Emerging technologies' role in reducing under-five mortality in a low-resource setting: Challenges and perceived opportunities by public health workers in Makonde District, Zimbabwe.
John BataniManoj Sewak MaharajPublished in: Journal of child health care : for professionals working with children in the hospital and community (2023)
Under-five mortality (U5M) remains a global challenge, with Sub-Saharan Africa being the hardest hit. The coronavirus disease 2019 (COVID-19) has strained healthcare systems, threatening to reverse current gains in U5M health outcomes. It threatened progress made towards achieving United Nations Sustainable Development Goal 3 due to its strain on healthcare systems, resource reassignment and its prioritisation by health authorities globally. Low-resource settings inherently face unique challenges in fighting U5M and providing quality healthcare to under-fives, like understaffing, drug shortages, underfunding, skills gaps and lack of specialised healthcare equipment, contributing to high U5M rates. This study explored public health facilities' challenges in reducing U5M in a low-resource setting in Zimbabwe and public health workers' perceptions of emerging technologies' role in addressing those challenges. Twenty public health workers participated in interviews and a focus group. They perceived emerging technologies (ETs) as a panacea to the challenges by supporting data-driven healthcare, improving follow-up outcomes through automated reminders of medication and clinic visits, aiding diagnosis, continuous monitoring, health education, drug supply monitoring, critical supplies delivery and skills development. In this paper, emerging technology is any information and communication technology that has not been utilised to its full potential in Zimbabwe's public health domain. Findings indicate that public health workers in Makonde would welcome ETs to improve under-five health and well-being.
Keyphrases
- public health
- healthcare
- coronavirus disease
- global health
- health information
- transcription factor
- mental health
- primary care
- sars cov
- depressive symptoms
- cardiovascular events
- physical activity
- risk factors
- type diabetes
- deep learning
- metabolic syndrome
- risk assessment
- machine learning
- skeletal muscle
- quality improvement
- south africa
- respiratory syndrome coronavirus
- climate change
- adipose tissue