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Genome-based transmission modelling separates imported tuberculosis from recent transmission within an immigrant population.

ABSTRACT: In many countries the incidence of tuberculosis (TB) is low and is largely shaped by immigrant populations from high-burden countries. This is the case in Norway, where more than 80?% of TB cases are found among immigrants from high-incidence countries. A variable latent period, low rates of evolution and structured social networks make separating import from within-border transmission a major conundrum to TB control efforts in many low-incidence countries. Clinical Mycobacterium tuberculosis isolates belonging to an unusually large genotype cluster associated with people born in the Horn of Africa have been identified in Norway over the last two decades. We modelled transmission based on whole-genome sequence data to estimate infection times for individual patients. By contrasting these estimates with time of arrival in Norway, we estimate on a case-by-case basis whether patients were likely to have been infected before or after arrival. Independent import was responsible for the majority of cases, but we estimate that about one-quarter of the patients had contracted TB in Norway. This study illuminates the transmission dynamics within an immigrant community. Our approach is broadly applicable to many settings where TB control programmes can benefit from understanding when and where patients acquired TB.

SUBMITTER: Ayabina D

PROVIDER: S-EPMC6249437 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Genome-based transmission modelling separates imported tuberculosis from recent transmission within an immigrant population.

Ayabina Diepreye D Ronning Janne O JO Alfsnes Kristian K Debech Nadia N Brynildsrud Ola B OB Arnesen Trude T Norheim Gunnstein G Mengshoel Anne-Torunn AT Rykkvin Rikard R Dahle Ulf R UR Colijn Caroline C Eldholm Vegard V

Microbial genomics 20180914 10

In many countries the incidence of tuberculosis (TB) is low and is largely shaped by immigrant populations from high-burden countries. This is the case in Norway, where more than 80 % of TB cases are found among immigrants from high-incidence countries. A variable latent period, low rates of evolution and structured social networks make separating import from within-border transmission a major conundrum to TB control efforts in many low-incidence countries. Clinical Mycobacterium tuberculosis is ...[more]

PMID: 30216147

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Project description:BackgroundThe overall incidence of tuberculosis (TB) in Western Europe has been declining since the 19th Century. However, immigrant sub-groups from high-prevalence countries are slowing down this trend. The aim of this study was to describe how immigration influences TB transmission in Germany. For that we prospectively investigated the dynamics of TB transmission between TB high-prevalence immigrant and TB low-prevalence local populations with molecular epidemiological methods and conventional contact investigations. Besides, we assessed transmission in relation to social mixing using an innovative tool that measures the integration of immigrants into the local social environment.MethodsA prospective study of confirmed culture positive cases of pulmonary TB and their contacts was carried out in a German federal state from 2003 to 2005. Data for the study included: 1) case data routinely collected by the local public health staff and transmitted to the state health office and the national surveillance centre, 2) a study questionnaire designed to capture social interactions of relevance for TB transmission and 3) molecular genotyping data (IS6110 DNA fingerprint and spoligotyping). The proportion of German cases caused by foreign-born cases, and vice versa, was estimated and an integration index was computed using a selected set of questions from the study questionnaire.ResultsA total of 749 cases of culture-positive pulmonary tuberculosis voluntarily enrolled in the study, representing 57.8% of all registered cases diagnosed over the study period. Data that included study questionnaire and DNA fingerprinting were available for 41% (n = 308) of the study participants. Forty-seven clusters, defined as a least two cases infected by the same TB strains, were identified by molecular methods and included 132 (17%) of the study participants. Epidemiological links were identified for 28% of the clusters by conventional epidemiological data. In mixed clusters, defined as clusters including German and foreign-born individuals, the probability of cases to be caused by foreign-born cases was estimated at 18.3%. We observed a trend to mixed clusters with increasing time spent by immigrants in the host country. This group also presented comparatively higher integration indexes than immigrants in immigrant-only clusters.ConclusionOur results confirm the findings of other studies that there is no significant TB transmission from TB high-prevalence immigrant to TB low-prevalence autochthonous population. This may be explained by the good performance of tuberculosis screening programmes for certain groups arriving in Germany from high- prevalence countries, by a low degree of mixing of immigrants with the local population or by a combination of both.

