Assessment of subnational level birth registration data in South Africa - Madamombe, Tawanda (Department of Human Biology, 2022)
Birth registration data forms part of vital statistics. It is the right of the child to be registered immediately after birth and to acquire an identity and a nationality as stipulated by the Convention on the Rights of the Child (UNICEF 1989). The assessment of birth registration is important to help authorities in the processes of planning and decision making. This study investigates birth registration data at a district level with the aim to establish the data's usefulness in determining reliable completeness of births and estimating total fertility rate (TFR). The study further analyses the spatial relationships between respective districts to each other based on levels of birth completeness and total fertility rate. The Geographical Information Systems (GIS) technique of the Global Moran's Index spatial autocorrelation is used to examine the spatial distribution of completeness and TFR. The Indirect method of relational Gompertz model is used to calculate robust estimates of actual births that occurred in the twelve-month period before 2011 Census and 2016 Community Survey, respectively. Then, the Hauer and Schmertmann (2020) method of determining fertility was used to validate results from the Gompertz model. The study establishes that there was an improvement in the promptness of birth registration between 2011 and 2016, highlighted by an 82% completeness in 2011 that increased to 85% in 2016 for births that were registered within the same year of occurrence. This is evidence that mothers are registering births at younger ages than before. The TFR decreased from 2.55 in 2011 to 2.28 in 2016. Apart from that, the study illustrated that districts with higher completeness levels tend to be in major urban agglomerations. However, no spatial relationship could be established meaning that the neighbouring districts do not follow any pattern when compared to each other. It was also noted that districts with low fertility are clustered near major cities. Although there are issues with data at lower levels of disaggregation such as districts, it has been shown that the use of robust methods produces results that help to give meaningful insights of birth registration data.