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BackgroundLimited evidence exists on the value for money of mHealth information programs in low resource settings. ObjectiveThis study sought to model the incremental cost-effectiveness of gradually scaling up text messaging services to pregnant women throughout Gauteng province, South Africa from 2012 to 2017. MethodsData collection occurred as part of a retrospective study in 6 health centers in Gauteng province. Stage-based short message service (SMS) text messages on maternal health were sent to pregnant women twice per week during pregnancy and continued until the infant’s first birthday. Program costs, incremental costs to users, and the health system costs for these women were measured along with changes in the utilization of antenatal care visits and childhood immunizations and compared with those from a control group of pregnant women who received no SMS text messages. Incremental changes in utilization were entered into the Lives Saved Tool and used to forecast lives saved and disability adjusted life years (DALYs) averted by scaling up program activities over 5 years to reach 60% of pregnant women across Gauteng province. Uncertainty was characterized using one-way and probabilistic uncertainty analyses. ResultsFive-year program costs were estimated to be US $1.2 million, 17% of which were incurred by costs on program development and 31% on SMS text message delivery costs. Costs to users were US $1.66 to attend clinic-based services, nearly 90% of which was attributed to wages lost. Costs to the health system included provider time costs to register users (US $0.08) and to provide antenatal care (US $4.36) and postnatal care (US $3.08) services. Incremental costs per DALY averted from a societal perspective ranged from US $1985 in the first year of implementation to US $200 in the 5th year. At a willingness-to-pay threshold of US $2000, the project had a 40% probability of being cost-effective in year 1 versus 100% in all years thereafter. ConclusionsStudy findings suggest that delivering SMS text messages on maternal health information to pregnant and postpartum women may be a cost-effective strategy for bolstering antenatal care and childhood immunizations, even at very small margins of coverage increases. Primary data obtained prospectively as part of more rigorous study designs are needed to validate modeled results.

: Introduction: In 2017, the Aurum Institute, with support from Unitaid, launched an initiative to expand short‐course therapy for the prevention of tuberculosis (TB) in 12 high‐burden countries. This study aimed to investigate the importance of “catalytic” effects beyond the original project timeframe when estimating cost‐effectiveness of such large investments. Methods: We estimated the cost‐effectiveness of the IMPAACT4TB (I4TB) initiative from a health system perspective, using a 10‐year time horizon. We first conservatively estimated costs using a “top‐down” approach considering only the direct health benefits of providing TB preventive therapy to people initiating antiretroviral therapy (ART) through I4TB activities. We then re‐estimated the incremental cost‐effectiveness of I4TB incorporating the costs and health benefits of potential catalytic effects beyond the program itself. Results: We estimated that TB preventive therapy through the I4TB initiative alone would prevent 14 201 cases of active TB and 1562 TB deaths over 10 years with an up‐front investment of $52.5 million; the estimated incremental cost‐effectiveness was $1580 per disability‐adjusted life year (DALY) averted. If this initiative could achieve its desired catalytic effects, an additional 375 648 cases and 41 321 deaths could be averted, at an incremental cost of $546 million and cost‐effectiveness of $713 per DALY averted. Conclusions: Our findings provide donors with reasonable evidence of value for money to support investment in short‐course TB preventive therapy for people initiating ART in high‐burden settings. Our study also illustrates the importance of considering long‐term secondary (“catalytic”) effects when evaluating the cost‐effectiveness of large‐scale initiatives designed to change a global policy landscape., INTRODUCTION Since 1993, the World Health Organization (WHO) has recommended preventive therapy for tuberculosis (TB) for people living with HIV (PLHIV) in whom active TB has been excluded (without testing [...]

: Introduction: Preventive therapy is essential for reducing tuberculosis (TB) burden among people living with HIV (PLWH) in high‐burden settings. Short‐course preventive therapy regimens, such as three‐month weekly rifapentine and isoniazid (3HP) and one‐month daily rifapentine and isoniazid (1HP), may help facilitate uptake of preventive therapy for latently infected patients, but the comparative cost‐effectiveness of these regimens under different conditions is uncertain. Methods: We used a Markov state‐transition model to estimate the incremental costs and effectiveness of 1HP versus 3HP in a simulated cohort of patients attending an HIV clinic in Uganda, as an example of a low‐income, high‐burden setting in which TB preventive therapy might be prescribed to PLWH. Our primary outcome was the incremental cost‐effectiveness ratio, expressed as 2019 US dollars per disability‐adjusted life year (DALY) averted. We estimated cost‐effectiveness under different conditions of treatment completion and efficacy of 1HP versus 3HP, latent TB prevalence and rifapentine price. Results: Assuming equivalent clinical outcomes using 1HP and 3HP and a rifapentine price of $0.21 per 150 mg, 1HP would cost an additional $4.66 per patient treated. Assuming equivalent efficacy but 20% higher completion with 1HP versus 3HP, 1HP would cost $1,221 per DALY averted relative to 3HP. This could be reduced to $18 per DALY averted if 1HP had 5% greater efficacy than 3HP and the price of rifapentine were 50% lower. At a rifapentine price of $0.06 per 150 mg, 1HP would become cost‐neutral relative to 3HP. Conclusions: 1HP has the potential to be cost‐effective under many realistic circumstances. Cost‐effectiveness depends on rifapentine price, relative completion and efficacy, prevalence of latent TB and local willingness‐to‐pay., Introduction Tuberculosis (TB) is the leading cause of death among people living with HIV (PLWH), and the leading single‐agent infectious cause of death worldwide [1,2]. TB preventive therapy for latently [...]

