Identifying dynamic tuberculosis case-finding policies for HIV/TB coepidemics.
ABSTRACT: The global tuberculosis (TB) control plan has historically emphasized passive case finding (PCF) as the most practical approach for identifying TB suspects in high burden settings. The success of this approach in controlling TB depends on infectious individuals recognizing their symptoms and voluntarily seeking diagnosis rapidly enough to reduce onward transmission. It now appears, at least in some settings, that more intensified case-finding (ICF) approaches may be needed to control TB transmission; these more aggressive approaches for detecting as-yet undiagnosed cases obviously require additional resources to implement. Given that TB control programs are resource constrained and that the incremental yield of ICF is expected to wane over time as the pool of undiagnosed cases is depleted, a tool that can help policymakers to identify when to implement or suspend an ICF intervention would be valuable. In this article, we propose dynamic case-finding policies that allow policymakers to use existing observations about the epidemic and resource availability to determine when to switch between PCF and ICF to efficiently use resources to optimize population health. Using mathematical models of TB/HIV coepidemics, we show that dynamic policies strictly dominate static policies that prespecify a frequency and duration of rounds of ICF. We also find that the use of a diagnostic tool with better sensitivity for detecting smear-negative cases (e.g., Xpert MTB/RIF) further improves the incremental benefit of these dynamic case-finding policies.
Project description:INTRODUCTION:Case detection by passive case finding (PCF) strategy alone is inadequate for detecting all tuberculosis (TB) cases in high burden settings especially Sub-Saharan Africa. Alternative case detection strategies such as community Active Case Finding (ACF) and Household Contact Investigations (HCI) are effective but empirical evidence of their cost-effectiveness is sparse. The objective of this study was to determine whether adding ACF or HCI compared with standard PCF alone represent cost-effective alternative TB case detection strategies in urban Africa. METHODS:A static decision modeling framework was used to examine the costs and effectiveness of three TB case detection strategies: PCF alone, PCF+ACF, and PCF+HCI. Probability and cost estimates were obtained from National TB program data, primary studies conducted in Uganda, published literature and expert opinions. The analysis was performed from the societal and provider perspectives over a 1.5 year time-frame. The main effectiveness measure was the number of true TB cases detected and the outcome was incremental cost-effectiveness ratios (ICERs) expressed as cost in 2013 US$ per additional true TB case detected. RESULTS:Compared to PCF alone, the PCF+HCI strategy was cost-effective at US$443.62 per additional TB case detected. However, PCF+ACF was not cost-effective at US$1492.95 per additional TB case detected. Sensitivity analyses showed that PCF+ACF would be cost-effective if the prevalence of chronic cough in the population screened by ACF increased 10-fold from 4% to 40% and if the program costs for ACF were reduced by 50%. CONCLUSIONS:Under our baseline assumptions, the addition of HCI to an existing PCF program presented a more cost-effective strategy than the addition of ACF in the context of an African city. Therefore, implementation of household contact investigations as a part of the recommended TB control strategy should be prioritized.
Project description:BACKGROUND:Cambodia has made notable progress in the fight against tuberculosis (TB). However, these gains are impeded by a significant proportion of undiagnosed cases. To effectively reach people with TB, active case-finding (ACF) strategies have been adopted by countries affected by the epidemic, including Cambodia, alongside passive case finding (PCF). Despite increased efforts to improve case detection, approximately 40% of TB cases in Cambodia remained undiagnosed in 2018. In Cambodia, several community-based TB ACF modalities have been implemented, but their effectiveness has yet to be systematically assessed. METHODS:This pragmatic cluster randomized controlled trial will be conducted between December 2019 and June 2021. We will randomize eight operational districts (clusters) in seven provinces (Kampong Cham, Kampong Thom, Prey Veng, Thbong Khmum, Kampong Chhnang, Kandal, and Kampong Speu) to either the control group (PCF) or the intervention groups (ACF using a seed-and-recruit model, ACF targeting household and neighborhood contacts, and ACF targeting persons aged ??55 years using mobile screening units). The primary endpoints will be TB case notification rates, additionality, and cumulative yield of TB cases. The secondary endpoints include treatment outcomes, the number needed to screen to find one TB case, and cost-effectiveness outcome measures. We will analyze the primary and secondary endpoints by intention to treat. We will compare cluster and individual-level characteristics using Student's t test and hierarchical or mixed-effect models to estimate the ratio of these means. The incremental cost-effectiveness ratio per disability-adjusted life year averted will also be considered as a benchmark to determine whether the interventions are cost-effective. DISCUSSION:This study will build an evidence base to inform future scale-up, implementation, and sustainability of ACF strategies in Cambodia and other similar settings. Implementation of this study will also complement TB control strategies in Cambodia by conducting ACF in operational districts without active interventions to find TB cases currently. Those who are ill and might have TB will be promptly screened, diagnosed, and linked to care. Early diagnosis and treatment initiation will also benefit their community by interrupting transmission and prevent further infections. The experience gained from this project will inform future attempts in conducting pragmatic trials in low-resource settings. TRIAL REGISTRATION:ClinicalTrials.gov, NCT04094350. Registered on 18 September 2019.
