Genotyping of <Emphasis Type="Italic">Mycobacterium tuberculosis</Emphasis> using whole genome sequencing

Tuberculosis (TB) is considered one of the most serious infectious diseases worldwide. Effective control of tuberculosis infection involves multiple steps, such as reliable detection, treatment, an epidemiological control as a part of case management, and further surveillance and monitoring of TB spread in the human population. Due to the accelerating advances in molecular biology, especially in DNA sequencing, in the past decade, the application of these methods has become crucial for TB evolution studies, differentiation of Mycobacterium tuberculosis genotypes, and their distribution. Currently, several molecular genetic methods are available. The oldest typing methods (e.g., IS6110-RFLP, spoligotyping, and MIRU-VNTR) can discover the chain of transmission to the patient. Currently, whole genome sequencing facilitates is furthermore able to identify the source of infection, the transmission trays among individuals sharing the same isolate, as well as determination of the TB evolution and its resistance to antituberculotic agents. It is obvious that this technique will become a new gold standard in genotyping methods in tuberculosis molecular epidemiological studies. In this article, molecular genetic typing methods with a special focus on whole genome sequencing and data management are reviewed.     

Transmission and dynamics of tuberculosis on generalized households

Tuberculosis (TB) transmission is enhanced by systematic exposure to an infectious individual. This enhancement usually takes place at either the home, workplace, and/or school (generalized household). Typical epidemiological models do not incorporate the impact of generalized households on the study of disease dynamics. Models that incorporate cluster (generalized household) effects and focus on their impact on TB's transmission dynamics are developed. Detailed models that consider the effect of casual infections, that is, those generated outside a cluster, are also presented. We find expressions for the Basic Reproductive Number as a function of cluster size. The formula for R0 separates the contributions of cluster and casual infections in the generation of secondary TB infections. Relationships between cluster and classical epidemic models are discussed as well as the concept of critical cluster size.     

Non-linear transmission and simple models for bovine tuberculosis

1.  A new model is presented for a possum–tuberculosis (TB) system ( Trichosurus vulpecula – Mycobacterium bovis ) that is both realistic and parsimonious. The model includes a phenomenological treatment of heterogeneity of risk for susceptible hosts, similar to that used in insect host–parasitoid systems.
2.  Parameter values for the model reflect current knowledge and differ significantly from those in other recent models of this system. Associated with these structural and parametric changes are substantially different predictions for the dynamics and control of TB in possums.
3.  The model predictions include (i) only limited host suppression due to the disease (< 10%, cf. several earlier simple models for TB in both possums and badgers); (ii) asymptotically stable disease dynamics (cf. homogeneous-mixing models that predict either extremely weak stability such that disease fails to recover when host density is temporarily reduced, or oscillatory behaviour and potential elimination of disease following such a perturbation); (iii) TB that is harder to control than in the homogeneous-mixing model equivalents, in line with practical experience; and (iv) a threshold host density for disease elimination that differs substantially from the host equilibrium density in the presence of disease.
4.  Homogeneous-mixing models are unable to reproduce this behaviour, whatever parameter values are chosen. Heterogeneous-mixing models with non-linear transmission may therefore be worth consideration in other endemic wildlife disease systems, as is now commonplace for insect–parasitoid and insect–pathogen ones.     

Modeling the impact of early therapy for latent tuberculosis patients and its optimal control analysis

Effective tuberculosis (TB) control depends on case findings to discover infectious cases, investigation of contacts of those with TB, as well as appropriate treatment. Adherence and successful completion of the treatment are equally important. Unfortunately, due to a number of personal, psychosocial, economic, medical, and health service factors, a significant number of TB patients become irregular and default from treatment. In this paper, a mathematical model is developed to assess the impact of early therapy for latent TB and non-adherence on controlling TB transmission dynamics. Equilibrium states of the model are determined and their local stability is examined. With the aid of the center manifold theory, it is established that the model undergoes a backward bifurcation. Qualitative mathematical analysis of the model suggests that a high level of latent tuberculosis case findings, coupled with a decrease of defaulting rate, may be effective in controlling TB transmission dynamics in the community. Population-level effects of organized campaigns to improve early therapy and to guarantee successful completion of each treatment are evaluated through numerical simulations and presented in support of the analytical results.     

