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Background Rapid diagnostic tests (RDTs) for coronavirus disease (COVID) are used in low- and middle-income countries (LMICs) to inform treatment decisions. However, to date, it is unclear when this use is cost-effective. Existing analyses are limited to a narrow set of countries and uses. The aim of this study is to assess the cost-effectiveness of COVID RDTs to inform the treatment of patients with severe illness in LMICs, considering real world practice. Methods and findings We assessed the cost-effectiveness of COVID testing across LMICs using a decision tree model, differentiating results by country income level, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) prevalence, and testing scenario (none, RDTs, polymerase chain reaction tests-PCRs and combinations). LMIC experts defined realistic care pathways and treatment options. Using a healthcare provider perspective and net monetary benefit approach, we assessed both intended (COVID symptom alleviation) and unintended (treatment side effects) health and economic impacts for each testing scenario. We included the side effects of corticosteroids, which are often the only available treatment for COVID. Because side effects depend both on the treatment and the patient's underlying illness (COVID or COVID-like illnesses, such as influenza), we considered the prevalence of COVID-like illnesses in our analyses. We found that SARS-CoV-2 testing of patients with severe COVID-like illness can be cost-effective in all LMICs, though only in some circumstances. High influenza prevalence among suspected COVID cases improves cost-effectiveness, since incorrectly provided corticosteroids may worsen influenza outcomes. In low- and some lower-middle-income countries, only patients with a high index of suspicion for COVID should be tested with RDTs, while other patients should be presumed to not have COVID. In some lower-middle-income and upper-middle-income countries, suspected severe COVID cases should almost always be tested. Further, in these settings, negative test results in patients with a high initial index of suspicion should be confirmed through PCR and, during influenza outbreaks, positive results in patients with a low initial index of suspicion should also be confirmed with a PCR. The use of interleukin-6 receptor blockers, when supported by testing, may also be cost-effective in higher-income LMICs. The cost at which they would be cost-effective in low-income countries ($162 to $406 per treatment course) is below current prices. The primary limitation of our analysis is substantial uncertainty around some of the parameters in our model due to limited data, most notably on current COVID mortality with standard of care, and insufficient evidence on the impact of corticosteroids on patients with severe influenza. Conclusions COVID testing can be cost-effective to inform treatment of LMIC patients with severe COVID-like disease. The optimal algorithm is driven by country income level and health budgets, the level of suspicion that the patient may have COVID, and influenza prevalence. Further research to better characterize the unintended effects of corticosteroids, particularly on influenza cases, could improve decision making around the treatment of those with COVID-like symptoms in LMICs., Author(s): Gabrielle Bonnet 1,*, John Bimba 2,3, Chancy Chavula 4, Harunavamwe N. Chifamba 5, Titus H. Divala 6, Andres G. Lescano 7, Mohammed Majam 8, Danjuma Mbo 9, Auliya A. [...]

BACKGROUND: One critical element to optimize funding decisions involves the cost and efficiency implications of implementing alternative program components and configurations. Program planners, policy makers and funders alike are in need of relevant, strategic data and analyses to help them plan and implement effective and efficient programs. Contrary to widely accepted conceptions in both policy and academic arenas, average costs per service (so-called unit costs) vary considerably across implementation settings and facilities. The objective of this work is twofold: 1) to estimate the variation of VMMC unit costs across service delivery platforms (SDP) in Sub-Saharan countries, and 2) to develop and validate a strategy to extrapolate unit costs to settings for which no data exists. METHODS: We identified high-quality VMMC cost studies through a literature review. Authors were contacted to request the facility-level datasets (primary data) underlying their results. We standardized the disparate datasets into an aggregated database which included 228 facilities in eight countries. We estimated multivariate models to assess the correlation between VMMC unit costs and scale, while simultaneously accounting for the influence of the SDP (which we defined as all possible combinations of type of facility, ownership, urbanicity, and country), on the unit cost variation. We defined SDP as any combination of such four characteristics. Finally, we extrapolated VMMC unit costs for all SDPs in 13 countries, including those not contained in our dataset. RESULTS: The average unit cost was 73 USD (IQR: 28.3, 100.7). South Africa showed the highest within-country cost variation, as well as the highest mean unit cost (135 USD). Uganda and Namibia had minimal within-country cost variation, and Uganda had the lowest mean VMMC unit cost (22 USD). Our results showed evidence consistent with economies of scale. Private ownership and Hospitals were significant determinants of higher unit costs. By identifying key cost drivers, including country- and facility-level characteristics, as well as the effects of scale we developed econometric models to estimate unit cost curves for VMMC services in a variety of clinical and geographical settings. CONCLUSION: While our study did not produce new empirical data, our results did increase by a tenfold the availability of unit costs estimates for 128 SDPs in 14 priority countries for VMMC. It is to our knowledge, the most comprehensive analysis of VMMC unit costs to date. Furthermore, we provide a proof of concept of the ability to generate predictive cost estimates for settings where empirical data does not exist.

