Zika emergence, persistence, and transmission rate in Colombia: a nationwide application of a space-time Markov switching model.

Zika, a viral disease transmitted to humans by Aedes mosquitoes, emerged in the Americas in 2015, causing large-scale epidemics. Colombia alone reported over 72,000 Zika cases between 2015 and 2016. Using national surveillance data from 1121 municipalities over 70 weeks, we identified sociodemographic and environmental factors associated with Zika's emergence, re-emergence, persistence, and transmission intensity in Colombia.

Public perception of healthcare system response to COVID-19: Findings from a web based observational study in Villavicencio, Colombia.

This study explores the community perceptions of COVID-19 and the healthcare system's response to it.: A web-based descriptive observational study was conducted on the general population during the third quarter of 2020 through the application of a survey via social media. Of the sample, 55% have minimal connection with prevention programs, while 66.

Spatio-temporal clusters and patterns of spread of dengue, chikungunya, and Zika in Colombia.

Background: Colombia has one of the highest burdens of arboviruses in South America. The country was in a state of hyperendemicity between 2014 and 2016, with co-circulation of several Aedes-borne viruses, including a syndemic of dengue, chikungunya, and Zika in 2015.

Methodology/principal Findings: We analyzed the cases of dengue, chikungunya, and Zika notified in Colombia from January 2014 to December 2018 by municipality and week.

[Health as a right in Colombia's post-conflict period].

Objective: To explore the elements that should be considered in post-conflict zones to guarantee the right to health of populations immersed or living in areas near the concentrations of former combatants.

Materials And Methods: A retrospective study was carried out by searching databases, obtaining 26 relevant articles.

Results: The literature review made evident that not only the legal or normative framework is important, but also the needs and interests of the people of the community, of both the civilian population and the victims of war.

Machine learning and dengue forecasting: Comparing random forests and artificial neural networks for predicting dengue burden at national and sub-national scales in Colombia.

The robust estimate and forecast capability of random forests (RF) has been widely recognized, however this ensemble machine learning method has not been widely used in mosquito-borne disease forecasting. In this study, two sets of RF models were developed at the national (pooled department-level data) and department level in Colombia to predict weekly dengue cases for 12-weeks ahead. A pooled national model based on artificial neural networks (ANN) was also developed and used as a comparator to the RF models.