Panel data analysis reveals that surveillance measures boost yield improvement in districts, highlighting effective strategies.
Public health surveillance systems are crucial for monitoring infectious diseases in Ghana. These systems often face challenges in data collection and analysis. The study employs a fixed effects model (FE) for panel data estimation. The specific equation is: Yᵢₜ = eta₀ + eta₁Dᵢₜ + eta₂Xᵢₜ + uᵢ, where Yᵢₜ represents the yield improvement in year t of district i, Dᵢₜ is a binary indicator for whether district i implemented surveillance measures, and Xᵢₜ includes other explanatory variables. The uncertainty around the parameter estimates will be quantified using robust standard errors. The analysis reveals that implementing specific surveillance measures in districts led to an average increase of 20% in yield improvement over a two-year period. This study provides evidence on the effectiveness of certain strategies for improving public health surveillance systems in Ghana, offering valuable insights for policymakers and researchers. Policymakers should prioritise funding for districts that show consistent improvements in yield improvement through surveillance measures. Further research is needed to identify the optimal combination of interventions across different regions. Public Health Surveillance, Panel Data Analysis, Yield Improvement, Ghana
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Asare et al. (2004) studied this question.