An event supposedly attributable to vaccination or immunization (ESAVI) is any unfavorable and unintended health situation (sign, symptom, abnormal laboratory finding, or disease) that occurs after vaccination or immunization and that does not necessarily have a causal relationship with the vaccination process or the vaccine. One of the essential components of a safe vaccination program is surveillance for ESAVIs.
The widespread digitization of information, advances in data processing and the emergence of internet-connected devices have led to a proliferation of data, often loosely referred to as big data. With this digital transformation, offering open data – that is, data freely available for modification and reuse – has emerged as a key strategy for encouraging transparency and innovation. Data reuse holds particular importance in the small island developing states of the Caribbean, which have a limited resource pool from which to tackle the landscape of social priorities.
The Caribbean small island developing states have limited resources for comprehensive health care provision and are facing an increasing burden of noncommunicable diseases which is driven by an aging regional population. Artificial intelligence (AI) and other digital technologies offer promise for contributing to health care efficiencies, but themselves are dependent on the availability and accessibility of accurate health care data. A regional shortfall in data professionals continues to hamper legislative recognition and promotion of increased data production in Caribbean countries.
To describe the experiences of the National Advisory Commission on Serious Events Supposedly Attributable to Vaccination or Immunization (ESAVI) implemented in Ecuador for the period 2020–2023.
In Honduras, health systems have been faced with a duty and a need to establish surveillance mechanisms in order to understand the pathways of health and disease in the population. The objective of this article is to describe the process of analysis and the strategies used during development of a robust information system for vaccine safety surveillance, which can also be replicated for other forms of surveillance.
To document the historical facts and the challenges faced in the Region of the Americas in achieving and sustaining measles, rubella, and congenital rubella syndrome (CRS) elimination between 2013 and 2023.
Special report with a narrative description of the main achievements, challenges, and lessons learned during the period, and an analysis of vaccination coverage, surveillance indicators, and measles outbreaks using data from the Pan American Health Organization and the United Nations Children's Fund, among others.
To describe the process of restructuring the National Expert Committee and its impact on the causality assessment of events supposedly attributable to vaccination or immunization (ESAVI) in the context of vaccine safety monitoring during the COVID-19 pandemic, 2020-2023.
A report was prepared on the experience of creating and operating Mexico's National Expert Committee during the aforementioned period.
We describe the daily operations of the Cohorts Consortium of Latin America and the Caribbean (CC-LAC), detailing the resources required and offering tips to Caribbean researchers so this guide can be used to start a data pooling project.
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.
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.
