Enhancing local public health decision-making: Incorporating end-user perspectives into influenza forecasting models

BackgroundInfluenza has a significant impact on morbidity and mortality, with disproportionate impact on non-White populations. Forecasts of flu timing/intensity have the potential to reduce morbidity, mortality, and health disparities by supporting decision-making by public health officials and clinicians. However, uptake and use of forecasts on local levels is low, with limited communication between model developers and end-users. The goals of this study are to: 1) understand the seasonal flu intervention decision-making process from the perspective of local public health officials and health care providers; and 2) identify these stakeholders data needs and priorities for flu forecasting models. MethodsThis mixed methods study included a brief survey and two rounds of focus groups with local public health officials and clinicians in a mid-sized metropolitan area in the Northeast US (N=16). Authors used descriptive statistics to analyze survey responses and content analysis to analyze qualitative data. ResultsParticipants described a decision-making process that included using data from forecast models and other sources to inform health interventions, health communication, and resource allocation. Primary outcomes for decision-making included disease prevention and health care preparedness. Participants articulated a variety of ways that forecasting models could assist them in delivering evidence-informed public health and clinical services, and data needs including sociodemographic characteristics and surveillance information at smaller spatial scales. There was a desire for functionality of models that reduced the time spent gathering information. ConclusionsFindings support the need for a participatory modeling approach to the design of influenza forecasts that improves uptake by including the goals and desires of end-users.