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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
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 | |||||||||||||||||||||
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| 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 | |||||||||||||||||||||
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| 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 | |||||||||||||||||||||
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