Influence of the identification of contacts on the adherence of index tuberculosis cases to treatment in a high incidence country

Tuberculosis contact tracing yield and associated factors in Uganda

BACKGROUND

The yield of tuberculosis (TB) contact tracing is historically low in Uganda. We determined factors associated with a positive contact tracing yield at an urban public TB clinic in Kampala, Uganda.

METHODS

We reviewed contact tracing registers of index TB cases registered between 2015 and 2020 at Kitebi Health Center, a primary level facility. Contacts who had symptoms of TB were designated as having presumptive TB. A contact investigation that yielded a new TB case was designated as a positive yield. We used logistic regression to determine factors associated with a positive yield of contact tracing.

RESULTS

Of 778 index TB cases, 455 (58.5%) had a contact investigation conducted. Index cases with a telephone contact in the unit TB register (adjusted odds ratio (aOR) 1.66, 95% CI 1.02-1.97, p = 0.036) were more likely to have a contact investigation conducted than those who did not. Of 1350 contacts, 105 (7.8%) had presumptive TB. Of these, 73 (69.5%) were further evaluated for active TB and 29 contacts had active TB. The contact tracing yield for active TB was therefore 2.1% (29/1,350). The odds of a positive yield increased tenfold with each additional presumptive contact evaluated for active TB (aOR 10.1, 95% CI 2.95-34.66, p < 0.001). Also, retreatment index TB cases were more likely to yield a positive contact (aOR 7.69 95% CI 2.08-25.00, p = 0.002) than to new cases.

CONCLUSION

TB contact tracing should aim to evaluate all contacts with presumptive TB and contacts of retreatment cases to maximise the yield of contact tracing.

Investigation of Contacts for Latent Mycobacterium Tuberculosis Infection: Application Software Development

Introduction:

Tuberculosis is a pathology that continues to be worthy of special attention from health professionals and society due to its high prevalence, proving to be a crucial public health problem.

Objectives:

To describe the development of an application for family health strategy professionals’ investigation of tuberculosis contacts for Latent Mycobacterium tuberculosis Infection.

Methods:

This study is applied research on an application software developed according to three of the five phases described by Falkembach for developing digital educational materials, which include analysis and planning, modeling, and implementation.

Results:

The application is dynamic; that is, it guides health professionals through sequenced screens according to professionals’ self-informed answers. This functionality helps them deciding whether to proceed to the treatment of the patient with Latent Mycobacterium tuberculosis Infection or returning to the initial stage of a tuberculosis contact.

The screens of the application follow the flowchart presented in the Ministry of Health’s Manual of recommendations for tuberculosis control in Brazil of 2018.

Conclusion:

The application developed to guide Family Health Strategy professionals regarding Latent Infection by Mycobacterium Tuberculosis can prevent human errors and increase the care quality when assessing tuberculosis contacts.

Contact tracing is associated with treatment success of index tuberculosis cases in Uganda

OBJECTIVE:

To determine the effect of contact tracing on the treatment outcomes of index tuberculosis (TB) cases in Uganda.

METHODS:

We evaluated TB cases registered at an urban public health facility in Uganda in 2015–2020. We extracted data from the unit’s TB and contact tracing registers. Treatment outcomes were classified as cure, loss to follow-up, death and treatment failure. Treatment success was the sum of cure and treatment completion.

RESULTS:

Among 778 TB cases, contact tracing was conducted for 455 (58.5%). Compared with cases without contract tracing (n=323), cases with contract tracing (n=455) had higher treatment success (92.5% vs 79.3%) and cure rates (57.1% vs 39.9%) and lower loss to follow-up (3.5% vs 9.3%), treatment failure (0.4% vs 1.6%) and death (3.5% vs 9.9%) (P<0.001). Contact tracing was associated with higher odds of treatment success (adjusted odds ratio (aOR) 3.00, 95% CI 1.92–4.70, P<0.001) and cure (aOR 3.11, 95% CI 1.97–4.90, P<0.001), and lower odds of loss to follow-up (aOR 0.33, (0.13–0.83), P=0.018) and death (aOR 0.38, (0.20–0.72), P=0.003).

CONCLUSION:

TB contact tracing should be conducted consistently not only for the benefit of identifying new TB cases but also to promote treatment success of index cases.

Coverage of tuberculosis and diabetes mellitus screening among household contacts of tuberculosis patients: a household-based cross-sectional survey from Southern Thailand

Background

The comorbid presence of tuberculosis and diabetes mellitus has become an increasingly important public health threat to the prevention and control of both diseases. Thus, household contact investigation may serve a dual purpose of screening for both tuberculosis and diabetes mellitus among household contacts. We therefore aimed to evaluate the coverage of screening for tuberculosis and diabetes mellitus among household contacts of tuberculosis index cases and to determine predictors of tuberculosis screening.

Methods

A household-based survey was conducted in February 2019 in Muang district of Phatthalung Province, Thailand where 95 index tuberculosis patients were newly diagnosed with pulmonary or pleural tuberculosis between October 2017 and September 2018. Household contacts of the index patients were interviewed using a structured questionnaire to ascertain their past-year history of tuberculosis screening and, if appropriate, diabetes mellitus screening. For children, the household head or an adult household member was interviewed as a proxy. Coverage of tuberculosis screening at the household level was regarded as households having all contacts screened for tuberculosis. Logistic regression and mixed-effects logistic regression models were used to determine predictors of tuberculosis screening at the household and individual levels, respectively, with the strengths of association presented as adjusted odds ratios (AOR) and 95% confidence intervals (CI).

Results

Of 61 responding households (64%), complete coverage of tuberculosis screening at the household level was 34.4% and among the 174 household contacts was 46.6%. About 20% of contacts did not receive any recommendation for tuberculosis screening. Households were more likely to have all members screened for tuberculosis if they were advised to be screened by a healthcare professional rather than someone else. At the individual level, contacts aged ≥35 years (AOR: 30.6, 95% CI: 2.0–466.0), being an employee (AOR: 0.1, 95% CI: 0.0–0.8) and those who had lived more than 5 years in the same household (AOR: 0.1, 95% CI: 0.0–0.8) were independent predictors for tuberculosis screening. Coverage of diabetes mellitus screening was 80.6% with lack of awareness being the main reason for not being screened.

Conclusions

Compared to diabetes screening, the coverage of tuberculosis screening was low. A better strategy to improve coverage of tuberculosis contact screening is needed.