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Tuberculosis remains the world's leading cause of death from an infectious agent, and is a serious health problem in Papua New Guinea (PNG) with an estimated 36,000 new cases each year. This study describes the genetic diversity of Mycobacterium tuberculosis among tuberculosis patients in the Balimo/Bamu region in the Middle Fly District of Western Province in PNG, and investigates rifampicin resistance-associated mutations. Archived Ziehl-Neelsen-stained sputum smears were used to conduct microbead-based spoligotyping and assess genotypic resistance. Among the 162 samples included, 80 (49.4%) generated spoligotyping patterns (n = 23), belonging predominantly to the L2 Lineage (44%) and the L4 Lineage (30%). This is consistent with what has been found in other PNG regions geographically distant from Middle Fly District of Western Province, but is different from neighbouring South-East Asian countries. Rifampicin resistance was identified in 7.8% of the successfully sequenced samples, with all resistant samples belonging to the L2/Beijing Lineage. A high prevalence of mixed L2/L4 profiles was suggestive of polyclonal infection in the region, although this would need to be confirmed. The method described here could be a game-changer in resource-limited countries where large numbers of archived smear slides could be used for retrospective (and prospective) studies of M. tuberculosis genetic epidemiology.

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.

Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

BACKGROUND:

Tuberculosis (TB) control efforts are hampered by an imperfect understanding of TB epidemiology. The true age distribution of disease is unknown because a large proportion of individuals with active TB remain undetected. Understanding of transmission is limited by the asymptomatic nature of latent infection and the pathogen's capacity for late reactivation. A better understanding of TB epidemiology is critically needed to ensure effective use of existing and future control tools.

METHODS:

We use an agent-based model to simulate TB epidemiology in the five highest TB burden countries-India, Indonesia, China, the Philippines and Pakistan-providing unique insights into patterns of transmission and disease. Our model replicates demographically realistic populations, explicitly capturing social contacts between individuals based on local estimates of age-specific contact in household, school and workplace settings. Time-varying programmatic parameters are incorporated to account for the local history of TB control.

RESULTS:

We estimate that the 15-19-year-old age group is involved in more than 20% of transmission events in India, Indonesia, the Philippines and Pakistan, despite representing only 5% of the local TB incidence. According to our model, childhood TB represents around one fifth of the incident TB cases in these four countries. In China, three quarters of incident TB were estimated to occur in the ≥ 45-year-old population. The calibrated per-contact transmission risk was found to be similar in each of the five countries despite their very different TB burdens.

CONCLUSIONS:

Adolescents and young adults are a major driver of TB in high-incidence settings. Relying only on the observed distribution of disease to understand the age profile of transmission is potentially misleading.

BACKGROUND:

Treatment outcomes among patients treated for multidrug-resistant tuberculosis (MDR-TB) are often sub-optimal. Therefore, the early prediction of poor treatment outcomes may be useful in patient care, especially for clinicians when they have the ability to make treatment decisions or offer counselling or additional support to patients. The aim of this study was to develop a simple clinical risk score to predict poor treatment outcomes in patients with MDR-TB, using routinely collected data from two large countries in geographically distinct regions.

METHODS:

We used MDR-TB data collected from Hunan Chest Hospital, China and Gondar University Hospital, Ethiopia. The data were divided into derivation (n = 343; 60%) and validation groups (n = 227; 40%). A poor treatment outcome was defined as treatment failure, lost to follow up or death. A risk score for poor treatment outcomes was derived using a Cox proportional hazard model in the derivation group. The model was then validated in the validation group.

RESULTS:

The overall rate of poor treatment outcome was 39.5% (n = 225); 37.9% (n = 86) in the derivation group and 40.5% (n = 139) in the validation group. Three variables were identified as predictors of poor treatment outcomes, and each was assigned a number of points proportional to its regression coefficient. These predictors and their points were: 1) history of taking second-line TB treatment (2 points), 2) resistance to any fluoroquinolones (3 points), and 3) smear did not convert from positive to negative at two months (4 points). We summed these points to calculate the risk score for each patient; three risk groups were defined: low risk (0 to 2 points), medium risk (3 to 5 points), and high risk (6 to 9 points). In the derivation group, poor treatment outcomes were reported for these three groups as 14%, 27%, and 71%, respectively. The area under the receiver operating characteristic curve for the point system in the derivation group was 0.69 (95% CI 0.60 to 0.77) and was similar to that in the validation group (0.67; 95% CI 0.56 to 0.78; p = 0.82).

CONCLUSION:

History of second-line TB treatment, resistance to any fluoroquinolones, and smear non-conversion at two months can be used to estimate the risk of poor treatment outcome in patients with MDR-TB with a moderate degree of accuracy (AUROC = 0.69).

Although different structures are used in modern tuberculosis (TB) models to simulate TB latency, it remains unclear whether they are all capable of reproducing the particular activation dynamics empirically observed. We aimed to determine which of these structures replicate the dynamics of progression accurately. We reviewed 88 TB-modelling articles and classified them according to the latency structure employed. We then fitted these different models to the activation dynamics observed from 1352 infected contacts diagnosed in Victoria (Australia) and Amsterdam (Netherlands) to obtain parameter estimates. Six different model structures were identified, of which only those incorporating two latency compartments were capable of reproducing the activation dynamics empirically observed. We found important differences in parameter estimates by age. We also observed marked differences between our estimates and the parameter values used in many previous models. In particular, when two successive latency phases are considered, the first period should have a duration that is much shorter than that used in previous studies. In conclusion, structures incorporating two latency compartments and age-stratification should be employed to accurately replicate the dynamics of TB latency. We provide a catalogue of parameter values and an approach to parameter estimation from empiric data for calibration of future TB-models.

Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

BACKGROUND:

Tuberculosis (TB) is now the world's leading infectious killer and major programmatic advances will be needed if we are to meet the ambitious new End TB Targets. Although mathematical models are powerful tools for TB control, such models must be flexible enough to capture the complexity and heterogeneity of the global TB epidemic. This includes simulating a disease that affects age groups and other risk groups differently, has varying levels of infectiousness depending upon the organ involved and varying outcomes from treatment depending on the drug resistance pattern of the infecting strain.

RESULTS:

We adopted sound basic principles of software engineering to develop a modular software platform for simulation of TB control interventions ("AuTuMN"). These included object-oriented programming, logical linkage between modules and consistency of code syntax and variable naming. The underlying transmission dynamic model incorporates optional stratification by age, risk group, strain and organ involvement, while our approach to simulating time-variant programmatic parameters better captures the historical progression of the epidemic. An economic model is overlaid upon this epidemiological model which facilitates comparison between new and existing technologies. A "Model runner" module allows for predictions of future disease burden trajectories under alternative scenario situations, as well as uncertainty, automatic calibration, cost-effectiveness and optimisation. The model has now been used to guide TB control strategies across a range of settings and countries, with our modular approach enabling repeated application of the tool without the need for extensive modification for each application.

CONCLUSIONS:

The modular construction of the platform minimises errors, enhances readability and collaboration between multiple programmers and enables rapid adaptation to answer questions in a broad range of contexts without the need for extensive re-programming. Such features are particularly important in simulating an epidemic as complex and diverse as TB.

Tuberculosis (TB) is a potentially fatal infectious disease that continues to be a public health problem in Bangladesh. Each year in Bangladesh an estimated 70,000 people die of TB and 300,000 new cases are projected. It is important to understand the association between TB incidence and weather factors in Bangladesh in order to develop proper intervention programs. In this study, we examine the delayed effect of weather variables on TB occurrence and estimate the burden of the disease that can be attributed to weather factors. We used generalized linear Poisson regression models to investigate the association between weather factors and TB cases reported to the Bangladesh National TB control program between 2007 and 2012 in three known endemic districts of North-East Bangladesh. The associated risk of TB in the three districts increases with prolonged exposure to temperature and rainfall, and persisted at lag periods beyond 6 quarters. The association between humidity and TB is strong and immediate at low humidity, but the risk decreases with increasing lag. Using the optimum weather values corresponding to the lowest risk of infection, the risk of TB is highest at low temperature, low humidity and low rainfall. Measures of the risk attributable to weather variables revealed that weather-TB cases attributed to humidity is higher than that of temperature and rainfall in each of the three districts. Our results highlight the high linearity of temporal lagged effects and magnitudes of the burden attributable to temperature, humidity, and rainfall on TB endemics. The results can hopefully advise the Bangladesh National TB control program and act as a practical reference for the early warning of TB cases.

BACKGROUND:

Pooling sputum specimens is one potential strategy for reducing the cost of using Xpert MTB/RIF, a rapid polymerase chain reaction (PCR)-based test, for the diagnosis of pulmonary tuberculosis. We sought to compare the sensitivity of two alternative method of pooling.

METHODS:

Patients referred for assessment for TB, whose initial sputum was Xpert MTB positive, were recruited and their sputum specimens were pooled for analysis with sputum specimens that were Xpert MTB negative. Two alternative pooling strategies were employed: one in which the concentration of sample reagent (buffer) was maintained at 2:1 (standard), in accordance with the manufacturer's instructions, and another in which the concentration of sample reagent was reduced to 1:1.

