Using mHealth Technologies for Case Finding in Tuberculosis and Other Infectious Diseases in Africa: Systematic Review.

Background: Mobile health (mHealth) technologies are increasingly used in contact tracing and case finding, enhancing and replacing traditional methods for managing infectious diseases such as Ebola, tuberculosis, COVID-19, and HIV. However, the variations in their development approaches, implementation scopes, and effectiveness introduce uncertainty regarding their potential to improve public health outcomes.

Objective: We conducted this systematic review to explore how mHealth technologies are developed, implemented, and evaluated.

Modeling the impact of universal tuberculosis molecular testing and timing of tuberculosis preventive treatment during antiretroviral therapy initiation in South Africa.

Objectives: Targeted universal tuberculosis (TB) testing can improve TB detection among people with HIV. This approach is being scaled up in South Africa through Xpert MTB/RIF Ultra testing for individuals starting antiretroviral therapy and annually thereafter. Clarity is needed on how Universal Xpert testing may affect TB preventive treatment (TPT) provision, and on whether TPT should be delayed until TB is ruled out.

Exploring equity in health and poverty impacts of control measures for SARS-CoV-2 in six countries.

Background: Policy makers need to be rapidly informed about the potential equity consequences of different COVID-19 strategies, alongside their broader health and economic impacts. While there are complex models to inform both potential health and macro-economic impact, there are few tools available to rapidly assess potential equity impacts of interventions.

Methods: We created an economic model to simulate the impact of lockdown measures in Pakistan, Georgia, Chile, UK, the Philippines and South Africa.

Estimating Cost Functions for Resource Allocation Using Transmission Models: A Case Study of Tuberculosis Case Finding in South Africa.

Objective: Cost functions linked to transmission dynamic models are commonly used to estimate the resources required for infectious disease policies. We present a conceptual and empirical approach for estimating these functions, allowing for nonconstant marginal costs. We aim to expand on the current approach which commonly assumes linearity of cost over scale.

Informing Balanced Investment in Services and Health Systems: A Case Study of Priority Setting for Tuberculosis Interventions in South Africa.

Objectives: Health systems face nonfinancial constraints that can influence the opportunity cost of interventions. Empirical methods to explore their impact, however, are underdeveloped. We develop a conceptual framework for defining health system constraints and empirical estimation methods that rely on routine data.

Examining Approaches to Estimate the Prevalence of Catastrophic Costs Due to Tuberculosis from Small-Scale Studies in South Africa.

Background And Objective: In context of the End TB goal of zero tuberculosis (TB)-affected households encountering catastrophic costs due to TB by 2020, the estimation of national prevalence of catastrophic costs due to TB is a priority to inform programme design. We explore approaches to estimate the national prevalence of catastrophic costs due to TB from existing datasets as an alternative to nationally representative surveys.

Methods: We obtained, standardized and merged three patient-level datasets from existing studies on patient-incurred costs due to TB in South Africa.

Estimating the Impact of Tuberculosis Case Detection in Constrained Health Systems: An Example of Case-Finding in South Africa.

Mathematical models are increasingly being used to compare strategies for tuberculosis (TB) control and inform policy decisions. Models often do not consider financial and other constraints on implementation and may overestimate the impact that can be achieved. We developed a pragmatic approach for incorporating resource constraints into mathematical models of TB.

Application of provincial data in mathematical modelling to inform sub-national tuberculosis program decision-making in South Africa.

South Africa has the highest tuberculosis (TB) disease incidence rate in the world, and TB is the leading infectious cause of death. Decisions on, and funding for, TB prevention and care policies are decentralised to the provincial governments and therefore, tools to inform policy need to operate at this level. We describe the use of a mathematical model planning tool at provincial level in a high HIV and TB burden country, to estimate the impact on TB burden of achieving the 90-(90)-90 targets of the Stop TB Partnership Global Plan to End TB.

Empirical estimation of resource constraints for use in model-based economic evaluation: an example of TB services in South Africa.

Background: Evidence on the relative costs and effects of interventions that do not consider 'real-world' constraints on implementation may be misleading. However, in many low- and middle-income countries, time and data scarcity mean that incorporating health system constraints in priority setting can be challenging.

Methods: We developed a 'proof of concept' method to empirically estimate health system constraints for inclusion in model-based economic evaluations, using intensified case-finding strategies (ICF) for tuberculosis (TB) in South Africa as an example.

The patient costs of care for those with TB and HIV: a cross-sectional study from South Africa.

Background: This study describes the post-diagnosis care-seeking costs incurred by people living with TB and/or HIV and their households, in order to identify the potential benefits of integrated care.

Methods: We conducted a cross-sectional study with 454 participants with TB or HIV or both in public primary health care clinics in Ekurhuleni North Sub-District, South Africa. We collected information on visits to health facilities, direct and indirect costs for participants and for their guardians and caregivers.

Methodological Issues to Consider When Collecting Data to Estimate Poverty Impact in Economic Evaluations in Low-income and Middle-income Countries.

Out-of-pocket spending is increasingly recognized as an important barrier to accessing health care, particularly in low-income and middle-income countries (LMICs) where a large portion of health expenditure comes from out-of-pocket payments. Emerging universal healthcare policies prioritize reduction of poverty impact such as catastrophic and impoverishing healthcare expenditure. Poverty impact is therefore increasingly evaluated alongside and within economic evaluations to estimate the impact of specific health interventions on poverty.