[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.