Systems analysis and improvement approach to optimize tuberculosis (SAIA-TB) screening, treatment, and prevention in South Africa: a stepped-wedge cluster randomized trial.

BACKGROUND: The use of systems engineering tools, including the development and use of care cascades using routinely collected data, process mapping, and continuous quality improvement, is used for frontline healthcare workers to devise systems level change. South Africa experiences high rates of tuberculosis (TB) infection and disease as well as HIV co-infection. The Department of Health has made significant gains in HIV services over the last two decades, reaching their set "90-90-90" targets for HIV. However, TB services, although robust, have lagged in comparison for both disease and infection. The Systems Analysis and Improvement Approach (SAIA) is a five-step implementation science method, drawn from systems engineering, to identify, define, and implement workflow modifications using cascade analysis, process mapping, and repeated quality improvement cycles within healthcare facilities. METHODS: This stepped-wedge cluster randomized trial will evaluate the effectiveness of SAIA on TB (SAIA-TB) cascade optimization for patients with TB and high-risk contacts across 16 clinics in four local municipalities in the Sarah Baartman district, Eastern Cape, South Africa. We hypothesize that SAIA-TB implementation will lead to a 20% increase in each of: TB screening, TB preventive treatment initiation, and TB disease treatment initiation during the 18-month intervention period. Focus group discussions and key informant interviews with clinic staff will also be conducted to determine drivers of implementation variability across clinics. DISCUSSION: This study has the potential to improve TB screening, treatment initiation, and completion for both active disease and preventive measures among individuals with and without HIV in a high burden setting. SAIA-TB provides frontline health care workers with a systems-level view of their care delivery system with the aim of sustainable systems-level improvements. TRIAL REGISTRATION: Clinicaltrials.gov, NCT06314386. Registered 18 March 2024, https://clinicaltrials.gov/study/NCT06314386 . NCT06314386.

Who Transmits Tuberculosis to Whom: A Cross-Sectional Analysis of a Cohort Study in Lima, Peru.

Rationale: The persistent burden of tuberculosis (TB) disease emphasizes the need to identify individuals with TB for treatment and those at a high risk of incident TB for prevention. Targeting interventions toward those at high risk of developing and transmitting TB is a public health priority. Objectives: We aimed to identify characteristics of individuals involved in TB transmission in a community setting, which may guide the prioritization of targeted interventions. Methods: We collected clinical and sociodemographic data from a cohort of patients with TB in Lima, Peru. We used whole-genome sequencing data to assess the genetic distance between all possible pairs of patients; we considered pairs to be the result of a direct transmission event if they differed by three or fewer SNPs, and we assumed that the first diagnosed patient in a pair was the transmitter and the second was the recipient. We used logistic regression to examine the association between host factors and the likelihood of direct TB transmission. Measurements and Main Results: Analyzing data from 2,518 index patients with TB, we identified 1,447 direct transmission pairs. Regardless of recipient attributes, individuals less than 34 years old, males, and those with a history of incarceration had a higher likelihood of being transmitters in direct transmission pairs. Direct transmission was more likely when both patients were drinkers or smokers. Conclusions: This study identifies men, young adults, former prisoners, alcohol consumers, and smokers as priority groups for targeted interventions. Innovative strategies are needed to extend TB screening to social groups such as young adults and prisoners with limited access to routine preventive care.

Cost of inaction: a framework to estimate the economic cost of missing a patient with tuberculosis in the Indian context.

