Towards UNAIDS Fast-Track goals: targeting priority geographic areas for HIV prevention and care in Zimbabwe

Moving beyond hotspots of HIV prevalence to geospatial hotspots of UNAIDS 95-95-95 targets in sub-Saharan Africa

The HIV epidemic in sub-Saharan Africa displays a varied geographical distribution, with particular regions termed as HIV hotspots due to a higher prevalence of infection. Addressing these hotspots is essential for controlling the epidemic. However, these regions, influenced by historical factors, challenge standard interventions. Legacy effects-the lasting impact of past events-play a substantial role in the persistence of these hotspots. To address this challenge of the standard interventions, we propose a shift towards the UNAIDS 95-95-95 targets. Spatial analysis of HIV viral load and antiretroviral therapy coverage can provide a more comprehensive perspective on the epidemic's dynamics. Studies in Zambia and Zimbabwe, using this approach, have revealed disparities in HIV care metrics across regions. By focusing on the UNAIDS 95-95-95 targets, more effective control strategies can be designed, with consideration of both historical and current factors. This approach would offer a solution-oriented strategy, emphasising tailored interventions based on specific regional needs.

Spatial heterogeneity in relationship between district patterns of HIV incidence and covariates in Zimbabwe: a multi-scale geographically weighted regression analysis

A study was conducted to investigate the district-level patterns of incidence of the human immunodeficiency virus (HIV) in Zimbabwe in the period 2005-2015 and explore variations in the relationship between covariates and HIV incidence across different districts. Demographic health survey data were analysed using hotspot analysis, spatial autocorrelation, and multi-scale geographically weighted regression (MGWR) techniques. The analysis revealed hotspots of the HIV epidemic in the southern and western regions of Zimbabwe in contrast to the eastern and northern regions. Specific districts in Matabeleland South and Matabeleland North provinces showed clusters of HIV incidence in 2005-2006, 2010-2011 and 2015. Variables studied were multiple sex partners and sexually transmitted infections (STI) condom use and being married. Recommendations include implementing targeted HIV prevention programmes in identified hotspots, prioritising interventions addressing the factors mentioned above as well as enhancing access to HIV testing and treatment services in high-risk areas, strengthening surveillance systems, and conducting further research to tailor interventions based on contextual factors. The study also emphasizes the need for regular monitoring and evaluation at the district level to inform effective responses to the HIV epidemic over time. By addressing the unique challenges and risk factors in different districts, significant progress can be made in reducing HIV transmission and improving health outcomes in Zimbabwe. These findings should be valuable for policymakers in resource allocation and designing evidence-based interventions.

Progress Towards UNAIDS's 95-95-95 Targets in Zimbabwe: Sociodemographic Constraints and Geospatial Heterogeneity

The HIV/AIDS epidemic remains critical in sub-Saharan Africa, with UNAIDS establishing "95-95-95" targets to optimize HIV care. Using the Zimbabwe Population-based HIV Impact Assessment (ZIMPHIA) geospatial data, this study aimed to identify patterns in these targets and determinants impacting the HIV care continuum in underserved Zimbabwean communities. Analysis techniques, including Gaussian kernel interpolation, optimized hotspot, and multivariate geospatial k-means clustering, were utilized to establish spatial patterns and cluster regional HIV care continuum needs. Further, we investigated healthcare availability, access, and social determinants and scrutinized the association between socio-demographic and behavioral covariates with HIV care outcomes. Disparities in progress toward the "95-95-95" targets were noted across different regions, with each target demonstrating unique geographic patterns, resulting in four distinct clusters with specific HIV care needs. Key factors associated with gaps in achieving targets included younger age, male sex, employment, and minority or no religious affiliation. Our study uncovers significant spatial heterogeneity in the HIV care continuum in Zimbabwe, with unique regional patterns in "95-95-95" targets. The spatial analysis of the UNAIDS targets presented here could prove instrumental in designing effective control strategies by identifying vulnerable communities that are falling short of these targets and require intensified efforts. Our result provides insights for designing region-specific interventions and enhancing community-level factors, emphasizing the need to address regional gaps and improve HIV care outcomes in vulnerable communities lagging behind.

