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Background Tuberculosis (TB) prevention through the use of preventive treatment is a critical activity in the elimination of TB. In multiple settings, limited staffing has been identified as a barrier to managing preventive treatment for TB contacts. This study aims to determine how health center staffing, service type, and TB caseload affects implementation of isoniazid preventive therapy (IPT) for TB contacts in southern Lima. Methods We conducted an ecological study in 2019 in southern Lima, Peru. Through the review of medical records, we identified contacts of TB patients who initiated IPT during 2016–2018, and who were 0–19 years old, the age group eligible for IPT according to Peruvian guidelines. We assessed bivariate associations between health center characteristics (numbers of physicians and nurses, types of services available, annual TB caseload) and IPT initiation and completion using binomial logistic regression. Results Among 977 contacts, 69% took more than a week to start IPT and 41% did not complete IPT. For those who successfully completed IPT, 58% did not complete full medical follow-up. There was no significant difference in IPT completion or adherence based on whether health centers had more physicians and nurses, more comprehensive services, or higher TB caseloads. Among contacts, female sex was associated with delay in initiating IPT (P = 0.005), age 5–19 years old was associated with completion of IPT (P = 0.025) and age P = 0.041). Conclusions There are significant gaps in IPT implementation in health centers of southern Lima, Peru, but insufficient staffing of health centers may not be responsible. Further research is needed to identify how IPT implementation can be improved, potentially through improving staff training or monitoring and supervision. Graphic abstract

Background QuantiFERON-TB Gold In-Tube® (QFT-GIT) test is used for the diagnosis of latent tuberculosis (TB) infection. Besides, QFT-GIT test could allow tracking changes in immune response among TB patients and their contacts. In high TB burden settings, reports on QFT-GIT conversions and reversions among TB patients and their contacts are limited. As part of a major project to study immune responses to TB infection, we investigated QFT-GIT test conversions and reversions among smear positive pulmonary TB patients and their household contacts over 12 months. Methods We followed a total of 107 HIV negative participants (33 patients and 74 contacts) in Addis Ababa. We did QFT-GIT test at baseline and 12 months later according to the manufacturer’s instructions. Results At baseline, 25/33 (75.8%) of the patients and 50/74 (67.6%) of the contacts were QFT-GIT positive. At 12 months, 2 more patients (1 test negative and 1 indeterminate) became test positive. Besides, 11/24 (45.8%) test negative contacts became positive. Only one patient and one contact who were test positive at baseline became test negative 12 months later. At 12 months, the proportions of QFT-GIT test positives for patients and contacts were, therefore, 78.8% and 81.1%, respectively. Among contacts, the proportion of QFT-GIT test positives at 12 months was significantly higher compared to the corresponding proportion at baseline (McNemar, p = 0.006); similarly, the median IFN-γ response significantly increased at 12 months compared with the baseline level (Wilcoxon matched-pairs signed rank test, p = 0.01). Patients, however, had comparable median IFN-γ levels at baseline and 12 months later (p = 0.56). Conclusion Nearly half of QFT-GIT negative household contacts at baseline became positive at 12 months. This suggests that repeated screening of QFT-GIT negative contacts may be needed for epidemiological studies and interventions of latent TB in an endemic setting. A large longitudinal study may be needed to confirm our observations.

Background There is a higher case-detection rate for leprosy among spatially proximate contacts such as household members and neighbors. Spatial information regarding the clustering of leprosy can be used to improve intervention strategies. Identifying high-risk areas within villages around known cases can be helpful in finding new cases. Methods Using geographic information systems, we created digital maps of four villages in a highly endemic area in northwest Bangladesh. The villages were surveyed three times over four years. The spatial pattern of the compounds – a small group of houses – was analyzed, and we looked for spatial clusters of leprosy cases. Results The four villages had a total population of 4,123. There were 14 previously treated patients and we identified 19 new leprosy patients during the observation period. However, we found no spatial clusters with a probability significantly different from the null hypothesis of random occurrence. Conclusion Spatial analysis at the microlevel of villages in highly endemic areas does not appear to be useful for identifying clusters of patients. The search for clustering should be extended to a higher aggregation level, such as the subdistrict or regional level. Additionally, in highly endemic areas, it appears to be more effective to target complete villages for contact tracing, rather than narrowly defined contact groups such as households.