A Sign of Superspreading in Tuberculosis: Highly Skewed Distribution of Genotypic Cluster Sizes

Mycobacterium tuberculosis cough aerosol culture status associates with host characteristics and inflammatory profiles

Interrupting transmission events is critical to tuberculosis control. Cough-generated aerosol cultures predict tuberculosis transmission better than microbiological or clinical markers. We hypothesize that highly infectious individuals with pulmonary tuberculosis (positive for cough aerosol cultures) have elevated inflammatory markers and unique transcriptional profiles compared to less infectious individuals. We performed a prospective, longitudinal study using cough aerosol sampling system. We enrolled 142 participants with treatment-naïve pulmonary tuberculosis in Kenya and assessed the association of clinical, microbiologic, and immunologic characteristics with Mycobacterium tuberculosis aerosolization and transmission in 129 household members. Contacts of the forty-three aerosol culture-positive participants (30%) are more likely to have a positive interferon-gamma release assay (85% vs 53%, P = 0.006) and higher median IFNγ level (P < 0.001, 4.28 IU/ml (1.77-5.91) vs. 0.71 (0.01-3.56)) compared to aerosol culture-negative individuals. We find that higher bacillary burden, younger age, larger mean upper arm circumference, and host inflammatory profiles, including elevated serum C-reactive protein and lower plasma TNF levels, associate with positive cough aerosol cultures. Notably, we find pre-treatment whole blood transcriptional profiles associate with aerosol culture status, independent of bacillary load. These findings suggest that tuberculosis infectiousness is associated with epidemiologic characteristics and inflammatory signatures and that these features may identify highly infectious persons.

Tuberculosis Infectiousness is Associated with Distinct Clinical and Inflammatory Profiles

Interrupting transmission events to prevent new acquisition of infection and disease is a critical part of tuberculosis (TB) control efforts. However, knowledge gaps in understanding the biology and determinants of TB transmission, including poor estimates of individual infectiousness and the lack of accurate and convenient biomarkers, undermine efforts to develop interventions. Cough-generated aerosol cultures have been found to predict TB transmission better than any microbiological or clinical markers in cohorts from Uganda and Brazil. We hypothesized that highly infectious individuals with pulmonary TB (defined as positive for cough aerosol cultures) have elevated inflammatory markers and unique transcriptional profiles compared to less infectious individuals (negative for cough aerosol cultures). We performed a prospective, longitudinal study using a cough aerosol sampling system as in other studies. We enrolled 142 participants with treatment-naïve pulmonary TB in Nairobi, Kenya, and assessed the association of clinical, microbiologic, and immunologic characteristics with Mtb aerosolization and transmission in 143 household members. Contacts of the forty-three aerosol culture-positive participants (30%) were more likely to have a positive IGRA (85% vs 53%, P = 0.005) and a higher median IGRA IFNγ level (P < 0.001, median 4.25 IU/ml (0.90-5.91) vs. 0.71 (0.01-3.56)) compared to aerosol culture-negative individuals. We found that higher bacillary burden, younger age, and larger mean upper arm circumference were associated with positive aerosol cultures. In addition, novel host inflammatory profiles, including elevated serum C-reactive protein and sputum cytokines, were associated with aerosol culture status. Notably, we found pre-treatment whole blood transcriptional profiles associated with aerosol culture status, independent of bacillary load. Together, these findings suggest that TB infectiousness is associated with epidemiologic characteristics and inflammatory signatures and that these features may be used to identify highly infectious persons. These results provide new public health tools and insights into TB pathogenesis.

Spatial modeling of Mycobacterium tuberculosis transmission with dyadic genetic relatedness data

Understanding factors that contribute to the increased likelihood of pathogen transmission between two individuals is important for infection control. However, analyzing measures of pathogen relatedness to estimate these associations is complicated due to correlation arising from the presence of the same individual across multiple dyadic outcomes, potential spatial correlation caused by unmeasured transmission dynamics, and the distinctive distributional characteristics of some of the outcomes. We develop two novel hierarchical Bayesian spatial methods for analyzing dyadic pathogen genetic relatedness data, in the form of patristic distances and transmission probabilities, that simultaneously address each of these complications. Using individual-level spatially correlated random effect parameters, we account for multiple sources of correlation between the outcomes as well as other important features of their distribution. Through simulation, we show the limitations of existing approaches in terms of estimating key associations of interest, and the ability of the new methodology to correct for these issues across datasets with different levels of correlation. All methods are applied to Mycobacterium tuberculosis data from the Republic of Moldova, where we identify previously unknown factors associated with disease transmission and, through analysis of the random effect parameters, key individuals, and areas with increased transmission activity. Model comparisons show the importance of the new methodology in this setting. The methods are implemented in the R package GenePair.

Assessing vaccine-mediated protection in an ultra-low dose Mycobacterium tuberculosis murine model

Despite widespread immunization with Bacille-Calmette-Guérin (BCG), the only currently licensed tuberculosis (TB) vaccine, TB remains a leading cause of mortality globally. There are many TB vaccine candidates in the developmental pipeline, but the lack of a robust animal model to assess vaccine efficacy has hindered our ability to prioritize candidates for human clinical trials. Here we use a murine ultra-low dose (ULD) Mycobacterium tuberculosis (Mtb) challenge model to assess protection conferred by BCG vaccination. We show that BCG confers a reduction in lung bacterial burdens that is more durable than that observed after conventional dose challenge, curbs Mtb dissemination to the contralateral lung, and, in a small percentage of mice, prevents detectable infection. These findings are consistent with the ability of human BCG vaccination to mediate protection, particularly against disseminated disease, in specific human populations and clinical settings. Overall, our findings demonstrate that the ultra-low dose Mtb infection model can measure distinct parameters of immune protection that cannot be assessed in conventional dose murine infection models and could provide an improved platform for TB vaccine testing.

Quantifying individual-level heterogeneity in infectiousness and susceptibility through household studies

The spread of SARS-CoV-2, like that of many other pathogens, is governed by heterogeneity. "Superspreading," or "over-dispersion," is an important factor in transmission, yet it is hard to quantify. Estimates from contact tracing data are prone to potential biases due to the increased likelihood of detecting large clusters of cases, and may reflect variation in contact behavior more than biological heterogeneity. In contrast, the average number of secondary infections per contact is routinely estimated from household surveys, and these studies can minimize biases by testing all members of a household. However, the models used to analyze household transmission data typically assume that infectiousness and susceptibility are the same for all individuals or vary only with predetermined traits such as age. Here we develop and apply a combined forward simulation and inference method to quantify the degree of inter-individual variation in both infectiousness and susceptibility from observations of the distribution of infections in household surveys. First, analyzing simulated data, we show our method can reliably ascertain the presence, type, and amount of these heterogeneities given data from a sufficiently large sample of households. We then analyze a collection of household studies of COVID-19 from diverse settings around the world, and find strong evidence for large heterogeneity in both the infectiousness and susceptibility of individuals. Our results also provide a framework to improve the design of studies to evaluate household interventions in the presence of realistic heterogeneity between individuals.

