Trade-offs between clinical performance and test accessibility in tuberculosis diagnosis: a multi-country modelling approach for target product profile development.

BACKGROUND: Tuberculosis continues to be a leading cause of infectious disease mortality, and effective screening and diagnosis remains crucial. Despite progress made, diagnostic gaps remain due to poor access to diagnostic tools and testing, particularly in rural and remote areas. As such, the development of target product profiles is essential in guiding the development of new diagnostic tools, however target product profiles often lack evidence-based information and do not consider trade-offs between test accuracy and accessibility. METHODS: A simulation-based model, in the form of a decision tree, was used to map out the baseline patient tuberculosis diagnostic pathway for individuals in Kenya, South Africa, and India. The model was then used to adapt this pathway to evaluate the trade-offs between increased access to testing and varying accuracy of new tuberculosis diagnostic tools within the health-care contexts of Kenya, South Africa, and India. The model aims to support target product profile development by quantifying the impact of new diagnostics on the standard of care. The model considered three diagnostic attributes, namely sample type (sputum vs non-sputum), site of testing (point of care, near point of care, and health setting) and turnaround time. FINDINGS: Our results indicate that per sample type, novel point-of-care tests would be the most accessible and even with lower sensitivities can achieve comparable or better case detection than the current standard of care in each country. Non-sputum diagnostics also have lower sensitivity requirements. Overall, target product profile parameters with reduced sensitivities from 70% for non-sputum and 78% for sputum tests could be accepted. INTERPRETATION: Diagnostics which bring tuberculosis tests and test results closer to the patient could reduce overall diagnostic loss despite potential reductions in sensitivity. This work provides a novel framework for guiding the future development of diagnostics, with an approach towards balancing accessibility and test performance. FUNDING: The Bill and Melinda Gates Foundation (INV-045721).

Impact and cost-effectiveness of SARS-CoV-2 self-testing strategies in schools: a multicountry modelling analysis.

OBJECTIVES: To determine the most epidemiologically effective and cost-effective school-based SARS-CoV-2 antigen-detection rapid diagnostic test (Ag-RDT) self-testing strategies among teachers and students. DESIGN: Mathematical modelling and economic evaluation. SETTING AND PARTICIPANTS: Simulated school and community populations were parameterised to Brazil, Georgia and Zambia, with SARS-CoV-2 self-testing strategies targeted to teachers and students in primary and secondary schools under varying epidemic conditions. INTERVENTIONS: SARS-CoV-2 Ag-RDT self-testing strategies for only teachers or teachers and students-only symptomatically or symptomatically and asymptomatically at 5%, 10%, 40% or 100% of schools at varying frequencies. OUTCOME MEASURES: Outcomes were assessed in terms of total infections and symptomatic days among teachers and students, as well as total infections and deaths within the community under the intervention compared with baseline. The incremental cost-effectiveness ratios (ICERs) were calculated for infections prevented among teachers and students. RESULTS: With respect to both the reduction in infections and total cost, symptomatic testing of all teachers and students appears to be the most cost-effective strategy. Symptomatic testing can prevent up to 69·3%, 64·5% and 75·5% of school infections in Brazil, Georgia and Zambia, respectively, depending on the epidemic conditions, with additional reductions in community infections. ICERs for symptomatic testing range from US$2 to US$19 per additional school infection averted as compared with symptomatic testing of teachers alone. CONCLUSIONS: Symptomatic testing of teachers and students has the potential to cost-effectively reduce a substantial number of school and community infections.

Cost of SARS-CoV-2 self-test distribution programmes by different modalities: a micro-costing study in five countries (Brazil, Georgia, Malaysia, Ethiopia and the Philippines).

OBJECTIVE: Diagnostic testing is an important tool to combat the COVID-19 pandemic, yet access to and uptake of testing vary widely 3 years into the pandemic. The WHO recommends the use of COVID-19 self-testing as an option to help expand testing access. We aimed to calculate the cost of providing COVID-19 self-testing across countries and distribution modalities. DESIGN: We estimated economic costs from the provider perspective to calculate the total cost and the cost per self-test kit distributed for three scenarios that differed by costing period (pilot, annual), the number of tests distributed (actual, planned, scaled assuming an epidemic peak) and self-test kit costs (pilot purchase price, 50% reduction). SETTING: We used data collected between August and December 2022 in Brazil, Georgia, Malaysia, Ethiopia and the Philippines from pilot implementation studies designed to provide COVID-19 self-tests in a variety of settings-namely, workplace and healthcare facilities. RESULTS: Across all five countries, 173 000 kits were distributed during pilot implementation with the cost/test distributed ranging from $2.44 to $12.78. The cost/self-test kit distributed was lowest in the scenario that assumed implementation over a longer period (year), with higher test demand (peak) and a test kit price reduction of 50% ($1.04-3.07). Across all countries and scenarios, test procurement occupied the greatest proportion of costs: 58-87% for countries with off-site self-testing (outside the workplace, for example, home) and 15-50% for countries with on-site self-testing (at the workplace). Staffing was the next key cost driver, particularly for distribution modalities that had on-site self-testing (29-35%) versus off-site self-testing (7-27%). CONCLUSIONS: Our results indicate that it is likely to cost between $2.44 and $12.78 per test to distribute COVID-19 self-tests across common settings in five heterogeneous countries. Cost-effectiveness analyses using these results will allow policymakers to make informed decisions on optimally scaling up COVID-19 self-test distribution programmes across diverse settings and evolving needs.