Project description:INTRODUCTION:Resource constraints in Low and Middle-Income Countries (LMICs) limit tuberculosis (TB) contact investigation despite evidence its benefits could outweigh costs, with increased efficiency when compared with intensified case finding (ICF). However, there is limited data on yield and cost per TB case identified. We compared yield and cost per TB case identified for ICF and Tuberculosis-Contact Investigation (TB-CI) in Uganda. METHODS:A retrospective cohort study based on data from 12 Ugandan hospitals was done between April and September 2017. Two methods of TB case finding (i.e. ICF and TB-CI) were compared. Regarding ICF, patients either self-reported their signs and symptoms or were prompted by health care workers, while TB-CI was done by home-visiting and screening contacts of TB patients. Patients who were presumed to have tuberculosis were requested to produce a sample for examination. TB yield was defined as a ratio of diagnoses to tests, and this was computed per method of diagnosis. The cost per TB case identified (medical, personnel, transportation and training) for each diagnosis method were computed using the activity-based approach, from the health care perspective. Cost data were analyzed using Windows Excel. RESULTS:454 index TB cases and 2,707 of their household contacts were investigated. Thirty-one per cent of contacts (840/2707) were found to be presumptive TB cases. A total of 7,685 tests were done, 6,967 for ICF and 718 for TB-CI. The yields were 18.62% (1297/6967) and 5.29% (38/718) for ICF and TB-CI, respectively. It cost US$ 120.60 to diagnose a case of TB using ICF compared to US$ 877.57 for TB-CI. CONCLUSION:The yield of TB-CI was found to be four-times lower and seven-times costlier compared to ICF. These findings suggest that ICF can improve TB case detection at a low cost, particularly in high TB prevalent settings.
Project description:There is limited evidence on whether active case finding (ACF) among marginalised and vulnerable populations mitigates the financial burden during tuberculosis (TB) diagnosis.To determine the effect of ACF among marginalised and vulnerable populations on prevalence and inequity of catastrophic costs due to TB diagnosis among TB-affected households when compared with passive case finding (PCF).In 18 randomly sampled ACF districts in India, during March 2016 to February 2017, we enrolled all new sputum-smear-positive TB patients detected through ACF and an equal number of randomly selected patients detected through PCF. Direct (medical and non-medical) and indirect costs due to TB diagnosis were collected through patient interviews at their residence. We defined costs due to TB diagnosis as 'catastrophic' if the total costs (direct and indirect) due to TB diagnosis exceeded 20% of annual pre-TB household income. We used concentration curves and indices to assess the extent of inequity.When compared with patients detected through PCF (n = 231), ACF patients (n = 234) incurred lower median total costs (US$ 4.6 and 20.4, p < 0.001). The prevalence of catastrophic costs in ACF and PCF was 10.3 and 11.5% respectively. Adjusted analysis showed that patients detected through ACF had a 32% lower prevalence of catastrophic costs relative to PCF [adjusted prevalence ratio (95% CI): 0.68 (0.69, 0.97)]. The concentration indices (95% CI) for total costs in both ACF [-0.15 (-0.32, 0.11)] and PCF [-0.06 (-0.20, 0.08)] were not significantly different from the line of equality and each other. The concentration indices (95% CI) for catastrophic costs in both ACF [-0.60 (-0.81, -0.39)] and PCF [-0.58 (-0.78, -0.38)] were not significantly different from each other: however, both the curves had a significant distribution among the poorest quintiles.ACF among marginalised and vulnerable populations reduced total costs and prevalence of catastrophic costs due to TB diagnosis, but could not address inequity.