Quantifying Mycobacterium tuberculosis Transmission Dynamics Across Global Settings: A Systematic Analysis

The degree to which individual heterogeneity in the production of secondary cases ("superspreading") affects tuberculosis (TB) transmission has not been systematically studied. We searched for population-based or surveillance studies in which whole genome sequencing was used to estimate TB transmission and in which the size distributions of putative TB transmission clusters were enumerated. We fitted cluster-size-distribution data to a negative binomial branching process model to jointly infer the transmission parameters $R$ (the reproduction number) and the dispersion parameter, $k$, which quantifies the propensity of superspreading in a population (generally, lower values of $k$ ($<1.0$) suggest increased heterogeneity). Of 4,796 citations identified in our initial search, 9 studies from 8 global settings met the inclusion criteria (n = 5 studies of all TB; n = 4 studies of drug-resistant TB). Estimated $R$ values (range, 0.10-0.73) were below 1.0, consistent with declining epidemics in the included settings; estimated $k$ values were well below 1.0 (range, 0.02-0.48), indicating the presence of substantial individual-level heterogeneity in transmission across all settings. We estimated that a minority of cases (range, 2%-31%) drive the majority (80%) of ongoing TB transmission at the population level. Identifying sources of heterogeneity and accounting for them in TB control may have a considerable impact on mitigating TB transmission.

Sweepstakes reproductive success via pervasive and recurrent selective sweeps

Highly fecund natural populations characterized by high early mortality abound, yet our knowledge about their recruitment dynamics is somewhat rudimentary. This knowledge gap has implications for our understanding of genetic variation, population connectivity, local adaptation, and the resilience of highly fecund populations. The concept of sweepstakes reproductive success, which posits a considerable variance and skew in individual reproductive output, is key to understanding the distribution of individual reproductive success. However, it still needs to be determined whether highly fecund organisms reproduce through sweepstakes and, if they do, the relative roles of neutral and selective sweepstakes. Here, we use coalescent-based statistical analysis of population genomic data to show that selective sweepstakes likely explain recruitment dynamics in the highly fecund Atlantic cod. We show that the Kingman coalescent (modelling no sweepstakes) and the Xi-Beta coalescent (modelling random sweepstakes), including complex demography and background selection, do not provide an adequate fit for the data. The Durrett-Schweinsberg coalescent, in which selective sweepstakes result from recurrent and pervasive selective sweeps of new mutations, offers greater explanatory power. Our results show that models of sweepstakes reproduction and multiple-merger coalescents are relevant and necessary for understanding genetic diversity in highly fecund natural populations. These findings have fundamental implications for understanding the recruitment variation of fish stocks and general evolutionary genomics of high-fecundity organisms.

Quantifying individual-level heterogeneity in infectiousness and susceptibility through household studies

The spread of SARS-CoV-2, like that of many other pathogens, is governed by heterogeneity. "Superspreading," or "over-dispersion," is an important factor in transmission, yet it is hard to quantify. Estimates from contact tracing data are prone to potential biases due to the increased likelihood of detecting large clusters of cases, and may reflect variation in contact behavior more than biological heterogeneity. In contrast, the average number of secondary infections per contact is routinely estimated from household surveys, and these studies can minimize biases by testing all members of a household. However, the models used to analyze household transmission data typically assume that infectiousness and susceptibility are the same for all individuals or vary only with predetermined traits such as age. Here we develop and apply a combined forward simulation and inference method to quantify the degree of inter-individual variation in both infectiousness and susceptibility from observations of the distribution of infections in household surveys. First, analyzing simulated data, we show our method can reliably ascertain the presence, type, and amount of these heterogeneities with data from a sufficiently large sample of households. We then analyze a collection of household studies of COVID-19 from diverse settings around the world, and find strong evidence for large heterogeneity in both the infectiousness and susceptibility of individuals. Our results also provide a framework to improve the design of studies to evaluate household interventions in the presence of realistic heterogeneity between individuals.

Model-based Analysis of Tuberculosis Genotype Clusters in the United States Reveals High Degree of Heterogeneity in Transmission and State-level Differences Across California, Florida, New York, and Texas

BACKGROUND

Reductions in tuberculosis (TB) transmission have been instrumental in lowering TB incidence in the United States. Sustaining and augmenting these reductions are key public health priorities.

METHODS

We fit mechanistic transmission models to distributions of genotype clusters of TB cases reported to the Centers for Disease Control and Prevention during 2012-2016 in the United States and separately in California, Florida, New York, and Texas. We estimated the mean number of secondary cases generated per infectious case (R0) and individual-level heterogeneity in R0 at state and national levels and assessed how different definitions of clustering affected these estimates.

RESULTS

In clusters of genotypically linked TB cases that occurred within a state over a 5-year period (reference scenario), the estimated R0 was 0.29 (95% confidence interval [CI], .28-.31) in the United States. Transmission was highly heterogeneous; 0.24% of simulated cases with individual R0 >10 generated 19% of all recent secondary transmissions. R0 estimate was 0.16 (95% CI, .15-.17) when a cluster was defined as cases occurring within the same county over a 3-year period. Transmission varied across states: estimated R0s were 0.34 (95% CI, .3-.4) in California, 0.28 (95% CI, .24-.36) in Florida, 0.19 (95% CI, .15-.27) in New York, and 0.38 (95% CI, .33-.46) in Texas.

CONCLUSIONS

TB transmission in the United States is characterized by pronounced heterogeneity at the individual and state levels. Improving detection of transmission clusters through incorporation of whole-genome sequencing and identifying the drivers of this heterogeneity will be essential to reducing TB transmission.

Characterizing tuberculosis transmission dynamics in high-burden urban and rural settings

Mycobacterium tuberculosis transmission dynamics in high-burden settings are poorly understood. Growing evidence suggests transmission may be characterized by extensive individual heterogeneity in secondary cases (i.e., superspreading), yet the degree and influence of such heterogeneity is largely unknown and unmeasured in high burden-settings. We conducted a prospective, population-based molecular epidemiology study of TB transmission in both an urban and rural setting of Botswana, one of the highest TB burden countries in the world. We used these empirical data to fit two mathematical models (urban and rural) that jointly quantified both the effective reproductive number, [Formula: see text], and the propensity for superspreading in each population. We found both urban and rural populations were characterized by a high degree of individual heterogeneity, however such heterogeneity disproportionately impacted the rural population: 99% of secondary transmission was attributed to only 19% of infectious cases in the rural population compared to 60% in the urban population and the median number of incident cases until the first outbreak of 30 cases was only 32 for the rural model compared to 791 in the urban model. These findings suggest individual heterogeneity plays a critical role shaping local TB epidemiology within subpopulations.

A Cluster-based Method to Quantify Individual Heterogeneity in Tuberculosis Transmission

BACKGROUND

Recent evidence suggests transmission of Mycobacterium tuberculosis (Mtb) may be characterized by extreme individual heterogeneity in secondary cases (i.e., few cases account for the majority of transmission). Such heterogeneity implies outbreaks are rarer but more extensive and has profound implications in infectious disease control. However, discrete person-to-person transmission events in tuberculosis (TB) are often unobserved, precluding our ability to directly quantify individual heterogeneity in TB epidemiology.