Optimal Tuberculosis Prevention and Control Strategy from a Mathematical Model Based on Real Data

A mathematical control model for the transmission dynamics of tuberculosis (TB) in South Korea is developed on the basis of the reported active-TB and relapse-TB incidence data. In this work, optimal control theory is used to propose optimal TB prevention and control strategy and rearrange the government TB budget for the best TB elimination plan. The impact of distancing, case finding, and/or case holding controls are investigated when the number of infected and infectious individuals are minimized, while the intervention costs are kept low. The implementation of optimal control measures shows that the distancing control, such as isolation of infectious people, early TB patient detection, and educational program/campaign for healthy control, is the most effective control factor for the prevention of TB transmission in South Korea.     

Comparing epidemic tuberculosis in demographically distinct heterogeneous populations

There is wide variation in endemic tuberculosis (TB) levels between countries and we seek to identify possible causes of these differences. In this study we present an epidemiological model of Mycobacterium tuberculosis infection to investigate the effects of host genetics and demographic factors on epidemic TB. We discuss the general framework for this approach and present analytical results to identify important parameters affecting steady-state prevalence and incidence rates of TB disease. We then use numerical simulations of our model to observe the effects of a genetically susceptible subpopulation on TB disease dynamics at the population level. Finally, we simulate infection within a genetically heterogeneous population in two demographic settings: India (a typical population with high TB prevalence) and the USA (a typical population with low TB prevalence). Results show that changes in transmission parameters, the fraction of the population genetically susceptible to infection, and demographic factors strongly affect TB prevalence and incidence rates.     

Modeling of Novel Diagnostic Strategies for Active Tuberculosis – A Systematic Review: Current Practices and Recommendations

Introduction

The field of diagnostics for active tuberculosis (TB) is rapidly developing. TB diagnostic modeling can help to inform policy makers and support complicated decisions on diagnostic strategy, with important budgetary implications. Demand for TB diagnostic modeling is likely to increase, and an evaluation of current practice is important. We aimed to systematically review all studies employing mathematical modeling to evaluate cost-effectiveness or epidemiological impact of novel diagnostic strategies for active TB.

Methods

Pubmed, personal libraries and reference lists were searched to identify eligible papers. We extracted data on a wide variety of model structure, parameter choices, sensitivity analyses and study conclusions, which were discussed during a meeting of content experts.

Results & Discussion

From 5619 records a total of 36 papers were included in the analysis. Sixteen papers included population impact/transmission modeling, 5 were health systems models, and 24 included estimates of cost-effectiveness. Transmission and health systems models included specific structure to explore the importance of the diagnostic pathway (n = 4), key determinants of diagnostic delay (n = 5), operational context (n = 5), and the pre-diagnostic infectious period (n = 1). The majority of models implemented sensitivity analysis, although only 18 studies described multi-way sensitivity analysis of more than 2 parameters simultaneously. Among the models used to make cost-effectiveness estimates, most frequent diagnostic assays studied included Xpert MTB/RIF (n = 7), and alternative nucleic acid amplification tests (NAATs) (n = 4). Most (n = 16) of the cost-effectiveness models compared new assays to an existing baseline and generated an incremental cost-effectiveness ratio (ICER).

Conclusion

Although models have addressed a small number of important issues, many decisions regarding implementation of TB diagnostics are being made without the full benefits of insight from mathematical models. Further models are needed that address a wider array of diagnostic and epidemiological settings, that explore the inherent uncertainty of models and that include additional epidemiological data on transmission implications of false-negative diagnosis and the pre-diagnostic period.     

The infectiousness of tuberculosis patients coinfected with HIV

Background

The current understanding of airborne tuberculosis (TB) transmission is based on classic 1950s studies in which guinea pigs were exposed to air from a tuberculosis ward. Recently we recreated this model in Lima, Perú, and in this paper we report the use of molecular fingerprinting to investigate patient infectiousness in the current era of HIV infection and multidrug-resistant (MDR) TB.

