Tuberculosis Cluster Research Articles

Transmission of tuberculosis and predictors of large clusters within three years in an urban setting in Tokyo, Japan: a population-based molecular epidemiological study

ObjectiveMolecular epidemiology is a promising tool for understanding tuberculosis transmission dynamics but has not been sufficiently utilised in Asian countries including Japan. The aim of this study was to estimate...

Sociodemographic profiling of tuberculosis hotspots in Ethiopia, 2014-2017.

Tuberculosis (TB) notification rates vary across regions in Ethiopia and districts within the Amhara Region. The Amhara Region is one of the main TB hotspot regions in the country. In this study we identified the spatial distribution of TB and characterized the sociodemographic factors of spatial clusters in the Amhara Region. An ecological spatial analysis of TB notifications from 2014 to 2017 was conducted to quantify the presence and location of spatial clusters of TB notifications at the district level within the Amhara Region. Global Moran's I statistics and local indicators of spatial association were used to explore the spatial clustering of TB notifications. Notifications from hotspots and low-risk districts were compared to identify significant sociodemographic factors using analysis of variance and Classification and Regression Tree analysis. The geographic information system and 'sp' packages of R software were used for spatial analysis. From 2014 to 2017 the average notification rate of all forms of TB in the Amhara Region was 107/100 000 population (range 18-614 per 100 000 population). District-level TB notification rates were positively spatially autocorrelated, with Moran's I value ranging from 0.207 to 0.276 (p=0.01). Hotspot TB clusters were found in the northwest and central part of the region. The proportion of migrants (F(3,124)=23.21, p<0.001, d=1.4) was found to be the most important factor associated with hotspot TB clustering. TB notification rates in the Amhara Region of Ethiopia over the past 4 y were significantly clustered. Distinguishing high-risk areas from low-risk areas and characterizing the proportion of migrants and other risk factors is important for targeted TB prevention and control in the region.

Detecting tuberculosis clusters in urban neighborhoods, Taipei, Taiwan: Linking geographic and genotyping evidence

Tuberculosis (TB) clusters, defined as two or more active TB cases with epidemiological links and the same genotype of Mycobacterium tuberculosis strains, are direct evidence of recent TB transmission. We analyzed TB cases newly diagnosed in 2006–2008, confirmed by the diagnostic laboratory, at a university-affiliated hospital in Taipei metropolitan area where TB is endemic in elderly populations. Numbers of randomly selected non-TB patients (as controls) from each district were proportional to the district population (Pearson's correlation coefficient = 0.8), which supports that patients who visited the hospital represent a spatially independent sample of total population in this area. We used the nearest neighbor hierarchical (NNH) clustering method and the spatial scan statistics to identify spatial TB clusters among 969 cases within the 10-km buffer, adjusting for the elderly population. One cluster with 10 TB cases from different households in geographic proximity to each other was detected by both NNH clustering and spatial scan statistics. Spoligotyping and mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) genotyping showed that four of the six M. tuberculosis strains from this spatial cluster were identical. Three of those four patients were older than 70 years, but none were nursing home residents. The identical genotypes of M. tuberculosis strains in clustered elderly TB patients living in neighborhoods indicate that recent transmission plays a significant role in TB endemicity among elderly populations in Taiwan.

The role of entry-screening procedures in the identification of multidrug-resistant Mycobacterium tuberculosis cluster cases amongst patients arriving in Europe from the horn of Africa, 2016-17

The role of entry-screening procedures in the identification of multidrug-resistant Mycobacterium tuberculosis cluster cases amongst patients arriving in Europe from the horn of Africa, 2016-17