METHODS

We used a modified negative binomial branching process model to quantify the extent of individual heterogeneity using only observed transmission cluster size distribution data (i.e., the simple sum of all cases in a transmission chain) without knowledge of individual-level transmission events. The negative binomial parameter k quantifies the extent of individual heterogeneity (generally, indicates extensive heterogeneity, and as transmission becomes more homogenous). We validated the robustness of the inference procedure considering common limitations affecting cluster size data. Finally, we demonstrate the epidemiologic utility of this method by applying it to aggregate US molecular surveillance data from the US Centers for Disease Control and Prevention.

RESULTS

The cluster-based method reliably inferred k using TB transmission cluster data despite a high degree of bias introduced into the model. We found that the TB transmission in the United States was characterized by a high propensity for extensive outbreaks (; 95% confidence interval = 0.09, 0.10).

CONCLUSIONS

The proposed method can accurately quantify critical parameters that govern TB transmission using simple, more easily obtainable cluster data to improve our understanding of TB epidemiology.

Early alveolar macrophage response and IL-1R-dependent T cell priming determine transmissibility of Mycobacterium tuberculosis strains

Mechanisms underlying variability in transmission of Mycobacterium tuberculosis strains remain undefined. By characterizing high and low transmission strains of M.tuberculosis in mice, we show here that high transmission M.tuberculosis strain induce rapid IL-1R-dependent alveolar macrophage migration from the alveolar space into the interstitium and that this action is key to subsequent temporal events of early dissemination of bacteria to the lymph nodes, Th1 priming, granulomatous response and bacterial control. In contrast, IL-1R-dependent alveolar macrophage migration and early dissemination of bacteria to lymph nodes is significantly impeded in infection with low transmission M.tuberculosis strain; these events promote the development of Th17 immunity, fostering neutrophilic inflammation and increased bacterial replication. Our results suggest that by inducing granulomas with the potential to develop into cavitary lesions that aids bacterial escape into the airways, high transmission M.tuberculosis strain is poised for greater transmissibility. These findings implicate bacterial heterogeneity as an important modifier of TB disease manifestations and transmission.

Multiple Merger Genealogies in Outbreaks of Mycobacterium tuberculosis

The Kingman coalescent and its developments are often considered among the most important advances in population genetics of the last decades. Demographic inference based on coalescent theory has been used to reconstruct the population dynamics and evolutionary history of several species, including Mycobacterium tuberculosis (MTB), an important human pathogen causing tuberculosis. One key assumption of the Kingman coalescent is that the number of descendants of different individuals does not vary strongly, and violating this assumption could lead to severe biases caused by model misspecification. Individual lineages of MTB are expected to vary strongly in reproductive success because 1) MTB is potentially under constant selection due to the pressure of the host immune system and of antibiotic treatment, 2) MTB undergoes repeated population bottlenecks when it transmits from one host to the next, and 3) some hosts show much higher transmission rates compared with the average (superspreaders).

Here, we used an approximate Bayesian computation approach to test whether multiple-merger coalescents (MMC), a class of models that allow for large variation in reproductive success among lineages, are more appropriate models to study MTB populations. We considered 11 publicly available whole-genome sequence data sets sampled from local MTB populations and outbreaks and found that MMC had a better fit compared with the Kingman coalescent for 10 of the 11 data sets. These results indicate that the null model for analyzing MTB outbreaks should be reassessed and that past findings based on the Kingman coalescent need to be revisited.

Ultra-low Dose Aerosol Infection of Mice with Mycobacterium tuberculosis More Closely Models Human Tuberculosis

Tuberculosis (TB) is a heterogeneous disease manifesting in a subset of individuals infected with aerosolized Mycobacterium tuberculosis (Mtb). Unlike human TB, murine infection results in uniformly high lung bacterial burdens and poorly organized granulomas. To develop a TB model that more closely resembles human disease, we infected mice with an ultra-low dose (ULD) of between 1-3 founding bacteria, reflecting a physiologic inoculum. ULD-infected mice exhibited highly heterogeneous bacterial burdens, well-circumscribed granulomas that shared features with human granulomas, and prolonged Mtb containment with unilateral pulmonary infection in some mice. We identified blood RNA signatures in mice infected with an ULD or a conventional Mtb dose (50-100 CFU) that correlated with lung bacterial burdens and predicted Mtb infection outcomes across species, including risk of progression to active TB in humans. Overall, these findings highlight the potential of the murine TB model and show that ULD infection recapitulates key features of human TB.

Genotyping indicates marked heterogeneity of tuberculosis transmission in the United States, 2009–2018

Heterogeneity in the number of secondary tuberculosis (TB) cases per source case, the effective reproductive number, R, is important in modelling prevention strategies' impact on incidence.

We estimated mean R (R_m) and calculate the dispersion parameter of this distribution, k, using surveillance and genotyping data for U.S. cases during 2009–2018. We modelled transmission assuming cases in a cluster have matching genotypes and share characteristics related to geography, temporal proximity (i.e. serial interval) and time since U.S. arrival among non-U.S.-born persons.

Complete data were available for 55 330/85 958 cases. Varying the serial interval and geographic proximity used to derive clusters, we consistently estimated R_m<1.0 and k < 0.08; the low value of k indicates a small number of source cases produce a disproportionate number of secondary cases.

U.S. TB reproductive number has a highly skewed distribution, indicating a minority of source cases disproportionately contribute to transmission.

Bacterial and host determinants of cough aerosol culture positivity in patients with drug-resistant versus drug-susceptible tuberculosis

A burgeoning epidemic of drug-resistant tuberculosis (TB) threatens to derail global control efforts. Although the mechanisms remain poorly clarified, drug-resistant strains are widely believed to be less infectious than drug-susceptible strains. Consequently, we hypothesized that lower proportions of patients with drug-resistant TB would have culturable Mycobacterium tuberculosis from respirable, cough-generated aerosols compared to patients with drug-susceptible TB, and that multiple factors, including mycobacterial genomic variation, would predict culturable cough aerosol production. We enumerated the colony forming units in aerosols (≤10 µm) from 452 patients with TB (227 with drug resistance), compared clinical characteristics, and performed mycobacterial whole-genome sequencing, dormancy phenotyping and drug-susceptibility analyses on M. tuberculosis from sputum. After considering treatment duration, we found that almost half of the patients with drug-resistant TB were cough aerosol culture-positive. Surprisingly, neither mycobacterial genomic variants, lineage, nor dormancy status predicted cough aerosol culture positivity. However, mycobacterial sputum bacillary load and clinical characteristics, including a lower symptom score and stronger cough, were strongly predictive, thereby supporting targeted transmission-limiting interventions. Effective treatment largely abrogated cough aerosol culture positivity; however, this was not always rapid. These data question current paradigms, inform public health strategies and suggest the need to redirect TB transmission-associated research efforts toward host-pathogen interactions.

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.

