BACKGROUND: There is limited evidence on COVID-19 vaccination uptake among people living with HIV (PLHIV) and health care workers (HCWs), with the current evidence concentrated in high-income countries. There is also limited documentation in the published literature regarding the feasibility and lessons from implementing targeted vaccination strategies to reach PLHIV and HCWs in low- and middle-income countries. PROGRAM DEVELOPMENT, PILOTING, AND IMPLEMENTATION: We designed and implemented multifaceted strategies to scale up targeted COVID-19 vaccination among PLHIV and HCWs in 11 administrative regions on the mainland of Tanzania plus Zanzibar. An initial 6-week intensification strategy was implemented using a diverse partnership model comprising key stakeholders at the national- and subnational levels. A layered package of strategies included expanding the number of certified vaccinators, creating vaccination points within HIV clinics, engaging HCWs to address their concerns, and building the capacity of HCWs as "champions" to promote and facilitate vaccination. We then closely monitored COVID-19 vaccination uptake in 562 high-volume HIV clinics. Between September 2021 and September 2022, the proportion of fully vaccinated adult PLHIV increased from <1% to 97% and fully vaccinated HCWs increased from 23% to 80%. LESSONS AND IMPLICATIONS: Our intra-action review highlighted the importance of leveraging a strong foundation of existing partnerships and platforms, integrating COVID-19 vaccination points within HIV clinics, and refining strategies to increase vaccination demand while ensuring continuity of vaccine supply to meet the increased demand. Lessons from Tanzania can inform targeted vaccination of vulnerable groups in future health emergencies.

INTRODUCTION: The World Health Organization recommended the initiation of antiretroviral therapy (ART) for people living with HIV (PLHIV) regardless of CD4 cell counts. Tanzania adopted this recommendation known as test-and-treat policy in 2016. However, programmatic implementation of this policy has not been assessed since its initiation. The objective of the study was to assess the impact of this policy in Tanzania. METHODS: This was a cross-sectional study among PLHIV aged 15 years and older using routinely collected program data. The dependent variable was interruption in treatment (IIT), defined as no clinical contact for at least 90 days after the last clinical appointment. The main independent variable was test-and-treat policy status which categorized PLHIV into the before and after groups. Co-variates were age, sex, facility type, clinical stage, CD4 count, ART duration, and body mass index. The associations were assessed using the generalized estimating equation with inverse probability weighting. RESULTS: The study involved 33,979 PLHIV-14,442 (42.5%) and 19,537 (57.5%) were in the before and after the policy groups, respectively. Among those who experienced IIT, 4,219 (29%) and 7,322 (38%) were in the before and after the policy groups respectively. Multivariable analysis showed PLHIV after the policy was instated had twice [AOR 2.03; 95%CI 1.74-2.38] the odds of experiencing IIT than those before the policy was adopted. Additionally, higher odds of experiencing IIT were observed among younger adults, males, and those with advanced HIV disease. CONCLUSION: Demographic and clinical status variables were associated with IIT, as well as the test-and-treat policy. To achieve epidemic control, programmatic adjustments on continuity of treatment may are needed to complement the programmatic implementation of the policy.

Reducing HIV-related morbidity and mortality, and effectively eliminating HIV transmission risk, depends on use of antiretroviral therapy (ART) to achieve and maintain viral load suppression (VLS)* (1,2). By 2020, sub-Saharan African countries are working to achieve VLS among 90% of persons using ART and 73% of all persons living with HIV infection (1). In Tanzania, a country with 1.4 million persons with HIV infection, 49.6% of HIV-positive persons aged 15-49 years had achieved VLS in 2017, including only 21.5% of men and 44.6% of women aged 25-29 years (3). To identify interventions that might increase VLS in Tanzania, and reduce VLS-associated sex and age-group disparities, the Bukoba Combination Prevention Evaluation (BCPE) scaled up new HIV testing, linkage to care, and retention on ART interventions throughout Bukoba Municipal Council (Bukoba), Tanzania, during October 2014-March 2017 (4,5). Located on the western shore of Lake Victoria, Bukoba is a mixed urban and rural municipality of 150,000 persons and capital of Kagera Region. Of the 31 regions of Tanzania, Kagera has the fourth highest prevalence of HIV infection (6.8%) among residents aged 15-49 years (3). CDC analyzed data from BCPE preintervention and postintervention surveys and found that VLS prevalence among HIV-positive Bukoba residents aged 18-49 years increased approximately twofold overall (from 28.6% to 64.8%) and among women (33.3% to 67.8%) and approximately threefold among men (20.5% to 59.1%) and young adults aged 18-29 years (15.6% to 56.7%). During 2017, BCPE facility-based testing and linkage interventions were approved as new service delivery models by the Tanzania Ministry of Health, Community Development, Gender, Elderly and Children (4,5). After a successful rollout to 208 facilities in 11 regions in 2018, BCPE interventions are being scaled up in all regions of Tanzania in 2019 with support from the United States President's Emergency Plan for AIDS Relief (PEPFAR).

BACKGROUND: Patient costs pose a challenge in accessing antiretroviral therapy for people living with HIV in sub-Saharan Africa. The study aimed at identifying drivers for out-of-pocket (OOP) costs in Tanzania. METHODS: In 2009, 500 adult patients who attended 10 HIV clinics across 7 regions of Tanzania were asked about time and resources consumed to access HIV services. Bivariate and multivariate median regression models were used to determine the main drivers for OOP costs. RESULTS: Male and female patients have a median OOP costs of $40.37 and $28.01 per year, respectively ( P = .01). Males spend significantly more on travel ($26.51) than females ($19.68; P = .02). Living in rural areas and poor social economic status (SES) are associated with greater OOP costs ( P = .001) for both sexes. CONCLUSION: Poor SES and rural residence are main drivers of OOP costs. Patients are less likely to seek health care unless they are in dire need, leading to expensive services.