Data-Driven Infectious Disease Control: Qualitative Study of Professionals' Attitudes, Barriers, and Needs

Abstract

Background: Data-driven strategies are increasingly integrated into infectious disease control (IDC), enabling professionals to act in a timely and proactive manner; however, their implementation requires alignment with professionals’ needs. Little is known about professionals’ views on data-driven IDC. Objective: This study aims to assess IDC professionals’ knowledge, attitudes, and perceptions toward working in a data-driven manner, as well as their needs, facilitators, and barriers. Methods: We conducted exploratory online focus group discussions (FGDs) with IDC professionals from the Public Health Services (PHSs) in the Netherlands. FGDs were organized by profession, followed by a final mixed-group session that included medical doctors, nurses, infection preventionists, epidemiologists, policy advisors, project leaders, and managers working in IDC. The topic guide was based on the Attitude-Social Influence-Efficacy model and the Consolidated Framework for Implementation Research, complemented with questions on current practices within the PHS related to data-driven work (DDW). Framework and thematic analyses were performed. Results: Between September 2024 and January 2025, nine FGDs were conducted with 36 IDC professionals. Five main themes emerged: (1) context of the work environment, (2) interpretation of DDW in the context of IDC, (3) added value of DDW, (4) views on team participation, and (5) perspectives on development and implementation. While participants mentioned that some data-driven strategies were already implemented within the PHS, they observed that data were not often translated into action. Attitudes toward DDW varied across participants, particularly regarding its definition, application in daily practice, the importance of data interpretation by professionals, results, implementation, and added value. Participation in DDW varied within teams and was influenced by role, interest, workload, time, knowledge, and willingness to change. Participants also identified various facilitators, barriers, and needs at the individual, process, and organizational levels, such as a national approach of data-driven IDC guided by a shared vision, defined role assignments, and clear protocols for data registration. Conclusions: In this study, IDC professionals generally expressed a positive attitude toward DDW but also identified several barriers and needs for future implementation. The limited translation of data into action was viewed as untapped potential. To support effective data-driven IDC, we recommend investing in a supportive work environment that promotes a clear, shared definition of DDW, including defined roles and responsibilities. By doing so, IDC professionals can shift from reactive to strategic, data-informed action and be better equipped future public health threats.