Molecular diversity of Mycobacterium tuberculosis strains in a slum area of Rio de Janeiro, Brazil

Mendes, Joycenea Matsuda; Machado, Silvia Maria Almeida; Lourenço, Maria Cristina da Silva; Ferreira, Rosa Maria Carvalho; Fonseca, Leila de Souza; Saad, Maria Helena Féres

doi:10.1590/s1806-37132008001200012

Cited by 5 publications

(5 citation statements)

References 15 publications

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“…Poly-drug resistance was observed in only one cluster by RAPD, but by MIRU, 50 per cent clusters showed poly-drug resistance. Higher clustering of MTB isolates from slums has been reported by several workers23. The lower rates of clustering (25-28.0%) found in our study may be because of inability to include all TB patients in the areas as well as that the infection may have been acquired from outside the slums.…”

Section: Discussioncontrasting

confidence: 70%

“…Several high TB incidence nations possess some hyperendemic ‘hotspots’ which contribute immensely to TB transmission2. Slums are one of these ‘hotspots’, characterized by poverty, overcrowding, concentration of lower socio-economic class and associated with multiple health problems, malnutrition, poorly ventilated houses and unhygienic environment3.…”

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confidence: 99%

“…The major diseases reported in these areas are TB (3.0%), blindness (1.9%) and leprosy (0.8%)6. High prevalence of TB in slums has been reported from India789 and western countries23. High prevalence of multidrug-resistant (MDR) TB has been reported from slums in Dhaka10 and Mumbai11, but no such information is available from slums of Jaipur.…”

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confidence: 99%

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Genetic diversity & drug sensitivity profiles of Mycobacterium tuberculosis isolates from two slums of Jaipur city, Rajasthan, India

et al. 2017

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Background & objectives:Slums are considered as hotspots of tuberculosis (TB). The study of genetic diversity and drug susceptibility profile of Mycobacterium tuberculosis (MTB) will help understand the transmission dynamics and can be used for better prevention and control of the disease. The aim of this study was to determine the drug susceptibility profiles and genetic diversity using the random amplified polymorphic DNA (RAPD) and mycobacterial interspersed repetitive units-variable number of tandem repeats (MIRU VNTR) of MTB isolates from sputum samples of pulmonary TB patients residing in the two slums of Jaipur city in Rajasthan, India.Methods:Sputum samples collected from pulmonary TB patients, their contacts and suspects during 2010-2012 were processed for microscopy and mycobacterial culture. Drug susceptibility testing was done by one per cent indirect proportion method on Lowenstein–Jensen medium for first-line anti-TB drugs rifampicin, isoniazid, ethambutol and streptomycin. MTB DNA was extracted by physicochemical method, and DNA fingerprinting was done by RAPD and MIRU VNTR analysis.Results:Among 175 sputum samples collected, 75 were positive (43.8%) for acid-fast bacilli, 83 for MTB culture and four were contaminated. Fifty two isolates (62.7%) were fully sensitive to four drugs, and five (6%) were multidrug resistant (MDR). RAPD analysis of 81 isolates revealed six clusters containing 23 (28.4%) isolates, and 58 (71.6%) were unique. MIRU VNTR analysis clustered 20 (24.7%) isolates, and 61 (75.3%) were unique.Interpretation & conclusions:About 62.7 per cent isolates from the sputum samples from slum areas were sensitive to four drugs; six per cent of isolates were MDR. Poly-resistance other than MDR was high (16%). About one-fourth isolates were clustered by either method. RAPD was rapid, less expensive but had low reproducibility. MIRU VNTR analysis could identify to greater extent the epidemiological link in the population studied.

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Section: Discussioncontrasting

confidence: 70%

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Genetic diversity & drug sensitivity profiles of Mycobacterium tuberculosis isolates from two slums of Jaipur city, Rajasthan, India

et al. 2017

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“…We therefore set three independent TB transmission rates: hotspot-to-hotspot, community-to-community, and the relative rate of cross-population (compared with within-population) transmission. A focused review of the literature (SI Materials and Methods) suggested that 30-50% of recent TB transmission at the city level is geographically clustered (25,26,28), but a small study in a Rio de Janeiro hotspot (29) found a higher rate of geographic aggregation (70%). Thus, for our baseline scenario, we estimated that a case of active TB in the hotspot would generate 0.5 secondary transmission events outside the hotspot for every transmission event occurring within the hotspot-a scenario that would lead to 67% geographic clustering among secondary cases if linked to the index case.…”

Section: Methodsmentioning

confidence: 99%

Heterogeneity in tuberculosis transmission and the role of geographic hotspots in propagating epidemics

