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Fine resolution mapping of population age-structures for health and development applications

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Fine resolution mapping of population age-structures for health and development applications. / Alegana, Victor A.; Atkinson, Peter M.; Pezzulo, Carla et al.
In: Interface, Vol. 12, No. 105, 20150073, 04.2015.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Alegana, VA, Atkinson, PM, Pezzulo, C, Sorichetta, A, Weiss, CD, Bird, T, Erbach-Schoenberg, E & Tatem, AJ 2015, 'Fine resolution mapping of population age-structures for health and development applications', Interface, vol. 12, no. 105, 20150073. https://doi.org/10.1098/rsif.2015.0073

APA

Alegana, V. A., Atkinson, P. M., Pezzulo, C., Sorichetta, A., Weiss, C. D., Bird, T., Erbach-Schoenberg, E., & Tatem, A. J. (2015). Fine resolution mapping of population age-structures for health and development applications. Interface, 12(105), Article 20150073. https://doi.org/10.1098/rsif.2015.0073

Vancouver

Alegana VA, Atkinson PM, Pezzulo C, Sorichetta A, Weiss CD, Bird T et al. Fine resolution mapping of population age-structures for health and development applications. Interface. 2015 Apr;12(105):20150073. Epub 2015 Mar 18. doi: 10.1098/rsif.2015.0073

Author

Alegana, Victor A. ; Atkinson, Peter M. ; Pezzulo, Carla et al. / Fine resolution mapping of population age-structures for health and development applications. In: Interface. 2015 ; Vol. 12, No. 105.

Bibtex

@article{4383291c610946fe8e4357deadc9b1ec,
title = "Fine resolution mapping of population age-structures for health and development applications",
abstract = "The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates of numbers of children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery. Traditionally, such estimates are derived from population censuses, but these can often be unreliable, outdated and of coarse resolution for resource-poor settings. Focusing on Nigeria, we use nationally representative household surveys and their cluster locations to predict the proportion of the under-five population in 1 × 1 km using a Bayesian hierarchical spatio-temporal model. Results showed that land cover, travel time to major settlements, night-time lights and vegetation index were good predictors and that accounting for fine-scale variation, rather than assuming a uniform proportion of under 5 year olds can result in significant differences in health metrics. The largest gaps in estimated bednet and vaccination coverage were in Kano, Katsina and Jigawa. Geolocated household surveys are a valuable resource for providing detailed, contemporary and regularly updated population age-structure data in the absence of recent census data. By combining these with covariate layers, age-structure maps of unprecedented detail can be produced to guide the targeting of interventions in resource-poor settings.",
keywords = "demography, geo-statistics, mapping",
author = "Alegana, {Victor A.} and Atkinson, {Peter M.} and Carla Pezzulo and Alessandro Sorichetta and Weiss, {Carol D.} and T. Bird and E. Erbach-Schoenberg and Tatem, {Andrew J.}",
note = "M1 - 105",
year = "2015",
month = apr,
doi = "10.1098/rsif.2015.0073",
language = "English",
volume = "12",
journal = "Interface",
issn = "1742-5689",
publisher = "Royal Society of London",
number = "105",

}

RIS

TY - JOUR

T1 - Fine resolution mapping of population age-structures for health and development applications

AU - Alegana, Victor A.

AU - Atkinson, Peter M.

AU - Pezzulo, Carla

AU - Sorichetta, Alessandro

AU - Weiss, Carol D.

AU - Bird, T.

AU - Erbach-Schoenberg, E.

AU - Tatem, Andrew J.

N1 - M1 - 105

PY - 2015/4

Y1 - 2015/4

N2 - The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates of numbers of children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery. Traditionally, such estimates are derived from population censuses, but these can often be unreliable, outdated and of coarse resolution for resource-poor settings. Focusing on Nigeria, we use nationally representative household surveys and their cluster locations to predict the proportion of the under-five population in 1 × 1 km using a Bayesian hierarchical spatio-temporal model. Results showed that land cover, travel time to major settlements, night-time lights and vegetation index were good predictors and that accounting for fine-scale variation, rather than assuming a uniform proportion of under 5 year olds can result in significant differences in health metrics. The largest gaps in estimated bednet and vaccination coverage were in Kano, Katsina and Jigawa. Geolocated household surveys are a valuable resource for providing detailed, contemporary and regularly updated population age-structure data in the absence of recent census data. By combining these with covariate layers, age-structure maps of unprecedented detail can be produced to guide the targeting of interventions in resource-poor settings.

AB - The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates of numbers of children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery. Traditionally, such estimates are derived from population censuses, but these can often be unreliable, outdated and of coarse resolution for resource-poor settings. Focusing on Nigeria, we use nationally representative household surveys and their cluster locations to predict the proportion of the under-five population in 1 × 1 km using a Bayesian hierarchical spatio-temporal model. Results showed that land cover, travel time to major settlements, night-time lights and vegetation index were good predictors and that accounting for fine-scale variation, rather than assuming a uniform proportion of under 5 year olds can result in significant differences in health metrics. The largest gaps in estimated bednet and vaccination coverage were in Kano, Katsina and Jigawa. Geolocated household surveys are a valuable resource for providing detailed, contemporary and regularly updated population age-structure data in the absence of recent census data. By combining these with covariate layers, age-structure maps of unprecedented detail can be produced to guide the targeting of interventions in resource-poor settings.

KW - demography

KW - geo-statistics

KW - mapping

U2 - 10.1098/rsif.2015.0073

DO - 10.1098/rsif.2015.0073

M3 - Journal article

VL - 12

JO - Interface

JF - Interface

SN - 1742-5689

IS - 105

M1 - 20150073

ER -