TY - JOUR
T1 - Estimating vaccine coverage in conflict settings using geospatial methods
T2 - a case study in Borno state, Nigeria
AU - Sbarra, Alyssa N.
AU - Rolfe, Sam
AU - Haeuser, Emily
AU - Nguyen, Jason Q.
AU - Adamu, Aishatu
AU - Adeyinka, Daniel
AU - Ajumobi, Olufemi
AU - Akunna, Chisom
AU - Amusa, Ganiyu
AU - Dahiru, Tukur
AU - Ekholuenetale, Michael
AU - Esezobor, Christopher
AU - Fowobaje, Kayode
AU - Hay, Simon I.
AU - Ibeneme, Charles
AU - Ibitoye, Segun Emmanuel
AU - Ilesanmi, Olayinka
AU - Kayode, Gbenga
AU - Krohn, Kris
AU - Lim, Stephen S.
AU - Medeiros, Lyla E.
AU - Mohammed, Shafiu
AU - Nwatah, Vincent
AU - Okoro, Anselm
AU - Olagunju, Andrew T.
AU - Olusanya, Bolajoko O.
AU - Osarenotor, Osayomwanbo
AU - Owolabi, Mayowa
AU - Pickering, Brandon
AU - Sufiyan, Mu’awiyyah Babale
AU - Uzochukwu, Benjamin
AU - Walker, Ally
AU - Mosser, Jonathan F.
N1 - Publisher Copyright:
© 2023, The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - Reliable estimates of subnational vaccination coverage are critical to track progress towards global immunisation targets and ensure equitable health outcomes for all children. However, conflict can limit the reliability of coverage estimates from traditional household-based surveys due to an inability to sample in unsafe and insecure areas and increased uncertainty in underlying population estimates. In these situations, model-based geostatistical (MBG) approaches offer alternative coverage estimates for administrative units affected by conflict. We estimated first- and third-dose diphtheria-tetanus-pertussis vaccine coverage in Borno state, Nigeria, using a spatiotemporal MBG modelling approach, then compared these to estimates from recent conflict-affected, household-based surveys. We compared sampling cluster locations from recent household-based surveys to geolocated data on conflict locations and modelled spatial coverage estimates, while also investigating the importance of reliable population estimates when assessing coverage in conflict settings. These results demonstrate that geospatially-modelled coverage estimates can be a valuable additional tool to understand coverage in locations where conflict prevents representative sampling.
AB - Reliable estimates of subnational vaccination coverage are critical to track progress towards global immunisation targets and ensure equitable health outcomes for all children. However, conflict can limit the reliability of coverage estimates from traditional household-based surveys due to an inability to sample in unsafe and insecure areas and increased uncertainty in underlying population estimates. In these situations, model-based geostatistical (MBG) approaches offer alternative coverage estimates for administrative units affected by conflict. We estimated first- and third-dose diphtheria-tetanus-pertussis vaccine coverage in Borno state, Nigeria, using a spatiotemporal MBG modelling approach, then compared these to estimates from recent conflict-affected, household-based surveys. We compared sampling cluster locations from recent household-based surveys to geolocated data on conflict locations and modelled spatial coverage estimates, while also investigating the importance of reliable population estimates when assessing coverage in conflict settings. These results demonstrate that geospatially-modelled coverage estimates can be a valuable additional tool to understand coverage in locations where conflict prevents representative sampling.
UR - http://www.scopus.com/inward/record.url?scp=85164157160&partnerID=8YFLogxK
U2 - 10.1038/s41598-023-37947-8
DO - 10.1038/s41598-023-37947-8
M3 - Article
C2 - 37422502
AN - SCOPUS:85164157160
SN - 2045-2322
VL - 13
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 11085
ER -