Evaluating the potential impact of enhancing HIV treatment and tuberculosis control programmes on the burden of tuberculosis

Mathematical models of drug-resistant tuberculosis lack bacterial heterogeneity: A systematic review

Drug-resistant tuberculosis (DR-TB) threatens progress in the control of TB. Mathematical models are increasingly being used to guide public health decisions on managing both antimicrobial resistance (AMR) and TB. It is important to consider bacterial heterogeneity in models as it can have consequences for predictions of resistance prevalence, which may affect decision-making. We conducted a systematic review of published mathematical models to determine the modelling landscape and to explore methods for including bacterial heterogeneity. Our first objective was to identify and analyse the general characteristics of mathematical models of DR-mycobacteria, including M. tuberculosis. The second objective was to analyse methods of including bacterial heterogeneity in these models. We had different definitions of heterogeneity depending on the model level. For between-host models of mycobacterium, heterogeneity was defined as any model where bacteria of the same resistance level were further differentiated. For bacterial population models, heterogeneity was defined as having multiple distinct resistant populations. The search was conducted following PRISMA guidelines in five databases, with studies included if they were mechanistic or simulation models of DR-mycobacteria. We identified 195 studies modelling DR-mycobacteria, with most being dynamic transmission models of non-treatment intervention impact in M. tuberculosis (n = 58). Studies were set in a limited number of specific countries, and 44% of models (n = 85) included only a single level of "multidrug-resistance (MDR)". Only 23 models (8 between-host) included any bacterial heterogeneity. Most of these also captured multiple antibiotic-resistant classes (n = 17), but six models included heterogeneity in bacterial populations resistant to a single antibiotic. Heterogeneity was usually represented by different fitness values for bacteria resistant to the same antibiotic (61%, n = 14). A large and growing body of mathematical models of DR-mycobacterium is being used to explore intervention impact to support policy as well as theoretical explorations of resistance dynamics. However, the majority lack bacterial heterogeneity, suggesting that important evolutionary effects may be missed.

Impact of interventions for tuberculosis prevention and care in South Africa - a systematic review of mathematical modelling studies

BACKGROUND

Substantial additional efforts are needed to prevent, find and successfully treat tuberculosis (TB) in South Africa (SA). In thepast decade, an increasing body of mathematical modelling research has investigated the population-level impact of TB prevention and careinterventions. 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 HealthOrganization'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 SAand reported on at least one of the End TB Strategy targets at population level. We described study populations, type of interventions andtheir target groups, and estimates of impact and other key findings. For studies of country-level interventions, we estimated average annualpercentage 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 combinationsof preventive and care-cascade interventions. Only one study focused on reducing catastrophic costs due to TB. The highest impactof a single intervention was estimated in studies of TB vaccination, TPT among people living with HIV, and scale-up of ART. Forpreventive 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 higherestimates of impact reported in studies of preventive interventions, highlighting the need to invest in TB prevention in SA. However, studyheterogeneity and inconsistent baseline scenarios limit the ability to compare impact estimates between studies. Combinations, rather thansingle interventions, are likely needed to reach the End TB Strategy targets in SA.

Impact of the gate-keeping policies of China's primary healthcare model on the future burden of tuberculosis in China: a protocol for a mathematical modelling study

INTRODUCTION

In the past three decades, China has made great strides in the prevention and treatment of tuberculosis (TB). However, the TB burden remains high. In 2019, China accounted for 8.4% of global incident cases of TB, the third highest in the world, with a higher prevalence in rural areas. The Healthy China 2030 highlights the gate-keeping role of primary healthcare (PHC). However, the impact of PHC reforms on the future TB burden is unclear. We propose to use mathematical models to project and evaluate the impacts of different gate-keeping policies.

METHODS AND ANALYSIS

We will develop a deterministic, population-level, compartmental model to capture the dynamics of TB transmission within adult rural population. The model will incorporate seven main TB statuses, and each compartment will be subdivided by service providers. The parameters involving preference for healthcare seeking will be collected using discrete choice experiment (DCE) method. We will solve the deterministic model numerically over a 20-year (2021-2040) timeframe and predict the TB prevalence, incidence and cumulative new infections under the status quo or various policy scenarios. We will also conduct an analysis following standard protocols to calculate the average cost-effectiveness for each policy scenario relative to the status quo. A numerical calibration analysis against the available published TB prevalence data will be performed using a Bayesian approach.

ETHICS AND DISSEMINATION

Most of the data or parameters in the model will be obtained based on secondary data (eg, published literature and an open-access data set). The DCE survey has been reviewed and approved by the Ethics Committee of the School of Public Health, Sun Yat-sen University. The approval number is SYSU [2019]140. Results of the study will be disseminated through peer-reviewed journals, media and conference presentations.

Is tuberculosis elimination a feasible goal in Colombia by 2050?

