Correlating Projected and Surveyed Population using Google Building Footprints in Jigawa State, Nigeria: Targeting Zero Dose Children Aligned with SDG Goal 3

This study evaluates the accuracy of projected population data and its implications for estimating zero-dose children in Jigawa State, Nigeria. The specific objectives were to correlate projected and surveyed population data using Google Building Footprints and assess the gap in zero-dose children across various settlement types. A quantitative approach was employed, utilizing data from Google’s Building Footprints, Copernicus Human Settlement, Sentinel Hub, OpenStreetMap, and NASA Earth data. A geolocated household survey was conducted, covering 1,600 buildings across 27 LGAs using stratified random sampling. Essential demographic and socio-economic data were collected. Ordinary Least Squares (OLS) regression analysis was performed to validate projected population data, and paired t-tests compared population estimates for rural and urban areas. For zero-dose children estimation, a model was developed incorporating settlement types, NDVI, time distance to health facilities, and nightlight data. The OLS regression analysis demonstrated a strong correlation between projected and surveyed data (coefficient = 0.823, p < 0.01) with an Adjusted R-Squared of 0.95. However, paired t-tests indicated significant discrepancies, with the projected data overestimating rural populations and underestimating urban populations. The total zero-dose children were estimated at 113,143 (32% of Target Population) based on projected data and 91,415 (26% of Target Population) based on survey data. Addressing these discrepancies is vital for effective public health planning and resource allocation, particularly in targeting interventions for zero-dose children in rural areas of Jigawa State. The findings emphasize the importance of localized adjustments and continuous monitoring to reflect actual demographic changes and improve healthcare accessibility