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).

Diagnostic yield as an important metric for the evaluation of novel tuberculosis tests: rationale and guidance for future research.

Better access to tuberculosis testing is a key priority for fighting tuberculosis, the leading cause of infectious disease deaths in people. Despite the roll-out of molecular WHO-recommended rapid diagnostics to replace sputum smear microscopy over the past decade, a large diagnostic gap remains. Of the estimated 10·6 million people who developed tuberculosis globally in 2022, more than 3·1 million were not diagnosed. An exclusive focus on improving tuberculosis test accuracy alone will not be sufficient to close the diagnostic gap for tuberculosis. Diagnostic yield, which we define as the proportion of people in whom a diagnostic test identifies tuberculosis among all people we attempt to test for tuberculosis, is an important metric not adequately explored. Diagnostic yield is particularly relevant for subpopulations unable to produce sputum such as young children, people living with HIV, and people with subclinical tuberculosis. As more accessible non-sputum specimens (eg, urine, oral swabs, saliva, capillary blood, and breath) are being explored for point-of-care tuberculosis testing, the concept of yield will be of growing importance. Using the example of urine lipoarabinomannan testing, we illustrate how even tests with limited sensitivity can diagnose more people with tuberculosis if they enable increased diagnostic yield. Using tongue swab-based molecular tuberculosis testing as another example, we provide definitions and guidance for the design and conduct of pragmatic studies that assess diagnostic yield. Lastly, we show how diagnostic yield and other important test characteristics, such as cost and implementation feasibility, are essential for increased effective population coverage, which is required for optimal clinical care and transmission impact. We are calling for diagnostic yield to be incorporated into tuberculosis test evaluation processes, including the WHO Grading of Recommendations, Assessment, Development, and Evaluations process, providing a crucial real-life implementation metric that complements traditional accuracy measures.

Men's Satisfaction with General Health Services is Associated with Future Use of HIV Testing in Malawi: A Community-Representative Survey.

Across sub-Saharan Africa, men are less likely to know their HIV status than women, leading to later treatment initiation. Little is known about how experiences with general health services affect men's use of HIV testing. We used data from a 2019 community-representative survey of men in Malawi to understand frequency and cause of men's negative health service experiences (defined as men reporting they "would not recommend" a facility) and their association with future HIV testing. We conducted univariable and multivariable logistic regressions to determine which aspects of health facility visits were associated with would-not-recommend experiences and to determine if would-not-recommend experiences 12-24 months prior to the survey were associated with HIV testing in the 12 months prior to the survey. Among 1,098 men eligible for HIV testing in the 12 months prior to the survey, median age was 34 years; 9% of men reported at least one would-not-recommend experience, which did not differ by sociodemographics, gender norm beliefs, or HIV stigma beliefs. The factors most strongly associated with would-not-recommend experiences were cost (aOR 5.8, 95%CI 2.9-11.4), cleanliness (aOR 4.2, 95%CI 1.8-9.9), medicine availability (aOR 3.3, 95%CI 1.7-6.4), and wait times (aOR 2.7, 95%CI 1.5-5.0). Reporting a would-not-recommend experience 12-24 months ago was associated with a 59% decrease in likelihood of testing for HIV in the last 12 months (aOR 0.41; 95% CI:0.17-0.96). Dissatisfaction with general health services was strongly associated with reduced HIV testing. Coverage of high-priority screening services like HIV testing may benefit from improving overall health system quality.

Implementation research: a protocol for two three-arm pragmatic randomised controlled trials on continuous glucose monitoring devices in people with type 1 diabetes in South Africa and Kenya.