A model of tuberculosis clustering in low incidence countries reveals more transmission in the United Kingdom than the Netherlands between 2010 and 2015

Tuberculosis (TB) remains a public health threat in low TB incidence countries, through a combination of reactivated disease and onward transmission. Using surveillance data from the United Kingdom (UK) and the Netherlands (NL), we demonstrate a simple and predictable relationship between the probability of observing a cluster and its size (the number of cases with a single genotype). We demonstrate that the full range of observed cluster sizes can be described using a modified branching process model with the individual reproduction number following a Poisson lognormal distribution. We estimate that, on average, between 2010 and 2015, a TB case generated 0.41 (95% CrI 0.30,0.60) secondary cases in the UK, and 0.24 (0.14,0.48) secondary cases in the NL. A majority of cases did not generate any secondary cases. Recent transmission accounted for 39% (26%,60%) of UK cases and 23%(13%,37%) of NL cases. We predict that reducing UK transmission rates to those observed in the NL would result in 538(266,818) fewer cases annually in the UK. In conclusion, while TB in low incidence countries is strongly associated with reactivated infections, we demonstrate that recent transmission remains sufficient to warrant policies aimed at limiting local TB spread.

Longitudinal dynamics of herd-level Mycobacterium bovis MLVA type surveillance in cattle in Northern Ireland 2003-2016

Investigating genetically-structured diversity in pathogen populations over time is important to better understand disease maintenance and spread. Herd-level surveillance of Mycobacterium bovis genotypes (multi-locus VNTR analysis types, MLVA types) from all culture-confirmed bovine tuberculosis (TB) herd cases was undertaken in Northern Ireland (NI), generating an unparalleled, longitudinal, population-level 14-year survey for this pathogen. Across this population, 295 genetically-distinct M. bovis MLVA types were identified in the 19,717 M. bovis isolates surveyed. Of these, the most frequent was MLVA type 002 (23.0%); 151 MLVA types were represented more than once, in groups ranging from 2 to 4438 isolates. Only 23 MLVA types were isolated in all 14 years. Investigating inter-annual frequency of M. bovis MLVA types, examples of statistically-significant expansions (MLVA types 002, 004, 006, 009 and 027), contractions (MLVA types 001, 007 and 011) and maintenance (MLVA types 003 and 005) were disclosed, during a period of fluctuating bovine TB herd-level incidence at the NI scale. The fixed period frequency distribution of MLVA types remained highly right-skewed. Novel VNTR copy number variant MLVA types (N = 242; an average of 17 per annum) were identified throughout the survey. The MLVA type distribution in the landscape was not random; MLVA types showed statistically-significant geographical localization and strong spatial associations with Divisional Veterinary Office (DVO) regions. There was also evidence of differential risk of particular MLVA types across breeds (Holstein/Friesian vs. other), age-class, and sex and some evidence of an association between the number of animals testing positive for bovine TB during the disclosing test and particular MLVA types, although there was substantial variation.

Heterogeneous infectiousness in mathematical models of tuberculosis: A systematic review

TB mathematical models employ various assumptions and approaches in dealing with the heterogeneous infectiousness of persons with active TB. We reviewed existing approaches and considered the relationship between them and existing epidemiological evidence. We searched the following electronic bibliographic databases from inception to 9 October 2018: MEDLINE, EMBASE, Biosis, Global Health and Scopus. Two investigators extracted data using a standardised data extraction tool. We included in the review any transmission dynamic model of M. tuberculosis transmission explicitly simulating heterogeneous infectiousness of person with active TB. We extracted information including: study objective, model structure, number of active TB compartments, factors used to stratify the active TB compartment, relative infectiousness of each active TB compartment and any intervention evaluated in the model. Our search returned 1899 unique references, of which the full text of 454 records were assessed for eligibility, and 99 studies met the inclusion criteria. Of these, 89 used compartmental models implemented with ordinary differential equations, while the most common approach to stratification of the active TB compartment was to incorporate two levels of infectiousness. However, various clinical characteristics were used to stratify the active TB compartments, and models differed as to whether they permitted transition between these states. Thirty-four models stratified the infectious compartment according to sputum smear status or pulmonary involvement, while 18 models stratified based on health care-related factors. Variation in infectiousness associated with drug-resistant M. tuberculosis was the rationale for stratifying active TB in 33 models, with these models consistently assuming that drug-resistant active TB cases were less infectious. Given the evidence of extensive heterogeneity in infectiousness of individuals with active TB, an argument exists for incorporating heterogeneous infectiousness, although this should be considered in light of the objectives of the study and the research question. PROSPERO Registration: CRD42019111936.

Hyper transmission of Beijing lineage Mycobacterium tuberculosis: Systematic review and meta-analysis

OBJECTIVES

The globally distributed "Beijing" lineage of Mycobacterium tuberculosis has been associated with outbreaks worldwide. Laboratory based studies have suggested that Beijing lineage may have increased fitness; however, it has not been established whether these differences are of epidemiological significance with regards to transmission. Therefore, we undertook a systematic review of epidemiological studies of tuberculosis clustering to compare the transmission dynamics of Beijing lineages versus the non-Beijing lineages.

METHODS

We systematically searched Embase and MEDLINE before 31st December 2018, for studies which provided information on the transmission dynamics of the different M. tuberculosis lineages. We included articles that conducted population-based cross-sectional or longitudinal molecular epidemiological studies reporting information about extent of transmission of different lineages. The protocol for this systematic review was prospectively registered with PROSPERO (CDR42018088579).

RESULTS

Of 2855 records identified by the search, 46 were included in the review, containing 42,700 patients from 27 countries. Beijing lineage was the most prevalent and highly clustered strain in 72.4% of the studies and had a higher likelihood of transmission than non-Beijing lineages (OR 1·81 [95% 1·28-2·57], I² = 94·0%, τ² = 0·59, p < 0·01).

CONCLUSIONS

Despite considerable heterogeneity across epidemiological contexts, Beijing lineage appears to be more transmissible than other lineages.

Molecular epidemiology of M. tuberculosis in Ethiopia: A systematic review and meta-analysis

The molecular epidemiology of Mycobacterium tuberculosis (M. tuberculosis, Mtb) is poorly documented in Ethiopia. The data that exists has not yet been collected in an overview metadata form. Thus, this review summarizes available literature on the genomic diversity, geospatial distribution and transmission patterns of Mtb lineages (L) and sublineages in Ethiopia. Spoligotyping and Mycobacterial Interspersed Repetitive Units-Variable Number Tandem Repeats (MIRU-VNTR) based articles were identified from MEDLINE via PubMed and Scopus. The last date of article search was done on 12th February 2019. Articles were selected following the PRISMA flow diagram. The proportion of (sub)lineages was summarized at national level and further disaggregated by region. Clustering and recent transmission index (RTI) were determined using metan command and random effect meta-analysis model. The meta-analysis was computed using Stata 14 (Stata Corp. College Station, TX, USA). Among 4371 clinical isolates, 99.5% were Mtb and 0.5% were M. bovis. Proportionally, L4, L3, L1 and L7 made up 62.3%, 21.7%, 7.9% and 3.4% of the total isolates, respectively. Among sublineages, L4.2. ETH/SIT149, L4.10/SIT53, L3. ETH1/SIT25 and L4.6/SIT37 were the leading clustered isolates accounting for 14.4%, 9.7%, 7.2% and 5.5%, respectively. Based on MIRU-VNTR, the rate of clustering was 41% and the secondary case rate from a single source case was estimated at 29%. Clustering and recent transmission index was higher in eastern and southwestern Ethiopia compared with the northwestern part of the country. High level of genetic diversity with a high rate of clustering was noted which collectively mirrored the phenomena of micro-epidemics and super-spreading. The largest set of clustered strains deserves special attention and further characterization using whole genome sequencing (WGS) to better understand the evolution, genomic diversity and transmission dynamics of Mtb.

