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Risk factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: A spatiotemporal analysis

BACKGROUND: Pakistan currently provides a substantial challenge to global polio eradication, having contributed to 73% of reported poliomyelitis in 2015 and 54% in 2016. A better understanding of the risk factors and movement patterns that contribute to poliovirus transmission across Pakistan would...

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Autores principales: Molodecky, Natalie A., Blake, Isobel M., O’Reilly, Kathleen M., Wadood, Mufti Zubair, Safdar, Rana M., Wesolowski, Amy, Buckee, Caroline O., Bandyopadhyay, Ananda S., Okayasu, Hiromasa, Grassly, Nicholas C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5467805/
https://www.ncbi.nlm.nih.gov/pubmed/28604777
http://dx.doi.org/10.1371/journal.pmed.1002323
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author Molodecky, Natalie A.
Blake, Isobel M.
O’Reilly, Kathleen M.
Wadood, Mufti Zubair
Safdar, Rana M.
Wesolowski, Amy
Buckee, Caroline O.
Bandyopadhyay, Ananda S.
Okayasu, Hiromasa
Grassly, Nicholas C.
author_facet Molodecky, Natalie A.
Blake, Isobel M.
O’Reilly, Kathleen M.
Wadood, Mufti Zubair
Safdar, Rana M.
Wesolowski, Amy
Buckee, Caroline O.
Bandyopadhyay, Ananda S.
Okayasu, Hiromasa
Grassly, Nicholas C.
author_sort Molodecky, Natalie A.
collection PubMed
description BACKGROUND: Pakistan currently provides a substantial challenge to global polio eradication, having contributed to 73% of reported poliomyelitis in 2015 and 54% in 2016. A better understanding of the risk factors and movement patterns that contribute to poliovirus transmission across Pakistan would support evidence-based planning for mass vaccination campaigns. METHODS AND FINDINGS: We fit mixed-effects logistic regression models to routine surveillance data recording the presence of poliomyelitis associated with wild-type 1 poliovirus in districts of Pakistan over 6-month intervals between 2010 to 2016. To accurately capture the force of infection (FOI) between districts, we compared 6 models of population movement (adjacency, gravity, radiation, radiation based on population density, radiation based on travel times, and mobile-phone based). We used the best-fitting model (based on the Akaike Information Criterion [AIC]) to produce 6-month forecasts of poliomyelitis incidence. The odds of observing poliomyelitis decreased with improved routine or supplementary (campaign) immunisation coverage (multivariable odds ratio [OR] = 0.75, 95% confidence interval [CI] 0.67–0.84; and OR = 0.75, 95% CI 0.66–0.85, respectively, for each 10% increase in coverage) and increased with a higher rate of reporting non-polio acute flaccid paralysis (AFP) (OR = 1.13, 95% CI 1.02–1.26 for a 1-unit increase in non-polio AFP per 100,000 persons aged <15 years). Estimated movement of poliovirus-infected individuals was associated with the incidence of poliomyelitis, with the radiation model of movement providing the best fit to the data. Six-month forecasts of poliomyelitis incidence by district for 2013–2016 showed good predictive ability (area under the curve range: 0.76–0.98). However, although the best-fitting movement model (radiation) was a significant determinant of poliomyelitis incidence, it did not improve the predictive ability of the multivariable model. Overall, in Pakistan the risk of polio cases was predicted to reduce between July–December 2016 and January–June 2017. The accuracy of the model may be limited by the small number of AFP cases in some districts. CONCLUSIONS: Spatiotemporal variation in immunization performance and population movement patterns are important determinants of historical poliomyelitis incidence in Pakistan; however, movement dynamics were less influential in predicting future cases, at a time when the polio map is shrinking. Results from the regression models we present are being used to help plan vaccination campaigns and transit vaccination strategies in Pakistan.
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spelling pubmed-54678052017-06-22 Risk factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: A spatiotemporal analysis Molodecky, Natalie A. Blake, Isobel M. O’Reilly, Kathleen M. Wadood, Mufti Zubair Safdar, Rana M. Wesolowski, Amy Buckee, Caroline O. Bandyopadhyay, Ananda S. Okayasu, Hiromasa Grassly, Nicholas C. PLoS Med Research Article BACKGROUND: Pakistan currently provides a substantial challenge to global polio eradication, having contributed to 73% of reported poliomyelitis in 2015 and 54% in 2016. A better understanding of the risk factors and movement patterns that contribute to poliovirus transmission across Pakistan would support evidence-based planning for mass vaccination campaigns. METHODS AND FINDINGS: We fit mixed-effects logistic regression models to routine surveillance data recording the presence of poliomyelitis associated with wild-type 1 poliovirus in districts of Pakistan over 6-month intervals between 2010 to 2016. To accurately capture the force of infection (FOI) between districts, we compared 6 models of population movement (adjacency, gravity, radiation, radiation based on population density, radiation based on travel times, and mobile-phone based). We used the best-fitting model (based on the Akaike Information Criterion [AIC]) to produce 6-month forecasts of poliomyelitis incidence. The odds of observing poliomyelitis decreased with improved routine or supplementary (campaign) immunisation coverage (multivariable odds ratio [OR] = 0.75, 95% confidence interval [CI] 0.67–0.84; and OR = 0.75, 95% CI 0.66–0.85, respectively, for each 10% increase in coverage) and increased with a higher rate of reporting non-polio acute flaccid paralysis (AFP) (OR = 1.13, 95% CI 1.02–1.26 for a 1-unit increase in non-polio AFP per 100,000 persons aged <15 years). Estimated movement of poliovirus-infected individuals was associated with the incidence of poliomyelitis, with the radiation model of movement providing the best fit to the data. Six-month forecasts of poliomyelitis incidence by district for 2013–2016 showed good predictive ability (area under the curve range: 0.76–0.98). However, although the best-fitting movement model (radiation) was a significant determinant of poliomyelitis incidence, it did not improve the predictive ability of the multivariable model. Overall, in Pakistan the risk of polio cases was predicted to reduce between July–December 2016 and January–June 2017. The accuracy of the model may be limited by the small number of AFP cases in some districts. CONCLUSIONS: Spatiotemporal variation in immunization performance and population movement patterns are important determinants of historical poliomyelitis incidence in Pakistan; however, movement dynamics were less influential in predicting future cases, at a time when the polio map is shrinking. Results from the regression models we present are being used to help plan vaccination campaigns and transit vaccination strategies in Pakistan. Public Library of Science 2017-06-12 /pmc/articles/PMC5467805/ /pubmed/28604777 http://dx.doi.org/10.1371/journal.pmed.1002323 Text en © 2017 Molodecky et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Molodecky, Natalie A.
Blake, Isobel M.
O’Reilly, Kathleen M.
Wadood, Mufti Zubair
Safdar, Rana M.
Wesolowski, Amy
Buckee, Caroline O.
Bandyopadhyay, Ananda S.
Okayasu, Hiromasa
Grassly, Nicholas C.
Risk factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: A spatiotemporal analysis
title Risk factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: A spatiotemporal analysis
title_full Risk factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: A spatiotemporal analysis
title_fullStr Risk factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: A spatiotemporal analysis
title_full_unstemmed Risk factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: A spatiotemporal analysis
title_short Risk factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: A spatiotemporal analysis
title_sort risk factors and short-term projections for serotype-1 poliomyelitis incidence in pakistan: a spatiotemporal analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5467805/
https://www.ncbi.nlm.nih.gov/pubmed/28604777
http://dx.doi.org/10.1371/journal.pmed.1002323
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