Public health outcome of Tuberculosis Cluster Investigations, England 2010–2013

ObjectivesTuberculosis (TB) is a serious re-emergent public health problem in the UK. In response to rising case incidence a National TB Strain-Typing Service based on molecular strain-typing was established. This facilitates early detection and investigation of clusters, targeted public health action, and prevention of further transmission. We review the added public health value of investigating molecular TB strain-typed (ST) clusters. MethodsA structured questionnaire for each ST cluster investigated in England between 1 January 2010 and 30 June 2013 was completed. Questions related to epidemiological links and public health action and the perceived benefits of ST cluster investigation. ResultsThere were 278 ST cluster investigations (CIs) involving 1882 TB cases. Cluster size ranged from 2 to 92. CIs identified new epidemiological links in 36% of clusters; in 18% STs were discordant refuting transmission thought to have occurred. Additional public health action was taken following 23% of CI. ConclusionsWe found positive benefits of TB molecular ST and CI, in identifying new epidemiological links between cases and taking public health action and in refuting transmission and saving resources. This needs to be translated to a decrease in transmission to provide evidence of public health value in this low prevalence high resource setting.

The bovine tuberculosis cluster in north County Sligo during 2014\u201316

BackgroundBovine tuberculosis (bTB, caused by infection with Mycobacterium bovis) is endemic in the Irish cattle population, and the subject of a national eradication programme since the late 1950s. During 2014, a substantial area-level bTB outbreak developing in north County Sligo, necessitating the need for an enhanced response. This paper describes this outbreak, the response that was undertaken and some lessons learned.ResultsIn the north Sligo area between 2014 and 2016, 23 (31.9%) of restricted herds had 4 or more reactors to the single intradermal comparative tuberculin test (SICTT)/animals with bTB lesions disclosed during the restriction, and the majority (55.5%) of test-positive animals were identified as standard reactors to the SICTT. The herds restricted during 2014–16 were typically larger than other herds in the study area and introduced more animals during 2013. M. bovis was also detected in local badgers, but not deer.ConclusionThis paper describes a substantial outbreak in north County Sligo over a 3-year period. A coordinated area-based approach was a key feature of the outbreak, and substantial resources were applied to bring the outbreak under control. No definitive source was identified, nor reasons why a substantial number of herds were infected over a relatively short period. A coordinated regional approach was taken, and a number of lessons were learned including the need for urgency, for a team-based approach, for a consistent message when dealing with the public, for an area-based approach, for a degree of flexibility for the breakdown manager, and for molecular tools to assist in answering key questions relating to the source and spread of M. bovis to many herds during this bTB outbreak.

Creating a web-based electronic tool to aid tuberculosis (TB) cluster investigation: data integration in TB surveillance activities in the United Kingdom, 2013 to 2016.

Molecular technology to identify relatedness between Mycobacterium tuberculosis complex isolates, representative of possible tuberculosis (TB) transmission between individuals, continues to evolve. At the same time, tools to utilise this information for public health action to improve TB control should also be implemented. Public Health England developed the Strain Typing Module (STM) as an integral part of the web-based surveillance system used in the United Kingdom following the roll-out of prospective 24 loci mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) strain typing. The creation of such a system required data integration and linkage, bringing together laboratory results and patient notification information. The STM facilitated widespread access to patient strain typing and clustering results for the public health community working in TB control. In addition, the system provided a log of cluster review and investigation decision making and results. Automated real-time data linkage between laboratory and notification data are essential to allow routine use of genotyping results in TB surveillance and control. Outputs must be accessible by those working in TB control at a local level to have any impact in ongoing public health activity.

Epidemiological characteristics and spatial-temporal clustering analysis on pulmonary tuberculosis in Changsha from 2013 to 2016

To analyze the epidemic characteristics and to explore the spatial-temporal clusters of pulmonary tuberculosis (PTB) in Changsha from 2013 to 2016. Methods: Descriptive analysis and space-time permutation scan statistic were used to analyze the reported PTB cases in Changsha from 2013 to 2016. Results: Between 2013 and 2016, a total of 17 721 PTB cases were reported in Changsha, with annual reported incidence rate at 60.87 per 100 000 population. Males and individuals aged 15 to <60 years accounted for higher proportion of PTB cases compared to females and other age groups. The number of reported PTB cases reached peak from March to May in each year. The space-time permutation scan statistic identified one most likely cluster and two secondary clusters of PTB cases. The most likely cluster covered most areas of Liuyang City and the North-east part of Changsha County from October 1, 2013 to February 28, 2014. The first cluster occupied 12 towns (streets) in Kaifu District and Changsha County in December 2016. The second cluster included four towns (streets) in Yuhua District and Tianxin District from March 1 to September 30, in 2013. Conclusion: Between 2013 and 2016, significant space-time clusters of PTB cases were identified in Changsha. These findings could provide a guide for development of regional intervention strategies for PTB control.

