Integrating Community-Based Interventions to Reverse the Convergent TB/HIV Epidemics in Rural South Africa.

The WHO recommends integrating interventions to address the devastating TB/HIV co-epidemics in South Africa, yet integration has been poorly implemented and TB/HIV control efforts need strengthening. Identifying infected individuals is particularly difficult in rural settings. We used mathematical modeling to predict the impact of community-based, integrated TB/HIV case finding and additional control strategies on South Africa's TB/HIV epidemics. We developed a model incorporating TB and HIV transmission to evaluate the effectiveness of integrating TB and HIV interventions in rural South Africa over 10 years. We modeled the impact of a novel screening program that integrates case finding for TB and HIV in the community, comparing it to status quo and recommended TB/HIV control strategies, including GeneXpert, MDR-TB treatment decentralization, improved first-line TB treatment cure rate, isoniazid preventive therapy, and expanded ART. Combining recommended interventions averted 27% of expected TB cases (95% CI 18-40%) 18% HIV (95% CI 13-24%), 60% MDR-TB (95% CI 34-83%), 69% XDR-TB (95% CI 34-90%), and 16% TB/HIV deaths (95% CI 12-29). Supplementing these interventions with annual community-based TB/HIV case finding averted a further 17% of TB cases (44% total; 95% CI 31-56%), 5% HIV (23% total; 95% CI 17-29%), 8% MDR-TB (68% total; 95% CI 40-88%), 4% XDR-TB (73% total; 95% CI 38-91%), and 8% TB/HIV deaths (24% total; 95% CI 16-39%). In addition to increasing screening frequency, we found that improving TB symptom questionnaire sensitivity, second-line TB treatment delays, default before initiating TB treatment or ART, and second-line TB drug efficacy were significantly associated with even greater reductions in TB and HIV cases. TB/HIV epidemics in South Africa were most effectively curtailed by simultaneously implementing interventions that integrated community-based TB/HIV control strategies and targeted drug-resistant TB. Strengthening existing TB and HIV treatment programs is needed to further reduce disease incidence

Prevalence and factors associated with diabetes mellitus among tuberculosis patients: a nationwide cohort

In Press, Corrected ProofThe association between diabetes mellitus (DM) and tuberculosis (TB) has been a matter of study worldwide, since it is assumed that DM triples the risk of TB. Recent studies have found discrepant prevalence of DM among TB patients, ranging from 5.3% in Denmark to 44% in India. There is an urgent need to control both epidemics in order to achieve the World Health Organization (WHO) TB elimination goal. To reach this goal, an integrated approach between TB elimination strategies and control of noncommunicable diseases that perpetuate the risk for TB is fundamental.(undefined

PLoS One

The WHO recommends integrating interventions to address the devastating TB/HIV co-epidemics in South Africa, yet integration has been poorly implemented and TB/HIV control efforts need strengthening. Identifying infected individuals is particularly difficult in rural settings. We used mathematical modeling to predict the impact of community-based, integrated TB/HIV case finding and additional control strategies on South Africa's TB/HIV epidemics. We developed a model incorporating TB and HIV transmission to evaluate the effectiveness of integrating TB and HIV interventions in rural South Africa over 10 years. We modeled the impact of a novel screening program that integrates case finding for TB and HIV in the community, comparing it to status quo and recommended TB/HIV control strategies, including GeneXpert, MDR-TB treatment decentralization, improved first-line TB treatment cure rate, isoniazid preventive therapy, and expanded ART. Combining recommended interventions averted 27% of expected TB cases (95% CI 18-40%) 18% HIV (95% CI 13-24%), 60% MDR-TB (95% CI 34-83%), 69% XDR-TB (95% CI 34-90%), and 16% TB/HIV deaths (95% CI 12-29). Supplementing these interventions with annual community-based TB/HIV case finding averted a further 17% of TB cases (44% total; 95% CI 31-56%), 5% HIV (23% total; 95% CI 17-29%), 8% MDR-TB (68% total; 95% CI 40-88%), 4% XDR-TB (73% total; 95% CI 38-91%), and 8% TB/HIV deaths (24% total; 95% CI 16-39%). In addition to increasing screening frequency, we found that improving TB symptom questionnaire sensitivity, second-line TB treatment delays, default before initiating TB treatment or ART, and second-line TB drug efficacy were significantly associated with even greater reductions in TB and HIV cases. TB/HIV epidemics in South Africa were most effectively curtailed by simultaneously implementing interventions that integrated community-based TB/HIV control strategies and targeted drug-resistant TB. Strengthening existing TB and HIV treatment programs is needed to further reduce disease incidence.20151K23AI089260/AI/NIAID NIH HHS/United States1U01GH000524-01/GH/CGH CDC HHS/United States2U01GM087719/GM/NIGMS NIH HHS/United States5U01GM105627/GM/NIGMS NIH HHS/United StatesK23 AI089260/AI/NIAID NIH HHS/United StatesR01DA015612/DA/NIDA NIH HHS/United StatesR01DA025932/DA/NIDA NIH HHS/United StatesR24TW007988/TW/FIC NIH HHS/United States25938501PMC4418809668

