User acceptance testing of the D-MOSS dengue predictive model as an early warning system in Malaysia

Dengue remains a significant public health challenge in Malaysia with recurring outbreaks, highlighng the need for effecve forecasng tools.This study aimed to evaluate user acceptance of the Dengue forecasng Model Satellite-based System (D-MOSS) in Malaysia, assessing its usability, strengths, challenges, and areas for improvement.A cross-seconal study was conducted among 32 stakeholders who were directly involved in using D-MOSS for dengue management.Data were collected during a naonal workshop using a structured survey adapted to the specific operaonal context of D-MOSS.Themac analysis was employed to analyse open-ended responses using R for keyword-based categorisaon and visualisaon.Parcipants reported high comprehension of D-MOSS features, with a 100% understanding of the outbreak thresholds and forecast values.Common strengths included the system's forecasng capability (66%), impact on outbreak management (22%) and user-friendly interface (12%).Challenges highlighted included accuracy and credibility (54%), performance and technical issues (27%), and granularity and usability of data (19%).For improvements, 40% suggested greater customisaon, such as smaller spaal resoluon, 25% emphasised interface enhancements, 20% advocated for comparave analysis features, and 15% proposed integrang acon planning tools.The system was perceived as a helpful tool for assisng proacve dengue management.D-MOSS demonstrated its user-friendliness and stakeholder adaptability, which support its applicaon in dengue surveillance.Addressing idenfied challenges and enhancing system features could strengthen its ulity and integraon, contribung to improved dengue surveillance and control efforts.