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March 22, 20260 citationsOpen Access

Reliability Measurement in Ghanaian Public Health Surveillance Systems: A Randomized Field Trial Approach

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NANana AmeyawDODaaqu OseiAAAli Abayomi

Key Points

  • The study aims to evaluate the reliability of public health surveillance systems in Ghana using rigorous methodological approaches.
  • Conducted a randomized field trial to assess public health surveillance reliability.
  • Utilized a mixed-methods design, incorporating both surveys and interviews.
  • Formulated a model with verifiable assumptions for reliability measurement.
  • Established a bounded error under perturbation conditions.
  • Demonstrated a convergent estimation process that links metrics to outcomes.
  • Found that a transparent analytical basis can support future research applications.

Abstract

This study addresses a current research gap in Medicine concerning Methodological evaluation of public health surveillance systems systems in Ghana: randomized field trial for measuring system reliability in Ghana. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of public health surveillance systems systems in Ghana: randomized field trial for measuring system reliability, Ghana, Africa, Medicine, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.

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Cite This Study

Ameyaw et al. (2015) studied this question.

synapsesocial.com/papers/69bf89a9f665edcd009e9779https://doi.org/10.5281/zenodo.19126148
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