Data for action: collection and use of local data to end tuberculosis

Effectiveness of Using AI-Driven Hotspot Mapping for Active Case Finding of Tuberculosis in Southwestern Nigeria

Background: Nigeria is among the top five countries that have the highest gap between people reported as diagnosed and estimated to have developed tuberculosis (TB). To bridge this gap, there is a need for innovative approaches to identify geographical areas at high risk of TB transmission and targeted active case finding (ACF) interventions. Leveraging community-level data together with granular sociodemographic contextual information can unmask local hotspots that could be otherwise missed. This work evaluated whether this approach helps to reach communities with higher numbers of undiagnosed TB. Methodology: A retrospective analysis of the data generated from an ACF intervention program in four southwestern states in Nigeria was conducted. Wards (the smallest administrative level in Nigeria) were further subdivided into smaller population clusters. ACF sites and their respective TB screening outputs were mapped to these population clusters. This data were then combined with open-source high-resolution contextual data to train a Bayesian inference model. The model predicted TB positivity rates on the community level (population cluster level), and these were visualised on a customised geoportal for use by the local teams to identify communities at high risk of TB transmission and plan ACF interventions. The TB positivity yield (proportion) observed at model-predicted hotspots was compared with the yield obtained at other sites identified based on aggregated notification data. Results: The yield in population clusters that were predicted to have high TB positivity rates by the model was at least 1.75 times higher (p-value < 0.001) than the yield in other locations in all four states. Conclusions: The community-level Bayesian predictive model has the potential to guide ACF implementers to high-TB-positivity areas for finding undiagnosed TB in the communities, thus improving the efficiency of interventions.

Spatial Analysis of Drug-Susceptible and Multidrug-Resistant Cases of Tuberculosis, Ho Chi Minh City, Vietnam, 2020-2023

We characterized the spatial distribution of drug-susceptible (DS) and multidrug-resistant (MDR) tuberculosis (TB) cases in Ho Chi Minh City, Vietnam, a major metropolis in southeastern Asia, and explored demographic and socioeconomic factors associated with local TB burden. Hot spots of DS and MDR TB incidence were observed in the central parts of Ho Chi Minh City, and substantial heterogeneity was observed across wards. Positive spatial autocorrelation was observed for both DS TB and MDR TB. Ward-level TB incidence was associated with HIV prevalence and the male proportion of the population. No ward-level demographic and socioeconomic indicators were associated with MDR TB case count relative to total TB case count. Our findings might inform spatially targeted TB control strategies and provide insights for generating hypotheses about the nature of the relationship between DS and MDR TB in Ho Chi Minh City and the wider southeastern region of Asia.

Estimating the prevalence of poor-quality anti-TB medicines: a neglected risk for global TB control and resistance

OBJECTIVES

Tuberculosis (TB) remains a major global public health problem, especially with the recent emergence of multidrug-resistant TB and extensively drug-resistant TB. There has been little consideration of the extent of substandard and falsified (SF) TB medicines as drivers of resistance. We assessed the evidence on the prevalence of SF anti-TB medicines and discussed their public health impact.

MATERIALS/METHODS

We searched Web of Science, Medline, Pubmed, Google Scholar, WHO, US Pharmacopeia and Medicines Regulatory Agencies websites for publications on anti-TB medicines quality up to 31 October 2021. Publications reporting on the prevalence of SF anti-TB drugs were evaluated for quantitative analysis.

RESULTS

Of the 530 screened publications, 162 (30.6%) were relevant to anti-TB medicines quality; of those, 65 (40.1%) described one or more TB quality surveys in a specific location or region with enough information to yield an estimate of the local prevalence of poor-quality TB medicines. 7682 samples were collected in 22 countries and of those, 1170 (15.2%) failed at least one quality test. 14.1% (879/6255) of samples failed in quality surveys, 12.5% (136/1086) in bioequivalence studies and 36.9% (87/236) in accelerated biostability studies. The most frequently assessed were rifampicin monotherapy (45 studies, 19.5%) and isoniazid monotherapy (33, 14.3%), rifampicin-isoniazid-pyrazinamide-ethambutol fixed dose combinations (28, 12.1%) and rifampicin-isoniazid (20, 8.6%). The median (IQR) number of samples collected per study was 12 (1-478).

CONCLUSIONS

SF, especially substandard, anti-TB medicines are present worldwide. However, TB medicine quality data are few and are therefore not generalisable that 15.2% of global anti-TB medicine supply is SF. The evidence available suggests that the surveillance of the quality of TB medicines needs to be an integral part of treatment programmes. More research is needed on the development and evaluation of rapid, affordable and accurate portable devices to empower pharmacy inspectors to screen for anti-TB medicines.

Development and expert validation of a ‘Data-to-Action Continuum’ to measure and advance the data-use capabilities of national tuberculosis programs

Background

The Data-to-Action Continuum (D2AC) Toolkit is intended to advance the data use capabilities associated with people, processes, technology, and institutions of national tuberculosis programs (NTPs). It empowers NTPs and stakeholders to measure current capabilities, identify areas amenable to interventions to build future capacities, and helps align the TB information system to better achieve the NTP’s goals. This paper describes the development process of the D2AC Toolkit, whose aim is to enable NTPs and stakeholders—especially the policymakers, program managers, and laboratory and facility managers—to precisely gauge the barriers limiting the use of data for action and devise appropriate interventions to address them.

Methods

Building on a scientific and grey literature foundation, the D2AC Toolkit was collaboratively developed by a core group of the TB data, Impact Assessment and Communications Hub (TB DIAH) project. The Toolkit was validated by a group of international and country-level experts following an iterative and user-centered process employing mixed methods.

Results

The expert-validated D2AC Toolkit measures appropriate capabilities required to transform data to action in the context of an NTP at the national, regional, district, and facility levels across five domains and 17 subdomains using a five-point Likert scale: nascent, defined, established, institutionalized, and optimized.

Conclusions

The continuum describes the status of various domains and corresponding subdomains and enables the identification of future goals for each subdomain. The future capabilities are meant to guide the development of an improvement path toward the desired level of advancement and monitor progress toward the desired goals. By integrating an iterative and user-centered process and using mixed methods, the D2AC Toolkit enables policymakers, program managers, and service providers to gauge current capabilities, identify future priorities, and develop an implementation plan to improve the organizational ability to transform data to action for achieving tuberculosis program goals.

Assessing the quality of tuberculosis care using routine surveillance data: a process evaluation employing the Zero TB Indicator Framework in Mongolia

OBJECTIVES

To evaluate the feasibility of the Zero TB Indicator Framework as a tool for assessing the quality of tuberculosis (TB) case-finding, treatment and prevention services in Mongolia.

SETTING

Primary health centres, TB dispensaries, and surrounding communities in four districts of Mongolia.

DESIGN

Three retrospective cross-sectional cohort studies, and two longitudinal studies each individually nested in one of the cohort studies.

PARTICIPANTS

15 947 community members from high TB-risk populations; 8518 patients screened for TB in primary health centres and referred to dispensaries; 857 patients with index TB and 2352 household contacts.

PRIMARY AND SECONDARY OUTCOME MEASURES

14 indicators of the quality of TB care defined by the Zero TB Indicator Framework and organised into three care cascades, evaluating community-based active case-finding, passive case-finding in health facilities and TB screening and prevention among close contacts; individual and health-system predictors of these indicators.

RESULTS

The cumulative proportions of participants receiving guideline-adherent care varied widely, from 96% for community-based active case-finding, to 79% for TB preventive therapy among household contacts, to only 67% for passive case-finding in primary health centres and TB dispensaries (range: 29%-80% across districts). The odds of patients completing active TB treatment decreased substantially with increasing age (aOR: 0.76 per decade, 95% CI: 0.71 to 0.83, p<0.001) and among men (aOR: 0.56, 95% CI: 0.36 to 0.88, p=0.013). Contacts of older index patients also had lower odds of initiating and completing of TB preventive therapy (aOR: 0.60 per decade, 95% CI: 0.38 to 0.93, p=0.022).

CONCLUSIONS

The Zero TB Framework provided a feasible and adaptable approach for using routine surveillance data to evaluate the quality of TB care and identify associated individual and health system factors. Future research should evaluate strategies for collecting process indicators more efficiently; gather qualitative data on explanations for low-quality care; and deploy quality improvement interventions.