RESULTS:

We tested 101 Xpert MTB positive sputum specimens. Among these, 96% of valid test results (95% confidence interval (CI) 89-99%) were positive using the "standard buffer method". Using the "reduced buffer pooling" method 94% of valid test results (95% CI 87-98%) were positive. McNemar's test for the difference in paired proportions did not reach statistical significance (P = 0.56).

CONCLUSION:

We have confirmed that pooling of two sputum specimens for testing in a single cartridge is a valid method of reducing the number of cartridges required when using Xpert MTB to detect pulmonary tuberculosis. Two alternative pooling strategies tested here yielded similar results.

TRIAL REGISTRATION:

The present study was conducted within the Active Casefinding in Tuberculosis (ACT3) Trial. The ACT3 Trial had been registered with Australian and New Zealand Clinical Trials Register on 8th April, 2014. The trial registration number is ACTRN12614000372684 . (Retrospectively registered).

BACKGROUND:

The risk of progression to tuberculosis (TB) disease is greatest soon after infection, yet disease may occur many years or decades later. However, rates of TB reactivation long after infection remain poorly quantified. Australia is a low-TB incidence setting and most cases occur among migrants. We explored how TB rates in Australian migrants varied with time from migration, age and gender.

METHODS:

We combined TB notifications in census years 2006, 2011 and 2016 with time and country-specific estimates oflatent TB prevalence in migrant cohorts to quantifypost-migration reactivation rates.

RESULTS:

During the census years 3,246 TB cases occurred among an estimated 2,084,000 migrants with latent-TB. There were consistent trends in post-migration reactivation rates, which appeared to be dependent on both time from migration and age. Rates were lower in cohorts with increasing time until at least twenty years from migration, and on this background there also appeared to be increasing rates during youth (15-24 years of age), and in those aged 70 years and above. Within five years of migration, annual reactivation rates were approximately 400 per 100,000 (uncertainty interval [UI]: 320-480), dropping to 170 (UI: 130-220) and 110 (UI: 70-160) from five-to-ten and ten-to-twenty, then sustaining at 60-70 per 100,000 up to sixty years from migration. Rates varied depending on age at migration.

CONCLUSIONS:

Post-migration reactivation rates appeared to show dependency on both time from migration and age. This approach to quantifying reactivation risk will enable evaluation of the potential impact of TB control and elimination strategies.

© The Author(s) 2019. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

BACKGROUND:

Globally 3.9% of new and 21% of re-treatment tuberculosis (TB) cases are multidrug-resistant or rifampicin-resistant (MDR/RR), which is often interpreted as evidence that drug resistance results mainly from poor treatment adherence. This study aims to assess the respective contributions of the different causal pathways leading to MDR/RR-TB at re-treatment.

METHODS:

We use a simple mathematical model to simulate progression between the different stages of disease and treatment for patients diagnosed with TB. The model is parameterised using region and country-specific TB disease burden data reported by the World Health Organization (WHO). The contributions of four separate causal pathways to MDR/RR-TB among re-treatment cases are estimated: I) initial drug-susceptible TB with resistance amplification during treatment; II) initial MDR/RR-TB inappropriately treated as drug-susceptible TB; III) MDR/RR-TB relapse despite appropriate treatment; and IV) re-infection with MDR/RR-TB.

RESULTS:

At the global level, Pathways I, II, III and IV contribute 38% (28-49, 95% Simulation Interval), 44% (36-52, 95% SI), 6% (5-7, 95% SI) and 12% (7-19, 95% SI) respectively to the burden of MDR/RR-TB among re-treatment cases. Pathway II is dominant in the Western Pacific (74%; 67-80 95% SI), Eastern Mediterranean (68%; 60-74 95% SI) and European (53%; 48-59 95% SI) regions, while Pathway I makes the greatest contribution in the American (53%; 40-66 95% SI), African (43%; 28-61 95% SI) and South-East Asian (50%; 40-59 95% SI) regions.

CONCLUSIONS:

Globally, failure to diagnose MDR/RR-TB at first presentation is the leading cause of the high proportion of MDR/RR-TB among re-treatment cases. These findings highlight the need for contextualised solutions to limit the impact and spread of MDR/RR-TB.

BACKGROUND:

Private healthcare providers are important to tuberculosis (TB) management globally, although internationally there are reports of suboptimal management and disparities in treatment commencement in the private sector. We compared the management of TB patients receiving private versus public healthcare in Victoria, an industrialised setting with low tuberculosis (TB) incidence.

METHODS:

Retrospective cohort study: 2002-2015. Private healthcare provision was included as an independent variable in several multivariate logistic and Cox proportional hazard regression models that assessed a range of outcome variables, encompassing treatment commencement delays, management and treatment outcomes.

RESULTS:

Of 5106 patients, 275 (5.4%) exclusively saw private providers, and 4714 (92.32%) public. Private care was associated with a shorter delay to presentation (HR 1.36, p = 0.065, 95% CI 1.02-2.00). Private patients were less likely to have genotypic testing (OR 0.66, p = 0.009, 95% CI 0.48-0.90), those with pulmonary involvement were less likely to have a sputum smear (OR 0.52, p = 0.011, 95% CI 0.31-0.86) and provided samples were less likely to be positive (OR 0.54, p = 0.070, 95% CI 0.27-1.05). Private patients with extrapulmonary TB were less likely to have a smear sample (OR 0.7, 95% CI 0.48-0.90, p = 0.009) and radiological abnormalities (OR 0.71, p = 0.070, 95% CI 0.27-1.05). Treatment commencement delays from presentation were comparable for cases with pulmonary involvement and extrapulmonary TB, although public extrapulmonary TB patients received radiological examinations slightly earlier than private patients (HR 0.79, p = 0.043, 95% CI 0.63-0.99) and public patients with pulmonary involvement from high burden settings commenced treatment following an abnormal CXR more promptly than their private counterparts (HR 0.41, p = 0.011, 95% CI 0.21-0.81). Private patients were more likely to receive <4 first-line medications (OR 2.17, p = 0.001, 95% CI 1.36-3.46), but treatment outcomes were comparable between sectors.

CONCLUSIONS:

The differences we identified are likely to reflect differing case-mix as well as clinician practice. Sputum smear status was an important covariable in our analysis; with its addition we found no significant disparity in the health-system delay to treatment commencement between sectors. Our study highlights the importance of TB programs engaging with private providers, enabling comprehensive data collection that is necessary for thorough and true comparison of TB management and optimisation of care.

Multidrug-resistant and rifampicin-resistant tuberculosis (MDR/RR-TB) represent an important challenge for global tuberculosis (TB) control. The high rates of MDR/RR-TB observed among re-treatment cases can arise from diverse pathways: de novo amplification during initial treatment, inappropriate treatment of undiagnosed MDR/RR-TB, relapse despite appropriate treatment, or reinfection with MDR/RR-TB. Mathematical modelling allows quantification of the contribution made by these pathways in different settings. This information provides valuable insights for TB policy-makers, allowing better contextualised solutions. However, mathematical modelling outputs need to consider local data and be easily accessible to decision makers in order to improve their usefulness. We present a user-friendly web-based modelling interface, which can be used by people without technical knowledge. Users can input their own parameter values and produce estimates for their specific setting. This innovative tool provides easy access to mathematical modelling outputs that are highly relevant to national TB control programs. In future, the same approach could be applied to a variety of modelling applications, enhancing local decision making.

BACKGROUND:

The worldwide emergence of multidrug-resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB) has posed additional challenges for global tuberculosis (TB) control efforts, as limited treatment options are available and treatment outcomes are often sub-optimal. This study determined treatment outcomes among a cohort of MDR-TB and XDR-TB patients in Hunan Province, China, and identified factors associated with poor treatment outcomes.

METHODS:

We conducted a retrospective study using data obtained from medical records of TB patients in Hunan Chest Hospital, and from the internet-based TB management information system managed by the Tuberculosis Control Institute of Hunan Province, for the period 2011 to 2014. Treatment outcomes were assessed for patients diagnosed with MDR-TB (TB resistant to at least isoniazid and rifampicin) and XDR-TB (MDR-TB plus resistance to any fluoroquinolone and at least 1 second-line injectable drug). Cumulative incidence functions were used to estimate time to events (i.e. poor treatment outcomes, loss to follow-up, and unfavourable treatment outcomes); and a competing-risks survival regression model was used to identify predictors of treatment outcomes.