Project description:BACKGROUND:The World Health Organization (WHO) End TB Strategy has established a milestone to reduce the number of tuberculosis (TB)- affected households facing catastrophic costs to zero by 2020. The role of active case finding (ACF) in reducing patient costs has not been determined globally. This study therefore aimed to compare costs incurred by TB patients diagnosed through ACF and passive case finding (PCF), and to determine the prevalence and intensity of patient-incurred catastrophic costs in Nepal. METHODS:The study was conducted in two districts of Nepal: Bardiya and Pyuthan (Province No. 5) between June and August 2018. One hundred patients were included in this study in a 1:1 ratio (PCF: ACF, 25 consecutive ACF and 25 consecutive PCF patients in each district). The WHO TB patient costing tool was applied to collect information from patients or a member of their family regarding indirect and direct medical and non-medical costs. Catastrophic costs were calculated based on the proportion of patients with total costs exceeding 20% of their annual household income. The intensity of catastrophic costs was calculated using the positive overshoot method. The chi-square and Wilcoxon-Mann-Whitney tests were used to compare proportions and costs. Meanwhile, the Mantel Haenszel test was performed to assess the association between catastrophic costs and type of diagnosis. RESULTS:Ninety-nine patients were interviewed (50 ACF and 49 PCF). Patients diagnosed through ACF incurred lower costs during the pre-treatment period (direct medical: USD 14 vs USD 32, P =?0.001; direct non-medical: USD 3 vs USD 10, P =?0.004; indirect, time loss: USD 4 vs USD 13, P <? 0.001). The cost of the pre-treatment and intensive phases combined was also lower for direct medical (USD 15 vs USD 34, P =?0.002) and non-medical (USD 30 vs USD 54, P =?0.022) costs among ACF patients. The prevalence of catastrophic direct costs was lower for ACF patients for all thresholds. A lower intensity of catastrophic costs was also documented for ACF patients, although the difference was not statistically significant. CONCLUSIONS:ACF can reduce patient-incurred costs substantially, contributing to the End TB Strategy target. Other synergistic policies, such as social protection, will also need to be implemented to reduce catastrophic costs to zero among TB-affected households.
Project description:BACKGROUND:Despite free TB services available in public health facilities, TB patients often face severe financial burden due to TB. WHO set a new global target that no TB-affected families experience catastrophic costs due to TB. To monitor the progress and strategize the optimal approach to achieve the target, there is a great need to assess baseline cost data, explore potential proxy indicators for catastrophic costs, and understand what intervention mitigates financial burden. In Cambodia, nationwide active case finding (ACF) targeting household and neighbourhood contacts was implemented alongside routine passive case finding (PCF). We analyzed household cost data from ACF and PCF to determine the financial benefit of ACF, update the baseline cost data, and explore whether any dissaving patterns can be a proxy for catastrophic costs in Cambodia. METHODS:In this cross-sectional comparative study, structured interviews were carried out with 108 ACF patients and 100 PCF patients. Direct and indirect costs, costs before and during treatment, costs as percentage of annual household income and dissaving patterns were compared between the two groups. RESULTS:The median total costs were lower by 17% in ACF than in PCF ($240.7 [IQR 65.5-594.6] vs $290.5 [IQR 113.6-813.4], p = 0.104). The median costs before treatment were significantly lower in ACF than in PCF ($5.1 [IQR 1.5-25.8] vs $22.4 [IQR 4.4-70.8], p<0.001). Indirect costs constituted the largest portion of total costs (72.3% in ACF and 61.5% in PCF). Total costs were equivalent to 11.3% and 18.6% of annual household income in ACF and PCF, respectively. ACF patients were less likely to dissave to afford TB-related expenses. Costs as percentage of annual household income were significantly associated with an occurrence of selling property (p = 0.02 for ACF, p = 0.005 for PCF). CONCLUSIONS:TB-affected households face severe financial hardship in Cambodia. ACF has the great potential to mitigate the costs incurred particularly before treatment. Social protection schemes that can replace lost income are critically needed to compensate for the most devastating costs in TB. An occurrence of selling household property can be a useful proxy for catastrophic cost in Cambodia.