Methods and Findings

All air from a mechanically ventilated negative-pressure HIV-TB ward was exhausted over guinea pigs housed in an airborne transmission study facility on the roof. Animals had monthly tuberculin skin tests, and positive reactors were removed for autopsy and organ culture for M. tuberculosis. Temporal exposure patterns, drug susceptibility testing, and DNA fingerprinting of patient and animal TB strains defined infectious TB patients. Relative patient infectiousness was calculated using the Wells-Riley model of airborne infection. Over 505 study days there were 118 ward admissions of 97 HIV-positive pulmonary TB patients. Of 292 exposed guinea pigs, 144 had evidence of TB disease; a further 30 were tuberculin skin test positive only. There was marked variability in patient infectiousness; only 8.5% of 118 ward admissions by TB patients were shown by DNA fingerprinting to have caused 98% of the 125 characterised cases of secondary animal TB. 90% of TB transmission occurred from inadequately treated MDR TB patients. Three highly infectious MDR TB patients produced 226, 52, and 40 airborne infectious units (quanta) per hour.

Conclusions

A small number of inadequately treated MDR TB patients coinfected with HIV were responsible for almost all TB transmission, and some patients were highly infectious. This result highlights the importance of rapid TB drug-susceptibility testing to allow prompt initiation of effective treatment, and environmental control measures to reduce ongoing TB transmission in crowded health care settings. TB infection control must be prioritized in order to prevent health care facilities from disseminating the drug-resistant TB that they are attempting to treat.     

Unmanned Aircraft Systems for Studying Spatial Abundance of Ungulates: Relevance to Spatial Epidemiology

Complex ecological and epidemiological systems require multidisciplinary and innovative research. Low cost unmanned aircraft systems (UAS) can provide information on the spatial pattern of hosts’ distribution and abundance, which is crucial as regards modelling the determinants of disease transmission and persistence on a fine spatial scale. In this context we have studied the spatial epidemiology of tuberculosis (TB) in the ungulate community of Doñana National Park (South-western Spain) by modelling species host (red deer, fallow deer and cattle) abundance at fine spatial scale. The use of UAS high-resolution images has allowed us to collect data to model the environmental determinants of host abundance, and in a further step to evaluate their relationships with the spatial risk of TB throughout the ungulate community. We discuss the ecological, epidemiological and logistic conditions under which UAS may contribute to study the wildlife/livestock sanitary interface, where the spatial aggregation of hosts becomes crucial. These findings are relevant for planning and implementing research, fundamentally when managing disease in multi-host systems, and focusing on risky areas. Therefore, managers should prioritize the implementation of control strategies to reduce disease of conservation, economic and social relevance.     

Projection of tuberculosis incidence with increasing immigration trends

Tuberculosis (TB) incidence rates vary substantially from regions to regions and from countries to countries. In countries such as Canada where TB incidence rate is low, increasing immigration trends may have significant impact on the TB transmission patterns in these countries. In this study we formulate a deterministic epidemiological model of TB transmission in two demographically distinct populations: Canadian born and foreign born populations, in order to investigate the effects of this demographic distinction on the short-term incidence and long-term transmission dynamics, and with special emphasis on the impact of immigration latent TB cases on the overall TB incidence rate in the whole population.     

Survival of mycobacterial species in aerosols generated from artificial saliva

Tuberculosis is transmitted primarily by the aerosol route and the aim of this study was to measure the ability of pathogenic mycobacteria to survive in aerosols generated from artificial saliva. Aerosols of Mycobacterium avium, Mycobacterium intracellulare and Mycobacterium tuberculosis were generated and maintained in air under controlled conditions using a Henderson apparatus and a rotating drum. There were no differences in aerosol survival between the three species, and all had a poor survival rate over a period of 1 h. These data confirm epidemiological studies that close and prolonged contact with a TB patient is required for transmission of infection.     