RESULT:

Of 481 bacteriologically-confirmed patients, with a mean age of 40 years (standard deviation SD ± 13 years), 10 (2%) had XDR-TB and the remainder (471; 98%) had MDR-TB. For the entire cohort, treatment success was 57% (n = 275); 58% (n = 272) for MDR-TB and 30% (n = 3) for XDR-TB. Overall, 27% were lost to follow-up (n = 130), 27% (n = 126) for MDR-TB and 40% (n = 4) for XDR-TB; and 16% had a poor treatment outcome (n = 76), 15% for MDR-TB and 30% (n = 3) for XDR-TB. Of the 10 XDR-TB patients, 3 (30%) completed treatment, 3 (30%) died and 4 (40%) were lost to follow-up. Of the 471 MDR-TB patients, 258 (57%) were cured, 16 (3%) completed treatment, 13 (3%) died, 60 (13%) experienced treatment failure, and 126 (27%) were lost to follow-up. Resistance to ofloxacin was an independent predictor of poor (AHR = 3.1; 95%CI = 1.5, 6.3), and unfavourable (AHR = 1.7; 95%CI = 1.07, 2.9) treatment outcomes. Patients who started treatment during 2011-2012 (AHR = 2.8; 95% CI = 1.5, 5.3) and 2013 (AHR = 2.1; 95% CI = 1.2, 3.9) had poorer treatment outcomes compared to patients who started treatment during 2014.

CONCLUSION:

Patients with MDR-TB and XDR-TB had low rates of treatment success in Hunan Province, especially among patients who started treatment during 2011 to 2013, with evidence of improved treatment outcomes in 2014. Resistance to ofloxacin was an independent predictor of poor treatment outcomes.

Tuberculosis (TB) remains a disease of high morbidity in Australia, with implications for both public health and the individual. Cost analyses is relevant for programmatic evaluation of TB. There is minimal published TB cost data in the Australian setting. Patients with drug sensitive active pulmonary TB (DS-PTB) and latent TB (LTBI) were enrolled in a single tertiary referral centre to evaluate healthcare provider costs. The median cost of treating drug susceptible pulmonary TB in this case series was 11,538 AUD. Approximately 50% of total costs is derived from inpatient hospitalisation bed days. In comparison, the average cost of managing latent TB was 582 AUD per completed course. We find the median provider cost of our DS-PTB treatment group comparable to costs from other regions globally with similar economic profiles. A program designed to detect and treat LTBI to prevent subsequent disease may be cost effective in appropriately selected patients and warrants further study.

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BACKGROUND:

Reported tuberculosis (TB) incidence globally continues to be heavily influenced by expert opinion of case detection rates and ecological estimates of disease duration. Both approaches are recognised as having substantial variability and inaccuracy, leading to uncertainty in true TB incidence and other such derived statistics.

METHODS:

We developed Bayesian binomial mixture geospatial models to estimate TB incidence and case detection rate (CDR) in Ethiopia. In these models the underlying true incidence was formulated as a partially observed Markovian process following a mixed Poisson distribution and the detected (observed) TB cases as a binomial distribution, conditional on CDR and true incidence. The models use notification data from multiple areas over several years and account for the existence of undetected TB cases and variability in true underlying incidence and CDR. Deviance information criteria (DIC) were used to select the best performing model.

RESULTS:

A geospatial model was the best fitting approach. This model estimated that TB incidence in Sheka Zone increased from 198 (95% Credible Interval (CrI) 187, 233) per 100,000 population in 2010 to 232 (95% CrI 212, 253) per 100,000 population in 2014. The model revealed a wide discrepancy between the estimated incidence rate and notification rate, with the estimated incidence ranging from 1.4 (in 2014) to 1.7 (in 2010) times the notification rate (CDR of 71% and 60% respectively). Population density and TB incidence in neighbouring locations (spatial lag) predicted the underlying TB incidence, while health facility availability predicted higher CDR.

CONCLUSION:

Our model estimated trends in underlying TB incidence while accounting for undetected cases and revealed significant discrepancies between incidence and notification rates in rural Ethiopia. This approach provides an alternative approach to estimating incidence, entirely independent of the methods involved in current estimates and is feasible to perform from routinely collected surveillance data.

The burden of tuberculosis (TB) in children reflects continuing and recent transmission within a population. This study aimed to identify spatiotemporal and socio-climatic factors associated with paediatric TB in north-western Ethiopia. Multivariate Poisson regression models were computed using a Bayesian framework. Estimates of parameters were generated using Markov chain Monte Carlo simulation. A total of 2,240 children aged under 15 years diagnosed with TB during the years 2013- 2016 were included in the analysis. The annual TB incidence rates were 44 and 28 per 100,000 children, for children aged under 15 and 5 years, respectively. Spatial clustering of TB was observed in the border area of north-western Ethiopia. The spatio-temporal transmission of childhood TB was found to be associated with district level socio-climatic factors such as urbanisation [relative risk (RR): 1.8; 95% credible interval (CrI): 1.2, 2.6], lower educational status (RR: 1.5; 95% CrI: 1.0, 2.1), a high percentage of internal migration (RR: 1.3; 95% CrI: 1.0, 1.6), high temperature (RR: 1.3; 95% CrI: 1.0, 1.7) and high rainfall (RR: 1.5; 95% CrI: 1.1, 2.0). We conclude that interventions targeting hotspot districts with a high proportion of childhood TB are important to reduce TB transmission in northwest Ethiopia.

BACKGROUND:

Accurate diagnosis and subsequent treatment of latent tuberculosis infection (LTBI) is essential for TB elimination. However, the absence of a gold standard test for diagnosing LTBI makes assessment of the true prevalence of LTBI and the accuracy of diagnostic tests challenging. Bayesian latent class models can be used to make inferences about disease prevalence and the sensitivity and specificity of diagnostic tests using data on the concordance between tests. We performed the largest meta-analysis to date aiming to evaluate the performance of tuberculin skin test (TST) and interferon-gamma release assays (IGRAs) for LTBI diagnosis in various patient populations using Bayesian latent class modelling.

METHODS:

Systematic search of PubMeb, Embase and African Index Medicus was conducted without date and language restrictions on September 11, 2017 to identify studies that compared the performance of TST and IGRAs for LTBI diagnosis. Two IGRA methods were considered: QuantiFERON-TB Gold In Tube (QFT-GIT) and T-SPOT.TB. Studies were included if they reported 2x2 agreement data between TST and QFT-GIT or T-SPOT.TB. A Bayesian latent class model was developed to estimate the sensitivity and specificity of TST and IGRAs in various populations, including immune-competent adults, immune-compromised adults and children. A TST cut-off value of 10 mm was used for immune-competent subjects and 5 mm for immune-compromised individuals.

FINDINGS:

A total of 157 studies were included in the analysis. In immune-competent adults, the sensitivity of TST and QFT-GIT were estimated to be 84% (95% credible interval [CrI] 82-85%) and 52% (50-53%), respectively. The specificity of QFT-GIT was 97% (96-97%) in non-BCG-vaccinated and 93% (92-94%) in BCG-vaccinated immune-competent adults. The estimated figures for TST were 100% (99-100%) and 79% (76-82%), respectively. T-SPOT.TB has comparable specificity (97% for both tests) and better sensitivity (68% versus 52%) than QFT-GIT in immune-competent adults. In immune-compromised adults, both TST and QFT-GIT display low sensitivity but high specificity. QFT-GIT and TST are equally specific (98% for both tests) in non-BCG-vaccinated children; however, QFT-GIT is more specific than TST (98% versus 82%) in BCG-vaccinated group. TST is more sensitive than QFT-GIT (82% versus 73%) in children.

CONCLUSIONS:

This study is the first to assess the utility of TST and IGRAs for LTBI diagnosis in different population groups using all available data with Bayesian latent class modelling. Our results challenge the current beliefs about the performance of LTBI screening tests, and have important implications for LTBI screening policy and practice. We estimated that the performance of IGRAs is not as reliable as previously measured in the general population. However, IGRAs are not or minimally affected by BCG and should be the preferred tests in this setting. Adoption of IGRAs in settings where BCG is widely administered will allow for a more accurate identification and treatment of LTBI.

BACKGROUND:

Currently, treatment of latent tuberculosis infection (LTBI) in Australia consists most commonly of a 9-month course of isoniazid (9H). A 3-month course of weekly isoniazid and rifapentine (3HP) has been shown to be as effective as 9 months of daily isoniazid, and associated with less hepatotoxicity; however, rifapentine is not currently available in Australia. Introduction of this regimen would have apparent advantages for people with LTBI in Victoria by safely shortening duration of LTBI therapy. However, the cost benefit of this new therapeutic approach is uncertain.

AIM:

Cost-analysis of standard and short-course therapy for LTBI in an Australian context.

METHODS:

Single-centre randomised controlled trial conducted between December 2013-March 2016. Participants underwent 1:1 randomisation to either a 9-month course of daily isoniazid or a 12-week course of weekly isoniazid and rifapentine. The primary outcome measure was total healthcare system costs (in Australian dollars; AUD) per completed course of LTBI therapy. Secondary cost analyses were performed to consider varying assumptions regarding commercial cost of rifapentine.

RESULTS:

Overall, 34 of 40 (85%) participants in the 9H group and 36/40 (90%) in the 3HR group completed therapy. One patient in the 3HP group was hospitalised for a febrile illness; no hospitalisations were recorded in the 9H group. The cost per completed course of 9H was 601 AUD, while that of 3HP was significantly lower at 511 AUD (P < 0.01).

CONCLUSIONS:

This study provides cost analysis evidence to support the use of 3HP for the treatment of LTBI in Australia.

