Abstract:
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.
