Imperial College London

ProfessorNicholasGrassly

Faculty of MedicineSchool of Public Health

Prof of Infectious Disease & Vaccine Epidemiology
 
 
 
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Contact

 

+44 (0)20 7594 3264n.grassly Website

 
 
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Location

 

G36Medical SchoolSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Molodecky:2017:10.1371/journal.pmed.1002323,
author = {Molodecky, NAL and Blake, IM and O'reilly, KM and Wadood, MZ and Safdar, RM and Wesolowski, A and Buckee, CO and Bandyopadhyay, AS and Okayasu, H and Grassly, NC},
doi = {10.1371/journal.pmed.1002323},
journal = {Plos Medicine},
title = {Risk-factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: a spatio-temporal analysis},
url = {http://dx.doi.org/10.1371/journal.pmed.1002323},
volume = {14},
year = {2017}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - BackgroundPakistan 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 findingsWe 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 mo
AU - Molodecky,NAL
AU - Blake,IM
AU - O'reilly,KM
AU - Wadood,MZ
AU - Safdar,RM
AU - Wesolowski,A
AU - Buckee,CO
AU - Bandyopadhyay,AS
AU - Okayasu,H
AU - Grassly,NC
DO - 10.1371/journal.pmed.1002323
PY - 2017///
SN - 1549-1676
TI - Risk-factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: a spatio-temporal analysis
T2 - Plos Medicine
UR - http://dx.doi.org/10.1371/journal.pmed.1002323
UR - http://hdl.handle.net/10044/1/48586
VL - 14
ER -