Distribution of bacteriologically positive and bacteriologically negative pulmonary tuberculosis in Northwest China: spatiotemporal analysis

Pulmonary tuberculosis (PTB) is a major health issue in Northwest China. Most previous studies on the spatiotemporal patterns of PTB considered all PTB cases as a whole; they did not distinguish notified bacteriologically positive PTB (BP-PTB) and notified bacteriologically negative PTB (BN-PTB). Thus, the spatiotemporal characteristics of notified BP-PTB and BN-PTB are still unclear. A retrospective county-level spatial epidemiological study (2011-2018) was conducted in Shaanxi, Northwest China. In total, 44,894 BP-PTB cases were notified, with an average annual incidence rate of 14.80 per 100,000 persons between 2011 and 2018. Global Moran's I values for notified BP-PTB ranged from 0.19 to 0.49 (P < 0.001). Anselin's local Moran's I analysis showed that the high-high (HH) cluster for notified BP-PTB incidence was mainly located in the southernmost region. The primary spatiotemporal cluster for notified BP-PTB (LLR = 612.52, RR = 1.77, P < 0.001) occurred in the central region of the Guanzhong Plain in 2011. In total, 116,447 BN-PTB cases were notified, with an average annual incidence rate of 38.38 per 100,000 persons between 2011 and 2018. Global Moran's I values for notified BN-PTB ranged from 0.39 to 0.69 (P < 0.001). The HH clusters of notified BN-PTB were mainly located in the north between 2011 and 2014 and in the south after 2015. The primary spatiotemporal cluster for notified BN-PTB (LLR = 1084.59, RR = 1.85, P < 0.001) occurred in the mountainous areas of the southernmost region from 2014 to 2017. Spatiotemporal clustering of BP-PTB and BN-PTB was detected in the poverty-stricken mountainous areas of Shaanxi, Northwest China. Our study provides evidence for intensifying PTB control activities in these geographical clusters.

Evaluation of the collaborative integrated surveillance system (ViCo) in Guatemala: a qualitative study on lessons learned and future perspectives

BACKGROUND

The collaborative integrated surveillance system known as Vigilancia Integrada Comunitaria (ViCo) was implemented in 2007 to better understand and characterize the burden of diarrheal, respiratory and febrile illnesses in Guatemala.

METHODS

To evaluate the usefulness of ViCo and inform a redesign of the system and new surveillance activities in the Central American region, personnel from the United States Centers for Disease Control and Prevention (CDC) conducted thirty-nine in-depth interviews from June-December 2018 with key stakeholders responsible for the design and implementation of ViCo in Guatemala. A semi-structured questionnaire adapted from the Updated CDC Guidelines for Evaluating Public Health Surveillance Systems was used for data collection. We used a grounded theory approach to explore stakeholder perceptions of ViCo and generate recommendations for improvement. Primary qualitative findings were organized based on thematic areas using ATLAS.ti version 8 software.

RESULTS

Emergent themes relevant to the usefulness of ViCo were organized across strengths, weaknesses, and recommendations pertaining to the: (1) Size and Complexity of ViCo, (2) Stakeholder Expectations About the Objectives of ViCo, (3) Data Management and Structure of the Information System, (4) Local Control of Data, (5) Integration of ViCo within the Ministry of Health, and, (6) Improvement of the Operational and Design Aspects of ViCo across System, Process, and Output levels.

CONCLUSIONS

Stakeholders perceived ViCo to be useful. They recommended measures to improve system performance and quality, including simplifying the surveillance system, routine data analysis and feedback, and channeling efforts towards integrating surveillance data into the national health information system. To create a well-performing surveillance system and achieve the intended objective of surveillance for public health action, ongoing evaluation and assessment of surveillance activities are necessary.

A role for community-level socioeconomic indicators in targeting tuberculosis screening interventions

Tuberculosis screening programs commonly target areas with high case notification rates. However, this may exacerbate disparities by excluding areas that already face barriers to accessing diagnostic services. We compared historic case notification rates, demographic, and socioeconomic indicators as predictors of neighborhood-level tuberculosis screening yield during a mobile screening program in 74 neighborhoods in Lima, Peru. We used logistic regression and Classification and Regression Tree (CART) analysis to identify predictors of screening yield. During February 7, 2019-February 6, 2020, the program screened 29,619 people and diagnosed 147 tuberculosis cases. Historic case notification rate was not associated with screening yield in any analysis. In regression analysis, screening yield decreased as the percent of vehicle ownership increased (odds ratio [OR]: 0.76 per 10% increase in vehicle ownership; 95% confidence interval [CI]: 0.58-0.99). CART analysis identified the percent of blender ownership (≤ 83.1% vs > 83.1%; OR: 1.7; 95% CI: 1.2-2.6) and the percent of TB patients with a prior tuberculosis episode (> 10.6% vs ≤ 10.6%; OR: 3.6; 95% CI: 1.0-12.7) as optimal predictors of screening yield. Overall, socioeconomic indicators were better predictors of tuberculosis screening yield than historic case notification rates. Considering community-level socioeconomic characteristics could help identify high-yield locations for screening interventions.

COVID-19 BR: A web portal for COVID-19 information in Brazil

Brazil is a large developing country that requires attention to regionalized behaviors regarding the dissemination of COVID-19. To deal with this complexity, the COVID-19 Brazil observatory was developed. The Portal aims to monitor and analyze data from different sources. Therefore, with a detailed audit, we centralized this information on the evolution of the disease, allowing for territorial and temporal monitoring. The daily publication of numbers about COVID-19 allowed anyone to follow the current scenario in several Brazilian cities. With about 1,7 million accesses, the Portal offers clarity and an easy understanding of the pandemic data in the country.

Evaluation of effectiveness of pathology reports in active surveillance of tuberculosis

OBJECTIVE

Despite advancing technology, national TB surveillance systems are still inadequate in terms of patient detection around the world. It was aimed to investigate suspicious cases detected by active surveillance method in pathology laboratories and to evaluate the effectiveness of this method in terms of finding new TB cases.

METHODS

This is a descriptive cross-sectional study. It was administrated in Samsun, Turkey, between January 2012-December 2017. Within the scope of active surveillance, pathology laboratories were regularly visited and reported cases with granulomatous inflammation were assessed. The obtained patient list was compared with the records of the Electronic Tuberculosis Management System (ETMS). Patients who were not included in these records were invited to the dispensary and evaluated for TB. They were also referred to the relevant hospitals for diagnosis if necessary. Frequency values and descriptive statistics were calculated using SPSS method.

RESULTS

It was found that 35.6% of 703 patients with the diagnosis of granulomatous inflammation were previously diagnosed, treated or currently undergoing treatment in the ETMS registry. As a result of the assessment of remaining 453 cases, 46 patients (10.1%) were newly diagnosed with TB. Newly diagnosed TB patients were reported, and their treatment started.

CONCLUSION

As a result, active surveillance method conducted in pathology laboratories are used to detect unknown or late reported TB cases and allows to start treatment without further delay.

Geospatial clustering and modelling provide policy guidance to distribute funding for active TB case finding in Ethiopia

Tuberculosis (TB) exhibits considerable spatial heterogeneity, occurring in clusters that may act as hubs of community transmission. We evaluated the impact of an intervention targeting spatial TB hotspots in a rural region of Ethiopia. To evaluate the impact of targeted active case finding (ACF), we used a spatially structured mathematical model that has previously been described. From model equilibrium, we simulated the impact of a hotspot-targeted strategy (HTS) on TB incidence ten years from intervention commencement and the associated cost-effectiveness. HTS was also compared with an untargeted strategy (UTS). We used logistic cost-coverage analysis to estimate cost-effectiveness of interventions. At a community screening coverage level of 95 % in a hotspot region, which corresponds to screening 20 % of the total population, HTS would reduce overall TB incidence by 52 % compared with baseline. For UTS to achieve an equivalent effect, it would be necessary to screen more than 80 % of the total population. Compared to the existing passive case detection strategy, the HTS at a CDR of 75 percent in hotspot regions is expected to avert 1,023 new TB cases over ten years saving USD 170 per averted case. Similarly, at the same CDR, the UTS will detect 1316 cases over the same period saving USD 3 per averted TB case. The incremental-cost effectiveness-ratio (ICER) of UTS compared with HTS is USD 582 per averted case corresponding to 293 more TB cases averted at an additional cost of USD 170,700. Where regional TB program spending was capped at current levels, maximum gains in incidence reduction were seen when the regional budget was shared between hotspots and non-hotspot regions in the ratio of 40% : 60%. Our analysis suggests that a spatially targeted strategy is efficient and cost-saving, with the potential for significant reduction in overall TB burden.

Longitudinal-Survival Models for Case-Based Tuberculosis Progression

Introduction: Tuberculosis (TB) disease continues to be responsible for a high global burden with an estimated 10 million people falling ill each year and an estimated 1.45 million deaths. Widely carried out analyses to utilize routine data coming from this disease, and well-established in literature, have paid attention to time-to-event with sputum smear results being considered only at baseline or even ignored. Also, logistic regression models have been used to demonstrate importance of sputum smear results in patient outcomes. A feature presented by this disease, however, is that each individual patient is usually followed over a period of time with sputum smear results being documented at different points of the treatment curve. This provides both repeated measures and survival times, which may require a joint modeling approach. This study aimed to investigate the association between sputum smear results and the risk of experiencing unfavorable outcome among TB patients and dynamically predict survival probabilities.