A genotypic and spatial epidemiologic analysis of Massachusetts' Mycobacterium tuberculosis cases from 2012 to 2015

BackgroundMassachusetts had a rate of 2.8 cases of tuberculosis (TB) per 100,000 individuals in 2015. Although TB in Massachusetts is on the decline, the case rate remains far above the 2020 National TB Target of 1.4 per 100,000. To reduce the TB case rate in Massachusetts, it is necessary to understand the local epidemiology and transmission risks. MethodsWe used an existing TB case database of Massachusetts TB cases in the time frame from 2012 to 2015, which links de-identified patient demographic information with TB genotypes obtained from the United States Centers for Disease Control and Prevention's (CDC) TB Genotyping Information Management System database. Two or more cases with identical genotypes, which were close in space (within 50 km), as determined in a geographic information system (GIS), and time (3 years), were considered TB clusters. ResultsWe analyzed 543 genotyped cases. We identified a total of 85 cases that met the TB cluster criteria, and a total of 33 clusters. US-born individuals (p = 0.003), homeless individuals (p = 0.001) and those reporting illicit substance use (p = 0.001) and alcohol use (p = 0.001) were more likely to appear in a TB cluster. ConclusionThrough a combined genotypic and spatial epidemiological approach, we identified populations and individuals more likely to be in a TB cluster. Testing populations identified as at risk for being in a TB cluster, and providing appropriate treatment, may decrease the overall TB case rate and support efforts to achieve national 2020 TB targets.

Spatial and space-time clustering of tuberculosis in Gurage Zone, Southern Ethiopia.

IntroductionSpatial targeting is advocated as an effective method that contributes for achieving tuberculosis control in high-burden countries. However, there is a paucity of studies clarifying the spatial nature of the disease in these countries. This study aims to identify the location, size and risk of purely spatial and space-time clusters for high occurrence of tuberculosis in Gurage Zone, Southern Ethiopia during 2007 to 2016.Materials and methodsA total of 15,805 patient data that were retrieved from unit TB registers were included in the final analyses. The spatial and space-time cluster analyses were performed using the global Moran’s I, Getis-Ord and Kulldorff’s scan statistics.ResultsEleven purely spatial and three space-time clusters were detected (P <0.001).The clusters were concentrated in border areas of the Gurage Zone. There were considerable spatial variations in the risk of tuberculosis by year during the study period.ConclusionsThis study showed that tuberculosis clusters were mainly concentrated at border areas of the Gurage Zone during the study period, suggesting that there has been sustained transmission of the disease within these locations. The findings may help intensify the implementation of tuberculosis control activities in these locations. Further study is warranted to explore the roles of various ecological factors on the observed spatial distribution of tuberculosis.

The use of whole-genome sequencing incluster investigation of a multidrug-resistant tuberculosis outbreak.

We used whole-genome sequencing (WGS) to delineate transmission networks and investigate the benefits of WGS during cluster investigation.We included clustered cases of multidrug-resistant (MDR) tuberculosis (TB)/extensively drug-resistant (XDR) TB linked by mycobacterial interspersed repetitive unit variable tandem repeat (MIRU-VNTR) strain typing or epidemiological information in the national cluster B1006, notified between 2007 and 2013 in the UK. We excluded from further investigation cases whose isolates differed by greater than 12 single nucleotide polymorphisms (SNPs). Data relating to patients' social networks were collected.27 cases were investigated and 22 had WGS, eight of which (36%) were excluded as their isolates differed by more than 12 SNPs to other cases. 18 cases were ruled into the transmission network based on genomic and epidemiological information. Evidence of transmission was inconclusive in seven out of 18 cases (39%) in the transmission network following WGS and epidemiological investigation.This investigation of a drug-resistant TB cluster illustrates the opportunities and limitations of WGS in understanding transmission in a setting with a high proportion of migrant cases. The use of WGS should be combined with classical epidemiological methods. However, not every cluster will be solvable, regardless of the quality of genomic data.