OBJECTIVES: To estimate the economic impact of failure to find and treat tuberculosis disease and prevent tuberculosis infection from progressing to active disease. DESIGN: Estimating the economic cost of not finding and treating a patient suffering from tuberculosis. SETTING: Estimation methodology is developed in the Indian context, as informed by local costs and reported tuberculosis epidemiology. PARTICIPANTS: No individual participants were included. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome measure is the total cost of patients with drug-susceptible and drug-resistant tuberculosis who are and are not found and treated by tuberculosis programmes, including costs for medications, lost productivity, healthcare services and furthered transmission. We calculate the economic burdens by varying the number of individuals a person sick with tuberculosis infects (10 or 15 people) and the risk of progression to tuberculosis disease if infected (5 or 8%). The secondary outcome measure is the amount saved by finding a patient early or who would not have otherwise been found. All costs are presented in US dollars (exchange rate: 72 Indian rupees/1 US$). RESULTS: By finding and treating a patient early before furthered transmission occurs-or stopping progression of tuberculosis infection to tuberculosis disease with preventive therapy-the Indian health system can save US$5502 to US$15 825 and US$5846 to US$25 575, for each individual with drug-susceptible and drug-resistant tuberculosis, respectively, across scenarios. CONCLUSIONS: These estimates provide crude, lower bounds for the potential costs of not appropriately diagnosing and treating a single patient with active tuberculosis in a timely manner, or preventing a patient with tuberculosis infection from progressing to active disease. The actual financial burden on society is far higher than estimated using this simple, short-term cost-effective analyses. Our results highlight the limitations of tuberculosis costing models to date, and demonstrate the importance of accounting for airborne transmission of tuberculosis.

The impact of clinical placement site, community clinic versus tertiary hospital, on midwifery students' clinical learning experience in Sierra Leone: a cohort study.

BACKGROUND: In midwifery education, the clinical learning experience (CLE) is a critical component to gaining competency and should comprise greater than 50% of a student's education. Many studies have identified positive and negative factors affecting students' CLE. However, few studies have directly compared the difference in CLE based on placement at a community clinic versus a tertiary hospital. METHODS: The aim of this study was to examine how clinical placement site, clinic or hospital, impacts students' CLE in Sierra Leone. A once 34-question survey was given to midwifery students attending one of four public midwifery schools in Sierra Leone. Median scores were compared for survey items by placement site using Wilcoxon tests. The relationship between clinical placement and student's experience were assessed using multilevel logistic regression. RESULTS: Two-hundred students (hospitals students = 145 (72.5%); clinic students = 55 (27.5%) across Sierra Leone completed surveys. Most students (76%, n = 151) reported satisfaction with their clinical placement. Students placed at clinics were more satisfied with opportunities to practice/develop skills (p = 0.007) and more strongly agreed preceptors treated them with respect (p = 0.001), helped improve their skills (p = 0.001), provided a safe environment to ask questions (p = 0.002), and had stronger teaching/mentorship skills (p = 0.009) than hospital students. Students placed at hospitals had greater satisfaction in exposure to certain clinical opportunities including completing partographs (p < 0.001); perineal suturing (p < 0.001); drug calculations/administration (p < 0.001) and estimation of blood loss (p = 0.004) compared to clinic students. The odds of students spending more than 4 h per day in direct clinical care were 5.841 (95% CI: 2.187-15.602) times higher for clinic students versus hospital students. There was no difference between clinical placement sites in regards to number of births students attended (OR 0.903; 95% CI: 0.399, 2.047) or number of births students managed without a preceptor/clinician present (OR 0.729; 95% CI: 0.285, 1.867). CONCLUSION: The clinical placement site, hospital or clinic, impacts midwifery students' CLE. Clinics offered students significantly greater attributes of a supportive learning environment and access to direct, hands-on opportunities for patient care. These findings may be helpful for schools when using limited resources to improve the quality of midwifery education.

Two Clinical Prediction Tools to Inform Rapid Tuberculosis Treatment Decision-making in Children.

Background: In the absence of bacteriologic confirmation to diagnose tuberculosis (TB) in children, it is suggested that treatment should be initiated when sufficient clinical evidence of disease is available. However, it is unclear what clinical evidence is sufficient to make this decision. To identify children who would benefit from rapid initiation of TB treatment, we developed 2 clinical prediction tools. Methods: We conducted a secondary analysis of a prospective intensified TB patient-finding intervention conducted in Pakistan in 2014-2016. TB disease was determined through either bacteriologic confirmation or a clinical diagnosis. We derived 2 tools: 1 uses classification and regression tree (CART) analysis to develop decision trees, while the second uses multivariable logistic regression to calculate a risk score. Results: Of the 5162 and 5074 children included in the CART and prediction score, respectively, 1417 (27.5%) and 1365 (26.9%) were eligible for TB treatment. CART identified abnormal chest radiographs and family history of TB as the most important predictors (area under the receiver operating characteristic curve [AUC], 0.949). The final prediction score model included age group (0-4, 5-9, 10-14), weight <5th percentile, cough, fever, weight loss, chest radiograph suggestive of TB disease, and family history of TB; the identified best cutoff score was 9 (AUC, 0.985%). Conclusions: Use of clinical evidence was sufficient to accurately identify children who would benefit from treatment initiation. Our tools performed well compared with existing algorithms, though these results need to be externally validated before operationalization.