© 2017 Royal Australasian College of Physicians.

BACKGROUND:

Tuberculosis (TB) is a serious health problem in Papua New Guinea (PNG) with an estimated 30000 new cases and 3800 deaths each year. In the Balimo region of the Western Province, diagnosis relies on clinical manifestations and on the microscopic detection of acid-fast bacilli (AFB) in sputum smears, a technique with limited sensitivity.

METHODS:

A molecular diagnosis assay targeting DNA extracted from archived sputum smear slides collected from the Balimo region (2012-2014) was conducted, without the need for a viable culture. The presence of Mycobacterium sp on 1162 slides prepared from 345 sputum samples was assessed using a real-time PCR (qPCR) approach.

RESULTS:

The qPCR technique identified the presence of mycobacteria in 35.4% of the smear slides and 59.7% of the tested sputum samples. Poor agreement was observed between the two diagnosis methods (smear AFB microscopy versus qPCR), with 100 AFB-positive sputum samples compared to 206 qPCR-positive sputum samples overall. Treatment was initiated in 90.2% of the smear-positive cases. Unnecessary treatment of 'false-positive' TB cases (AFB-negative/qPCR-negative) was very low (8.6%) and was even lower when the nine patients diagnosed with extrapulmonary TB were excluded from the analysis. However, the prevalence of false-negatives (AFB-negative/qPCR-positive) was high (28.5%).

CONCLUSIONS:

Undetected smear-negative TB is occurring in the Balimo region of PNG, as well as some unnecessary empirical treatment. Molecular methods of diagnosis could greatly reduce the frequency of inappropriate clinical assessment, as well as providing point-of-care diagnosis. This may provide substantial patient and programmatic benefits, including lowering the economic burden on patients from rural areas seeking medical diagnosis in Balimo.

Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

INTRODUCTION:

The sequelae of multidrug-resistant tuberculosis (MDR-TB) are poorly understood and inconsistently reported. We will aim to assess the existing evidence for the clinical, psychological, social and economic sequelae of MDR-TB and to assess the health-related quality of life in patients with MDR-TB.

METHODS AND ANALYSIS:

We will perform a systematic review and meta-analysis of published studies reporting sequelae of MDR-TB. We will search PubMed, SCOPUS, ProQuest, Web of Science and PsychINFO databases up to 5 September 2017. MDR-TB sequelae will include any clinical, psychological, social and economic effects as well as health-related quality of life that occur after MDR-TB treatment or illness. Two researchers will screen the titles and abstracts of all citations identified in our search, extract data, and assess the scientific quality using standardised formats. Providing there is appropriate comparability in the studies, we will use a random-effects meta-analysis model to produce pooled estimates of MDR-TB sequelae from the included studies. We will stratify the analyses based on treatment regimen, comorbidities (such as HIV status and diabetes mellitus), previous TB treatment history and study setting.

ETHICS AND DISSEMINATION:

As this study will be based on published data, ethical approval is not required. The final report will be disseminated through publication in a peer-reviewed scientific journal and will also be presented at relevant conferences.

PROSPERO REGISTRATION NUMBER:

CRD42017073182.

© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

We performed a systematic review and meta-analyses of studies assessing tuberculosis (TB) patient-related risk factors for transmission of Mycobacterium tuberculosis infection. Meta-analyses were conducted for sputum smear-positivity, lung cavitation and HIV seropositivity of index patients with both crude and adjusted odds ratios (AORs) pooled using random effect models. Thirty-seven studies were included in the review. We found that demographic characteristics such as age and sex were not significant risk factors, while behaviours such as smoking and alcohol intake were associated with infectiousness although inconsistently. Treatment delay of >28 days was a significant predictor of greater infectiousness. Contacts of sputum smear-positive index patients were found to be more likely to be infected than contacts of sputum smear-negative patients, with a pooled AOR of 2.15 (95% confidence interval (CI) 1.47-3.17, I 2 = 38%). Similarly, contacts of patients with the cavitary disease were around twice as likely to be infected as contacts of patients without cavitation (pooled AOR 1.9, 95% CI 1.26-2.84, I 2 = 63%). In contrast, HIV seropositive patients were associated with few contact infections than HIV seronegative patients (AOR 0.45, 95% CI 0.26-0.80, I 2 = 52%). In conclusion, behavioural and clinical characteristics of TB patients can be used to identify highly infectious patients for targeted interventions.

AIM:

Our aim was threefold: first, to determine the incidence of active TB in our cohort, second to investigate the risk factors for active TB and third, to understand current screening practices. The ultimate goal was to use our findings to inform development of local and national guidelines.

METHODS:

The records of all adult patients who underwent renal transplantation at our centre from 2005 to 2014 were retrospectively reviewed to assess current screening practices, the risks for and burden of active TB.

RESULTS:

A total of 660 individuals underwent renal transplantation during this period, totalling 3647 person years of follow up. Two patients were diagnosed with active TB after renal transplant, resulting in an incidence of 55 per 100 000 person-years. Of 656 transplant recipients, 102 (15.5%) were born in high TB incidence countries and 89 (13.5%) had an interferon gamma release assay (IGRA) at any point. Individuals born in high TB risk countries had a much higher incidence of active TB (353 per 100 000 person-years). Ten individuals had positive IGRA tests, of whom two were treated for active TB, two received chemoprophylaxis and six were not treated.

CONCLUSIONS:

In the absence of formal guidelines, IGRA-based screening for LTBI was infrequently performed. Our data suggest that screening and treatment of renal transplant recipients born in high incidence countries is an important preventive measure.

© 2018 Asian Pacific Society of Nephrology.

BACKGROUND:

Motivated by the unexplained variation in the performance of some vaccines across different settings, we extend previous theoretical work to consider the potential impact of incomplete case ascertainment on measures of vaccine efficacy (VE), which is more likely in subclinical or clinically unimportant infections, such as rotavirus gastroenteritis.

METHODS:

By simulating the measurement of VE under outbreak conditions using a discrete time stochastic SIR model, we compare three commonly used measures, VE_Risk, VE_Rate, and VE_Hazard, calculated respectively based on risk ratio, rate ratio and hazard ratio of disease. We investigate how these measures are influenced by factors such as biological activity, action mechanism of vaccine, proportion of cases ascertained, and underlying force of infection.

RESULTS:

Under plausibly low levels of ascertainment, the group with the most infections, and therefore the most missed cases, has the most falsely inflated denominator, producing similar rates in the control and intervention groups. As a result, VE_Rate and VE_Hazard will underestimate the true VE compared to high case ascertainment scenarios. Furthermore, the extent of underestimation is greater for leaky vaccine models with lower biological protective effects and under conditions which are conducive to high transmission.

CONCLUSIONS:

This study demonstrates that a biologically active vaccine may produce a low measured VE under a range of epidemiological, vaccine-related and logistical conditions. Low case ascertainment may partly explain the observed heterogeneity in the performance of rotavirus vaccine across different settings, and should be considered in the design and interpretation of future field trials.

Copyright © 2018 Elsevier Ltd. All rights reserved.

BACKGROUND:

Much of the extensive research regarding transmission of malaria is underpinned by mathematical modelling. Compartmental models, which focus on interactions and transitions between population strata, have been a mainstay of such modelling for more than a century. However, modellers are increasingly adopting agent-based approaches, which model hosts, vectors and/or their interactions on an individual level. One reason for the increasing popularity of such models is their potential to provide enhanced realism by allowing system-level behaviours to emerge as a consequence of accumulated individual-level interactions, as occurs in real populations.

METHODS:

A systematic review of 90 articles published between 1998 and May 2018 was performed, characterizing agent-based models (ABMs) relevant to malaria transmission. The review provides an overview of approaches used to date, determines the advantages of these approaches, and proposes ideas for progressing the field.

RESULTS:

The rationale for ABM use over other modelling approaches centres around three points: the need to accurately represent increased stochasticity in low-transmission settings; the benefits of high-resolution spatial simulations; and heterogeneities in drug and vaccine efficacies due to individual patient characteristics. The success of these approaches provides avenues for further exploration of agent-based techniques for modelling malaria transmission. Potential extensions include varying elimination strategies across spatial landscapes, extending the size of spatial models, incorporating human movement dynamics, and developing increasingly comprehensive parameter estimation and optimization techniques.

CONCLUSION:

Collectively, the literature covers an extensive array of topics, including the full spectrum of transmission and intervention regimes. Bringing these elements together under a common framework may enhance knowledge of, and guide policies towards, malaria elimination. However, because of the diversity of available models, endorsing a standardized approach to ABM implementation may not be possible. Instead it is recommended that model frameworks be contextually appropriate and sufficiently described. One key recommendation is to develop enhanced parameter estimation and optimization techniques. Extensions of current techniques will provide the robust results required to enhance current elimination efforts.

OBJECTIVE:

Papua New Guinea (PNG) has an emerging tuberculosis (TB) epidemic which has become a national public health priority. In Western Province, there are few data about TB outside Daru and the South Fly District. This study describes the epidemiology of TB diagnosed at Balimo District Hospital (BDH) in the Middle Fly District of Western Province, PNG.