The role of super-spreading events in Mycobacterium tuberculosis transmission: evidence from contact tracing

BACKGROUND

In current epidemiology of tuberculosis (TB), heterogeneity in infectiousness among TB patients is a challenge, which is not well studied. We aimed to quantify this heterogeneity and the presence of "super-spreading" events that can assist in designing optimal public health interventions.

METHODS

TB epidemiologic investigation data notified between 1 January 2005 and 31 December 2015 from Victoria, Australia were used to quantify TB patients' heterogeneity in infectiousness and super-spreading events. We fitted a negative binomial offspring distribution (NBD) for the number of secondary infections and secondary active TB disease each TB patient produced. The dispersion parameter, k, of the NBD measures the level of heterogeneity, where low values of k (e.g. k < 1) indicate over-dispersion. Super-spreading was defined as patients causing as many or more secondary infections as the 99th centile of an equivalent homogeneous distribution. Contact infection was determined based on a tuberculin skin test (TST) result of ≥10 mm. A NBD model was fitted to identify index characteristics that were associated with the number of contacts infected and risk ratios (RRs) were used to quantify the strength of this association.

RESULTS

There were 4190 (2312 pulmonary and 1878 extrapulmonary) index TB patients and 18,030 contacts. A total of 15,522 contacts were tested with TST, of whom 3213 had a result of ≥10 mm. The dispersion parameter, k for secondary infections was estimated at 0.16 (95%CI 0.14-0.17) and there were 414 (9.9%) super-spreading events. From the 3213 secondary infections, 2415 (75.2%) were due to super-spreading events. There were 226 contacts who developed active TB disease and a higher level of heterogeneity was found for this outcome than for secondary infection, with k estimated at 0.036 (95%CI 0.025-0.046). In regression analyses, we found that infectiousness was greater among index patients found by clinical presentation and those with bacteriological confirmation.

CONCLUSION

TB transmission is highly over dispersed and super-spreading events are responsible for a substantial majority of secondary infections. Heterogeneity of transmission and super-spreading are critical issues to consider in the design of interventions and models of TB transmission dynamics.

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.

Can We Breed Cattle for Lower Bovine TB Infectivity?

Host resistance and infectivity are genetic traits affecting infectious disease transmission. This Perspective discusses the potential exploitation of genetic variation in cattle infectivity, in addition to resistance, to reduce the risk, and prevalence of bovine tuberculosis (bTB). In bTB, variability in M. bovis shedding has been previously reported in cattle and wildlife hosts (badgers and wild boars), but the observed differences were attributed to dose and route of infection, rather than host genetics. This article addresses the extent to which cattle infectivity may play a role in bTB transmission, and discusses the feasibility, and potential benefits from incorporating infectivity into breeding programmes. The underlying hypothesis is that bTB infectivity, like resistance, is partly controlled by genetics. Identifying and reducing the number of cattle with high genetic infectivity, could reduce further a major risk factor for herds exposed to bTB. We outline evidence in support of this hypothesis and describe methodologies for detecting and estimating genetic parameters for infectivity. Using genetic-epidemiological prediction models we discuss the potential benefits of selection for reduced infectivity and increased resistance in terms of practical field measures of epidemic risk and severity. Simulations predict that adding infectivity to the breeding programme could enhance and accelerate the reduction in breakdown risk compared to selection on resistance alone. Therefore, given the recent launch of genetic evaluations for bTB resistance and the UK government's goal to eradicate bTB, it is timely to consider the potential of integrating infectivity into breeding schemes.

Building capacity for advances in tuberculosis research; proceedings of the third RePORT international meeting

RePORT International is a global network of research sites in India, Brazil, Indonesia, South Africa, China, and the Philippines dedicated to collaborative tuberculosis research in the context of HIV. A standardized research protocol (the Common Protocol) guides the enrollment of participants with active pulmonary tuberculosis and contacts into observational cohorts. The establishment of harmonized clinical data and bio-repositories will allow cutting-edge, large-scale advances in the understanding of tuberculosis, including identification of novel biomarkers for progression to active tuberculosis and relapse after treatment. The RePORT International infrastructure aims to support research capacity development through enabling globally-diverse collaborations. To that end, representatives from the RePORT International network sites, funding agencies, and other stakeholders gathered together in Brazil in September 2017 to present updates on relevant research findings and discuss ideas for collaboration. Presenters emphasized research involving biomarker identification for incipient tuberculosis, host immunity and pharmacogenomics, co-morbidities such as HIV and type 2 diabetes mellitus, and tuberculosis transmission in vulnerable and high-risk populations. Currently, 962 active TB participants and 670 household contacts have contributed blood, sputum, urine and microbes to in-country biorepositories. Cross-consortium collaborations have begun sharing data and specimens to analyze molecular and cytokine predictive patterns.

Longitudinal genotyping surveillance of Mycobacterium tuberculosis in an area with high tuberculosis incidence shows high transmission rate of the modern Beijing subfamily in Japan

Tuberculosis (TB) is a severe and wide-spread infectious disease worldwide. The modern Beijing subfamily, one lineage of M. tuberculosis, reportedly has high pathogenicity and transmissibility. This study used a molecular epidemiological approach to investigate the transmissibility of the modern Beijing subfamily in the Airin area of Osaka City, Japan. During 2006-2016, we collected 596 M. tuberculosis clinical isolates in the Airin area, Osaka city, Japan. We analyzed the 24-locus variable number of tandem repeats typing optimized for the Beijing family of isolates, M. tuberculosis lineage, and patient epidemiological data. The proportion of the modern Beijing subfamily was significantly higher not only than previously obtained data for the Airin area: it was also higher than the nationwide in Japan. The rate of recent clusters, defined as a variable number of tandem repeats profile identified within two years, of the modern Beijing subfamily was significantly higher than that the rate of recent clusters of the ancient Beijing subfamily. Results suggest that TB control measures formulated with attention to the modern Beijing subfamily might be an important benchmark to understanding recent TB transmission in the area.