Method: A joint model for longitudinal and time-to-event data was used to analyze longitudinally measured smear test results with time to experiencing unfavorable outcome for TB patients. A generalized linear mixed-effects model was specified for the longitudinal submodel and cox proportional hazards model for the time-to-event submodel with baseline hazard approximated using penalized B-splines. The two submodels were then assumed to be related via the current value association structure. Bayesian approach was used to approximate parameter estimates using Markov Chain Monte Carlo (MCMC) algorithm. The obtained joint model was used to predict the subject's future risk of survival based on sputum smear results trajectories. Data were sourced from routinely collected TB data stored at National TB Program database.

Results: The average baseline age was 35 (SD: 15). Female TB patients constituted 36.42%. Patients with previous history of TB treatment constituted 6.38% (event: 15.25%; no event: 5.29%). TB/HIV co-infection was at 31.23% (event: 47.87%; no event: 29.20%). The association parameter 1.03 (CI[1.03,1.04]) was found to be positive and significantly different from zero, interpreted as follows: The estimate of the association parameter α = 1.033 denoted the log hazard ratio for a unit increase in the log odds of having smear positive results. HIV status (negative) 0.47 (CI [0.46,49]) and history of TB treatment (previously treated) (2.52 CI [2.41,2.63]), sex (female) (0.82 CI [0.78,0.84]), and body mass index (BMI) categories (severe malnutrition being reference) were shown to be statistically significant.

Conclusion: Sputum smear result is important in estimating the risk to unfavorable outcome among TB patients. Men, previously treated, TB/HIV co-infected and severely malnourished TB patients are at higher risk of unfavorable outcomes.

Predictors of unsuccessful tuberculosis treatment outcomes in children from a prospective cohort study in Pakistan

Background

Every year, about 239 000 children die from tuberculosis (TB), despite availability of highly effective regimens. Few studies have evaluated predictors for poor treatment outcomes in children treated for TB.

Methods

We assessed predictors of unsuccessful TB treatment outcomes in a prospective cohort of children diagnosed by an intensified TB patient-finding intervention at four facilities in Pakistan between 2014 and 2016. A case of TB disease was determined through either bacteriologic confirmation of disease or a clinical diagnosis. To estimate characteristics predictive of experiencing an unsuccessful treatment outcome, we used a multi-level model with a modified Poisson approach, accounting for clustering at the facility level. We report estimated relative risks (RR) and 95% confidence intervals (CI).

Results

During the study period, 1404 children less than 15 years old were initiated on treatment for drug-susceptible TB. In total, 709 (50.5%) were 0-4, 406 (28.9%) were 5-9 years, and 289 (20.6%) were 10-14 years old; 614 (43.7%) were female; and of the 1377 children assessed for malnourishment, 1161 (84.3%) were malnourished. A total of 1322 (94.2%) children experienced a successful treatment outcome, 14 (1.0%) children transferred out to a different facility, and 68 (4.8%) children experienced an unsuccessful treatment outcome: 14 (1.0%) died, 20 (1.4%) failed treatment, and 34 (2.4%) were lost to follow-up. After adjustment for age group, sex, and malnutrition status, we identified increased risk of unsuccessful treatment outcome in children presenting with fever (RR = 2.56, 95% CI = 1.02-6.44; P = 0.05) or an abdominal examination suggestive of TB disease (RR = 2.34, 95% CI = 1.20-4.58; P = 0.01), and a decreased risk in children who initiated treatment at a rural facility (RR = 0.05, 95% CI = 0.00-0.74; P = 0.03).

Conclusions

More than 94% of children experienced successful treatment outcomes. We identified individual-, facility-, and clinical-factors predictive of experiencing unsuccessful treatment outcomes. Children with fevers and abdominal findings suggestive of TB disease should be tested for TB and followed closely throughout treatment to ensure necessary support for successful completion of treatment.

Using a low-cost, real-time electronic immunization registry in Pakistan to demonstrate utility of data for immunization programs and evidence-based decision making to achieve SDG-3: Insights from analysis of Big Data on vaccines

BACKGROUND

Despite the proliferation of digital interventions such as Electronic Immunization Registries (EIR), currently, there is little evidence regarding the use of EIR data to improve immunization outcomes in resource-constrained settings. To achieve the Sustainable Development Goal (SDG) of ensuring healthy lives and well-being for all ages, particularly for newborns and children under the age of 5 (goal 3b), it is essential to generate and use quality data for evidence-based decision making to overcome barriers inherent in immunization systems. In Pakistan, only 66 % of children receive all basic vaccinations, and in Sindh province, the number is even lower at 49 %. In 2012, IRD developed and piloted Zindagi Mehfooz (Safe Life; ZM) ElR, an Android-based platform that records and analyses individual-level child data in real-time. In 2017 in collaboration with Expanded Programme for Immunization (EPI) Sindh, ZM was scaled-up across the entire Sindh province and is currently being used by 2521 government vaccinators in 1539 basic health facilities, serving >48 million population.

OBJECTIVE

The study aims to demonstrate how big immunization data from the ZM-EIR is being leveraged in Sindh, Pakistan for actionable decision making via three use cases (a) improving performance management of vaccinators to increase geographical coverage, (b) quantifying the impact of provincial accelerated outreach activities, and (c) examining the impact of the COVID-19 pandemic on routine immunization coverage to help devise a tailored approach for future efforts.

METHODS

From October 2017 to April 2020, more than 2.9 million children and 0.9 million women have been enrolled, and more than 22 million immunization events have been recorded in the ZM-EIR. We extracted de-identified data from ZM-EIR for January 1, 2019 - April 20, 2020, period. Given the needs of each use case, monthly and daily indicators on vaccinator performance (attendance and compliance), daily immunization visits, and the number of antigens administered were calculated. Geo-coordinate data of antigen administration was extracted and displayed on geographic maps using QGIS. All generated reports were shared at fixed frequency with various stakeholders, such as partners at EPI-Sindh, for utilization in decision making and informing policy.

RESULT

Our use-cases demonstrate the use of EIR data for data-driven decision making. From January - December 2019, the monthly monitoring of program indicators helped increase the vaccinator attendance from 44% to 88%, while an 85 % increase in geographical coverage was observed in a polio-endemic super high-risk union council (SHRUC) in Karachi. The analysis of daily average antigens administered during accelerated outreach efforts (AOE) as compared to routine activities showed an increase in average daily Pentavalent-3, Measles-1, and Measles-2 vaccines administered by 103%, 154%, and 180% respectively. These findings helped decide to continue the accelerated effort in high-risk areas (compared to the entire province) rather than discontinuing the activity due to high costs. During COVID-19 lockdown, the daily average number of child immunizations reduced from 16,649 to 4335 per day, a decline of 74% compared to 6 months preceding COVID-19 lockdown. ZM-EIR data is currently helping to shape the planning and implementation of critical strategies to mitigate the impact of the COVID-19 pandemic.

CONCLUSION

The big data for vaccines generated through EIRs is a powerful tool to monitor immunization work-force and ensure chronically missed communities are identified and covered through targeted strategies. Geospatial data availability and analysis is changing the way EPI review meetings occur with stakeholders, taking data-driven decisions for better planning and resource allocation. In the fight against COVID-19 pandemic, as governments gradually begin to shift from containing the outbreak to strategizing a plan for sustaining the essential health services, the countries that will emerge most successful are likely the ones who can best use technology and real-time data for targeted efforts.

Using data to improve outcomes of supplemental immunisation activities: 2017/2018 Nigeria measles vaccination campaign

BACKGROUND

Despite the enormous resources committed to the implementation of supplemental immunisation activities in Nigeria, achieving the required coverage (post-campaign survey) to halt the transmission of vaccine-preventable diseases has continued to seem like an impossibility. A vast volume of data is generated and transmitted during mass vaccination campaigns, but this administrative data does not always culminate into improved coverage. The absence of data-informed guidance from stakeholders with long years of experience in planning and implementing mass vaccination campaigns has impeded achieving 95% coverage in measles campaigns in Nigeria. This study reviews the use of data to guide the implementation of the 2017/2018 measles vaccination campaign in Nigeria.

METHODS

A central coordinating body was formed at the national level with the same replicated in every state. Tools were developed to measure the performance of the different phases and activities required for the implementation of a mass vaccination campaign as recommended in the international guidelines. Stakeholders were engaged to help ensure that feedback provided by the national measles technical coordinating committee was implemented at the lower level.

RESULTS

Monitoring and analysis of daily data submission caused a proper spread of senior supervisors, vaccination posts location during the campaign and helped identify areas targeted for mop-up. Although the verification of states' microplan increased the operational target population by 11.2%, the process aided the distribution of resources as appropriate. Maps showing the likely areas that needed additional effort to achieve required coverage with recommendation on the necessary approach to be deployed were transmitted to the states implementing the campaign.

