Spatial and spatiotemporal pattern of stroke relative risk in Ghana using Bayesian modelling approach

Abstract

This study offers valuable insights that can inform resource allocation to regions experiencing elevated stroke risk. Identified high-risk regions can inform targeted screening strategies, referral pathway strengthening, and resource prioritization. Diagnostic capacity (including CT/MRI access), health-facility reporting quality, and surveillance system upgrades needed to reduce measurement bias and improve case ascertainment. Furthermore, we situate the findings within Ghana's existing noncommunicable disease (NCD) policy frameworks and describe how routine updates of the model using new DHIMS2 data can support ongoing decision-making.