Spatial and social inequities in HIV testing utilization in the context of rapid scale-up of HIV/AIDS services in rural Mozambique

Abstract

The massive scale-up of HIV counseling, testing, and treatment services in resource-limited sub-Saharan settings with high HIV prevalence has significant implications for the course of the HIV/AIDS epidemic. It also offers important broader policy lessons for improving access to critical health services. Applying GIS-based methods and multilevel regression analysis to unique longitudinal three-wave survey data from rural Mozambique, this study investigates the impact of a rapid expansion of HIV-related services on access to and utilization of HIV testing. The results illustrate the declining importance of spatial barriers to utilization of HIV testing services as these services expanded. In addition, the expansion of HIV-related services decreased the spatial variability of HIV testing among the survey respondents. At the same time, some important non-spatial variation, such as that in educational level, persisted despite the expansion of services. These results illustrate the process and consequences of health service diffusion.

Gendered relationship between HIV stigma and HIV testing among men and women in Mozambique: a cross-sectional study to inform a stigma reduction and male-targeted HIV testing intervention

“…Low awareness of one’s status is likely attributable to low HIV testing rates; in 2015, only 38% of men participating in the Demographic Health Survey (DHS) reported any history of HIV testing and only 19% had been tested within the last 12 months, compared with 31% among women 15. HIV testing services have expanded substantially across the country over the last decade and, with improved access, geographic information systems data mapped to serial cross-sectional surveys among women have found that distance to HIV testing services is no longer a barrier to HIV testing at the regional level 19. As such structural barriers are minimised, additional research to understand lingering barriers to HIV testing—the first entry point to HIV prevention and care continua—is needed.…”

How to allocate limited healthcare resources: Lessons from the introduction of antiretroviral therapy in rural Mozambique

“…Many studies have demonstrated the value of using wealth-based indicators to rank households based on asset or wealth (Filmer and Pritchett, 1999; Khan et al, 2006; Flimer and Kinnon, 2012; Giesbert and Schindler, 2012; Yao et al, 2014). We use detailed information on dwelling conditions, access to electricity and water, access to a latrine, and asset ownership to generate a composite measure of economic well-being using PCA, based on weights derived from the first component in the PCA.…”

“…The use of these services as a proxy is justified by the high fertility rates observed across villages in the study (Yao et al, 2012), which suggest that the quality of services offered is most likely to be distributed based upon maternal need. It is important to note that while the majority of services examined in the quality measure are MCH-specific, the health clinics do have the ability to offer general services to the public (i.e., males may also be seen at these clinics) as these health clinics represent the only type of health facility immediately available to rural residents (Yao et al, 2014). …”

“…We consider multiple measures of access for this analysis, using distance to nearest clinic, distance to nearest clinic offering ART, and average quality of surrounding clinics. Cost is not considered a barrier to access in this study because of the commitment made by the Mozambican government to provide ART for free through state-run clinics (WHO, 2007; Yao et al, 2014). To examine the potential implications of limited resources, we construct a village-specific quality score comprised of available resources for each clinic that is then weighted by its distance from the village.…”

Finding Hidden HIV Clusters to Support Geographic-Oriented HIV Interventions in Kenya

“…Spatial clustering patterns may exist in relation to physical geographical features: for example, a road or railway network, commercial activity such as large farms and their positioning or proximity of clusters to such features. Cluster analysis and mapping may be used to identify “micro-epidemics” in certain geographic areas such as rural communities, 14 populations at higher risk of HIV infection, 15 demonstrate decline in HIV prevalence, 16 key populations such as female sex workers (FSWs), 17 and for assessing access to HIV-related services such as HIV testing and counseling 18 , 19 or provision of antiretroviral treatment. 20 In addition, mapping may be used for allocation of targets, 7 thereby improving efficiencies in resource allocation.…”