Project description:The WHO recommended intervention of Directly Observed Treatment, Short-course (DOTS) appears to have been less successful than expected in reducing the burden of TB in some high prevalence settings. One strategy for enhancing DOTS is incorporating active case-finding through screening contacts of TB patients as widely used in low-prevalence settings. Predictive models that incorporate population-level effects on transmission provide one means of predicting impacts of such interventions. We aim to identify all TB transmission modelling studies addressing contact tracing and to describe and critically assess their modelling assumptions, parameter choices and relevance to policy. We searched MEDLINE, SCOPUS, COMPENDEX, Google Scholar and Web of Science databases for relevant English language publications up to February 2012. Of the 1285 studies identified, only 5 studies met our inclusion criteria of models of TB transmission dynamics in human populations designed to incorporate contact tracing as an intervention. Detailed implementation of contact processes was only present in two studies, while only one study presented a model for a high prevalence, developing world setting. Some use of relevant data for parameter estimation was made in each study however validation of the predicted impact of interventions was not attempted in any of the studies. Despite a large body of literature on TB transmission modelling, few published studies incorporate contact tracing. There is considerable scope for future analyses to make better use of data and to apply individual based models to facilitate more realistic patterns of infectious contact. Combined with a focus on high burden settings this would greatly increase the potential for models to inform the use of contract tracing as a TB control policy. Our findings highlight the potential for collaborative work between clinicians, epidemiologists and modellers to gather data required to enhance model development and validation and hence better inform future public health policy.

Project description:BACKGROUND:Whole genome sequencing provides better delineation of transmission clusters in Mycobacterium tuberculosis than traditional methods. However, its ability to reveal individual transmission links within clusters is limited. Here, we used a 2-step approach based on Bayesian transmission reconstruction to (1) identify likely index and missing cases, (2) determine risk factors associated with transmitters, and (3) estimate when transmission happened. METHODS AND FINDINGS:We developed our transmission reconstruction method using genomic and epidemiological data from a population-based study from Valencia Region, Spain. Tuberculosis (TB) incidence during the study period was 8.4 cases per 100,000 people. While the study is ongoing, the sampling frame for this work includes notified TB cases between 1 January 2014 and 31 December 2016. We identified a total of 21 transmission clusters that fulfilled the criteria for analysis. These contained a total of 117 individuals diagnosed with active TB (109 with epidemiological data). Demographic characteristics of the study population were as follows: 80/109 (73%) individuals were Spanish-born, 76/109 (70%) individuals were men, and the mean age was 42.51 years (SD 18.46). We found that 66/109 (61%) TB patients were sputum positive at diagnosis, and 10/109 (9%) were HIV positive. We used the data to reveal individual transmission links, and to identify index cases, missing cases, likely transmitters, and associated transmission risk factors. Our Bayesian inference approach suggests that at least 60% of index cases are likely misidentified by local public health. Our data also suggest that factors associated with likely transmitters are different to those of simply being in a transmission cluster, highlighting the importance of differentiating between these 2 phenomena. Our data suggest that type 2 diabetes mellitus is a risk factor associated with being a transmitter (odds ratio 0.19 [95% CI 0.02-1.10], p < 0.003). Finally, we used the most likely timing for transmission events to study when TB transmission occurred; we identified that 5/14 (35.7%) cases likely transmitted TB well before symptom onset, and these were largely sputum negative at diagnosis. Limited within-cluster diversity does not allow us to extrapolate our findings to the whole TB population in Valencia Region. CONCLUSIONS:In this study, we found that index cases are often misidentified, with downstream consequences for epidemiological investigations because likely transmitters can be missed. Our findings regarding inferred transmission timing suggest that TB transmission can occur before patient symptom onset, suggesting also that TB transmits during sub-clinical disease. This result has direct implications for diagnosing TB and reducing transmission. Overall, we show that a transition to individual-based genomic epidemiology will likely close some of the knowledge gaps in TB transmission and may redirect efforts towards cost-effective contact investigations for improved TB control.

Dataset Information

Genome-based transmission modelling separates imported tuberculosis from recent transmission within an immigrant population.

Publications

Genome-based transmission modelling separates imported tuberculosis from recent transmission within an immigrant population.

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