On sunspots, click science and molecular iconography

CRISPR-spoligotyping and MIRU-VNTR typing, SITVIT_WEB and MIRU-VNTRplus are the methods and online resources most widely used for Mycobacterium tuberculosis genotype family assignment and clustering analysis. They have been proven invaluable for molecular epidemiological studies of this important human pathogen in setting up the terminology and classification framework. However, they are inherently limited by insufficient knowledge of evolution of the targeted genome loci (especially, CRISPR). The situation is aggravated by the dogmatic, iconographic perception of these increasingly user-friendly online tools. Here, I present a critical essay on hot practical aspects related to the use of SITVIT_WEB and MIRU-VNTRplus, in particular, partly inadequate (sub)clade assignment due to imperfect decision rules, partly outdated methodological options offered to the users that permit to build scientifically unsound phylogenies from spoligotyping data. A confusing terminology, misclassification and false clustering are not abstract issues but make a scientific discussion meaningless, and I propose some courses for improvement.

The influence of mutation gene rpoB of Mycobacterium tuberculosis cluster I (507-534) on the elimination 25-desacetyl rifampicin in urine of tuberculosis subjects

The study aimed to evaluate the influence of mutation gene rpoB of Mycobacterium (M.) tuberculosis cluster I (507-534) on the elimination of 25-Desacetyl Rifampicin (25-DR) in the urine of tuberculosis (TB) subjects. Early morning sputum took from patient TB before treatment. Urine collected after 2 hours taken Fixed-Dose Combination (FDC) at days 7th treatment. All sputum were sequencing at Macrogen Korea Laboratory. Urine was analyzed by high-Performance Liquid Chromatography (HPLC) using the method of Lily et al. Mean (standard deviation) for mutation and non-mutation of rpoB M. tuberculosis group were 7.6147 (4.4478) and 4.5772 (1.7532) μg/ml, respectively. Shapiro-Wilk test showed normally distributed data, with significance 0.3. Independent t-test performed p-value 0.167 and confidence interval (CI) from -1.648 to 7.723. The mutation gene rpoB of M. tuberculosis cluster, I (507-534) in this study, did not affect elimination 25-DR in theurine of TB subjects statistically and clinically.

Investigating a tuberculosis cluster among Filipino health care workers in a low-incidence country.

Nearly 8% of adult tuberculosis (TB) cases in England, Wales and Northern Ireland (EW&NI) occur among health care workers (HCWs), the majority of whom are from high TB incidence countries. To determine if a TB cluster containing multiple HCWs was due to nosocomial transmission. A cluster of TB cases notified in EW&NI from 2009 to 2014, with indistinguishable 24-locus mycobacterial interspersed repetitive unit-variable number of tandem repeats (MIRU-VNTR) profiles, was identified through routine national cluster review. Cases were investigated to identify epidemiological links, and occupational health (OH) information was collected for HCW cases. To further discriminate strains, typing of eight additional loci was conducted. Of the 53 cases identified, 22 were HCWs. The majority (n = 43), including 21 HCWs, were born in the Philippines. Additional typing split the cluster into three subclusters and seven unique strains. No epidemiological links were identified beyond one household and a common residential area. HCWs in this cluster received no or inadequate OH assessment. The MIRU-VNTR profile of this cluster probably reflects common endemic strains circulating in the Philippines, with reactivation occurring in the UK. Furthermore, 32-locus typing showed that 24-locus MIRU-VNTR failed to distinguish strain diversity. The lack of OH assessment indicates that latent tuberculous infection could have been identified and treated, thereby preventing active cases from occurring.

Statistical Method to Detect Tuberculosis Outbreaks among Endemic Clusters in a Low-Incidence Setting.

We previously reported use of genotype surveillance data to predict outbreaks among incident tuberculosis clusters. We propose a method to detect possible outbreaks among endemic tuberculosis clusters. We detected 15 possible outbreaks, of which 10 had epidemiologic data or whole-genome sequencing results. Eight outbreaks were corroborated.

