Multiple large clusters of tuberculosis in London: a cross-sectional analysis of molecular and spatial data

Multi Drug Resistant Tuberculosis Clusters in Mpumalanga Province, South Africa, 2013-2016: A Spatial Analysis

OBJECTIVE

To identify spatial clusters with unusually high levels of MDR-TB which are highly unlikely to have arisen by chance in Mpumalanga Province, South Africa.

METHODS

Home addresses of all MDR-TB patients were collected from four MDR-TB facilities from 2013 to 2016. We mapped all addresses, linking them to the nearest ward with population estimates. A spatial analysis was conducted using kernel density in ArcGIS to estimate and map the distribution of the disease and used Gertis-Ord Gi to test for significant clustering.

RESULTS

A total of 4,065 MDR-TB patients were mapped. Ten significant clusters (p-value < 0.05) were found across the province in six sub-districts: Mbombela, Nkomazi, Emalahleni, Govan Mbeki, Lekwa and Mkhondo. Mbombela has the highest number of significant clusters. The central region did not have any MDR-TB clusters.

CONCLUSION

There is clear evidence of MDR-TB clustering in Mpumalanga. This calls for concentrated TB prevention efforts and proper allocation of resources. Further investigations are needed to identify MDR-TB predictors.

Genotyping indicates marked heterogeneity of tuberculosis transmission in the United States, 2009–2018

Heterogeneity in the number of secondary tuberculosis (TB) cases per source case, the effective reproductive number, R, is important in modelling prevention strategies' impact on incidence.

We estimated mean R (R_m) and calculate the dispersion parameter of this distribution, k, using surveillance and genotyping data for U.S. cases during 2009–2018. We modelled transmission assuming cases in a cluster have matching genotypes and share characteristics related to geography, temporal proximity (i.e. serial interval) and time since U.S. arrival among non-U.S.-born persons.

Complete data were available for 55 330/85 958 cases. Varying the serial interval and geographic proximity used to derive clusters, we consistently estimated R_m<1.0 and k < 0.08; the low value of k indicates a small number of source cases produce a disproportionate number of secondary cases.

U.S. TB reproductive number has a highly skewed distribution, indicating a minority of source cases disproportionately contribute to transmission.

Molecular surveillance of antimicrobial resistance and transmission pattern of Mycobacterium leprae in Chinese leprosy patients

Reports on antimicrobial resistance (AMR) of Mycobacterium leprae, relationship with bacteriological index (BI), and transmission in China are limited. We investigated the emergence of AMR mutations, the relationship between BI and AMR in complete, moderate and lack of BI decline cases, and molecular epidemiological features of AMR cases by enrolling 290 leprosy cases from four endemic provinces. Seven (2.41%), one (0.34%), five (1.72%), one (0.34%), and one (0.34%) strains had single mutations in folP1, rpoC, gyrA, gyrB, and 23S rRNA, respectively. Double mutations in folP1 and gyrA, rpoB and gyrA, and gyrA and 23S rRNA were observed in one (0.34%) strain each. Mutated strains occurred in three out of 81 (95% CI-0.005-0.079, p = 0.083) cases with complete BI decline, in seven out of 103 (95% CI 0.018-0.117, p = 0.008) cases with moderate BI decline, and in four out of 34 (95% CI 0.003-0.231, p = 0.044) cases with lack of BI decline. Most of these mutated strains were geographically separated and diverged genotypically. AMR mutations may not be the main cause of the lack of BI decline. The low transmission of AMR strains at the county level indicates an ongoing transmission at close contact levels.

Cannabis use and the risk of tuberculosis: a systematic review

BACKGROUND

Cannabis has been identified as a possible risk factor in some tuberculosis (TB) outbreaks. As the most widely used (largely) illegal substance in Western countries this may be an important public health concern. We aim to systematically review the evidence on the association between cannabis use and TB (latent infection and active disease) to inform ongoing and future TB prevention and control strategies.

METHODS

We conducted a systematic review. We searched Ovid Medline, Embase and PsycInfo, together with the World Health Organization website and Google Scholar, for all years to January 2018. Reference lists and conference abstracts were hand-searched, a forward citation search was conducted on the Web of Science, and experts were contacted. Two authors independently screened studies for inclusion, extracted data and assessed risk of bias using an adapted version of ROBINS-I ("Risk of Bias in Non-randomised Studies - of Interventions"). Data were narratively synthesised.