METHODS:

All patients (n = 1614) diagnosed with TB at BDH from April 2013 to February 2017 were recorded. Incidence of reported new cases was calculated for the combined Balimo Urban and Gogodala Rural local level government areas. Analyses investigated patient demographic and clinical information, differences between pulmonary and extrapulmonary TB patients, and predictors of treatment failure.

RESULTS:

The average case notification rate (2014-2016) was 727 TB cases per 100 000 people per year. One-quarter of TB cases were in children, and 77.1% of all cases had an extrapulmonary TB diagnosis. There was a 1:1.1 ratio of female to male TB cases. When comparing pulmonary and extrapulmonary TB patients, extrapulmonary TB was more likely in those aged up to 14 years and over 54 years. Extrapulmonary TB was more likely in new patients, and pulmonary TB more likely in previously treated patients. Residence in rural regions was associated with treatment failure.

CONCLUSION:

There is a high burden of TB in the Balimo region, including a very high proportion of extrapulmonary TB. These factors emphasise the importance of BDH as the primary hospital for TB cases in the Balimo region and the Middle Fly District, and the need for resources and staff to manage both drug-susceptible and drug-resistant TB cases.

© 2018 John Wiley & Sons Ltd.

BACKGROUND:

Clinical studies and mathematical simulation suggest that active surveillance with contact isolation is associated with reduced vancomycin-resistant enterococci (VRE) prevalence compared to passive surveillance. Models using pre- and post-intervention data that account for the imperfect observation and serial dependence of VRE transmission events can better estimate the effectiveness of active surveillance and subsequent contact isolation; however, such analyses have not been performed.

METHODS:

A mathematical model was fitted to surveillance data collected pre- and post-implementation of active surveillance with contact isolation in the haematology-oncology ward. We developed a Hidden Markov Model to describe undetected and observed VRE colonisation/infection status based on the detection activities in the ward. Bayesian inference was used to estimate transmission rates. The effectiveness of active surveillance was assumed to be via increased detection and subsequent contact isolation of VRE positive patients.

RESULTS:

We estimated that 31% (95% credible interval: 0.33-85%) of the VRE transmissions were due to cross-transmission between patients. The ratio of transmission rates from patients with contact isolation versus those without contact isolation was 0.33 (95% credible interval: 0.050-1.22).

CONCLUSIONS:

The majority of the VRE acquisitions in the haematology-oncology ward was estimated to be due to background rates of VRE, rather than within ward patient to patient acquisition. The credible interval for cross-transmission was wide which results in a large degree of uncertainty in the estimates. Factors that could account for background VRE acquisition include endogenous acquisition from antibiotic selection pressure and VRE in the environment. Contact isolation was not significantly associated with reduced VRE transmission in settings where the majority of VRE acquisition was due to background acquisition, emphasising the need to identify and address the source of acquisition. As the credible interval for the ratio of VRE transmission in contact isolated versus non-contact isolated patients crossed 1, there is a probability that the transmission rate in contact isolation was not lower. Our finding highlights the need to optimise infection control measures other than active surveillance for VRE and subsequent contact isolation to reduce VRE transmission. Such measures could include antimicrobial stewardship, environmental cleaning, and hand hygiene.

BACKGROUND:

Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden.

METHODS:

We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO ( CRD42016036655 ).

RESULTS:

We identified 168 eligible studies with spatial methods used to describe the spatial distribution (n = 154), spatial clusters (n = 73), predictors of spatial patterns (n = 64), the role of congregate settings (n = 3) and the household (n = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff's spatial scan statistic followed by local Moran's I and Getis and Ord's local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined.

CONCLUSIONS:

A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control.

BACKGROUND:

Mental health disorders, social stress, and poor health-related quality of life are commonly reported among people with tuberculosis (TB). We conducted a systematic review and meta-analysis to quantify mental health disorders, social stressors, and health-related quality of life in patients with multidrug-resistant tuberculosis (MDR-TB).

METHODS:

We searched PubMed, SCOPUS, ProQuest, Web of Science, and PsycINFO databases for studies that reported data on mental health disorders, social stressors, and health-related quality of life among MDR-TB patients. Hand-searching the reference lists of included studies was also performed. Studies were selected according to pre-defined selection criteria and data were extracted by two authors. Pooled prevalence and weighted mean difference estimates were performed using random-effects meta-analysis. Heterogeneity was explored using meta-regression, and subgroup analyses were performed.

RESULTS:

We included a total of 40 studies that were conducted in 20 countries. Depression, anxiety, and psychosis were the most common mental health disorders reported in the studies. The overall pooled prevalence was 25% (95% confidence interval (CI): 14, 39) for depression, 24% (95% CI: 2, 57) for anxiety, and 10% (95% CI: 7, 14) for psychosis. There was substantial heterogeneity in the estimates. The stratified analysis showed that the prevalence of psychosis was 4% (95% CI: 0, 22) before MDR-TB treatment commencement, and 9% (95% CI: 5, 13) after MDR-TB treatment commencement. The most common social stressors reported were stigma, discrimination, isolation, and a lack of social support. Health-related quality of life was significantly lower among MDR-TB patients when compared to drug-susceptible TB patients (Q = 9.88, p = 0.01, I² = 80%).

CONCLUSIONS:

This review found that mental health and social functioning are compromised in a significant proportion of MDR-TB patients, a finding confirmed by the poor health-related quality of life reported. Thus, there is a substantial need for integrating mental health services, social protection and social support into the clinical and programmatic management of MDR-TB.

Copyright © 2018. Published by Elsevier Ltd.

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.

© The Author(s) 2018. Published by Oxford University Press for the Infectious Diseases Society of America.

A tuberculosis (TB) model that accounts for heterogeneity in host susceptibility to tuberculosis is proposed, with the aim of investigating the implications this may have for the effectiveness of public health interventions. The model examines the possibility that recovered individuals treated from active TB and individuals treated with preventive therapy acquire different levels of immunity. This contrasts with recent studies that assume the two cohorts acquire the same level of immunity, and therefore both groups are reinfected at the same rate. The analysis presented here examines the impact of this assumption when designing intervention strategies. Comparison of reinfection rates between cohorts treated with preventive therapy and recovered individuals who were previously treated for active TB provides important epidemiological insights. It is found that the reinfection rate of the cohort treated with preventive therapy is the one that plays the key role in qualitative changes in TB dynamics. By contrast, the reinfection rate of recovered individuals (previously treated from active TB) plays a minor role. Moreover, the study shows that preventive treatment of individuals during early latency is always beneficial regardless of the level of susceptibility to reinfection. Further, if patients have greater immunity following treatment for late latent infection, then treatment is again beneficial. However, if susceptibility increases following treatment for late latent infection, the effect of treatment depends on the epidemiological setting. That is: (i) in (very) low burden settings, the effect on reactivation predominates and the burden declines with treatment; (ii) in moderate to high burden settings the effect of reinfection predominates and burden increases with treatment. The effect is most dominant between the two reinfection thresholds, RT2 and RT1, respectively associated with individuals being treated with preventive therapy and individuals with untreated late latent TB infection.

Short-course regimens for multidrug-resistant tuberculosis (MDR-TB) are urgently needed. Limited data suggest that the new drug bedaquiline (BDQ) may have the potential to shorten MDR-TB treatment to less than 6 months when used in conjunction with standard anti-TB drugs. However, the feasibility of BDQ in shortening MDR-TB treatment duration remains to be established. Mathematical modeling provides a platform to investigate different treatment regimens and predict their efficacy. We developed a mathematical model to capture the immune response to TB inside a human host environment. This model was then combined with a pharmacokinetic-pharmacodynamic model to simulate various short-course BDQ-containing regimens. Our modeling suggests that BDQ could reduce MDR-TB treatment duration to just 18 weeks (4 months) while still maintaining a very high treatment success rate (100% for daily BDQ for 2 weeks, or 95% for daily BDQ for 1 week during the intensive phase). The estimated time to bacterial clearance of these regimens ranges from 27 to 33 days. Our findings provide the justification for empirical evaluation of short-course BDQ-containing regimens. If short-course BDQ-containing regimens are found to improve outcomes, then we anticipate clear cost savings and a subsequent improvement in the efficiency of national TB programs.

Copyright © 2018 American Society for Microbiology.

Migration is a key driver of tuberculosis (TB) in many low-incidence settings, with the majority of TB cases attributed to reactivation of latent TB (LTBI) acquired overseas. A greater understanding of LTBI risk in heterogeneous migrant populations would aid health planning. We aimed to estimate the LTBI prevalence and distribution among locally born and overseas-born Australians.Annual risks of TB infection estimates were applied to population cohorts (by country of birth, year of arrival and age) in Australian census data in 2006, 2011 and 2016.Both the absolute number and proportion of Australian residents with LTBI increased from 4.6% (interquartile range (IQR) 4.2-5.2%) in 2006 to 5.1% (IQR 4.7-5.5%) in 2016, due to the increasing proportion of the population born overseas (23.8% in 2006 to 28.3% in 2016). Of all residents estimated to have LTBI in 2016; 93.2% were overseas born, 21.6% were aged <35 years and 34.4% had migrated to Australia since 2007.The overall prevalence of LTBI in Australia is low. Some residents, particularly migrants from high-incidence settings, may have considerably higher risk of LTBI, and these findings allow for tailored public health interventions to reduce the risk and impact of future TB disease.

