Household Contact Tracing With Intensified Tuberculosis and Human Immunodeficiency Virus Screening in South Africa: A Cluster-Randomized Trial

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Study Justification:
The study aimed to investigate whether household contact tracing and intensive tuberculosis (TB) and human immunodeficiency virus (HIV) screening would improve TB-free survival. The justification for the study was to determine if these interventions could facilitate early diagnosis and access to TB preventive treatment, ultimately reducing the incidence of TB and death.
Highlights:
– The study was conducted in South Africa and involved household contacts of index TB patients.
– The intervention group received home tracing and intensive TB/HIV screening, while the standard of care (SOC) group received clinic referral letters.
– The primary outcome measured was incident TB or death at 15 months.
– The cumulative incidence of TB or death did not differ significantly between the intervention and SOC arms.
– However, tuberculin skin test (TST) positivity was higher in the intervention arm compared to the SOC arm.
– Undiagnosed HIV was similar between the two arms.
– The study concluded that household contact tracing with intensive screening and referral did not reduce incident TB or death, suggesting that providing referral letters to household contacts could be an alternative strategy.
Recommendations:
Based on the study findings, the following recommendations can be made:
1. Consider implementing referral letters for household contacts of index TB patients as an alternative strategy to home visits for contact tracing.
2. Ensure access to TST and TB preventive treatment for household contacts, especially those with positive TST results.
3. Strengthen existing TB and HIV screening programs to improve early detection and treatment initiation.
Key Role Players:
To address the recommendations, the following key role players may be needed:
1. Government health departments and policymakers responsible for TB and HIV control programs.
2. Healthcare providers, including doctors, nurses, and community health workers, involved in TB and HIV screening and treatment.
3. Laboratory services for TB and HIV testing.
4. Community organizations and support groups to raise awareness and provide education on TB and HIV prevention.
Cost Items for Planning Recommendations:
While the actual costs will vary depending on the local context, the following cost items should be considered in planning the recommendations:
1. Training and capacity building for healthcare providers on contact tracing, TB and HIV screening, and treatment.
2. Procurement and distribution of TST supplies and TB preventive treatment medications.
3. Laboratory testing costs for TB and HIV diagnostics.
4. Community outreach and education programs.
5. Monitoring and evaluation activities to assess the impact of the recommendations.
Please note that the provided information is based on the description and findings of the study. For more detailed and accurate cost estimates, it is recommended to consult local health authorities and experts.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study design is a cluster-randomized trial, which is a robust method. The sample size is large, with over 4,000 contacts included. However, the primary outcome of incident TB or death did not differ significantly between the intervention and standard of care arms. To improve the strength of the evidence, future studies could consider increasing the duration of follow-up, including a larger number of study sites, and ensuring consistent implementation of the intervention across all sites.

BACKGROUND: Household contact tracing for tuberculosis (TB) may facilitate diagnosis and access to TB preventive treatment (TPT). We investigated whether household contact tracing and intensive TB/human immunodeficiency virus (HIV) screening would improve TB-free survival. METHODS: Household contacts of index TB patients in 2 South African provinces were randomized to home tracing and intensive HIV/TB screening or standard of care (SOC; clinic referral letters). The primary outcome was incident TB or death at 15 months. Secondary outcomes included tuberculin skin test (TST) positivity in children ≤14 years and undiagnosed HIV. RESULTS: From December 2016 through March 2019, 1032 index patients (4459 contacts) and 1030 (4129 contacts) were randomized to the intervention and SOC arms. Of intervention arm contacts, 3.2% (69 of 2166) had prevalent microbiologically confirmed TB. At 15 months, the cumulative incidence of TB or death did not differ between the intensive screening (93 of 3230, 2.9%) and SOC (80 of 2600, 3.1%) arms (hazard ratio, 0.90; 95% confidence interval [CI], .66-1.24). TST positivity was higher in the intensive screening arm (38 of 845, 4.5%) compared with the SOC arm (15 of 800, 1.9%; odds ratio, 2.25; 95% CI, 1.07-4.72). Undiagnosed HIV was similar between arms (41 of 3185, 1.3% vs 32 of 2543, 1.3%; odds ratio, 1.02; 95% CI, .64-1.64). CONCLUSIONS: Household contact tracing with intensive screening and referral did not reduce incident TB or death. Providing referral letters to household contacts of index patients is an alternative strategy to home visits. CLINICAL TRIALS REGISTRATION: ISRCTN16006202.

