The role of prisons in disseminating tuberculosis in Brazil: A genomic epidemiology study

Walter, Katharine S.; Santos, Paulo César Pereira dos; Gonçalves, Thais Oliveira; Silva, Bruna Oliveira da; Santos, Andréa da Silva; Leite, Alessandra de Cássia; Silva, Alessandra Moura da; Moreira, Flora Martinez Figueira; Oliveira, Roberto Dias de; Lemos, Everton Ferreira; Cunha, Eunice Atsuko Totumi; Liu, Yiran E.; Ko, Albert I.; Colijn, Caroline; Cohen, Ted; Mathema, Barun; Croda, Júlio; Andrews, Jason R

doi:10.1016/j.lana.2022.100186

Cited by 22 publications

(22 citation statements)

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“…Mtb sequence data from captured ES swabs allowed us to assign taxonomy and investigate phylogenetic relatedness between samples. All seven captured ES swab samples were assigned to lineage 4, the predominant lineage in the state, and nested within previously sampled genomic diversity from the state 30 ( Figure 3 ).…”

Section: Resultsmentioning

confidence: 69%

Detection of M. tuberculosis in the environment as a tool for identifying high-risk locations for tuberculosis transmission

Verma

Moreira

Morais

et al. 2022

Preprint

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Tuberculosis (TB) remains a leading cause of infectious mortality globally, yet most cases cannot be epidemiologically linked even with extensive contact investigations and whole genome sequencing. Consequently, there remain major gaps in our understanding of where and when M. tuberculosis (Mtb) exposures occur. We aimed to investigate whether Mtb can be detected in environments where TB patients were recently present, which could serve as a tool for characterizing exposure risk. We collected 389 environment surface (ES) swabs from two high TB burden prisons in Brazil, sampling 41 (n=340) cells occupied by individuals with active TB and 7 (n=49) cells from individuals without TB. In a subset of pooled swabs (n=6) and a swab from a cigarette lighter from the cell with active TB patients, we enriched Mtb DNA using RNA-bait hybrid capture assays and performed whole genome sequencing. In prison cells, Mtb DNA was detected in 55/340 (16%) of ES swabs from cells occupied by active TB patients and none (0/49) from cells in which no active TB patients were present. Mtb was detected in 13/16 (81%) prison cells occupied by the individuals with high/medium sputum Xpert Mtb load and 8/25 (32%) with low/very low sputum Mtb load (p=0.003). Seven hybrid capture samples had a median genomic coverage of 140X. rpoB mutations conferring high-level rifampin resistance were detected in 3/7 ES swabs. Mtb was frequently detectable in environments recently occupied by individuals with active TB. This approach could be applied in congregate environments to identify and characterize high-risk settings for Mtb exposure.

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Section: Resultsmentioning

confidence: 69%

Detection of M. tuberculosis in the environment as a tool for identifying high-risk locations for tuberculosis transmission

Verma

Moreira

Morais

et al. 2022

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“…Phylodynamic methods that estimate the parameters of an epidemiological model from genomic data are becoming available ( Kühnert et al, 2016 ; Didelot et al, 2017 ; Volz and Siveroni, 2018 ). However, these analyses have limits that cannot be overcome exclusively with phylogenetic data ( Louca et al, 2021 ), and in any case they are challenging with current MTB data sets ( Kühnert et al, 2018 ; Walter et al, 2022 ). Methodological advances, the integration of different types of data, and more complete and longer sampling series of MTB epidemics will allow to study epidemiological dynamics more accurately in the future.…”

Section: Discussionmentioning

confidence: 99%

“…For example, the method proposed by Stimson et al, 2019 groups strains based on a probabilistic model that takes into account the clock rate and the time of sampling. Other studies sidestepped the choice of one specific value by performing clustering multiple times with different thresholds, and comparing the results ( Holt et al, 2018 ; Meehan et al, 2018 ; Yang et al, 2018 ; López et al, 2020 ; Shuaib et al, 2020 ; Cox et al, 2021 , Liu et al, 2021 ; Walter et al, 2022 ; Yang et al, 2022 ). Despite their limitations, clustering methods are considered useful to study transmission dynamics in MTB.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Holt et al, 2018 found that in Vietnam, MTB Lineage 2 (L2) had higher clustering rates compared to MTB Lineage 4 (L4) and MTB Lineage 1 (L1), and interpreted these results as evidence for more frequent transmission of L2 strains, compared to L4 and L1 strains. Finally, in recent studies the distribution of terminal branch lengths (TBL) was used as a proxy for transmissibility in different MTB lineages ( Holt et al, 2018 ; Freschi et al, 2021 ; Walter et al, 2022 ), partially complementing classical clustering analyses. All these approaches are based on the assumption that increased transmission results in increased clustering rates and shorter terminal branches.…”