Geospatial assessment of the convergence of communicable and non-communicable diseases in South Africa

Introduction

Several low-and middle-income countries are undergoing rapid epidemiological transition with a rising burden of non-communicable diseases (NCDs). South Africa (SA) is a country with one of the largest HIV epidemics worldwide and a growing burden of NCDs where the collision of these epidemics poses a major public health challenge.

Methods

Using data from a large nationally representative survey, the South Africa Demographic and Health Survey (SADHS 2016), we conducted a geospatial analysis of several diseases including HIV, tuberculosis (TB), cardiovascular, respiratory, and metabolic diseases to identify areas with a high burden of co-morbidity within the country. We explored the spatial structure of each disease and associations between diseases using different spatial and visual data methodologies. We also assessed the individual level co-occurrence of HIV and the other diseases included in the analysis.

Results

The spatial distribution for HIV prevalence showed that this epidemic is most intense in the eastern region of the country, mostly within the Gauteng, Mpumalanga, and Kwazulu-Natal provinces. In contrast, chronic diseases had their highest prevalence rates the southern region of the country, particularly in the Eastern and Western Cape provinces. Individual-level analyses were consistent with the spatial correlations and found no statistically significant associations between HIV infection and the presence of any NCDs.

Conclusions

We found no evidence of geospatial overlap between the HIV epidemic and NCDs in SA. These results evidence the complex epidemiological landscape of the country, characterized by geographically distinct areas exhibiting different health burdens. The detailed description of the heterogenous prevalence of HIV and NCDs in SA reported in this study could be a useful tool to inform and direct policies to enhance targeted health service delivery according to the local health needs of each community.

Review of antiretroviral therapy coverage in 10 highest burden HIV countries in Africa: 2015-2020

Africa is responsible for two-thirds of the global total of new HIV infections. South Africa, Nigeria, Mozambique, Uganda, Tanzania, Zambia, Zimbabwe, Kenya, Malawi, and Ethiopia were responsible for 80% of HIV cases in Africa in 2014 according to the Joint United Nations Programme on HIV/AIDS (UNAIDS). This study assesses antiretroviral coverage strategies implemented by these countries after the initiation of the "Fast-Track strategy to end the AIDS epidemic by 2030." Data reported in this review were obtained from different e-bibliographic including PubMed, Google Scholar, and Research Gate. Key terms were "Antiretroviral therapy," "Antiretroviral treatment," "HIV treatment," "HIV medication," "HIV/AIDS therapy," "HIV/AIDS treatment" + each of the countries listed earlier. We also extracted data on antiretroviral therapy (ART) coverage from the UNAIDS database. About 50 papers published from 2015 to 2021 met the inclusion criteria. All 10 countries have experienced an increase in ART coverage from 2015 to 2020 with an average of 47.6% increment. Nigeria recorded the highest increase in the rate of ART coverage (72% increase) while Ethiopia had the least (30%). New strategies adopted to increase ART coverage and retention in most countries were community-based models and the use of mobile health technology rather than clinic-based. These strategies focus on promoting task shifting, door-to-door access to HIV services, and a long-term supply of antiretroviral medications. Most of these strategies are still in the piloting stage. However, some new strategies and frameworks have been adopted nationwide in countries like Mozambique, Tanzania, Zambia, Zimbabwe, Kenya, and Malawi. Identified challenges include lack of funding, inadequate testing and surveillance services, poor digital penetration, and cultural/religious beliefs. The adoption of community-based and digital health strategies could have contributed to increased ART coverage and retention. African countries should facilitate nationwide scaling of ART coverage strategies to attain the 95-95-95 goal by 2030.

Progress Toward the 90-90-90 HIV Targets in Zimbabwe and Identifying Those Left Behind

OBJECTIVE

We present findings from the nationally representative Zimbabwe Population-based HIV Impact Assessment that characterize Zimbabwe's progress toward the Joint United Nations Programme on HIV/AIDS 90-90-90 targets.

DESIGN

We conducted a cross-sectional household survey.

METHODS

Consenting adults and children in the household were eligible to participate in Zimbabwe Population-based HIV Impact Assessment (October 2015-August 2016). Participants completed face-to-face interviews and provided blood for HIV, CD4, viral load, and syphilis testing. Viral load suppression (VLS) was defined as HIV RNA <1000 copies/mL. HIV-positive specimens were tested for the presence of selected antiretroviral drugs. Data were weighted. Analysis was restricted to HIV-positive adults aged 15-64 years.