RESULTS

Of 377 records identified, 11 studies were eligible. Study designs were heterogeneous. Six studies utilised a relevant comparator group. Four of these investigated the association between cannabis use and latent TB infection; all provided some evidence of an association, although only two of these had adjusted for confounders. The remaining two comparator studies investigated the association between cannabis use and active TB disease; neither found evidence of an association after adjusting for confounding. All six studies were at "Serious" risk of bias. The five studies which did not utilise a relevant comparator group were all indicative of TB outbreaks occurring among cannabis users, but the quality of the evidence was very weak.

CONCLUSIONS

Evidence for an association between cannabis use and TB acquisition is weak. The topic warrants further robust primary research including the collection of consistent and accurate exposure information, including cannabis use practices, dose and frequency, and adjustment for confounders.

Spatial analysis of HIV-TB co-clustering in Uganda

BACKGROUND

Tuberculosis (TB) is the leading cause of death for individuals infected with Human immunodeficiency virus (HIV). Conversely, HIV is the most important risk factor in the progression of TB from the latent to the active status. In order to manage this double epidemic situation, an integrated approach that includes HIV management in TB patients was proposed by the World Health Organization and was implemented in Uganda (one of the countries endemic with both diseases). To enable targeted intervention using the integrated approach, areas with high disease prevalence rates for TB and HIV need to be identified first. However, there is no such study in Uganda, addressing the joint spatial patterns of these two diseases.

METHODS

This study uses global Moran's index, spatial scan statistics and bivariate global and local Moran's indices to investigate the geographical clustering patterns of both diseases, as individuals and as combined. The data used are TB and HIV case data for 2015, 2016 and 2017 obtained from the District Health Information Software 2 system, housed and maintained by the Ministry of Health, Uganda.

RESULTS

Results from this analysis show that while TB and HIV diseases are highly correlated (55-76%), they exhibit relatively different spatial clustering patterns across Uganda. The joint TB/HIV prevalence shows consistent hotspot clusters around districts surrounding Lake Victoria as well as northern Uganda. These two clusters could be linked to the presence of high HIV prevalence among the fishing communities of Lake Victoria and the presence of refugees and internally displaced people camps, respectively. The consistent cold spot observed in eastern Uganda and around Kasese could be explained by low HIV prevalence in communities with circumcision tradition.

CONCLUSIONS

This study makes a significant contribution to TB/HIV public health bodies around Uganda by identifying areas with high joint disease burden, in the light of TB/HIV co-infection. It, thus, provides a valuable starting point for an informed and targeted intervention, as a positive step towards a TB and HIV-AIDS free community.

Spatial and temporal analysis of tuberculosis in an area of social inequality in Northeast Brazil

BACKGROUND

Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis. It is a disease known worldwide for its vulnerability factors, magnitude and mortality. The objective of the study was to analyze the spatial and temporal dynamics of TB in the area of social inequality in northeast Brazil between the years 2001 and 2016.

METHODS

An ecological time series study with the use of spatial analysis techniques was carried out from 2001 to 2016. The units of analysis were the 75 municipalities in the state of Sergipe. Data from the Notification of Injury Information System were used. For the construction of the maps, the cartographic base of the state of Sergipe, obtained at the Instituto Brasileiro de Geografia e Estatística, was used. Georeferenced data were analysed using TerraView 4.2.2 software (Instituto Nacional de Pesquisas Espaciais) and QGis 2.18.2 (Open Source Geospatial Foundation). Spatial analyses included the empirical Bayesian model and the global and local Moran indices. The time trend analyses were performed by the software Joinpoint Regression, Version 4.5.0.1, with the variables of sex, age, cure and abandonment.

RESULTS

There was an increasing trend of tuberculosis cases in patients under 20 years old and 20-39 years old, especially in males. Cured cases showed a decreasing trend, and cases of treatment withdrawal were stationary. A spatial dependence was observed in almost all analysed territories but with different concentrations. Significant spatial correlations with the formation of clusters in the southeast and northeast of the state were observed. The probability of illness among municipalities was determined not to occur in a random way.

CONCLUSION

The identification of risk areas and priority groups can help health planning by refining the focus of attention to tuberculosis control. Understanding the epidemiological, spatial and temporal dynamics of tuberculosis can allow for improved targeting of strategies for disease prevention and control.

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.

