Identifying Hotspots of Multidrug-Resistant Tuberculosis Transmission Using Spatial and Molecular Genetic Data

Genomic analysis of lineage-specific transmission of multidrug resistance tuberculosis in China

OBJECTIVES

We investigated the genetic diversities and lineage-specific transmission dynamics of multidrug-resistant tuberculosis (MDR-TB), with the goal of determining the potential factors driving the MDR epidemics in China.

METHODS

We curated a large nationwide Mycobacterium tuberculosis (M. tuberculosis) whole genome sequence data set, including 1313 MDR strains. We reconstructed the phylogeny and mapped the transmission networks of MDR-TB across China using Bayesian inference. To identify drug-resistance variants linked to enhanced transmissibility, we employed ordinary least-squares (OLS) regression analysis.

RESULT

The majority of MDR-TB strains in China belong to lineage 2.2.1. Transmission chain analysis has indicated that the repeated and frequent transmission of L2.2.1 plays a central role in the establishment of MDR epidemic in China, but no occurrence of a large predominant MDR outbreak was detected. Using OLS regression, the most common single nucleotide polymorphisms (SNPs) associated with resistance to isoniazid (katG_p.Ser315Thr and katG_p.Ser315Asn) and rifampicin (rpoB_p.Ser450Leu, rpoB_p.His445Tyr, rpoB_p.His445Arg, rpoB_p.His445Asp, and rpoB_p.His445Asn) were more likely to be found in L2 clustered strains. Several putative compensatory mutations in rpoA, rpoC, and katG were significantly associated with clustering. The eastern, central, and southern regions of China had a high level of connectivity for the migration of L2 MDR strains throughout the country. The skyline plot showed distinct population size expansion dynamics for MDR-TB lineages in China.

CONCLUSION

MDR-TB epidemic in China is predominantly driven by the spread of highly transmissible Beijing strains. A range of drug-resistance mutations of L2 MDR-TB strains displayed minimal fitness costs and may facilitate their transmission.

Identifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model

BACKGROUND

Multidrug resistant tuberculosis (MDR-TB) represents a major public health concern in the Republic of Moldova, with an estimated 31% of new and 56% of previously treated TB cases having MDR disease in 2022. A recent genomic epidemiology study of incident TB occurring in 2018 and 2019 found that 92% of MDR-TB was the result of transmission. The MDR phenotype was concentrated among two M. tuberculosis (Mtb) lineages: L2.2.1 (Beijing) and L4.2.1 (Ural).

METHODS

We developed and applied a hierarchical Bayesian multinominal logistic regression model to Mtb genomic, spatial, and epidemiological data collected from all individuals with diagnosed TB in Moldova in 2018 and 2019 to identify locations in which specific Mtb strains are being transmitted. We then used a logistic regression model to estimate locality-level factors associated with local transmission.

FINDINGS

We found differences in the spatial distribution and degree of local concentration of disease due to specific strains of Beijing and Ural lineage Mtb. Foci of transmission for four strains of Beijing lineage Mtb, predominantly of the MDR-TB phenotype, were located in several regions, but largely concentrated in Transnistria. In contrast, transmission of Ural lineage Mtb had less marked patterns of spatial aggregation, with a single strain (also of the MDR phenotype) spatially clustered in southern Transnistria. We found a 30% (95% credible interval 2%-80%) increase in odds of a locality being a transmission cluster for each increase of 100 persons per square kilometer, while higher local tuberculosis incidence and poverty were not associated with a locality being a transmission focus.

INTERPRETATION

Our results identified localities where specific Mtb transmission networks were concentrated and quantified the association between locality-level factors and focal transmission. This analysis revealed Transnistria as the primary area where specific Mtb strains (predominantly of the MDR-TB phenotype) were locally transmitted and suggests that targeted intensified case finding in this region may be an attractive policy option.

FUNDING

Funding for this work was provided by the National Institute of Allergy and Infectious Diseases at the US National Institutes of Health.

Enhanced active case finding of drug-resistant tuberculosis in Namibia: a protocol for the hotspots, hospitals, and households (H3TB) study

INTRODUCTION

Namibia is a high tuberculosis (TB)-burden country with an estimated incidence of 460/100 000 (around 12 000 cases) per year. Approximately 4.5% of new cases and 7.9% of previously treated TB cases are multidrug resistant (MDR) and 47% of patients with MDR-TB are HIV coinfected. Published data suggest a clustering of MDR-TB transmission in specific areas. Identifying transmission clusters is key to implementing high-yield and cost-effective interventions. This includes knowing the yield of finding TB cases in high-transmission zones (eg, community hotspots, hospitals or households) to deliver community-based interventions. We aim to identify such transmission zones for enhanced case finding and evaluate the effectiveness of this approach.

METHODS AND ANALYSIS

H3TB is an observational cross-sectional study evaluating MDR-TB active case finding strategies. Sputum samples from MDR-TB cases in three regions of Namibia will be evaluated by whole genome sequencing (WGS) in addition to routine sputum investigations (Xpert MTB/RIF, culture and drug susceptibility testing). We will collect information on household contacts, use of community spaces and geographical map intersections between participants, synthesising these data to identify transmission hotspots. We will look at the feasibility, acceptability, yield and cost of case finding strategies in these hotspots, and in households of patients with MDR-TB and visitors of hospitalised patients with MDR-TB. A compartmental transmission dynamic model will be constructed to evaluate the impact and cost-effectiveness of the strategies if scaled.

ETHICS AND DISSEMINATION

Ethics approval was obtained. Participants will give informed consent. H3TB will capitalise on a partnership with the Ministry of Health and Social Services to follow up individuals diagnosed with MDR-TB and integrate WGS data with innovative contact network mapping, to allow enhanced case finding. Study data will contribute towards a systems approach to TB control. Equally important, it will serve as a role model for similar studies in other high-incidence settings.

Identification of Risk Factors Associated with Tuberculosis in Southwest Iran: A Machine Learning Method

Background

Tuberculosis is a principal public health issue. Reducing and controlling tuberculosis did not result in the expected success despite implementing effective preventive and therapeutic programs, one of the reasons for which is the delay in definitive diagnosis. Therefore, creating a diagnostic aid system for tuberculosis screening can help in the early diagnosis of this disease. This research aims to use machine learning techniques to identify economic, social, and environmental factors affecting tuberculosis.

Methods

This case-control study included 80 individuals with TB and 172 participants as controls. During January-October 2021, information was collected from thirty-six health centers in Ahvaz, southwest Iran. Five different machine learning approaches were used to identify factors associated with TB, including BMI, sex, age , marital status, education, employment status, size of the family, monthly income, cigarette smoking, hookah smoking, history of chronic illness, history of imprisonment, history of hospital admission, first-class family, second-class family, third-class family, friend, co-worker, neighbor, market, store, hospital, health center, workplace, restaurant, park, mosque, Basij base, Hairdressers and school. The data was analyzed using the statistical programming R software version 4.1.1.

Results

According to the calculated evaluation criteria, the accuracy level of 5 SVM, RF, LSSVM, KNN, and NB models is 0.99, 0.72, 0.97,0.99, and 0.95, respectively, and except for RF, the other models had the highest accuracy. Among the 39 investigated variables, 16 factors including First-class family (20.83%), friend (17.01%), health center (41.67%), hospital (24.74%), store (18.49%), market (14.32%), workplace (9.46%), history of hospital admission (51.82%), BMI (43.75%), sex (40.36%), age (22.83%), educational status (60.59%), employment status (43.58%), monthly income (63.80%), addiction (44.10%), history of imprisonment (38.19%) were of the highest importance on tuberculosis.

Conclusion

The obtained results demonstrated that machine-learning techniques are effective in identifying economic, social, and environmental factors associated with tuberculosis. Identifying these different factors plays a significant role in preventing and performing appropriate and timely interventions to control this disease.

Polyketide synthases mutation in tuberculosis transmission revealed by whole genomic sequence, China, 2011-2019

Introduction: Tuberculosis (TB) is an infectious disease caused by a bacterium called Mycobacterium tuberculosis (Mtb). Previous studies have primarily focused on the transmissibility of multidrug-resistant (MDR) or extensively drug-resistant (XDR) Mtb. However, variations in virulence across Mtb lineages may also account for differences in transmissibility. In Mtb, polyketide synthase (PKS) genes encode large multifunctional proteins which have been shown to be major mycobacterial virulence factors. Therefore, this study aimed to identify the role of PKS mutations in TB transmission and assess its risk and characteristics. Methods: Whole genome sequences (WGSs) data from 3,204 Mtb isolates was collected from 2011 to 2019 in China. Whole genome single nucleotide polymorphism (SNP) profiles were used for phylogenetic tree analysis. Putative transmission clusters (≤10 SNPs) were identified. To identify the role of PKS mutations in TB transmission, we compared SNPs in the PKS gene region between "clustered isolates" and "non-clustered isolates" in different lineages. Results: Cluster-associated mutations in ppsA, pks12, and pks13 were identified among different lineage isolates. They were statistically significant among clustered strains, indicating that they may enhance the transmissibility of Mtb. Conclusion: Overall, this study provides new insights into the function of PKS and its localization in M. tuberculosis. The study found that ppsA, pks12, and pks13 may contribute to disease progression and higher transmission of certain strains. We also discussed the prospective use of mutant ppsA, pks12, and pks13 genes as drug targets.