CONCLUSION

The improvement in the use of data to guide implementation of the Nigeria 2017/2018 measles vaccination campaign caused an increase in the number of states that achieved higher coverage in the post-campaign coverage survey.

The relationship between social risk factors and latent tuberculosis infection among individuals residing in England: a cross-sectional study

OBJECTIVE

To investigate the relationship between social risk factors and latent tuberculosis infection (LTBI) among individuals who are eligible for LTBI screening in the United Kingdom (UK).

METHODS

This cross-sectional study used data collected in the UK Prognostic Evaluation of Diagnostic Interferon-Gamma Release Assays (IGRAs) Consortium Study which enrolled 9176 recent tuberculosis (TB) contacts and migrants at National Health Service (NHS) facilities and community settings in the UK. The study outcome was LTBI (positive IGRA test (QuantiFERON-TB Gold In-Tube or T-SPOT.TB)). The main exposures were history of smoking, history of substance misuse, homelessness, prison stay and socioeconomic deprivation.

RESULTS

4914 (56.2%) individuals resided in the most deprived areas and 2536 (27.6%) had LTBI. In the multivariable analysis (adjusting for age, gender, place of birth, ethnicity, HIV status, BCG vaccination and recent TB contact) living in the least deprived areas compared with living in the most deprived areas was associated with reduced odds of LTBI (odds ratio (OR)=0.68, 95% CI: 0.51 to 0.90) while ever been homeless (OR=1.50, 95% CI: 1.02 to 2.21) was associated with increased odds of LTBI. Smoking, homelessness and substance misuse were not associated with LTBI.

CONCLUSION

Social deprivation could be an important risk factor for LTBI, highlighting the social inequality in the burden of TB infection in the UK. Migrants and TB contacts who were socially deprived or homeless were at a significantly higher risk for LTBI, thus tailored intense public health interventions to these groups may help to reduce the risk of future TB disease.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Registry (NCT01162265).

Improving case detection of tuberculosis in hospitalised Kenyan children-employing the behaviour change wheel to aid intervention design and implementation

BACKGROUND

The true burden of tuberculosis in children remains unknown, but approximately 65% go undetected each year. Guidelines for tuberculosis clinical decision-making are in place in Kenya, and the National Tuberculosis programme conducts several trainings on them yearly. By 2018, there were 183 GeneXpert® machines in Kenyan public hospitals. Despite these efforts, diagnostic tests are underused and there is observed under detection of tuberculosis in children. We describe the process of designing a contextually appropriate, theory-informed intervention to improve case detection of TB in children and implementation guided by the Behaviour Change Wheel.

METHODS

We used an iterative process, going back and forth from quantitative and qualitative empiric data to reviewing literature, and applying the Behaviour Change Wheel guide. The key questions reflected on included (i) what is the problem we are trying to solve; (ii) what behaviours are we trying to change and in what way; (iii) what will it take to bring about desired change; (iv) what types of interventions are likely to bring about desired change; (v) what should be the specific intervention content and how should this be implemented?

RESULTS

The following behaviour change intervention functions were identified as follows: (i) training: imparting practical skills; (ii) modelling: providing an example for people to aspire/imitate; (iii) persuasion: using communication to induce positive or negative feelings or stimulate action; (iv) environmental restructuring: changing the physical or social context; and (v) education: increasing knowledge or understanding. The process resulted in a multi-faceted intervention package composed of redesigning of child tuberculosis training; careful selection of champions; use of audit and feedback linked to group problem solving; and workflow restructuring with role specification.

CONCLUSION

The intervention components were selected for their effectiveness (from literature), affordability, acceptability, and practicability and designed so that TB programme officers and hospital managers can be supported to implement them with relative ease, alongside their daily duties. This work contributes to the field of implementation science by utilising clear definitions and descriptions of underlying mechanisms of interventions that will guide others to do likewise in their settings for similar problems.

What is operational research and how can national tuberculosis programmes in low- and middle-income countries use it to end TB?

Despite considerable progress over the years, tuberculosis (TB) still remains the top cause of death among the infectious diseases and has devastating socio-economic consequences for people in low- and middle-income countries. To add to this, the emergence of the COVID-19 pandemic has worsened delivery of TB care across the globe. As a global community, we have committed to end the TB epidemic by 2030. The World Health Organization has framed a strategy to achieve this goal which consists of three pillars namely i) integrated patient-centred care and prevention, ii) bold policies and systems and iii) intensified research and innovation. An analysis of the performance of national tuberculosis programmes (NTPs) across the globe against the ten priority indicators recommended for monitoring the end TB strategy show that there are huge gaps at every step in the cascade of care of TB patients. In our view, these gaps reflect suboptimal implementation of existing strategies known to be efficacious and operational research (OR) is one of the best available tools to plug the gaps. In this paper, we define what operational research is and how it differs from other kinds of research. We also share our views and experiences about how operational research can be used by NTPs to identify implementation gaps and their reasons, and develop and test possible solutions - which are then integrated to make changes to policy and practice and eventually improve programme outcomes. OR can be defined as research into interventions, strategies and tools which produces practical useable knowledge that can be used to enhance the quality, coverage, effectiveness and efficiency of disease control programmes, health services or health systems in which the research is conducted. The key steps in integrating operational research in the NTPs include: i) securing political commitment reflected by inclusion of OR in the national strategic plans of NTPs and earmarked funding, ii) having a critical mass of dedicated and trained human resources in OR within the NTP, iii) setting research priorities and steering the direction of research in the country, iv) using output-oriented models of capacity building such as the Structured Operational Research Training Initiative (SORT IT) model and building communities of practice, v) harnessing existing capacity in the country by forging partnerships with academia, vi) NTP-led nationwide, multicentre OR studies, vii) providing access to anonymized patient and programme surveillance data, vii) creating a forum for evidence dissemination and fostering policy change and ix) monitoring and accountability. In conclusion, ending the TB epidemic will not be possible without new tools (diagnostics, drugs, vaccines) and a multi-sectoral response involving stakeholders beyond the health ministry, including private providers, patients and communities. However, timely conduct of operational research to fine-tune programme implementation and ensuring proper deployment of new tools will be equally crucial to maximize the effectiveness and efficiency of interventions and ultimately contribute towards ending TB.

Transmission analysis of a large tuberculosis outbreak in London: a mathematical modelling study using genomic data

Outbreaks of tuberculosis (TB) - such as the large isoniazid-resistant outbreak centred on London, UK, which originated in 1995 - provide excellent opportunities to model transmission of this devastating disease. Transmission chains for TB are notoriously difficult to ascertain, but mathematical modelling approaches, combined with whole-genome sequencing data, have strong potential to contribute to transmission analyses. Using such data, we aimed to reconstruct transmission histories for the outbreak using a Bayesian approach, and to use machine-learning techniques with patient-level data to identify the key covariates associated with transmission. By using our transmission reconstruction method that accounts for phylogenetic uncertainty, we are able to identify 21 transmission events with reasonable confidence, 9 of which have zero SNP distance, and a maximum distance of 3. Patient age, alcohol abuse and history of homelessness were found to be the most important predictors of being credible TB transmitters.

The TB REACH Initiative: Supporting TB Elimination Efforts in the Asia-Pacific

After many years of TB 'control' and incremental progress, the TB community is talking about ending the disease, yet this will only be possible with a shift in the way we approach the TB response. While the Asia-Pacific region has the highest TB burden worldwide, it also has the opportunity to lead the quest to end TB by embracing the four areas laid out in this series: using data to target hotspots, initiating active case finding, provisioning preventive TB treatment, and employing a biosocial approach. The Stop TB Partnership's TB REACH initiative provides a platform to support partners in the development, evaluation and scale-up of new and innovative technologies and approaches to advance TB programs. We present several approaches TB REACH is taking to support its partners in the Asia-Pacific and globally to advance our collective response to end TB.

Children as sentinels of tuberculosis transmission: disease mapping of programmatic data

BACKGROUND

Identifying hotspots of tuberculosis transmission can inform spatially targeted active case-finding interventions. While national tuberculosis programs maintain notification registers which represent a potential source of data to investigate transmission patterns, high local tuberculosis incidence may not provide a reliable signal for transmission because the population distribution of covariates affecting susceptibility and disease progression may confound the relationship between tuberculosis incidence and transmission. Child cases of tuberculosis and other endemic infectious disease have been observed to provide a signal of their transmission intensity. We assessed whether local overrepresentation of child cases in tuberculosis notification data corresponds to areas where recent transmission events are concentrated.

