Effectiveness and challenges of digital tools implementation for enhancing infectious disease surveillance data quality in low- and middle-income countries: A systematic review protocol

Monitoring infectious diseases is essential for preventing and controlling outbreaks, especially in low- and middle-income countries (LMICs), where issues like poor infrastructure, lack of trained staff, and limited resources can make data collection challenging. Digital tools such as mobile health...

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Published in:PloS one Vol. 20; no. 8; p. e0330904
Main Authors: Olu-Abiodun, Oluwatosin, Faturoti, Aderinsola, Adepoju, Akinmade, Adeloye, Davies, Adebiyi, Akindele, Abiodun, Olumide
Format: Journal Article
Language:English
Published: United States Public Library of Science 22.08.2025
Public Library of Science (PLoS)
Subjects:
Communicable diseases
Communicable Diseases - epidemiology
Computer and Information Sciences
Data Accuracy
Data collection
Developing Countries
Diagnosis
Earth Sciences
Effectiveness
Global health
Health surveillance
Humans
Infectious diseases
Information systems
Infrastructure
Management
Medical informatics
Medical personnel
Medical research
Medicine and Health Sciences
Meta-analysis
Methods
Mobile Applications
Population Surveillance - methods
Prevention
Public health
Qualitative analysis
Research and Analysis Methods
Science Policy
Sentinel health events
Social Sciences
Study Protocol
Surveillance
Systematic Reviews as Topic
Technology application
Telemedicine
Training
Nigeria
ISSN:1932-6203, 1932-6203
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Summary:Monitoring infectious diseases is essential for preventing and controlling outbreaks, especially in low- and middle-income countries (LMICs), where issues like poor infrastructure, lack of trained staff, and limited resources can make data collection challenging. Digital tools such as mobile health apps and electronic reporting systems show promise in addressing these problems. However, it's still unclear how well these tools actually improve the quality of data, like how quickly information is reported, how accurate it is, whether all necessary data is captured, and if the data can be trusted. This review aims to explore three main points: (1) how digital tools influence the quality of infectious disease data in LMICs; (2) what factors help or hinder their successful use; and (3) what recommendations can be made for policymakers and health workers based on the evidence. We will search several databases, including PubMed/MEDLINE, EMBASE, Scopus, CINAHL, and Google Scholar, for studies published from January 2000 to July 2025. To further reduce publication bias, we will search the following institutional repositories (African Health Observatory and Indian Council of Medical Research). The types of studies are randomised trials, quasi-experimental studies, and mixed-methods evaluations that compare digital solutions with traditional methods in LMIC settings. Data extracted will include outcomes such as delays in reporting, error rates, and completeness, and factors like infrastructure and workforce readiness. The quality of each study will be assessed using ROBINS-I for non-randomized studies and ROB2 for randomized controlled trials. Where possible, we will combine data statistically using meta-analysis and analyse qualitative findings for deeper insights. This review will offer a clear picture of how effective digital tools are in improving disease surveillance. It will identify common challenges, such as poor connectivity and issues with system integration, and emphasize factors that lead to success, like proper training and government support. Overall, the findings will help shape better strategies to strengthen digital disease monitoring, finally contributing to stronger global health security.
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Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0330904