Integrating Molecular Diagnostics and GIS Mapping: A Multidisciplinary Approach to Understanding Tuberculosis Disease Dynamics in South Africa Using Xpert MTB/RIF

An investigation was carried out to examine the use of national Xpert MTB/RIF data (2013-2017) and GIS technology for MTB/RIF surveillance in South Africa. The aim was to exhibit the potential of using molecular diagnostics for TB surveillance across the country. The variables analysed include Mycobacterium tuberculosis (Mtb) positivity, the mycobacterial proportion of rifampicin-resistant Mtb (RIF), and probe frequency. The summary statistics of these variables were generated and aggregated at the facility and municipal level. The spatial distribution patterns of the indicators across municipalities were determined using the Moran's I and Getis Ord (Gi) statistics. A case-control study was conducted to investigate factors associated with a high mycobacterial load. Logistic regression was used to analyse this study's results. There was striking spatial heterogeneity in the distribution of Mtb and RIF across South Africa. The median patient age, urban setting classification, and number of health care workers were found to be associated with the mycobacterial load. This study illustrates the potential of using data generated from molecular diagnostics in combination with GIS technology for Mtb surveillance in South Africa. Spatially targeted interventions can be implemented in areas where high-burden Mtb persists.

Genotypic and spatial analysis of transmission dynamics of tuberculosis in Shanghai, China: a 10-year prospective population-based surveillance study

Background

With improved tuberculosis (TB) control programs, the incidence of TB in China declined dramatically over the past few decades, but recently the rate of decrease has slowed, especially in large cities such as Shanghai. To help formulate strategies to further reduce TB incidence, we performed a 10-year study in Songjiang, a district of Shanghai, to delineate the characteristics, transmission patterns, and dynamic changes of the local TB burden.

Methods

We conducted a population-based study of culture-positive pulmonary TB patients diagnosed in Songjiang during 2011-2020. Genomic clusters were defined with a threshold distance of 12-single-nucleotide-polymorphisms based on whole-genome sequencing, and risk factors for clustering were identified by logistic regression. Transmission inference was performed using phybreak. The distances between the residences of patients were compared to the genomic distances of their isolates. Spatial patient hotspots were defined with kernel density estimation.

Findings

Of 2212 enrolled patients, 74.7% (1652/2212) were internal migrants. The clustering rate (25.2%, 558/2212) and spatial concentrations of clustered and unclustered patients were unchanged over the study period. Migrants had significantly higher TB rates but less clustering than residents. Clustering was highest in male migrants, younger patients and both residents and migrants employed in physical labor. Only 22.1% of transmission events occurred between residents and migrants, with residents more likely to transmit to migrants. The clustering risk decreased rapidly with increasing distances between patient residences, but more than half of clustered patient pairs lived ≥5 km apart. Epidemiologic links were identified for only 15.6% of clustered patients, mostly in close contacts.

Interpretation

Although some of the TB in Songjiang's migrant population is caused by strains brought by infected migrants, local, recent transmission is an important driver of the TB burden. These results suggest that further reductions in TB incidence require novel strategies to detect TB early and interrupt urban transmission.

Funding

Shanghai Municipal Science and Technology Major Project (ZD2021CY001), National Natural Science Foundation of China (82272376), National Research Council of Science and Technology Major Project of China (2017ZX10201302-006).

Investigating the intensity of social contacts associated with tuberculosis: a weighted networks model

BACKGROUND

Tuberculosis is known as one of the principal health problems, especially in developing countries. This study aimed to visualize, statistically model, and describe the weighted networks to investigate the intensity of social contacts associated with tuberculosis.

METHODS

In this case-control study, we applied weighted network analysis to assess the network of person-time spent in stores, workplaces, restaurants, mosques, Police bases, homes, hospitals, colleges, hairdressers, schools, contact homes, health centers, cinemas, parks, and markets. Modules will be determined based on the similarities between the variables in a topology overlap matrix. The most important variables will be found considering the association between each variable and module eigenvalues.

RESULTS

The result shows the extracted modules of locations based on the connectivity followed by the person-time at each place. The correlation (p-value) between TB and the turquoise, blue, and brown modules was 0.058 (0.351), 0.004 (0.943), and 0.117 (0.039), respectively. The brown module is the most important one, demonstrating a significant connection between homes, contact homes, health centers, and hospitals. Therefore, an association was found between person-time in four places and the occurrence of TB.

CONCLUSION

The finding of this study showed that most transmission of tuberculosis infection occurs in homes, contact homes, health centers, and hospitals. These place evaluations allow the identification of people with more contact and in need of screening, so critically leading to the identification of more patients with active TB.

Predicting resistance to fluoroquinolones among patients with rifampicin-resistant tuberculosis using machine learning methods

Background

Limited access to drug-susceptibility tests (DSTs) and delays in receiving DST results are challenges for timely and appropriate treatment of multi-drug resistant tuberculosis (TB) in many low-resource settings. We investigated whether data collected as part of routine, national TB surveillance could be used to develop predictive models to identify additional resistance to fluoroquinolones (FLQs), a critical second-line class of anti-TB agents, at the time of diagnosis with rifampin-resistant TB.

Methods and findings

We assessed three machine learning-based models (logistic regression, neural network, and random forest) using information from 540 patients with rifampicin-resistant TB, diagnosed using Xpert MTB/RIF and notified in the Republic of Moldova between January 2018 and December 2019. The models were trained to predict the resistance to FLQs based on demographic and TB clinical information of patients and the estimated district-level prevalence of resistance to FLQs. We compared these models based on the optimism-corrected area under the receiver operating characteristic curve (OC-AUC-ROC). The OC-AUC-ROC of all models were statistically greater than 0.5. The neural network model, which utilizes twelve features, performed best and had an estimated OC-AUC-ROC of 0.87 (0.83,0.91), which suggests reasonable discriminatory power. A limitation of our study is that our models are based only on data from the Republic of Moldova and since not externally validated, the generalizability of these models to other populations remains unknown.

Conclusions

Models trained on data from phenotypic surveillance of drug-resistant TB can predict resistance to FLQs based on patient characteristics at the time of diagnosis with rifampin-resistant TB using Xpert MTB/RIF, and information about the local prevalence of resistance to FLQs. These models may be useful for informing the selection of antibiotics while awaiting results of DSTs.

Spatial heterogeneity of extensively drug resistant-tuberculosis in Western Cape Province, South Africa

Tuberculosis (TB) remains a leading infectious disease killer globally. Treatment outcomes are especially poor among people with extensively drug-resistant (XDR) TB, until recently defined as rifampicin-resistant (RR) TB with resistance to an aminoglycoside (amikacin) and a fluoroquinolone (ofloxacin). We used laboratory TB test results from Western Cape province, South Africa between 2012 and 2015 to identify XDR-TB and pre-XDR-TB (RR-TB with resistance to one second-line drug) spatial hotspots. We mapped the percentage and count of individuals with RR-TB that had XDR-TB and pre-XDR-TB across the province and in Cape Town, as well as amikacin-resistant and ofloxacin-resistant TB. We found the percentage of pre-XDR-TB and the count of XDR-TB/pre-XDR-TB highly heterogeneous with geographic hotspots within RR-TB high burden areas, and found hotspots in both percentage and count of amikacin-resistant and ofloxacin-resistant TB. The spatial distribution of percentage ofloxacin-resistant TB hotspots was similar to XDR-TB hotspots, suggesting that fluoroquinolone-resistace is often the first step to additional resistance. Our work shows that interventions used to reduce XDR-TB incidence may need to be targeted within spatial locations of RR-TB, and further research is required to understand underlying drivers of XDR-TB transmission in these locations.

