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March 12, 20260 citationsOpen Access

Methodological Evaluation of Public Health Surveillance Systems Adoption in Tanzanian Settings: A Quasi-Experimental Design Study

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KGKamwita Gahinyoga

Key Points

  • This study aims to evaluate the adoption of public health surveillance systems in different Tanzanian settings, identifying key factors influencing adoption.
  • Utilized a mixed-methods approach combining quantitative surveys and qualitative interviews.
  • Data collected from healthcare facilities across three diverse Tanzanian regions.
  • Employed quasi-experimental design to analyze adoption rates influenced by local governance and resources.
  • Adoption rates were 30% in rural areas compared to 50% in urban areas.
  • Local governance structures and resource availability significantly influenced surveillance system adoption.
  • Interviews indicated challenges in training and support for staff in underserved regions.

Abstract

Public health surveillance systems are essential for monitoring diseases and outbreaks in Tanzania, where resources are often limited. However, their adoption varies among different regions and institutions. A mixed-methods approach was employed, combining quantitative data from surveys with qualitative insights from interviews. Data were collected from healthcare facilities across three regions in Tanzania, representing diverse health systems. The findings indicate that adoption rates varied significantly by region (30% in rural areas vs. 50% in urban areas), primarily influenced by local governance structures and resource availability. Interviews revealed challenges related to training and support for staff. This study provides a comprehensive methodological framework for evaluating public health surveillance systems, highlighting the importance of tailored interventions based on regional context. Health authorities should prioritise targeted training programmes and logistical support in underserved regions to improve system adoption and effectiveness. public health surveillance, Tanzanian settings, quasi-experimental design, adoption rates, healthcare facilities Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.

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Cite This Study

Kamwita Gahinyoga (2011) studied this question.

synapsesocial.com/papers/69b2581996eeacc4fcec76a1https://doi.org/10.5281/zenodo.18925673
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