Spatiotemporal infectious disease modeling: a BME-SIR approach.

This paper is concerned with the modeling of infectious disease spread in a composite space-time domain under conditions of uncertainty. We focus on stochastic modeling that accounts for basic mechanisms of disease distribution and multi-sourced in situ uncertainties. Starting from the general formu...

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Autores principales:	Jose Angulo, Hwa-Lung Yu, Andrea Langousis, Alexander Kolovos, Jinfeng Wang, Ana Esther Madrid, George Christakos
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f0e881135e734636aaed790ca3c3a29f
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spelling	oai:doaj.org-article:f0e881135e734636aaed790ca3c3a29f2021-11-18T08:53:24ZSpatiotemporal infectious disease modeling: a BME-SIR approach.1932-620310.1371/journal.pone.0072168https://doaj.org/article/f0e881135e734636aaed790ca3c3a29f2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24086257/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203This paper is concerned with the modeling of infectious disease spread in a composite space-time domain under conditions of uncertainty. We focus on stochastic modeling that accounts for basic mechanisms of disease distribution and multi-sourced in situ uncertainties. Starting from the general formulation of population migration dynamics and the specification of transmission and recovery rates, the model studies the functional formulation of the evolution of the fractions of susceptible-infected-recovered individuals. The suggested approach is capable of: a) modeling population dynamics within and across localities, b) integrating the disease representation (i.e. susceptible-infected-recovered individuals) with observation time series at different geographical locations and other sources of information (e.g. hard and soft data, empirical relationships, secondary information), and c) generating predictions of disease spread and associated parameters in real time, while considering model and observation uncertainties. Key aspects of the proposed approach are illustrated by means of simulations (i.e. synthetic studies), and a real-world application using hand-foot-mouth disease (HFMD) data from China.Jose AnguloHwa-Lung YuAndrea LangousisAlexander KolovosJinfeng WangAna Esther MadridGeorge ChristakosPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 9, p e72168 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jose Angulo Hwa-Lung Yu Andrea Langousis Alexander Kolovos Jinfeng Wang Ana Esther Madrid George Christakos Spatiotemporal infectious disease modeling: a BME-SIR approach.
description	This paper is concerned with the modeling of infectious disease spread in a composite space-time domain under conditions of uncertainty. We focus on stochastic modeling that accounts for basic mechanisms of disease distribution and multi-sourced in situ uncertainties. Starting from the general formulation of population migration dynamics and the specification of transmission and recovery rates, the model studies the functional formulation of the evolution of the fractions of susceptible-infected-recovered individuals. The suggested approach is capable of: a) modeling population dynamics within and across localities, b) integrating the disease representation (i.e. susceptible-infected-recovered individuals) with observation time series at different geographical locations and other sources of information (e.g. hard and soft data, empirical relationships, secondary information), and c) generating predictions of disease spread and associated parameters in real time, while considering model and observation uncertainties. Key aspects of the proposed approach are illustrated by means of simulations (i.e. synthetic studies), and a real-world application using hand-foot-mouth disease (HFMD) data from China.
format	article
author	Jose Angulo Hwa-Lung Yu Andrea Langousis Alexander Kolovos Jinfeng Wang Ana Esther Madrid George Christakos
author_facet	Jose Angulo Hwa-Lung Yu Andrea Langousis Alexander Kolovos Jinfeng Wang Ana Esther Madrid George Christakos
author_sort	Jose Angulo
title	Spatiotemporal infectious disease modeling: a BME-SIR approach.
title_short	Spatiotemporal infectious disease modeling: a BME-SIR approach.
title_full	Spatiotemporal infectious disease modeling: a BME-SIR approach.
title_fullStr	Spatiotemporal infectious disease modeling: a BME-SIR approach.
title_full_unstemmed	Spatiotemporal infectious disease modeling: a BME-SIR approach.
title_sort	spatiotemporal infectious disease modeling: a bme-sir approach.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/f0e881135e734636aaed790ca3c3a29f
work_keys_str_mv	AT joseangulo spatiotemporalinfectiousdiseasemodelingabmesirapproach AT hwalungyu spatiotemporalinfectiousdiseasemodelingabmesirapproach AT andrealangousis spatiotemporalinfectiousdiseasemodelingabmesirapproach AT alexanderkolovos spatiotemporalinfectiousdiseasemodelingabmesirapproach AT jinfengwang spatiotemporalinfectiousdiseasemodelingabmesirapproach AT anaesthermadrid spatiotemporalinfectiousdiseasemodelingabmesirapproach AT georgechristakos spatiotemporalinfectiousdiseasemodelingabmesirapproach
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Spatiotemporal infectious disease modeling: a BME-SIR approach.

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