Spatial clustering of drug-resistant tuberculosis in Hlabisa subdistrict, KwaZulu-Natal, 2011-2015.

SETTING:Incidence rates of tuberculosis (TB) in South Africa are among the highest in the world, and drug resistance is a major concern. Understanding geographic variations in disease may guide targeted interventions.OBJECTIVE:To characterise the spatial distribution of drug-resistant TB (DR-TB) in a rural area of KwaZulu-Natal, South Africa, and to test for clustering.DESIGN:This was a cross-sectional analysis of DR-TB patients managed at a rural district hospital from 2011 to 2015. We mapped all patients in hospital data to local areas, and then linked to a population-based demographic surveillance system to map the patients to individual homesteads. We used kernel density estimation to visualise the distribution of disease and tested for clustering using spatial scan statistics.RESULTS:There were 489 patients with DR-TB in the subdistrict; 111 lived in the smaller demographic surveillance area. Spatial clustering analysis identified a high-risk cluster (relative risk of DR-TB inside vs. outside cluster 3.0, P <0.001) in the south-east, a region characterised by high population density and a high prevalence of human immunodeficiency virus infection.CONCLUSION:We have demonstrated evidence of a geographic high-risk cluster of DR-TB. This suggests that targeting interventions to spatial areas of highest risk, where transmission may be ongoing, could be effective.

Molecular epidemiology of tuberculosis in Tasmania and genomic characterisation of its first known multi-drug resistant case.

BackgroundThe origin and spread of tuberculosis (TB) in Tasmania and the types of strains of Mycobacterium tuberculosis complex (MTBC) present in the population are largely unknown.ObjectiveThe aim of this study was to perform the first genomic analysis of MTBC isolates from Tasmania to better understand the epidemiology of TB in the state.MethodsWhole-genome sequencing was performed on cultured isolates of MTBC collected from 2014–2016. Single-locus variant analysis was applied to determine the phylogeny of the isolates and the presence of drug-resistance mutations. The genomic data were then cross-referenced against public health surveillance records on each of the cases.ResultsWe determined that 83.3% of TB cases in Tasmania from 2014–2016 occurred in non-Australian born individuals. Two possible TB clusters were identified based on single locus variant analysis, one from November-December 2014 (n = 2), with the second from May-August 2015 (n = 4). We report here the first known isolate of multi-drug resistant (MDR) M. tuberculosis in Tasmania from 2016 for which we established its drug resistance mutations and potential overseas origin. In addition, we characterised a case of M. bovis TB in a Tasmanian-born person who presented in 2014, approximately 40 years after the last confirmed case in the state’s bovids.ConclusionsTB in Tasmania is predominantly of overseas origin with genotypically-unique drug-susceptible isolates of M. tuberculosis. However, the state also exhibits features of TB that are observed in other jurisdictions, namely, the clustering of cases, and drug resistance. Early detection of TB and contact tracing, particularly of overseas-born cases, coordinated with rapid laboratory drug-susceptibility testing and molecular typing, will be essential for Tasmania to reach the World Health Organisation’s TB eradication goals for low-incidence settings.

Spatial distribution of tuberculosis in Manaus and its social determinants, 2008-2013.

Brazil ranks eighteenth worldwide in annual numbers of new tuberculosis (TB) cases. The municipality of Manaus, Amazonas State, has the highest incidence of TB in Brazil. To evaluate the quality of TB epidemiological surveillance, and to describe the spatial distribution pattern of TB incidence in Manaus and its social determinants. An ecological study was performed based on secondary data from TB epidemiological surveillance reports. An index was developed to classify neighborhoods in terms of the quality of surveillance and suspected underreporting. Based on data from neighborhoods with better surveillance performance, we observed that the average number of residents per room, the unemployment rate and the proportion of households connected to a sewage system were significant predictors of TB incidence. Seven neighborhoods in the south and west of the city had clusters of high TB transmission. Our results suggest that the association between TB and social vulnerability is obscured by the poor quality of TB surveillance data. We identified priority areas that require immediate TB control interventions and those where local surveillance efforts should be improved, and generated information useful for formulating more effective actions.