METHODS

We visualized spatial clustering of children < 5 years old notified to Peru's National Tuberculosis Program from two districts of Lima, Peru, from 2005 to 2007 using a log-Gaussian Cox process to model the intensity of the point-referenced child cases. To identify where clustering of child cases was more extreme than expected by chance alone, we mapped all cases from the notification data onto a grid and used a hierarchical Bayesian spatial model to identify grid cells where the proportion of cases among children < 5 years old is greater than expected. Modeling the proportion of child cases allowed us to use the spatial distribution of adult cases to control for unobserved factors that may explain the spatial variability in the distribution of child cases. We compare where young children are overrepresented in case notification data to areas identified as transmission hotspots using molecular epidemiological methods during a prospective study of tuberculosis transmission conducted from 2009 to 2012 in the same setting.

RESULTS

Areas in which childhood tuberculosis cases are overrepresented align with areas of spatial concentration of transmission revealed by molecular epidemiologic methods.

CONCLUSIONS

Age-disaggregated notification data can be used to identify hotspots of tuberculosis transmission and suggest local force of infection, providing an easily accessible source of data to target active case-finding intervention.

Increasing Drug Resistance Among Persons With Tuberculosis in Massachusetts, 2009-2018

We examined Massachusetts tuberculosis surveillance data from to 2009 to 2018. Of 1533 culture-confirmed cases, 190 (12.4%) demonstrated resistance to isoniazid including 32 (2.1%) with rifampin resistance. In multivariable analysis, isoniazid resistance increased significantly over time (per-year odds ratio = 1.07, 95% confidence interval = 1.01-1.13, P = .018) and was associated with younger age, foreign birth, and prior tuberculosis treatment.

Finding gaps in TB notifications: spatial analysis of geographical patterns of TB notifications, associations with TB program efforts and social determinants of TB risk in Bangladesh, Nepal and Pakistan

BACKGROUND

In order to effectively combat Tuberculosis, resources to diagnose and treat TB should be allocated effectively to the areas and population that need them. Although a wealth of subnational data on TB is routinely collected to support local planning, it is often underutilized. Therefore, this study uses spatial analytical techniques and profiling to understand and identify factors underlying spatial variation in TB case notification rates (CNR) in Bangladesh, Nepal and Pakistan for better TB program planning.

METHODS

Spatial analytical techniques and profiling was used to identify subnational patterns of TB CNRs at the district level in Bangladesh (N = 64, 2015), Nepal (N = 75, 2014) and Pakistan (N = 142, 2015). A multivariable linear regression analysis was performed to assess the association between subnational CNR and demographic and health indicators associated with TB burden and indicators of TB programme efforts. To correct for spatial dependencies of the observations, the residuals of the multivariable models were tested for unexplained spatial autocorrelation. Spatial autocorrelation among the residuals was adjusted for by fitting a simultaneous autoregressive model (SAR).

RESULTS

Spatial clustering of TB CNRs was observed in all three countries. In Bangladesh, TB CNR were found significantly associated with testing rate (0.06%, p < 0.001), test positivity rate (14.44%, p < 0.001), proportion of bacteriologically confirmed cases (- 1.33%, p < 0.001) and population density (4.5*10-3%, p < 0.01). In Nepal, TB CNR were associated with population sex ratio (1.54%, p < 0.01), facility density (- 0.19%, p < 0.05) and treatment success rate (- 3.68%, p < 0.001). Finally, TB CNR in Pakistan were found significantly associated with testing rate (0.08%, p < 0.001), positivity rate (4.29, p < 0.001), proportion of bacteriologically confirmed cases (- 1.45, p < 0.001), vaccination coverage (1.17%, p < 0.001) and facility density (20.41%, p < 0.001).

CONCLUSION

Subnational TB CNRs are more likely reflective of TB programme efforts and access to healthcare than TB burden. TB CNRs are better used for monitoring and evaluation of TB control efforts than the TB epidemic. Using spatial analytical techniques and profiling can help identify areas where TB is underreported. Applying these techniques routinely in the surveillance facilitates the use of TB CNRs in program planning.

Spatial distribution of people diagnosed with tuberculosis through routine and active case finding: a community-based study in Kampala, Uganda

BACKGROUND

Routine tuberculosis (TB) notifications are geographically heterogeneous, but their utility in predicting the location of undiagnosed TB cases is unclear. We aimed to identify small-scale geographic areas with high TB notification rates based on routinely collected data and to evaluate whether these areas have a correspondingly high rate of undiagnosed prevalent TB.

METHODS

We used routinely collected data to identify geographic areas with high TB notification rates and evaluated the extent to which these areas correlated with the location of undiagnosed cases during a subsequent community-wide active case finding intervention in Kampala, Uganda. We first enrolled all adults who lived within 35 contiguous zones and were diagnosed through routine care at four local TB Diagnosis and Treatment Units. We calculated average monthly TB notification rates in each zone and defined geographic areas of "high risk" as zones that constituted the 20% of the population with highest notification rates. We compared the observed proportion of TB notifications among residents of these high-risk zones to the expected proportion, using simulated estimates based on population size and random variation alone. We then evaluated the extent to which these high-risk zones identified areas with high burdens of undiagnosed TB during a subsequent community-based active case finding campaign using a chi-square test.

RESULTS

We enrolled 45 adults diagnosed with TB through routine practices and who lived within the study area (estimated population of 49 527). Eighteen zones reported no TB cases in the 9-month period; among the remaining zones, monthly TB notification rates ranged from 3.9 to 39.4 per 100 000 population. The five zones with the highest notification rates constituted 62% (95% CI: 47-75%) of TB cases and 22% of the population-significantly higher than would be expected if population size and random chance were the only determinants of zone-to-zone variation (48%, 95% simulation interval: 40-59%). These five high-risk zones accounted for 42% (95% CI: 34-51%) of the 128 cases detected during the subsequent community-based case finding intervention, which was significantly higher than the 22% expected by chance (P < 0.001) but lower than the 62% of cases notified from those zones during the pre-intervention period (P = 0.02).

CONCLUSIONS

There is substantial heterogeneity in routine TB notification rates at the zone level. Using facility-based TB notification rates to prioritize high-yield areas for active case finding could double the yield of such case-finding interventions.

Initial loss to follow up of tuberculosis patients in South Africa: perspectives of program managers

Background

Tuberculosis (TB) remains a serious public health problem in South Africa. Initial loss to follow up (LTFU) rates among TB patients are high, varying between 14.9 and 22.5%. From the perspective of patients, documented reasons for this include poor communication between patient and staff after testing, not being aware that results are ready and other competing priorities such as preference to go to work as opposed to seeking healthcare. Ward-based Outreach Teams (WBOTs) routinely conduct home visits to ensure adherence to medication for various conditions including TB. We explored reasons for TB initial loss to follow up from the perspectives of TB program managers and WBOT program managers, with a focus on the WBOT’s (potential) role in reducing initial LTFU, in particular.

Methods

Key informant interviews with five WBOT program managers and four TB program managers were conducted. The interviews were audio-recorded, then transcribed and exported to NVivo 11 software for coding. A hybrid analytic approach consisting of both inductive and deductive coding was used to identify themes.

Results

The age of the nine managers ranged between 28 and 52 years old, of which two were male. They had been in their current position for between 2 to 12 years. Prior to treatment initiation, WBOTs screen household members for TB and refer them for TB testing if need be, but integration of the two programs is emphasized only after TB treatment has been initiated. Counseling of patients testing for TB is not guaranteed due to frequent staff rotations and staff shortages. Participants reported that possible dissatisfaction with services as well as stigma associated with the TB diagnosis could explain loss to follow up prior to treatment initiation.

Conclusion

Program managers view health system related factors such as staff rotations, poor communication with patients and lack of counseling as contributing to the problem of initial LTFU among TB patients. The integration of the WBOT and TB programs is limited to referring suspected cases for testing and patients already on treatment.

Spatiotemporal analysis of drug-resistant TB patients registered in selected districts of Karnataka, South India: a cross-sectional study

Background

Tuberculosis (TB) depicts heterogeneous spatial patterns with geographical aggregation of TB cases due to either ongoing person-to-person transmission or reactivation of latent infection in a community sharing risk factor. In this regard, we aimed to assess the spatiotemporal aggregation of drug-resistant TB (DR-TB) patients notified to the national TB program (NTP) from 2015 to 2018 in selected districts of Karnataka, South India.

Methods

This was a cross-sectional study among DR-TB patients notified from Dakshina Kannada, Udupi, and Chikamagalur districts of the state of Karnataka. Clinico-demographic details were extracted from treatment cards. The registered addresses of the patients were geocoded (latitude and longitude) using Google Earth. Using the QGIS software, spot map, heat maps and grid maps 25 km² with more than the expected count of DR-TB patients were constructed.

Results

Of the total 507 patients studied, 376 (74%) were males and the mean (standard deviation) age of the study participants was 41.4 (13.9) years. From 2015 to 2018, the number of patients increased from 85 to 209 per year, the area of aggregation in square kilometers increased from 113.6 to 205.7, and the number of rectangular grids with more than the expected DR-TB patients (> 1) increased from 12 to 47.