OUP accepted manuscript

Background

Objectives

Methods

Results

Conclusions

Integrative transnational analysis to dissect tuberculosis transmission events along the migratory route from Africa to Europe

BACKGROUND

Growing international migration has increased the complexity of tuberculosis transmission patterns. Italy's decision to close its borders in 2018 made of Spain the new European porte entrée for migration from the Horn of Africa (HA). In one of the first rescues of migrants from this region at the end of 2018, tuberculosis was diagnosed in eight subjects, mainly unaccompanied minors.

METHODS

Mycobacterium tuberculosis isolates from these recently arrived migrants were analysed by Mycobacterial Interspersed Repetitive-Unit/Variable-Number of Tandem Repeat (MIRU-VNTR) and subsequent whole genome sequencing (WGS) analysis. Data were compared with those from collections from other European countries receiving migrants from the HA and a strain-specific PCR was applied for a fast searching of common strains. Infections in a cellular model were performed to assess strain virulence.

RESULTS

MIRU-VNTR analysis allowed identifying an epidemiological cluster involving three of the eight cases from Somalia (0 single-nucleotide polymorphisms between isolates, HA cluster). Following detailed interviews revealed that two of these cases had shared the same migratory route in most of the trip and had spent a long time at a detention camp in Libya. To confirm potential en route transmission for the three cases, we searched the same strain in collections from other European countries receiving migrants from the HA. MIRU-VNTR, WGS and a strain-specific PCR for the HA strain were applied. The same strain was identified in 12 cases from Eritrea diagnosed soon after their arrival in 2018 to the Netherlands, Belgium and Italy. Intracellular replication rate of the strain did not reveal abnormal virulence.

CONCLUSIONS

Our study suggests a potential en route transmission of a pan-susceptible strain, which caused at least 15 tuberculosis cases in Somalian and Eritrean migrants diagnosed in four different European countries.

Quantifying geographic heterogeneity in TB incidence and the potential impact of geographically targeted interventions in South and North City Corporations of Dhaka, Bangladesh: a model-based study

In rapidly growing and high-burden urban centres, identifying tuberculosis (TB) transmission hotspots and understanding the potential impact of interventions can inform future control and prevention strategies. Using data on local demography, TB reports and patient reporting patterns in Dhaka South City Corporation (DSCC) and Dhaka North City Corporation (DNCC), Bangladesh, between 2010 and 2017, we developed maps of TB reporting rates across wards in DSCC and DNCC and identified wards with high rates of reported TB (i.e. 'hotspots') in DSCC and DNCC. We developed ward-level transmission models and estimated the potential epidemiological impact of three TB interventions: active case finding (ACF), mass preventive therapy (PT) and a combination of ACF and PT, implemented either citywide or targeted to high-incidence hotspots. There was substantial geographic heterogeneity in the estimated TB incidence in both DSCC and DNCC: incidence in the highest-incidence wards was over ten times higher than in the lowest-incidence wards in each city corporation. ACF, PT and combined ACF plus PT delivered to 10% of the population reduced TB incidence by a projected 7%-9%, 13%-15% and 19%-23% over five years, respectively. Targeting TB hotspots increased the projected reduction in TB incidence achieved by each intervention 1.4- to 1.8-fold. The geographical pattern of TB notifications suggests high levels of ongoing TB transmission in DSCC and DNCC, with substantial heterogeneity at the ward level. Interventions that reduce transmission are likely to be highly effective and incorporating notification data at the local level can further improve intervention efficiency.

Community transmission of multidrug-resistant tuberculosis is associated with activity space overlap in Lima, Peru

Background

Transmission of multidrug-resistant tuberculosis (MDRTB) requires spatial proximity between infectious cases and susceptible persons. We assess activity space overlap among MDRTB cases and community controls to identify potential areas of transmission.

Methods

We enrolled 35 MDRTB cases and 64 TB-free community controls in Lima, Peru. Cases were whole genome sequenced and strain clustering was used as a proxy for transmission. GPS data were gathered from participants over seven days. Kernel density estimation methods were used to construct activity spaces from GPS locations and the utilization distribution overlap index (UDOI) was used to quantify activity space overlap.

Results

Activity spaces of controls (median = 35.6 km², IQR = 25.1–54) were larger than cases (median = 21.3 km², IQR = 17.9–48.6) (P = 0.02). Activity space overlap was greatest among genetically clustered cases (mean UDOI = 0.63, sd = 0.67) and lowest between cases and controls (mean UDOI = 0.13, sd = 0.28). UDOI was positively associated with genetic similarity of MDRTB strains between case pairs (P < 0.001). The odds of two cases being genetically clustered increased by 22% per 0.10 increase in UDOI (OR = 1.22, CI = 1.09–1.36, P < 0.001).

Conclusions

Activity space overlap is associated with MDRTB clustering. MDRTB transmission may be occurring in small, overlapping activity spaces in community settings. GPS studies may be useful in identifying new areas of MDRTB transmission.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-05953-8.

Blood RNA signatures predict recent tuberculosis exposure in mice, macaques and humans

Tuberculosis (TB) is the leading cause of death due to a single infectious disease. Knowing when a person was infected with Mycobacterium tuberculosis (M.tb) is critical as recent infection is the strongest clinical risk factor for progression to TB disease in immunocompetent individuals. However, time since M.tb infection is challenging to determine in routine clinical practice. To define a biomarker for recent TB exposure, we determined whether gene expression patterns in blood RNA correlated with time since M.tb infection or exposure. First, we found RNA signatures that accurately discriminated early and late time periods after experimental infection in mice and cynomolgus macaques. Next, we found a 6-gene blood RNA signature that identified recently exposed individuals in two independent human cohorts, including adult household contacts of TB cases and adolescents who recently acquired M.tb infection. Our work supports the need for future longitudinal studies of recent TB contacts to determine whether biomarkers of recent infection can provide prognostic information of TB disease risk in individuals and help map recent transmission in communities.

Children as sentinels of tuberculosis transmission: disease mapping of programmatic data

BACKGROUND

Identifying hotspots of tuberculosis transmission can inform spatially targeted active case-finding interventions. While national tuberculosis programs maintain notification registers which represent a potential source of data to investigate transmission patterns, high local tuberculosis incidence may not provide a reliable signal for transmission because the population distribution of covariates affecting susceptibility and disease progression may confound the relationship between tuberculosis incidence and transmission. Child cases of tuberculosis and other endemic infectious disease have been observed to provide a signal of their transmission intensity. We assessed whether local overrepresentation of child cases in tuberculosis notification data corresponds to areas where recent transmission events are concentrated.

METHODS

We visualized spatial clustering of children < 5 years old notified to Peru's National Tuberculosis Program from two districts of Lima, Peru, from 2005 to 2007 using a log-Gaussian Cox process to model the intensity of the point-referenced child cases. To identify where clustering of child cases was more extreme than expected by chance alone, we mapped all cases from the notification data onto a grid and used a hierarchical Bayesian spatial model to identify grid cells where the proportion of cases among children < 5 years old is greater than expected. Modeling the proportion of child cases allowed us to use the spatial distribution of adult cases to control for unobserved factors that may explain the spatial variability in the distribution of child cases. We compare where young children are overrepresented in case notification data to areas identified as transmission hotspots using molecular epidemiological methods during a prospective study of tuberculosis transmission conducted from 2009 to 2012 in the same setting.

RESULTS

Areas in which childhood tuberculosis cases are overrepresented align with areas of spatial concentration of transmission revealed by molecular epidemiologic methods.

CONCLUSIONS

Age-disaggregated notification data can be used to identify hotspots of tuberculosis transmission and suggest local force of infection, providing an easily accessible source of data to target active case-finding intervention.

The Importance of Heterogeneity to the Epidemiology of Tuberculosis

Although less well-recognized than for other infectious diseases, heterogeneity is a defining feature of tuberculosis (TB) epidemiology. To advance toward TB elimination, this heterogeneity must be better understood and addressed. Drivers of heterogeneity in TB epidemiology act at the level of the infectious host, organism, susceptible host, environment, and distal determinants. These effects may be amplified by social mixing patterns, while the variable latent period between infection and disease may mask heterogeneity in transmission. Reliance on notified cases may lead to misidentification of the most affected groups, as case detection is often poorest where prevalence is highest. Assuming that average rates apply across diverse groups and ignoring the effects of cohort selection may result in misunderstanding of the epidemic and the anticipated effects of control measures. Given this substantial heterogeneity, interventions targeting high-risk groups based on location, social determinants, or comorbidities could improve efficiency, but raise ethical and equity considerations.