RESULTS

We enrolled 11,098 men and 14,033 women aged 15-64 years. HIV prevalence was 14.1%. Of those living with HIV, 76.8% (95% confidence interval [CI]: 74.9 to 78.7) were aware of their HIV status or had detectable antiretroviral levels. Of these, 88.4% (95% CI: 87.1 to 89.7) were receiving antiretroviral therapy (ART), and of these people, 85.3% (95% CI: 83.4 to 87.1) had VLS. Male sex age 15-34 years and having 1 or more sexual partners were associated with being unaware of one's HIV-positive status. Age <50 years and not taking cotrimoxazole were associated with being less likely to be being both aware and taking ART. Male sex, age <50 years, and taking cotrimoxazole were associated with being on ART but not having VLS.

CONCLUSIONS

Zimbabwe has made great strides toward epidemic control. Focusing resources on case finding, particularly among men, people aged <35 years, and sexually active individuals can help Zimbabwe attain 90-90-90 targets.

Associated health and social determinants of mobile populations across HIV epidemic gradients in Southern Africa

Background

Growing travel connectivity and economic development have dramatically increased the magnitude of human mobility in Africa. In public health, vulnerable population groups such as mobile individuals are at an elevated risk of sexually transmitted diseases, including HIV.

Methods

The population-based Demographic Health Survey data of five Southern African countries with different HIV epidemic intensities (Angola, Malawi, South Africa, Zambia, and Zimbabwe) were used to investigate the association between HIV serostatus and population mobility adjusting for socio-demographic, sexual behavior and spatial covariates.

Results

Mobility was associated with HIV seropositive status only in Zimbabwe (adjusted odds ratio [AOR] = 1.37 [95% confidence interval [CI]: 1.01–1.67]). These associations were not significant in Angola, Malawi, South Africa, and Zambia. Females had higher odds of mobility than males in Zimbabwe (AOR = 1.37, CI: 1.10–1.69). The odds of mobility decreased with age in all five countries.

Conclusions

Our findings highlight the heterogeneity of the social and health determinants of mobile populations in several countries with different HIV epidemic intensities. Effective interventions using precise geographic focus combined with detailed attribute characterization of mobile populations can enhance their impact especially in areas with high density of mobile individuals and high HIV prevalence.

Beyond HIV prevalence: identifying people living with HIV within underserved areas in South Africa

INTRODUCTION

Despite progress towards the Joint United Nations Programme on HIV/AIDS 95-95-95 targets, South Africa is still suffering from one of the largest HIV epidemics globally. In this study, we generated high-resolution HIV prevalence maps and identified people living with HIV (PLHIV) in underserved areas to provide essential information for the optimal allocation of HIV-related services.

METHODS

The data come from the South Africa Demographic and Health Survey conducted in 2016 and spatial variables from other published literature. We produced high-resolution maps of HIV prevalence and underserved areas, defined as a greater than 30 min travel time to the nearest healthcare facility. Using these maps and the population density, we mapped PLHIV and the PLHIV within underserved areas for 30, 60 and 120 min thresholds.

RESULTS

There was substantial geographic variation in HIV prevalence, ranging from 1.4% to 24.2%, with a median of 11.5% for men, and from 2.1% to 48.1%, with a median of 20.6% for women. Gauteng province showed the highest density for both HIV prevalence and PLHIV. 80% of all areas in the country were identified as underserved areas (30 min threshold), which contained more than 16% and 20% of the total men and women living with HIV, respectively. KwaZulu-Natal province had the largest number of PLHIV in underserved areas (30 min threshold) and showed less than one healthcare facility per 1000 PLHIV.

CONCLUSION

Our study showed extensive spatial variation of HIV prevalence and significant numbers of PLHIV in underserved areas in South Africa. Moreover, we identified locations where HIV-related services need to be intensified to reach the ~1.5 million PLHIV in underserved areas, particularly in KwaZulu-Natal province, with less than one healthcare facility per 1000 PLHIV.