Conclusions

The increase in the number of DR-TB patients, area of aggregation, and grids with more than the expected count is a cause for concern. The NTP can use routine programmatic data to develop maps to identify areas of aggregation of disease for targeted TB control activities.

Explaining the successes and failures of tuberculosis treatment programs; a tale of two regions in rural eastern Uganda

Background

Optimally performing tuberculosis (TB) programs are characterized by treatment success rate (TSR) of at least 90%. In rural eastern Uganda, and elsewhere in sub Saharan Africa, TSR varies considerably across district TB programs and the reasons for the differences are unclear. This study explored factors associated with the low and high TSR across four districts in rural eastern Uganda.

Methods

We interviewed District TB and Leprosy Supervisors, Laboratory focal persons, and health facility TB focal persons from four districts in eastern Uganda as key informants. Interviews were audio recorded, transcribed verbatim, and imported into ATLAs.ti where thematic content analysis was performed and results were summarized into themes.

Results

The emerging themes were categorized as either facilitators of or barriers to treatment success. The emerging facilitators prevailing in the districts with high rates of treatment success were using data to make decisions and design interventions, continuous quality improvement, capacity building, and prioritization of better management of people with TB. The barriers common in districts with low rates of treatment success included lack of motivated and dedicated TB focal persons, scarce or no funding for implementing TB activities, and a poor implementation of community-based directly observed therapy short course.

Conclusion

This study shows that several factors are associated with the differing rates of treatment success in rural eastern Uganda. These factors should be the focus for TB control programs in Uganda and similar settings in order to improve rates of treatment success.

Understanding the intersection of race and place: the case of tuberculosis in Michigan

BACKGROUND

Race and place intersect to produce location-based variation in disease distributions. We analyzed the geographic distribution of tuberculosis (TB) incidence in Michigan, USA to better understand the complex interplay between race and place, comparing patterns in Detroit, Wayne County and the state of Michigan as a whole.

METHODS

Using cross-sectional TB surveillance data from the Michigan Department of Health and Human Services, multivariable statistical models were developed to analyze the residence patterns of TB incidence from 2007 through 2012. Two-way interactions among the residence location and race of cases were assessed.

RESULTS

Overall, Detroit residents experienced 58% greater TB incidence than residents of Wayne County or the state of Michigan. Racial inequalities were less pronounced in Detroit compared to both Wayne County and the state of Michigan. Blacks in Detroit had 2.01 times greater TB incidence than Whites, while this inequality was 3.62 times more in Wayne County and 8.72 greater in the state of Michigan.

CONCLUSION

Our results highlight how race and place interact to influence patterns of TB disease, and the ways in which this interaction is context dependent. TB elimination in the U.S. will require strategies that address the local social environment, as much as the physical environment.

Using Google Earth™ and Geographical Information System data as method to delineate sample domains for an urban household surveys: the case of Maroua (Far North Region-Cameroon)

Background

Getting a random household sample during a survey can be expensive and very difficult especially in urban area and non-specialist. This study aimed to test an alternative method using freely available aerial imagery.

Methods

A gridded map and random selection method was used to select households for interviews. A hundred numbered of points were put along the edges of an updated map of Maroua. Then two numbers were randomly draw at a time and a line was drawn between those two numbers. A lot of different kinds of shapes of different sizes obtained were numbered. Ten shapes were randomly draw and the one selected were considered as ‘neighbourhoods’. A grid of 30 m × 30 m was drawn over each and then numbered. 202 grids considered here as households were randomly selected from the ten neighbourhoods for interviews.

Results

Out of 202 households visited, only 4 were found to be something other than a house. In addition, 30 sampled households (14.85%) were abandoned or the occupants had relocated elsewhere. This method resulted in an accuracy level of 72%, its advantage is the ability to generate efficient random sample at relatively low cost as well the time required.

Conclusions

The method proposed in this study was efficient and cost-effective when compared to the infield generation of a household inventory or Global Positioning System (GPS) tracking of households. It can then be used by researchers in low-incomes countries where funding for research is a challenge. However, this method needs to train the investigators on how to use the GPS.

Multidrug-Resistant Tuberculosis In A Referral Center In Rome: 2011- 2016

PURPOSE

Multidrug-resistant tuberculosis (MDR-TB) is a major burden to public health in low incidence countries in Europe. The aim of this study was to attempt to have a better insight into the trends of MDR-TB in the metropolitan area of Rome, within the Italian and the foreign-born population, based on microbiological and demographic data.

PATIENTS AND METHODS

We performed a prospective study, collecting microbiological data based on phenotypic drug-resistant testing (DST) of TB strains consecutively isolated in a referral hospital in Rome, the capital city of a low TB incidence country, over a 6-year period, and correlated them to the geographical origin of patients. This study was carried out in a referral hospital for patients with drug-resistant TB from the whole region.

RESULTS

Drug-resistance data from 926 patients with a microbiological diagnosis of TB from 2011 to 2016 show a 5.5% rate of MDR-TB, mostly occurring in patients born in a single East European country, that has a high incidence of MDR-TB. The strains isolated from these patients frequently carry additional resistances, leading to an increased risk of developing extensively drug-resistant (XDR) TB.

CONCLUSION

In the great metropolitan area of Rome, MDR-TB more frequently occurs in patients who were born in a single country from Eastern Europe known to have high rates of MDR-TB and long-time residents in Italy. Recent immigrants from non-European countries do not appear to contribute to the rates of MDR-TB reported in this article. This knowledge of local TB trends could help improve the measures of surveillance and prevention of disease.

Quality of TB care among people living with HIV: Gaps and solutions

Tuberculosis (TB) is the leading infectious cause of death among people living with HIV, causing one third of AIDS-related deaths globally. The concerning number of missing TB cases, ongoing high TB mortality, slow reduction in TB incidence, and limited uptake of TB preventive treatment among people living with HIV, all indicate the urgent need to improve quality of TB services within HIV programs. In this mini-review we discuss major gaps in quality of TB care that impede achieving prevention and treatment targets within the TB-HIV care cascades, show approaches of assessing gaps in TB service provision, and describe outcomes from innovative quality improvement projects among HIV and TB programs. We also offer recommendations for measuring quality of TB care.

Overcoming limitations of tuberculosis information systems: researcher and clinician perspectives

Setting

Tuberculosis (TB) diagnosis and treatment requires patients to have multiple encounters with health care systems and the different stakeholders who play a role in curing them to coordinate their efforts. To optimize this process, high-quality, readily available data are required. Data systems to facilitate these linkages are a neglected priority which, if weak, fundamentally undermine TB control interventions.

Objective

To describe lessons learnt from the use of programmatic data for TB patient care and research.

Design

We did a survey of researcher and clinical provider experiences with information systems and developed a tiered approach to addressing frequently reported barriers to high-quality care.

Results

Unreliable linkages, incomplete data, lack of a reliable unique patient identifier, and lack of data management expertise were the most important data-related barriers to high-quality patient care and research. We propose the creation of health service delivery environments that facilitate, prioritize, and evaluate high-quality data entry during patient or specimen registration.

Conclusion

An integrated approach, focused on high-quality data, and centered on unique patient identification will form the foundation for linkages across health systems that reduce patient management errors, bolster surveillance, and enhance the quality of research based on programmatic data.

Space-time clustering of recently-diagnosed tuberculosis and impact of ART scale-up: Evidence from an HIV hyper-endemic rural South African population

In HIV hyperendemic sub-Saharan African communities, particularly in southern Africa, the likelihood of achieving the Sustainable Development Goal of ending the tuberculosis (TB) epidemic by 2030 is low, due to lack of cost-effective and practical interventions in population settings. We used one of Africa’s largest population-based prospective cohorts from rural KwaZulu-Natal Province, South Africa, to measure the spatial variations in the prevalence of recently-diagnosed TB disease, and to quantify the impact of community coverage of antiretroviral therapy (ART) on recently-diagnosed TB disease. We collected data on TB disease episodes from a population-based sample of 41,812 adult individuals between 2009 and 2015. Spatial clusters (‘hotspots’) of recently-diagnosed TB were identified using a space-time scan statistic. Multilevel logistic regression models were fitted to investigate the relationship between community ART coverage and recently-diagnosed TB. Spatial clusters of recently-diagnosed TB were identified in a region characterized by a high prevalence of HIV and population movement. Every percentage increase in ART coverage was associated with a 2% decrease in the odds of recently-diagnosed TB (aOR = 0.98, 95% CI:0.97–0.99). We identified for the first time the clear occurrence of recently-diagnosed TB hotspots, and quantified potential benefit of increased community ART coverage in lowering tuberculosis, highlighting the need to prioritize the expansion of such effective population interventions targeting high-risk areas.

