Development of a composite scoring system to rank communities at high risk of zero-dose children in Cameroon: A geospatial analysis

Abstract

Background: Despite growing efforts to improve access to vaccination, millions of children, especially in developing countries, have not received a single dose of diphtheria, tetanus, and pertussis (DTP) vaccine. Consequently, they are often called zero-dose children (ZDC). With limited health resources, prioritising communities for rapid and mass zero-dose catch-up vaccination in missed communities to avert epidemic outbreaks is complicated by unreliable denominators used to compute vaccination coverages. Incorporating other indicators of access and utilisation of vaccination services can help with identifying and ranking missed communities based on the likelihood of finding ZDC. We described the process of generating a scoring method to rank health areas in Cameroon based on their likelihood of containing ZDC.

Methods: We used geospatial analysis to compute and aggregate health area characteristics, including hard-to-reach (HTR) areas (defined as areas of settlement above a one- (for urban areas) or 15-kilometre radius (for rural areas) beyond a vaccinating health facility), amount of area covered by slums and new area settlement, and percentage of children unvaccinated for DTP-1. We attributed a weight based on the ability to limit accessibility or utilisation of vaccination services to each characteristic and computed the score as a weighted average of health area characteristics. The health area score ranged from 0 to 1, with higher scores representing a higher likelihood of containing ZDC. We stratified the analysis by rural and urban health areas.

Results: We observed substantial district and regional variations in health area scores, with hotspots health areas (administrative level 4) observed in the Far North (0.83), North (0.81), Adamawa (0.80), East (0.75), and South West (0.67) regions. The Adamawa region had the highest percentage of health areas with the highest score (78%), followed by the East (50%), West (48%), and North (46%) regions. For most regions (Far North, South, South West, Littoral, West, and North West), DTP-1 contributed the most to the score. However, HTR settlement areas within a health area contributed substantially to the overall score in the East, North, and Adamawa regions.

Conclusions: We found substantial variations in health area scores with hotspots in the Far North, North, Adamawa, East, and South West regions. Although DTP-1 could be used as an indicator to identify health areas with ZDC for most communities, HTR settlement area was a valuable indicator in ranking priority health areas in the East, North, and Adamawa regions, further emphasising the need to consider other indicators before prioritisation.