EPIDEMIOLOGY AND HEALTH DATA INSIGHTS
Review Article
Oct 01, 2026 8 6

From Digital Surveillance to Public Health Action: A Systematic Review and Implementation Readiness Framework for Communicable Disease Surveillance in Low- and Middle-Income Countries

Evelyn Foster-Pagaebi 1 * ,
Joseph Pirfa Joshua 2,
Chibueze Chukwuemeka Chukwudi 3,
OcheDomi David Ekele 4,
Kilsi Henry Donabon 5,
Chinwike Onyeka Ugoka 6,
Ebitimi Collins Opumie 7
1 Department of Clinical PharmacyNiger Delta University, Bayelsa, Nigeria2 Department of Obstetrics and Gynaecology, Jos University Teaching Hospital, Plateau, Nigeria3 Department of Obstetrics and Gynaecology, Full Health Specialist Hospital, Edo, Nigeria4 Department of Strategic Information and Knowledge Management, Excellence Community Education Welfare Schemes (ECEWS), Abuja, Nigeria 5 Department of Clinical Services, Nasrum_Minallah Pharmacy Ltd., Rivers, Nigeria 6 Department of Public Health, Northumbria University, Newcastle, United Kingdom 7 Department of Counselling, Nigerian Defence Academy, Kaduna, Nigeria * Corresponding Author
Epidemiology and Health Data Insights, 2(5), 2026, ehdi056, https://doi.org/10.63946/ehdi/19469
Publication date: Oct 01, 2026
Full Text (PDF)

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.

KEYWORDS

Communicable Disease Surveillance Digital Surveillance Outbreak Detection Implementation Readiness Public Health Action LMICs Artificial Intelligence

CITATION (Vancouver)

Foster-Pagaebi E, Joshua JP, Chukwudi CC, Ekele OD, Donabon KH, Ugoka CO, et al. From Digital Surveillance to Public Health Action: A Systematic Review and Implementation Readiness Framework for Communicable Disease Surveillance in Low- and Middle-Income Countries. Epidemiology and Health Data Insights. 2026;2(5):ehdi056. https://doi.org/10.63946/ehdi/19469
APA
Foster-Pagaebi, E., Joshua, J. P., Chukwudi, C. C., Ekele, O. D., Donabon, K. H., Ugoka, C. O., & Opumie, E. C. (2026). From Digital Surveillance to Public Health Action: A Systematic Review and Implementation Readiness Framework for Communicable Disease Surveillance in Low- and Middle-Income Countries. Epidemiology and Health Data Insights, 2(5), ehdi056. https://doi.org/10.63946/ehdi/19469
Harvard
Foster-Pagaebi, E., Joshua, J. P., Chukwudi, C. C., Ekele, O. D., Donabon, K. H., Ugoka, C. O., and Opumie, E. C. (2026). From Digital Surveillance to Public Health Action: A Systematic Review and Implementation Readiness Framework for Communicable Disease Surveillance in Low- and Middle-Income Countries. Epidemiology and Health Data Insights, 2(5), ehdi056. https://doi.org/10.63946/ehdi/19469
AMA
Foster-Pagaebi E, Joshua JP, Chukwudi CC, et al. From Digital Surveillance to Public Health Action: A Systematic Review and Implementation Readiness Framework for Communicable Disease Surveillance in Low- and Middle-Income Countries. Epidemiology and Health Data Insights. 2026;2(5), ehdi056. https://doi.org/10.63946/ehdi/19469
Chicago
Foster-Pagaebi, Evelyn, Joseph Pirfa Joshua, Chibueze Chukwuemeka Chukwudi, OcheDomi David Ekele, Kilsi Henry Donabon, Chinwike Onyeka Ugoka, and Ebitimi Collins Opumie. "From Digital Surveillance to Public Health Action: A Systematic Review and Implementation Readiness Framework for Communicable Disease Surveillance in Low- and Middle-Income Countries". Epidemiology and Health Data Insights 2026 2 no. 5 (2026): ehdi056. https://doi.org/10.63946/ehdi/19469
MLA
Foster-Pagaebi, Evelyn et al. "From Digital Surveillance to Public Health Action: A Systematic Review and Implementation Readiness Framework for Communicable Disease Surveillance in Low- and Middle-Income Countries". Epidemiology and Health Data Insights, vol. 2, no. 5, 2026, ehdi056. https://doi.org/10.63946/ehdi/19469

