Enhancing HIV/STI decision-making: challenges and opportunities in leveraging predictive models for individuals, healthcare providers, and policymakers

Abstract

Abstract The prevention and control of human immunodeficiency virus and sexually transmitted infections (HIV/STI) face challenges worldwide, especially in China. Prediction tools, which analyze medical data and information to make future predictions, were once mainly used in HIV/STI research to help make diagnostic or prognostic decisions, has have now extended to the public as a freely accessible tool. This article provides an overview of the different roles of prediction tools in preventing and controlling HIV/STI from the perspectives of individuals, healthcare providers, and policymakers. For individuals, prediction tools serve as a risk assessment solution that assess their risk and consciously improve risk reception or change risky behaviors. For researchers, prediction tools are powerful for assisting in identifying risk factors and predicting patients’ infection risk, which can inform timely and accurate intervention planning in the future. In order to achieve the best performance, current research increasingly underscores the necessity of considering multiple levels of information, such as socio-behavioral data, in developing a robust prediction tool. In addition, it is also crucial to conduct trials in clinical settings to validate the effectiveness of prediction tools. Many studies only use theoretical parameters such as model accuracy to estimate its predictive. If these improvements are made, the application of prediction tools could be a potentially inspiring solution in the prevention and control of HIV/STI, and an opportunity for achieving the World Health Organization’s agenda to end the HIV/STI epidemic by 2030.