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

Abstract

Background: Globally, prisons are high-incidence settings for tuberculosis. Yet the role of prisons as reservoirs of M. tuberculosis, propagating epidemics through spillover to surrounding communities, has been difficult to measure directly.

Methods: To quantify the role of prisons in driving wider community M. tuberculosis transmission, we conducted prospective genomic surveillance in Central West Brazil from 2014 to 2019. We whole genome sequenced 1152 M. tuberculosis isolates collected during active and passive surveillance inside and outside prisons and linked genomes to detailed incarceration histories. We applied multiple phylogenetic and genomic clustering approaches and inferred timed transmission trees.

Findings: M. tuberculosis sequences from incarcerated and non-incarcerated people were closely related in a maximum likelihood phylogeny. The majority (70.8%; 46/65) of genomic clusters including people with no incarceration history also included individuals with a recent history of incarceration. Among cases in individuals with no incarceration history, 50.6% (162/320) were in clusters that included individuals with recent incarceration history, suggesting that transmission chains often span prisons and communities. We identified a minimum of 18 highly probable spillover events, M. tuberculosis transmission from people with a recent incarceration history to people with no prior history of incarceration, occurring in the state's four largest cities and across sampling years. We additionally found that frequent transfers of people between the state's prisons creates a highly connected prison network that likely disseminates M. tuberculosis across the state.

Interpretation: We developed a framework for measuring spillover from high-incidence environments to surrounding communities by integrating genomic and spatial information. Our findings indicate that, in this setting, prisons serve not only as disease reservoirs, but also disseminate M. tuberculosis across highly connected prison networks, both amplifying and propagating M. tuberculosis risk in surrounding communities.

Funding: Brazil's National Council for Scientific and Technological Development and US National Institutes of Health.

Keywords: Disease reservoir; Epidemiology; Genomics; Prisons; Spillover; Tuberculosis.

Figure 1

Tuberculosis is increasingly concentrated within prisons in Mato Grosso do Sul, Brazil. (a) Map of Brazil with states colored by the 2019 incarceration rate with Mato Grosso do Sul outlined in black. (b) Map of Mato Grosso do Sul state with the cities with passive surveillance only and where active surveillance was additionally conducted within prisons. (c) The incarcerated population size in Mato Grosso do Sul grew by 142% from 2005 to 2020, increasing from 7891 to 19,065 people. (d) Mato Grosso do Sul state's annual new and retreatment tuberculosis notifications, colored by incarceration status and (e) the notification rate per 100,000 people for the incarcerated population and non-incarcerated populations from 2009 to 2019. The y-axis is log-scaled. The mean tuberculosis notification rate was more than 46 times greater among the incarcerated population compared to the non-incarcerated population. The green and yellow bars (d) and (e) indicate the period of active surveillance in prisons in Campo Grande and Dourados, respectively.

Figure 2

M. tuberculosis isolates from incarcerated and non-incarcerated people are closely related in Mato Grosso do Sul, Brazil. A maximum likelihood phylogeny of 932 tuberculosis isolates from Lineage 4 inferred from a multiple sequence alignment of 19,753 SNPs and rooted on two Lineage 1 isolates from this study. Branch lengths are in units of substitutions per site. Branches are colored by sub-lineage. From the inside, rings are colored by incarceration status at time of TB notification, antimicrobial resistance prediction, and genomic cluster (Methods). “Other” resistance indicates resistance to at least one antibiotic other than isoniazid or rifampicin. The clade containing the largest predicted genomic cluster (Cluster 5), including 170 isolates, is highlighted in purple.

Figure 3

A single, recently emerged M. tuberculosis clone spans prisons and the community across the major cities Mato Grosso do Sul state. (a) A Bayesian time-calibrated phylogeny of the largest sampled genomic cluster of 170 isolates. The cluster emerged approximately 23 years before the most recently sampled isolate, with a most recent common ancestor in 1996 (95% HPD: 1989–2003). Tip point color indicates patient's incarceration status at the time of tuberculosis notification. Annotation bar colors indicate city. Grey error bars indicate the 95% Bayesian highest posterior density intervals for node date. Clade posterior support values are shown on the middle of branches for clades with posterior support > 0.5. (b) A haplotype network of the single largest genomic cluster, including 170 isolates. Nodes represent unique haplotypes and are scaled to number of isolates. Points along branches indicate SNP distances between haplotypes. Node color indicates incarceration status at the time of diagnosis.

Figure 4

Prisons disseminate tuberculosis through the frequent movement of people between prisons. (a) Incarceration locates people within highly connected contact networks. Map of Mato Grosso do Sul state with orange points indicating the 21 prisons which most frequently transfer people between prisons. Edges are colored by the mean number of yearly transfers made between prisons from 2015 to 2018, including transfers in both directions. Edges were drawn between prison pairs with more than 10 transfers in the study period. Transfers between prisons within a city are not shown. (b) An M. tuberculosis clone (depicted in Figure 3) spreads throughout multiple prisons, jails, and the community. Each line represents an individual patient infected with an isolate in the largest genomic cluster, ordered by notification date. Line color indicates patient location, determined by matching patient names with the state incarceration database (Methods). Points indicate TB notification dates; point color indicates patient location at the time of TB notification. Individuals with notification dates after December 31, 2018 are not shown.