Sensitivity of Various Case Detection Algorithms for Community-based Tuberculosis Screening.

Using data from 388 people diagnosed with tuberculosis through a community-based screening program in Lima, Peru, we estimated that cough screening followed by sputum smear microscopy would have detected only 23% of cases found using an algorithm of radiographic screening followed by rapid nucleic acid amplification testing and clinical evaluation.

Geospatial analysis of reported activity locations to identify sites for tuberculosis screening.

Mobile screening units can help close tuberculosis case detection gaps. Placing screening units where people at high risk for undiagnosed tuberculosis preferentially spend time could make screening more resource-effective. We conducted a case-control study in Lima, Peru to identify locations where people with tuberculosis were more likely to spend time than community controls. We surveyed participants about activity locations over the past 6 months. We used density-based clustering to assess how patient and control activity locations differed, and logistic regression to compare location-based exposures. We included 109 tuberculosis patients and 79 controls. In density-based clustering analysis, the two groups had similar patterns of living locations, but their work locations clustered in distinct areas. Both groups were similarly likely to use public transit, but patients predominantly used buses and were less likely to use rapid transit (adjusted odds ratio [aOR] 0.31, 95% confidence interval [CI] 0.10-0.96) or taxis (aOR 0.42, 95% CI 0.21-0.85). Patients were more likely to have spent time in prison (aOR 11.55, 95% CI 1.48-90.13). Placing mobile screening units at bus terminals serving locations where tuberculosis patients have worked and within and around prisons could help reach people with undiagnosed tuberculosis.

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.

Age-specific Clinical Presentation and Risk Factors for Extrapulmonary Tuberculosis Disease in Children.

BACKGROUND: Clinical presentation for extrapulmonary tuberculosis (EPTB) in children can be variable and nonspecific, leading to delayed diagnosis, disease and death. We describe the age-specific clinical presentation and identify risk factors for EPTB among children in Pakistan. METHODS: In 2015-2016 in 4 facilities in Sindh, Pakistan, children were diagnosed with TB either through bacteriologic confirmation or clinical-radiologic criteria. EPTB comprised any form of TB disease that did not involve the lungs. Among children with TB disease, we report demographics, clinical characteristics and symptoms, family medical history and diagnostic test results for children with and without EPTB. We conduct age-specific regression analyses to identify factors associated with an EPTB diagnosis among children age 0-4, 5-9 and 10-14 years. RESULTS: A total of 1163 children were diagnosed with TB disease, of which 157 (13.5%) had EPTB. Of those, 46 (29.3%) were 0-4, 53 (33.8%) were 5-9 and 58 (36.9%) were 10-14 years old. Of children with EPTB, the most frequently reported sites were lymph node (113, 72.4%) and abdominal (31, 19.9%). Weight loss was associated with an increased risk of EPTB in the 0-4-year-old (adjusted odds ratio: 2.80, 95% confidence interval: 1.05-7.47) and 10-14-year-old (adjusted odds ratio: 2.79, 95% confidence interval: 1.28-6.07) groups, and the presence of cough was associated with a decreased risk of EPTB. CONCLUSIONS: This study provides new knowledge about age-specific clinical presentation and risk factors of EPTB in children in Pakistan. Our results can help to optimize clinical algorithms designed to achieve a timely diagnosis in children with EPTB along with improved treatment outcomes.

Geographic accessibility to health facilities predicts uptake of community-based tuberculosis screening in an urban setting.