SUPPLEMENTARY FILES

Supplementary File

REFERENCES

  1. Nguyen-Tien T, Unger F, Yano T, Mutua F, Cook EA, Lee HS, et al. Challenges and recommendations for embracing digital tools for one health surveillance in LMICs: viewpoints from a special session of 17th ISVEE. One Health. 2025 Oct 13;101242. doi:10.1016/j.onehlt.2025.101242
  2. Tetuh KM, Salyer SJ, Aliddeki D, Tibebu B, Osman F, Amabo FC, et al. Evaluating event-based surveillance capacity in Africa: use of the Africa CDC scorecard, 2022–2023. Prev Med Rep. 2023 Dec 1;36:102398. doi:10.1016/j.pmedr.2023.102398
  3. Njeru I, Kareko D, Kisangau N, Langat D, Liku N, Owiso G, et al. Use of technology for public health surveillance reporting: opportunities, challenges and lessons learnt from Kenya. BMC Public Health. 2020 Jul 13;20(1):1101. doi:10.1186/s12889-020-09222-2
  4. Ssendagire S, Karanja MJ, Abdi A, Lubogo M, Azad Al A, Mzava K, et al. Progress and experiences of implementing an integrated disease surveillance and response system in Somalia; 2016–2023. Front Public Health. 2023 Sep 7;11:1204165. doi:10.3389/fpubh.2023.1204165
  5. World Health Organization Regional Office for Africa (WHO/AFRO). Technical Guidelines for Integrated Disease Surveillance and Response in the African Region. 3rd ed. Brazzaville: WHO Regional Office for Africa; 2019. WHO Reference Number: WHO/AF/WHE/CPI/05. Available from: https://www.who.int/publications/i/item/WHO-AF-WHE-CPI-05-2019
  6. Nwokedi VU, Orenolu IO, Ajobiewe MA, Kidane SZ, Alo TE, Foster-Pagaebi E, et al. Strengthening preparedness for infectious disease outbreaks in Sub-Saharan Africa: lessons from recent outbreaks. Epidemiol Health Data Insights. 2025 Sep 2;1(3):ehdi010. doi:10.63946/ehdi/16853
  7. Lawal O, Oyebamiji HO, Kelenna IJ, Chioma FJ, Oyefeso E, Adeyemi BI, et al. A review on usage of digital health literacy to combat antibiotic misuse and misinformation in Nigeria. J Pharma Insights Res. 2025 Apr 5;3(2):258-69. doi:10.69613/dja1jc18
  8. Villanueva-Miranda I, Xiao G, Xie Y. Artificial intelligence in early warning systems for infectious disease surveillance: a systematic review. Front Public Health. 2025 Jun 23;13:1609615. doi:10.3389/fpubh.2025.1609615
  9. Gardy JL, Loman NJ. Towards a genomics-informed, real-time, global pathogen surveillance system. Nat Rev Genet. 2018 Jan;19(1):9-20. doi:10.1038/nrg.2017.88
  10. Kaburi BB, Wyss K, Kenu E, Asiedu-Bekoe F, Hauri AM, Laryea DO, et al. Facilitators and barriers in the implementation of a digital surveillance and outbreak response system in Ghana before and during the COVID-19 pandemic: qualitative analysis of stakeholder interviews. JMIR Form Res. 2023 Oct 20;7(1):e45715. doi:10.2196/45715
  11. Yano T, Phornwisetsirikun S, Susumpow P, Visrutaratna S, Chanachai K, Phetra P, et al. A participatory system for preventing pandemics of animal origins: pilot study of the participatory one health disease detection (PODD) system. JMIR Public Health Surveill. 2018 Mar 21;4(1):e7375. doi:10.2196/publichealth.7375
  12. Karimuribo ED, Mutagahywa E, Sindato C, Mboera L, Mwabukusi M, Njenga MK, et al. A smartphone app (AfyaData) for innovative one health disease surveillance from community to national levels in Africa: intervention in disease surveillance. JMIR Public Health Surveill. 2017 Dec 18;3(4):e7373. doi:10.2196/publichealth.7373
  13. Olson D, Lamb M, Lopez MR, Colborn K, Paniagua-Avila A, Zacarias A, et al. Performance of a mobile phone app-based participatory syndromic surveillance system for acute febrile illness and acute gastroenteritis in rural Guatemala. J Med Internet Res. 2017 Nov 9;19(11):e368. doi:10.2196/jmir.8041
  14. Mustapha AY, Chianumba EC, Forkuo AY, Osamika D, Komi LS. Systematic review of mobile health (mHealth) applications for infectious disease surveillance in developing countries. Int J Multidiscip Res Growth Eval. 2022 Feb;1020-33. doi:10.54660/.IJMRGE.2022.3.1.1020-1033
