Background The rapid growth of mobile technology has given rise to the development of mobile health (mHealth) applications aimed at treating and preventing a wide range of health conditions. However, evidence on the use of mHealth in high disease burdened settings such as sub-Sharan Africa is not clear. Given this, we systematically mapped evidence on mHealth for disease diagnosis and treatment support by health workers in sub-Saharan Africa. Methods We conducted a scoping review study guided by the Arksey and O’Malley’s framework, Levac et al. recommendations, and Joanna Briggs Institute guidelines. We thoroughly searched the following databases: MEDLINE and CINAHL with full text via EBSCOhost; PubMed; Science Direct and Google Scholar for relevant articles from the inception of mHealth technology to April 2020. Two reviewers independently screened abstracts and full-text articles using the eligibility criteria as reference. This study employed the mixed methods appraisal tool version 2018 to assess the methodological quality of the included studies. Results Out of the 798 articles identified, only 12 published articles presented evidence on the availability and use of mHealth for disease diagnosis and treatment support by health workers in SSA since 2010. Of the 12 studies, four studies were conducted in Kenya; two in Malawi; two in Nigeria; one in South Africa; one in Zimbabwe; one in Mozambique, and one in Lesotho. Out of the 12 studies, one reported the use of mHealth for diseases diagnosis; three reported the use of mHealth to manage HIV; two on the management of HIV/TB; two on the treatment of malaria; one each on the management of hypertension; cervical cancer; and three were not specific on any disease condition. All the 12 included studies underwent methodological quality appraisal with a scored between 70 and 100%. Conclusions The study shows that there is limited research on the availability and use of mHealth by health workers for disease diagnosis and treatment support in sub-Saharan Africa. We, therefore, recommend primary studies focusing on the use of mHealth by health workers for disease diagnosis and treatment support in sub-Saharan Africa.

Background: In sub-Saharan Africa (SSA), most prisons are overcrowded with poor ventilation and put prisoners disproportionally at risk of exposure to Mycobacterium tuberculosis (TB) and developing TB infection but are mostly missed due to poor access to healthcare. Active case-finding (ACF) of TB in prisons facilitates early diagnosis and treatment of inmates and prevent the spread. We explored literature and described evidence on TB ACF interventions and approaches for prisoners in SSA prisons. Methods: Guided by the Arksey and O'Malley framework, we searched PubMed, Google Scholar, SCOPUS, Academic search complete, CINAHL and MEDLINE with full text via EBSCOhost for articles on prisoners and ACF from 2000 to May 2019 with no language restriction. Two investigators independently screened the articles at the abstract and fulltext stages in parallel guided by the eligibility criteria as well as performed the methodological quality appraisal of the included studies using the latest mixed-method appraisal tool. We extracted all relevant data, organized them into themes and sub-themes, and presented a narrative summary of the results. Results: Of the 391 eligible articles found, 31 met the inclusion criteria. All 31 articles were published between 2006 and 2019 with the highest six (19.4%) in 2015. We found evidence in 11 countries. That is

Background: The rapid growth of mobile technology has given rise to the development of mobile health programmes aimed at treating and preventing a wide range of health conditions. However, evidence on the use of mHealth in high disease burdened settings such as SSA is not clear. We systematically mapped evidence on mHealth for disease diagnosis and treatment support by health workers in SSA. Methods: We conducted a scoping review study guided by the Arksey and O’Malley’s framework, Levac et al recommendations, and Joanna Briggs Institute guidelines. We thoroughly searched the following databases: MEDLINE and CINAHL with full-text via EBSCOhost; PubMed; Science Direct and Google Scholar for relevant articles from inception to July 2019. Two independent reviewers screened abstracts and full-text articles using the eligibility criteria as reference. This study employed the mixed methods appraisal tool version 2018 to assess the methodological quality of the included studies. Results: Out of the 572 articles identified , only 10 published articles presented evidence on mHealth for treatment support by health workers in SSA since 2010. No studies reported evidence on mHealth for disease diagnosis by health workers in SSA. Of the 10 studies, four studies were conducted in Kenya; one in South Africa; one in Malawi; one in Zimbabwe; one in Mozambique; one in Nigeria and one in Lesotho. Of the 10 studies: three reported the use of mHealth to manage HIV; two on the management of HIV/TB; two on treatment of malaria; one each on the management of hypertension; cervical cancer; and one was not specific on any disease condition. All the 10 included studies underwent methodological quality appraisal with a scored between 70 and 100%. Conclusions: The study shows that there is limited research on the availability and use of mHealth by health workers for treatment support in SSA. This study also shows there is no literature on the availability and use of mHealth by health workers for disease diagnosis in SSA. We, therefore, recommend primary studies focusing on the use of mHealth by health workers for disease diagnosis in SSA. Keywords: Mobile Health; Disease diagnosis; Treatment support; sub-Saharan Africa

Mobile health devices are emerging applications that could help deliver point-of-care (POC) diagnosis, particularly in settings with limited laboratory infrastructure, such as Sub-Saharan Africa (SSA). The advent of Severe acute respiratory syndrome coronavirus 2 has resulted in an increased deployment and use of mHealth-linked POC diagnostics in SSA. We performed a systematic review and meta-analysis to evaluate the accuracy of mobile-linked point-of-care diagnostics in SSA. Our systematic review and meta-analysis were guided by the Preferred Reporting Items requirements for Systematic Reviews and Meta-Analysis. We exhaustively searched PubMed, Science Direct, Google Scholar, MEDLINE, and CINAHL with full text via EBSCOhost databases, from mHealth inception to March 2021. The statistical analyses were conducted using OpenMeta-Analyst software. All 11 included studies were considered for the meta-analysis. The included studies focused on malaria infections, Schistosoma haematobium, Schistosoma mansoni, soil-transmitted helminths, and Trichuris trichiura. The pooled summary of sensitivity and specificity estimates were moderate compared to those of the reference representing the gold standard. The overall pooled estimates of sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of mobile-linked POC diagnostic devices were as follows: 0.499 (95% CI: 0.458–0.541), 0.535 (95% CI: 0.401–0.663), 0.952 (95% CI: 0.60–1.324), 1.381 (95% CI: 0.391–4.879), and 0.944 (95% CI: 0.579–1.538), respectively. Evidence shows that the diagnostic accuracy of mobile-linked POC diagnostics in detecting infections in SSA is presently moderate. Future research is recommended to evaluate mHealth devices’ diagnostic potential using devices with excellent sensitivities and specificities for diagnosing diseases in this setting.

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