Project description:BACKGROUND:The barriers to access diagnosis and receive treatment, in addition to insufficient case identification and reporting, lead to tuberculosis (TB) spreads in communities, especially among hard-to-reach populations. This study evaluated a community-based active case finding (ACF) strategy for the detection of tuberculosis cases among high-risk groups and general population in China between 2013 and 2015. METHODS:This retrospective cohort study conducted an ACF in ten communities of Dongchuan County, located in northeast Yunnan Province between 2013 and 2015; and compared to 136 communities that had passive case finding (PCF). The algorithm for ACF was: 1) screen for TB symptoms among community enrolled residents by home visits, 2) those with positive symptoms along with defined high-risk groups underwent chest X-ray (CXR), followed by sputum microscopy confirmation. TB incidence proportion and the number needed to screen (NNS) to detect one case were calculated to evaluate the ACF strategy compared to PCF, chi-square test was applied to compare the incidence proportion of TB cases' demography and the characteristics for detected cases under different strategies. Thereafter, the incidence rate ratio (IRR) and multiple Fisher's exact test were applied to compare the incidence proportion between general population and high-risk groups. Patient and diagnostic delays for ACF and PCF were compared by Wilcoxon rank sum test. RESULTS:A total of 97 521 enrolled residents were visited with the ACF cumulatively, 12.3% were defined as high-risk groups or had TB symptoms. Sixty-six new TB patients were detected by ACF. There was no significant difference between the cumulative TB incidence proportion for ACF (67.7/100000 population) and the prevalence for PCF (62.6/100000 population) during 2013 to 2015, though the incidence proportion in ACF communities decreased after three rounds active screening, concurrent with the remained stable prevalence in PCF communities. The cumulative NNS were 34, 39 and 29 in HIV/AIDS infected individuals, people with positive TB symptoms and history of previous TB, respectively, compared to 1478 in the general population. The median patient delay under ACF was 1 day (Interquartile range, IQR: 0-27) compared to PCF with 30 days (IQR: 14-61). CONCLUSIONS:This study confirmed that massive ACF was not effective in general population in a moderate TB prevalence setting. The priority should be the definition and targeting of high-risk groups in the community before the screening process is launched. The shorter time interval of ACF between TB symptoms onset and linkage to healthcare service may decrease the risk of TB community transmission. Furthermore, integrated ACF strategy in the National Project of Basic Public Health Service may have long term public health impact.
Project description:Background: Community-based active case finding (ACF) for tuberculosis (TB) implemented among marginalised and vulnerable populations in 285 districts of India resulted in reduction of diagnosis delay and prevalence of catastrophic costs due to TB diagnosis. We were interested to know whether this translated into improved treatment outcomes. Globally, there is limited published literature from marginalised and vulnerable populations on the independent effect of community-based ACF on treatment outcomes when compared to passive case finding (PCF). Objectives: To determine the relative differences in unfavourable treatment outcomes (death, loss-to-follow-up, failure, not evaluated) of ACF and PCF-diagnosed people. Methods: Cohort study involving record reviews and interviews in 18 randomly selected districts. We enrolled all ACF-diagnosed people with new smear-positive pulmonary TB, registered under the national TB programme between March 2016 and February 2017, and an equal number of randomly selected PCF-diagnosed people in the same settings. We used log binomial models to adjust for confounders. Results: Of 572 enrolled, 275 belonged to the ACF and 297 to the PCF group. The proportion of unfavourable outcomes were 10.2% (95% CI: 7.1%, 14.3%) in the ACF and 12.5% (95% CI: 9.2%, 16.7%) in the PCF group (p = 0.468). The association between ACF and unfavourable outcomes remained non-significant after adjusting for confounders available from records [aRR: 0.83 (95% CI: 0.56, 1.21)]. Due to patient non-availability at their residence, interviews were conducted for 465 (81.3%). In the 465 cohort too, there was no association after adjusting for confounders from records and interviews [aRR: 1.05 (95% CI: 0.62, 1.77)]. Conclusion: We did not find significant differences in the treatment outcomes. Due to the wide CIs, studies with larger sample sizes are urgently required. Studies are required to understand how to translate the benefits of ACF to improved treatment outcomes.
