Characterizing and mapping the spatial variability of HIV risk among adolescent girls and young women: A cross-county analysis of population-based surveys in Eswatini, Haiti, and Mozambique.

BACKGROUND: To stem the HIV epidemic among adolescent girls and young women (AGYW), prevention programs must target services towards those most at risk for HIV. This paper investigates approaches to estimate HIV risk and map the spatial heterogeneity of at-risk populations in three countries: Eswatini, Haiti and Mozambique. METHODS: We analyzed HIV biomarker and risk factor data from recent population-based household surveys. We characterized risk using three approaches: complementary log-log regression, latent class analysis (LCA), and presence of at least one risk factor. We calculated the proportion and 95 percent confidence intervals of HIV-negative AGYW at risk across the three methods and employed Chi-square tests to investigate associations between risk classification and HIV status. Using geolocated survey data at enumeration clusters and high-resolution satellite imagery, we applied algorithms to predict the number and proportion of at-risk AGYW at hyperlocal levels. RESULTS: The any-risk approach yielded the highest proportion of at-risk and HIV-negative AGYW across five-year age bands: 26%-49% in Eswatini, 52%-67% in Haiti, and 32%-84% in Mozambique. Using LCA, between 8%-16% of AGYW in Eswatini, 37%-62% in Haiti, and 56%-80% in Mozambique belonged to a high vulnerability profile. In Haiti and Mozambique, the regression-based profile yielded the lowest estimate of at-risk AGYW. In general, AGYW characterized as "at risk" across the three methods had significantly higher odds of HIV infection. Hyperlocal maps indicated high levels of spatial heterogeneity in HIV risk prevalence and population density of at-risk AGYW within countries. CONCLUSION: Characterizing risk among AGYW can help HIV prevention programs better understand the differential effect of multiple risk factors, facilitate early identification of high-risk AGYW, and design tailored interventions. Hyperlocal mapping of these at-risk populations can help program planners target prevention interventions to geographic areas with populations at greatest risk for HIV to achieve maximal impact on HIV incidence reduction.

Characterizing and mapping the spatial variability of HIV risk among adolescent girls and young women: A cross-county analysis of population-based surveys in Eswatini, Haiti, and Mozambique

Background: To stem the HIV epidemic among adolescent girls and young women (AGYW), prevention programs must target services towards those most at risk for HIV. This paper investigates approaches to estimate HIV risk and map the spatial heterogeneity of at-risk populations in three countries: Eswatini, Haiti and Mozambique. Methods: We analyzed HIV biomarker and risk factor data from recent population-based household surveys. We characterized risk using three approaches: complementary log-log regression, latent class analysis (LCA), and presence of at least one risk factor. We calculated the proportion and 95 percent confidence intervals of HIV-negative AGYW at risk across the three methods and employed Chi-square tests to investigate associations between risk classification and HIV status. Using geolocated survey data at enumeration clusters and high-resolution satellite imagery, we applied algorithms to predict the number and proportion of at-risk AGYW at hyperlocal levels. Results: The any-risk approach yielded the highest proportion of at-risk and HIV-negative AGYW across five-year age bands: 26%-49% in Eswatini, 52%-67% in Haiti, and 32%-84% in Mozambique. Using LCA, between 8%-16% of AGYW in Eswatini, 37%-62% in Haiti, and 56%-80% in Mozambique belonged to a high vulnerability profile. In Haiti and Mozambique, the regression-based profile yielded the lowest estimate of at-risk AGYW. In general, AGYW characterized as "at risk" across the three methods had significantly higher odds of HIV infection. Hyperlocal maps indicated high levels of spatial heterogeneity in HIV risk prevalence and population density of at-risk AGYW within countries. Conclusion: Characterizing risk among AGYW can help HIV prevention programs better understand the differential effect of multiple risk factors, facilitate early identification of high-risk AGYW, and design tailored interventions. Hyperlocal mapping of these at-risk populations can help program planners target prevention interventions to geographic areas with populations at greatest risk for HIV to achieve maximal impact on HIV incidence reduction.

Multipurpose prevention technologies for sexual and reproductive health: mapping global needs for introduction of new preventive products.

OBJECTIVES: Worldwide, women face sexual and reproductive health (SRH) risks including unintended pregnancy and sexually transmitted infections (STIs) including HIV. Multipurpose prevention technologies (MPTs) combine protection against two or more SRH risks into one product. Male and female condoms are the only currently available MPT products, but several other forms of MPTs are in development. We examined the global distribution of selected SRH issues to determine where various risks have the greatest geographical overlap. STUDY DESIGN: We examined four indicators relevant to MPTs in development: HIV prevalence, herpes simplex virus type 2 prevalence (HSV-2), human papillomavirus prevalence (HPV) and the proportion of women with unmet need for modern contraception. Using ArcGIS Desktop, we mapped these indicators individually and in combination on choropleth and graduated symbol maps. We conducted a principal components analysis to reduce data and enable visual mapping of all four indicators on one graphic to identify overlap. RESULTS: Our findings document the greatest overlapping risks in Sub-Saharan Africa, and we specify countries in greatest need by specific MPT indication. CONCLUSIONS: These results can inform strategic planning for MPT introduction, market segmentation and demand generation; data limitations also highlight the need for improved (non-HIV) STI surveillance globally. IMPLICATIONS: MPTs are products in development with the potential to empower women to prevent two or more SRH risks. Geographic analysis of overlapping SRH risks demonstrates particularly high need in Sub-Saharan Africa. This study can help to inform strategic planning for MPT introduction, market segmentation and demand generation.

Idle chatter or learning? Evidence of social learning about clinicians and the health system from rural Tanzania.

We examine data from the rural Arusha region in Tanzania in which households are asked to recall the illness episodes of randomly chosen other households in their village. We interviewed 502 randomly selected households from 22 villages in 20 wards of Arusha. We analyze the probability that a household can recall another illness episode as a function of the characteristics of the illness, the location and type of health care chosen and the outcome experienced. We found that households are more likely to recall severe illnesses, illnesses for which good quality care is important, illnesses that resulted in visits to hospitals and illnesses when the patient was not cured. In addition, households are more likely to recall illnesses that resulted in a visit to a facility where the average tenure of clinicians is less than two years. The results suggest that households deliberately collect information in order to learn about clinicians and facilities in their local area. We show evidence that households use this information when they choose whether to visit new health care providers. In particular, households are less likely to visit a new provider when they hear of bad outcomes and more likely to do so when they hear of good outcomes.