Big Data Analytics for Integrated Infectious Disease Surveillance in sub-Saharan Africa
Background: Infectious disease outbreaks are common in sub-Saharan Africa (SSA). Consequently, integrated public health surveillance has become increasingly essential for the region. Health surveillance systems enable early detection and monitoring of emerging and re-emerging disease outbreaks, thus...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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AOSIS
2024-01-01
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| Series: | South African Journal of Information Management |
| Subjects: | |
| Online Access: | https://sajim.co.za/index.php/sajim/article/view/1668 |
| _version_ | 1797336119342268416 |
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| author | Mourine S. Achieng Oluwamayowa O. Ogundaini |
| author_facet | Mourine S. Achieng Oluwamayowa O. Ogundaini |
| author_sort | Mourine S. Achieng |
| collection | DOAJ |
| description | Background: Infectious disease outbreaks are common in sub-Saharan Africa (SSA). Consequently, integrated public health surveillance has become increasingly essential for the region. Health surveillance systems enable early detection and monitoring of emerging and re-emerging disease outbreaks, thus informing preparedness and response measures. However, complex and intertwined factors obstruct a successful integrated public health surveillance in SSA, with dire consequences.
Objectives: The objective of this article was to establish how big data analytics can be used to enhance integrated infectious disease surveillance and response in SSA.
Method: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was used to identify and select relevant articles. A total of 10 studies that addressed the article’s objective were selected.
Results: Findings reveal several barriers to the application of big data analytics for public health surveillance in SSA. These include the absence of regulatory and data governance frameworks for big data management in healthcare, disparities in digital health infrastructure across SSA’s healthcare systems, and the digital and analytical skills required for data capture and interpretation. The development of regulatory frameworks is essential for the ethical application of analytical technologies such as artificial intelligence.
Conclusion: This article’s contributions emphasise the need for comprehensive strategies for the application of big data analytics for public health surveillance, as well as addressing barriers to its successful application by highlighting the requirements for an integrated infectious disease surveillance and response system in SSA.
Contribution: The article contributes to the body of knowledge on the interplay between the public health space and digital health interventions by emphasising the beneficial applications of big data analytics for surveillance and response to address emerging and re-emerging infectious disease outbreaks in the health systems of sub-Saharan Africa. |
| first_indexed | 2024-03-08T08:49:32Z |
| format | Article |
| id | doaj.art-94e90c1e94ac41eabee15329bdcacee8 |
| institution | Directory Open Access Journal |
| issn | 2078-1865 1560-683X |
| language | English |
| last_indexed | 2024-03-08T08:49:32Z |
| publishDate | 2024-01-01 |
| publisher | AOSIS |
| record_format | Article |
| series | South African Journal of Information Management |
| spelling | doaj.art-94e90c1e94ac41eabee15329bdcacee82024-02-01T12:48:41ZengAOSISSouth African Journal of Information Management2078-18651560-683X2024-01-01261e1e1110.4102/sajim.v26i1.1668774Big Data Analytics for Integrated Infectious Disease Surveillance in sub-Saharan AfricaMourine S. Achieng0Oluwamayowa O. Ogundaini1Department of Digital Transformation and Innovation, Graduate School of Business Leadership, University of South Africa, MidrandDepartment of Digital Transformation and Innovation, Graduate School of Business Leadership, University of South Africa, MidrandBackground: Infectious disease outbreaks are common in sub-Saharan Africa (SSA). Consequently, integrated public health surveillance has become increasingly essential for the region. Health surveillance systems enable early detection and monitoring of emerging and re-emerging disease outbreaks, thus informing preparedness and response measures. However, complex and intertwined factors obstruct a successful integrated public health surveillance in SSA, with dire consequences. Objectives: The objective of this article was to establish how big data analytics can be used to enhance integrated infectious disease surveillance and response in SSA. Method: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was used to identify and select relevant articles. A total of 10 studies that addressed the article’s objective were selected. Results: Findings reveal several barriers to the application of big data analytics for public health surveillance in SSA. These include the absence of regulatory and data governance frameworks for big data management in healthcare, disparities in digital health infrastructure across SSA’s healthcare systems, and the digital and analytical skills required for data capture and interpretation. The development of regulatory frameworks is essential for the ethical application of analytical technologies such as artificial intelligence. Conclusion: This article’s contributions emphasise the need for comprehensive strategies for the application of big data analytics for public health surveillance, as well as addressing barriers to its successful application by highlighting the requirements for an integrated infectious disease surveillance and response system in SSA. Contribution: The article contributes to the body of knowledge on the interplay between the public health space and digital health interventions by emphasising the beneficial applications of big data analytics for surveillance and response to address emerging and re-emerging infectious disease outbreaks in the health systems of sub-Saharan Africa.https://sajim.co.za/index.php/sajim/article/view/1668big data analyticsintegrated infectious disease surveillancepublic healthdigital healthhealth securityhealth systemssub-saharan africa |
| spellingShingle | Mourine S. Achieng Oluwamayowa O. Ogundaini Big Data Analytics for Integrated Infectious Disease Surveillance in sub-Saharan Africa South African Journal of Information Management big data analytics integrated infectious disease surveillance public health digital health health security health systems sub-saharan africa |
| title | Big Data Analytics for Integrated Infectious Disease Surveillance in sub-Saharan Africa |
| title_full | Big Data Analytics for Integrated Infectious Disease Surveillance in sub-Saharan Africa |
| title_fullStr | Big Data Analytics for Integrated Infectious Disease Surveillance in sub-Saharan Africa |
| title_full_unstemmed | Big Data Analytics for Integrated Infectious Disease Surveillance in sub-Saharan Africa |
| title_short | Big Data Analytics for Integrated Infectious Disease Surveillance in sub-Saharan Africa |
| title_sort | big data analytics for integrated infectious disease surveillance in sub saharan africa |
| topic | big data analytics integrated infectious disease surveillance public health digital health health security health systems sub-saharan africa |
| url | https://sajim.co.za/index.php/sajim/article/view/1668 |
| work_keys_str_mv | AT mourinesachieng bigdataanalyticsforintegratedinfectiousdiseasesurveillanceinsubsaharanafrica AT oluwamayowaoogundaini bigdataanalyticsforintegratedinfectiousdiseasesurveillanceinsubsaharanafrica |