Modelling the spatial variability and uncertainty for under-vaccination and zero-dose children in fragile settings

Abstract

Abstract Universal access to childhood vaccination is important to child health and sustainable development. Here we identify, at a fine spatial scale, under-immunized children and zero-dose children. Using Chad, as an example, the most recent nationally representative household survey that included recommended vaccine antigens was assembled. Age-disaggregated population (12–23 months) and vaccination coverage were modelled at a fine spatial resolution scale (1km × 1 km) using a Bayesian geostatistical framework adjusting for a set of parsimonious covariates. There was a variation at fine spatial scale in the population 12–23 months a national mean of 18.6% (CrI 15.8%–22.6%) with the highest proportion in the South-East district of Laremanaye 20.0% (14.8–25.0). Modelled coverage at birth was 49.0% (31.2%–75.3%) for BCG, 44.8% (27.1–74.3) for DTP1, 24.7% (12.5–46.3) for DTP3 and 47.0% (30.6–71.0) for measles (MCV1). Combining coverage estimates with the modelled population at a fine spatial scale yielded 312,723 (Lower estimate 156055–409266) zero-dose children based on DTP1. Improving routine immunization will require investment in the health system as part of enhancing primary health care. The uncertainties in our estimates highlight areas that require further investigation and higher quality data to gain a better understanding of vaccination coverage.

Keywords

• Bayesian geostatistical modelling
• Exceedance probability
• Under-immunization
• Zero-dose