A public health approach to reducing violence within the CARICOM region.

Widespread crime has become a worldwide problem so much so that violence is now ranked fourth globally in its contribution to disability-adjusted life years in the 10 to 24 age group. Homicides, a surrogate marker of violent crime, have shown an upward trend in almost all of the CARICOM countries, and homicide rates over the past 3 years have consistently increased, though the pattern of violence varies by country. This background has informed the need for greater emphasis on the need for a different approach to dealing with crime in the CARICOM region. The CARICOM governments recently hosted a symposium on crime and violence as a public health issue. The public health approach to crime has been used with measurable success in different parts of the world and, more recently in Trinidad, one of the CARICOM countries. The paper outlines the outcomes of the symposium and discusses its implications for the region.

FOMO (fate of online media only) in infectious disease modeling: a review of compartmental models.

Mathematical models played in a major role in guiding policy decisions during the COVID-19 pandemic. These models while focusing on the spread and containment of the disease, largely ignored the impact of media on the disease transmission. Media plays a major role in shaping opinions, attitudes and perspectives and as the number of people online increases, online media are fast becoming a major source for news and health related information and advice. Consequently, they may influence behavior and in due course disease dynamics. Unlike traditional media, online media are themselves driven and influenced by their users and thus have unique features. The main techniques used to incorporate online media mathematically into compartmental models, with particular reference to the ongoing COVID-19 pandemic are reviewed. In doing so, features specific to online media that have yet to be fully integrated into compartmental models such as misinformation, different time scales with regards to disease transmission and information, time delays, information super spreaders, the predatory nature of online media and other factors are identified together with recommendations for their incorporation.

Harnessing Social Media in the Modelling of Pandemics-Challenges and Opportunities.

As COVID-19 spreads throughout the world without a straightforward treatment or widespread vaccine coverage in the near future, mathematical models of disease spread and of the potential impact of mitigation measures have been thrust into the limelight. With their popularity and ability to disseminate information relatively freely and rapidly, information from social media platforms offers a user-generated, spontaneous insight into users' minds that may capture beliefs, opinions, attitudes, intentions and behaviour towards outbreaks of infectious disease not obtainable elsewhere. The interactive, immersive nature of social media may reveal emergent behaviour that does not occur in engagement with traditional mass media or conventional surveys. In recognition of the dramatic shift to life online during the COVID-19 pandemic to mitigate disease spread and the increasing threat of further pandemics, we examine the challenges and opportunities inherent in the use of social media data in infectious disease modelling with particular focus on their inclusion in compartmental models.

Not so elementary - the reasoning behind a medical diagnosis.

This article was migrated. The article was marked as recommended. Making a diagnosis is a complex process involving incomplete yet dynamic information. At no other time in the history of medicine has information been so readily available and accessible resulting in a greater need for clarity of thinking. A clear understanding of the underlying reasoning processes involved is necessary so as to avoid misdiagnosis and to avoid unnecessary often costly and time-consuming tests. This article explores the main reasoning processes inherent in the making of a diagnosis - deduction, induction and abduction.