Copyright ©ERS 2018.

OBJECTIVE:

Accurate and timely diagnosis of tuberculosis (TB) is essential to control the global pandemic. Currently available immunodiagnostic tests cannot discriminate between latent tuberculosis infection (LTBI) and active tuberculosis. This study aimed to determine whether candidate mycobacterial antigen-stimulated cytokine biomarkers can discriminate between TB-uninfected and TB-infected adults, and additionally between LTBI and active TB disease.

METHODS:

193 adults were recruited, and categorised into four unambiguous diagnostic groups: microbiologically-proven active TB, LTBI, sick controls (non-TB lower respiratory tract infections) and healthy controls. Whole blood assays were used to determine mycobacterial antigen (CFP-10, ESAT-6, PPD)-stimulated cytokine (IL-1ra, IL-2, IL-10, IL-13, TNF-α, IFN-γ, IP-10 and MIP-1β) responses, measured by Luminex multiplex immunoassay.

RESULTS:

The background-corrected mycobacterial antigen-stimulated cytokine responses of all eight cytokines were significantly higher in TB-infected participants compared with TB-uninfected individuals, with IL-2 showing the best performance characteristics. In addition, mycobacterial antigen-stimulated responses with IL-1ra, IL-10 and TNF-α were higher in participants with active TB compared those with LTBI, reaching statistical significance with PPD stimulation, although there was a degree of overlap between the two groups.

CONCLUSION:

Mycobacterial antigen-stimulated cytokine responses may prove useful in future immunodiagnostic tests to discriminate between tuberculosis-infected and tuberculosis-uninfected individual, and potentially between LTBI and active tuberculosis.

Copyright © 2018 Elsevier Ltd. All rights reserved.

Background:

Latent tuberculosis infection (LTBI) is a critical driver of the global burden of active TB, and therefore LTBI treatment is key for TB elimination. Treatment regimens for LTBI include self-administered daily isoniazid for 6 (6H) or 9 (9H) months, self-administered daily rifampicin plus isoniazid for 3 months (3RH), self-administered daily rifampicin for 4 months (4R) and weekly rifapentine plus isoniazid for 3 months self-administered (3HP-SAT) or administered by a healthcare worker as directly observed therapy (3HP-DOT). Data on the relative cost-effectiveness of these regimens are needed to assist policymakers and clinicians in selecting an LTBI regimen.

Objectives:

To evaluate the cost-effectiveness of all regimens for treating LTBI.

Methods:

We developed a Markov model to investigate the cost-effectiveness of 3HP-DOT, 3HP-SAT, 4R, 3RH, 9H and 6H for LTBI treatment in a cohort of 10000 adults with LTBI. Cost-effectiveness was evaluated from a health system perspective over a 20 year time horizon.

Results:

Compared with no preventive treatment, 3HP-DOT, 3HP-SAT, 4R, 3RH, 9H and 6H prevented 496, 470, 442, 418, 370 and 276 additional cases of active TB per 10000 patients, respectively. All regimens reduced costs and increased QALYs compared with no preventive treatment. 3HP was more cost-effective under DOT than under SAT at a cost of US$27948 per QALY gained.

Conclusions:

Three months of weekly rifapentine plus isoniazid is more cost-effective than other regimens. Greater recognition of the benefits of short-course regimens can contribute to the scale-up of prevention and achieving the 'End TB' targets.

We investigate the global dynamics of a general Kermack-McKendrick-type epidemic model formulated in terms of a system of renewal equations. Specifically, we consider a renewal model for which both the force of infection and the infected removal rates are arbitrary functions of the infection age, [Formula: see text], and use the direct Lyapunov method to establish the global asymptotic stability of the equilibrium solutions. In particular, we show that the basic reproduction number, [Formula: see text], represents a sharp threshold parameter such that for [Formula: see text], the infection-free equilibrium is globally asymptotically stable; whereas the endemic equilibrium becomes globally asymptotically stable when [Formula: see text], i.e. when it exists.

Papua New Guinea (PNG) has a high burden of tuberculosis (TB), including drug-resistant TB (DR-TB). DR-TB has been identified in patients in Western Province, although there has been limited study outside the provincial capital of Daru. This study focuses on the Balimo region of Western Province, aiming to identify the proportion of DR-TB, and characterise Mycobacterium tuberculosis (MTB) drug resistance-associated gene mutations. Sputum samples were investigated for MTB infection using published molecular methods. DNA from MTB-positive samples was amplified and sequenced, targeting the rpoB and katG genes to identify mutations associated with rifampicin and isoniazid resistance respectively. A total of 240 sputum samples were collected at Balimo District Hospital (BDH). Of these, 86 were classified as positive based on the results of the molecular assays. For samples where rpoB sequencing was successful, 10.0% (5/50, 95% CI 4.4⁻21.4%) were considered rifampicin-resistant through detection of drug resistance-associated mutations. We have identified high rates of presumptive DR-TB in the Balimo region of Western Province, PNG. These results emphasise the importance of further surveillance, and strengthening of diagnostic and treatment services at BDH and throughout Western Province, to facilitate detection and treatment of DR-TB, and limit transmission in this setting.

In this retrospective study, we used whole-genome sequencing (WGS) to delineate transmission dynamics, characterize drug-resistance markers, and identify risk factors of transmission among Papua New Guinea residents of the Torres Strait Protected Zone (TSPZ) who had tuberculosis diagnoses during 2010-2015. Of 117 isolates collected, we could acquire WGS data for 100; 79 were Beijing sublineage 2.2.1.1, which was associated with active transmission (odds ratio 6.190, 95% CI 2.221-18.077). Strains were distributed widely throughout the TSPZ. Clustering occurred more often within than between villages (p = 0.0013). Including 4 multidrug-resistant tuberculosis isolates from Australia citizens epidemiologically linked to the TSPZ into the transmission network analysis revealed 2 probable cross-border transmission events. All multidrug-resistant isolates (33/104) belonged to Beijing sublineage 2.2.1.1 and had high-level isoniazid and ethionamide co-resistance; 2 isolates were extensively drug resistant. Including WGS in regional surveillance could improve tuberculosis transmission tracking and control strategies within the TSPZ.

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.

BACKGROUND:

Tuberculosis (TB) is the leading cause of death from an infectious disease in Ethiopia, killing more than 30 thousand people every year. This study aimed to determine whether the rates of poor TB treatment outcome varied geographically across Ethiopia at district and zone levels and whether such variability was associated with socioeconomic, behavioural, health care access, or climatic conditions.

METHODS:

A geospatial analysis was conducted using national TB data reported to the health management information system (HMIS), for the period 2015-2017. The prevalence of poor TB treatment outcomes was calculated by dividing the sum of treatment failure, death and loss to follow-up by the total number of TB patients. Binomial logistic regression models were computed and a spatial analysis was performed using a Bayesian framework. Estimates of parameters were generated using Markov chain Monte Carlo (MCMC) simulation. Geographic clustering was assessed using the Getis-Ord Gi* statistic, and global and local Moran's I statistics.

RESULTS:

A total of 223,244 TB patients were reported from 722 districts in Ethiopia during the study period. Of these, 63,556 (28.5%) were cured, 139,633 (62.4%) completed treatment, 6716 (3.0%) died, 1459 (0.7%) had treatment failure, and 12,200 (5.5%) were lost to follow-up. The overall prevalence of a poor TB treatment outcome was 9.0% (range, 1-58%). Hot-spots and clustering of poor TB treatment outcomes were detected in districts near the international borders in Afar, Gambelia, and Somali regions and cold spots were detected in Oromia and Amhara regions. Spatial clustering of poor TB treatment outcomes was positively associated with the proportion of the population with low wealth index (OR: 1.01; 95%CI: 1.0, 1.01), the proportion of the population with poor knowledge about TB (OR: 1.02; 95%CI: 1.01, 1.03), and higher annual mean temperature per degree Celsius (OR: 1.15; 95% CI: 1.08, 1.21).

CONCLUSIONS:

This study showed significant spatial variation in poor TB treatment outcomes in Ethiopia that was related to underlying socioeconomic status, knowledge about TB, and climatic conditions. Clinical and public health interventions should be targeted in hot spot areas to reduce poor TB treatment outcomes and to achieve the national End-TB Strategy targets.

