Botswana tuberculosis (TB) stakeholders broadly support scaling up next-generation whole genome sequencing: Ethical and practical considerations for Botswana and global health.

Global health agencies are increasingly promoting the scale-up of next-generation whole genome sequencing (NG-WGS) of pathogens into infectious disease control programs, including for tuberculosis (TB). However, little is known about how stakeholders in low-to-middle income countries (LMICs) understand the ethics, benefits, and risks of these proposals. We conducted a qualitative study in Greater Gaborone, Botswana to learn how TB stakeholders there viewed a potential scale-up of NG-WGS into Botswana's TB program. We conducted 30 interviews and four deliberative dialogues with TB stakeholders based in Greater Gaborone, the country's largest city and capital. We created and showed participants an animated video series about a fictional family that experienced TB diagnosis, treatment, contact tracing, and data uses that were informed by NG-WGS. We analyzed transcripts using reflexive thematic analysis. We found broad support for the scale-up of TB NG-WGS in Botswana, owing to perceived benefits. Support was qualified with statements about ensuring adequate planning, resource-allocation, community and stakeholder engagement, capacity-building, and assessing ethical norms around publishing data. Our results suggest that scaling up NG-WGS for TB in Botswana would be supported by stakeholders there, contingent upon the government and other entities adequately investing in the initiative. These findings are relevant to other LMICs considering scale-ups of NG-WGS and related technologies for infectious diseases and suggest the need for sustained research into the acceptability of pathogen sequencing in other contexts.

Using genetic data to identify transmission risk factors: Statistical assessment and application to tuberculosis transmission.

Identifying host factors that influence infectious disease transmission is an important step toward developing interventions to reduce disease incidence. Recent advances in methods for reconstructing infectious disease transmission events using pathogen genomic and epidemiological data open the door for investigation of host factors that affect onward transmission. While most transmission reconstruction methods are designed to work with densely sampled outbreaks, these methods are making their way into surveillance studies, where the fraction of sampled cases with sequenced pathogens could be relatively low. Surveillance studies that use transmission event reconstruction then use the reconstructed events as response variables (i.e., infection source status of each sampled case) and use host characteristics as predictors (e.g., presence of HIV infection) in regression models. We use simulations to study estimation of the effect of a host factor on probability of being an infection source via this multi-step inferential procedure. Using TransPhylo-a widely-used method for Bayesian estimation of infectious disease transmission events-and logistic regression, we find that low sensitivity of identifying infection sources leads to dilution of the signal, biasing logistic regression coefficients toward zero. We show that increasing the proportion of sampled cases improves sensitivity and some, but not all properties of the logistic regression inference. Application of these approaches to real world data from a population-based TB study in Botswana fails to detect an association between HIV infection and probability of being a TB infection source. We conclude that application of a pipeline, where one first uses TransPhylo and sparsely sampled surveillance data to infer transmission events and then estimates effects of host characteristics on probabilities of these events, should be accompanied by a realistic simulation study to better understand biases stemming from imprecise transmission event inference.

Tuberculosis attributed to transmission within healthcare facilities, Botswana-The Kopanyo Study.

OBJECTIVE: Healthcare facilities are a well-known high-risk environment for transmission of M. tuberculosis, the etiologic agent of tuberculosis (TB) disease. However, the link between M. tuberculosis transmission in healthcare facilities and its role in the general TB epidemic is unknown. We estimated the proportion of overall TB transmission in the general population attributable to healthcare facilities. METHODS: We combined data from a prospective, population-based molecular epidemiologic study with a universal electronic medical record (EMR) covering all healthcare facilities in Botswana to identify biologically plausible transmission events occurring at the healthcare facility. Patients with M. tuberculosis isolates of the same genotype visiting the same facility concurrently were considered an overlapping event. We then used TB diagnosis and treatment data to categorize overlapping events into biologically plausible definitions. We calculated the proportion of overall TB cases in the cohort that could be attributable to healthcare facilities. RESULTS: In total, 1,881 participants had TB genotypic and EMR data suitable for analysis, resulting in 46,853 clinical encounters at 338 healthcare facilities. We identified 326 unique overlapping events involving 370 individual patients; 91 (5%) had biologic plausibility for transmission occurring at a healthcare facility. A sensitivity analysis estimated that 3%-8% of transmission may be attributable to healthcare facilities. CONCLUSIONS: Although effective interventions are critical in reducing individual risk for healthcare workers and patients at healthcare facilities, our findings suggest that development of targeted interventions aimed at community transmission may have a larger impact in reducing TB.