A Predominant Variable-Number Tandem-Repeat Cluster of Mycobacterium tuberculosis Isolates among Asylum Seekers in the Netherlands and Denmark, Deciphered by Whole-Genome Sequencing.

ABSTRACTIn many countries, Mycobacterium tuberculosis isolates are routinely subjected to variable-number tandem-repeat (VNTR) typing to investigate M. tuberculosis transmission. Unexpectedly, cross-border clusters were identified among African refugees in the Netherlands and Denmark, although transmission in those countries was unlikely. Whole-genome sequencing (WGS) was applied to analyze transmission in depth and to assess the precision of VNTR typing. WGS was applied to 40 M. tuberculosis isolates from refugees in the Netherlands and Denmark (most of whom were from the Horn of Africa) that shared the exact same VNTR profile. Cluster investigations were undertaken to identify in-country epidemiological links. Combining WGS results for the isolates (all members of the central Asian strain [CAS]/Delhi genotype), from both European countries, an average genetic distance of 80 single-nucleotide polymorphisms (SNPs) (maximum, 153 SNPs) was observed. The few pairs of isolates with confirmed epidemiological links, except for one pair, had a maximum distance of 12 SNPs. WGS divided this refugee cluster into several subclusters of patients from the same country of origin. Although the M. tuberculosis cases, mainly originating from African countries, shared the exact same VNTR profile, most were clearly distinguished by WGS. The average genetic distance in this specific VNTR cluster was 2 times greater than that in other VNTR clusters. Thus, identical VNTR profiles did not represent recent direct M. tuberculosis transmission for this group of patients. It appears that either these strains from Africa are extremely conserved genetically or there is ongoing transmission of this genotype among refugees on their long migration routes from Africa to Europe.

A cluster of multidrug-resistant Mycobacterium tuberculosis among patients arriving in Europe from the Horn of Africa: a molecular epidemiological study

SummaryBackgroundThe risk of tuberculosis outbreaks among people fleeing hardship for refuge in Europe is heightened. We describe the cross-border European response to an outbreak of multidrug-resistant tuberculosis among patients from the Horn of Africa and Sudan.MethodsOn April 29 and May 30, 2016, the Swiss and German National Mycobacterial Reference Laboratories independently triggered an outbreak investigation after four patients were diagnosed with multidrug-resistant tuberculosis. In this molecular epidemiological study, we prospectively defined outbreak cases with 24-locus mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) profiles; phenotypic resistance to isoniazid, rifampicin, ethambutol, pyrazinamide, and capreomycin; and corresponding drug resistance mutations. We whole-genome sequenced all Mycobacterium tuberculosis isolates and clustered them using a threshold of five single nucleotide polymorphisms (SNPs). We collated epidemiological data from host countries from the European Centre for Disease Prevention and Control.FindingsBetween Feb 12, 2016, and April 19, 2017, 29 patients were diagnosed with multidrug-resistant tuberculosis in seven European countries. All originated from the Horn of Africa or Sudan, with all isolates two SNPs or fewer apart. 22 (76%) patients reported their travel routes, with clear spatiotemporal overlap between routes. We identified a further 29 MIRU-VNTR-linked cases from the Horn of Africa that predated the outbreak, but all were more than five SNPs from the outbreak. However all 58 isolates shared a capreomycin resistance-associated tlyA mutation.InterpretationOur data suggest that source cases are linked to an M tuberculosis clone circulating in northern Somalia or Djibouti and that transmission probably occurred en route before arrival in Europe. We hypothesise that the shared mutation of tlyA is a drug resistance mutation and phylogenetic marker, the first of its kind in M tuberculosis sensu stricto.FundingThe Swiss Federal Office of Public Health, the University of Zurich, the Wellcome Trust, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), the Medical Research Council, BELTA-TBnet, the European Union, the German Center for Infection Research, and Leibniz Science Campus Evolutionary Medicine of the Lung (EvoLUNG).