In the face of growing health challenges, nontraditional sources of data, such as open data, have the potential to transform how decisions are made and used to inform public health policies. Focusing on the COVID-19 pandemic, this article presents a case study employing sentiment analysis on unstructured social media data from Twitter (now X) to gauge public sentiment regarding pandemic-related restrictions. Our study aims to uncover and analyze Jamaican citizens’ emotions and opinions surrounding COVID-19 restrictions following an outbreak at a call center in April 2020.

Objective

To quantify three aspects of data-related developmental progress across 57 Small Island Developing States (SIDS) recognized by the United Nations: statistical capacity measured using the Statistical Performance Indicators (SPI), data availability using the Sustainable Development Goal (SDG) indicators, and gender-stratified indicators. 

Objectives

This study aimed to explore the use of data from routine health information systems (RHIS) as a public good in Trinidad and Tobago, the challenges faced in doing this and opportunities for strengthening the health information system. 

Data sharing increasingly underpins collaborative research to address complex regional and global public health problems. Advances in analytic tools, including machine learning, have expanded the potential benefits derived from large global repositories of open data. Participating in open data collaboratives offers opportunities for Caribbean researchers to advance the health of the region’s population through shared data driven science and policy. However, ethical challenges complicate these efforts.

The CaribData project, funded by the Inter-American Development Bank and implemented by The University of the West Indies, aims to enhance data-handling, -sharing and reuse capabilities in the Caribbean. The project focuses on four main objectives: developing an online data-handling platform, creating a sustainable training and mentoring program, launching a data communication initiative and conducting data availability audits.

The dissemination of biomedical research data beyond academia remains limited. In response, funding agencies now regularly require that the projects they fund make research data openly available for reuse. This emerging open data movement aims to democratize data access, often guided by the FAIR data technical standards, requiring that data should be findable, accessible, interoperable and reusable. Recently, participant communities have advocated the idea that improving data democracy does not address the inequities underlying the power dynamics of research enterprises.

Objective

To document and compare risk factors and control measures for the largest measles outbreaks in the post-elimination era in the Region of the Americas. 

Methods

Description of risk factors such as vaccination coverage, notification rate of suspected cases, measles incidence, and a summary of control measures for major measles outbreaks in six countries from 2017 to 2023. The analysis also includes a review of outbreak characteristics (time, place, and person). 

Objective

Identify the challenges that Mexico faced during the measles outbreak during the COVID-19 pandemic and describe the interventions to interrupt measles virus circulation. 

Methods

Descriptive, retrospective study of actions taken during the measles outbreak during the COVID-19 pandemic. 

Objective

Describe good practices in epidemiological surveillance implemented in El Salvador between 2019 and 2023 to sustain the elimination of measles, rubella, and congenital rubella syndrome. 

Method

Special descriptive report on the implementation of good epidemiological and laboratory surveillance practices for measles, rubella, and congenital rubella syndrome from 2019 to 2023. 

Objective

To assess the contribution of rapid vaccination monitoring to the achievement of vaccination coverage targets in catch-up vaccination campaigns. 

Methods

Data on catch-up vaccination were obtained from the database of the Directorate of Vaccine- Preventable Diseases. Data analysis was performed in Stata V.15®. Frequency and summary statistics were calculated; the p value was used to determine statistical significance. The change in mean coverage between interventions was assessed with Student’s t-test.