The epidemiology of tuberculosis in urban populations is changing. Combining conventional epidemiologic techniques with DNA fingerprinting of Mycobacterium tuberculosis can improve the understanding of how tuberculosis is transmitted.
We used restriction-fragment-length polymorphism (RFLP) analysis to study M. tuberculosis isolates from all patients reported to the tuberculosis registry in San Francisco during 1991 and 1992. These results were interpreted along with clinical, demographic, and epidemiologic data. Patients infected with the same strains were identified according to their RFLP patterns, and patients with identical patterns were grouped in clusters. Risk factors for being in a cluster were analyzed.
Of 473 patients studied, 191 appeared to have active tuberculosis as a result of recent infection. Tracing of patients' contacts with the use of conventional methods identified links among only 10 percent of these patients. DNA fingerprinting, however, identified 44 clusters, 20 of which consisted of only 2 persons and the largest of which consisted of 30 persons. In patients under 60 years of age, Hispanic ethnicity (odds ratio, 3.3; P = 0.02), black race (odds ratio, 2.3; P = 0.02), birth in the United States (odds ratio, 5.8; P < 0.001), and a diagnosis of the acquired immunodeficiency syndrome (odds ratio, 1.8; P = 0.04) were independently associated with being in a cluster. Further study of patients in clusters confirmed that poorly compliant patients with infectious tuberculosis have a substantial adverse effect on the control of this disease.
Despite an efficient tuberculosis-control program, nearly a third of new cases of tuberculosis in San Francisco are the result of recent infection. Few of these instances of transmission are identified by conventional contact tracing.
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[Show abstract][Hide abstract] ABSTRACT: Understanding the transmission dynamics of infectious diseases is important for both biological research and public health applications. It has been widely demonstrated that statistical modeling provides a ﬁrm basis for inferring relevant epidemiological quantities from incidence and molecular data. However, the complexity of transmission dynamic models causes two challenges: Firstly, the likelihood function of the models is generally not computable and computationally intensive simulation-based inference methods need to be employed. Secondly, the model may not be fully identiﬁable from the available data. While the ﬁrst diﬃculty can be tackled by computational and algorithmic advances, the second obstacle is more fundamental. Identiﬁability issues may lead to inferences which are more driven by the prior assumptions than the data themselves. We here consider a popular and relatively simple, yet analytically intractable model for the spread of tuberculosis based on classical IS6110 ﬁngerprinting data. We report on the identiﬁability of the model, presenting also some methodological advances regarding the inference. Using likelihood approximations, it is shown that the reproductive value cannot be identiﬁed from the data available and that the posterior distributions obtained in previous work have likely been substantially dominated by the assumed prior distribution. Further, we show that the inferences are inﬂuenced by the assumed infectious population size which has generally been kept ﬁxed in previous work. We demonstrate that the infectious population size can be inferred if the remaining epidemiological parameters are already known with suﬃcient precision.
"email@example.com Since the 1990s, methods such as RFLP based on the insertion element IS6110 (van Embden et al., 1993) have been used to distinguish clusters of patients with shared DNA-fingerprint patterns, suggesting recent transmission (Small et al., 1994), but within the clusters, these methods cannot distinguish who transmitted to whom. Whole genome sequencing provides far greater resolution, and if data are collected in a whole population over several years, single nucleotide polymorphisms (SNPs) can be used to construct transmission networks (Bryant et al., 2013; Walker et al., 2013, 2014). "
[Show abstract][Hide abstract] ABSTRACT: To improve understanding of the factors influencing tuberculosis transmission and the role of pathogen variation, we sequenced all available specimens from patients diagnosed over 15 years in a whole district in Malawi. Mycobacterium tuberculosis lineages were assigned and transmission networks constructed, allowing ≤10 single nucleotide polymorphisms (SNPs) difference. We defined disease as due to recent infection if the network-determined source was within 5 years, and assessed transmissibility from forward transmissions resulting in disease. High-quality sequences were available for 1687 disease episodes (72% of all culture-positive episodes): 66% of patients linked to at least one other patient. The between-patient mutation rate was 0.26 SNPs/year (95% CI 0.21-0.31). We showed striking differences by lineage in the proportion of disease due to recent transmission and in transmissibility (highest for lineage-2 and lowest for lineage-1) that were not confounded by immigration, HIV status or drug resistance. Transmissions resulting in disease decreased markedly over time.
"The increased risk of active TB among HIV-infected persons was initially mainly attributed to an increased risk of reactivation of a latent infection (Selwyn et al. 1989; Girardi et al. 2000); however, a growing body of evidence suggests that both situations are present and should be carefully analyzed for different countries/populations . Studies performed in urban settings in the United States indicated that almost two-thirds of M. tuberculosis isolates from HIV-infected patients appeared in clusters, suggesting increased recent infections (Small et al. 1994; Allwood et al. 1997). Further support for this suggestion was provided by DNA fingerprinting of nosocomial TB outbreaks, including transmission of multidrug-resistant (MDR) strains (Beck-Sague et al. 1992; Daley et al. 1992; Edlin et al. 1992; Coronado et al. 1993). "