Keyword: Communicable Disease Surveillance
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Review Article
Epidemiology and Health Data Insights, 2(5), 2026, ehdi056, https://doi.org/10.63946/ehdi/19469
ABSTRACT:
Background: Communicable and emerging disease surveillance is fundamental to outbreak preparedness and public health response, yet it remains constrained across low- and middle-income countries (LMICs). Technological advancements in digital health and Artificial Intelligence (AI) have provided the ability to increase real-time reporting opportunities, outbreak intelligence, predictive analytics, and anticipatory public health action. However, evidence is sparse on what conditions of implementation drive successful outcomes.
Methods: A systematic review was performed according to the PRISMA 2020 guidelines. A literature search was conducted in PubMed/MEDLINE, Web of Science, and Google Scholar for studies published between January 2015 and May 2026, which highlights surveillance systems in LMICs. The findings were narratively synthesized and recurring implementation determinants were identified and synthesized thematically to develop an implementation readiness framework.
Results: Seventeen empirical studies were included. Digital surveillance reported improvements in reporting timeliness, completeness, outbreak signal detection, and surveillance data generation. Cross-study synthesis identified six recurring readiness domains which informed the development of the Digital Surveillance and Artificial Intelligence Implementation Readiness Framework (DSIRF-AI) to guide stakeholders in enhancing surveillance outcomes.
Conclusion: Digital surveillance systems were associated with improved surveillance performance. The proposed DSIRF-AI provides an evidence-derived conceptual framework for implementation of communicable disease surveillance in LMIC settings.
Methods: A systematic review was performed according to the PRISMA 2020 guidelines. A literature search was conducted in PubMed/MEDLINE, Web of Science, and Google Scholar for studies published between January 2015 and May 2026, which highlights surveillance systems in LMICs. The findings were narratively synthesized and recurring implementation determinants were identified and synthesized thematically to develop an implementation readiness framework.
Results: Seventeen empirical studies were included. Digital surveillance reported improvements in reporting timeliness, completeness, outbreak signal detection, and surveillance data generation. Cross-study synthesis identified six recurring readiness domains which informed the development of the Digital Surveillance and Artificial Intelligence Implementation Readiness Framework (DSIRF-AI) to guide stakeholders in enhancing surveillance outcomes.
Conclusion: Digital surveillance systems were associated with improved surveillance performance. The proposed DSIRF-AI provides an evidence-derived conceptual framework for implementation of communicable disease surveillance in LMIC settings.