Epidemiological characterization and geographic distribution of human immunodeficiency virus/acquired immunodeficiency syndrome infection in North African countries

BACKGROUND

Human immunodeficiency virus (HIV) infection is a major global public health concern. North African countries carry a disproportionate burden of HIV representing one of the highest rates in Africa.

AIM

To characterize the epidemiological and spatial trends of HIV infection in this region.

METHODS

A systematic review was carried out on all the published data regarding HIV/acquired immunodeficiency syndrome in North African countries over ten years (2008-2017) following the PRISMA guidelines. We performed a comprehensive literature search using Medline PubMed, Embase, regional and international databases, and country-level reports with no language restriction. The quality, quantity, and geographic coverage of the data were assessed at both the national and regional levels. We used random-effects methods, spatial variables, and stratified results by demographic factors. Only original data on the prevalence of HIV infection were included and independently evaluated by professional epidemiologists.

RESULTS

A total of 721 records were identified but only 41 that met the criteria were included in the meta-analysis. There was considerable variability in the prevalence estimates of HIV within the countries of the region. The overall prevalence of HIV ranged from 0.9% [95% confidence interval (CI) 0.8-1.27] to 3.8% (95%CI 1.17-6.53). The highest prevalence was associated with vulnerable groups and particularly drug abusers and sexually promiscuous individuals. The dense HIV clustering noted varied from one country to another. At least 13 HIV subtypes and recombinant forms were prevalent in the region. Subtype B was the most common variant, followed by CRF02_AG.

CONCLUSION

This comprehensive review indicates that HIV infection in North African countries is an increasing threat. Effective national and regional strategies are needed to improve monitoring and control of HIV transmission, with particular emphasis on geographic variability and HIV clustering.

A feasibility study to assess Imbrasia belina (mopane worm) sensitisation and related respiratory health outcomes in a rural community in Gwanda district, Zimbabwe

Background

Allergic diseases are considered to be some of the fastest growing chronic conditions in Africa. Of concern is the paucity of knowledge about the local environment and its role in allergic disease development. In response to this, we explored whether Imbrasia belina, a popular indigenous edible insect commonly known as mopane worm, is a potential allergen of clinical and public health significance in Zimbabwe. This study was intended to assess the plausibility and feasibility of this hypothesis with a view to evaluate the insect’s health impact in a larger study.

Methods

The study participants included male and female villagers aged 10 years and above in Gwanda district, Zimbabwe. Eligible participants who completed the household questionnaire were referred to the local clinic for skin prick tests and to measure lung function and allergic airway inflammation. Allergen sensitisation patterns were evaluated using 10 different inhalant allergen extracts including an in-house preparation of mopane worm. Lung function was measured with a Koko Legend spirometer, and fractional exhaled nitric oxide levels (FeNO) (NIOX VERO) were measured in participants with at least one abnormal spirometric parameter. Data was analysed using Stata version 13 software.

Results

Of the 46 eligible participants that completed the household questionnaire, 17 went to the clinic giving a response rate of 37%. The majority who completed the questionnaire were adults (91%) and the children (9%) were all female. The prevalence of sensitisation to Imbrasia belina was 50%, and the prevalence ranged from 22 to 72% for the other allergens including cockroach, mosquito and house dust mites. The data collection tools were safe and well tolerated by participants with no adverse events reported. Self-reported respiratory symptoms, abnormal lung function and elevated FeNO were recorded amongst participants sensitised to mopane worm.

Conclusion

Pre-defined feasibility criteria were met with the exception of a lower than expected response rate for clinic data collection in this pilot study. For the main study, modifying the sampling strategy and applying more consistent community engagement will improve the response rates.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40814-021-00780-9.

Is It the Timing? Short-Term Mobility and Coital Frequency in Agbogbloshie, Ghana

Short-term mobility is often associated with increased sexual risk behavior. Mobile individuals often have higher rates of sexual risk behavior compared to non-mobile individuals, but the reasons why are not clear. Using monthly retrospective panel data from 202 men and 282 women in Agbogbloshie, Ghana, we tested whether short-term mobility was associated with changes in coital frequency, and whether the association was due to the act of travel in the given month (e.g., enabling higher risk behavior), the reason for travel, or an individual's travel propensity at other times in the year. Overnight travel specifically to visit family or friends, or for education, health, or other reasons, was associated with increased coital frequency for men. However, men with higher travel propensities had lower overall coital frequency and the act of traveling enabled more sex only for the most frequent male travelers. Men who seldom traveled had much higher coital frequency, but the act of traveling was not associated with additional sex acts. For women, travel for education, health, or other reasons increased coital frequency. Occasional female travelers had slightly more sex acts compared to non-mobile women, and the act of traveling for these women was associated with slight increases in coital frequency, supporting the enabling hypothesis. Highly mobile women had fewer sex acts per month on average. Our findings suggest that mobility characteristics measured on a broad temporal scale, as well as the reason for mobility, are important to understand the relationship between short-term mobility and sexual behavior.

