Cost-effectiveness analysis of point-of-care rapid testing versus laboratory-based testing for antenatal screening of syphilis in Brazil

Objectives Severe consequences of mother-to-child transmission of syphilis and high increasing incidence of congenital syphilis remains an important public health problem in Brazil. Our objective was to assess the cost-effectiveness of a rapid point-of-care test (RT) and treatment of positive mothers immediately compared with a laboratory-based standard test (ST) with treatment at next follow-up visit. Methods A decision analytic model was developed to estimate the incremental cost-effectiveness ratio (ICER) between antenatal syphilis screening strategies. The model was built with lifetime horizon from Brazilian health system perspective using 3% and 5% discount rates. A hypothetical cohort of pregnant women at reproductive age were used in the model. Health outcomes: low birth weight, stillbirths, neonatal deaths and congenital syphilis were estimated in disability-adjusted life-years (DALYs) lost. Microcosting study and secondary data provided parameters of direct medical costs. Probabilistic sensitivity analysis was undertaken. Results For base case, the mean cost per pregnant woman screened was $2.63 (RT) and$2.48 (ST), respectively. Maternal syphilis was associated with a loss of 0.0043 DALYs (RT) and 0.0048 DALYs (ST) per mother screened. Expected value of incremental cost per DALY averted was $298.08. After 10 000 probabilistic sensitivity analysis model runs, incremental cost and health benefits were$0.15 (95% credible interval –1.56 to 1.92) and 0.00042 DALYs (95% credible interval –0.0036 to 0.0044), respectively, with a mean ICER of $357.44 per DALY. Screening with RT has a 58$3,200 per DALY. Conclusions In Brazil, antenatal screening with syphilis RT and immediate treatment is likely to be cost-effective compared with standard screening and must be prioritized in local settings

Modeling the epidemiological impact of the UNAIDS 2025 targets to end AIDS as a public health threat by 2030

Background: UNAIDS has established new program targets for 2025 to achieve the goal of eliminating AIDS as a public health threat by 2030. This study reports on efforts to use mathematical models to estimate the impact of achieving those targets. // Methods and findings: We simulated the impact of achieving the targets at country level using the Goals model, a mathematical simulation model of HIV epidemic dynamics that includes the impact of prevention and treatment interventions. For 77 high-burden countries, we fit the model to surveillance and survey data for 1970 to 2020 and then projected the impact of achieving the targets for the period 2019 to 2030. Results from these 77 countries were extrapolated to produce estimates for 96 others. Goals model results were checked by comparing against projections done with the Optima HIV model and the AIDS Epidemic Model (AEM) for selected countries. We included estimates of the impact of societal enablers (access to justice and law reform, stigma and discrimination elimination, and gender equality) and the impact of Coronavirus Disease 2019 (COVID-19). Results show that achieving the 2025 targets would reduce new annual infections by 83% (71% to 86% across regions) and AIDS-related deaths by 78% (67% to 81% across regions) by 2025 compared to 2010. Lack of progress on societal enablers could endanger these achievements and result in as many as 2.6 million (44%) cumulative additional new HIV infections and 440,000 (54%) more AIDS-related deaths between 2020 and 2030 compared to full achievement of all targets. COVID-19–related disruptions could increase new HIV infections and AIDS-related deaths by 10% in the next 2 years, but targets could still be achieved by 2025. Study limitations include the reliance on self-reports for most data on behaviors, the use of intervention effect sizes from published studies that may overstate intervention impacts outside of controlled study settings, and the use of proxy countries to estimate the impact in countries with fewer than 4,000 annual HIV infections. // Conclusions: The new targets for 2025 build on the progress made since 2010 and represent ambitious short-term goals. Achieving these targets would bring us close to the goals of reducing new HIV infections and AIDS-related deaths by 90% between 2010 and 2030. By 2025, global new infections and AIDS deaths would drop to 4.4 and 3.9 per 100,000 population, and the number of people living with HIV (PLHIV) would be declining. There would be 32 million people on treatment, and they would need continuing support for their lifetime. Incidence for the total global population would be below 0.15% everywhere. The number of PLHIV would start declining by 2023