Development of a TB vaccine trial site in Africa and lessons from the Ebola experience

Tuberculosis is the deadliest infection of our time. In contrast, about 11,000 people died of Ebola between 2014 and 2016. Despite this manifest difference in mortality, there is now a vaccine licensed in the United States and by the European Medicines Agency, with up to 100% efficacy against Ebola. The developments that led to the trialing of the Ebola vaccine were historic and unprecedented. The single licensed TB vaccine (BCG) has limited efficacy. There is a dire need for a more efficacious TB vaccine. To deploy such vaccines, trials are needed in sites that combine high disease incidence and research infrastructure. We describe our twelve-year experience building a TB vaccine trial site in contrast to the process in the recent Ebola outbreak. There are additional differences. Relative to the Ebola pipeline, TB vaccines have fewer trials and a paucity of government and industry led trials. While pathogens have varying levels of difficulty in the development of new vaccine candidates, there yet appears to be greater interest in funding and coordinating Ebola interventions. TB is a global threat that requires similar concerted effort for elimination.

Citywide Transmission of Multidrug-resistant Tuberculosis Under China's Rapid Urbanization: A Retrospective Population-based Genomic Spatial Epidemiological Study

BACKGROUND

Population movement could extend multidrug-resistant tuberculosis (MDR-TB) transmission and complicate its global prevalence. We sought to identify the high-risk populations and geographic sites of MDR-TB transmission in Shenzhen, the most common destination for internal migrants in China.

METHODS

We performed a population-based, retrospective study in patients diagnosed with MDR-TB in Shenzhen during 2013-2017. By defining genomic clusters with a threshold of 12-single-nucleotide polymorphism distance based on whole-genome sequencing of their clinical strains, the clustering rate was calculated to evaluate the level of recent transmission. Risk factors were identified by multivariable logistic regression. To further delineate the epidemiological links, we invited the genomic-clustered patients to an in-depth social network investigation.

RESULTS

In total, 105 (25.2%) of the 417 enrolled patients with MDR-TB were grouped into 40 genome clusters, suggesting recent transmission of MDR strains. The adjusted risk for student to have a clustered strain was 4.05 (95% confidence interval, 1.06-17.0) times greater than other patients. The majority (70%, 28/40) of the genomic clusters involved patients who lived in different districts, with residences separated by an average of 8.76 kilometers. Other than household members, confirmed epidemiological links were also identified among classmates and workplace colleagues.

CONCLUSIONS

These findings demonstrate that local transmission of MDR-TB is a serious problem in Shenzhen. While most transmission occurred between people who lived distant from each other, there was clear evidence that transmission occurred in schools and workplaces, which should be included as targeted sites for active case finding.The average residential distance between genomic-clustered cases was more than 8 kilometers, while schools and workplaces, identified as sites of transmission in this study, deserve increased vigilance for targeted case finding of multidrug-resistant tuberculosis.

Spatial distribution of people diagnosed with tuberculosis through routine and active case finding: a community-based study in Kampala, Uganda

BACKGROUND

Routine tuberculosis (TB) notifications are geographically heterogeneous, but their utility in predicting the location of undiagnosed TB cases is unclear. We aimed to identify small-scale geographic areas with high TB notification rates based on routinely collected data and to evaluate whether these areas have a correspondingly high rate of undiagnosed prevalent TB.

METHODS

We used routinely collected data to identify geographic areas with high TB notification rates and evaluated the extent to which these areas correlated with the location of undiagnosed cases during a subsequent community-wide active case finding intervention in Kampala, Uganda. We first enrolled all adults who lived within 35 contiguous zones and were diagnosed through routine care at four local TB Diagnosis and Treatment Units. We calculated average monthly TB notification rates in each zone and defined geographic areas of "high risk" as zones that constituted the 20% of the population with highest notification rates. We compared the observed proportion of TB notifications among residents of these high-risk zones to the expected proportion, using simulated estimates based on population size and random variation alone. We then evaluated the extent to which these high-risk zones identified areas with high burdens of undiagnosed TB during a subsequent community-based active case finding campaign using a chi-square test.

RESULTS

We enrolled 45 adults diagnosed with TB through routine practices and who lived within the study area (estimated population of 49 527). Eighteen zones reported no TB cases in the 9-month period; among the remaining zones, monthly TB notification rates ranged from 3.9 to 39.4 per 100 000 population. The five zones with the highest notification rates constituted 62% (95% CI: 47-75%) of TB cases and 22% of the population-significantly higher than would be expected if population size and random chance were the only determinants of zone-to-zone variation (48%, 95% simulation interval: 40-59%). These five high-risk zones accounted for 42% (95% CI: 34-51%) of the 128 cases detected during the subsequent community-based case finding intervention, which was significantly higher than the 22% expected by chance (P < 0.001) but lower than the 62% of cases notified from those zones during the pre-intervention period (P = 0.02).

CONCLUSIONS

There is substantial heterogeneity in routine TB notification rates at the zone level. Using facility-based TB notification rates to prioritize high-yield areas for active case finding could double the yield of such case-finding interventions.

A positively selected FBN1 missense variant reduces height in Peruvian individuals

On average, Peruvian individuals are among the shortest in the world¹. Here we show that Native American ancestry is associated with reduced height in an ethnically diverse group of Peruvian individuals, and identify a population-specific, missense variant in the FBN1 gene (E1297G) that is significantly associated with lower height. Each copy of the minor allele (frequency of 4.7%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). To our knowledge, this is the largest effect size known for a common height-associated variant. FBN1 encodes the extracellular matrix protein fibrillin 1, which is a major structural component of microfibrils. We observed less densely packed fibrillin-1-rich microfibrils with irregular edges in the skin of individuals who were homozygous for G1297 compared with individuals who were homozygous for E1297. Moreover, we show that the E1297G locus is under positive selection in non-African populations, and that the E1297 variant shows subtle evidence of positive selection specifically within the Peruvian population. This variant is also significantly more frequent in coastal Peruvian populations than in populations from the Andes or the Amazon, which suggests that short stature might be the result of adaptation to factors that are associated with the coastal environment in Peru.

Whole Genome Sequencing and Spatial Analysis Identifies Recent Tuberculosis Transmission Hotspots in Ghana

Whole genome sequencing (WGS) is progressively being used to investigate the transmission dynamics of Mycobacterium tuberculosis complex (MTBC). We used WGS analysis to resolve traditional genotype clusters and explored the spatial distribution of confirmed recent transmission clusters. Bacterial genomes from a total of 452 MTBC isolates belonging to large traditional clusters from a population-based study spanning July 2012 and December 2015 were obtained through short read next-generation sequencing using the illumina HiSeq2500 platform. We performed clustering and spatial analysis using specified R packages and ArcGIS. Of the 452 traditional genotype clustered genomes, 314 (69.5%) were confirmed clusters with a median cluster size of 7.5 genomes and an interquartile range of 4–12. Recent tuberculosis (TB) transmission was estimated as 24.7%. We confirmed the wide spread of a Cameroon sub-lineage clone with a cluster size of 78 genomes predominantly from the Ablekuma sub-district of Accra metropolis. More importantly, we identified a recent transmission cluster associated with isoniazid resistance belonging to the Ghana sub-lineage of lineage 4. WGS was useful in detecting unsuspected outbreaks; hence, we recommend its use not only as a research tool but as a surveillance tool to aid in providing the necessary guided steps to track, monitor, and control TB.

Investigation of an extensive outbreak of HIV infection among children in Sindh, Pakistan: protocol for a matched casecontrol study

INTRODUCTION

In April 2019, 14 children were diagnosed with HIV infection by a private healthcare provider in Larkana district, Sindh province, Pakistan. Over the next 3 months, 930 individuals were diagnosed with HIV, >80% below 16 years, the largest ever outbreak of HIV in children in Pakistan. In this protocol paper, we describe research methods for assessing likely modes of HIV transmission in this outbreak and investigate spatial and molecular epidemiology.

METHODS AND ANALYSIS

A matched case-control study will be conducted with 406 cases recruited. Cases will be children aged below 16 years registered for care at the HIV treatment centre at Shaikh Zayed Children Hospital in Larkana City. Controls will be children who are HIV-uninfected (confirmed by a rapid HIV test) matched 1:1 by age (within 1 year), sex and neighbourhood. Following written informed consent from the guardian, a structured questionnaire will be administered to collect data on sociodemographic indices and exposure to risk factors for parenteral, vertical and sexual (only among those aged above 10 years) HIV transmission. A blood sample will be collected for hepatitis B and C serology (cases and controls) and HIV lineage studies (cases only). Mothers of participants will be tested for HIV to investigate the possibility of mother-to-child transmission. Conditional logistic regression will be used to investigate the association of a priori defined risk factors with HIV infection. Phylogenetic analyses will be conducted. Global positioning system coordinates of participants' addresses will be collected to investigate concordance between the genetic and spatial epidemiology.

