Open-source health technologies for epidemiological research and public health surveillance
ANNALS OF EPIDEMIOLOGY, vol.122, pp.0-1, 2026 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 122
- Publication Date: 2026
- Doi Number: 10.1016/j.annepidem.2026.110250
- Journal Name: ANNALS OF EPIDEMIOLOGY
- Journal Indexes: Academic Search Ultimate (EBSCO), Scopus, Science Citation Index Expanded (SCI-EXPANDED), BIOSIS, CINAHL, EMBASE, Gender Studies Database, MEDLINE, Public Affairs Index
- Page Numbers: pp.0-1
- Kütahya Health Sciences University Affiliated: Yes
Abstract
Open-source health technologies may support epidemiological research and public health surveillance through adaptable diagnostic, monitoring, and data systems. Rising healthcare costs, unequal access to diagnostic technologies, and growing infectious and chronic disease burdens have increased interest in locally maintainable approaches, particularly in resource-limited settings. This structured narrative review synthesizes peer-reviewed and gray literature alongside project documentation on open-source hardware, software, data platforms, surveillance systems, and integrated hardware–software systems relevant to epidemiology and public health. Applications include diagnostic devices, wearable monitoring systems, environmental sensors, health information systems, and digital surveillance platforms that may support case detection, outbreak monitoring, population-level data collection, chronic disease surveillance, and public health response. The evidence remains heterogeneous. Many examples are prototypes or early implementations, and their effectiveness, safety, scalability, and sustainability vary across settings. Challenges include regulatory uncertainty, cybersecurity and privacy risks, limited standardization, interoperability barriers, uneven documentation, and technical expertise gaps. Openness alone does not ensure accessibility, safety, clinical effectiveness, sustainability, or open or anonymized public health data. These technologies should therefore be viewed as complementary tools whose practical value depends on validation, ethical data practices, sustainable implementation, and integration with public health infrastructure.