The tuberculosis (TB) health burden in Fiji has been declining in recent years, although challenges remain in improving control of the diabetes co-epidemic and achieving adequate case detection across the widely dispersed archipelago. We applied a mathematical model of TB transmission to the TB epidemic in Fiji that captured the historical reality over several decades, including age stratification, diabetes, varying disease manifestations, and incorrect diagnoses. Next, we simulated six intervention scenarios that are under consideration by the Fiji National Tuberculosis Program. Our findings show that the interventions were able to achieve only modest improvements in disease burden, with awareness raising being the most effective intervention to reduce TB incidence, and treatment support yielding the highest impact on mortality. These improvements would fall far short of the ambitious targets that have been set by the country, and could easily be derailed by moderate increases in the diabetes burden. Furthermore, the effectiveness of the interventions was limited by the extensive pool of latent TB infection, because the programs were directed at only active cases, and thus were unlikely to achieve the desired reductions in burden. Therefore, it is essential to address the co-epidemic of diabetes and treat people with latent TB infection.

BACKGROUND:

The 2050 Millennium Development Goals (MDG) for tuberculosis (TB) aim for elimination of TB as a public health issue. We used a mathematical modelling approach to evaluate the feasibility of this target in a low-prevalence setting with immigration-related strategies directed at latent tuberculosis.

METHODS:

We used a stochastic individual-based model to simulate tuberculosis disease among immigrants to Victoria, Australia; a representative low-transmission setting. A variety of screening and treatment approaches aimed at preventing reactivation of latent infection were applied to evaluate overall tuberculosis incidence reduction and rates of multidrug resistant disease.

RESULTS:

Without additional intervention, tuberculosis incidence was predicted to reach 34.5 cases/million by 2050. Strategies involving the introduction of an available screening/treatment combination reduced TB incidence to between 16.9-23.8 cases/million, and required screening of 136-427 new arrivals for each case of TB prevented. Limiting screening to higher incidence regions of origin was less effective but more efficient.

CONCLUSIONS:

Public health strategies targeting latent tuberculosis infection in immigrants may substantially reduce tuberculosis incidence in a low prevalence region. However, immigration-focused strategies cannot achieve the 2050 MDG and alternative or complementary approaches are required.

© 2014 The Authors. ANZJPH © 2014 Public Health Association of Australia.

We present a mathematical model to simulate tuberculosis (TB) transmission in highly endemic regions of the Asia-Pacific, where epidemiology does not appear to be primarily driven by HIV-coinfection. The ten-compartment deterministic model captures many of the observed phenomena important to disease dynamics, including partial and temporary vaccine efficacy, declining risk of active disease following infection, the possibility of reinfection both during the infection latent period and after treatment, multidrug resistant TB (MDR-TB) and de novo resistance during treatment. We found that the model could not be calibrated to the estimated incidence rate without allowing for reinfection during latency, and that even in the presence of a moderate fitness cost and a lower value of R0, MDR-TB becomes the dominant strain at equilibrium. Of the modifiable programmatic parameters, the rate of detection and treatment commencement was the most important determinant of disease rates with each respective strain, while vaccination rates were less important. Improved treatment of drug-susceptible TB did not result in decreased rates of MDR-TB through prevention of de novo resistance, but rather resulted in a modest increase in MDR-TB through strain replacement. This was due to the considerably greater relative contribution of community transmission to MDR-TB incidence, by comparison to de novo amplification of resistance in previously susceptible strains.

Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Vaccine effect, as measured in clinical trials, may not accurately reflect population-level impact. Furthermore, little is known about how sensitive apparent or real vaccine impacts are to factors such as the risk of re-infection or the mechanism of protection. We present a dynamic compartmental model to simulate vaccination for endemic infections. Several measures of effectiveness are calculated to compare the real and apparent impact of vaccination, and assess the effect of a range of infection and vaccine characteristics on these measures. Although broadly correlated, measures of real and apparent vaccine effectiveness can differ widely. Vaccine impact is markedly underestimated when primary infection provides partial natural immunity, when coverage is high and when post-vaccination infectiousness is reduced. Despite equivalent efficacy, 'all or nothing' vaccines are more effective than 'leaky' vaccines, particularly in settings with high risk of re-infection and transmissibility. Latent periods result in greater real impacts when risk of re-infection is high, but this effect diminishes if partial natural immunity is assumed. Assessments of population-level vaccine effects against endemic infections from clinical trials may be significantly biased, and vaccine and infection characteristics should be considered when modelling outcomes of vaccination programs, as their impact may be dramatic.

BACKGROUND:

It is often stated that the lifetime risk of developing active TB after an index infection is 5% to 10%, one-half of which accrues in the 2 to 5 years following infection. The goal of this study was to determine whether such estimates are consistent with local programmatic data.

METHODS:

This study included close contacts of individuals with active pulmonary TB notified in the Australian state of Victoria from January 1, 2005, to December 31, 2013, who we deemed to have been infected as a result of their exposure. Survival analysis was first performed on the assumption of complete follow-up through to the end of the study period. The analysis was then repeated with imputation of censorship for migration, death, and preventive treatment, using local mortality and migration data combined with programmatic data on the administration of preventive therapy.

RESULTS:

Of 613 infected close contacts, 67 (10.9%) developed active TB during the study period. Assuming complete follow-up, the 1,650-day cumulative hazard was 11.5% (95% CI, 8.9-14.1). With imputation of censorship for death, migration, and preventive therapy, the median 1,650-day cumulative hazard over 10,000 simulations was 14.5% (95% CI, 11.1-17.9). Most risk accrued in the first 5 months after infection, and risk was greatest in the group aged < 5 years, reaching 56.0% with imputation, but it was also elevated in older children (27.6% in the group aged 5-14 years).

CONCLUSIONS:

The risk of active TB following infection is several-fold higher than traditionally accepted estimates, and it is particularly high immediately following infection and in children.

Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Tuberculosis (TB) and multidrug-resistant TB (MDR-TB) are major health problems in Western Province, Papua New Guinea. While comprehensive expansion of TB control programs is desirable, logistical challenges are considerable, and there is substantial uncertainty regarding the true disease burden. We parameterized our previously described mathematical model of Mycobacterium tuberculosis dynamics in Western Province, following an epidemiologic assessment. Five hypothetical scenarios representing alternative programmatic approaches during the period from 2013 to 2023 were developed with local staff. Bayesian uncertainty analyses were undertaken to explicitly acknowledge the uncertainty around key epidemiologic parameters, and an economic evaluation was performed. With continuation of existing programmatic strategies, overall TB incidence remained stable at 555 cases per 100,000 population per year (95% simulation interval (SI): 420, 807), but the proportion of incident cases attributable to MDR-TB increased from 16% to 35%. Comprehensive, provincewide strengthening of existing programs reduced incidence to 353 cases per 100,000 population per year (95% SI: 246, 558), with 46% being cases of MDR-TB, while incorporating programmatic management of MDR-TB into these programs reduced incidence to 233 cases per 100,000 population per year (95% SI: 198, 269) with 14% MDR-TB. Most economic costs were due to hospitalization during the intensive treatment phase. Broad scale-up of TB control activities in Western Province with incorporation of programmatic management of MDR-TB is vital if control is to be achieved. Community-based treatment approaches are important to reduce the associated economic costs.

© The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

OBJECTIVES:

Multidrug-resistant tuberculosis (MDR-TB) is a threat to tuberculosis (TB) control. To guide TB control, it is essential to understand the extent to which and the circumstances in which MDR-TB will replace drug-susceptible TB (DS-TB) as the dominant phenotype. The issue was examined by assessing evidence from genomics, pharmacokinetics, and epidemiology studies. This evidence was then synthesized into a mathematical model.

METHODS:

This model considers two TB strains, one with and one without an MDR phenotype. It was considered that intrinsic transmissibility may be different between the two strains, as may the control response including the detection, treatment failure, and default rates. The outcomes were explored in terms of the incidence of MDR-TB and time until MDR-TB surpasses DS-TB as the dominant strain.

RESULTS AND CONCLUSIONS:

The ability of MDR-TB to dominate DS-TB was highly sensitive to the relative transmissibility of the resistant strain; however, MDR-TB could dominate even when its transmissibility was modestly reduced (to between 50% and 100% as transmissible as the DS-TB strain). This model suggests that it may take decades or more for strain replacement to occur. It was also found that while the amplification of resistance is the early cause of MDR-TB, this will rapidly give way to person-to-person transmission.

Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

BACKGROUND:

The post-2015 End TB Strategy sets global targets of reducing tuberculosis incidence by 50% and mortality by 75% by 2025. We aimed to assess resource requirements and cost-effectiveness of strategies to achieve these targets in China, India, and South Africa.

METHODS:

We examined intervention scenarios developed in consultation with country stakeholders, which scaled up existing interventions to high but feasible coverage by 2025. Nine independent modelling groups collaborated to estimate policy outcomes, and we estimated the cost of each scenario by synthesising service use estimates, empirical cost data, and expert opinion on implementation strategies. We estimated health effects (ie, disability-adjusted life-years averted) and resource implications for 2016-35, including patient-incurred costs. To assess resource requirements and cost-effectiveness, we compared scenarios with a base case representing continued current practice.

FINDINGS:

Incremental tuberculosis service costs differed by scenario and country, and in some cases they more than doubled existing funding needs. In general, expansion of tuberculosis services substantially reduced patient-incurred costs and, in India and China, produced net cost savings for most interventions under a societal perspective. In all three countries, expansion of access to care produced substantial health gains. Compared with current practice and conventional cost-effectiveness thresholds, most intervention approaches seemed highly cost-effective.

