Developing forecasting capacity for public health emergency management in Africa using syndemics approach: lessons from the COVID-19 pandemic

Abstract

Forecasting is an important aspect of decision-making in health and other social aspects of human life. Forecasting can simply be defined as the process of making probabilities about a real-world event using existing data built in a mathematical model.1 This understanding underpins why forecasting is sometimes used interchangeably with the word â € modelling'. Forecasting capacity describes a system that comprises of surveillance database, experts and relevant technologies, and it remains an indispensable workforce development need for promoting data-driven decision-making in health, as frequently advocated by the WHO.2 Generally, the usefulness and usability of forecasting is one that is not unknown or unbeneficial to most people across the world, particularly in non-emergency situations, from its use in daily weather reporting through global projections on economy, and diseases burden. Similarly, from epidemiological perspective, evidence from various forecasting models was observed to have played a major role to improve emergency response in past disease outbreaks (eg, Ebola) and towards the COVID-19 pandemic in the areas not limited to SARS-CoV2 patterns determination, containment and mitigation measures implementation, risk communication, resource management and vaccine development.3-8