We conducted an open, 2-arm, cluster-randomized trial of household contact tracing and intensive TB/HIV screening in South Africa (ISRCTN16006202). Methods have been described previously (Supplementary Materials, Protocol) [19]. The Mangaung Municipality in Free State Province is predominantly urban with an estimated population of 780 755, an antenatal HIV prevalence of 31.7%, and estimated annual TB incidence in 2019 of 476/100 000. In 2018, the more rural Capricorn Health District in Limpopo Province had an estimated population of 1 338 763 [20], an antenatal HIV seroprevalence in 2015 of 21.6%, and estimated annual TB incidence in 2019 of 201/100 000 [21, 22]. During the study period, there were few programmatic attempts made to identify and screen household contacts for TB. Study teams identified consecutive eligible index TB patients at government clinics and hospitals within study site boundaries. We included TB patients of any age but required those aged ≥7 years to have laboratory-confirmed pulmonary TB, whereas those aged <7 years could have physician-diagnosed TB of any organ, with or without laboratory confirmation. We additionally included TB patients who died within 8 weeks of TB diagnosis. We excluded institutionalized TB patients and withdrew participants whose households we could not locate or from where no household member could be recruited. A list of household contacts was obtained at enrollment. Households of index patients were defined as people living together within a set of rooms under a contiguous roof linked by doorways or windows through which air moved and where household members had shared airspace by either sleeping overnight at least once or had shared at least 2 meals in the same household as the index case in the 14 days prior to the index case’s diagnosis of TB. Index cases and their households were block-randomized to either intervention or standard of care (SOC) in a 1:1 ratio, stratified by district. Investigator blinding was maintained until after the final participant household follow-up was completed. In the intervention group, research fieldworkers visited households within 14 days of index TB patient enrollment (maximum 3 attempts), obtaining written individual or parental consent for adults and children aged <18 years, respectively, with assent from older children. A questionnaire was administered to each household member (Supplementary Materials, Questionnaires), and sputum specimens were obtained where possible (but not required from children aged <5 years) and were tested using Xpert and mycobacterial growth indicator tube (MGIT) culture. Household contacts received TST (from a variety of sources due to global shortages), administered and read within 72 hours [23]. Study nurses dispensed the first month of TPT (6 months of daily isoniazid) to participants living with HIV who tested negative for TB, participants not living with HIV with positive TST (≥10 mm), and children aged <5 years. Subsequent TPT was obtained from local clinics. For household members without a confirmed HIV diagnosis, rapid point-of-care HIV testing was offered to participants aged ≥18 months, and polymerase chain reaction on dried blood spot was provided for children aged <18 months whose maternal HIV status was unknown or positive. Participants living with HIV had a CD4 count measured and were referred to their nearest clinic for assessment and initiation of ART. Intervention households were visited approximately 3 months after enrollment to support treatment linkage. In the SOC arm, index TB patients (or their representative, if deceased or a child) were given referral letters for every household member by the recruiting team at the health facility, recommending that each household contact take the letter to their local clinic and be screened for TB and HIV. At 15 months after randomization, study teams visited all households, updated the household membership list, and recorded episodes of incident TB and death. We investigated household members for HIV (if untested) and TB (if symptomatic). All children aged ≤14 years had TST placed, read at 48–72 hours. The primary outcome was time to TB or death, measured among all household members included in the household census at baseline, from 1 month after randomization through the final 15-month ascertainment visit. Primary analysis included all incident TB diagnoses, irrespective of diagnostic method; sensitivity analyses included only bacteriologically confirmed incident cases of TB. Secondary outcomes were prevalence of TB infection (TST induration ≥10 mm) at month 15 among household children aged ≤14 years, time to initiation of TB treatment, and prevalence of undiagnosed or untreated HIV at month 15. Primary analyses for all outcomes were restricted to household contacts resident at baseline enumeration; supplementary analyses included all household contacts regardless of baseline residency. In protocol-specified subgroup analysis, we compared outcomes by trial site and TST positivity by household contact age (<5 years, ≥5 years). The University of Witwatersrand Human Research Ethics Committee (Medical) and the London School of Hygiene and Tropical Medicine granted ethical approval. Assuming a mean household size of 5.5 and a primary outcome incidence of 2000/100 000 person-years, 1200 index cases per site (total 2400) provided 80% power to detect a 30% overall difference in the primary outcome between groups with alpha 0.05 and intracluster correlation coefficient 0.3. All statistical analyses were performed using Stata v16 (StataCorp, College Station, TX). Analyses were done on an intention-to-treat basis. This study is reported following CONSORT guidelines for cluster-randomized trials (Supplementary Materials, Checklist). We summarized baseline index and household characteristics by trial arm. For the primary outcome, follow-up time began 1 month after randomization (to avoid counting prevalent TB cases) and ended at the month-15 visit or the date of TB or death. Cox proportional hazards regression with robust standard errors was used to assess the impact of the intervention on the primary outcome, with a time-by-treatment interaction term fitted to assess the proportionality assumption. Logistic regression with generalized estimating equations was used to assess the impact of the intervention on binary outcomes. Interaction terms were fitted to assess effect modification in planned subgroup analyses.