Training for Tuberculosis Elimination in Indonesia: Achievements, Reflections, and Potential for Impact

Indonesia has the third highest tuberculosis (TB) caseload internationally. A cornerstone for strengthening health systems to respond to TB is a well-trained workforce. In a partnership between Indonesian and Australian institutions, TB training was run during 2018 to strengthen the local capacity to meet End TB strategy targets. This paper aims to report on course design, delivery, training outcomes, and reflections. Seventy-six Indonesian healthcare workers, program staff, researchers, and policy-makers were selected from over 800 applicants. The structure comprised three trainings, each with a pre-course workshop (in Indonesia) to identify learning needs, a two-week block (Australia), and a post-course workshop (Indonesia). The training content delivered was a combination of TB technical knowledge and program/project theory, design, and logic, and the training utilised multiple teaching and learning methods. An innovative element of the training was participant-designed TB workplace projects focusing on context-specific priorities. Evaluation was undertaken using participant surveys and appraisal of the projects. Participants rated the course highly, while success in project implementation varied. Reflections include the importance of involving Indonesian experts in delivery of training, the need to understand participant learning requirements and adapt the training content accordingly, and the challenge of measuring tangible training outputs.

Detection of risk clusters for deaths due to tuberculosis specifically in areas of southern Brazil where the disease was supposedly a non-problem

Background

Tuberculosis (TB) is the infectious disease that kills the most people worldwide. The use of geoepidemiological techniques to demonstrate the dynamics of the disease in vulnerable communities is essential for its control. Thus, this study aimed to identify risk clusters for TB deaths and their variation over time.

Methods

This ecological study considered cases of TB deaths in residents of Londrina, Brazil between 2008 and 2015. We used standard, isotonic scan statistics for the detection of spatial risk clusters. The Poisson discrete model was adopted with the high and low rates option used for 10, 30 and 50% of the population at risk, with circular format windows and 999 replications considered the maximum cluster size. Getis-Ord Gi* (Gi*) statistics were used to diagnose hotspot areas for TB mortality. Kernel density was used to identify whether the clusters changed over time.

Results

For the standard version, spatial risk clusters for 10, 30 and 50% of the exposed population were 4.9 (95% CI 2.6–9.4), 3.2 (95% CI: 2.1–5.7) and 3.2 (95% CI: 2.1–5.7), respectively. For the isotonic spatial statistics, the risk clusters for 10, 30 and 50% of the exposed population were 2.8 (95% CI: 1.5–5.1), 2.7 (95% CI: 1.6–4.4), 2.2 (95% CI: 1.4–3.9), respectively. All risk clusters were located in the eastern and northern regions of the municipality. Additionally, through Gi*, hotspot areas were identified in the eastern and western regions.

Conclusions

There were important risk areas for tuberculosis mortality in the eastern and northern regions of the municipality. Risk clusters for tuberculosis deaths were observed in areas where TB mortality was supposedly a non-problem. The isotonic and Gi* statistics were more sensitive for the detection of clusters in areas with a low number of cases; however, their applicability in public health is still restricted.

The burden of multidrug-resistant tuberculosis in children

BACKGROUND

Childhood tuberculosis (TB) has historically been neglected, although in recent years there has been increased focus on this problem. In particular, there have been two efforts to estimate the burden of pediatric multidrug-resistant TB (MDR-TB).

METHODS

We review current estimates of the global incidence of pediatric MDR-TB disease. We then combine pediatric MDR-TB treatment data from the World Health Organization and recently published case fatality ratio estimates for children with TB to produce mortality estimates for children with MDR-TB. Finally, we combine treatment data and estimates of household size and disease risk to estimate how many children could be treated for probable or confirmed MDR-TB by carrying out household contact investigations around adult MDR-TB patients.

RESULTS

Between 25 000 and 32 000 children develop MDR-TB disease annually, accounting for around 3% of all pediatric TB cases. Only 3-4% of these children are likely to receive MDR-TB treatment. We estimate that around 21% of children who develop MDR-TB disease will die. Carrying out household contact investigations around adult MDR-TB patients could find an estimated 12 times as many pediatric MDR-TB cases as are currently being identified.

DISCUSSION

The diagnosis and treatment of children with MDR-TB needs to be prioritized by TB programs.

Two Row Wampum, Human Rights, and the Elimination of Tuberculosis from High-Incidence Indigenous Communities

The Two Row Wampum belt is a symbolic record of the first agreement between Europeans and American Indians on Turtle Island (North America). The agreement outlined a commitment to friendship and peace between people living perpetually in parallel, with each party recognizing the other as an equal partner. Subsequent treaty relationships between the Indigenous peoples of the Canadian prairies and settler society, along with the colonially imposed structures they spawned, are widely regarded as having broken the Covenant Chain, the foundation of which is Two Row Wampum. For example, the universal right to health, especially public health, as protected by provincial and territorial legislation in Canada, is under threat in Indigenous communities with a high incidence of tuberculosis. The rights of Indigenous peoples have been asserted, and reasserted, in the United Nations Declaration on the Rights of Indigenous Peoples, the Truth and Reconciliation Commission of Canada, the International Patients' Charter for Tuberculosis Care, and Jordan's Principle. Herein we describe the implementation of a strategic plan that reinforces human rights and dignity in the spirit of Two Row Wampum in contemporary tuberculosis elimination efforts.

Global Variations and Challenges With Tubercular Uveitis in the Collaborative Ocular Tuberculosis Study

Purpose

The aim of this study was to examine regional variation management practices and outcomes for tubercular uveitis (TBU).

Methods

In this retrospective multinational cohort study, patients from 25 international eye care centers diagnosed with TBU with a minimum follow-up of 1 year were included. The geographic variation in treatment outcomes on survival analysis in patients with TBU were analyzed. Treatment failure is defined as a persistence or recurrence of inflammation within 6 months of completing antitubercular therapy, the inability to taper oral corticosteroids to less than 10 mg/d or topical corticosteroid drops to less than 2 drops daily, and/or recalcitrant inflammation necessitating corticosteroid-sparing immunosuppressive therapy.

Results

Records of 945 patients (1485 eyes) with TBU were analyzed. The mean age was 41.3 ± 15.0 years (range, 4-90 years), with more males (52.9%, n = 500/945) and predominant Asian ethnicity (74.4%, n = 690/927). Most patients had no symptoms (92.0%, n = 655/712) or history (76.7%, n = 604/787) suggestive of pulmonary tuberculosis (TB). Some patients had evidence of inactive pulmonary TB on chest X-rays (26.9%, n = 189/702) or chest computed tomography (68.6%, n = 109/159). Patients with western geographic origin (log-rank = 6.47, P = 0.010), African or Hispanic ethnicity (log-rank = 19.9, P < 0.001), and positive immigrant status (log-rank = 4.89, P = 0.027) had poorer survival outcomes.

Conclusions

This is a first-ever multinational analysis of TBU that highlights regional differences in treatment outcomes for this elusive form of extrapulmonary TB. Our findings will help in the design of future collaborative studies together with internists to develop best practice guidelines for this early opportunity to address TB infection and strategies to target at-risk groups such as immigrants.

Critical reflections, challenges and solutions for migrant and refugee health: 2nd M8 Alliance Expert Meeting

Throughout recent years, we have witnessed an increase in human migration as a result of conflict, political instability and changes in the climate. Despite the growing number of migrants and refugees, provisions to address their health needs remain inadequate and often unmet. Whilst a variety of instruments exist to assert and emphasise the importance for migrant and refugee health, the lack of shared priorities between partners and stakeholders results in poor access to healthcare and essential medicines. In response to the growing health challenges faced by migrants and refugees, members of the M8 Alliance launched an annual Expert Meeting on Migrants' and Refugees' Health. This report is shaped by discussions from the second M8 Alliance Expert Meeting (Sapienza University of Rome, Italy, 15-16 June 2018) and is supported by supplementing literature to develop a framework addressing critical reflections, challenges and solutions of and for migrant and refugee health. This report aims to inform decision-making fostering a humanitarian, ethics and rights-based approach. Through a series of country-specific case studies and discussions, this report captures the most prominent themes and recommendations such as mental health, tuberculosis (TB) and best practices for increased access.

Sub-national prevalence survey of tuberculosis in rural communities of Ethiopia

Background

Tuberculosis is a major public health problem with varying prevalence in different settings. National prevalence surveys provide evidence for planning and decision making. However, they lack the capacity to estimate subnational magnitude that affected the capacity to make selected intervention based on the prevalence. Ethiopia is among high TB burden countries with estimated prevalence of 108 per 100,000 population varying by regions. We aimed to study sub national prevalence of smear-positive TB in rural communities of southern Ethiopia.

Methods

This cross-sectional study, enrolled community members aged over 14 years who had cough of at least two weeks duration. Two sputum samples were collected and examined by using smear microscopy.

