Exploring the validity of routine individuated service data for antenatal HIV surveillance in the Western Cape

In the Western Cape, South Africa, public-sector individual-level routine data are consolidated from multiple sources through the Provincial Health Data Centre (PHDC). This enables the description of temporal changes in population-wide antenatal HIV seroprevalence. We evaluated the validity of these data compared to aggregated program data and population-wide sentinel antenatal HIV seroprevalence surveys for the Western Cape province.

We conducted a retrospective cohort analysis of all pregnancies identified in the PHDC from January 2011 to December 2020. Evidence of antenatal and HIV care from electronic platforms were linked using a unique patient identifier. HIV prevalence estimates were triangulated and compared with available survey estimates and aggregated programmatic data from registers as recorded in the District Health Information System. Provincial, district-level and age-group HIV prevalence estimates were compared between data systems using correlation coefficients, absolute differences and trend analysis.

Of the 977800 pregnancies ascertained, PHDC HIV prevalence estimates from 2011-2013 were widely disparate from aggregate and survey data (due to incomplete electronic data), whereas from 2014 onwards, estimates were within the 95% confidence interval of survey estimates, and closely correlated to aggregate data estimates (r = 0.8; p = 0.01), with an average prevalence difference of 0.4%. PHDC data show a slow but steady increase in provincial HIV prevalence from 16.7% in 2015 to 18.6% in 2020. The highest HIV prevalence was in the Cape Metro district (20.3%) Prevalence estimates by age group were comparable between sentinel surveys and PHDC from 2015 onwards, with prevalence estimates stable over time among younger age-groups (15-24 years) but increased among older age-groups (> 34 years).

This study compares sentinel seroprevalence surveys with both register-based aggregate data and consolidated individuated administrative data. We show that in this setting linked individuated data may be reliably used for HIV surveillance and provide more granular estimates with greater efficiency than seroprevalence surveys and register-based aggregate data.