Where is tuberculosis transmission happening? Insights from the literature, new tools to study transmission and implications for the elimination of tuberculosis

More than 10 million new cases of tuberculosis (TB) are diagnosed worldwide each year. The majority of these cases occur in low- and middle-income countries where the TB epidemic is predominantly driven by transmission. Efforts to 'end TB' will depend upon our ability to halt ongoing transmission. However, recent studies of new approaches to interrupt transmission have demonstrated inconsistent effects on reducing population-level TB incidence. TB transmission occurs across a wide range of settings, that include households and hospitals, but also community-based settings. While home-based contact investigations and infection control programmes in hospitals and clinics have a successful track record as TB control activities, there is a gap in our knowledge of where, and between whom, community-based transmission of TB occurs. Novel tools, including molecular epidemiology, geospatial analyses and ventilation studies, provide hope for improving our understanding of transmission in countries where the burden of TB is greatest. By integrating these diverse and innovative tools, we can enhance our ability to identify transmission events by documenting the opportunity for transmission-through either an epidemiologic or geospatial connection-alongside genomic evidence for transmission, based upon genetically similar TB strains. A greater understanding of locations and patterns of transmission will translate into meaningful improvements in our current TB control activities by informing targeted, evidence-based public health interventions.

Internal migration and transmission dynamics of tuberculosis in Shanghai, China: an epidemiological, spatial, genomic analysis

BACKGROUND

Massive internal migration from rural to urban areas poses new challenges for tuberculosis control in China. We aimed to combine genomic, spatial, and epidemiological data to describe the dynamics of tuberculosis in an urban setting with large numbers of migrants.

METHODS

We did a population-based study of culture-positive Mycobacterium tuberculosis isolates in Songjiang, Shanghai. We used whole-genome sequencing to discriminate apparent genetic clusters of M tuberculosis sharing identical variable-number-tandem-repeat (VNTR) patterns, and analysed the relations between proximity of residence and the risk of genomically clustered M tuberculosis. Finally, we used genomic, spatial, and epidemiological data to estimate time of infection and transmission links among migrants and residents.

FINDINGS

Between Jan 1, 2009, and Dec 31, 2015, 1620 cases of culture-positive tuberculosis were recorded, 1211 (75%) of which occurred among internal migrants. 150 (69%) of 218 people sharing identical VNTR patterns had isolates within ten single-nucleotide polymorphisms (SNPs) of at least one other strain, consistent with recent transmission of M tuberculosis. Pairs of strains collected from individuals living in close proximity were more likely to be genetically similar than those from individuals who lived far away-for every additional km of distance between patients' homes, the odds that genotypically matched strains were within ten SNPs of each other decreased by about 10% (OR 0·89 [95% CI 0·87-0·91]; p<0·0001). We inferred that transmission from residents to migrants occurs as commonly as transmission from migrants to residents, and we estimated that more than two-thirds of migrants in genomic clusters were infected locally after migration.

INTERPRETATION

The primary mechanism driving local incidence of tuberculosis in urban centres is local transmission between both migrants and residents. Combined analysis of epidemiological, genomic, and spatial data contributes to a richer understanding of local transmission dynamics and should inform the design of more effective interventions.

FUNDING

National Natural Science Foundation of China, National Science and Technology Major Project of China, and US National Institutes of Health.

Prediction of Local Transmission of Mycobacterium tuberculosis Isolates of a Predominantly Beijing Lineage by Use of a Variable-Number Tandem-Repeat Typing Method Incorporating a Consensus Set of Hypervariable Loci

Strain genotyping based on the variable-number tandem repeat (VNTR) is widely applied for identifying the transmission of Mycobacterium tuberculosis A consensus set of four hypervariable loci (1982, 3232, 3820, and 4120) has been proposed to improve the discrimination of Beijing lineage strains. Herein, we evaluated the utility of these four hypervariable loci for tracing local tuberculosis transmission in 981 cases over a 14-month period in Japan (2010 to 2011). We used six different VNTR systems, with or without the four hypervariable loci. Patient ages and weighted standard distances (a measure of the dispersion of genotype-clustered cases) were used as proxies for estimating local tuberculosis transmission. The highest levels of isolate discrimination were achieved with VNTR systems that incorporated the four hypervariable loci (i.e., the Japan Anti-Tuberculosis Association [JATA]18-VNTR, mycobacterial interspersed repetitive unit [MIRU]28-VNTR, and 24_Beijing-VNTR). The clustering rates by JATA12-VNTR, MIRU15-VNTR, JATA15-VNTR, JATA18-VNTR, MIRU28-VNTR, and 24_Beijing-VNTR systems were 52.2%, 51.0%, 39.0%, 24.1%, 23.1%, and 22.0%, respectively. As the discriminative power increased, the median weighted standard distances of the clusters tended to decrease (from 311 to 80 km, P < 0.001, Jonckheere-Terpstra trend test). Concurrently, the median ages of patients in the clusters tended to decrease (from 68 to 60 years, P < 0.001, Jonckheere-Terpstra trend test). These findings suggest that strain typing using the four hypervariable loci improves the prediction of active local tuberculosis transmission. The four-locus set can therefore contribute to the targeted control of tuberculosis in settings with high prevalence of Beijing lineage strains.