Molecular epidemiology of drug-resistant tuberculosis in Sweden

Drug-resistant tuberculosis (TB), including the more severe forms of multidrug- and extensively drug-resistant forms, is an increasing public health concern globally. In Sweden the majority of patients with TB are immigrants from countries with a high incidence of TB including the drug-resistant forms. In this study, the spread of resistant TB in Sweden was investigated by molecular fingerprinting. Isolates resistant to at least one of the drugs, isoniazid, rifampicin, ethambutol or streptomycin, from 400 patients collected between 1994 and 2005, were studied by restriction fragment length polymorphism (RFLP) and by spoligotyping. Thirty-five clusters of patients infected with strains with identical RFLP and spoligotyping patterns (2-96 patients per cluster), comprising a total of 203 patients, were found. One large outbreak of isoniazid resistant tuberculosis was identified, involving 96 patients, mainly from the Horn of Africa. To identify chains of transmission, molecular epidemiological characterization of TB isolates should, if possible, be performed on isolates from all new TB patients.     

How host heterogeneity governs tuberculosis reinfection?

Recurrent episodes of tuberculosis (TB) can be due to relapse of latent infection or exogenous reinfection, and discrimination is crucial for control planning. Molecular genotyping of Mycobacterium tuberculosis isolates offers concrete opportunities to measure the relative contribution of reinfection in recurrent disease. Here, a mathematical model of TB transmission is fitted to data from 14 molecular epidemiology studies, enabling the estimation of relevant epidemiological parameters. Meta-analysis reveals that rates of reinfection after successful treatment are higher than rates of new TB, raising an important question about the underlying mechanism. We formulate two alternative mechanisms within our model framework: (i) infection increases susceptibility to reinfection or (ii) infection affects individuals differentially, thereby recruiting high-risk individuals to the group at risk for reinfection. The second mechanism is better supported by the fittings to the data, suggesting that reinfection rates are inflated through a population phenomenon that occurs in the presence of heterogeneity in individual risk of infection. As a result, rates of reinfection are higher when measured at the population level even though they might be lower at the individual level. Finally, differential host recruitment is modulated by transmission intensity, being less pronounced when incidence is high.     

Drug resistance in tuberculosis--a reinfection model

There is increasing recognition that reinfection is an important component of TB transmission. Moreover, it has been shown that partial immunity has significant epidemiological consequences, particularly in what concerns disease prevalence and effectiveness of control measures. We address the problem of drug resistance as a competition between two types of strains of Mycobacterium tuberculosis: those that are sensitive to anti-tuberculosis drugs and those that are resistant. Our objective is to characterise the role of reinfection in the transmission of drug-resistant tuberculosis. The long-term behaviour of our model reflects how reinfection modifies the conditions for coexistence of sensitive and resistant strains. This sets the scene for discussing how strain prevalence is affected by different control strategies. It is shown that intervention effectiveness is highly sensitive to the baseline epidemiological setting.     

Tuberculosis models with fast and slow dynamics: the role of close and casual contacts

Models that incorporate local and individual interactions are introduced in the context of the transmission dynamics of tuberculosis (TB). The multi-level contact structure implicitly assumes that individuals are at risk of infection from close contacts in generalized household (clusters) as well as from casual (random) contacts in the general population. Epidemiological time scales are used to reduce the dimensionality of the model and singular perturbation methods are used to corroborate the results of time-scale approximations. The concept and impact of optimal average cluster or generalized household size on TB dynamics is discussed. We also discuss the potential impact of our results on the spread of TB.     

A Novel Tool Improves Existing Estimates of Recent Tuberculosis Transmission in Settings of Sparse Data Collection

In any setting, a proportion of incident active tuberculosis (TB) reflects recent transmission (“recent transmission proportion”), whereas the remainder represents reactivation. Appropriately estimating the recent transmission proportion has important implications for local TB control, but existing approaches have known biases, especially where data are incomplete. We constructed a stochastic individual-based model of a TB epidemic and designed a set of simulations (derivation set) to develop two regression-based tools for estimating the recent transmission proportion from five inputs: underlying TB incidence, sampling coverage, study duration, clustered proportion of observed cases, and proportion of observed clusters in the sample. We tested these tools on a set of unrelated simulations (validation set), and compared their performance against that of the traditional ‘n-1’ approach. In the validation set, the regression tools reduced the absolute estimation bias (difference between estimated and true recent transmission proportion) in the ‘n-1’ technique by a median [interquartile range] of 60% [9%, 82%] and 69% [30%, 87%]. The bias in the ‘n-1’ model was highly sensitive to underlying levels of study coverage and duration, and substantially underestimated the recent transmission proportion in settings of incomplete data coverage. By contrast, the regression models’ performance was more consistent across different epidemiological settings and study characteristics. We provide one of these regression models as a user-friendly, web-based tool. Novel tools can improve our ability to estimate the recent TB transmission proportion from data that are observable (or estimable) by public health practitioners with limited available molecular data.     