INTERPRETATION:

Expansion of tuberculosis services seems cost-effective for high-burden countries and could generate substantial health and economic benefits for patients, although substantial new funding would be required. Further work to determine the optimal intervention mix for each country is necessary.

FUNDING:

Bill & Melinda Gates Foundation.

Copyright © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license. Published by Elsevier Ltd.. All rights reserved.

BACKGROUND:

The post-2015 End TB Strategy proposes targets of 50% reduction in tuberculosis incidence and 75% reduction in mortality from tuberculosis by 2025. We aimed to assess whether these targets are feasible in three high-burden countries with contrasting epidemiology and previous programmatic achievements.

METHODS:

11 independently developed mathematical models of tuberculosis transmission projected the epidemiological impact of currently available tuberculosis interventions for prevention, diagnosis, and treatment in China, India, and South Africa. Models were calibrated with data on tuberculosis incidence and mortality in 2012. Representatives from national tuberculosis programmes and the advocacy community provided distinct country-specific intervention scenarios, which included screening for symptoms, active case finding, and preventive therapy.

FINDINGS:

Aggressive scale-up of any single intervention scenario could not achieve the post-2015 End TB Strategy targets in any country. However, the models projected that, in the South Africa national tuberculosis programme scenario, a combination of continuous isoniazid preventive therapy for individuals on antiretroviral therapy, expanded facility-based screening for symptoms of tuberculosis at health centres, and improved tuberculosis care could achieve a 55% reduction in incidence (range 31-62%) and a 72% reduction in mortality (range 64-82%) compared with 2015 levels. For India, and particularly for China, full scale-up of all interventions in tuberculosis-programme performance fell short of the 2025 targets, despite preventing a cumulative 3·4 million cases. The advocacy scenarios illustrated the high impact of detecting and treating latent tuberculosis.

INTERPRETATION:

Major reductions in tuberculosis burden seem possible with current interventions. However, additional interventions, adapted to country-specific tuberculosis epidemiology and health systems, are needed to reach the post-2015 End TB Strategy targets at country level.

FUNDING:

Bill and Melinda Gates Foundation.

Copyright © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license. Published by Elsevier Ltd.. All rights reserved.

BACKGROUND:

Multidrug-resistant tuberculosis (MDR-TB) is a major threat to global TB control. MDR-TB treatment regimens typically have a high pill burden, last 20 months or more and often lead to unsatisfactory outcomes. A 9-11 month regimen with seven antibiotics has shown high success rates among selected MDR-TB patients in different settings and is conditionally recommended by the World Health Organization.

METHODS:

We construct a transmission-dynamic model of TB to estimate the likely impact of a shorter MDR-TB regimen when applied in a low HIV prevalence region of Uzbekistan (Karakalpakstan) with high rates of drug resistance, good access to diagnostics and a well-established community-based MDR-TB treatment programme providing treatment to around 400 patients. The model incorporates acquisition of additional drug resistance and incorrect regimen assignment. It is calibrated to local epidemiology and used to compare the impact of shorter treatment against four alternative programmatic interventions.

RESULTS:

Based on empirical outcomes among MDR-TB patients and assuming no improvement in treatment success rates, the shorter regimen reduced MDR-TB incidence from 15.2 to 9.7 cases per 100,000 population per year and MDR-TB mortality from 3.0 to 1.7 deaths per 100,000 per year, achieving comparable or greater gains than the alternative interventions. No significant increase in the burden of higher levels of resistance was predicted. Effects are probably conservative given that the regimen is likely to improve success rates.

CONCLUSIONS:

In addition to benefits to individual patients, we find that shorter MDR-TB treatment regimens also have the potential to reduce transmission of resistant strains. These findings are in the epidemiological setting of treatment availability being an important bottleneck due to high numbers of patients being eligible for treatment, and may differ in other contexts. The high proportion of MDR-TB with additional antibiotic resistance simulated was not exacerbated by programmatic responses and greater gains may be possible in contexts where the regimen is more widely applicable.

SETTING:

Isoniazid preventive therapy (IPT) is effective for preventing active tuberculosis (TB), although its mechanism of action is poorly understood and the optimal disease burden for IPT use has not been defined.

OBJECTIVE:

To describe the relationship between TB incidence and IPT effectiveness.

METHODS:

We constructed a model of TB transmission dynamics to investigate IPT effectiveness under various epidemiological settings. The model structure was intended to be highly adaptable to uncertainty in both input parameters and the mechanism of action of IPT. To determine the optimal setting for IPT use, we identified the lowest number needed to treat (NNT) with IPT to prevent one case of active TB.

RESULTS:

We found that the NNT as a function of TB incidence shows a 'U-shape', whereby IPT impact is greatest at an intermediate incidence and attenuated at both lower and higher incidence levels. This U-shape was observed over a broad range of parameter values; the optimal TB incidence was between 500 and 900 cases per 100 000 per year.

CONCLUSIONS:

TB burden is a critical factor to consider when making decisions about communitywide implementation of IPT. We believe that the total disease burden should not preclude programmatic application of IPT.

BACKGROUND:

Globally 3.9% of new and 21% of re-treatment tuberculosis (TB) cases are multidrug-resistant or rifampicin-resistant (MDR/RR), which is often interpreted as evidence that drug resistance results mainly from poor treatment adherence. This study aims to assess the respective contributions of the different causal pathways leading to MDR/RR-TB at re-treatment.

METHODS:

We use a simple mathematical model to simulate progression between the different stages of disease and treatment for patients diagnosed with TB. The model is parameterised using region and country-specific TB disease burden data reported by the World Health Organization (WHO). The contributions of four separate causal pathways to MDR/RR-TB among re-treatment cases are estimated: I) initial drug-susceptible TB with resistance amplification during treatment; II) initial MDR/RR-TB inappropriately treated as drug-susceptible TB; III) MDR/RR-TB relapse despite appropriate treatment; and IV) re-infection with MDR/RR-TB.

RESULTS:

At the global level, Pathways I, II, III and IV contribute 38% (28-49, 95% Simulation Interval), 44% (36-52, 95% SI), 6% (5-7, 95% SI) and 12% (7-19, 95% SI) respectively to the burden of MDR/RR-TB among re-treatment cases. Pathway II is dominant in the Western Pacific (74%; 67-80 95% SI), Eastern Mediterranean (68%; 60-74 95% SI) and European (53%; 48-59 95% SI) regions, while Pathway I makes the greatest contribution in the American (53%; 40-66 95% SI), African (43%; 28-61 95% SI) and South-East Asian (50%; 40-59 95% SI) regions.

CONCLUSIONS:

Globally, failure to diagnose MDR/RR-TB at first presentation is the leading cause of the high proportion of MDR/RR-TB among re-treatment cases. These findings highlight the need for contextualised solutions to limit the impact and spread of MDR/RR-TB.

OBJECTIVES:

Multidrug-resistant tuberculosis (MDR-TB) is a threat to tuberculosis (TB) control. To guide TB control, it is essential to understand the extent to which and the circumstances in which MDR-TB will replace drug-susceptible TB (DS-TB) as the dominant phenotype. The issue was examined by assessing evidence from genomics, pharmacokinetics, and epidemiology studies. This evidence was then synthesized into a mathematical model.

METHODS:

This model considers two TB strains, one with and one without an MDR phenotype. It was considered that intrinsic transmissibility may be different between the two strains, as may the control response including the detection, treatment failure, and default rates. The outcomes were explored in terms of the incidence of MDR-TB and time until MDR-TB surpasses DS-TB as the dominant strain.

RESULTS AND CONCLUSIONS:

The ability of MDR-TB to dominate DS-TB was highly sensitive to the relative transmissibility of the resistant strain; however, MDR-TB could dominate even when its transmissibility was modestly reduced (to between 50% and 100% as transmissible as the DS-TB strain). This model suggests that it may take decades or more for strain replacement to occur. It was also found that while the amplification of resistance is the early cause of MDR-TB, this will rapidly give way to person-to-person transmission.

Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Multidrug-resistant and rifampicin-resistant tuberculosis (MDR/RR-TB) represent an important challenge for global tuberculosis (TB) control. The high rates of MDR/RR-TB observed among re-treatment cases can arise from diverse pathways: de novo amplification during initial treatment, inappropriate treatment of undiagnosed MDR/RR-TB, relapse despite appropriate treatment, or reinfection with MDR/RR-TB. Mathematical modelling allows quantification of the contribution made by these pathways in different settings. This information provides valuable insights for TB policy-makers, allowing better contextualised solutions. However, mathematical modelling outputs need to consider local data and be easily accessible to decision makers in order to improve their usefulness. We present a user-friendly web-based modelling interface, which can be used by people without technical knowledge. Users can input their own parameter values and produce estimates for their specific setting. This innovative tool provides easy access to mathematical modelling outputs that are highly relevant to national TB control programs. In future, the same approach could be applied to a variety of modelling applications, enhancing local decision making.