of an adequate and timely response to the COVID-19 health emergency. The aim of this article is to describe the methodology and results of the early outbreak detection tool called COVID-19 Alert. An early warning traffic light was developed that uses time series analysis and a Bayesian method of early detection of outbreaks from electronic records on COVID-19 for suspected cases, confirmed cases, disabilities, hospitalizations, and deaths. Through Alerta COVID-19, the beginning of the fifth wave of COVID-19 in the IMSS was detected in a timely manner, three weeks before the official declaration. The proposed method is aimed at generating early warnings before the start of a new wave of COVID-19, monitoring the serious phase of the epidemic, and supporting decision-making within the institution; unlike other tools that have an approach aimed at communicating risks to the community. We can conclude that the Alerta COVID-19 is an agile tool that incorporates robust methods for the early detection of outbreaks.</p>","PeriodicalId":21419,"journal":{"name":"Revista médica del Instituto Mexicano del Seguro Social","volume":"60 Suppl 2","pages":"160-172"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10652999/pdf/","citationCount":"0","resultStr":"{\"title\":\"[Early alert of COVID-19 outbreaks to plan the response in the IMSS].\",\"authors\":\"José Esteban Fernández-Gárate, Aide Jazmín González-Cruz, Jorge Zenil-Pérez, Ismael Seth Medina-Reyes, Humberto Frances-Salgado, Xóchitl Refugio Romero-Guerrero\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The Instituto Mexicano del Seguro Social (IMSS) developed and implemented epidemic monitoring and modeling tools to support the organization and planning of an adequate and timely response to the COVID-19 health emergency. The aim of this article is to describe the methodology and results of the early outbreak detection tool called COVID-19 Alert. An early warning traffic light was developed that uses time series analysis and a Bayesian method of early detection of outbreaks from electronic records on COVID-19 for suspected cases, confirmed cases, disabilities, hospitalizations, and deaths. Through Alerta COVID-19, the beginning of the fifth wave of COVID-19 in the IMSS was detected in a timely manner, three weeks before the official declaration. The proposed method is aimed at generating early warnings before the start of a new wave of COVID-19, monitoring the serious phase of the epidemic, and supporting decision-making within the institution; unlike other tools that have an approach aimed at communicating risks to the community. We can conclude that the Alerta COVID-19 is an agile tool that incorporates robust methods for the early detection of outbreaks.</p>\",\"PeriodicalId\":21419,\"journal\":{\"name\":\"Revista médica del Instituto Mexicano del Seguro Social\",\"volume\":\"60 Suppl 2\",\"pages\":\"160-172\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10652999/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista médica del Instituto Mexicano del Seguro Social\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista médica del Instituto Mexicano del Seguro Social","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
[Early alert of COVID-19 outbreaks to plan the response in the IMSS].
The Instituto Mexicano del Seguro Social (IMSS) developed and implemented epidemic monitoring and modeling tools to support the organization and planning of an adequate and timely response to the COVID-19 health emergency. The aim of this article is to describe the methodology and results of the early outbreak detection tool called COVID-19 Alert. An early warning traffic light was developed that uses time series analysis and a Bayesian method of early detection of outbreaks from electronic records on COVID-19 for suspected cases, confirmed cases, disabilities, hospitalizations, and deaths. Through Alerta COVID-19, the beginning of the fifth wave of COVID-19 in the IMSS was detected in a timely manner, three weeks before the official declaration. The proposed method is aimed at generating early warnings before the start of a new wave of COVID-19, monitoring the serious phase of the epidemic, and supporting decision-making within the institution; unlike other tools that have an approach aimed at communicating risks to the community. We can conclude that the Alerta COVID-19 is an agile tool that incorporates robust methods for the early detection of outbreaks.