  15. Maddah N, Verma A, Almashmoum M, Ainsworth J. Effectiveness of public health digital surveillance systems for infectious disease prevention and control at mass gatherings: systematic review. J Med Internet Res. 2023 May 19;25:e44649. doi:10.2196/44649
  16. McClymont H, Lambert SB, Barr I, Vardoulakis S, Bambrick H, Hu W. Internet-based surveillance systems and infectious diseases prediction: an updated review of the last 10 years and lessons from the COVID-19 pandemic. J Epidemiol Glob Health. 2024 Sep;14(3):645-57. doi:10.1007/s44197-024-00272-y
  17. Kambalame D, Yelewa M, Iversen BG, Khunga N, Macdonald E, Nordstrand K, et al. Factors influencing operationalization of Integrated Disease Surveillance in Malawi. Public Health. 2024 Mar 1;228:100-4. doi:10.1016/j.puhe.2023.12.030
  18. Wu TS, Mvula MV, Chado EK, Kamanga BN, Mapemba DD, Billy RE, et al. Establishing One Health Surveillance Platform for Electronic Integrated Disease Surveillance and Response in Malawi: action design research study. JMIR Public Health Surveill. 2026 Jan 26;12:e72029. doi:10.2196/72029
  19. Pratt B, Parker M, Bull S. Equitable design and use of digital surveillance technologies during COVID-19: norms and concerns. J Empir Res Hum Res Ethics. 2022 Dec;17(5):573-86. doi:10.1177/15562646221118127
  20. Ferretti A, Vayena E. In the shadow of privacy: overlooked ethical concerns in COVID-19 digital epidemiology. Epidemics. 2022 Dec 1;41:100652. doi:10.1016/j.epidem.2022.100652
  21. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021 Mar 29;372:n71. doi:10.1136/bmj.n71
  22. Thomas J, Harden A. Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Med Res Methodol. 2008;8:45. doi:10.1186/1471-2288-8-45
  23. World Health Organization. Recommendations on Digital Interventions for Health System Strengthening. Geneva: WHO; 2019. Available from: https://www.ncbi.nlm.nih.gov/books/NBK541902/ Accessed June 14, 2026.
  24. Damschroder LJ, Reardon CM, Widerquist MA, Lowery J. The updated Consolidated Framework for Implementation Research based on user feedback. Implement Sci. 2022 Oct 29;17(1):75. doi:10.1186/s13012-022-01245-0
  25. Greenhalgh T, Wherton J, Papoutsi C, Lynch J, Hughes G, Hinder S, et al. Beyond adoption: a new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. J Med Internet Res. 2017 Nov 1;19(11):e8775. doi:10.2196/jmir.8775
  26. Hong QN, Fàbregues S, Bartlett G, Boardman F, Cargo M, Dagenais P, et al. The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. Educ Inf. 2018 Nov;34(4):285-91. doi:10.3233/EFI-180221
  27. Sterne JA, Hernán MA, Reeves BC, Savović J, Berkman ND, Viswanathan M, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ. 2016 Oct 12;355:i4919. doi:10.1136/bmj.i4919
  28. Sterne JA, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron I, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019 Aug 28;366:l4898. doi:10.1136/bmj.l4898
  29. Cochrane Effective Practice and Organisation of Care (EPOC). EPOC Resources for Review Authors. Oslo: Norwegian Institute of Public Health; 2017. Available from: https://epoc.cochrane.org/resources/epoc-resources-review-authors Accessed June 14, 2026.
  30. Critical Appraisal Skills Programme (CASP). CASP Qualitative Studies Checklist. Oxford: CASP; 2018. Available from: https://casp-uk.net/casp-tools-checklists/Accessed June 14, 2026.
  31. Moons KG, Damen JA, Kaul T, Hooft L, Navarro CA, Dhiman P, et al. PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods. BMJ. 2025 Mar 24;388:e082505. doi:10.1136/bmj-2024-082505
  32. Aromataris E, Munn Z, editors. JBI Manual for Evidence Synthesis. Adelaide: Joanna Briggs Institute; 2020. doi:10.46658/JBIMES-20-01
