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Integrating geostatistical maps and infectious disease transmission models using adaptive multiple importance sampling

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Retkute, Renata, Touloupou, Panayiota, Basáñez, Maria-Gloria, Hollingsworth, T. Deirdre and Spencer, Simon E. F. (2021) Integrating geostatistical maps and infectious disease transmission models using adaptive multiple importance sampling. Annals of Applied Statistics, 15 (4). pp. 1980-1998. doi:10.1214/21-AOAS1486

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Official URL: https://doi.org/10.1214/21-AOAS1486

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Abstract

The Adaptive Multiple Importance Sampling algorithm (AMIS) is an iterative technique which recycles samples from all previous iterations in order to improve the efficiency of the proposal distribution. We have formulated a new statistical framework, based on AMIS, to take the output from a geostatistical model of infectious disease prevalence, incidence or relative risk, and project it forward in time under a mathematical model for transmission dynamics. We adapted the AMIS algorithm so that it can sample from multiple targets simultaneously by changing the focus of the adaptation at each iteration. By comparing our approach against the standard AMIS algorithm, we showed that these novel adaptations greatly improve the efficiency of the sampling. We tested the performance of our algorithm on four case studies: ascariasis in Ethiopia, onchocerciasis in Togo, human immunodeficiency virus (HIV) in Botswana, and malaria in the Democratic Republic of the Congo.

Item Type: Journal Article
Alternative Title:
Subjects: R Medicine > RA Public aspects of medicine
Divisions: Faculty of Science, Engineering and Medicine > Science > Statistics
Library of Congress Subject Headings (LCSH): Communicable diseases , Communicable diseases -- Transmission -- Mathematical models, Epidemiology -- Statistical methods, Medical mapping
Journal or Publication Title: Annals of Applied Statistics
Publisher: Insitute of Mathematical Statistics
ISSN: 1932-6157
Official Date: December 2021
Dates:
DateEvent
December 2021Published
17 May 2021Accepted
Volume: 15
Number: 4
Page Range: pp. 1980-1998
DOI: 10.1214/21-AOAS1486
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
Copyright Holders: Copyright © 2021 Institute of Mathematical Statistics
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
OPP1184344Bill and Melinda Gates Foundationhttp://dx.doi.org/10.13039/100000865
OPP1186851Bill and Melinda Gates Foundationhttp://dx.doi.org/10.13039/100000865
OPP1156227Bill and Melinda Gates Foundationhttp://dx.doi.org/10.13039/100000865
MR/R015600/1[MRC] Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
MR/R015600/1Department for International Developmenthttp://dx.doi.org/10.13039/501100000278
EDCTP2 programEuropean Commissionhttp://dx.doi.org/10.13039/501100000780
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