ETHICS AND DISSEMINATION

Ethical approval was granted by the Ethics Review Committee of the Aga Khan University, Karachi. Study results will be shared with Sindh and National AIDS Control Programs, relevant governmental and non-governmental organisations, presented at national and international research conferences and published in international peer-reviewed scientific journals.

Spatio-temporal co-occurrence of hotspots of tuberculosis, poverty and air pollution in Lima, Peru

Growing evidence suggests pollution and other environmental factors have a role in the development of tuberculosis (TB), however, such studies have never been conducted in Peru. Considering the association between air pollution and specific geographic areas, our objective was to determine the spatial distribution and clustering of TB incident cases in Lima and their co-occurrence with clusters of fine particulate matter (PM2.5) and poverty. We found co-occurrences of clusters of elevated concentrations of air pollutants such as PM2.5, high poverty indexes, and high TB incidence in Lima. These findings suggest an interplay of socio-economic and environmental in driving TB incidence.

Circulation of M. tuberculosis Beijing genotype in Latin America and the Caribbean

Lineage 2 (East Asian), which includes the Beijing genotype, is one of the most prevalent lineages of Mycobacterium tuberculosis (Mtb) throughout the world. The Beijing family is associated to hypervirulence and drug-resistant tuberculosis. The study of this genotype's circulation in Latin America is crucial for achieving total control of TB, the goal established by the World Health Organization, for the American sub-continent, before 2035. In this sense, the present work presents an overview of the status of the Beijing genotype for this region, with a bibliographical review, and data analysis of MIRU-VNTRs for available Beijing isolates. Certain countries present a prevalent trend of <5%, suggesting low transmissibility for the region, with the exception of Cuba (17.2%), Perú (16%) and Colombia (5%). Minimum Spanning Tree analysis, obtained from MIRU-VNTR data, shows distribution of specific clonal complex strains in each country. From this data, in most countries, we found that molecular epidemiology has not been a tool used for the control of TB, suggesting that the Beijing genotype may be underestimated in Latin America. It is recommended that countries with the highest incidence of the Beijing genotype use effective control strategies and increased care, as a requirement for public health systems.

Spatial relationships between small-holder farms coupled with livestock management practices are correlated with the distribution of antibiotic resistant bacteria in northern Tanzania

We examined the spatial distribution of antibiotic-resistant coliform bacteria amongst livestock from three distinct cultural groups, where group-level differences in practices (e.g., antibiotic use) may influence the magnitude of antibiotic resistance, while livestock interactions (e.g., mixing herds, shared markets) between these locations may reduce heterogeneity in the distribution of antibiotic resistant bacteria. Data was collected as part of a larger study of antibiotic-resistance in northern Tanzania. Simple regression and generalized linear regression were used to assess livestock management and care practices in relation to the prevalence of multidrug-resistant (MDR) coliform bacteria. Simple and multivariable logistic regression were then used to identify how different management practices affected the odds of households being found within MDR "hotspots." Households that had a higher median neighbourhood value within a 3000 m radius showed a significant positive correlation with livestock MDR prevalence (β = 4.33, 95% CI: 2.41-6.32). Households were more likely to be found within hotspots if they had taken measures to avoid disease (Adjusted Odds Ratio (AOR) 1.53, CI: 1.08-2.18), and if they reported traveling less than a day to reach the market (AOR 2.66, CI: 1.18-6.01). Hotspot membership was less likely when a greater number of livestock were kept at home (AOR 0.81, CI: 0.69-0.95), if livestock were vaccinated (AOR 0.32, CI: 0.21-0.51), or if distance to nearest village was greater (AOR 0.46, CI: 0.36-0.59). The probability of MDR increases when herds are mixed, consistent with evidence for passive transmission of resistant bacteria between animals. Reduced MDR with vaccination is consistent with many studies showing reduced antibiotic use with less disease burden. The neighbourhood effect has implications for design of intervention studies.

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.

A Case-Control Study to Identify Community Venues Associated with Genetically-clustered, Multidrug-resistant Tuberculosis Disease in Lima, Peru

BACKGROUND

The majority of tuberculosis transmission occurs in community settings. Our primary aim in this study was to assess the association between exposure to community venues and multidrug-resistant (MDR) tuberculosis. Our secondary aim was to describe the social networks of MDR tuberculosis cases and controls.

METHODS

We recruited laboratory-confirmed MDR tuberculosis cases and community controls that were matched on age and sex. Whole-genome sequencing was used to identify genetically clustered cases. Venue tracing interviews (nonblinded) were conducted to enumerate community venues frequented by participants. Logistic regression was used to assess the association between MDR tuberculosis and person-time spent in community venues. A location-based social network was constructed, with respondents connected if they reported frequenting the same venue, and an exponential random graph model (ERGM) was fitted to model the network.

RESULTS

We enrolled 59 cases and 65 controls. Participants reported 729 unique venues. The mean number of venues reported was similar in both groups (P = .92). Person-time in healthcare venues (adjusted odds ratio [aOR] = 1.67, P = .01), schools (aOR = 1.53, P < .01), and transportation venues (aOR = 1.25, P = .03) was associated with MDR tuberculosis. Healthcare venues, markets, cinemas, and transportation venues were commonly shared among clustered cases. The ERGM indicated significant community segregation between cases and controls. Case networks were more densely connected.

CONCLUSIONS

Exposure to healthcare venues, schools, and transportation venues was associated with MDR tuberculosis. Intervention across the segregated network of case venues may be necessary to effectively stem transmission.

Spatially targeted screening to reduce tuberculosis transmission in high-incidence settings

As the leading infectious cause of death worldwide and the primary proximal cause of death in individuals living with HIV, tuberculosis remains a global concern. Existing tuberculosis control strategies that rely on passive case-finding appear insufficient to achieve targets for reductions in tuberculosis incidence and mortality. Active case-finding strategies aim to detect infectious individuals earlier in their infectious period to reduce onward transmission and improve treatment outcomes. Empirical studies of active case-finding have produced mixed results and determining how to direct active screening to those most at risk remains a topic of intense research. Our systematic review of literature evaluating the effects of geographically targeted tuberculosis screening interventions found three studies in low tuberculosis incidence settings, but none conducted in high tuberculosis incidence countries. We discuss open questions related to the use of spatially targeted approaches for active screening in countries where tuberculosis incidence is highest.

Protective effects of household-based TB interventions are robust to neighbourhood-level variation in exposure risk in Lima, Peru: a model-based analysis

Background

Untargeted active screening and treatment programmes for tuberculosis (TB) have not been shown to be more effective than passive screening and isoniazid preventive therapy (IPT) for reducing TB incidence. In this manuscript, we compare the efficacy of targeting screening and IPT on high-risk household contacts of diagnosed TB cases, with less-targeted active screening approaches in Lima, Peru.

Methods

We conducted a population-based prospective cohort study within households of TB cases in Lima. We identified all adults diagnosed with incident pulmonary TB from 2009 through 2012 at 106 participating public health centres (HC) within our catchment area of ∼3.3 million inhabitants. We estimated combined effects of community and household exposure on the risk of latent TB infection (LTBI) and incident TB disease. We used simulation modelling to assess the efficacy of TB screening programmes for reducing the risk of incident TB in these contacts.

Results

Individuals with household exposure to TB are more likely to present with LTBI and TB disease than those without this exposure, despite wide variation in community exposure. Simulations suggest that more cases are prevented by 1000 administrations of IPT to tuberculin skin test (TST)-positive household contacts of identified TB cases (30, 95% CI = 16,47) than from blanket screening and treatment in the community (7, 95% CI = 2,17).

Conclusions

Household exposure remains a major driver of incident TB risk among household contacts of identified TB cases. Targeting interventions on these individuals is likely to prevent more cases of TB than blanket screening of individuals in the community.

Optimizing community screening for tuberculosis: Spatial analysis of localized case finding from door-to-door screening for TB in an urban district of Ho Chi Minh City, Viet Nam

BACKGROUND

Tuberculosis (TB) is the deadliest infectious disease globally. Current case finding approaches may miss many people with TB or detect them too late.

DATA AND METHODS

This study was a retrospective, spatial analysis of routine TB surveillance and cadastral data in Go Vap district, Ho Chi Minh City. We geocoded TB notifications from 2011 to 2015 and calculated theoretical yields of simulated door-to-door screening in three concentric catchment areas (50m, 100m, 200m) and three notification window scenarios (one, two and four quarters) for each index case. We calculated average yields, compared them to published reference values and fit a GEE (Generalized Estimating Equation) linear regression model onto the data.

