Browsing by Author "de Villiers, Abigail Kate"

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    Spatially-targeted digital chest radiography-based screening to reduce tuberculosis in high-burden settings : simulation of an adaptive decision-making approach and cost-effectiveness analysis
    (Stellenbosch : Stellenbosch University, 2022-04) de Villiers, Abigail Kate; Marx, Florian; Nyasulu, Peter; Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Global Health. Epidemiology and Biostatistics.
    ENGLISH SUMMARY: Background. Interventions to actively detect individuals with tuberculosis (TB) and to enable timely treatment could accelerate TB control. Spatially-targeted interventions that concentrate screening within geographic “hotspots” of tuberculosis incidence, could lead to more effective allocation of already limited resources. However, identifying and prioritizing areas with the highest burdens of undetected TB is challenging. The aim of this thesis was to investigate the effectiveness and cost-effectiveness of an adaptive decision-making approach for spatially-targeted, community-based TB screening in high burden settings. Towards this principal aim, there were three objectives: (1) to develop a Monte-Carlo simulation model of a hypothetical digital chest radiography (dCXR)-based TB screening intervention and then to use the simulation to (2) project, in 24 high TB burden communities in South Africa and Zambia, the case-finding yield under the adaptive approach compared to untargeted (random) allocation of screening resources and to (3) investigate the cost-effectiveness of the adaptive approach relative to random and notification based allocation in 12 high burden communities in metropolitan Cape Town, South Africa. Methods. A probabilistic simulation model to simulate a TB screening intervention with TB prevalence estimates derived from a large community-randomized trial was developed. A hypothetical scenario of TB screening was assumed under which mobile screening units were allocated among communities during a 52-week period. A Thompson sampling algorithm was implemented to adaptively allocate screening units based on Bayesian probabilities of local TB prevalence that are continuously updated during weekly screening rounds. The simulation was used to estimate and compare yields of bacteriologically-confirmed TB patients detected per 1,000 screenings performed. Thereafter, the simulation was extended to estimate costs and disability-adjusted life years averted (DALYs). Results. Random allocation of four screening units among the 24 communities would result in an expected 665 (95% uncertainty interval 523-819) TB cases detected over one year, equivalent to 8.9 (7.5-10.4) per 1,000 screened. Spatially-targeted allocation informed by the adaptive decision-making approach would increase this yield. Balanced, adaptive allocation resulted in an expected 1,234 (983-1,487) TB cases detected, 16.5 (14.5-19.0) per 1,000 screened. Numbers of dCXR-based screenings to find one additional TB case declined during the first 12-14 weeks as a result of Bayesian learning. Random-allocation of three screening units among the 12 communities was estimated to avert 1,523(980 – 2,181) DALYs at a cost of $216 ($149 – $321) per DALY averted. Balanced, adaptive allocation could yield an additional 19% of DALYs at an incremental cost of $61 ($24 – $177) per additional DALY averted relative to random allocation. However, this incremental cost per DALY averted increased with increasing costs incurred to adaptively relocate screening units among communities. Conclusion. An approach for spatially-targeted TB screening is proposed that could reduce the number of dCXR screenings necessary to detect additional TB cases in high-burden settings. Furthermore, the approach could result in additional health benefits at relatively low additional cost. However, the extent to which this approach is cost-effective and feasible depends on the additional logistics and costs incurred to relocate the screening units. Empirical research is needed to determine whether this approach could be successfully implemented.