Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics.

Tuberculosis (TB) killed more people globally than any other single pathogen over the past decade. Where surveillance is weak, estimating TB burden estimates uses modeling. In many African countries, increases in HIV prevalence and antiretroviral therapy have driven dynamic TB epidemics, complicating estimation of burden, trends, and potential intervention impact. We therefore develop a novel age-structured TB transmission model incorporating evolving demographic, HIV and antiretroviral therapy effects, and calibrate to TB prevalence and notification data from 12 African countries. We use Bayesian methods to include uncertainty for all TB model parameters, and estimate age-specific annual risks of TB infection, finding up to 16.0%/year in adults, and the proportion of TB incidence from recent (re)infection, finding a mean across countries of 34%. Rapid reduction of the unacceptably high burden of TB in high HIV prevalence settings will require interventions addressing progression as well as transmission.

Accuracy of computer-aided chest X-ray in community-based tuberculosis screening: Lessons from the 2016 Kenya National Tuberculosis Prevalence Survey.

Community-based screening for tuberculosis (TB) could improve detection but is resource intensive. We set out to evaluate the accuracy of computer-aided TB screening using digital chest X-ray (CXR) to determine if this approach met target product profiles (TPP) for community-based screening. CXR images from participants in the 2016 Kenya National TB Prevalence Survey were evaluated using CAD4TBv6 (Delft Imaging), giving a probabilistic score for pulmonary TB ranging from 0 (low probability) to 99 (high probability). We constructed a Bayesian latent class model to estimate the accuracy of CAD4TBv6 screening compared to bacteriologically-confirmed TB across CAD4TBv6 threshold cut-offs, incorporating data on Clinical Officer CXR interpretation, participant demographics (age, sex, TB symptoms, previous TB history), and sputum results. We compared model-estimated sensitivity and specificity of CAD4TBv6 to optimum and minimum TPPs. Of 63,050 prevalence survey participants, 61,848 (98%) had analysable CXR images, and 8,966 (14.5%) underwent sputum bacteriological testing; 298 had bacteriologically-confirmed pulmonary TB. Median CAD4TBv6 scores for participants with bacteriologically-confirmed TB were significantly higher (72, IQR: 58-82.75) compared to participants with bacteriologically-negative sputum results (49, IQR: 44-57, p<0.0001). CAD4TBv6 met the optimum TPP; with the threshold set to achieve a mean sensitivity of 95% (optimum TPP), specificity was 83.3%, (95% credible interval [CrI]: 83.0%-83.7%, CAD4TBv6 threshold: 55). There was considerable variation in accuracy by participant characteristics, with older individuals and those with previous TB having lowest specificity. CAD4TBv6 met the optimal TPP for TB community screening. To optimise screening accuracy and efficiency of confirmatory sputum testing, we recommend that an adaptive approach to threshold setting is adopted based on participant characteristics.

Durations of asymptomatic, symptomatic, and care-seeking phases of tuberculosis disease with a Bayesian analysis of prevalence survey and notification data.

BACKGROUND: Ratios of bacteriologically positive tuberculosis (TB) prevalence to notification rates are used to characterise typical durations of TB disease. However, this ignores the clinical spectrum of tuberculosis disease and potentially long infectious periods with minimal or no symptoms prior to care-seeking. METHODS: We developed novel statistical models to estimate progression from initial bacteriological positivity including smear conversion, symptom onset and initial care-seeking. Case-detection ratios, TB incidence, durations, and other parameters were estimated by fitting the model to tuberculosis prevalence survey and notification data (one subnational and 11 national datasets) within a Bayesian framework using Markov chain Monte Carlo methods. RESULTS: Analysis across 11 national datasets found asymptomatic tuberculosis durations in the range 4-8 months for African countries; three countries in Asia (Cambodia, Lao PDR, and Philippines) showed longer durations of > 1 year. For the six countries with relevant data, care-seeking typically began half-way between symptom onset and notification. For Kenya and Blantyre, Malawi, individual-level data were available. The sex-specific durations of asymptomatic bacteriologically-positive tuberculosis were 9.0 months (95% credible interval [CrI]: 7.2-11.2) for men and 8.1 months (95% CrI: 6.2-10.3) for women in Kenya, and 4.9 months (95% CrI: 2.6-7.9) for men and 3.5 months (95% CrI: 1.3-6.2) for women in Blantyre. Age-stratified analysis of data for Kenya showed no strong age-dependence in durations. For Blantyre, HIV-stratified analysis estimated an asymptomatic duration of 1.3 months (95% CrI: 0.3-3.0) for HIV-positive people, shorter than the 8.5 months (95% CrI: 5.0-12.7) for HIV-negative people. Additionally, case-detection ratios were higher for people living with HIV than HIV-negative people (93% vs 71%). CONCLUSION: Asymptomatic TB disease typically lasts around 6 months. We found no evidence of age-dependence, but much shorter durations among people living with HIV, and longer durations in some Asian settings. To eradicate TB transmission, greater gains may be achieved by proactively screening people without symptoms through active case finding interventions.