Based on the provided information, it appears that the study conducted a cluster-randomized trial to investigate the impact of household contact tracing and intensive TB/HIV screening on TB-free survival in South Africa. The trial compared the intervention group, which received home visits, screening, and referral, with the standard of care group, which received referral letters for screening at local clinics. The primary outcome measured was incident TB or death at 15 months. Secondary outcomes included tuberculin skin test (TST) positivity in children aged ≤14 years and undiagnosed HIV.

In terms of innovations to improve access to maternal health, it is important to note that the study focused on TB and HIV screening among household contacts of index TB patients, rather than specifically targeting maternal health. Therefore, the specific innovations related to maternal health may not be explicitly mentioned in the provided information.

However, based on the broader context of maternal health and innovations in healthcare, here are some potential recommendations that could be considered to improve access to maternal health:

1. Telemedicine and mobile health (mHealth) solutions: Implementing telemedicine and mHealth platforms can enable remote consultations, monitoring, and support for pregnant women, especially in areas with limited access to healthcare facilities. This can help improve access to prenatal care, provide timely advice, and reduce the need for unnecessary travel.

2. Community-based interventions: Engaging community health workers and midwives to provide maternal health services at the community level can enhance access to care, especially in rural or underserved areas. These interventions can include antenatal care, postnatal care, and education on maternal and newborn health.

3. Maternal health clinics or centers: Establishing dedicated maternal health clinics or centers can provide comprehensive care for pregnant women, including prenatal check-ups, childbirth services, and postnatal care. These facilities can be equipped with skilled healthcare professionals and necessary resources to ensure safe and quality care.

4. Mobile clinics or outreach programs: Deploying mobile clinics or organizing regular outreach programs can bring maternal health services closer to remote or marginalized communities. These initiatives can provide prenatal care, vaccinations, health education, and referrals for further care when needed.

5. Maternal health information systems: Implementing robust information systems can help track and monitor maternal health indicators, identify areas of improvement, and facilitate data-driven decision-making. This can contribute to improving the overall quality and accessibility of maternal health services.