Marked Microevolution of a Unique Mycobacterium tuberculosis Strain in 17 Years of Ongoing Transmission in a High Risk Population

The transmission and persistence of Mycobacterium tuberculosis within high risk populations is a threat to tuberculosis (TB) control. In the current study, we used whole genome sequencing (WGS) to decipher the transmission dynamics and microevolution of M. tuberculosis ON-A, an endemic strain responsible for an ongoing outbreak of TB in an urban homeless/under-housed population. Sixty-one M. tuberculosis isolates representing 57 TB cases from 1997 to 2013 were subjected to WGS. Sequencing data was integrated with available epidemiological information and analyzed to determine how the M. tuberculosis ON-A strain has evolved during almost two decades of active transmission. WGS offers higher discriminatory power than traditional genotyping techniques, dividing the M. tuberculosis ON-A strain into 6 sub-clusters, each defined by unique single nucleotide polymorphism profiles. One sub-cluster, designated ON-A^NM (Natural Mutant; 26 isolates from 24 cases) was also defined by a large, 15 kb genomic deletion. WGS analysis reveals the existence of multiple transmission chains within the same population/setting. Our results help validate the utility of WGS as a powerful tool for identifying genomic changes and adaptation of M. tuberculosis.     

Typing of Mycobacterium tuberculosis strains isolated in Community Health Centers of Rio de Janeiro City, Brazil

Fingerprinting of Mycobacterium tuberculosis strains from tuberculosis (TB) patients attended in Community Health Centers (CHCs) of Rio de Janeiro was performed to verify possible risk factors for TB transmission. A prospective community-based study was performed during the period of July 1996 to December 1996 by collecting sputum samples of 489 patients in 11 different CHCs in four different planning areas (APs) of the city. Bacteriological, clinical, and epidemiological information was collected and M. tuberculosis genotypes defined after restriction fragment length polymorphism (IS6110-RFLP) and double repetitive element (DRE) fingerprinting of RFLP-clustered cases. Risk factors for TB transmission were looked for using three levels of cluster stringency. Among 349 (71%) positive cultures obtained, IS6110-RFLP typing could be performed on strains from 153 different patients. When using identity of RFLP patterns as cluster definition, 49 (32%) of the strains belonged to a cluster and none of the clinical or epidemiologic characteristics was associated with higher clustering levels. However, higher clustering level was observed in the AP including the central region of the city when compared to others. This strongly suggests that more recent transmission occurs in that area and this may be related with higher incidence of TB and HIV in this region.     

Occupational risk of tuberculosis transmission in a low incidence area

Background

To investigate the occupational risk of tuberculosis (TB) infection in a low-incidence setting, data from a prospective study of patients with culture-confirmed TB conducted in Hamburg, Germany, from 1997 to 2002 were evaluated.

Methods

M. tuberculosis isolates were genotyped by IS6110 RFLP analysis. Results of contact tracing and additional patient interviews were used for further epidemiological analyses.

Results

Out of 848 cases included in the cluster analysis, 286 (33.7%) were classified into 76 clusters comprising 2 to 39 patients. In total, two patients in the non-cluster and eight patients in the cluster group were health-care workers. Logistic regression analysis confirmed work in the health-care sector as the strongest predictor for clustering (OR 17.9). However, only two of the eight transmission links among the eight clusters involving health-care workers had been detected previously. Overall, conventional contact tracing performed before genotyping had identified only 26 (25.2%) of the 103 contact persons with the disease among the clustered cases whose transmission links were epidemiologically verified.

Conclusion

Recent transmission was found to be strongly associated with health-care work in a setting with low incidence of TB. Conventional contact tracing alone was shown to be insufficient to discover recent transmission chains. The data presented also indicate the need for establishing improved TB control strategies in health-care settings.