When distance matters: Mapping HIV health care underserved communities in sub-Saharan Africa

Despite efforts to increase the proportion of individuals diagnosed with HIV who receive anti-retroviral therapy, 28% of people living with HIV (PLHIV) aged 15 years and older in eastern and southern Africa and 42% in western and central Africa were not receiving anti-retroviral therapy in 2019. Therefore, improving access to health care services is key to reduce HIV incidence and prevalence. The main aim of this study was to generate high-resolution maps of underserved areas where people cannot access the closest health care facilities within appropriate travel time in sub-Saharan Africa (SSA). Main sources of data for this study were the estimated number of PLHIV for adults aged 15-49 years in 47 countries in SSA and the global map of travel time to the nearest health care facility by motorized and non-motorized transportation. These data were used to estimate and map the number of PLHIV in underserved areas at a travel distance of 10, 30, and 60 minutes from the nearest healthcare facility. We identified and mapped more than 7 million PLHIV in the areas with a lack of access to health care within 10-minute travel time and 1.5 million PLHIV in the areas with a lack of access to health care within 60-minute travel time. The identified locations of underserved areas are an indicator of the challenge faced by PLHIV in accessing health services in SSA, a situation that is likely worsened by the COVID-19 pandemic. These findings can contribute to developing cost-effective geospatial policies for interventions aimed at underserved areas at a finer resolution for communities that have usually been identified in aggregated spatial areas. Further development and implementation of tailored intervention and treatment programs, especially in areas identified as underserved for PLHIV, should be explored. Geospatial analyses could complement the decision-making process with stakeholders to enhance healthcare access for PLHIV in SSA.

Predictors of high HIV+ prevalence in Mozambique: A complex samples logistic regression modeling and spatial mapping approaches

Introduction

The burden of HIV infection in southern Africa is a public health concern with an increasing number of new infections. This study sought to investigate the predictors of HIV prevalence in Mozambique through a complex samples logistic regression and spatial mapping approach using nationally representative data.

Methods

We conducted a secondary data analysis using the 2015 Mozambique Demographic and Health Survey and AIDS Indicator Survey. The analysis performed in four stages while incorporating population survey sampling weights did the following: i) created a complex sample plan file in SPSS, ii) performed the weighted estimate of HIV prevalence, iii) performed complex sample chi-square test of independence, and then iv) performed complex sample logistic regression modeling.

Results

Out of 11,270 participants, 1,469 (13.0%) tested positive for HIV. The prevalence of HIV infection was higher in females (15.1%) than males (10.2%). We found that urban dwellers were more likely to be HIV-positive compared to rural dwellers (AOR: 1.70; CI: 1.27, 2.27). We observed provincial variations in HIV prevalence, with Maputo Cidade (17.4%), Maputo Provincia (22.6%), Gaza (25.2%) recording higher prevalence above the national estimate. Other independent predictors of HIV infection in Mozambique included age, education level, marital status, total lifetime sexual partners, and having had an STI in the last 12 months.

Conclusions

The study revealed associations between high-risk sexual behavior and HIV infection. Results from our spatial mapping approach can help health policy makers to better allocate resources for cost-effective HIV/AIDS interventions. Pre-Exposure Prophylaxis (PrEP) campaigns among high-risk groups should be pursued to lower the reservoir of HIV among high-risk groups.

