Optimizing diagnostic networks to increase patient access to TB diagnostic services: Development of the diagnostic network optimization (DNO) approach and learnings from its application in Kenya, India and the Philippines.

Diagnostic network optimization (DNO) is an analytical approach that enables use of available country data to inform evidence-based decision-making to optimize access to diagnostic services. A DNO methodology was developed using available data sources and a commercial supply chain optimization software. In collaboration with Ministries of Health and partners, the approach was applied in Kenya, India and the Philippines to map TB diagnostic networks, identify misalignments, and determine optimal network design to increase patient access to TB diagnostic services and improve device utilization. The DNO analysis was successfully applied to evaluate and inform TB diagnostic services in Kenya, India and the Philippines as part of national strategic planning for TB. The analysis was tailored to each country's specific objectives and allowed evaluation of factors such as the number and placement of different TB diagnostics, design of sample referral networks and integration of early infant diagnosis for HIV at national and sub-national levels and across public and private sectors. Our work demonstrates the value of DNO as an innovative approach to analysing and modelling diagnostic networks, particularly suited for use in low-resource settings, as an open-access approach that can be applied to optimize networks for any disease.

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

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

Closing the loop in child TB contact management: completion of TB preventive therapy outcomes in western Kenya.

SETTING: Children especially those <5 years of age exposed to pulmonary tuberculosis (TB) are at a high risk of severe TB disease and death. Isoniazid preventive therapy (IPT) has been shown to decrease disease progression by up to 90%. Kenya, a high TB burden country experiences numerous operational challenges that limit implementation of TB preventive services. IPT completion in child contacts is not routinely reported in Kenya. OBJECTIVE: This study aims to review the child contact management (CCM) cascade and present IPT outcomes across 10 clinics in western Kenya. DESIGN: A retrospective chart review of programmatic data of a TB Reach-funded active, clinic-based CCM strategy. RESULTS: Of 553 child contacts screened, 231 (42%) were reported symptomatic. 74 (13%) of the child contacts were diagnosed with active TB disease. Of those eligible for IPT, 427 (90%) initiated IPT according to TB REACH project data while 249 (58%) were recorded in the IPT register with 49 (11%) recorded as a transfer to other facilities. Of the 249 recorded in the IPT register, 205 (82%) were documented to complete therapy (48% of project initiation children). CONCLUSION: Our evaluation shows gaps in the routine CCM care cascade related to completeness of documentation that require further programmatic monitoring and evaluation to improve CCM outcomes.

'If not TB, what could it be?' Chest X-ray findings from the 2016 Kenya Tuberculosis Prevalence Survey.

BACKGROUND: The prevalence of diseases other than TB detected during chest X-ray (CXR) screening is unknown in sub-Saharan Africa. This represents a missed opportunity for identification and treatment of potentially significant disease. Our aim was to describe and quantify non-TB abnormalities identified by TB-focused CXR screening during the 2016 Kenya National TB Prevalence Survey. METHODS: We reviewed a random sample of 1140 adult (≥15 years) CXRs classified as 'abnormal, suggestive of TB' or 'abnormal other' during field interpretation from the TB prevalence survey. Each image was read (blinded to field classification and study radiologist read) by two expert radiologists, with images classified into one of four major anatomical categories and primary radiological findings. A third reader resolved discrepancies. Prevalence and 95% CIs of abnormalities diagnosis were estimated. FINDINGS: Cardiomegaly was the most common non-TB abnormality at 259 out of 1123 (23.1%, 95% CI 20.6% to 25.6%), while cardiomegaly with features of cardiac failure occurred in 17 out of 1123 (1.5%, 95% CI 0.9% to 2.4%). We also identified chronic pulmonary pathology including suspected COPD in 3.2% (95% CI 2.3% to 4.4%) and non-specific patterns in 4.6% (95% CI 3.5% to 6.0%). Prevalence of active-TB and severe post-TB lung changes was 3.6% (95% CI 2.6% to 4.8%) and 1.4% (95% CI 0.8% to 2.3%), respectively. INTERPRETATION: Based on radiological findings, we identified a wide variety of non-TB abnormalities during population-based TB screening. TB prevalence surveys and active case finding activities using mass CXR offer an opportunity to integrate disease screening efforts. FUNDING: National Institute for Health Research (IMPALA-grant reference 16/136/35).