Quantifying TB transmission: a systematic review of reproduction number and serial interval estimates for tuberculosis

Tuberculosis (TB) is the leading global infectious cause of death. Understanding TB transmission is critical to creating policies and monitoring the disease with the end goal of TB elimination. To our knowledge, there has been no systematic review of key transmission parameters for TB. We carried out a systematic review of the published literature to identify studies estimating either of the two key TB transmission parameters: the serial interval (SI) and the reproductive number. We identified five publications that estimated the SI and 56 publications that estimated the reproductive number. The SI estimates from four studies were: 0.57, 1.42, 1.44 and 1.65 years; the fifth paper presented age-specific estimates ranging from 20 to 30 years (for infants <1 year old) to <5 years (for adults). The reproductive number estimates ranged from 0.24 in the Netherlands (during 1933-2007) to 4.3 in China in 2012. We found a limited number of publications and many high TB burden settings were not represented. Certain features of TB dynamics, such as slow transmission, complicated parameter estimation, require novel methods. Additional efforts to estimate these parameters for TB are needed so that we can monitor and evaluate interventions designed to achieve TB elimination.

Cough Frequency During Treatment Associated With Baseline Cavitary Volume and Proximity to the Airway in Pulmonary TB

BACKGROUND

Cough frequency, and its duration, is a biomarker that can be used in low-resource settings without the need of laboratory culture and has been associated with transmission and treatment response. Radiologic characteristics associated with increased cough frequency may be important in understanding transmission. The relationship between cough frequency and cavitary lung disease has not been studied.

METHODS

We analyzed data in 41 adults who were HIV negative and had culture-confirmed, drug-susceptible pulmonary TB throughout treatment. Cough recordings were based on the Cayetano Cough Monitor, and sputum samples were evaluated using microscopic observation drug susceptibility broth culture; among culture-positive samples, bacillary burden was assessed by means of time to positivity. CT scans were analyzed by a US-board-certified radiologist and a computer-automated algorithm. The algorithm evaluated cavity volume and cavitary proximity to the airway. CT scans were obtained within 1 month of treatment initiation. We compared small cavities (≤ 7 mL) and large cavities (> 7 mL) and cavities located closer to (≤ 10 mm) and farther from (> 10 mm) the airway to cough frequency and cough cessation until treatment day 60.

RESULTS

Cough frequency during treatment was twofold higher in participants with large cavity volumes (rate ratio [RR], 1.98; P = .01) and cavities located closer to the airway (RR, 2.44; P = .001). Comparably, cough ceased three times faster in participants with smaller cavities (adjusted hazard ratio [HR], 2.89; P = .06) and those farther from the airway (adjusted HR, 3.61;, P = .02). Similar results were found for bacillary burden and culture conversion during treatment.

CONCLUSIONS

Cough frequency during treatment is greater and lasts longer in patients with larger cavities, especially those closer to the airway.

Variation in Wolbachia effects on Aedes mosquitoes as a determinant of invasiveness and vectorial capacity

Wolbachia has been introduced into Aedes aegypti mosquitoes to control the spread of arboviruses, such as dengue, chikungunya and Zika. Studies showed that certain Wolbachia strains (such as wMel) reduce replication of dengue viruses in the laboratory, prompting the release of mosquitoes carrying the bacterium into the field, where vectorial capacity can be realistically assessed in relation to native non-carriers. Here we apply a new analysis to two published datasets, and show that wMel increases the mean and the variance in Ae. aegypti susceptibility to dengue infection when introgressed into Brazil and Vietnam genetic backgrounds. In the absence of other processes, higher mean susceptibility should lead to enhanced viral transmission. The increase in variance, however, widens the basis for selection imposed by unexplored natural forces, retaining the potential for reducing transmission overall.

Wolbachia infection in mosquitoes reduces dengue virus spread under specific lab conditions, prompting its use in disease control. Here, King et al. show that Wolbachia increases mean and variance in mosquito susceptibility and explain how this affects Wolbachia invasion and dengue transmission.

An explanation for the low proportion of tuberculosis that results from transmission between household and known social contacts

We currently have little idea where Mycobacterium tuberculosis (Mtb) transmission occurs in high incidence settings. Molecular studies suggest that only around 8-19% of transmission to adults occurs within-household, or between known social-contacts. This contrasts with findings from social-contact studies, which show that substantial proportions of contact time occur in households, workplaces and schools. A mathematical model of social-contact behaviour and Mtb transmission was developed, incorporating variation in susceptibility and infectiousness. Three types of contact were simulated: household, repeated (individuals outside household contacted repeatedly with daily-monthly frequency) and non-repeated. The model was parameterised using data from Cape Town, South Africa, on mean and variance in contact numbers and contact durations, by contact type, and fitted to an estimate of overdispersion in numbers of secondary cases ('superspreading') in Cape Town. Household, repeated, and non-repeated contacts contributed 36%, 13%, and 51% of contact time, and 13%, 8%, and 79% of disease, respectively. Results suggest contact saturation, exacerbated by long disease durations and superspreading, cause the high proportion of transmission between non-repeated contacts. Household and social-contact tracing is therefore unlikely to reach most tuberculosis cases. A better understanding of transmission locations, and methods to identify superspreaders, are urgently required to improve tuberculosis prevention strategies.

Relative abundance of Mycobacterium bovis molecular types in cattle: a simulation study of potential epidemiological drivers

Background

The patterns of relative species abundance are commonly studied in ecology and epidemiology to provide insights into underlying dynamical processes. Molecular types (MVLA-types) of Mycobacterium bovis, the causal agent of bovine tuberculosis, are now routinely recorded in culture-confirmed bovine tuberculosis cases in Northern Ireland. In this study, we use ecological approaches and simulation modelling to investigate the distribution of relative abundances of MVLA-types and its potential drivers. We explore four biologically plausible hypotheses regarding the processes driving molecular type relative abundances: sampling and speciation; structuring of the pathogen population; historical changes in population size; and transmission heterogeneity (superspreading).

Results

Northern Irish herd-level MVLA-type surveillance shows a right-skewed distribution of MVLA-types, with a small number of types present at very high frequencies and the majority of types very rare. We demonstrate that this skew is too extreme to be accounted for by simple neutral ecological processes. Simulation results indicate that the process of MVLA-type speciation and the manner in which the MVLA-typing loci were chosen in Northern Ireland cannot account for the observed skew. Similarly, we find that pathogen population structure, assuming for example a reservoir of infection in a separate host, would drive the relative abundance distribution in the opposite direction to that observed, generating more even abundances of molecular types. However, we find that historical increases in bovine tuberculosis prevalence and/or transmission heterogeneity (superspreading) are both capable of generating the skewed MVLA-type distribution, consistent with findings of previous work examining the distribution of molecular types in human tuberculosis.

Conclusion

Although the distribution of MVLA-type abundances does not fit classical neutral predictions, our simulations show that increases in pathogen population size and/or superspreading are consistent with the pattern observed, even in the absence of selective pressures acting on the system.

Electronic supplementary material

The online version of this article (doi:10.1186/s12917-017-1190-5) contains supplementary material, which is available to authorized users.

