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. Author manuscript; available in PMC: 2019 Oct 3.
Published in final edited form as: Nature. 2019 Feb 27;566(7745):467–474. doi: 10.1038/s41586-019-0956-2

Table 1. Examples of mHealth enhancement of infectious disease diagnosis, treatment and control.

Area Function mHealth Opportunities

Outbreak Identification Novel outbreak monitoring Electronic collection of epidemiological and clinical data

Diagnosis Community or self-testing Early detection, automated result capture and analysis
Disease characterisation Portable genetic sequencing of samples (e.g. to identify emerging drug resistance)
Syndromic surveillance Multi source data capture and passive reporting (e.g. activity levels and location history)

Treatment and Patient Management Linkage to clinical care Mobile connection to clinical care (decision trees, electronic prescribing)
More efficient and effective use of stakeholder time Automated report generation and supply chain management, reduce transcription errors in reporting
Chronic infection monitoring and response to therapy Long term biomarker reporting and analysis to guide community-based medication and care

Disease Control and Elimination Cluster ‘hot spot’ identification

Outbreak response

Epidemic control
Rapid geospatial and phylogenetic mapping

Real time reporting to public health agencies to implement control strategies via connected clinical and public health systems

Social media queries capture and mapping during outbreaks

Electronic implementation of control measures

Data visualisation for epidemiological and clinical mapping, contact management and monitoring the effectiveness of interventions

Targeted information dissemination