Population-Based Geospatial and Molecular Epidemiologic Study of Tuberculosis Transmission Dynamics, Botswana, 2012-2016

Genomic and Spatial Analysis on the Recent Transmission of Mycobacterium tuberculosis in Eastern China: A 10-Year Retrospective Population-Based Study

Purpose

Understanding the mode of Mycobacterium tuberculosis (M. tuberculosis) transmission is crucial for disease prevention and control. Compared to traditional genotyping methods, whole genome sequencing (WGS) provides higher resolution and comprehensive genetic information, enabling the tracing of infection sources and determining of transmission routes to resolve extensive tuberculosis (TB) outbreaks. We conducted a ten-year study on the transmission of M. tuberculosis in a population in eastern China.

Patients and Methods

We selected Lianyungang, an eastern city in China, as the study site. Patients diagnosed with active pulmonary TB from 2011 to 2020 were enrolled as the study subjects. We isolated and sequenced 2252 M. tuberculosis. Strains with pairwise genetic distances of less than 12 single nucleotide polymorphisms were defined as genomic clusters and which were considered recent transmissions. Kernel density estimation and K-function analysis were applied to explore the spatial distribution of recently transmitted strains.

Results

After excluding non-tuberculous mycobacteria and duplicated samples, 2114 strains were included in the final analysis. These strains comprised lineage 2 (1593, 75.35%) and 4 (521, 24.65%). There were 672 clustered strains, with a recent transmission rate of 31.79%. The logistic regression model showed that the risk of recent transmission was high in students [adjusted odds ratio (aOR): 2.68, 95% confidence interval (CI): 1.63-4.49, P<0.001] and people infected with L2.2.1 strains (aOR: 1.59, 95% CI: 1.20-2.12). Higher spatial aggregation of TB transmission has been concentrated in Haizhou, Donghai, and Guanyun for the past 10 years. Three outbreaks affecting 46 patients were spatially spaced, with 11 to 23 persons each. Different groups exhibited varying geographic distances between the initial and later cases.

Conclusion

There are areas with a high risk of transmission for M. tuberculosis in the research site, and the risk varies among different populations. Accurate prevention strategies targeted at specific regions and key populations can help curb the prevalence of TB.

Association of lineage 4.2.2 of Mycobacterium tuberculosis with the 63-bp deletion variant of the mpt64 gene

IMPORTANCE

To date, rapid diagnostic methods based on the MPT64 antigen assay are increasingly utilized to differentiate between non-tuberculous mycobacteria and TB disease in clinical settings. Furthermore, numerous novel techniques based on the MPT64 release assay are continuously being developed and applied for the identification of both pulmonary and extrapulmonary TB. However, the diagnostic accuracy of the MPT64 antigen assay is influenced by the presence of 63 bp deletion variants within the mpt64 gene. To our knowledge, this is the first report on the association between the 63 bp deletion variant in mpt64 and Mycobacterium tuberculosis L4.2.2 globally, which highlights the need for the cautious utilization of MPT64-based testing in regions where L4.2.2 isolates are prevalent, such as China and Vietnam, and MPT64 negative results should be confirmed with another assay. In addition, further studies on vaccine development and immunology based on MPT64 should consider these isolates with 63 bp deletion variant.

Tuberculosis Variant with Rifampin Resistance Undetectable by Xpert MTB/RIF, Botswana

GeneXpert MTB/RIF, a tool widely used for diagnosing tuberculosis, has limitations for detecting rifampin resistance in certain variants. We report transmission of a pre-extensively drug-resistant variant in Botswana that went undetected by GeneXpert. The public health impact of misdiagnosis emphasizes the need for comprehensive molecular testing to identify resistance and guide treatment.

Recent progress in the genotyping of bovine tuberculosis and its rapid diagnosis via nanoparticle-based electrochemical biosensors

Bovine tuberculosis (bTB) is considered a worldwide infectious zoonotic disease. Mycobacterium bovis causes bTB disease. It is one of the Mycobacterium tuberculosis complex (MTBC) members. MTBC is a clonal complex of close relatives with approximately 99.95% similarity. M. bovis is a spillover pathogen that can transmit from animals to humans and rarely from humans to animals with contact. Genotyping techniques are important to discriminate and differentiate between MTBC species. Spoligotyping and mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) are widely used but they have some limitations. As an alternative, whole genome sequencing approaches have been utilized due to their high-resolution power. They are employed in typing M. bovis and explain the evolutionary and phylogenetic relationships between isolates. The control of bTB disease has attracted a large amount of attention. Rapid and proper diagnosis is necessary for monitoring the disease as an initial step for its control and treatment. Nanotechnology has a potential impact on the rapid diagnosis and treatment of bTB through the use of nanocarrier and metal nanoparticles (NPs). Special attention has been paid to voltammetric and impedimetric electrochemical strategies as facile, sensitive, and selective methods for the efficient detection of tuberculosis. The efficacy of these sensors is enhanced in the presence of NPs, which act as recognition and/or redox probes. Gold, silver, copper, cobalt, graphene, and magnetic NPs, as well as polypyrrole nanowires and multiwalled carbon nanotubes have been employed for detecting tuberculosis. Overall, NP-based electrochemical sensors represent a promising tool for the diagnosis of bTB.