BACKGROUND: Self-monitoring of glucose is an essential component of type 1 diabetes (T1D) management. In recent years, continuous glucose monitoring (CGM) has provided an alternative to daily fingerstick testing for the optimisation of insulin dosing and general glucose management in people with T1D. While studies have been conducted to evaluate the impact of CGM on clinical outcomes in the US, Europe and Australia, there are limited data available for low- and middle-income countries (LMICs) and further empirical evidence is needed to inform policy decision around their use in these countries. METHODS: This trial was designed as a pragmatic, parallel-group, open-label, multicentre, three-arm, randomised (1:1:1) controlled trial of continuous or periodic CGM device use versus standard of care in people with T1D in South Africa and Kenya. The primary objective of this trial will be to assess the impact of continuous or periodic CGM device use on glycaemic control as measured by change from baseline glycosylated haemoglobin (HbA1c). Additional assessments will include clinical outcomes (glucose variation, time in/below/above range), safety (adverse events, hospitalisations), quality of life (EQ-5D, T1D distress score, Glucose Monitoring Satisfaction Survey for T1D), and health economic measures (incremental cost-effectiveness ratios, quality adjusted life years). DISCUSSION: This trial aims to address the substantial evidence gap on the impact of CGM device use on clinical outcomes in LMICs, specifically South Africa and Kenya. The trial results will provide evidence to inform policy and treatment decisions in these countries. TRIAL REGISTRATION: NCT05944731 (Kenya), July 6, 2023; NCT05944718 (South Africa), July 13, 2023.

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.

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-effectiveness of intervention combinations towards the elimination of vertical transmission of HIV in limited-resource settings: a mathematical modelling study.

BACKGROUND: Since 2000, there has been a substantial global reduction in the vertical transmission of HIV. Despite effective interventions, gaps still remain in progress towards elimination in many low-income and middle-income countries. We developed a mathematical model to determine the most cost-effective combinations of interventions to prevent vertical transmission. METHODS: We developed a 12-month Markov model to follow a cohort of women of childbearing age (aged 15-49 years) in Zambia (n=1 107 255) who were either pregnant, in delivery, or breastfeeding; the population included in the model reflects the estimated number of pregnant women in Zambia from the 2018 Zambia Demographic and Health Survey. The model incorporated nine interventions: infant prophylaxis; three different HIV retesting schedule options; oral pre-exposure prophylaxis; maternal peer-support groups; regimen shift; tracing of loss to follow-up; and point-of-care viral load testing. We analysed incident HIV infections among mothers and infants, intervention costs, and evaluated 190 scenarios of different combinations of inventions to calculate the incremental cost-effectiveness ratios (ICERs) over 1 year. FINDINGS: Three interventions with the greatest reduction in vertical transmission, individually, were support groups for 80% of those in need (35% reduction in infant infections), HIV retesting schedules (6·5% reduction), and infant prophylaxis (4·5% reduction). Of all 190 scenarios evaluated, eight were on the cost-effectiveness frontier (ie, were considered to be cost-effective); all eight included increasing infant prophylaxis, regimen shift, and use of support groups. Excluding the highest-cost scenarios, for a 1-22% increase in total budget, 23-43% of infant infections could be prevented, producing ICERs between US$244 and $16 242. INTERPRETATION: Using the interventions modelled, it is possible to reduce vertical transmission and to cost-effectively prevent up to 1734 infant HIV infections (43% reduction) in Zambia over a period of 1 year. To optimise their effect, these interventions must be scaled with fidelity. Future work is needed to incorporate evidence on additional innovative interventions and HIV risk factors, and to apply the model to other country contexts to support targeted implementation and resource use. FUNDING: The ELMA Foundation.

Determinants of epidemic size and the impacts of lulls in seasonal influenza virus circulation.

During the COVID-19 pandemic, levels of seasonal influenza virus circulation were unprecedentedly low, leading to concerns that a lack of exposure to influenza viruses, combined with waning antibody titres, could result in larger and/or more severe post-pandemic seasonal influenza epidemics. However, in most countries the first post-pandemic influenza season was not unusually large and/or severe. Here, based on an analysis of historical influenza virus epidemic patterns from 2002 to 2019, we show that historic lulls in influenza virus circulation had relatively minor impacts on subsequent epidemic size and that epidemic size was more substantially impacted by season-specific effects unrelated to the magnitude of circulation in prior seasons. From measurements of antibody levels from serum samples collected each year from 2017 to 2021, we show that the rate of waning of antibody titres against influenza virus during the pandemic was smaller than assumed in predictive models. Taken together, these results partially explain why the re-emergence of seasonal influenza virus epidemics was less dramatic than anticipated and suggest that influenza virus epidemic dynamics are not currently amenable to multi-season prediction.