BACKGROUND: Mumbai is one of the most densely populated areas in the world and is a major contributor to the tuberculosis (TB) epidemic in India. A test and treat approach for TB infection (TBI) amongst household contacts (HHC) is part of the national policy for TB preventive treatment (TPT). However, in practice, the use of interferon-gamma release assay (IGRA) tests for infection are limited, and prevalence of TBI in Mumbai is not known. METHODS: We conducted a cross-sectional study among HHCs exposed to persons with microbiologically-confirmed, drug-susceptible pulmonary TB that were notified for antituberculosis treatment in Mumbai, India during September-December, 2021. Community-based field workers made home visits and offered IGRA (QuantiFERON-TB(®) Gold In-Tube Plus) tests to HHC aged 5 years and older. After ruling out active TB disease, HHC with IGRA-positive test results were referred for TPT. All HHC were monitored for at least 24 months for progression to active TB disease. RESULTS: Among 502 HHCs tested, 273 (54%) had IGRA-positive results. A total of 254 (93%) were classified as TBI and were eligible for TPT, of which 215 (85%) initiated TPT, and 194 (90%) completed TPT successfully. There was substantial variation in rates of TBI per household. In 32% of households, all HHC (100%) were IGRA positive and in 64% of households >50% of HHC were infected. In all, 22 HHCs (4%; 22/558) were diagnosed with TB disease; of these, five HHC were diagnosed during follow up, of which three were IGRA positive and had no evidence of disease at initial screening but chose not to initiate TPT. CONCLUSION: A test and treat strategy for HHC resulted in the detection of a substantial proportion of TBI and secondary TB cases. Home-based IGRA testing led to high participation rates, clinical evaluations, TPT initiation, and early diagnoses of additional secondary cases. A community-focused, test and treat approach was feasible in this population and could be considered for broader implementation.

PROBLEM: Medication for opioid use disorder (MOUD) is recommended for persons with opioid use disorder (OUD) during pregnancy. However, knowledge gaps exist about best practices for management of OUD during pregnancy and these data are needed to guide clinical care. PERIOD COVERED: 2014-2021. DESCRIPTION OF THE SYSTEM: Established in 2019, the Maternal and Infant Network to Understand Outcomes Associated with Medication for Opioid Use Disorder During Pregnancy (MAT-LINK) is a surveillance network of seven clinical sites in the United States. Boston Medical Center, Kaiser Permanente Northwest, The Ohio State University, and the University of Utah were the initial clinical sites in 2019. In 2021, three clinical sites were added to the network (the University of New Mexico, the University of Rochester, and the University of South Florida). Persons receiving care at the seven clinical sites are diverse in terms of geography, urbanicity, race and ethnicity, insurance coverage, and type of MOUD received. The goal of MAT-LINK is to capture demographic and clinical information about persons with OUD during pregnancy to better understand the effect of MOUD on outcomes and, ultimately, provide information for clinical care and public health interventions for this population. MAT-LINK maintains strict confidentiality through robust information technology architecture. MAT-LINK surveillance methods, population characteristics, and evaluation findings are described in this inaugural surveillance report. This report is the first to describe the system, presenting detailed information on funding, structure, data elements, and methods as well as findings from a surveillance evaluation. The findings presented in this report are limited to selected demographic characteristics of pregnant persons overall and by MOUD treatment status. Clinical and outcome data are not included because data collection and cleaning have not been completed; initial analyses of clinical and outcome data will begin in 2023. RESULTS: The MAT-LINK surveillance network gathered data on 5,541 reported pregnancies with a known pregnancy outcome during 2014-2021 among persons with OUD from seven clinical sites. The mean maternal age was 29.7 (SD = ±5.1) years. By race and ethnicity, 86.3% of pregnant persons were identified as White, 25.4% as Hispanic or Latino, and 5.8% as Black or African American. Among pregnant persons, 81.6% had public insurance, and 84.4% lived in urban areas. Compared with persons not receiving MOUD during pregnancy, those receiving MOUD during pregnancy were more likely to be older and White and to have public insurance. The evaluation of the surveillance system found that the initial four clinical sites were not representative of demographics of the South or Southwest regions of the United States and had low representation from certain racial and ethnic groups compared with the overall U.S. population; however, the addition of three clinical sites in 2021 made the surveillance network more representative. Automated extraction and processing improved the speed of data collection and analysis. The ability to add new clinical sites and variables demonstrated the flexibility of MAT-LINK. INTERPRETATION: MAT-LINK is the first surveillance system to collect comprehensive, longitudinal data on pregnant person-infant dyads with perinatal outcomes associated with MOUD during pregnancy from multiple clinical sites. Analyses of clinical site data demonstrated different sociodemographic characteristics between the MOUD and non-MOUD treatment groups. PUBLIC HEALTH ACTIONS: MAT-LINK is a timely and flexible surveillance system with data on approximately 5,500 pregnancies. Ongoing data collection and analyses of these data will provide information to support clinical and public health guidance to improve health outcomes among pregnant persons with OUD and their children.