A Counterexample Regarding Labelled Well-Quasi-Ordering

Korpelainen, Lozin, and Razgon conjectured that a hereditary property of graphs which is well-quasi-ordered by the induced subgraph order and defined by only finitely many minimal forbidden induced subgraphs is labelled well-quasi-ordered, a notion stronger than that of n-well-quasi-order introduced by Pouzet in the 1970s. We present a counterexample to this conjecture. In fact, we exhibit a hereditary property of graphs which is well-quasi-ordered by the induced subgraph order and defined by finitely many minimal forbidden induced subgraphs yet is not 2-well-quasi-ordered. This counterexample is based on the widdershins spiral, which has received some study in the area of permutation patterns

Point-of-Care Tests to Strengthen Health Systems and Save Newborn Lives: The Case of Syphilis

Rosanna Peeling and colleagues describe their experience of introducing point-of-care testing to screen for syphilis in pregnant women living in low- and middle-income countries

To err is human, to correct is public health: a systematic review examining poor quality testing and misdiagnosis of HIV status.

INTRODUCTION: In accordance with global testing and treatment targets, many countries are seeking ways to reach the "90-90-90" goals, starting with diagnosing 90% of all people with HIV. Quality HIV testing services are needed to enable people with HIV to be diagnosed and linked to treatment as early as possible. It is essential that opportunities to reach people with undiagnosed HIV are not missed, diagnoses are correct and HIV-negative individuals are not inadvertently initiated on life-long treatment. We conducted this systematic review to assess the magnitude of misdiagnosis and to describe poor HIV testing practices using rapid diagnostic tests. METHODS: We systematically searched peer-reviewed articles, abstracts and grey literature published from 1 January 1990 to 19 April 2017. Studies were included if they used at least two rapid diagnostic tests and reported on HIV misdiagnosis, factors related to potential misdiagnosis or described quality issues and errors related to HIV testing. RESULTS: Sixty-four studies were included in this review. A small proportion of false positive (median 3.1%, interquartile range (IQR): 0.4-5.2%) and false negative (median: 0.4%, IQR: 0-3.9%) diagnoses were identified. Suboptimal testing strategies were the most common factor in studies reporting misdiagnoses, particularly false positive diagnoses due to using a "tiebreaker" test to resolve discrepant test results. A substantial proportion of false negative diagnoses were related to retesting among people on antiretroviral therapy. Conclusions HIV testing errors and poor practices, particularly those resulting in false positive or false negative diagnoses, do occur but are preventable. Efforts to accelerate HIV diagnosis and linkage to treatment should be complemented by efforts to improve the quality of HIV testing services and strengthen the quality management systems, particularly the use of validated testing algorithms and strategies, retesting people diagnosed with HIV before initiating treatment and providing clear messages to people with HIV on treatment on the risk of a "false negative" test result

Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods

Gibbons CL, Mangen M-JJ, Plaß D, et al. Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods. BMC Public Health. 2014;14(1): 147.Background: Efficient and reliable surveillance and notification systems are vital for monitoring public health and disease outbreaks. However, most surveillance and notification systems are affected by a degree of underestimation (UE) and therefore uncertainty surrounds the 'true' incidence of disease affecting morbidity and mortality rates. Surveillance systems fail to capture cases at two distinct levels of the surveillance pyramid: from the community since not all cases seek healthcare (under-ascertainment), and at the healthcare-level, representing a failure to adequately report symptomatic cases that have sought medical advice (underreporting). There are several methods to estimate the extent of under-ascertainment and underreporting. Methods: Within the context of the ECDC-funded Burden of Communicable Diseases in Europe (BCoDE)-project, an extensive literature review was conducted to identify studies that estimate ascertainment or reporting rates for salmonellosis and campylobacteriosis in European Union Member States (MS) plus European Free Trade Area (EFTA) countries Iceland, Norway and Switzerland and four other OECD countries (USA, Canada, Australia and Japan). Multiplication factors (MFs), a measure of the magnitude of underestimation, were taken directly from the literature or derived (where the proportion of underestimated, under-ascertained, or underreported cases was known) and compared for the two pathogens. Results: MFs varied between and within diseases and countries, representing a need to carefully select the most appropriate MFs and methods for calculating them. The most appropriate MFs are often disease-,country-, age-, and sex-specific. Conclusions: When routine data are used to make decisions on resource allocation or to estimate epidemiological parameters in populations, it becomes important to understand when, where and to what extent these data represent the true picture of disease, and in some instances (such as priority setting) it is necessary to adjust for underestimation. MFs can be used to adjust notification and surveillance data to provide more realistic estimates of incidence