Combating Tuberculosis: Using Time-Dependent Sensitivity Analysis to Develop Strategies for Treatment and Prevention

Although many organizations throughout the world have worked tirelessly to control tuberculosis (TB) epidemics, no country has yet been able to eradicate the disease completely. We present two compartmental models representing the spread of a TB epidemic through a population. The first is a general TB model; the second is an adaptation for regions in which HIV is prevalent, accounting for the effects of TB/HIV co-infection. Using active subspaces, we conduct time-dependent sensitivity analysis on both models to explore the significance of certain parameters with respect to the spread of TB. We use the results of this sensitivity analysis to determine the most effective strategies for treatment and prevention throughout the epidemic

Unpacking the dynamics of double stigma : how the HIV-TB co-epidemic alters TB stigma and its management among healthcare workers

Background HIV and tuberculosis (TB) are intricably interlinked in South Africa. The social aspects of this co-epidemic remain relatively unexplored. More specifically, no research has quantitatively explored the double stigma associated with HIV and TB in this context, and more specifically the impact of the co-epidemic on [1] the stigmatisation of TB and [2] the TB stigma mangement strategy of covering (i.e. the use of TB as a cover for having HIV). The current study aims to address this research gap by disentangling the complex mechanisms related to HIV-TB stigma. Methods Using Structural Equation Modelling (SEM), data of 882 health care workers (HCWs) in the Free State province, South Africa, are analysed to investigate the link between the stigmatization of HIV and TB and the stigma management by those affected. The current study focuses on health care workers (HCWs), as both TB and HIV have a severe impact on this professional group. Results The results demonstrate that the perceived link between the epidemics is significantly associated with double HIV-TB stigmatization. Furthermore, the link between the illnesses and the double stigma are driving the stigmatization of TB. Finally, the link between HIV and TB as well as the stigmatization of both diseases by colleagues are associated with an increased use of covering as a stigma management strategy. Conclusions This is the first quantitative study disentagling the mediating role of double stigma in the context of the co-epidemic as well as the impact of the co-epidemic on the social connotations of TB. The results stress the need for an integrated approach in the fight against HIV and TB recognizing the intertwined nature of the co-epidemic, not only in medical-clinical terms, but also in its social consequences

Epidemiological impact of targeted interventions for people with diabetes mellitus on tuberculosis transmission in India: Modelling based predictions.

INTRODUCTION: Diabetes mellitus (DM) is a leading driver of tuberculosis (TB) disease in TB-DM burdened countries. We aimed to assess the impact on TB disease of several intervention strategies targeting people with DM in India. METHODS: A previously validated TB-DM mathematical model was extended to include interventions targeting DM individuals. The model stratified the population by age, DM status, TB infection status and stage, TB disease form, treatment, recovery, and intervention status. RESULTS: By 2050, different TB vaccination strategies (coverage of 50 % and vaccine efficacies ranging between 50 %-60 %) reduced TB incidence and mortality rates by 4.5 %-20.8 % and 4.1 %-22.1 %, respectively, and averted 3.1 %-12.8 % of TB disease cases in the total population. Number of vaccinations needed to avert one TB case (effectiveness) was 14-105. Varying the coverage levels of latent TB treatment (coverage of 50 %-80 % and drug effectiveness of 90 %) reduced TB incidence and mortality rates by 7.1 %-11.3 % and 8.2 %-13.0 %, respectively, averting 4.2 %-6.7 % of TB cases, with effectiveness of 38-40. Different scenarios for dual and concurrent treatment of those with TB and DM, reduced TB incidence and mortality rates by 0.1 %-0.4 % and 1.3 %-4.8 %, respectively, averting 0.1 %-0.2 % of TB cases, with effectiveness of 28-107. Different scenarios for managing and controlling DM (regardless of TB status) reduced TB incidence and mortality rates by 4.5 %-16.5 % and 6.5 %-22.2 %, respectively, averting 2.9 %-10.8 % of TB cases, with effectiveness of 6-24. CONCLUSION: Gains can be attained by targeting DM individuals with interventions to reduce TB burden. Most strategies were effective with <50 intervention doses needed to avert one TB disease case, informing key updates of current treatment guidelines

Social distancing strategies against disease spreading

The recurrent infectious diseases and their increasing impact on the society has promoted the study of strategies to slow down the epidemic spreading. In this review we outline the applications of percolation theory to describe strategies against epidemic spreading on complex networks. We give a general outlook of the relation between link percolation and the susceptible-infected-recovered model, and introduce the node void percolation process to describe the dilution of the network composed by healthy individual, $i.e$, the network that sustain the functionality of a society. Then, we survey two strategies: the quenched disorder strategy where an heterogeneous distribution of contact intensities is induced in society, and the intermittent social distancing strategy where health individuals are persuaded to avoid contact with their neighbors for intermittent periods of time. Using percolation tools, we show that both strategies may halt the epidemic spreading. Finally, we discuss the role of the transmissibility, $i.e$, the effective probability to transmit a disease, on the performance of the strategies to slow down the epidemic spreading.Comment: to be published in "Perspectives and Challenges in Statistical Physics and Complex Systems for the Next Decade", Word Scientific Pres