Mumbai, India's second largest city, has one of the highest prevalences of drug-resistant tuberculosis* (DRTB) in the world. Treatment for DRTB takes longer and is more complicated than treatment for drug-susceptible tuberculosis (TB). Approximately 300 persons receive a new DRTB diagnosis each year in Mumbai's Dharavi slum(†); historically, fewer than one half of these patients complete DRTB treatment. As nationwide restrictions to mitigate the COVID-19 pandemic were implemented, a program to facilitate uninterrupted DRTB care for patients receiving treatment was also implemented. A comprehensive tool and risk assessment provided support to DRTB patients and linked those who relocated outside of Dharavi during the pandemic to DRTB care at their destination. During May 2020-September 2022, a total of 973 persons received DRTB treatment in Dharavi, including 255 (26%) who relocated during treatment. Overall, 25 (3%) DRTB patients were lost to follow-up, a rate substantially lower than the rate before the pandemic (18%). Proactive planning and implementation of simple tools retained patients on treatment during periods of travel restrictions and relocations, improving programmatic outcomes. This approach might aid public health programs serving migrant populations or patients receiving treatment for DRTB during public health emergencies.

BACKGROUND: Influenza vaccination during pregnancy prevents influenza among women and their infants but remains underused among pregnant women. We aimed to quantify the risk of antenatal influenza and examine its association with perinatal outcomes. METHODS: We did a prospective cohort study in pregnant women in India, Peru, and Thailand. Before the 2017 and 2018 influenza seasons, we enrolled pregnant women aged 18 years or older with expected delivery dates 8 weeks or more after the season started. We contacted women twice weekly until the end of pregnancy to identify illnesses with symptoms of myalgia, cough, runny nose or nasal congestion, sore throat, or difficulty breathing and collected mid-turbinate nasal swabs from symptomatic women for influenza real-time RT-PCR testing. We assessed the association of antenatal influenza with preterm birth, late pregnancy loss (≥13 weeks gestation), small for gestational age (SGA), and birthweight of term singleton infants using Cox proportional hazards models or generalised linear models to adjust for potential confounders. FINDINGS: Between March 13, 2017, and Aug 3, 2018, we enrolled 11 277 women with a median age of 26 years (IQR 23-31) and gestational age of 19 weeks (14-24). 1474 (13%) received influenza vaccines. 310 participants (3%) had influenza (270 [87%] influenza A and 40 [13%] influenza B). Influenza incidences weighted by the population of women of childbearing age in each study country were 88·7 per 10 000 pregnant woman-months (95% CI 68·6 to 114·8) during the 2017 season and 69·6 per 10 000 pregnant woman-months (53·8 to 90·2) during the 2018 season. Antenatal influenza was not associated with preterm birth (adjusted hazard ratio [aHR] 1·4, 95% CI 0·9 to 2·0; p=0·096) or having an SGA infant (adjusted relative risk 1·0, 95% CI 0·8 to 1·3, p=0·97), but was associated with late pregnancy loss (aHR 10·7, 95% CI 4·3 to 27·0; p<0·0001) and reduction in mean birthweight of term, singleton infants (-55·3 g, 95% CI -109·3 to -1·4; p=0·0445). INTERPRETATION: Women had a 0·7-0·9% risk of influenza per month of pregnancy during the influenza season, and antenatal influenza was associated with increased risk for some adverse pregnancy outcomes. These findings support the added value of antenatal influenza vaccination to improve perinatal outcomes. FUNDING: US Centers for Disease Control and Prevention. TRANSLATIONS: For the Thai, Hindi, Marathi and Spanish translations of the abstract see Supplementary Materials section.