OBJECTIVES: Annually, more than 30% of individuals with tuberculosis (TB) remain undiagnosed. We aimed to assess whether geographic accessibility measures can identify neighborhoods that would benefit from TB screening services targeted toward closing the diagnosis gap. METHODS: We used data from a community-based mobile TB screening program in Carabayllo district, Lima, Peru. We constructed four accessibility measures from the geographic center of neighborhoods to health facilities. We used logistic regression to assess the association between these measures and screening uptake in one's residential neighborhood versus elsewhere, with quasi-information criterion values to assess the association. RESULTS: We analyzed the screening locations for 25,000 Carabayllo residents from 49 neighborhoods. Pedestrian walk time was preferable to Euclidean distance or vehicular time in our models. For each additional 12 minutes walking time between the neighborhood and the health facility, the odds of residents using TB screening units located in their neighborhoods increased by 50% (95% CI: 26%-78%). Females had 9% (95% CI: 3%-16%) increased odds versus males of using a screening unit in their own neighborhood. CONCLUSION: Placing mobile TB screening units in neighborhoods with longer pedestrian time to access health facilities could benefit individuals who face more acute access barriers to health care.

Mapping local hot spots with routine tuberculosis data: A pragmatic approach to identify spatial variability.

OBJECTIVE: To use routinely collected data, with the addition of geographic information and census data, to identify local hot spots of rates of reported tuberculosis cases. DESIGN: Residential locations of tuberculosis cases identified from eight public health facilities in Lima, Peru (2013-2018) were linked to census data to calculate neighborhood-level annual case rates. Heat maps of tuberculosis case rates by neighborhood were created. Local indicators of spatial autocorrelation, Moran's I, were used to identify where in the study area spatial clusters and outliers of tuberculosis case rates were occurring. Age- and sex-stratified case rates were also assessed. RESULTS: We identified reports of 1,295 TB cases across 74 neighborhoods during the five-year study period, for an average annual rate of 124.2 reported TB cases per 100,000 population. In evaluating case rates by individual neighborhood, we identified a median rate of reported cases of 123.6 and a range from 0 to 800 cases per 100,000 population. Individuals aged 15-44 years old and men had higher case rates than other age groups and women. Locations of both hot and cold spots overlapped across age- and gender-specific maps. CONCLUSIONS: There is significant geographic heterogeneity in rates of reported TB cases and evident hot and cold spots within the study area. Characterization of the spatial distribution of these rates and local hot spots may be one practical tool to inform the work of local coalitions to target TB interventions in their zones.

Age-specific effectiveness of a tuberculosis screening intervention in children.

OBJECTIVE: To apply a cascade-of-care framework to evaluate the effectiveness-by age of the child-of an intensified tuberculosis patient-finding intervention. DESIGN: From a prospective screening program at four hospitals in Pakistan (2014-2016) we constructed a care cascade comprising six steps: screened, positive screen, evaluated, diagnosed, started treatment, and successful outcome. We evaluated the cascade by each year of age from 0 to 14 and report the age-specific mean proportion and standard deviation. RESULTS: On average across all ages, only 12.5% (standard deviation: 2.0%) of children with a positive screen were not evaluated. Among children who had a complete evaluation, the highest percentages of children diagnosed with tuberculosis were observed in children 0-4 (mean: 31.9%; standard deviation: 4.8%), followed by lower percentages in children 5-9 (mean: 22.4%; standard deviation: 2.2%), and 10-14 (mean: 26.0%; standard deviation:5.4%). Nearly all children diagnosed with tuberculosis initiated treatment, and an average of 93.3% (standard deviation: 3.3%) across all ages had successful treatment outcomes. CONCLUSIONS: This intervention was highly effective across ages 0-14 years. Our study illustrates the utility of applying operational analyses of age-stratified cascades to identify age-specific gaps in pediatric tuberculosis care that can guide future, novel interventions to close these gaps.

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.

Feasibility of a school-based mental health program implementation to improve the status of depression and quality of life of mothers of children with autism spectrum disorders in urban Bangladesh: MENTHOL study.