Colombia has an underreporting of 30% of the total cases, according to World Health Organization (WHO) estimations. In 2016, successful tuberculosis (TB) treatment rate was 70%, and the mortality rate ranged between 3.5% and 10%. In 2015, Colombia adopted and adapted the End TB strategy and set a target of 50% reduction in incidence and mortality by 2035 compared with 2015. The aims of this study were: To evaluate whether Colombia will be able to achieve the goals of TB incidence and mortality by 2050, using the current strategies; and whether the implementation of new screening, diagnosis and TB treatment strategies will allow to achieve those WHO targets. An ecological study was conducted using TB case-notification, successful treatment and mortality rates from the last 8 years (2009-17). System dynamics analysis was performed using simulated scenarios: (1) continuation with the same trends following the trajectory of the last 8 years (Status quo) and (2) modification of the targets between 2017 through 2050, assuming the implementation of multimodal strategies to increase the screening, to improve the early diagnosis and to improve the treatment adherence. Following the current strategies, it is projected that Colombia will not achieve the End TB strategy targets. Achieving the goal of TB incidence of 10/100 000 by 2050 will only be possible by implementing combined strategies for increasing screening of people with respiratory symptoms, improving access to rapid diagnostic tests and improving treatment adherence. Therefore, it is necessary to design and implement simultaneous strategies according to the population needs and resources, in order to stride towards the End TB targets.

Temporal pattern of tuberculosis cure, mortality, and treatment abandonment in Brazilian capitals

Objective:

to analyze the temporal pattern of tuberculosis cure, mortality, treatment abandonment in Brazilian capitals.

Method:

this is an ecological study whose data source was the Information System of Notifiable Diseases for Tuberculosis (Sistema de Informação de Agravos de Notificação para Tuberculose). For analysis of temporal evolution, regressions by join points were performed considering the annual percentage variation and the significance of the trend change with 95% confidence interval.

Results:

542,656 cases of tuberculosis were found, with emphasis on a 3% decrease per year in the cure rate for Campo Grande (interval: −5.0 - −0.9) and a 3.5% increase for Rio de Janeiro (interval: 1.9 - 4.7). Regarding abandonment, it decreased 10.9% per year in Rio Branco (interval: −15.8 - −5.7) and increased 12.8% per year in Fortaleza (interval: 7.6 - 18.3). For mortality, a decreasing or stationary tendency was identified, with a greater decrease (7.8%) for Porto Velho (interval:−11.0 - −5.0) and a lower one (2.5%) in Porto Alegre (interval:−4.5 - −0.6).

Conclusion:

the rates of cure and abandonment are far from the ones recommended by the World Health Organization, showing that Brazilian capitals need interventions aimed at changing this pattern.

Decreased risk of HIV-associated TB during antiretroviral therapy expansion in rural Eswatini from 2009 to 2016: a cohort and population-based analysis

OBJECTIVES

This paper assesses patient- and population-level trends in TB notifications during rapid expansion of antiretroviral therapy in Eswatini which has an extremely high incidence of both TB and HIV.

METHODS

Patient- and population-level predictors and rates of HIV-associated TB were examined in the Shiselweni region in Eswatini from 2009 to 2016. Annual population-level denominators obtained from projected census data and prevalence estimates obtained from population-based surveys were combined with individual-level TB treatment data. Patient- and population-level predictors of HIV-associated TB were assessed with multivariate logistic and multivariate negative binomial regression models.

RESULTS

Of 11 328 TB cases, 71.4% were HIV co-infected and 51.8% were women. TB notifications decreased fivefold between 2009 and 2016, from 1341 to 269 cases per 100 000 person-years. The decline was sixfold in PLHIV vs. threefold in the HIV-negative population. Main patient-level predictors of HIV-associated TB were recurrent TB treatment (adjusted odds ratio [aOR] 1.40, 95% confidence interval [CI]: 1.19-1.65), negative (aOR 1.31, 1.15-1.49) and missing (aOR 1.30, 1.11-1.53) bacteriological status and diagnosis at secondary healthcare level (aOR 1.18, 1.06-1.33). Compared with 2009, the probability of TB decreased for all years from 2011 (aOR 0.69, 0.58-0.83) to 2016 (aOR 0.54, 0.43-0.69). The most pronounced population-level predictor of TB was HIV-positive status (adjusted incidence risk ratio 19.47, 14.89-25.46).

CONCLUSIONS

This high HIV-TB prevalence setting experienced a rapid decline in TB notifications, most pronounced in PLHIV. Achievements in HIV-TB programming were likely contributing factors.