  33. Valerio MG, Laher B, Phuka J, Lichand G, Paolotti D, Leal Neto O. Participatory disease surveillance for the early detection of cholera-like diarrheal disease outbreaks in rural villages in Malawi: prospective cohort study. JMIR Public Health Surveill. 2024 Jul 16;10:e49539. doi:10.2196/49539
  34. El-Khatib Z, Shah M, Zallappa SN, Nabeth P, Guerra J, Manengu CT, et al. SMS-based smartphone application for disease surveillance has doubled completeness and timeliness in a limited-resource setting—evaluation of a 15-week pilot program in Central African Republic (CAR). Confl Health. 2018 Oct 24;12(1):42. doi:10.1186/s13031-018-0177-6
  35. Hirai A, Silenou B, Bukasa T, Barka BM, Mwakisenda F, Dörrbecker J, et al. Evaluating the performance of digital surveillance for epidemic-prone diseases in Kwango Province, Democratic Republic of Congo. Front Public Health. 2025 Nov 19;13:1669745. doi:10.3389/fpubh.2025.1669745
  36. Mugasha R, Kwiringira A, Ntono V, Nakiire L, Ayebazibwe I, Kyozira C, et al. Scaling up and enhancing the functionality of the Electronic Integrated Diseases Surveillance and Response System in Uganda, 2020-2022: description of the journey, challenges, and lessons learned. JMIR Public Health Surveill. 2025 Apr 14;11(1):e59783. doi:10.2196/59783
  37. Harvey D, Valkenburg W, Amara A. Predicting malaria epidemics in Burkina Faso with machine learning. PLoS One. 2021 Jun 18;16(6):e0253302. doi:10.1371/journal.pone.0253302
  38. Williams GS, Koua EL, Abdelmalik P, Kambale F, Kibangou E, Nguna J, et al. Evaluation of the epidemic intelligence from open sources (EIOS) system for the early detection of outbreaks and health emergencies in the African region. BMC Public Health. 2025 Mar 4;25(1):857. doi:10.1186/s12889-025-21998-9
  39. Edson R, Rutayisire R, El-Khatib Z, Nsekuye O, Mucunguzi HV, Muvunyi R, et al. SARS-CoV-2 detection in international travelers through wastewater-based epidemiology at the Kigali International Airport: genomic surveillance study. JMIR Public Health Surveill. 2025 Nov 27;11(1):e71104. doi:10.2196/71104
  40. Nyenswah TG, Skrip L, Stone M, Schue JL, Peters DH, Brieger WR. Documenting the development, adoption and pre-Ebola implementation of Liberia's integrated disease surveillance and response (IDSR) strategy. BMC Public Health. 2023 Oct 25;23(1):2093. doi:10.1186/s12889-023-17006-7
  41. Eneh SC, Anokwuru CC, Onukansi FO, Obi CG, Ikhuoria OV, Dauda ZU, et al. Implementation of integrated disease surveillance and response systems in West Africa: lessons learned and future directions. BMJ Health Care Inform. 2025 Jul 7;32(1):e101346. doi:10.1136/bmjhci-2024-101346
  42. Mayaki LD. Artificial intelligence-enabled early warning systems for national infectious disease surveillance: real-world evidence of accelerated outbreak detection and response. Int J Comput Artif Intell. 2026;7(1):122-37. doi:10.33545/27076571.2026.v7.i1b.254
  43. Louis FJ, Nichols L, de la Torre C, Dahourou AG. Strengthening outbreak detection in Africa to achieve the 7-1-7 global framework: challenges and opportunities. Public Health Rev. 2025 Aug 14;46:1608039. doi:10.3389/phrs.2025.1608039
  44. Struelens MJ, Ludden C, Werner G, Sintchenko V, Jokelainen P, Ip M. Real-time genomic surveillance for enhanced control of infectious diseases and antimicrobial resistance. Front Sci. 2024 Apr 25;2:1298248. doi:10.3389/fsci.2024.1298248
  45. Kaburi BB, Harries M, Hauri AM, Kenu E, Wyss K, Silenou BC, et al. Availability of published evidence on coverage, cost components, and funding support for digitalisation of infectious disease surveillance in Africa, 2003–2022: a systematic review. BMC Public Health. 2024 Jun 28;24(1):1731. doi:10.1186/s12889-024-19205-2

LICENSE

Creative Commons License
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.