Background: We assessed the feasibility of implementing psychological counseling services (PCS) for mothers of children with autism spectrum disorders (ASD) integrated within special education settings in urban Bangladesh. Method: In two special education schools for ASD in Dhaka City, trained female psychologists screened mothers using the Patient Health Questionnaire (PHQ-9). PCS was administered to all the mothers irrespective of a diagnosis of depression. Mothers with a PHQ-9 score >4 who met criteria for a major depressive episode (MDE) based on the DSM-IV Structured Interview Axis I Disorders (SCID-I) were also administered skill-building training through monthly home visits to support ASD care. The level of depression was assessed by the Depression Measurement Scale (DMS), and quality of life (QoL) was measured by Visual Analogue Scale (VAS) of EQ5D5L scale before and after PCS. Result: Among 188 mothers enrolled in the study, 81 (43%) received PCS, and 27.1% (22) had MDE. In the first month, 73 sessions were scheduled and 60 completed (85%). In the last month, 53 sessions were scheduled and 52 completed (98%). The mean DMS score decreased from 79.5 ± 23 to 60 ± 20 (p = 0.004), and DMS scores were significantly higher among mothers with MDE (97.8 ± 12.1 v. 69.9 ± 22.1; p < 0.001) compared to those without MDE (72.7 ± 22.6 v. 56.1 ± 18.1; p = 0.003). The mean VAS score improved from 70.3 ± 14.1 to 80.2 ± 13.3 (p = 0.001) between the first and the last session. Changes in DMS were negatively correlated with changes in VAS scores (ß: -0.213, 95% CI 0.370 to -0.056). Conclusion: Within special education schools for ASD in urban Bangladesh, it was feasible to administer an integrated program of PCS for mothers of children with ASD by trained psychologists who were able to screen and intervene to reduce their level of depression and improve their quality of life.

Diagnostic value of symptoms for pediatric SARS-CoV-2 infection in a primary care setting.

PURPOSE: To evaluate the diagnostic value of symptoms used by daycares and schools to screen children and adolescents for SARS-CoV-2 infection, we analyzed data from a primary care setting. METHODS: This cohort study included all patients ≤17 years old who were evaluated at Providence Community Health Centers (PCHC; Providence, U.S.), for COVID-19 symptoms and/or exposure, and received SARS-CoV-2 polymerase chain reaction (PCR) testing between March-June 2020. Participants were identified from PCHC electronic medical records. For three age groups- 0-4, 5-11, and 12-17 years-we estimated the sensitivity, specificity, and area under the receiver operating curve (AUC) of individual symptoms and three symptom combinations: a case definition published by the Rhode Island Department of Health (RIDOH), and two novel combinations generated by different statistical approaches to maximize sensitivity, specificity, and AUC. We evaluated symptom combinations both with and without consideration of COVID-19 exposure. Myalgia, headache, sore throat, abdominal pain, nausea, anosmia, and ageusia were not assessed in 0-4 year-olds due to the lower reliability of these symptoms in this group. RESULTS: Of 555 participants, 217 (39.1%) were SARS-CoV-2-infected. Fever was more common among 0-4 years-olds (p = 0.002); older children more frequently reported fatigue (p = 0.02). In children ≥5 years old, anosmia or ageusia had 94-98% specificity. In all ages, exposure history most accurately predicted infection. With respect to individual symptoms, cough most accurately predicted infection in <5 year-olds (AUC 0.69) and 12-17 year-olds (AUC 0.62), while headache was most accurate in 5-11 year-olds (AUC 0.62). In combination with exposure history, the novel symptom combinations generated statistically to maximize test characteristics had sensitivity >95% but specificity <30%. No symptom or symptom combination had AUC ≥0.70. CONCLUSIONS: Anosmia or ageusia in children ≥5 years old should raise providers' index of suspicion for COVID-19. However, our overall findings underscore the limited diagnostic value of symptoms.

The Impact of Tuberculosis on the Well-Being of Adolescents and Young Adults.