Background Modeling studies have concluded that 60–80% of tuberculosis (TB) infections result from reinfection of previously infected persons. The annual rate of infection (ARI), a standard measure of the risk of TB infection in a community, may not accurately reflect the true risk of infection among previously infected persons. We constructed a model of infection and reinfection with Mycobacterium tuberculosis to explore the predictive accuracy of ARI and its effect on disease incidence. Methods We created a deterministic simulation of the progression from TB infection to disease and simulated the prevalence of TB infection at the beginning and end of a theoretical year of infection. We considered 10 disease prevalence scenarios ranging from 100/100 000 to 1000/100 000 in simulations where TB exposure probability was homogeneous across the whole simulated population or heterogeneously stratified into high-risk and low-risk groups. ARI values, rates of progression from infection to disease, and the effect of multiple reinfections were obtained from published studies. Results With homogeneous exposure risk, observed ARI values produced expected numbers of infections. However, when heterogeneous risk was introduced, observed ARI was seen to underestimate true ARI by 25–58%. Of the cases of TB disease that occurred, 36% were among previously infected persons when prevalence was 100/100 000, increasing to 79% of cases when prevalence was 1000/100 000. Conclusions Measured ARI underestimates true ARI as a result of heterogeneous population mixing. The true force of infection in a community may be greater than previously appreciated. Hyperendemic communities likely contribute disproportionally to the global TB disease burden. [ABSTRACT FROM AUTHOR]

Background Targeted testing and treatment (TTT) for latent tuberculosis (TB) infection (LTBI) is a recommended strategy to accelerate TB reductions and further TB elimination in the United States. Evidence on cost-effectiveness of TTT for key populations can help advance this goal. Methods We used a model of TB transmission to estimate the numbers of individuals who could be tested by interferon-γ release assay and treated for LTBI with 3 months of self-administered rifapentine and isoniazid (3HP) under various TTT scenarios. Specifically, we considered rapidly scaling up TTT among people who are non–US-born, diabetic, living with human immunodeficiency virus (HIV), homeless or incarcerated in California, Florida, New York, and Texas—states where more than half of US TB cases occur. We projected costs (from the healthcare system perspective, in 2018 dollars), 30-year reductions in TB incidence, and incremental cost-effectiveness (cost per quality-adjusted life-year [QALY] gained) for TTT in each modeled population. Results The projected cost-effectiveness of TTT differed substantially by state and population, while the health impact (number of TB cases averted) was consistently greatest among non–US-born individuals. TTT was most cost-effective among persons with HIV (from $2828/QALY gained in Florida to $11 265/QALY gained in New York) and least cost-effective among people with diabetes (from $223 041/QALY gained in California to $817 753/QALY in New York). Conclusions The modeled cost-effectiveness of TTT for LTBI varies across states but was consistently greatest among people with HIV; moderate among people who are non–US-born, incarcerated, or homeless; and least cost-effective among people with diabetes. [ABSTRACT FROM AUTHOR]

While the importance of mHealth scale-up has been broadly emphasized in the mHealth community, it is necessary to guide scale up efforts and investment in ways to help achieve the mortality reduction targets set by global calls to action such as the Millennium Development Goals, not merely to expand programs. We used the Lives Saved Tool (LiST)–an evidence-based modeling software–to identify priority areas for maternal and neonatal health services, by formulating six individual and combined interventions scenarios for two countries, Bangladesh and Uganda. Our findings show that skilled birth attendance and increased facility delivery as targets for mHealth strategies are likely to provide the biggest mortality impact relative to other intervention scenarios. Although further validation of this model is desirable, tools such as LiST can help us leverage the benefit of mHealth by articulating the most appropriate delivery points in the continuum of care to save lives. [ABSTRACT FROM AUTHOR]