Prediction of SARS-CoV-2 infection with a Symptoms-Based model to aid public health decision making in Latin America and other low and middle income settings.

Symptoms-based models for predicting SARS-CoV-2 infection may improve clinical decision-making and be an alternative to resource allocation in under-resourced settings. In this study we aimed to test a model based on symptoms to predict a positive test result for SARS-CoV-2 infection during the COVID-19 pandemic using logistic regression and a machine-learning approach, in Bogotá, Colombia. Participants from the CoVIDA project were included.

Factors Associated With SARS-CoV-2 Infection in Bogotá, Colombia: Results From a Large Epidemiological Surveillance Study.

Background: Epidemiologic surveillance of COVID-19 is essential to collect and analyse data to improve public health decision making during the pandemic. There are few initiatives led by public-private alliances in Colombia and Latin America. The CoVIDA project contributed with RT-PCR tests for SARS-CoV-2 in mild or asymptomatic populations in Bogotá.

Internal displacement in Colombia: Fifteen distinguishing features.

This commentary aims to delineate the distinguishing features of conflict-induced internal displacement in the nation of Colombia, South America. Even as Colombia is currently implementing a spectrum of legal, social, economic, and health programs for "victims of armed conflict," with particular focus on internally displaced persons (IDPs), the dynamics of forced migration on a mass scale within this country are little known beyond national borders.   The authors of this commentary are embarking on a global mental health research program in Bogota, Colombia to define best practices for reaching the displaced population and implementing sustainable, evidence-based screening and intervention for common mental disorders.