Cost-Effectiveness Analysis of a Regional Program for Identifying and Treating Children with Correctable Refractive Error in Indonesia.

PURPOSE: Indonesia is a rapidly growing county with over 262 million inhabitants, but among highly populated countries it has one of the lowest concentrations of eye care providers. This study evaluated the cost-effectiveness of a program implemented in South Sulawesi, Indonesia that trained school teachers to conduct vision screenings, organized in-school evaluations by opticians, and provided free eyeglasses to school children with refractive error (RE). METHODS: Schoolteachers across 6 districts in South Sulawesi were trained to screen children with possible RE for subsequent evaluation by opticians. All costs associated with designing and implementing the program (administration, training personnel, labor, service delivery, etc.) were assessed. Expenditures and outcomes data were utilized to calculate the cost per disability-adjusted-life-year (DALY) averted using both 2010 and 2016 Global Burden of Disease (GBD) weights. RESULTS: 521 teachers screened 41,212 students across 172 schools in South Sulawesi. 4,506 (10.9%) students failed screening, 2,652 were seen by optometrists, and 2,038 received glasses.The total program cost was US$97,380, with glasses (39.6%) and labor (23.3%) accounting for the two biggest expenditures. In districts with school-based refraction services, the costs per student screened, refracted, and receiving glasses were $2.57, $31.33, and $41.40, respectively; costs were $2.04, $59.80, and $73.22 when district services were instead provided centrally. The estimated cost per DALY averted was US$89.04 based on GBD 2010 weights. CONCLUSION: Treating children with correctable RE in limited resource settings can be done cost-effectively through a school-based model.

A model for estimating costs and benefits of new vaccine technologies from the perspective of both buyers and sellers.

Although vaccination is widely considered one of the most cost-effective health interventions available, global coverage rates for many vaccines remain lower than necessary for disease elimination and eradication. New vaccine technologies can play an important role in addressing barriers to vaccination and increasing coverage rates. To identify and prioritize vaccine technology investments, decision makers must be able to compare the overall costs and benefits of each investment option. While these data points may exist, they are often confined to silos. Decision makers would benefit from a model that synthesizes this broad range of data and provides clear and actionable information. To facilitate vaccine investment, purchasing and deployment decisions, we developed a systematic and transparent cost-benefit model that estimates the value and risk of a given investment scenario from the perspective of both "buyers" (e.g., global donors, country governments) and "sellers" (e.g., developers, manufacturers) of vaccines. This model, which can be used to evaluate scenarios related to a single vaccine presentation or a portfolio of vaccine presentations, leverages our published approach for estimating the impact of improved vaccine technologies on vaccination coverage rates. This article presents a description of the model and provides an illustrative example application to a portfolio of measles-rubella vaccine technologies currently under development. Although the model is generally applicable to organizations involved in vaccine investment, manufacturing or purchasing, we believe it may be particularly useful to those engaged in vaccine markets that rely strongly on funding from institutional donors.

A method for estimating the impact of new vaccine technologies on vaccination coverage rates.

Vaccines are one of the most cost-effective tools for improving human health and well-being. The impact of a vaccine on population health is partly determined by its coverage rate, the proportion of eligible individuals vaccinated. Coverage rate is a function of the vaccine presentation and the population in which that presentation is deployed. This population includes not only the individuals vaccinated, but also the logistics and healthcare systems responsible for vaccine delivery. Because vaccine coverage rates remain below targets in many settings, vaccine manufacturers and purchasers have a shared interest in better understanding the relationship between vaccine presentation, population characteristics, and coverage rate. While there have been some efforts to describe this relationship, existing research and tools are limited in their ability to quantify coverage rate changes across a broad set of antigens, vaccine presentations, and geographies. In this article, we present a method for estimating the impact of improved vaccine technologies on vaccination coverage rates. It is designed for use with low- and middle-income country vaccination programs. This method uses publicly available data and simple calculations based on probability theory to generate coverage rate values. We first present the conceptual framework and mathematical approach. Using a Microsoft Excel-based implementation, we then apply the method to a vaccine technology in early-stage development: micro-array patch for a measles-rubella vaccine (MR-MAP). Example outputs indicate that a complete switch from the current subcutaneous presentation to MR-MAP in the 73 countries ever eligible for Gavi support would increase overall vaccination coverage by 3.0-4.9 percentage points depending on the final characteristics of the MR-MAP. This change equates to an additional 2.6-4.2 million children vaccinated per year. Our method can be readily extended to other antigens and vaccine technologies to provide quick, low-cost estimates of coverage impact. As vaccine manufacturers and purchasers face increasingly complex decisions, such estimates could facilitate objective comparisons between options and help these decision makers obtain the most value for money.

A Rapid Cost Modeling Tool for Evaluating and Improving Public Health Supply Chain Designs.

Effective and efficient health supply chains play a vital role in achieving health outcomes by ensuring supplies are available for people to access quality health services. However, supplying health commodities to service delivery points is complex and costly in many low- and middle-income countries. Thus, governments and partner organizations are often interested in understanding how to design their health supply chains more cost efficiently.Several modeling tools exist in the public and private market that can help assess supply chain efficiency and identify supply chain design improvements. These tools are generally capable of providing users with very precise cost estimates, but they often use proprietary software and require detailed data inputs. This can result in a somewhat lengthy and expensive analysis process, which may be prohibitive for many decision makers, especially in the early stages of a supply chain design process. For many use cases, such as advocacy, informing workshop and technical meetings, and narrowing down initial design options, decision makers may often be willing to trade some detail and accuracy in exchange for quicker and lower-cost analysis results. To our knowledge, there are no publicly available tools focused on generating quick, high-level estimates of the cost and efficiency of different supply chain designs.To address this gap, we designed and tested an Excel-based Rapid Supply Chain Modeling (RSCM) Tool. Our assessment indicated that, despite requiring significantly less data, the RSCM Tool can generate cost estimates that are similar to other common analysis and modeling methods. Furthermore, to better understand how the RSCM Tool aligns with real-world processes and decision-making timelines, we used it to inform an ongoing immunization supply chain redesign in Angola. For the use cases described above we believe that the RSCM Tool addresses an important need for quicker and less expensive ways to identify more cost-efficient supply chain designs.