Migration, hotspots, and dispersal of HIV infection in Rakai, Uganda

HIV prevalence varies markedly throughout Africa, and it is often presumed areas of higher HIV prevalence (i.e., hotspots) serve as sources of infection to neighboring areas of lower prevalence. However, the small-scale geography of migration networks and movement of HIV-positive individuals between communities is poorly understood. Here, we use population-based data from ~22,000 persons of known HIV status to characterize migratory patterns and their relationship to HIV among 38 communities in Rakai, Uganda with HIV prevalence ranging from 9 to 43%. We find that migrants moving into hotspots had significantly higher HIV prevalence than migrants moving elsewhere, but out-migration from hotspots was geographically dispersed, contributing minimally to HIV burden in destination locations. Our results challenge the assumption that high prevalence hotspots are drivers of transmission in regional epidemics, instead suggesting that migrants with high HIV prevalence, particularly women, selectively migrate to these areas.

HIV transmission and source-sink dynamics in sub-Saharan Africa

Multiple phylogenetic studies of HIV in sub-Saharan Africa have shown that mobility-driven transmission frequently occurs: many communities export and import strains. Mobility-driven transmission can result in source-sink dynamics: one community can sustain a micro-epidemic in another community in which transmission is too low to be self-sustaining. In epidemiology, the basic reproduction number (R₀) is used to specify the sustainability threshold. R₀ represents the average number of secondary infections generated by one infected individual in a community in which everyone is susceptible. If R₀ is greater than 1, transmission is high enough to sustain an epidemic; if R₀ is less than 1, it is not. Here, we discuss the conditions that are needed (in terms of R₀) for source-sink transmission dynamics to occur in generalised HIV epidemics in sub-Saharan Africa, present an example of where these conditions could occur (ie, Namibia), and discuss the necessity of considering mobility-driven transmission when designing control strategies. Additionally, we discuss the need for a new generation of HIV transmission models that are more realistic than the current models. The new models should reflect not only geographical variation in epidemiology and demography, but also the spatial-temporal complexity of population-level movement patterns.

Why and where an HIV cure is needed and how it might be achieved

Despite considerable global investment, only 60% of people who live with HIV currently receive antiretroviral therapy. The sustainability of current programmes remains unknown and key incidence rates are declining only modestly. Given the complexities and expenses associated with lifelong medication, developing an effective curative intervention is now a global priority. Here we review why and where a cure is needed, and how it might be achieved. We argue for expanding these efforts from resource-rich regions to sub-Saharan Africa and elsewhere: for any intervention to have an effect, region-specific biological, therapeutic and implementation issues must be addressed.

Optimal allocation of HIV resources among geographical regions

BACKGROUND

Health resources are limited, which means spending should be focused on the people, places and programs that matter most. Choosing the mix of programs to maximize a health outcome is termed allocative efficiency. Here, we extend the methodology of allocative efficiency to answer the question of how resources should be distributed among different geographic regions.

METHODS

We describe a novel geographical optimization algorithm, which has been implemented as an extension to the Optima HIV model. This algorithm identifies an optimal funding of services and programs across regions, such as multiple countries or multiple districts within a country. The algorithm consists of three steps: (1) calibrating the model to each region, (2) determining the optimal allocation for each region across a range of different budget levels, and (3) finding the budget level in each region that minimizes the outcome (such as reducing new HIV infections and/or HIV-related deaths), subject to the constraint of fixed total budget across all regions. As a case study, we applied this method to determine an illustrative allocation of HIV program funding across three representative oblasts (regions) in Ukraine (Mykolayiv, Poltava, and Zhytomyr) to minimize the number of new HIV infections.

RESULTS

Geographical optimization was found to identify solutions with better outcomes than would be possible by considering region-specific allocations alone. In the case of Ukraine, prior to optimization (i.e. with status quo spending), a total of 244,000 HIV-related disability-adjusted life years (DALYs) were estimated to occur from 2016 to 2030 across the three oblasts. With optimization within (but not between) oblasts, this was estimated to be reduced to 181,000. With geographical optimization (i.e., allowing reallocation of funds between oblasts), this was estimated to be further reduced to 173,000.

CONCLUSIONS

With the increasing availability of region- and even facility-level data, geographical optimization is likely to play an increasingly important role in health economic decision making. Although the largest gains are typically due to reallocating resources to the most effective interventions, especially treatment, further gains can be achieved by optimally reallocating resources between regions. Finally, the methods described here are not restricted to geographical optimization, and can be applied to other problems where competing resources need to be allocated with constraints, such as between diseases.