It is important to note that these recommendations are general and may need to be tailored to the specific context and challenges faced in improving access to maternal health in South Africa or any other region.
AI Innovations Description
The study conducted a cluster-randomized trial in South Africa to investigate the effectiveness of household contact tracing and intensive tuberculosis (TB) and human immunodeficiency virus (HIV) screening in improving TB-free survival and access to TB preventive treatment (TPT) for household contacts of index TB patients. The intervention involved home visits, questionnaire administration, sputum specimen collection, tuberculin skin testing (TST), provision of TPT, HIV testing, and referral to clinics for assessment and initiation of antiretroviral therapy (ART). The standard of care (SOC) arm involved providing referral letters to household contacts for TB and HIV screening at local clinics.

The primary outcome of the study was incident TB or death at 15 months. Secondary outcomes included TST positivity in children aged ≤14 years and undiagnosed HIV. The study found that the cumulative incidence of TB or death did not differ significantly between the intervention and SOC arms. However, TST positivity was higher in the intervention arm compared to the SOC arm. Undiagnosed HIV was similar between the two arms.

Based on the findings of this study, the recommendation for developing an innovation to improve access to maternal health could be to implement a similar household contact tracing and screening approach for pregnant women. This could involve identifying pregnant women at healthcare facilities and conducting home visits to provide comprehensive maternal health services, including TB and HIV screening, TST, provision of TPT, HIV testing, and referral for further assessment and treatment. By bringing these services directly to pregnant women in their homes, barriers to accessing maternal health care, such as transportation and time constraints, can be reduced. This approach can help ensure early detection and management of TB and HIV in pregnant women, ultimately improving maternal and child health outcomes.
AI Innovations Methodology
The study described is focused on household contact tracing and intensive tuberculosis (TB) and human immunodeficiency virus (HIV) screening in South Africa. The goal of the study was to determine if these interventions would improve TB-free survival and access to TB preventive treatment (TPT). The study involved randomized household contacts of index TB patients in two South African provinces.

The primary outcome of the study was incident TB or death at 15 months. Secondary outcomes included tuberculin skin test (TST) positivity in children aged 14 years or younger and undiagnosed HIV. The study found that household contact tracing with intensive screening and referral did not reduce incident TB or death. Providing referral letters to household contacts of index patients was identified as an alternative strategy to home visits.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define the target population: Identify the specific population that would benefit from improved access to maternal health. This could include pregnant women, new mothers, or women of reproductive age.

2. Identify the recommendations: Determine the specific recommendations that would improve access to maternal health. These could include interventions such as increased antenatal care visits, improved access to skilled birth attendants, or enhanced postnatal care services.

3. Collect baseline data: Gather data on the current state of access to maternal health in the target population. This could include information on the number of antenatal care visits, rates of skilled birth attendance, or availability of postnatal care services.

4. Simulate the impact of the recommendations: Use statistical modeling techniques to simulate the impact of implementing the recommendations on improving access to maternal health. This could involve estimating the potential increase in antenatal care visits, the percentage of births attended by skilled birth attendants, or the number of women receiving postnatal care.

5. Assess the outcomes: Evaluate the outcomes of the simulation to determine the potential impact of the recommendations on improving access to maternal health. This could include measuring changes in maternal mortality rates, rates of complications during childbirth, or improvements in overall maternal health indicators.

6. Refine and adjust the recommendations: Based on the simulation results, refine and adjust the recommendations as necessary. This could involve identifying additional interventions or modifying existing strategies to further improve access to maternal health.

7. Implement and monitor: Implement the recommendations and closely monitor the impact on access to maternal health. Continuously evaluate the outcomes and make adjustments as needed to ensure ongoing improvement.

By following this methodology, it is possible to simulate the impact of recommendations on improving access to maternal health and make informed decisions about implementing interventions that can have a positive impact on maternal health outcomes.

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