BACKGROUND: Tuberculosis (TB) patients with human immunodeficiency virus (HIV) co-infection have worse TB treatment outcomes compared to patients with TB alone. The distribution of unfavourable treatment outcomes differs by socio-demographic and clinical characteristics, allowing for early identification of patients at risk. OBJECTIVE: To develop a statistical model that can provide individual probabilities of unfavourable outcomes based on demographic and clinical characteristics of TB-HIV co-infected patients. METHODOLOGY: We used data from all TB patients with known HIV-positive test results (aged >/=15 years) registered for first-line anti-TB treatment (ATT) in 2015 under the Revised National TB Control Programme (RNTCP) in Delhi, India. We included variables on demographics and pre-treatment clinical characteristics routinely recorded and reported to RNTCP and the National AIDS Control Organization. Binomial logistic regression was used to develop a statistical model to estimate probabilities of unfavourable TB treatment outcomes (i.e., death, loss to follow-up, treatment failure, transfer out of program, and a switch to drug-resistant regimen). RESULTS: Of 55,260 TB patients registered for ATT in 2015 in Delhi, 928 (2%) had known HIV-positive test results. Of these, 816 (88%) had drug-sensitive TB and were >/=15 years. Among 816 TB-HIV patients included, 157 (19%) had unfavourable TB treatment outcomes. We developed a model for predicting unfavourable outcomes using age, sex, disease classification (pulmonary versus extra-pulmonary), TB treatment category (new or previously treated case), sputum smear grade, known HIV status at TB diagnosis, antiretroviral treatment at TB diagnosis, and CD4 cell count at ATT initiation. The chi-square p-value for model calibration assessed using the Hosmer-Lemeshow test was 0.15. The model discrimination, measured as the area under the receiver operator characteristic (ROC) curve, was 0.78. CONCLUSION: The model had good internal validity, but should be validated with an independent cohort of TB-HIV co-infected patients to assess its performance before clinical or programmatic use.

INTRODUCTION: Multidrug-resistant Tuberculosis (MDR TB) is emerging public health concern globally. Lost to follow-up (LTFU) is one of the key challenge in MDRTB treatment. In 2013, 18% of MDR TB patients were reported LTFU in India. A qualitative study was conducted to obtain better understanding of both patient and provider related factors for LTFU among MDR TB treatment. METHODS: Qualitative semi-structured personal interviews were conducted with 20 MDRTB patients reported as LTFU and 10 treatment providers in seven districts linked to Nagpur Drug resistant TB Centre (DRTBC) during August 2012-February 2013. Interviews were transcribed and inductive content analysis was performed to derive emergent themes. RESULTS: We found multiple factors influencing MDR TB treatment adherence. Barriers to treatment adherence included drug side effects, a perceived lack of provider support, patient financial constraints, conflicts with the timing of treatment services, alcoholism and social stigma. CONCLUSIONS: Patient adherence to treatment is multi-factorial and involves individual patient factors, provider factors, and community factors. Addressing issue of LTFU during MDRTB treatment requires enhanced efforts towards resolving medical problems like adverse drug effects, developing short duration treatment regimens, reducing pill burden, motivational counselling, flexible timings for DOT services, social, family support for patients & improving awareness about disease.