Gender difference in mortality among pulmonary tuberculosis HIV co-infected adults aged 15-49 years in Kenya.

SETTING: Kenya, 2012-2015. OBJECTIVE: To explore whether there is a gender difference in all-cause mortality among smear positive pulmonary tuberculosis (PTB)/ HIV co-infected patients treated for tuberculosis (TB) between 2012 and 2015 in Kenya. DESIGN: Retrospective cohort of 9,026 smear-positive patients aged 15-49 years. All-cause mortality during TB treatment was the outcome of interest. Time to start of antiretroviral therapy (ART) initiation was considered as a proxy for CD4 cell count. Those who took long to start of ART were assumed to have high CD4 cell count. RESULTS: Of the 9,026 observations analysed, 4,567(51%) and 4,459(49%) were women and men, respectively. Overall, out of the 9,026 patients, 8,154 (90%) had their treatment outcome as cured, the mean age in years (SD) was 33.3(7.5) and the mean body mass index (SD) was 18.2(3.4). Men were older (30% men' vs 17% women in those ≥40 years, p = <0.001) and had a lower BMI <18.5 (55.3% men vs 50.6% women, p = <0.001). Men tested later for HIV: 29% (1,317/4,567) of women HIV tested more than 3 months prior to TB treatment, as compared to 20% (912/4,459) men (p<0.001). Mortality was higher in men 11% (471/4,459) compared to women 9% (401/4,567, p = 0.004). There was a 17% reduction in the risk of death among women (adjusted HR 0.83; 95% CI 0.72-0.96; p = 0.013). Survival varied by age-groups, with women having significantly better survival than men, in the age-groups 40 years and over (log-rank p = 0.006). CONCLUSION: Women with sputum positive PTB/HIV co-infection have a significantly lower risk of all-cause mortality during TB treatment compared to men. Men were older, had lower BMI and tested later for HIV than women.

Outcomes of isoniazid preventive therapy among people living with HIV in Kenya: A retrospective study of routine health care data.

INTRODUCTION: Isoniazid preventive therapy (IPT) taken by People Living with HIV (PLHIV) protects against active tuberculosis (TB). Despite its recommendation, data is scarce on the uptake of IPT among PLHIV and factors associated with treatment outcomes. We aimed at determining the proportion of PLHIV initiated on IPT, assessed TB screening practices during and after IPT and IPT treatment outcomes. METHODS: A retrospective cohort study of a representative sample of PLHIV initiated on IPT between July 2015 and June 2018 in Kenya. For PLHIV initiated on IPT during the study period, we abstracted patient IPT uptake data from the National data warehouse. In contrast, we obtained information on socio-demographic, TB screening practices, IPT initiation, follow up, and outcomes from health facilities' patient record cards, IPT cards, and IPT registers. Further, we assessed baseline characteristics as potential correlates of developing active TB during and after treatment and IPT completion using multivariable logistic regression. RESULTS: From the data warehouse, 138,442 PLHIV were enrolled into ART during the study period and initiated 95,431 (68.9%) into IPT. We abstracted 4708 patients' files initiated on IPT, out of which 3891(82.6%) had IPT treatment outcomes documented, 4356(92.5%) had ever screened for TB at every clinic visit, and 4,243(90.1%) had documentation of TB screening on the IPT tool before IPT initiation. 3712(95.4%) of patients with documented IPT treatment outcomes completed their treatment. 42(0.89%) of the abstracted patients developed active TB,16(38.1%) during, and 26(61.9%) after completing IPT. Follow up for active TB at 6-month post-IPT completion was done for 2729(73.5%) of patients with IPT treatment outcomes. Sex, Viral load suppression, and clinic type were associated with TB development (p<0.05). Levels 4, 5, FBO, and private facilities and IPT prescription practices were associated with IPT completion (p<0.05). CONCLUSION: IPT initiation stands at two-thirds of the PLHIV, with a high completion rate. TB screening practices were better during IPT than after completion. Development of active TB during and after IPT emphasizes the need for a keen follow up.