Clinical and Virological Outcomes of TB/HIV Coinfected Patients Treated With Dolutegravir-Based HIV Antiretroviral Regimens: Programmatic Experience From Botswana.

BACKGROUND: Dolutegravir (DTG) has recently been recommended as a preferred first-line regimen for the treatment of new and treatment-experienced HIV-infected patients. However, potential drug interactions between DTG and rifampicin remain a clinical and public health concern. METHODS: We analyzed HIV and Tuberculosis (TB) treatment outcomes of HIV-infected patients concomitantly receiving rifampicin- and DTG-based regimens under programmatic conditions in Botswana. The outcomes of interest were successful TB treatment and viral load suppression. We used multivariable logistic models to determine predictors for each outcome of interest. RESULTS: A total of 1225 patients were included in the analysis to evaluate predictors of successful TB outcome. Among patients on DTG and non-DTG regimens, 90.9% and 88.3% achieved favorable TB treatment outcomes, respectively. Of those who received DTG-based regimen; 44% received once-daily dosing and 53% twice-daily dosing. We found that DTG was associated with favorable TB treatment outcome (adjusted odds ratio = 1.56; 95% confidence interval = 1.06 to 2.31), after adjusting for age, gender, and CD4 cell counts. High rates of viral load suppression were found across all antiretroviral therapy (ART) regimen categories (>92% for all). We did not find an independent association between DTG and viral suppression after adjustment of other covariates. CONCLUSIONS: The use of DTG-based ART regimens in patients coinfected with TB and HIV lead to favorable TB and HIV treatment outcomes, comparable to those achieved with alternative ART regimens. Our results provide reassurance to TB and HIV programs about the overall programmatic concomitant use of these first-line treatment regimens for the management of HIV and TB coinfected patients.

Diagnosis of pulmonary tuberculosis and assessment of treatment response through analyses of volatile compound patterns in exhaled breath samples.

OBJECTIVES: We determined the performance of a sensor array (an electronic nose) made of 8 metalloporphyrins coated quartz microbalances sensors for the diagnosis and prognosis of pulmonary tuberculosis (TB) using exhaled breath samples. METHODS: TB cases and healthy controls were prospectively enrolled. Signals from volatile organic compounds (VOCs) in breath samples were measured at days 0, 2, 7, 14, and 30 of TB therapy and correlated with clinical and microbiological measurements. RESULTS: Fifty one pulmonary TB cases and 20 healthy HIV-uninfected controls were enrolled in the study. 31 (61%) of the 51 pulmonary TB cases were coinfected with HIV. At day 0 (before TB treatment initiation) the sensitivity of our device was estimated at 94.1% (95% confidence interval [CI], 83.8-98.8%) and specificity was 90.0% (95% CI, 68.3-98.8%) for distinguishing TB cases from controls. Time-dependent changes in the breath signals were identified as time on TB treatment progressed. Time-dependent signal changes were more pronounced among HIV-uninfected patients. CONCLUSION: The identification of VOCs' signals in breath samples using a sensor array achieved high sensitivity and specificity for the diagnosis of TB and allowed following signal changes during TB treatment.

Identification of a Large Pool of Microorganisms with an Array of Porphyrin Based Gas Sensors.

The association between volatile compounds (VCs) and microorganisms, as demonstrated by several studies, may offer the ground for a rapid identification of pathogens. To this regard, chemical sensors are a key enabling technology for the exploitation of this opportunity. In this study, we investigated the performance of an array of porphyrin-coated quartz microbalance gas sensors in the identification of a panel of 12 bacteria and fungi. The porphyrins were metal complexes and the free base of a functionalized tetraphenylporphyrin. Our results show that the sensor array distinguishes the VC patterns produced by microorganisms in vitro. Besides being individually identified, bacteria are also sorted into Gram-positive and Gram-negative.