Effects of Coronavirus Disease Pandemic on Tuberculosis Notifications, Malawi.

The coronavirus disease (COVID-19) pandemic might affect tuberculosis (TB) diagnosis and patient care. We analyzed a citywide electronic TB register in Blantyre, Malawi and interviewed TB officers. Malawi did not have an official COVID-19 lockdown but closed schools and borders on March 23, 2020. In an interrupted time series analysis, we noted an immediate 35.9% reduction in TB notifications in April 2020; notifications recovered to near prepandemic numbers by December 2020. However, 333 fewer cumulative TB notifications were received than anticipated. Women and girls were affected more (30.7% fewer cases) than men and boys (20.9% fewer cases). Fear of COVID-19 infection, temporary facility closures, inadequate personal protective equipment, and COVID-19 stigma because of similar symptoms to TB were mentioned as reasons for fewer people being diagnosed with TB. Public health measures could benefit control of both TB and COVID-19, but only if TB diagnostic services remain accessible and are considered safe to attend.

Patient pathways of tuberculosis care-seeking and treatment: an individual-level analysis of National Health Insurance data in Taiwan.

INTRODUCTION: Patients with tuberculosis (TB) often experience difficulties in accessing diagnosis and treatment. Patient pathway analysis identifies mismatches between TB patient care-seeking patterns and service coverage, but to date, studies have only employed cross-sectional aggregate data. METHODS: We developed an algorithmic approach to analyse and interpret patient-level routine data on healthcare use and to construct patients' pathways from initial care-seeking to treatment outcome. We applied this to patients with TB in a simple random sample of one million patients' records in the Taiwan National Health Insurance database. We analysed heterogeneity in pathway patterns, delays, service coverage and patient flows between different health system levels. RESULTS: We constructed 7255 pathways for 6258 patients. Patients most commonly initially sought care at the primary clinic level, where the capacity for diagnosing TB patients was 12%, before eventually initiating treatment at higher levels. Patient pathways are extremely heterogeneous prior to diagnosis, with the 10% most complex pathways accounting for 48% of all clinical encounters, and 55% of those pathways yet to initiate treatment after a year. Extended consideration of alternative diagnoses was more common for patients aged 65 years or older and for patients with chronic lung disease. CONCLUSION: Our study demonstrates that longitudinal analysis of routine individual-level healthcare data can be used to generate a detailed picture of TB care-seeking pathways. This allows an understanding of several temporal aspects of care pathways, including lead times to care and the variability in patient pathways.

Improving the Use of Mortality Data in Public Health: A Comparison of Garbage Code Redistribution Models.

Objectives. To describe and compare 3 garbage code (GC) redistribution models: naïve Bayes classifier (NB), coarsened exact matching (CEM), and multinomial logistic regression (MLR).Methods. We analyzed Taiwan Vital Registration data (2008-2016) using a 2-step approach. First, we used non-GC death records to evaluate 3 different prediction models (NB, CEM, and MLR), incorporating individual-level information on multiple causes of death (MCDs) and demographic characteristics. Second, we applied the best-performing model to GC death records to predict the underlying causes of death. We conducted additional simulation analyses for evaluating the predictive performance of models.Results. When we did not account for MCDs, all 3 models presented high average misclassification rates in GC assignment (NB, 81%; CEM, 86%; MLR, 81%). In the presence of MCD information, NB and MLR exhibited significant improvement in assignment accuracy (19% and 17% misclassification rate, respectively). Furthermore, CEM without a variable selection procedure resulted in a substantially higher misclassification rate (40%).Conclusions. Comparing potential GC redistribution approaches provides guidance for obtaining better estimates of cause-of-death distribution and highlights the significance of MCD information for vital registration system reform.