RESULTS

The sample included 3,046 TB patients. Adjusted theoretical yields in 50m, 100m and 200m catchment areas were 0.32% (95%CI: 0.27,0.37), 0.21% (95%CI: 0.14,0.29) and 0.17% (95%CI: 0.09,0.25), respectively, in the baseline notification window scenario. Theoretical yields in the 50m-catchment area for all notification window scenarios were significantly higher than a reference yield from literature. Yield was positively associated with treatment failure index cases (beta = 0.12, p = 0.001) and short-term inter-province migrants (beta = 0.06, p = 0.022), while greater distance to the DTU (beta = -0.02, p<0.001) was associated with lower yield.

CONCLUSIONS

This study is an example of inter-departmental collaboration and application of repurposed cadastral data to progress towards the end TB objectives. The results from Go Vap showed that the use of spatial analysis may be able to identify areas where targeted active case finding in Vietnam can help improve TB case detection.

Spatial Patterns of Extensively Drug-Resistant Tuberculosis Transmission in KwaZulu-Natal, South Africa

Background

Transmission is driving the global drug-resistant tuberculosis (TB) epidemic; nearly three-quarters of drug-resistant TB cases are attributable to transmission. Geographic patterns of disease incidence, combined with information on probable transmission links, can define the spatial scale of transmission and generate hypotheses about factors driving transmission patterns.

Methods

We combined whole-genome sequencing data with home Global Positioning System coordinates from 344 participants with extensively drug-resistant (XDR) TB in KwaZulu-Natal, South Africa, diagnosed from 2011 to 2014. We aimed to determine if genomically linked (difference of ≤5 single-nucleotide polymorphisms) cases lived close to one another, which would suggest a role for local community settings in transmission.

Results

One hundred eighty-two study participants were genomically linked, comprising 1084 case-pairs. The median distance between case-pairs' homes was 108 km (interquartile range, 64-162 km). Between-district, as compared to within-district, links accounted for the majority (912/1084 [84%]) of genomic links. Half (526 [49%]) of genomic links involved a case from Durban, the urban center of KwaZulu-Natal.

Conclusions

The high proportions of between-district links with Durban provide insight into possible drivers of province-wide XDR-TB transmission, including urban-rural migration. Further research should focus on characterizing the contribution of these drivers to overall XDR-TB transmission in KwaZulu-Natal to inform design of targeted strategies to curb the drug-resistant TB epidemic.

Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review

BACKGROUND

Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden.

METHODS

We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO ( CRD42016036655 ).

RESULTS

We identified 168 eligible studies with spatial methods used to describe the spatial distribution (n = 154), spatial clusters (n = 73), predictors of spatial patterns (n = 64), the role of congregate settings (n = 3) and the household (n = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff's spatial scan statistic followed by local Moran's I and Getis and Ord's local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined.

CONCLUSIONS

A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control.

Investigating spillover of multidrug-resistant tuberculosis from a prison: a spatial and molecular epidemiological analysis

BACKGROUND

Congregate settings may serve as institutional amplifiers of tuberculosis (TB) and multidrug-resistant tuberculosis (MDR-TB). We analyze spatial, epidemiological, and pathogen genetic data prospectively collected from neighborhoods surrounding a prison in Lima, Peru, where inmates experience a high risk of MDR-TB, to investigate the risk of spillover into the surrounding community.

METHODS

Using hierarchical Bayesian statistical modeling, we address three questions regarding the MDR-TB risk: (i) Does the excess risk observed among prisoners also extend outside the prison? (ii) If so, what is the magnitude, shape, and spatial range of this spillover effect? (iii) Is there evidence of additional transmission across the region?

RESULTS

The region of spillover risk extends for 5.47 km outside of the prison (95% credible interval: 1.38, 9.63 km). Within this spillover region, we find that nine of the 467 non-inmate patients (35 with MDR-TB) have MDR-TB strains that are genetic matches to strains collected from current inmates with MDR-TB, compared to seven out of 1080 patients (89 with MDR-TB) outside the spillover region (p values: 0.022 and 0.008). We also identify eight spatially aggregated genetic clusters of MDR-TB, four within the spillover region, consistent with local transmission among individuals living close to the prison.

CONCLUSIONS

We demonstrate a clear prison spillover effect in this population, which suggests that interventions in the prison may have benefits that extend to the surrounding community.

Using routinely collected laboratory data to identify high rifampicin-resistant tuberculosis burden communities in the Western Cape Province, South Africa: A retrospective spatiotemporal analysis

BACKGROUND

South Africa has the highest tuberculosis incidence globally (781/100,000), with an estimated 4.3% of cases being rifampicin resistant (RR). Control and elimination strategies will require detailed spatial information to understand where drug-resistant tuberculosis exists and why it persists in those communities. We demonstrate a method to enable drug-resistant tuberculosis monitoring by identifying high-burden communities in the Western Cape Province using routinely collected laboratory data.

METHODS AND FINDINGS

We retrospectively identified cases of microbiologically confirmed tuberculosis and RR-tuberculosis from all biological samples submitted for tuberculosis testing (n = 2,219,891) to the Western Cape National Health Laboratory Services (NHLS) between January 1, 2008, and June 30, 2013. Because the NHLS database lacks unique patient identifiers, we performed a series of record-linking processes to match specimen records to individual patients. We counted an individual as having a single disease episode if their positive samples came from within two years of each other. Cases were aggregated by clinic location (n = 302) to estimate the percentage of tuberculosis cases with rifampicin resistance per clinic. We used inverse distance weighting (IDW) to produce heatmaps of the RR-tuberculosis percentage across the province. Regression was used to estimate annual changes in the RR-tuberculosis percentage by clinic, and estimated average size and direction of change was mapped. We identified 799,779 individuals who had specimens submitted from mappable clinics for testing, of whom 222,735 (27.8%) had microbiologically confirmed tuberculosis. The study population was 43% female, the median age was 36 years (IQR 27-44), and 10,255 (4.6%, 95% CI: 4.6-4.7) cases had documented rifampicin resistance. Among individuals with microbiologically confirmed tuberculosis, 8,947 (4.0%) had more than one disease episode during the study period. The percentage of tuberculosis cases with rifampicin resistance documented among these individuals was 11.4% (95% CI: 10.7-12.0). Overall, the percentage of tuberculosis cases that were RR-tuberculosis was spatially heterogeneous, ranging from 0% to 25% across the province. Our maps reveal significant yearly fluctuations in RR-tuberculosis percentages at several locations. Additionally, the directions of change over time in RR-tuberculosis percentage were not uniform. The main limitation of this study is the lack of unique patient identifiers in the NHLS database, rendering findings to be estimates reliant on the accuracy of the person-matching algorithm.

CONCLUSIONS

Our maps reveal striking spatial and temporal heterogeneity in RR-tuberculosis percentages across this province. We demonstrate the potential to monitor RR-tuberculosis spatially and temporally with routinely collected laboratory data, enabling improved resource targeting and more rapid locally appropriate interventions.

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.

Prevalence of pyrazinamide resistance and Wayne assay performance analysis in a tuberculosis cohort in Lima, Peru

BACKGROUND

Multidrug-resistant tuberculosis (MDR-TB) regimens often contain pyrazinamide (PZA) even if susceptibility to the drug has not been confirmed. This gap is due to the limited availability and reliability of PZA susceptibility testing.

OBJECTIVES

To estimate the prevalence of PZA resistance using the Wayne assay among TB patients in Lima, Peru, to describe characteristics associated with PZA resistance and to compare the performance of Wayne with that of BACTEC™ MGIT™ 960.

METHODS

PZA susceptibility using the Wayne assay was tested in patients diagnosed with culture-positive pulmonary TB from September 2009 to August 2012. Factors associated with PZA resistance were evaluated. We compared the performance of the Wayne assay to that of MGIT 960 in a convenience sample.

RESULTS

The prevalence of PZA resistance was 6.6% (95%CI 5.8-7.5) among 3277 patients, and 47.7% (95%CI 42.7-52.6) among a subset of 405 MDR-TB patients. In multivariable analysis, MDR-TB (OR 86.0, 95%CI 54.0-136.9) and Latin American-Mediterranean lineage (OR 3.40, 95%CI 2.33-4.96) were associated with PZA resistance. The Wayne assay was in agreement with MGIT 960 in 83.9% of samples (κ 0.66, 95%CI 0.56-0.76).

CONCLUSION

PZA resistance was detected using the Wayne assay in nearly half of MDR-TB patients in Lima. This test can inform the selection and composition of regimens, especially those dependent on additional resistance.

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.