Providing social support to tuberculosis (TB) patients is a recommended strategy as households having TB patients find themselves in a spiral of poverty because of high cost, huge income loss and several other economic consequences associated with TB treatment. However, there are few examples of social support globally. The Indian government introduced the 'Nikshay Poshan Yojana' scheme in 2018 to provide nutritional support for all registered TB patients. A financial incentive of 500 Indian Rupee (6 United States Dollars) per month was proposed to be transferred directly to the registered beneficiaries' validated bank accounts. We examined the reach, timing, amount of benefit receipt and the extent to which the benefit alleviated catastrophic costs (used as a proxy to measure the impact on permanent economic welfare as catastrophic cost is the level of cost that is likely to result in a permanent negative economic impact on households) by interviewing 1482 adult drug-susceptible TB patients from 16 districts of four states during 2019 to 2023, using the methods recommended by the World Health Organization for estimating household costs of TB nationally. We also estimated the potential amount of social support required to achieve a zero catastrophic cost target. At the end of treatment, 31–54% of study participants received the benefit. In all, 34–60% of TB patients experienced catastrophic costs using different estimation methods and the benefit helped 2% of study participants to remain below the catastrophic cost threshold. A uniform benefit amount of Indian Rupee 10 000 (127 United States Dollars) for 6 months of treatment could reduce the incidence of catastrophic costs by 43%. To improve the economic welfare of TB patients, levels of benefit need to be substantially increased, which will have considerable budgetary impact on the TB programme. Hence, a targeted rather than universal approach may be considered. To maximize impact, at least half of the revised amount should be given immediately after treatment registration. [ABSTRACT FROM AUTHOR]

Focusing only on cases and deaths hides the pandemic's lasting health burden on people, societies and economies. Focusing only on cases and deaths hides the pandemic's lasting health burden on people, societies and economies., Author(s): Andrew Briggs, Anna Vassall Author Affiliations: Count the cost of disability caused by COVID-19 A person receiving dialysis. COVID-19 can leave people with lasting damage to their kidneys, among [...]

BackgroundThe Avahan programme has provided HIV prevention activities, including condom promotion, to female sex workers (FSWs) in southern India since 2004. Evidence suggests Avahan averted 202,000 HIV infections over 4 years. For replicating this intervention elsewhere, it is essential to understand how the intervention's impact could have been optimised for different budget levels.MethodsBehavioural data were used to determine how condom use varied for FSWs with different levels of intervention intensity. Cost data from 64 Avahan districts quantified how district-level costs related to intervention scale and intensity. A deterministic model for HIV transmission amongst FSWs and clients projected the impact and cost of intervention strategies for different scale and intensity, and identified the optimal strategies that maximise impact for different budget levels.ResultsAs budget levels increase, the optimal intervention strategy is to first increase intervention intensity which achieves little impact, then scale-up coverage to high levels for large increases in impact, and lastly increase intensity further for small additional gains. The cost-effectiveness of these optimal strategies generally improves with increasing resources, while straying from these strategies can triple costs for the same impact. Projections suggest Avahan was close to being optimal, and moderate budget reductions (≥ 20%) would have reduced impact considerably (>40%).DiscussionOur analysis suggests that tailoring the design of HIV prevention programmes for FSWs can improve impact, and that a certain level of resources are required to achieve demonstrable impact. These insights are critical for optimising the use of limited resources for preventing HIV.