The health needs of adolescents and young adults (AYAs) have been neglected in tuberculosis (TB) care, control, and research. AYAs, who are distinct from younger children and older adults, undergo dynamic physical, psychological, emotional, cognitive, and social development. Five domains of adolescent well-being are crucial to a successful transition between childhood and adulthood: (1) Good health; (2) connectedness and contribution to society; (3) safety and a supportive environment; (4) learning, competence, education, skills, and employability; and (5) agency and resilience. This review summarizes the evidence of the impact of TB disease and treatment on these five domains of AYA well-being.

Prediction Tool to Identify Children at Highest Risk of Tuberculosis Disease Progression Among Those Exposed at Home.

BACKGROUND: There is a dearth of research to understand which children, among those who are exposed at home to tuberculosis (TB), are at the highest risk of TB disease, to tailor care. We sought to identify predictors of TB progression in children. METHODS: We conducted a prospective cohort study of children living with adults with pulmonary TB in Lima, Peru (2009-2012). We applied classification and regression tree analysis to examine potential predictors of incident TB disease during 12 months in 3 age groups (0-4, 5-9, and 10-14 years). We calculated the relative risk (RR) for top predictors in each age group. RESULTS: Among 4545 children 0-14 years old, 156 (3.4%) were diagnosed with TB within 1 year of household exposure to TB (3.4%, 2.3%, and 4.7% in children 0-4, 5-9, and 10-14 years old, respectively). The most important predictor of TB was having a positive tuberculin skin test (TST) result, with RRs of 6.6 (95% CI, 4.0-10.7), 6.6 (95% CI, 3.2-13.6), and 5.2 (95% CI, 3.0-9.0) in the age groups 0-4, 5-9, and 10-14 years, respectively. In young children with a positive TST, not using isoniazid preventive treatment further increased risk of disease (RR, 12.2 [95% CI, 3.8-39.2]). CONCLUSIONS: We present a tool that identifies child household contacts at high risk of TB disease progression based on data collected during contact tracing. In addition to the use of TB preventive therapy for all children exposed at home to TB, those children at highest risk of progressing to TB disease may benefit from more frequent follow-up.

Identifying barriers and facilitators to implementation of community-based tuberculosis active case finding with mobile X-ray units in Lima, Peru: a RE-AIM evaluation.

OBJECTIVES: Identify barriers and facilitators to integrating community tuberculosis screening with mobile X-ray units into a health system. METHODS: Reach, effectiveness, adoption, implementation and maintenance evaluation. SETTING: 3-district region of Lima, Peru. PARTICIPANTS: 63 899 people attended the mobile units from 7 February 2019 to 6 February 2020. INTERVENTIONS: Participants were screened by chest radiography, which was scored for abnormality by computer-aided detection. People with abnormal X-rays were evaluated clinically and by GeneXpert MTB/RIF (Xpert) sputum testing. People diagnosed with tuberculosis at the mobile unit were accompanied to health facilities for treatment initiation. PRIMARY AND SECONDARY OUTCOME MEASURES: Reach was defined as the percentage of the population of the three-district region that attended the mobile units. Effectiveness was defined as the change in tuberculosis case notifications over a historical baseline. Key implementation fidelity indicators were the percentages of people who had chest radiography performed, were evaluated clinically, had sputum samples collected, had valid Xpert results and initiated treatment. RESULTS: The intervention reached 6% of the target population and was associated with an 11% (95% CI 6 to 16) increase in quarterly case notifications, adjusting for the increasing trend in notifications over the previous 3 years. Implementation indicators for screening, sputum collection and Xpert testing procedures all exceeded 85%. Only 82% of people diagnosed with tuberculosis at the mobile units received treatment; people with negative or trace Xpert results were less likely to receive treatment. Suboptimal treatment initiation was driven by health facility doctors' lack of familiarity with Xpert and lack of confidence in diagnoses made at the mobile unit. CONCLUSION: Mobile X-ray units were a feasible and effective strategy to extend tuberculosis diagnostic services into communities and improve early case detection. Effective deployment however requires advance coordination among stakeholders and targeted provider training to ensure that people diagnosed with tuberculosis by new modalities receive prompt treatment.