Forecasting the impact of population ageing on tuberculosis incidence.

BACKGROUND: Tuberculosis (TB) disease reactivates from distant latent infection or recent (re)infection. Progression risks increase with age. Across the World Health Organisation Western Pacific region, many populations are ageing and have the highest per capita TB incidence rates in older age groups. However, methods for analysing age-specific TB incidence and forecasting epidemic trends while accounting for demographic change remain limited. METHODS: We applied the Lee-Carter models, which were originally developed for mortality modelling, to model the temporal trends in age-specific TB incidence data from 2005 to 2018 in Taiwan. Females and males were modelled separately. We combined our demographic forecasts, and age-specific TB incidence forecasts to project TB incidence until 2035. We compared TB incidence projections with demography fixed in 2018 to projections accounting for demographic change. RESULTS: Our models quantified increasing incidence rates with age and declining temporal trends. By 2035, the forecast suggests that the TB incidence rate in Taiwan will decrease by 54% (95% Prediction Interval (PI): 45%-59%) compared to 2015, while most age-specific incidence rates will reduce by more than 60%. In 2035, adults aged 65 and above will make up 78% of incident TB cases. Forecast TB incidence in 2035 accounting for demographic change will be 39% (95% PI: 36%-42%) higher than without population ageing. CONCLUSIONS: Age-specific incidence forecasts coupled with demographic forecasts can inform the impact of population ageing on TB epidemics. The TB control programme in Taiwan should develop plans specific to older age groups and their care needs.

Adult mortality of diseases and injuries attributable to selected metabolic, lifestyle, environmental, and infectious risk factors in Taiwan: a comparative risk assessment.

BACKGROUND: To facilitate priority-setting in health policymaking, we compiled the best available information to estimate the adult mortality (>30 years) burden attributable to 13 metabolic, lifestyle, infectious, and environmental risk factors in Taiwan. METHODS: We obtained data on risk factor exposure from nationally representative health surveys, cause-specific mortality from the National Death Registry, and relative risks from epidemiological studies and meta-analyses. We applied the comparative risk assessment framework to estimate mortality burden attributable to individual risk factors or risk factor clusters. RESULTS: In 2009, high blood glucose accounted for 14,900 deaths (95% UI: 11,850-17,960), or 10.4% of all deaths in that year. It was followed by tobacco smoking (13,340 deaths, 95% UI: 10,330-16,450), high blood pressure (11,190 deaths, 95% UI: 8,190-14,190), ambient particulate matter pollution (8,600 deaths, 95% UI: 7,370-9,840), and dietary risks (high sodium intake and low intake of fruits and vegetables, 7,890 deaths, 95% UI: 5,970-9,810). Overweight-obesity and physical inactivity accounted for 7,620 deaths (95% UI: 6,040-9,190), and 7,400 deaths (95% UI: 6,670-8,130), respectively. The cardiometabolic risk factors of high blood pressure, high blood glucose, high cholesterol, and overweight-obesity jointly accounted for 12,120 deaths (95% UI: 11,220-13,020) from cardiovascular diseases. For domestic risk factors, infections from hepatitis B virus (HBV) and hepatitis C virus (HCV) were responsible for 6,300 deaths (95% UI: 5,610-6,980) and 3,170 deaths (95% UI: 1,860-4,490), respectively, and betel nut use was associated with 1,780 deaths from oral, laryngeal, and esophageal cancer (95% UI: 1,190-2,360). The leading risk factors for years of life lost were similar, but the impact of tobacco smoking and alcohol use became larger because the attributable deaths from these risk factors occurred among young adults aged less than 60 years. CONCLUSIONS: High blood glucose, tobacco smoking, and high blood pressure are the major risk factors for deaths from diseases and injuries among Taiwanese adults. A large number of years of life would be gained if the 13 modifiable risk factors could be removed or reduced to the optimal level.