Project description:BACKGROUND:Axshya SAMVAD is an active tuberculosis (TB) case finding (ACF) strategy under project Axshya (Axshya meaning 'free of TB' and SAMVAD meaning 'conversation') among marginalized and vulnerable populations in 285 districts of India. OBJECTIVES:To compare patient characteristics, health seeking, delays in diagnosis and treatment initiation among new sputum smear positive TB patients detected through ACF and passive case finding (PCF) under the national TB programme in marginalized and vulnerable populations between March 2016 and February 2017. METHODS:This observational analytic study was conducted in 18 randomly sampled Axshya districts. We enrolled all TB patients detected through ACF and an equal number of randomly selected patients detected through PCF in the same settings. Data on patient characteristics, health seeking and delays were collected through record review and patient interviews (at their residence). Delays included patient level delay (from eligibility for sputum examination to first contact with any health care provider (HCP)), health system level diagnosis delay (from contact with first HCP to TB diagnosis) and treatment initiation delays (from diagnosis to treatment initiation). Total delay was the sum of patient level, health system level diagnosis delay and treatment initiation delays. RESULTS:We included 234 ACF-diagnosed and 231 PCF-diagnosed patients. When compared to PCF, ACF patients were relatively older (?65 years, 14% versus 8%, p = 0.041), had no formal education (57% versus 36%, p<0.001), had lower monthly income per capita (median 13.1 versus 15.7 USD, p = 0.014), were more likely from rural areas (92% versus 81%, p<0.002) and residing far away from the sputum microscopy centres (more than 15 km, 24% versus 18%, p = 0.126). Fewer patients had history of significant loss of weight (68% versus 78%, p = 0.011) and sputum grade of 3+ (15% versus 21%, p = 0.060). Compared to PCF, HCP visits among ACF patients was significantly lower (median one versus two HCPs, p<0.001). ACF patients had significantly lower health system level diagnosis delay (median five versus 19 days, p = 0.008) and the association remained significant after adjusting for potential confounders. Patient level and total delays were not significantly different. CONCLUSION:Axshya SAMVAD linked the most impoverished communities to TB care and resulted in reduction of health system level diagnosis delay.
Project description:Background and objectives:The effects of active case finding (ACF) models that mobilise community networks for early identification and treatment of tuberculosis (TB) remain unknown. We investigated and compared the effect of community-based ACF using a seed-and-recruit model with one-off roving ACF and passive case finding (PCF) on the time to treatment initiation and identification of bacteriologically confirmed TB. Methods:In this retrospective cohort study conducted in 12 operational districts in Cambodia, we assessed relationships between ACF models and: 1) the time to treatment initiation using Cox proportional hazards regression; and 2) the identification of bacteriologically confirmed TB using modified Poisson regression with robust sandwich variance. Results:We included 728 adults with TB, of whom 36% were identified via the community-based ACF using a seed-and-recruit model. We found community-based ACF using a seed-and-recruit model was associated with shorter delay to treatment initiation compared to one-off roving ACF (hazard ratio 0.81, 95% CI 0.68-0.96). Compared to one-off roving ACF and PCF, community-based ACF using a seed-and-recruit model was 45% (prevalence ratio (PR) 1.45, 95% CI 1.19-1.78) and 39% (PR 1.39, 95% CI 0.99-1.94) more likely to find and detect bacteriologically confirmed TB, respectively. Conclusion:Mobilising community networks to find TB cases was associated with early initiation of TB treatment in Cambodia. This approach was more likely to find bacteriologically confirmed TB cases, contributing to the reduction of risk of transmission within the community.