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Tuberculosis (TB) exhibits considerable spatial heterogeneity, occurring in clusters that may act as hubs of community transmission. We evaluated the impact of an intervention targeting spatial TB hotspots in a rural region of Ethiopia. To evaluate the impact of targeted active case finding (ACF), we used a spatially structured mathematical model that has previously been described. From model equilibrium, we simulated the impact of a hotspot-targeted strategy (HTS) on TB incidence ten years from intervention commencement and the associated cost-effectiveness. HTS was also compared with an untargeted strategy (UTS). We used logistic cost-coverage analysis to estimate cost-effectiveness of interventions. At a community screening coverage level of 95 % in a hotspot region, which corresponds to screening 20 % of the total population, HTS would reduce overall TB incidence by 52 % compared with baseline. For UTS to achieve an equivalent effect, it would be necessary to screen more than 80 % of the total population. Compared to the existing passive case detection strategy, the HTS at a CDR of 75 percent in hotspot regions is expected to avert 1,023 new TB cases over ten years saving USD 170 per averted case. Similarly, at the same CDR, the UTS will detect 1316 cases over the same period saving USD 3 per averted TB case. The incremental-cost effectiveness-ratio (ICER) of UTS compared with HTS is USD 582 per averted case corresponding to 293 more TB cases averted at an additional cost of USD 170,700. Where regional TB program spending was capped at current levels, maximum gains in incidence reduction were seen when the regional budget was shared between hotspots and non-hotspot regions in the ratio of 40% : 60%. Our analysis suggests that a spatially targeted strategy is efficient and cost-saving, with the potential for significant reduction in overall TB burden., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

As Bulgaria transitions away from Global Fund grant, robust estimates of the comparative impact of the various response strategies under consideration are needed to ensure sustained effectiveness of the tuberculosis (TB) programme. We tailored an established mathematical model for TB control to the epidemic in Bulgaria to project the likely outcomes of seven intervention scenarios. Under existing programmatic conditions projected forward, the country's targets for achieving TB elimination in the coming decades will not be achieved. No interventions under consideration were predicted to accelerate the baseline projected reduction in epidemiological indicators significantly. Discontinuation of the 'Open Doors' program and activities of non-governmental organisations would result in a marked exacerbation of the epidemic (increasing incidence in 2035 by 6-8% relative to baseline conditions projected forward). Changing to a short course regimen for multidrug-resistant TB (MDR-TB) would substantially decrease MDR-TB mortality (by 21.6% in 2035 relative to baseline conditions projected forward). Changing to ambulatory care for eligible patients would not affect TB burden but would be markedly cost-saving. In conclusion, Bulgaria faces important challenges in transitioning to a primarily domestically-financed TB programme. The country should consider maintaining currently effective programs and shifting towards ambulatory care to ensure program sustainability.

We performed a systematic review and meta-analyses of studies assessing tuberculosis (TB) patient-related risk factors for transmission of Mycobacterium tuberculosis infection. Meta-analyses were conducted for sputum smear-positivity, lung cavitation and HIV seropositivity of index patients with both crude and adjusted odds ratios (AORs) pooled using random effect models. Thirty-seven studies were included in the review. We found that demographic characteristics such as age and sex were not significant risk factors, while behaviours such as smoking and alcohol intake were associated with infectiousness although inconsistently. Treatment delay of >28 days was a significant predictor of greater infectiousness. Contacts of sputum smear-positive index patients were found to be more likely to be infected than contacts of sputum smear-negative patients, with a pooled AOR of 2.15 (95% confidence interval (CI) 1.47-3.17, I 2 = 38%). Similarly, contacts of patients with the cavitary disease were around twice as likely to be infected as contacts of patients without cavitation (pooled AOR 1.9, 95% CI 1.26-2.84, I 2 = 63%). In contrast, HIV seropositive patients were associated with few contact infections than HIV seronegative patients (AOR 0.45, 95% CI 0.26-0.80, I 2 = 52%). In conclusion, behavioural and clinical characteristics of TB patients can be used to identify highly infectious patients for targeted interventions.

Background: Tuberculosis (TB) is now the world's leading infectious killer and major programmatic advances will be needed if we are to meet the ambitious new End TB Targets. Although mathematical models are powerful tools for TB control, such models must be flexible enough to capture the complexity and heterogeneity of the global TB epidemic. This includes simulating a disease that affects age groups and other risk groups differently, has varying levels of infectiousness depending upon the organ involved and varying outcomes from treatment depending on the drug resistance pattern of the infecting strain., Results: We adopted sound basic principles of software engineering to develop a modular software platform for simulation of TB control interventions ("AuTuMN"). These included object-oriented programming, logical linkage between modules and consistency of code syntax and variable naming. The underlying transmission dynamic model incorporates optional stratification by age, risk group, strain and organ involvement, while our approach to simulating time-variant programmatic parameters better captures the historical progression of the epidemic. An economic model is overlaid upon this epidemiological model which facilitates comparison between new and existing technologies. A "Model runner" module allows for predictions of future disease burden trajectories under alternative scenario situations, as well as uncertainty, automatic calibration, cost-effectiveness and optimisation. The model has now been used to guide TB control strategies across a range of settings and countries, with our modular approach enabling repeated application of the tool without the need for extensive modification for each application., Conclusions: The modular construction of the platform minimises errors, enhances readability and collaboration between multiple programmers and enables rapid adaptation to answer questions in a broad range of contexts without the need for extensive re-programming. Such features are particularly important in simulating an epidemic as complex and diverse as TB.