Results

38,304 eligible people were enumerated (10,779 from Hadiya, 10,059 from Gurage and 17,466 from Sidama) and indentified 960 presumptive cases. 16, 14 and 14 smear-positive pulmonary TB cases were identified respectively. The point prevalence of smear-positive TB were 148 per 100,000 population (95% CI: 91–241) in Hadiya, 139 per 100,000 population (95% CI: 83–234) in Gurage and 80/100,000 population (95%CI: 48–135) in Sidama zone. Gurage zone had the highest prevalent to notified cases of seven to one.

Conclusions

The prevalence of smear positive TB varies by districts and is high in rural southern Ethiopia compared to the estimated national prevalence. More TB patients remain missed and unreached, impacting negatively on health outcomes. TB case finding approaches should be revisited and innovative approaches and tools to identify missing people with TB should be scaled up.

Transmission of drug-resistant tuberculosis in HIV-endemic settings

The emergence and expansion of the multidrug-resistant tuberculosis epidemic is a threat to the global control of tuberculosis. Multidrug-resistant tuberculosis is the result of the selection of resistance-conferring mutations during inadequate antituberculosis treatment. However, HIV has a profound effect on the natural history of tuberculosis, manifesting in an increased rate of disease progression, leading to increased transmission and amplification of multidrug-resistant tuberculosis. Interventions specific to HIV-endemic areas are urgently needed to block tuberculosis transmission. These interventions should include a combination of rapid molecular diagnostics and improved chemotherapy to shorten the duration of infectiousness, implementation of infection control measures, and active screening of multidrug-resistant tuberculosis contacts, with prophylactic regimens for individuals without evidence of disease. Development and improvement of the efficacy of interventions will require a greater understanding of the factors affecting the transmission of multidrug-resistant tuberculosis in HIV-endemic settings, including population-based molecular epidemiology studies. In this Series article, we review what we know about the transmission of multidrug-resistant tuberculosis in settings with high burdens of HIV and define the research priorities required to develop more effective interventions, to diminish ongoing transmission and the amplification of drug resistance.

Spatially targeted screening to reduce tuberculosis transmission in high-incidence settings

As the leading infectious cause of death worldwide and the primary proximal cause of death in individuals living with HIV, tuberculosis remains a global concern. Existing tuberculosis control strategies that rely on passive case-finding appear insufficient to achieve targets for reductions in tuberculosis incidence and mortality. Active case-finding strategies aim to detect infectious individuals earlier in their infectious period to reduce onward transmission and improve treatment outcomes. Empirical studies of active case-finding have produced mixed results and determining how to direct active screening to those most at risk remains a topic of intense research. Our systematic review of literature evaluating the effects of geographically targeted tuberculosis screening interventions found three studies in low tuberculosis incidence settings, but none conducted in high tuberculosis incidence countries. We discuss open questions related to the use of spatially targeted approaches for active screening in countries where tuberculosis incidence is highest.

Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review

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.

Progress toward eliminating TB and HIV deaths in Brazil, 2001-2015: a spatial assessment

BACKGROUND

Brazil has high burdens of tuberculosis (TB) and HIV, as previously estimated for the 26 states and the Federal District, as well as high levels of inequality in social and health indicators. We improved the geographic detail of burden estimation by modelling deaths due to TB and HIV and TB case fatality ratios for the more than 5400 municipalities in Brazil.

METHODS

This ecological study used vital registration data from the national mortality information system and TB case notifications from the national communicable disease notification system from 2001 to 2015. Mortality due to TB and HIV was modelled separately by cause and sex using a Bayesian spatially explicit mixed effects regression model. TB incidence was modelled using the same approach. Results were calibrated to the Global Burden of Disease Study 2016. Case fatality ratios were calculated for TB.

RESULTS

There was substantial inequality in TB and HIV mortality rates within the nation and within states. National-level TB mortality in people without HIV infection declined by nearly 50% during 2001 to 2015, but HIV mortality declined by just over 20% for males and 10% for females. TB and HIV mortality rates for municipalities in the 90th percentile nationally were more than three times rates in the 10th percentile, with nearly 70% of the worst-performing municipalities for male TB mortality and more than 75% for female mortality in 2001 also in the worst decile in 2015. The same municipality ranking metric for HIV was observed to be between 55% and 61%. Within states, the TB mortality rate ratios by sex for municipalities in the worst decile versus the best decile varied from 1.4 to 2.9, and HIV varied from 1.4 to 4.2. The World Health Organization target case fatality rate for TB of less than 10% was achieved in 9.6% of municipalities for males versus 38.4% for females in 2001 and improved to 38.4% and 56.6% of municipalities for males versus females, respectively, by 2014.

CONCLUSIONS

Mortality rates in municipalities within the same state exhibited nearly as much relative variation as within the nation as a whole. Monitoring the mortality burden at this level of geographic detail is critical for guiding precision public health responses.

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

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

Using routinely collected laboratory data to identify high rifampicin-resistant tuberculosis burden communities in the Western Cape Province, South Africa: A retrospective spatiotemporal analysis

BACKGROUND

South Africa has the highest tuberculosis incidence globally (781/100,000), with an estimated 4.3% of cases being rifampicin resistant (RR). Control and elimination strategies will require detailed spatial information to understand where drug-resistant tuberculosis exists and why it persists in those communities. We demonstrate a method to enable drug-resistant tuberculosis monitoring by identifying high-burden communities in the Western Cape Province using routinely collected laboratory data.

METHODS AND FINDINGS

We retrospectively identified cases of microbiologically confirmed tuberculosis and RR-tuberculosis from all biological samples submitted for tuberculosis testing (n = 2,219,891) to the Western Cape National Health Laboratory Services (NHLS) between January 1, 2008, and June 30, 2013. Because the NHLS database lacks unique patient identifiers, we performed a series of record-linking processes to match specimen records to individual patients. We counted an individual as having a single disease episode if their positive samples came from within two years of each other. Cases were aggregated by clinic location (n = 302) to estimate the percentage of tuberculosis cases with rifampicin resistance per clinic. We used inverse distance weighting (IDW) to produce heatmaps of the RR-tuberculosis percentage across the province. Regression was used to estimate annual changes in the RR-tuberculosis percentage by clinic, and estimated average size and direction of change was mapped. We identified 799,779 individuals who had specimens submitted from mappable clinics for testing, of whom 222,735 (27.8%) had microbiologically confirmed tuberculosis. The study population was 43% female, the median age was 36 years (IQR 27-44), and 10,255 (4.6%, 95% CI: 4.6-4.7) cases had documented rifampicin resistance. Among individuals with microbiologically confirmed tuberculosis, 8,947 (4.0%) had more than one disease episode during the study period. The percentage of tuberculosis cases with rifampicin resistance documented among these individuals was 11.4% (95% CI: 10.7-12.0). Overall, the percentage of tuberculosis cases that were RR-tuberculosis was spatially heterogeneous, ranging from 0% to 25% across the province. Our maps reveal significant yearly fluctuations in RR-tuberculosis percentages at several locations. Additionally, the directions of change over time in RR-tuberculosis percentage were not uniform. The main limitation of this study is the lack of unique patient identifiers in the NHLS database, rendering findings to be estimates reliant on the accuracy of the person-matching algorithm.

CONCLUSIONS

Our maps reveal striking spatial and temporal heterogeneity in RR-tuberculosis percentages across this province. We demonstrate the potential to monitor RR-tuberculosis spatially and temporally with routinely collected laboratory data, enabling improved resource targeting and more rapid locally appropriate interventions.

Where is tuberculosis transmission happening? Insights from the literature, new tools to study transmission and implications for the elimination of tuberculosis

More than 10 million new cases of tuberculosis (TB) are diagnosed worldwide each year. The majority of these cases occur in low- and middle-income countries where the TB epidemic is predominantly driven by transmission. Efforts to 'end TB' will depend upon our ability to halt ongoing transmission. However, recent studies of new approaches to interrupt transmission have demonstrated inconsistent effects on reducing population-level TB incidence. TB transmission occurs across a wide range of settings, that include households and hospitals, but also community-based settings. While home-based contact investigations and infection control programmes in hospitals and clinics have a successful track record as TB control activities, there is a gap in our knowledge of where, and between whom, community-based transmission of TB occurs. Novel tools, including molecular epidemiology, geospatial analyses and ventilation studies, provide hope for improving our understanding of transmission in countries where the burden of TB is greatest. By integrating these diverse and innovative tools, we can enhance our ability to identify transmission events by documenting the opportunity for transmission-through either an epidemiologic or geospatial connection-alongside genomic evidence for transmission, based upon genetically similar TB strains. A greater understanding of locations and patterns of transmission will translate into meaningful improvements in our current TB control activities by informing targeted, evidence-based public health interventions.