Genotyping and spatial analysis of pulmonary tuberculosis and diabetes cases in the state of Veracruz, Mexico

Background

Genotyping and georeferencing in tuberculosis (TB) have been used to characterize the distribution of the disease and occurrence of transmission within specific groups and communities.

Objective

The objective of this study was to test the hypothesis that diabetes mellitus (DM) and pulmonary TB may occur in spatial and molecular aggregations.

Material and methods

Retrospective cohort study of patients with pulmonary TB. The study area included 12 municipalities in the Sanitary Jurisdiction of Orizaba, Veracruz, México. Patients with acid-fast bacilli in sputum smears and/or Mycobacterium tuberculosis in sputum cultures were recruited from 1995 to 2010. Clinical (standardized questionnaire, physical examination, chest X-ray, blood glucose test and HIV test), microbiological, epidemiological, and molecular evaluations were carried out. Patients were considered “genotype-clustered” if two or more isolates from different patients were identified within 12 months of each other and had six or more IS6110 bands in an identical pattern, or < 6 bands with identical IS6110 RFLP patterns and spoligotype with the same spacer oligonucleotides. Residential and health care centers addresses were georeferenced. We used a Jeep hand GPS. The coordinates were transferred from the GPS files to ArcGIS using ArcMap 9.3. We evaluated global spatial aggregation of patients in IS6110-RFLP/ spoligotype clusters using global Moran´s I. Since global distribution was not random, we evaluated “hotspots” using Getis-Ord Gi* statistic. Using bivariate and multivariate analysis we analyzed sociodemographic, behavioral, clinic and bacteriological conditions associated with “hotspots”. We used STATA® v13.1 for all statistical analysis.

Results

From 1995 to 2010, 1,370 patients >20 years were diagnosed with pulmonary TB; 33% had DM. The proportion of isolates that were genotyped was 80.7% (n = 1105), of which 31% (n = 342) were grouped in 91 genotype clusters with 2 to 23 patients each; 65.9% of total clusters were small (2 members) involving 35.08% of patients. Twenty three (22.7) percent of cases were classified as recent transmission. Moran`s I indicated that distribution of patients in IS6110-RFLP/spoligotype clusters was not random (Moran`s I = 0.035468, Z value = 7.0, p = 0.00). Local spatial analysis showed statistically significant spatial aggregation of patients in IS6110-RFLP/spoligotype clusters identifying “hotspots” and “coldspots”. GI* statistic showed that the hotspot for spatial clustering was located in Camerino Z. Mendoza municipality; 14.6% (50/342) of patients in genotype clusters were located in a hotspot; of these, 60% (30/50) lived with DM. Using logistic regression the statistically significant variables associated with hotspots were: DM [adjusted Odds Ratio (aOR) 7.04, 95% Confidence interval (CI) 3.03–16.38] and attending the health center in Camerino Z. Mendoza (aOR18.04, 95% CI 7.35–44.28).

Conclusions

The combination of molecular and epidemiological information with geospatial data allowed us to identify the concurrence of molecular clustering and spatial aggregation of patients with DM and TB. This information may be highly useful for TB control programs.

Drug-Resistant tuberculosis - primary transmission and management

The DOTS strategy assisted global tuberculosis (TB) control, but was unable to prevent the emergence and spread of drug-resistant strains. Genomic evidence confirms the transmission of drug-resistant Mycobacterium tuberculosis strains in many different settings, indicative of epidemic spread. These findings emphasise the need for enhanced infection control measures in health care and congregate settings. Young children in TB endemic areas are particularly vulnerable. Although advances in TB drug and vaccine development are urgently needed, improved access to currently available preventive therapy and treatment for drug resistant TB could reduce the disease burden and adverse outcomes experienced by children. We review new insights into the transmission dynamics of drug resistant TB, the estimated disease burden in children and optimal management strategies to consider.

Research Roadmap for Tuberculosis Transmission Science: Where Do We Go From Here and How Will We Know When We're There?

High rates of tuberculosis transmission are driving the ongoing global tuberculosis epidemic, and there is a pressing need for research focused on understanding and, ultimately, halting transmission. The ongoing tuberculosis–human immunodeficiency virus (HIV) coepidemic and rising rates of drug-resistant tuberculosis in parts of the world add further urgency to this work. Success in this research will require a concerted, multidisciplinary effort on the part of tuberculosis scientists, clinicians, programs, and funders and must span the research spectrum from biomedical sciences to the social sciences, public health, epidemiology, cost-effectiveness analyses, and operations research. Heterogeneity of tuberculosis disease, both among individual patients and among communities, poses a substantial challenge to efforts to interrupt transmission. As such, it is likely that effective interventions to stop transmission will require a combination of approaches that will vary across different epidemiologic settings. This research roadmap summarizes key gaps in our current understanding of transmission, as laid out in the preceding articles in this series. We also hope that it will be a call to action for the global tuberculosis community to make a sustained commitment to tuberculosis transmission science. Halting transmission today is an essential step on the path to end tuberculosis tomorrow.

What We Know About Tuberculosis Transmission: An Overview

Tuberculosis remains a global health problem with an enormous burden of disease, estimated at 10.4 million new cases in 2015. To stop the tuberculosis epidemic, it is critical that we interrupt tuberculosis transmission. Further, the interventions required to interrupt tuberculosis transmission must be targeted to high-risk groups and settings. A simple cascade for tuberculosis transmission has been proposed in which (1) a source case of tuberculosis (2) generates infectious particles (3) that survive in the air and (4) are inhaled by a susceptible individual (5) who may become infected and (6) then has the potential to develop tuberculosis. Interventions that target these events will interrupt tuberculosis transmission and accelerate the decline in tuberculosis incidence and mortality. The purpose of this article is to provide a high-level overview of what is known about tuberculosis transmission, using the tuberculosis transmission cascade as a framework, and to set the scene for the articles in this series, which address specific aspects of tuberculosis transmission.

Combining molecular typing and spatial pattern analysis to identify areas of high tuberculosis transmission in a moderate-incidence county in Taiwan

In total, 303 randomly selected clinical Mycobacterium tuberculosis (MTB) isolates from 303 patients (collected January to December 2012) in central Taiwan were examined. The major lineages found were Beijing (N = 114, 37.62%), Haarlem (N = 76, 25.08%) and East African-Indian (EAI) (N = 42, 13.86%). Notably, younger persons (≤30 years old) were 6.58 times more likely to be infected with a Beijing genotype compared to older persons (>70 years) (p < 0.05). Combining molecular typing methods and geographical information system (GIS) analysis, we uncovered a twofold higher incidence of Beijing strains in a hotspot area (33%) compared to non-hotspot areas (17%). By 24 MIRU-VNTR typing, persons in clustered groups were 1.96 times more likely to be infected with a Beijing strain compared with non-clustered persons, suggesting recent spread and emergence of MTB. Finally, we observed a trend in which TB incidence increased as the density/concentration of analyzed environmental factors increased, suggesting that environmental factors are associated with TB transmission; however, only population density was found to be significantly associated with increased risk of TB (p < 0.05). Molecular typing methods combined with spatial analysis suggest possible TB transmission. Early intervention to interrupt transmission may be most effective if targeted to hot zones of TB.

The epidemiology, pathogenesis, transmission, diagnosis, and management of multidrug-resistant, extensively drug-resistant, and incurable tuberculosis

Global tuberculosis incidence has declined marginally over the past decade, and tuberculosis remains out of control in several parts of the world including Africa and Asia. Although tuberculosis control has been effective in some regions of the world, these gains are threatened by the increasing burden of multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis. XDR tuberculosis has evolved in several tuberculosis-endemic countries to drug-incurable or programmatically incurable tuberculosis (totally drug-resistant tuberculosis). This poses several challenges similar to those encountered in the pre-chemotherapy era, including the inability to cure tuberculosis, high mortality, and the need for alternative methods to prevent disease transmission. This phenomenon mirrors the worldwide increase in antimicrobial resistance and the emergence of other MDR pathogens, such as malaria, HIV, and Gram-negative bacteria. MDR and XDR tuberculosis are associated with high morbidity and substantial mortality, are a threat to health-care workers, prohibitively expensive to treat, and are therefore a serious public health problem. In this Commission, we examine several aspects of drug-resistant tuberculosis. The traditional view that acquired resistance to antituberculous drugs is driven by poor compliance and programmatic failure is now being questioned, and several lines of evidence suggest that alternative mechanisms-including pharmacokinetic variability, induction of efflux pumps that transport the drug out of cells, and suboptimal drug penetration into tuberculosis lesions-are likely crucial to the pathogenesis of drug-resistant tuberculosis. These factors have implications for the design of new interventions, drug delivery and dosing mechanisms, and public health policy. We discuss epidemiology and transmission dynamics, including new insights into the fundamental biology of transmission, and we review the utility of newer diagnostic tools, including molecular tests and next-generation whole-genome sequencing, and their potential for clinical effectiveness. Relevant research priorities are highlighted, including optimal medical and surgical management, the role of newer and repurposed drugs (including bedaquiline, delamanid, and linezolid), pharmacokinetic and pharmacodynamic considerations, preventive strategies (such as prophylaxis in MDR and XDR contacts), palliative and patient-orientated care aspects, and medicolegal and ethical issues.

