About this Research Topic
Optimizing health care at structural, institutional, and personal levels is an ongoing challenge globally. The management of sexually transmitted infections (STIs) and HIV have enjoyed significant success in the wake of advancing technological and innovation developments to mitigate them. Despite these advances, particularly in low-income settings, clinical care has suffered limited success because of the effects of financial constraints. Health departments experience difficulties with keeping up with the demand for timely testing, medical care facilities suffer the effects of limited human and physical resources, and the general public often fall victim to impoverishment by not being able to access medical testing and or management opportunities for a multitude of reasons. Therefore, it becomes imperative to identify strategies that already work, as well as innovations that will allow all stakeholders in the healthcare continuum to enhance programs, particularly in under-resourced environments.
In low- and middle-income countries (LMIC), resource availability, confidentiality concerns, costs related to testing for diseases, and accessing complementary medication have hindered the management of HIV and STIs. Accordingly, research into addressing the aforementioned concerns has been undertaken. The use of electronic health (eHealth) and mobile health (mHealth) interventions has been explored, to facilitate efficiency at a structural level, and also to support patients to take ownership for their health. eHealth and mHealth, despite requiring some fine-tuning, have shown promise. Machine learning (ML), another innovation, can be used to predict disease susceptibility. These innovations together with community centered healthcare service delivery and pharmacy level identification and management of HIV and other STIs exhibit enormous potential in assisting the World Health Organization (WHO) to achieve its AIDS eradication goal by 2030 is enormous.
Topics may include, but are by no means limited to:
• Systematic reviews of trends, strengths, and weaknesses of HIV and STI healthcare service delivery in the current LMIC context
• Comparative studies on m/eHealth initiatives vs traditional healthcare methods
• Case studies on m/eHealth initiatives in sub-Saharan Africa and LMIC
• Usability and feasibility studies on innovations within the digital healthcare realm
• The impact of e/mhealth on patient participation in the full range of care and prevention, ranging from screening, linkage to care, treatment, behavioral interventions
• The impact of predictive analysis like ML in identifying population groups who are at higher risk of contracting HIV and/or other STIs
• Usability and feasibility studies related to the use of ML
• The impact of mobile applications on disease management
• Community delivered healthcare
• Self-management/self-monitoring
In low- and middle-income countries (LMIC), resource availability, confidentiality concerns, costs related to testing for diseases, and accessing complementary medication have hindered the management of HIV and STIs. Accordingly, research into addressing the aforementioned concerns has been undertaken. The use of electronic health (eHealth) and mobile health (mHealth) interventions has been explored, to facilitate efficiency at a structural level, and also to support patients to take ownership for their health. eHealth and mHealth, despite requiring some fine-tuning, have shown promise. Machine learning (ML), another innovation, can be used to predict disease susceptibility. These innovations together with community centered healthcare service delivery and pharmacy level identification and management of HIV and other STIs exhibit enormous potential in assisting the World Health Organization (WHO) to achieve its AIDS eradication goal by 2030 is enormous.
Topics may include, but are by no means limited to:
• Systematic reviews of trends, strengths, and weaknesses of HIV and STI healthcare service delivery in the current LMIC context
• Comparative studies on m/eHealth initiatives vs traditional healthcare methods
• Case studies on m/eHealth initiatives in sub-Saharan Africa and LMIC
• Usability and feasibility studies on innovations within the digital healthcare realm
• The impact of e/mhealth on patient participation in the full range of care and prevention, ranging from screening, linkage to care, treatment, behavioral interventions
• The impact of predictive analysis like ML in identifying population groups who are at higher risk of contracting HIV and/or other STIs
• Usability and feasibility studies related to the use of ML
• The impact of mobile applications on disease management
• Community delivered healthcare
• Self-management/self-monitoring
Keywords: eHealth, mHealth, Machine learning, healthcare innovation, HIV, community healthcare
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