Use of High-Resolution Geospatial and Genomic Data to Characterize Recent Tuberculosis Transmission, Botswana

Combining genomic and geospatial data can be useful for understanding Mycobacterium tuberculosis transmission in high-burden tuberculosis (TB) settings. We performed whole-genome sequencing on M. tuberculosis DNA extracted from sputum cultures from a population-based TB study conducted in Gaborone, Botswana, during 2012-2016. We determined spatial distribution of cases on the basis of shared genotypes among isolates. We considered clusters of isolates with ≤5 single-nucleotide polymorphisms identified by whole-genome sequencing to indicate recent transmission and clusters of ≥10 persons to be outbreaks. We obtained both molecular and geospatial data for 946/1,449 (65%) participants with culture-confirmed TB; 62 persons belonged to 5 outbreaks of 10-19 persons each. We detected geospatial clustering in just 2 of those 5 outbreaks, suggesting heterogeneous spatial patterns. Our findings indicate that targeted interventions applied in smaller geographic areas of high-burden TB identified using integrated genomic and geospatial data might help interrupt TB transmission during outbreaks.

Depression, Anxiety, and Cigarette Smoking Among Patients with Tuberculosis

Smoking adversely affects tuberculosis (TB) outcomes and may be associated with depression and anxiety among people diagnosed with TB in Botswana. We conducted a cross-sectional study among patients newly diagnosed with TB in Gaborone, Botswana, evaluating factors associated with self-reported cigarette smoking. We performed Poisson regression analyses with robust variance to examine whether depressive and anxiety symptoms were associated with smoking. Among 180 participants with TB enrolled from primary health clinics, depressive symptoms were reported in 47 (26.1%) participants and anxiety symptoms were reported in 85 (47.2%) participants. Overall, 45 (25.0%) participants reported current smoking. Depressive symptoms were associated with a higher prevalence of smoking (adjusted prevalence ratio [aPR]: 2.04; 95% confidence interval [CI]: 1.29-3.25) in the adjusted analysis. The association between anxiety symptoms and smoking did not reach statistical significance (aPR: 1.26; 95% CI: 0.77-2.05). Future studies should further investigate these associations when addressing TB care.

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.

Characterizing tuberculosis transmission dynamics in high-burden urban and rural settings

Mycobacterium tuberculosis transmission dynamics in high-burden settings are poorly understood. Growing evidence suggests transmission may be characterized by extensive individual heterogeneity in secondary cases (i.e., superspreading), yet the degree and influence of such heterogeneity is largely unknown and unmeasured in high burden-settings. We conducted a prospective, population-based molecular epidemiology study of TB transmission in both an urban and rural setting of Botswana, one of the highest TB burden countries in the world. We used these empirical data to fit two mathematical models (urban and rural) that jointly quantified both the effective reproductive number, [Formula: see text], and the propensity for superspreading in each population. We found both urban and rural populations were characterized by a high degree of individual heterogeneity, however such heterogeneity disproportionately impacted the rural population: 99% of secondary transmission was attributed to only 19% of infectious cases in the rural population compared to 60% in the urban population and the median number of incident cases until the first outbreak of 30 cases was only 32 for the rural model compared to 791 in the urban model. These findings suggest individual heterogeneity plays a critical role shaping local TB epidemiology within subpopulations.

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.

Know your tuberculosis epidemic-Is it time to add Mycobacterium tuberculosis immunoreactivity back into global surveillance?

Tuberculosis (TB) still causes 1.5 million deaths globally each year. Over recent decades, slow and uneven declines in TB incidence have resulted in a falling prevalence of TB disease, which increasingly concentrates in vulnerable populations. Falling prevalence, while welcome, poses new challenges for TB surveillance. Cross-sectional disease surveys require very large sample sizes to accurately estimate disease burden, and even more participants to detect trends over time or identify high-risk areas or populations, making them prohibitively resource-intensive. In the past, tuberculin skin surveys measuring Mycobacterium tuberculosis (Mtb) immunoreactivity were widely used to monitor TB epidemiology in high-incidence settings, but were limited by challenges with both delivering and interpreting the test. Here we argue that the shifting epidemiology of tuberculosis, and the development of new tests for Mtb infection, make it timely and important to revisit the strategy of TB surveillance based on infection or immunoreactivity. Mtb infection surveys carry their own operational challenges and fundamental questions, for example: around survey design and frequency; which groups should be included; how the prevalence of immunoreactivity in a population should be used to estimate force of infection; how individual results should be interpreted and managed; and how surveillance can be delivered efficiently and ethically. However, if these knowledge gaps are addressed, the relative feasibility and lower costs of Mtb infection surveillance offer a powerful and affordable opportunity to better "know your TB epidemic", understand trends, identify high-risk and underserved communities, and tailor public health responses to dynamic epidemiology.

The Relevance of Genomic Epidemiology for Control of Tuberculosis in West Africa

Tuberculosis (TB), an airborne infectious disease caused by Mycobacterium tuberculosis complex (MTBC), remains a global health problem. West Africa has a unique epidemiology of TB that is characterized by medium- to high-prevalence. Moreover, the geographical restriction of M. africanum to the sub-region makes West Africa have an extra burden to deal with a two-in-one pathogen. The region is also burdened with low case detection, late reporting, poor treatment adherence leading to development of drug resistance and relapse. Sporadic studies conducted within the subregion report higher burden of drug resistant TB (DRTB) than previously thought. The need for more sensitive and robust tools for routine surveillance as well as to understand the mechanisms of DRTB and transmission dynamics for the design of effective control tools, cannot be overemphasized. The advancement in molecular biology tools including traditional fingerprinting and next generation sequencing (NGS) technologies offer reliable tools for genomic epidemiology. Genomic epidemiology provides in-depth insight of the nature of pathogens, circulating strains and their spread as well as prompt detection of the emergence of new strains. It also offers the opportunity to monitor treatment and evaluate interventions. Furthermore, genomic epidemiology can be used to understand potential emergence and spread of drug resistant strains and resistance mechanisms allowing the design of simple but rapid tools. In this review, we will describe the local epidemiology of MTBC, highlight past and current investigations toward understanding their biology and spread as well as discuss the relevance of genomic epidemiology studies to TB control in West Africa.