The potential impact of the COVID-19 pandemic on the tuberculosis epidemic a modelling analysis.

BACKGROUND: Routine services for tuberculosis (TB) are being disrupted by stringent lockdowns against the novel SARS-CoV-2 virus. We sought to estimate the potential long-term epidemiological impact of such disruptions on TB burden in high-burden countries, and how this negative impact could be mitigated. METHODS: We adapted mathematical models of TB transmission in three high-burden countries (India, Kenya and Ukraine) to incorporate lockdown-associated disruptions in the TB care cascade. The anticipated level of disruption reflected consensus from a rapid expert consultation. We modelled the impact of these disruptions on TB incidence and mortality over the next five years, and also considered potential interventions to curtail this impact. FINDINGS: Even temporary disruptions can cause long-term increases in TB incidence and mortality. If lockdown-related disruptions cause a temporary 50% reduction in TB transmission, we estimated that a 3-month suspension of TB services, followed by 10 months to restore to normal, would cause, over the next 5 years, an additional 1⋅19 million TB cases (Crl 1⋅06-1⋅33) and 361,000 TB deaths (CrI 333-394 thousand) in India, 24,700 (16,100-44,700) TB cases and 12,500 deaths (8.8-17.8 thousand) in Kenya, and 4,350 (826-6,540) cases and 1,340 deaths (815-1,980) in Ukraine. The principal driver of these adverse impacts is the accumulation of undetected TB during a lockdown. We demonstrate how long term increases in TB burden could be averted in the short term through supplementary "catch-up" TB case detection and treatment, once restrictions are eased. INTERPRETATION: Lockdown-related disruptions can cause long-lasting increases in TB burden, but these negative effects can be mitigated with rapid restoration of TB services, and targeted interventions that are implemented as soon as restrictions are lifted. FUNDING: USAID and Stop TB Partnership.

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.

The spatial epidemiology of leprosy in Kenya: A retrospective study.

BACKGROUND: Leprosy elimination defined as a registered prevalence rate of less than 1 case per 10,000 persons was achieved in Kenya at the national level in 1989. However, there are still pockets of leprosy in some counties where late diagnosis and consequent physical disability persist. The epidemiology of leprosy in Kenya for the period 2012 through to 2015 was defined using spatial methods. METHODS: This was a retrospective ecological correlational study that utilized leprosy case based data extracted from the National Leprosy Control Program database. Geographic information system and demographic data were obtained from Kenya National Bureau of Statistics (KNBS). Chi square tests were carried out to check for association between sociodemographic factors and disease indicators. Two Spatial Poisson Conditional Autoregressive (CAR) models were fitted in WinBUGS 1.4 software. The first model included all leprosy cases (new, retreatment, transfers from another health facility) and the second one included only new leprosy cases. These models were used to estimate leprosy relative risks per county as compared to the whole country i.e. the risk of presenting with leprosy given the geographical location. PRINCIPAL FINDINGS: Children aged less than 15 years accounted for 7.5% of all leprosy cases indicating active leprosy transmission in Kenya. The risk of leprosy notification increased by about 5% for every 1 year increase in age, whereas a 1% increase in the proportion of MB cases increased the chances of new leprosy case notification by 4%. When compared to the whole country, counties with the highest risk of leprosy include Kwale (relative risk of 15), Kilifi (RR;8.9) and Homabay (RR;4.1), whereas Turkana had the lowest relative risk of 0.005. CONCLUSION: Leprosy incidence exhibits geographical variation and there is need to institute tailored local control measures in these areas to reduce the burden of disability.

Assessing tuberculosis control priorities in high-burden settings: a modelling approach.