Dowdy

Golub

Chaisson

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

137

132

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The importance of high-incidence "hotspots" to population-level tuberculosis (TB) incidence remains poorly understood. TB incidence varies widely across countries, but within smaller geographic areas (e.g., cities), TB transmission may be more homogeneous than other infectious diseases. We constructed a steady-state compartmental model of TB in Rio de Janeiro, replicating nine epidemiological variables (e.g., TB incidence) within 1% of their observed values. We estimated the proportion of TB transmission originating from a high-incidence hotspot (6.0% of the city's population, 16.5% of TB incidence) and the relative impact of TB control measures targeting the hotspot vs. the general community. If each case of active TB in the hotspot caused 0.5 secondary transmissions in the general community for each within-hotspot transmission, the 6.0% of people living in the hotspot accounted for 35.3% of city-wide TB transmission. Reducing the TB transmission rate (i.e., number of secondary infections per infectious case) in the hotspot to that in the general community reduced city-wide TB incidence by 9.8% in year 5, and 29.7% in year 50-an effect similar to halving time to diagnosis for the remaining 94% of the community. The importance of the hotspot to city-wide TB control depended strongly on the extent of TB transmission from the hotspot to the general community. High-incidence hotspots may play an important role in propagating TB epidemics. Achieving TB control targets in a hotspot containing 6% of a city's population can have similar impact on citywide TB incidence as achieving the same targets throughout the remaining community.infectious disease transmission | theoretical models | urban population | epidemiology | communicable disease control T uberculosis (TB) remains a leading infectious cause of morbidity and mortality, with over 8.8 million cases and 1.4 million deaths annually worldwide (1). TB is known to cluster in hyperendemic "hotspots" often characterized by crowding (2), poverty (3), HIV infection (4), and other social determinants (5). However, compared with other infectious diseases [e.g., sexually transmitted diseases (6) and vector-borne diseases (7)], where 20% of the population may generate 80% of transmission (7), TB transmission appears relatively more homogeneous. As a result, though spatial targeting is often advocated as an efficient method for achieving control of diseases such as malaria (8), the degree to which hotspots contribute to community-wide transmission of TB remains uncertain. The concept of geographically defined hotspots driving TB transmission has biological plausibility. Preventing TB cases in high-transmission areas (e.g., crowded urban slums, poorly ventilated hospitals) may avert many more secondary transmissions than similar efforts in low-transmission areas. Similarly, cases in high-transmission areas are more likely to represent recent infection (which is more amenable to intervention) than reactivation of latent disease (9). Prior explorations of heterogeneity in TB tra...

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“…Our coupling term is considerably lower than hotspot-to-community transmission term used in a modelling study of urban Rio de Janeiro, in which each infective in a hotspot region was assumed to cause 0.5 transmission events outside of the hotspot for each event caused within the hotspot [ 20 ]. However, it is important to note that this parameter in the Rio de Janeiro study was derived from a study that was based on a very small sample size ( n = 10) and geographical clustering was not statistically defined [ 35 ]. Rather, geographical clusters were defined by at least two cases sharing a common molecular structure and from the same or close neighbourhoods.…”

Section: Discussionmentioning

confidence: 99%

The role of geospatial hotspots in the spatial spread of tuberculosis in rural Ethiopia: a mathematical model

et al. 2018

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Geospatial tuberculosis (TB) hotspots are hubs of TB transmission both within and across community groups. We aimed to quantify the extent to which these hotspots account for the spatial spread of TB in a high-burden setting. We developed spatially coupled models to quantify the spread of TB from geographical hotspots to distant regions in rural Ethiopia. The population was divided into three ‘patches’ based on their proximity to transmission hotspots, namely hotspots, adjacent regions and remote regions. The models were fitted to 5-year notification data aggregated by the metapopulation structure. Model fitting was achieved with a Metropolis–Hastings algorithm using a Poisson likelihood to compare model-estimated notification rate with observed notification rates. A cross-coupled metapopulation model with assortative mixing by region closely fit to notification data as assessed by the deviance information criterion. We estimated 45 hotspot-to-adjacent regions transmission events and 2 hotspot-to-remote regions transmission events occurred for every 1000 hotspot-to-hotspot transmission events. Although the degree of spatial coupling was weak, the proportion of infections in the adjacent region that resulted from mixing with hotspots was high due to the high prevalence of TB cases in a hotspot region, with approximately 75% of infections attributable to hotspot contact. Our results suggest that the role of hotspots in the geospatial spread of TB in rural Ethiopia is limited, implying that TB transmission is primarily locally driven.

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Molecular diversity of Mycobacterium tuberculosis strains in a slum area of Rio de Janeiro, Brazil

Cited by 5 publications

References 15 publications

Genetic diversity & drug sensitivity profiles of Mycobacterium tuberculosis isolates from two slums of Jaipur city, Rajasthan, India

Genetic diversity & drug sensitivity profiles of Mycobacterium tuberculosis isolates from two slums of Jaipur city, Rajasthan, India

Heterogeneity in tuberculosis transmission and the role of geographic hotspots in propagating epidemics

The role of geospatial hotspots in the spatial spread of tuberculosis in rural Ethiopia: a mathematical model

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