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The COVID-19 pandemic was reported from March 2020 in Zimbabwe. COVID-19 containment measures which included repeated lockdowns have disrupted community interactions, reduced working hours, restricted travel and restricted HIV services for people living with HIV (PLHIV), among others. The study adopted a cross-sectional design. Both qualitative and quantitative data were collected in all the 10 provinces and analysed. A sample size of 480 was calculated for the cross-sectional survey. Secondary data on HIV early warning indicators from 2018 to 2021 were extracted from 20 randomly selected health facilities and used for modelling. Mathematical modelling was conducted to assess the impact of COVID-19 on PLHIV. AIDS-related deaths increased from 20 100 in 2019 to 22 200 in 2020. In addition, there were significant years of life lost (yLLs) from premature mortality and years of life lost due to disability (yLDs) from COVID-19. Prevalence of COVID-19 among PLHIV was 4%. COVID-19 vaccination coverage was 64%, which is higher than the national average of 42%. Stress and breach of confidentiality as ARV medicines were given out in open spaces and fear of contracting COVID-19 were the perceived psychological issues. COVID-19 disrupted HIV service provision, increased AIDS-related deaths and caused psychological challenges.

Understanding the economic implications of COVID-19 for the HIV epidemic and response is critical for designing policies and strategies to effectively sustain past gains and accelerate progress to end these colliding pandemics. While considerable cross-national empirical evidence exists at the global level, there is a paucity of such deep-dive evidence at national level. This article addresses this gap. While Zimbabwe experienced fewer COVID-19 cases and deaths than most countries, the pandemic has had profound economic effects, reducing gross domestic product by nearly 7% in 2020. This exacerbates the long-term economic crisis that began in 1998. This has left many households vulnerable to the economic fallout from COVID-19, with the number of the extreme poor having increased to 49% of the population in 2020 (up from 38% in 2019). The national HIV response, largely financed externally, has been one of the few bright spots. Overall, macro-economic and social conditions heavily affected the capacity of Zimbabwe to respond to COVID-19. Few options were available for borrowing the needed sums of money. National outlays for COVID-19 mitigation and vaccination amounted to 2% of GDP, with one-third funded by external donors. Service delivery innovations helped sustain access to HIV treatment during national lockdowns. As a result of reduced access to HIV testing, the number of people initiating HIV treatment declined. In the short term, there are likely to be few immediate health care consequences of the slowdown in treatment initiation due to the country’s already high level of HIV treatment coverage. However, a longer-lasting slowdown could impede national progress towards ending HIV and AIDS. The findings suggest a need to finance the global commons, specifically recognising that investing in health care is investing in economic recovery.

Objectives: Sex work sites have been hypothesised to be at the root of the observed heterogeneity in HIV prevalence in sub-Saharan Africa. We determined if proximity to sex work sites is associated with HIV prevalence among the general population in Zimbabwe, a country with one of the highest HIV prevalence in the world. Methods: In this cross-sectional study we use a unique combination of nationally representative geolocated individual-level data from 16,121 adults (age 15–49 years) from 400 sample locations and the locations of 55 sex work sites throughout Zimbabwe; covering an estimated 95% of all female sex workers (FSWs). We calculated the shortest distance by road from each survey sample location to the nearest sex work site, for all sites and by type of sex work site, and conducted univariate and multivariate multilevel logistic regressions to determine the association between distance to sex work sites and HIV seropositivity, controlling for age, sex, male circumcision status, number of lifetime sex partners, being a FSW client or being a stable partner of an FSW client. Results: We found no significant association between HIV seroprevalence and proximity to the nearest sex work site among the general population in Zimbabwe, regardless of which type of site is closest (city site adjusted odds ratio [aOR] 1.010 [95% confidence interval {CI} 0.992–1.028]; economic growth point site aOR 0.982 [95% CI 0.962–1.002]; international site aOR 0.995 [95% CI 0.979–1.012]; seasonal site aOR 0.987 [95% CI 0.968–1.006] and transport site aOR 1.007 [95% CI 0.987–1.028]). Individual-level indicators of sex work were significantly associated with HIV seropositivity: being an FSW client (aOR 1.445 [95% CI 1.188–1.745]); nine or more partners versus having one to three lifetime partners (aOR 2.072 [95% CI 1.654–2.596]). Conclusions: Sex work sites do not seem to directly affect HIV prevalence among the general population in surrounding areas. Prevention and control interventions for HIV at these locations should primarily focus on sex workers and their clients, with special emphasis on including and retaining mobile sex workers and clients into services.

HIV modelling and economic analyses have had a prominent role in guiding programmatic responses to HIV in sub-Saharan Africa. We reflect critically how the HIV modelling field might develop in future. We argue for HIV modelling to be more routinely aligned with national government and ministry of health priorities, recognizing their legitimate mandates and stewardship responsibilities, for HIV and other wider health programmes. We also place importance on an environment existing in which collaboration between modellers, and joint approaches to addressing modelling questions, becomes the norm rather than exception. Such an environment can accelerate translation of modelling analyses into policy formulation because areas where models agree can be prioritized for action, whereas areas over which uncertainty prevails can be slated for additional study, data collection and analysis. We also argue the need for HIV modelling to increasingly be integrated with the modelling of health needs beyond HIV, particularly in allocative efficiency analyses, where focusing on one disease over another may lead to worse health overall. Such integration may also enhance partnership with national governments whose mandates extend beyond HIV and to all of health care. Finally, we see a need for there to be substantial and equitable investment in capacity strengthening within African countries, so that African researchers will increasingly be leading modelling exercises. Building a critical mass of expertise, strengthened through external collaboration and knowledge exchange, should be the ultimate goal.