Progression to tuberculosis disease increases with multiple exposures

During a single year, a Canadian village had 34 individuals with microbiologically confirmed tuberculosis (TB) among 169 people with a new infection (20%). A contact investigation revealed multiple exposures for each person. We investigated whether the intensity of exposure might contribute to this extraordinary risk of disease.We carried out a case-control study using a public health database. Among those with a new infection, 34 had culture-confirmed TB (cases) and 118 did not progress to disease (controls). 17 patients with probable disease were excluded. Contact investigation data were utilised to tabulate the number of potential sources (total exposures). Generalised estimating equations with a logit link were used to identify associations between exposures and progression, and to investigate other potential risk factors.The median (interquartile range) number of total exposures was 15 (3-23) for cases and 3 (2-12) for controls (p=0.001). The adjusted OR for disease was 1.11 (95% CI 1.06-1.16) per additional exposure, corresponding to an OR of 3.4 for disease when comparing the medians of 15 versus 3 total exposures. This association increased when restricting to tuberculin skin test conversions.Increased exposure could be a marker of greater risk of progression to TB disease. Therefore, this risk may not be transportable across epidemiologic settings with variable exposure intensities.

Plan Beta for tuberculosis: it's time to think seriously about poorly ventilated congregate settings

Globally, the rates of decline in tuberculosis (TB) incidence are disappointing, but in line with model predictions regarding the likely impact of the DOTS strategy. Here, we review evidence from basic epidemiology, molecular epidemiology and modelling, all of which suggest that, in high-burden settings, the majority of Mycobacterium tuberculosis transmission may occur in indoor congregate settings. We argue that mass environmental modifications in these places might have a significant impact on TB control and suggest a research agenda that might inform interventions of this nature. The necessary technology exists and, critically, implementation would not be dependent on health care workers who are in short supply in the communities worst affected by TB.

Spatial-Temporal Epidemiology of Tuberculosis in Mainland China: An Analysis Based on Bayesian Theory

OBJECTIVE

To explore the spatial-temporal interaction effect within a Bayesian framework and to probe the ecological influential factors for tuberculosis.

METHODS

Six different statistical models containing parameters of time, space, spatial-temporal interaction and their combination were constructed based on a Bayesian framework. The optimum model was selected according to the deviance information criterion (DIC) value. Coefficients of climate variables were then estimated using the best fitting model.

RESULTS

The model containing spatial-temporal interaction parameter was the best fitting one, with the smallest DIC value (-4,508,660). Ecological analysis results showed the relative risks (RRs) of average temperature, rainfall, wind speed, humidity, and air pressure were 1.00324 (95% CI, 1.00150-1.00550), 1.01010 (95% CI, 1.01007-1.01013), 0.83518 (95% CI, 0.93732-0.96138), 0.97496 (95% CI, 0.97181-1.01386), and 1.01007 (95% CI, 1.01003-1.01011), respectively.

CONCLUSIONS

The spatial-temporal interaction was statistically meaningful and the prevalence of tuberculosis was influenced by the time and space interaction effect. Average temperature, rainfall, wind speed, and air pressure influenced tuberculosis. Average humidity had no influence on tuberculosis.

Cough Aerosols of Mycobacterium tuberculosis in the Prediction of Incident Tuberculosis Disease in Household Contacts

BACKGROUND

Tuberculosis disease develops in only 5%-10% of humans infected with Mycobacterium tuberculosis The mechanisms underlying this variability remain poorly understood. We recently demonstrated that colony-forming units of M. tuberculosis in cough-generated aerosols are a better predictor of infection than the standard sputum acid-fast bacilli smear. We hypothesized that cough aerosol cultures may also predict progression to tuberculosis disease in contacts.

METHODS

We conducted a retrospective cohort study of 85 patients with smear-positive tuberculosis and their 369 household contacts in Kampala, Uganda. Index case patients underwent a standard evaluation, and we cultured M. tuberculosis from cough aerosols. Contacts underwent a standard evaluation at enrollment, and they were later traced to determine their tuberculosis status.

RESULTS

During a median follow-up of 3.9 years, 8 (2%) of the contacts developed tuberculosis disease. In unadjusted and adjusted analyses, incident tuberculosis disease in contacts was associated with sputum Mycobacterial Growth Indicator Tube culture (odds ratio, 8.2; 95% confidence interval, 1.1-59.2; P = .04), exposure to a high-aerosol tuberculosis case patient (6.0, 1.4-25.2; P = .01), and marginally, human immunodeficiency virus in the contact (6.11; 0.89-41.7; P = .07). We present data demonstrating that sputum and aerosol specimens measure 2 related but different phenomena.

CONCLUSIONS

We found an increased risk of tuberculosis progression among contacts of high-aerosol case patients. The hypothesis that a larger infectious inoculum, represented by high aerosol production, determines the risk of disease progression deserves evaluation in future prospective studies.

End TB strategy: the need to reduce risk inequalities

Background

Diseases occur in populations whose individuals differ in essential characteristics, such as exposure to the causative agent, susceptibility given exposure, and infectiousness upon infection in the case of infectious diseases.

Discussion

Concepts developed in demography more than 30 years ago assert that variability between individuals affects substantially the estimation of overall population risk from disease incidence data. Methods that ignore individual heterogeneity tend to underestimate overall risk and lead to overoptimistic expectations for control. Concerned that this phenomenon is frequently overlooked in epidemiology, here we feature its significance for interpreting global data on human tuberculosis and predicting the impact of control measures.

Summary

We show that population-wide interventions have the greatest impact in populations where all individuals face an equal risk. Lowering variability in risk has great potential to increase the impact of interventions. Reducing inequality, therefore, empowers health interventions, which in turn improves health, further reducing inequality, in a virtuous circle.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-016-1464-8) contains supplementary material, which is available to authorized users.

A theoretical framework to identify invariant thresholds in infectious disease epidemiology

Setting global strategies and targets for disease prevention and control often involves mathematical models. Model structure is typically subject to intense scrutiny, such as confrontation with empirical data and alternative formulations, while a less frequently challenged aspect is the widely adopted reduction of parameters to their average values. Focusing on endemic diseases, we use a general transmission model to explain how mean field approximations decrease the estimated R0 from prevalence data, while threshold phenomena - such as the epidemic and reinfection thresholds - remain invariant. This results in an underestimation of the effort required to control disease, which may be particularly severe when the approximation inappropriately places transmission estimates below important thresholds. These concepts are widely applicable across endemic pathogen systems.

The transmission of Mycobacterium tuberculosis in high burden settings

Unacceptable levels of Mycobacterium tuberculosis transmission are noted in high burden settings and a renewed focus on reducing person-to-person transmission in these communities is needed. We review recent developments in the understanding of airborne transmission. We outline approaches to measure transmission in populations and trials and describe the Wells-Riley equation, which is used to estimate transmission risk in indoor spaces. Present research priorities include the identification of effective strategies for tuberculosis infection control, improved understanding of where transmission occurs and the transmissibility of drug-resistant strains, and estimates of the effect of HIV and antiretroviral therapy on transmission dynamics. When research is planned and interventions are designed to interrupt transmission, resource constraints that are common in high burden settings-including shortages of health-care workers-must be considered.

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

BACKGROUND

We aimed to identify and determine the etiology of "hotspots" of concentrated multidrug-resistant tuberculosis (MDR-tuberculosis) risk in Lima, Peru.