Space-time clustering of recently-diagnosed tuberculosis and impact of ART scale-up: Evidence from an HIV hyper-endemic rural South African population

In HIV hyperendemic sub-Saharan African communities, particularly in southern Africa, the likelihood of achieving the Sustainable Development Goal of ending the tuberculosis (TB) epidemic by 2030 is low, due to lack of cost-effective and practical interventions in population settings. We used one of Africa’s largest population-based prospective cohorts from rural KwaZulu-Natal Province, South Africa, to measure the spatial variations in the prevalence of recently-diagnosed TB disease, and to quantify the impact of community coverage of antiretroviral therapy (ART) on recently-diagnosed TB disease. We collected data on TB disease episodes from a population-based sample of 41,812 adult individuals between 2009 and 2015. Spatial clusters (‘hotspots’) of recently-diagnosed TB were identified using a space-time scan statistic. Multilevel logistic regression models were fitted to investigate the relationship between community ART coverage and recently-diagnosed TB. Spatial clusters of recently-diagnosed TB were identified in a region characterized by a high prevalence of HIV and population movement. Every percentage increase in ART coverage was associated with a 2% decrease in the odds of recently-diagnosed TB (aOR = 0.98, 95% CI:0.97–0.99). We identified for the first time the clear occurrence of recently-diagnosed TB hotspots, and quantified potential benefit of increased community ART coverage in lowering tuberculosis, highlighting the need to prioritize the expansion of such effective population interventions targeting high-risk areas.

The prevalence of HIV among adults with pulmonary TB at a population level in Zambia

Background

Tuberculosis and HIV co-infection is one of the main drivers of poor outcome for both diseases in Zambia. HIV infection has been found to predict TB infection/disease and TB has been reported as a major cause of death among individuals with HIV. Improving case detection of TB/HIV co-infection has the potential to lead to early treatment of both conditions and can impact positively on treatment outcomes. This study was conducted in order to determine the HIV prevalence among adults with tuberculosis in a national prevalence survey setting in Zambia, 2013–2014.

Methods

A countrywide cross sectional survey was conducted in 2013/2014 using stratified cluster sampling, proportional to population size for rural and urban populations. Each of the 66 countrywide clusters represented one census supervisory area with cluster size averaging 825 individuals. Socio-demographic characteristics were collected during a household visit by trained survey staff. A standard symptom-screening questionnaire was administered to 46,099 eligible individuals across all clusters, followed by chest x-ray reading for all eligible. Those symptomatic or with x-ray abnormalities were confirmed or ruled out as TB case by either liquid culture or Xpert MTBRif performed at the three central reference laboratories. HIV testing was offered to all participants at the survey site following the national testing algorithm with rapid tests. The prevalence was expressed as the proportion of HIV among TB cases with 95% confidence limits.

Results

A total of 265/6123 (4.3%) participants were confirmed of having tuberculosis. Thirty-six of 151 TB survey cases who accepted HIV testing were HIV-seropositive (23.8%; 95% CI 17.2–31.4). The mean age of the TB/HIV cases was 37.6 years (range 24–70). The majority of the TB/HIV cases had some chest x-ray abnormality (88.9%); were smear positive (50.0%), and/or had a positive culture result (94.4%). None of the 36 detected TB/HIV cases were already on TB treatment, and 5/36 (13.9%) had a previous history of TB treatment. The proportion of TB/HIV was higher in urban than in the rural clusters. The HIV status was unknown for 114/265 (43.0%) of the TB cases.

Conclusions

The TB/HIV prevalence in the general population was found to be lower than what is routinely reported as incident TB/HIV cases at facility level. However; the TB/HIV co-infection was higher in areas with higher TB prevalence. Innovative and effective strategies for ensuring TB/HIV co-infected individuals are detected and treated early are required.

Cost-effectiveness and resource implications of aggressive action on tuberculosis in China, India, and South Africa: a combined analysis of nine models

BACKGROUND

The post-2015 End TB Strategy sets global targets of reducing tuberculosis incidence by 50% and mortality by 75% by 2025. We aimed to assess resource requirements and cost-effectiveness of strategies to achieve these targets in China, India, and South Africa.

METHODS

We examined intervention scenarios developed in consultation with country stakeholders, which scaled up existing interventions to high but feasible coverage by 2025. Nine independent modelling groups collaborated to estimate policy outcomes, and we estimated the cost of each scenario by synthesising service use estimates, empirical cost data, and expert opinion on implementation strategies. We estimated health effects (ie, disability-adjusted life-years averted) and resource implications for 2016-35, including patient-incurred costs. To assess resource requirements and cost-effectiveness, we compared scenarios with a base case representing continued current practice.

FINDINGS

Incremental tuberculosis service costs differed by scenario and country, and in some cases they more than doubled existing funding needs. In general, expansion of tuberculosis services substantially reduced patient-incurred costs and, in India and China, produced net cost savings for most interventions under a societal perspective. In all three countries, expansion of access to care produced substantial health gains. Compared with current practice and conventional cost-effectiveness thresholds, most intervention approaches seemed highly cost-effective.

INTERPRETATION

Expansion of tuberculosis services seems cost-effective for high-burden countries and could generate substantial health and economic benefits for patients, although substantial new funding would be required. Further work to determine the optimal intervention mix for each country is necessary.

FUNDING

Bill & Melinda Gates Foundation.