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Review
. 2019 Feb;566(7745):467-474.
doi: 10.1038/s41586-019-0956-2. Epub 2019 Feb 27.

Taking connected mobile-health diagnostics of infectious diseases to the field

Affiliations
Review

Taking connected mobile-health diagnostics of infectious diseases to the field

Christopher S Wood et al. Nature. 2019 Feb.

Abstract

Mobile health, or 'mHealth', is the application of mobile devices, their components and related technologies to healthcare. It is already improving patients' access to treatment and advice. Now, in combination with internet-connected diagnostic devices, it offers novel ways to diagnose, track and control infectious diseases and to improve the efficiency of the health system. Here we examine the promise of these technologies and discuss the challenges in realizing their potential to increase patients' access to testing, aid in their treatment and improve the capability of public health authorities to monitor outbreaks, implement response strategies and assess the impact of interventions across the world.

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Conflict of interest statement

Author Information

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1
The growing power of low cost smartphones. Smartphone adoption (the percentage of global (red) or sub-Saharan Africa (blue) mobile phone connections that come from a smartphone), processor speed (CPU clock frequency) and camera resolution (primary camera megapixels) of the flagship models of popular smartphone manufacturers. The stated processor speed takes into account multiple processor cores at a parallelisation of 50 %. “High End” models retail for between approximately € 610-1000 whereas “Low Cost” models retail for between € 60-160.
Figure 2
Figure 2
Deploying an mHealth connected diagnostic. The stages, stakeholders, example outcomes (blue) and challenges (red) to deploying an effective mHealth intervention that employs a connected diagnostic device.
Figure 3
Figure 3
Diagnosis by device. How a connected diagnostic test can be used to detect disease markers - from the physical to the molecular – via sensors either built into or external to the phone.
Figure 4
Figure 4
The digital and healthcare divide in Uganda. Map of healthcare facilities (2012) and the population density (2015) >5 km from healthcare facilities. Areas and healthcare facilities are coloured according to the generation of cellular network in range, where the range is calculated from cell tower location and the distance of the furthest measured signal. The white circles around the health facilities indicate the 5 km radius threshold.

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