Incorporation of model-based quantitative estimation techniques into government policymaking for HIV care and treatment

Issues: In the setting of HIV care and treatment, where simplified quantifications are of limited utility due to the complex nature of the systems involved, model-based quantitative estimation techniques can be a valuable tool to support decisionmaking. Description: CSHOR has developed a simulation-based resource planning model for HIV care and treatment in resource limited settings called SIMCLIN. The model uses as inputs the epidemiologic profile, treatment protocol, and clinic operations data to simulate the clinical experience of patients, and tabulates the resources required to deliver care according to the treatment protocol (including human resources, antiretrovirals, drugs to prevent and treat opportunistic infections, and laboratory tests.). SIMCLIN reads in inputs from an MS Access database and outputs directly to MS Word and can be applied at a clinic, regional, and national level. Lessons Learned: We have used the model to estimate the: 1) resources required to support a treatment and scale-up plan; 2) maximum patient capacity that can be supported in a system with constrained resources; and 3) change in resource requirements and patient capacity if treatment protocols or clinic operations are altered. CSHOR disseminates results and policy implications to maximize the impact of the model applications. Recommendations: SIMCLIN is a flexible model that provides data to assist policymakers with decisions about resource allocation and optimal design of systems and protocols. We will discuss examples from our work with the governments of Ethiopia and Tanzania to demonstrate ways they have incorporated these techniques into their policy making at different levels.