METHODS

From 2009 to 2012, we conducted a prospective cohort study among households of tuberculosis cases from 106 health center (HC) areas in Lima, Peru. All notified tuberculosis cases and their household contacts were followed for 1 year. Symptomatic individuals were screened by microscopy and culture; positive cultures were tested for drug susceptibility (DST) and genotyped by 24-loci mycobacterial interspersed repetitive units-variable-number tandem repeats (MIRU-VNTR).

RESULTS

3286 individuals with culture-confirmed disease, DST, and 24-loci MIRU-VNTR were included in our analysis. Our analysis reveals: (1) heterogeneity in annual per-capita incidence of tuberculosis and MDR-tuberculosis by HC, with a rate of MDR-tuberculosis 89 times greater (95% confidence interval [CI], 54,185) in the most-affected versus the least-affected HC; (2) high risk for MDR-tuberculosis in a region spanning several HCs (odds ratio = 3.19, 95% CI, 2.33, 4.36); and (3) spatial aggregation of MDR-tuberculosis genotypes, suggesting localized transmission.

CONCLUSIONS

These findings reveal that localized transmission is an important driver of the epidemic of MDR-tuberculosis in Lima. Efforts to interrupt transmission may be most effective if targeted to this area of the city.

Mathematical Modelling and Tuberculosis: Advances in Diagnostics and Novel Therapies

As novel diagnostics, therapies, and algorithms are developed to improve case finding, diagnosis, and clinical management of patients with TB, policymakers must make difficult decisions and choose among multiple new technologies while operating under heavy resource constrained settings. Mathematical modelling can provide helpful insight by describing the types of interventions likely to maximize impact on the population level and highlighting those gaps in our current knowledge that are most important for making such assessments. This review discusses the major contributions of TB transmission models in general, namely, the ability to improve our understanding of the epidemiology of TB. We focus particularly on those elements that are important to appropriately understand the role of TB diagnosis and treatment (i.e., what elements of better diagnosis or treatment are likely to have greatest population-level impact) and yet remain poorly understood at present. It is essential for modellers, decision-makers, and epidemiologists alike to recognize these outstanding gaps in knowledge and understand their potential influence on model projections that may guide critical policy choices (e.g., investment and scale-up decisions).

Risk of using logistic regression to illustrate exposure-response relationship of infectious diseases

Background

In most biological experiments, especially infectious disease, the exposure-response relationship is interrelated by a multitude of factors rather than many independent factors. Little is known about the suitability of ordinary, categorical exposures, and logarithmic transformation which have been presented in logistic regression models to assess the likelihood of an infectious disease as a function of a risk or exposure. This study aims to examine and compare the current approaches.

Methods

A simulated human immunodeficiency virus (HIV) population, dynamic infection data for 100,000 individuals with 1% initial prevalence and 2% infectivity, was created. Using the Monte Carlo method (computational algorithm) to repeat random sampling to obtain numerical results, linearity between log odds and exposure, and suitability in practice were examined in the three model approaches.

Results

Despite diverse population prevalence, the linearity was not satisfied between log odds and raw exposures. Logarithmic transformation of exposures improved the linearity to a certain extent, and categorical exposures satisfied the linear assumption (which was important for modelling). When the population prevalence was low (assumed < 10%), performances of the three models were significantly different. Comparing to ordinary logistic regression, the logarithmic transformation approach demonstrated better accuracy of estimation except that at the two inflection points: likelihood of infection increased from slowly to sharply, then slowly again. The approach using categorical exposures had better estimations around the real values, but the measurement was coarse due to categorization.

Conclusions

It is not suitable to directly use ordinary logistic regression to explore the exposure-response relationship of HIV as an infectious disease. This study provides some recommendations for practical implementations including: 1) utilize categorical exposure if a large sample size and low population prevalence are provided; 2) utilize a logarithmic transformed exposure if the sample size is insufficient or the population prevalence is too high (such as 30%).

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2334-14-540) contains supplementary material, which is available to authorized users.

Drivers and trajectories of resistance to new first-line drug regimens for tuberculosis

Background

 New first-line drug regimens for treatment of tuberculosis (TB) are in clinical trials: emergence of resistance is a key concern. Because population-level data on resistance cannot be collected in advance, epidemiological models are important tools for understanding the drivers and dynamics of resistance before novel drug regimens are launched.

Methods

 We developed a transmission model of TB after launch of a new drug regimen, defining drug-resistant TB (DR-TB) as resistance to the new regimen. The model is characterized by (1) the probability of acquiring resistance during treatment, (2) the transmission fitness of DR-TB relative to drug-susceptible TB (DS-TB), and (3) the probability of treatment success for DR-TB versus DS-TB. We evaluate the effect of each factor on future DR-TB prevalence, defined as the proportion of incident TB that is drug-resistant.

Results

 Probability of acquired resistance was the strongest predictor of the DR-TB proportion in the first 5 years after the launch of a new drug regimen. Over a longer term, however, the DR-TB proportion was driven by the resistant population's transmission fitness and treatment success rates. Regardless of uncertainty in acquisition probability and transmission fitness, high levels (>10%) of drug resistance were unlikely to emerge within 50 years if, among all cases of TB that were detected, 85% of those with DR-TB could be appropriately diagnosed as such and then successfully treated.

Conclusions

 Short-term surveillance cannot predict long-term drug resistance trends after launch of novel first-line TB regimens. Ensuring high treatment success of drug-resistant TB through early diagnosis and appropriate second-line therapy can mitigate many epidemiological uncertainties and may substantially slow the emergence of drug-resistant TB.

Transforming the fight against tuberculosis: targeting catalysts of transmission

The global tuberculosis control community has committed itself to ambitious 10-year targets. To meet these targets, biomedical advances alone will be insufficient; a more targeted public health tuberculosis strategy is also needed. We highlight the role of "tuberculosis transmission catalysts," defined as variabilities in human behavior, bacillary properties, and host physiology that fuel the propagation of active tuberculosis at the local level. These catalysts can be categorized as factors that increase contact rates, infectiousness, or host susceptibility. Different catalysts predominate in different epidemiological and sociopolitical settings, and public health approaches are likely to succeed only if they are tailored to target the major catalysts driving transmission in the corresponding community. We argue that global tuberculosis policy should move from a country-level focus to a strategy that prioritizes collection of data on key transmission catalysts at the local level followed by deployment of "catalyst-targeted" interventions, supported by strengthened health systems.

A review of the neurological and neurosurgical implications of tuberculosis in children

Tuberculous involvement of the central nervous system (CNS) and vertebral column is the most lethal and disabling form of tuberculosis (TB). Several factors contribute to poor outcome, including cerebrovascular involvement with ischemia, hydrocephalus, direct parenchymal injury and formation of abscess and inflammation in the brain and spinal cord, hyponatremia, seizures, and delayed diagnosis. Spinal spondylitis from TB and associated spinal deformity is the leading cause of paraplegia in developing countries. The evidence for supportive treatment of TB infection of the CNS is limited, leading to substantial differences in management protocols. Many of the treatment approaches used in TB infection of the CNS have been extrapolated from treatment of other acute neurological disorders such as bacterial meningitis and traumatic brain injury. We review data from the available literature and highlight questions relating to the neurological and neurosurgical care of children with TB infection of the CNS and vertebral column.