Predictive modelling of the effectiveness of vaccines against COVID-19 in Bogotá: Methodological innovation involving different variants and computational optimisation efficiency.

The uncertainty associated with the future of viruses such as SARS-CoV-2 poses a challenge to public health officials because of its implications for welfare, economics and population health. In this document, we develop an age-stratified epidemiological-mathematical model to predict various health outcomes, considering the effectiveness of COVID-19 vaccines. The analytical model proposed and developed for this research is based on the approach constructed by the COVID-19 International Modelling Consortium.

Science, technology, and innovation in health for the next twenty years: A survey analysis in Colombia.

Background: Colombia is a Latin American country with a very complex social and political context that has not allowed the allocation of sufficient resources to the fields of science, technology, and innovation (STI). This is particularly worrying for the area of health since not enough resources are allocated for public health, research, or education.

Methods: The so-called "Great Survey in Health 2019" was administered online through the SurveyMonkey platform to 5298 people in different regions of the country, representing the public, private, and academic sectors.

Predicting chronic kidney disease progression with artificial intelligence.

Background: The use of tools that allow estimation of the probability of progression of chronic kidney disease (CKD) to advanced stages has not yet achieved significant practical importance in clinical setting. This study aimed to develop and validate a machine learning-based model for predicting the need for renal replacement therapy (RRT) and disease progression for patients with stage 3-5 CKD.

Methods: This was a retrospective, closed cohort, observational study.

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review.

Background: The interaction between modelers and policymakers is becoming more common due to the increase in computing speed seen in recent decades. The recent pandemic caused by the SARS-CoV-2 virus was no exception. Thus, this study aims to identify and assess epidemiological mathematical models of SARS-CoV-2 applied to real-world data, including immunization for coronavirus 2019 (COVID-19).

Detecting unexpected growths in health technologies expenditures: the case of MIPRES in Colombia.

We developed an algorithm to explore unexpected growth in the usage and costs of health technologies. We exploit data from the expenditures on technologies funded by the Colombian government under the compulsory insurance system, where all prescriptions for technologies not included in an explicit list must be registered in a centralized information system, covering the period from 2017 to 2022. The algorithm consists of two steps: an outlier detection method based on the density of the expenditures for selecting a first set of technologies to consider (39 technologies out of 106,957), and two anomaly detection models for time series to determine which insurance companies, health providers, and regions have the most notorious increases.

Advance Market Commitments (AMC) model application for Colombian purchase strategy of COVID-19 vaccines.

This research estimated the optimal size and composition of the portfolio, and its benefit-cost ratio, of COVID-19 vaccines that Colombia should negotiate as a price-taking country. The Advance Market Commitments (AMC) mathematical model was applied using the parameters from the Colombian context and from a literature review. The findings indicate that the optimal portfolio of Colombia should include 13 vaccines, mainly from two platforms: i) RNA and ii) inactivated virus.

Vulnerability interactive geographic viewer against COVID-19 at the block level in Colombia: Analytical tool based on machine learning techniques.

To mitigate the effects of the coronavirus disease 2019 (COVID-19) pandemic, different countries have developed computational tools and dashboards that generate value for decision-making in public health. We aimed to build an interactive geographic viewer for vulnerability to COVID-19 at the block level in Colombia to identify the location of populations that, because of sociodemographic characteristics and health conditions, could have more complications from COVID-19 infections. The vulnerability levels of the different blocks of 1,102 municipal capitals were calculated.

[Survival in renal transplant recipients in Colombia, 2008-2012].

Introduction: The Red Nacional de Donación y Trasplantes of the Colombian Instituto Nacional de Salud reported that in 2014, 1,059 organ transplants were performed, of which 761 were kidney transplants, and 643 (84.5%) of these were from cadaveric organ donors.

Objective: To describe the socio-demographic characteristics of patients who received renal transplants, as well as their outcomes in terms of survival.

A Novel Treatment of Denuded Areas in Newborns: A Report of 2 Successful Cases.

Covering denuded areas in the extremes of life is challenging for the plastic surgeon. In newborns, this becomes a greater challenge because of the immaturity of all of their systems, making any injury a potential risk for death. We present in this case report a successful treatment of 2 cases covered with cultured autologous keratinocytes.