Impact of interventions for tuberculosis prevention and care in South Africa – a systematic review of mathematical modelling studies
DOI:
https://doi.org/10.7196/SAMJ.2023.v113i3.16812Keywords:
SARS-CoV, TBAbstract
Background. Substantial additional efforts are needed to prevent, find and successfully treat tuberculosis (TB) in South Africa (SA). In the
past decade, an increasing body of mathematical modelling research has investigated the population-level impact of TB prevention and care
interventions. To date, this evidence has not been assessed in the SA context.
Objective. To systematically review mathematical modelling studies that estimated the impact of interventions towards the World Health
Organization’s End TB Strategy targets for TB incidence, TB deaths and catastrophic costs due to TB in SA.
Methods. We searched the PubMed, Web of Science and Scopus databases for studies that used transmission-dynamic models of TB in SA
and reported on at least one of the End TB Strategy targets at population level. We described study populations, type of interventions and
their target groups, and estimates of impact and other key findings. For studies of country-level interventions, we estimated average annual
percentage declines (AAPDs) in TB incidence and mortality attributable to the intervention.
Results. We identified 29 studies that met our inclusion criteria, of which 7 modelled TB preventive interventions (vaccination,
antiretroviral treatment (ART) for HIV, TB preventive treatment (TPT)), 12 considered interventions along the care cascade for TB
(screening/case finding, reducing initial loss to follow-up, diagnostic and treatment interventions), and 10 modelled combinations
of preventive and care-cascade interventions. Only one study focused on reducing catastrophic costs due to TB. The highest impact
of a single intervention was estimated in studies of TB vaccination, TPT among people living with HIV, and scale-up of ART. For
preventive interventions, AAPDs for TB incidence varied between 0.06% and 7.07%, and for care-cascade interventions between 0.05%
and 3.27%.
Conclusion. We describe a body of mathematical modelling research with a focus on TB prevention and care in SA. We found higher
estimates of impact reported in studies of preventive interventions, highlighting the need to invest in TB prevention in SA. However, study
heterogeneity and inconsistent baseline scenarios limit the ability to compare impact estimates between studies. Combinations, rather than
single interventions, are likely needed to reach the End TB Strategy targets in SA
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