BACKGROUND: In the context of WHO's End TB strategy, there is a need to focus future control efforts on those interventions and innovations that would be most effective in accelerating declines in tuberculosis burden. Using a modelling approach to link the tuberculosis care cascade to transmission, we aimed to identify which improvements in the cascade would yield the greatest effect on incidence and mortality. METHODS: We engaged with national tuberculosis programmes in three country settings (India, Kenya, and Moldova) as illustrative examples of settings with a large private sector (India), a high HIV burden (Kenya), and a high burden of multidrug resistance (Moldova). We collated WHO country burden estimates, routine surveillance data, and tuberculosis prevalence surveys from 2011 (for India) and 2016 (for Kenya). Linking the tuberculosis care cascade to tuberculosis transmission using a mathematical model with Bayesian melding in each setting, we examined which cascade shortfalls would have the greatest effect on incidence and mortality, and how the cascade could be used to monitor future control efforts. FINDINGS: Modelling suggests that combined measures to strengthen the care cascade could reduce cumulative tuberculosis incidence by 38% (95% Bayesian credible intervals 27-43) in India, 31% (25-41) in Kenya, and 27% (17-41) in Moldova between 2018 and 2035. For both incidence and mortality, modelling suggests that the most important cascade losses are the proportion of patients visiting the private health-care sector in India, missed diagnosis in health-care settings in Kenya, and drug sensitivity testing in Moldova. In all settings, the most influential delay is the interval before a patient's first presentation for care. In future interventions, the proportion of individuals with tuberculosis who are on high-quality treatment could offer a more robust monitoring tool than routine notifications of tuberculosis. INTERPRETATION: Linked to transmission, the care cascade can be valuable, not only for improving patient outcomes but also in identifying and monitoring programmatic priorities to reduce tuberculosis incidence and mortality. FUNDING: US Agency for International Development, Stop TB Partnership, UK Medical Research Council, and Department for International Development.

Epidemiology of Pediatric Tuberculosis in Kenya and Risk Factors for Mortality during Treatment: A National Retrospective Cohort Study.

OBJECTIVES: To describe the epidemiology of childhood tuberculosis (TB) in Kenya, assess the magnitude of TB/human immunodeficiency virus (HIV) co-infection and identify risk factors for mortality during TB treatment. STUDY DESIGN: We conducted a retrospective analysis of the Kenyan national TB program data for patients enrolled from 2013 through 2015. A total of 23 753 children aged less than 15 years were included in the analysis. Survival analysis was performed with censorship at 9 months and mortality was the main outcome. We used Cox proportional hazards regression for assessing risk factors for mortality. RESULTS: Childhood TB accounted for 9% (n = 24 216) of all patients with TB; 98% of the notified children (n = 23 753) were included in the analysis. TB/HIV co-infection was 28% (n = 6112). Most TB cases (71%; n = 16 969) were detected through self-referral. Treatment was successful in 90% (n = 19 088) and 4% (n = 1058) died. Independent risk factors for mortality included being HIV infected but not on antiretroviral therapy (adjusted hazard ratio [aHR], 4.84; 95% CI, 3.59-6.51), being HIV infected and on antiretroviral therapy (aHR, 3.69; 95% CI, 3.14-4.35), children aged less than 5 years (aHR, 1.25; 95% CI, 1.08-1.44), and being diagnosed with smear negative pulmonary disease (aHR, 1.68; 95% CI, 1.27-2.24). CONCLUSIONS: Most childhood TB cases in Kenya were detected through passive case finding. TB/HIV co-infection is high among children on treatment for TB, and HIV is associated with an increased risk of death. There is a need to intensify active case finding among children. TB prevention interventions among HIV-infected children, early diagnosis of HIV, and early antiretroviral therapy initiation among children on TB treatment should be strengthened.

Using Patient-Pathway Analysis to Inform a Differentiated Program Response to Tuberculosis: The Case of Kenya.

