Multilevel Regression Analysis for Evaluating Cost-Effectiveness of Public Health Surveillance Systems in Ghana,

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Autori principali: Boateng, Efua, Gyamfi, Abena, Agyeman, Kofi
Natura: Recurso digital
Lingua:inglese
Pubblicazione: Zenodo 2010
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author Boateng, Efua
Gyamfi, Abena
Agyeman, Kofi
author_facet Boateng, Efua
Gyamfi, Abena
Agyeman, Kofi
contents <p>Public health surveillance systems in Ghana have been established to monitor and respond to infectious diseases effectively. However, their cost-effectiveness remains a subject of debate. A longitudinal study employing multilevel logistic regression models to analyse data from surveillance records and financial reports. Uncertainty in estimates is quantified using robust standard errors. The analysis revealed that the cost-effectiveness varied significantly by geographical region, with urban areas showing a higher return on investment compared to rural settings (p < 0.05). Multilevel regression analysis successfully elucidated the factors affecting the cost-effectiveness of public health surveillance systems in Ghana. Targeted interventions should be developed for underserved regions, focusing on enhancing infrastructure and resource allocation to improve overall efficiency. Public Health Surveillance, Cost-Effectiveness Analysis, Multilevel Regression, Ghana Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18901450
institution Zenodo
language eng
publishDate 2010
publisher Zenodo
record_format zenodo
spellingShingle Multilevel Regression Analysis for Evaluating Cost-Effectiveness of Public Health Surveillance Systems in Ghana,
Boateng, Efua
Gyamfi, Abena
Agyeman, Kofi
Geographic
Multilevel
Regression
Analysis
Public
Health
Surveillance
<p>Public health surveillance systems in Ghana have been established to monitor and respond to infectious diseases effectively. However, their cost-effectiveness remains a subject of debate. A longitudinal study employing multilevel logistic regression models to analyse data from surveillance records and financial reports. Uncertainty in estimates is quantified using robust standard errors. The analysis revealed that the cost-effectiveness varied significantly by geographical region, with urban areas showing a higher return on investment compared to rural settings (p < 0.05). Multilevel regression analysis successfully elucidated the factors affecting the cost-effectiveness of public health surveillance systems in Ghana. Targeted interventions should be developed for underserved regions, focusing on enhancing infrastructure and resource allocation to improve overall efficiency. Public Health Surveillance, Cost-Effectiveness Analysis, Multilevel Regression, Ghana Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.</p>
title Multilevel Regression Analysis for Evaluating Cost-Effectiveness of Public Health Surveillance Systems in Ghana,
topic Geographic
Multilevel
Regression
Analysis
Public
Health
Surveillance
url https://doi.org/10.5281/zenodo.18901450