Section: Introductionmentioning

confidence: 99%

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Understanding drivers of phylogenetic clustering and terminal branch lengths distribution in epidemics of Mycobacterium tuberculosis

Menardo

2022

eLife

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Detecting factors associated with transmission is important to understand disease epidemics, and to design effective public health measures. Clustering and terminal branch lengths (TBL) analyses are commonly applied to genomic data sets of Mycobacterium tuberculosis (MTB) to identify sub-populations with increased transmission. Here, I used a simulation-based approach to investigate what epidemiological processes influence the results of clustering and TBL analyses, and whether differences in transmission can be detected with these methods. I simulated MTB epidemics with different dynamics (latency, infectious period, transmission rate, basic reproductive number R0, sampling proportion, sampling period, and molecular clock), and found that all considered factors, except for the length of the infectious period, affect the results of clustering and TBL distributions. I show that standard interpretations of this type of analyses ignore two main caveats: (1) clustering results and TBL depend on many factors that have nothing to do with transmission, (2) clustering results and TBL do not tell anything about whether the epidemic is stable, growing, or shrinking, unless all the additional parameters that influence these metrics are known, or assumed identical between sub-populations. An important consequence is that the optimal SNP threshold for clustering depends on the epidemiological conditions, and that sub-populations with different epidemiological characteristics should not be analyzed with the same threshold. Finally, these results suggest that different clustering rates and TBL distributions, that are found consistently between different MTB lineages, are probably due to intrinsic bacterial factors, and do not indicate necessarily differences in transmission or evolutionary success.

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“…Genomic approaches have dated introductions of M. tuberculosis and reconstructed patterns of historic spread across Central and South America 9,10 , estimated the contribution of recent transmission to incident TB cases 11 , reconstructed the emergence of resistance-associated mutations 12 , and inferred likely individual-level transmission events 13 . In Brazil 14 and Georgia 13 , for example, genomic approaches identified frequent transmission within prisons as well as evidence of spillover from prisons to surrounding communities. A single M. tuberculosis molecular study from Paraguay 15 on strains collected in 2003 reported that M. tuberculosis spoligotypes found across South America including the Latin-American (LAM) and Haarlem lineages were also common in Paraguay 15,16 .…”

Section: Introductionmentioning

confidence: 99%

Phylogeography and transmission ofM. tuberculosisspanning prisons and surrounding communities in Paraguay

Estigarribia¹,

Sequera

Aguirre

et al. 2022

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Recent rises in incident tuberculosis (TB) cases in Paraguay and the increasing concentration of TB within prisons highlight the urgency of targeting strategies to interrupt transmission and prevent new infections. However, whether specific cities or carceral institutions play a disproportionate role in transmission remains unknown. We conducted prospective genomic surveillance, sequencing 471 M. tuberculosis genomes, from inside and outside prisons in Paraguay's two largest urban areas, Asuncion and Ciudad del Este, from 2016 to 2021. We found genomic evidence of frequent recent transmission within prisons and transmission linkages spanning prisons and surrounding populations. We identified a signal of frequent M. tuberculosis spread between urban areas and marked recent population size expansion of the three largest genomic transmission clusters. Together, our findings highlight the urgency of strengthening TB control programs to reduce transmission risk within prisons, where, in Paraguay, incidence was 70 times that outside prisons in 2021.

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The role of prisons in disseminating tuberculosis in Brazil: A genomic epidemiology study

Cited by 22 publications

References 29 publications

Detection of M. tuberculosis in the environment as a tool for identifying high-risk locations for tuberculosis transmission

Detection of M. tuberculosis in the environment as a tool for identifying high-risk locations for tuberculosis transmission

Understanding drivers of phylogenetic clustering and terminal branch lengths distribution in epidemics of Mycobacterium tuberculosis

Phylogeography and transmission ofM. tuberculosisspanning prisons and surrounding communities in Paraguay

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