Spatial patterns of multidrug resistant tuberculosis and relationships to socio-economic, demographic and household factors in northwest Ethiopia

Background

Understanding the geographical distribution of multidrug-resistant tuberculosis (MDR-TB) in high TB burden countries such as Ethiopia is crucial for effective control of TB epidemics in these countries, and thus globally. We present the first spatial analysis of multidrug resistant tuberculosis, and its relationship to socio-economic, demographic and household factors in northwest Ethiopia.

Methods

An ecological study was conducted using data on patients diagnosed with MDR-TB at the University of Gondar Hospital MDR-TB treatment centre, for the period 2010 to 2015. District level population data were extracted from the Ethiopia National and Regional Census Report. Spatial autocorrelation was explored using Moran’s I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate Poisson regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using a Bayesian Markov chain Monte Carlo (MCMC) simulation approach with Gibbs sampling, in WinBUGS.

Results

A total of 264 MDR-TB patients were included in the analysis. The overall crude incidence rate of MDR-TB for the six-year period was 3.0 cases per 100,000 population. The highest incidence rate was observed in Metema (21 cases per 100,000 population) and Humera (18 cases per 100,000 population) districts; whereas nine districts had zero cases. Spatial clustering of MDR-TB was observed in districts located in the Ethiopia-Sudan and Ethiopia-Eritrea border regions, where large numbers of seasonal migrants live. Spatial clustering of MDR-TB was positively associated with urbanization (RR: 1.02; 95%CI: 1.01, 1.04) and the percentage of men (RR: 1.58; 95% CI: 1.26, 1.99) in the districts; after accounting for these factors there was no residual spatial clustering.

Conclusion

Spatial clustering of MDR-TB, fully explained by demographic factors (urbanization and percent male), was detected in the border regions of northwest Ethiopia, in locations where seasonal migrants live and work. Cross-border initiatives including options for mobile TB treatment and follow up are important for the effective control of MDR-TB in the region.

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

Large outbreaks of tuberculosis (TB) represent a particular threat to disease control because they reflect multiple instances of active transmission. The extent to which long chains of transmission contribute to high TB incidence in London is unknown. We aimed to estimate the contribution of large clusters to the burden of TB in London and identify risk factors.

We identified TB patients resident in London notified between 2010 and 2014, and used 24-locus mycobacterial interspersed repetitive units–variable number tandem repeat strain typing data to classify cases according to molecular cluster size. We used spatial scan statistics to test for spatial clustering and analysed risk factors through multinomial logistic regression.

TB isolates from 7458 patients were included in the analysis. There were 20 large molecular clusters (with n>20 cases), comprising 795 (11%) of all cases; 18 (90%) large clusters exhibited significant spatial clustering. Cases in large clusters were more likely to be UK born (adjusted odds ratio 2.93, 95% CI 2.28–3.77), of black-Caribbean ethnicity (adjusted odds ratio 3.64, 95% CI 2.23–5.94) and have multiple social risk factors (adjusted odds ratio 3.75, 95% CI 1.96–7.16).

Large clusters of cases contribute substantially to the burden of TB in London. Targeting interventions such as screening in deprived areas and social risk groups, including those of black ethnicities and born in the UK, should be a priority for reducing transmission.

Large clusters contribute substantially to the burden of tuberculosis in London, indicating ongoing transmissionhttp://ow.ly/3xk23068P6w

High rates of multidrug-resistant and rifampicin-resistant tuberculosis among re-treatment cases: where do they come from?

BACKGROUND

Globally 3.9% of new and 21% of re-treatment tuberculosis (TB) cases are multidrug-resistant or rifampicin-resistant (MDR/RR), which is often interpreted as evidence that drug resistance results mainly from poor treatment adherence. This study aims to assess the respective contributions of the different causal pathways leading to MDR/RR-TB at re-treatment.

METHODS

We use a simple mathematical model to simulate progression between the different stages of disease and treatment for patients diagnosed with TB. The model is parameterised using region and country-specific TB disease burden data reported by the World Health Organization (WHO). The contributions of four separate causal pathways to MDR/RR-TB among re-treatment cases are estimated: I) initial drug-susceptible TB with resistance amplification during treatment; II) initial MDR/RR-TB inappropriately treated as drug-susceptible TB; III) MDR/RR-TB relapse despite appropriate treatment; and IV) re-infection with MDR/RR-TB.

RESULTS

At the global level, Pathways I, II, III and IV contribute 38% (28-49, 95% Simulation Interval), 44% (36-52, 95% SI), 6% (5-7, 95% SI) and 12% (7-19, 95% SI) respectively to the burden of MDR/RR-TB among re-treatment cases. Pathway II is dominant in the Western Pacific (74%; 67-80 95% SI), Eastern Mediterranean (68%; 60-74 95% SI) and European (53%; 48-59 95% SI) regions, while Pathway I makes the greatest contribution in the American (53%; 40-66 95% SI), African (43%; 28-61 95% SI) and South-East Asian (50%; 40-59 95% SI) regions.

CONCLUSIONS

Globally, failure to diagnose MDR/RR-TB at first presentation is the leading cause of the high proportion of MDR/RR-TB among re-treatment cases. These findings highlight the need for contextualised solutions to limit the impact and spread of MDR/RR-TB.

Epidemiology of Drug-Resistant Tuberculosis

As we move into the era of the Sustainable Development Goals (SDGs), the World Health Organization (WHO) has developed the End TB strategy 2016-2035 with a goal to end the global epidemic of tuberculosis (TB) by 2035. Achieving the targets laid out in the Strategy will require strengthening of the whole TB diagnosis and treatment cascade, including improved case detection, the establishment of universal drug susceptibility testing and rapid treatment initiation. An estimated 3.9% of new TB cases and 21% of previously treated cases had rifampicin-resistant (RR) or multidrug-resistant (MDR) TB in 2015. These levels have remained stable over time, although limited data are available from major high burden settings. In addition to the emergence of drug resistance due to inadequate treatment, there is growing evidence that direct transmission is a large contributor to the RR/MDR-TB epidemic. Only 340,000 of the estimated 580,000 incident cases of RR/MDR-TB were notified to WHO in 2015. Among these, only 125,000 were initiated on second-line treatment. RR/MDR-TB epidemics are likely to be driven by direct transmission. The most important risk factor for MDR-TB is a history of previous treatment. Other risk factors vary according to setting but can include hospitalisation, incarceration and HIV infection. Children have the same risk of MDR-TB as adults and represent a diagnostic and treatment challenge. Rapid molecular technologies have revolutionized the diagnosis of drug-resistant TB. Until capacity can be established to test every TB patient for rifampicin resistance, countries should focus on gradually expanding their coverage of testing. DNA sequencing technologies are being increasingly incorporated into patient management and drug resistance surveillance. They offer additional benefits over conventional culture-based phenotypic testing, including a faster turn-around time for results, assessment of resistance patterns to a range of drugs, and investigation of strain clustering and transmission.

Tuberculosis

Tuberculosis (TB) is an airborne infectious disease caused by organisms of the Mycobacterium tuberculosis complex. Although primarily a pulmonary pathogen, M. tuberculosis can cause disease in almost any part of the body. Infection with M. tuberculosis can evolve from containment in the host, in which the bacteria are isolated within granulomas (latent TB infection), to a contagious state, in which the patient will show symptoms that can include cough, fever, night sweats and weight loss. Only active pulmonary TB is contagious. In many low-income and middle-income countries, TB continues to be a major cause of morbidity and mortality, and drug-resistant TB is a major concern in many settings. Although several new TB diagnostics have been developed, including rapid molecular tests, there is a need for simpler point-of-care tests. Treatment usually requires a prolonged course of multiple antimicrobials, stimulating efforts to develop shorter drug regimens. Although the Bacillus Calmette-Guérin (BCG) vaccine is used worldwide, mainly to prevent life-threatening TB in infants and young children, it has been ineffective in controlling the global TB epidemic. Thus, efforts are underway to develop newer vaccines with improved efficacy. New tools as well as improved programme implementation and financing are necessary to end the global TB epidemic by 2035.