Background: A recent tuberculosis prevalence survey in Kenya found that the country is home to nearly twice as many patients with tuberculosis as previously estimated. Kenya has prioritized identifying and treating the unnotified or missing cases of tuberculosis. This requires a better understanding of patient care seeking and system weaknesses. Methods: A patient-pathway analysis (PPA) was completed to assess the alignment between patient care seeking and the availability of tuberculosis diagnostic and treatment services at the national level and for all 47 counties at the subnational level in Kenya. Results: It was estimated that more than half of patients initiate care in the public sector. Nationally, just under half of patients encountered tuberculosis diagnostic and treatment capacity where they initiated care. Overall, there was distinct variation in diagnostic and treatment availability across counties and facility levels. Discussion: The PPA results emphasized the need for a differentiated approach to tuberculosis care, by county, and the distinct need for better referral systems. The majority of Kenyans actively sought care; improving diagnostic and treatment capacity in the formal and informal private sector, as well as in the public sector, could help identify the majority of missing cases.

Reduction of HIV-associated excess mortality by antiretroviral treatment among tuberculosis patients in Kenya.

BACKGROUND: Mortality from TB continues to be a global public health challenge. TB ranks alongside Human Immunodeficiency Virus (HIV) as the leading infectious causes of death globally. HIV is a major driver of TB related morbidity and mortality while TB is the leading cause of mortality among people living with HIV/AIDS. We sought to determine excess mortality associated with HIV and the effect of antiretroviral therapy on reducing mortality among tuberculosis patients in Kenya. METHODS: We conducted a retrospective analysis of Kenya national tuberculosis program data of patients enrolled from 2013 through 2014. We used direct standardization to obtain standardized mortality ratios for tuberculosis patients compared with the general population. We calculated the population attributable fraction of tuberculosis deaths due to HIV based on the standardized mortality ratio for deaths among TB patients with HIV compared to TB patients without HIV. We used Cox proportional hazards regression for assessing risk factors for mortality. RESULTS: Of 162,014 patients included in the analysis, 6% died. Mortality was 10.6 (95% CI: 10.4-10.8) times higher among TB patients than the general population; 42% of deaths were attributable to HIV infection. Patients with HIV who were not receiving ART had an over four-fold risk of death compared to patients without HIV (aHR = 4.2, 95% CI 3.9-4.6). In contrast, patients with HIV who were receiving ART had only 2.6 times the risk of death (aHR = 2.6, 95% CI 2.5-2.7). CONCLUSION: HIV was a significant contributor to TB-associated deaths in Kenya. Mortality among HIV-infected individuals was higher among those not on ART than those on ART. Early initiation of ART among HIV infected people (a "test and treat" approach) should further reduce TB-associated deaths.

Using Survival Analysis to Identify Risk Factors for Treatment Interruption among New and Retreatment Tuberculosis Patients in Kenya.

Despite high tuberculosis (TB) treatment success rate, treatment adherence is one of the major obstacles to tuberculosis control in Kenya. Our objective was to identify patient-related factors that were associated with time to TB treatment interruption and the geographic distribution of the risk of treatment interruption by county. Data of new and retreatment patients registered in TIBU, a Kenyan national case-based electronic data recording system, between 2013 and 2014 was obtained. Kaplan-Meier curves and log rank tests were used to assess the adherence patterns. Mixed-effects Cox proportional hazards modeling was used for multivariate analysis. Records from 90,170 patients were included in the study. The cumulative incidence of treatment interruption was 4.5% for new patients, and 8.5% for retreatment patients. The risk of treatment interruption was highest during the intensive phase of treatment. Having previously been lost to follow-up was the greatest independent risk factor for treatment interruption (HR: 4.79 [3.99, 5.75]), followed by being HIV-positive not on ART (HR: 1.96 [1.70, 2.26]) and TB relapse (HR: 1.70 [1.44, 2.00]). Male and underweight patients had high risks of treatment interruption (HR: 1.46 [1.35, 1.58]; 1.11 [1.03, 1.20], respectively). High rates of treatment interruption were observed in counties in the central part of Kenya while counties in the northeast had the lowest risk of treatment interruption. A better understanding of treatment interruption risk factors is necessary to improve adherence to treatment. Interventions should focus on patients during the intensive phase, patients who have previously been lost to follow-up, and promotion of integrated TB and HIV services among public and private facilities.