Effect of diabetes on tuberculosis control in 13 countries with high tuberculosis: a modelling study.

BACKGROUND: Diabetes increases the risk of tuberculosis incidence and the risk of adverse treatment outcomes in patients with tuberculosis. Because prevalence of diabetes is increasing in low-income and middle-income countries where the burden of tuberculosis is high, prevention of diabetes carries the potential to improve tuberculosis control worldwide. METHODS: We used dynamic tuberculosis transmission models to analyse the potential effect of diabetes on tuberculosis epidemiology in 13 countries with high tuberculosis burden. We used data for previous diabetes prevalence in each country and constructed scenarios to represent the potential ranges of future diabetes prevalence. The country-specific model was calibrated to the estimated trend of tuberculosis incidence. We estimated the tuberculosis burden that can be reduced by alternative scenarios of diabetes prevention. FINDINGS: If the prevalence of diabetes continues to rise as it has been in the past decade in the 13 countries (base case scenario), by 2035, the cumulative reduction in tuberculosis incidence would be 8·8% (95% credible interval [CrI] 4·0-15·8) and mortality would be 34·0% (30·3-39·6). Lowering the prevalence of diabetes by an absolute level of 6·6-13·8% could accelerate the decline of tuberculosis incidence by an absolute level of 11·5-25·2% and tuberculosis mortality by 8·7-19·4%. Compared with the base case scenario, stopping the rise of diabetes would avoid 6·0 million (95% CrI 5·1-6·9) incident cases and 1·1 million (1·0-1·3) tuberculosis deaths in 13 countries during 20 years. If interventions reduce diabetes incidence by 35% by 2025, 7·8 million (6·7-9·0) tuberculosis cases and 1·5 million (1·3-1·7) tuberculosis deaths could be averted by 2035. INTERPRETATION: The diabetes epidemic could substantially affect tuberculosis epidemiology in high burden countries. The communicable disease and non-communicable disease sectors need to move beyond conventional boundaries and link with each other to form a joint response to diabetes and tuberculosis. FUNDING: Taiwan National Science Council.

Assessment of the patient, health system, and population effects of Xpert MTB/RIF and alternative diagnostics for tuberculosis in Tanzania: an integrated modelling approach.

BACKGROUND: Several promising new diagnostic methods and algorithms for tuberculosis have been endorsed by WHO. National tuberculosis programmes now face the decision on which methods to implement and where to place them in the diagnostic algorithm. METHODS: We used an integrated model to assess the effects of different algorithms of Xpert MTB/RIF and light-emitting diode (LED) fluorescence microscopy in Tanzania. To understand the effects of new diagnostics from the patient, health system, and population perspective, the model incorporated and linked a detailed operational component and a transmission component. The model was designed to represent the operational and epidemiological context of Tanzania and was used to compare the effects and cost-effectiveness of different diagnostic options. FINDINGS: Among the diagnostic options considered, we identified three strategies as cost effective in Tanzania. Full scale-up of Xpert would have the greatest population-level effect with the highest incremental cost: 346 000 disability-adjusted life-years (DALYs) averted with an additional cost of US$36·9 million over 10 years. The incremental cost-effectiveness ratio (ICER) of Xpert scale-up ($169 per DALY averted, 95% credible interval [CrI] 104-265) is below the willingness-to-pay threshold ($599) for Tanzania. Same-day LED fluorescence microscopy is the next most effective strategy with an ICER of $45 (95% CrI 25-74), followed by LED fluorescence microscopy with an ICER of $29 (6-59). Compared with same-day LED fluorescence microscopy and Xpert full rollout, targeted use of Xpert in presumptive tuberculosis cases with HIV infection, either as an initial diagnostic test or as a follow-on test to microscopy, would produce DALY gains at a higher incremental cost and therefore is dominated in the context of Tanzania. INTERPRETATION: For Tanzania, this integrated modelling approach predicts that full rollout of Xpert is a cost-effective option for tuberculosis diagnosis and has the potential to substantially reduce the national tuberculosis burden. It also estimates the substantial level of funding that will need to be mobilised to translate this into clinical practice. This approach could be adapted and replicated in other developing countries to inform rational health policy formulation.