hybridModels: An R Package for the Stochastic Simulation of Disease Spreading in Dynamic Networks

Página do item simplificado
dc.contributorSistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSP
dc.contributor.authorMARQUES, Fernando S.
dc.contributor.authorGRISI-FILHO, Jose H. H.
dc.contributor.authorAMAKU, Marcos
dc.contributor.authorSILVA, Jean C. R.
dc.contributor.authorALMEIDA, Erivania C.
dc.contributor.authorSILVA JUNIOR, Jose L.
dc.date.accessioned2023-06-21T14:15:38Z
dc.date.available2023-06-21T14:15:38Z
dc.date.issued2020
dc.description.abstractDisease spreading simulations are traditionally performed using coupled differential equations. However, in the setting of metapopulations, most of the solutions provided by this method do not account for the dynamic topography of subpopulations. Conversely, the alternative approach of individual-based modeling (IBM) may add computational cost and complexity. Hybrid models allow for the study of disease spreading because they combine both aforementioned approaches by separating them across different scales: a local scale that addresses subpopulation dynamics using coupled differential equations and a global scale that addresses the contact between these subpopulations using IBM. We present a simple way of simulating the spread of disease in dynamic networks using the high-level statistical computational language R and the hybridModels package. We built four examples using disease spread models at the local scale in several different networks: an animal movement network; a three-node network, whose model solution using a stochastic simulation algorithm is compared with the ordinary differential equations approach; the commuting of individuals between patches, which we compare with the permanent migration of individuals; and the commuting of individuals within the metropolitan area of Sao Paulo.eng
dc.description.indexPubMed
dc.description.indexWoS
dc.description.indexScopus
dc.identifier.citationJOURNAL OF STATISTICAL SOFTWARE, v.94, n.6, p.1-32, 2020
dc.identifier.doi10.18637/jss.v094.i06
dc.identifier.issn1548-7660
dc.identifier.urihttps://observatorio.fm.usp.br/handle/OPI/54055
dc.language.isoeng
dc.publisherJOURNAL STATISTICAL SOFTWAREeng
dc.relation.ispartofJournal of Statistical Software
dc.rightsopenAccesseng
dc.rights.holderCopyright JOURNAL STATISTICAL SOFTWAREeng
dc.subjectmodelingeng
dc.subjectdynamic networkseng
dc.subjectepidemiceng
dc.subjectstochastic simulationeng
dc.subjectReng
dc.subject.otherinfectious-diseaseseng
dc.subject.otherseasonal influenzaeng
dc.subject.othercattle movementseng
dc.subject.othertrade patternseng
dc.subject.othermouth-diseaseeng
dc.subject.othersurveillanceeng
dc.subject.otherstrategieseng
dc.subject.otherepidemicseng
dc.subject.othertopologyeng
dc.subject.otherprotocoleng
dc.subject.wosComputer Science, Interdisciplinary Applicationseng
dc.subject.wosStatistics & Probabilityeng
dc.titlehybridModels: An R Package for the Stochastic Simulation of Disease Spreading in Dynamic Networkseng
dc.typearticleeng
dc.type.categoryoriginal articleeng
dc.type.versionpublishedVersioneng
dspace.entity.typePublication
hcfmusp.author.externalMARQUES, Fernando S.:Univ Sao Paulo, Sao Paulo, Brazil
hcfmusp.author.externalGRISI-FILHO, Jose H. H.:Univ Sao Paulo, Sao Paulo, Brazil
hcfmusp.author.externalSILVA, Jean C. R.:Univ Fed Rural Pernambuco, Recife, PE, Brazil
hcfmusp.author.externalALMEIDA, Erivania C.:Agencia Def & Fiscalizacao Agr Pernambuco, Recife, PE, Brazil
hcfmusp.author.externalSILVA JUNIOR, Jose L.:Agencia Def & Fiscalizacao Agr Pernambuco, Recife, PE, Brazil
hcfmusp.citation.scopus4
hcfmusp.contributor.author-fmusphcMARCOS AMAKU
hcfmusp.description.beginpage1
hcfmusp.description.endpage32
hcfmusp.description.issue6
hcfmusp.description.volume94
hcfmusp.origemWOS
hcfmusp.origem.scopus2-s2.0-85087363134
hcfmusp.origem.wosWOS:000552357100001
hcfmusp.publisher.cityLOS ANGELESeng
hcfmusp.publisher.countryUSAeng
hcfmusp.relation.referenceAznar MN, 2011, PREV VET MED, V98, P119, DOI 10.1016/j.prevetmed.2010.11.004eng
hcfmusp.relation.referenceBigras-Poulin M, 2006, PREV VET MED, V76, P11, DOI 10.1016/j.prevetmed.2006.04.004eng
hcfmusp.relation.referenceBigras-Poulin M, 2007, PREV VET MED, V80, P143, DOI 10.1016/j.prevetmed.2007.02.004eng
hcfmusp.relation.referenceButtner K, 2015, TRANSBOUND EMERG DIS, V62, P188, DOI 10.1111/tbed.12106eng
hcfmusp.relation.referenceBuhnerkempe MG, 2013, PREV VET MED, V112, P318, DOI 10.1016/j.prevetmed.2013.08.002eng
hcfmusp.relation.referenceCao Y, 2006, J CHEM PHYS, V124, DOI 10.1063/1.2159468eng
hcfmusp.relation.referenceChatterjee A, 2005, J CHEM PHYS, V122, DOI 10.1063/1.1833357eng
hcfmusp.relation.referenceChowell G, 2008, EPIDEMIOL INFECT, V136, P852, DOI 10.1017/S0950268807009144eng
hcfmusp.relation.referenceChowell G, 2010, P ROY SOC B-BIOL SCI, V277, P1857, DOI 10.1098/rspb.2009.1897eng
hcfmusp.relation.referenceCoelho FC, 2008, SOURCE CODE BIOL MED, V3, DOI 10.1186/1751-0473-3-3eng
hcfmusp.relation.referenceCsardi G., 2006, INTERJOURNAL COMPLEX, V1695eng
hcfmusp.relation.referenceDube C, 2008, TRANSBOUND EMERG DIS, V55, P382, DOI 10.1111/j.1865-1682.2008.01053.xeng
hcfmusp.relation.referenceFrossling J, 2012, PREV VET MED, V105, P202, DOI 10.1016/j.prevetmed.2011.12.011eng
hcfmusp.relation.referenceGarner MG, 2005, AUST VET J, V83, P758, DOI 10.1111/j.1751-0813.2005.tb11589.xeng
hcfmusp.relation.referenceGillespie DT, 2007, ANNU REV PHYS CHEM, V58, P35, DOI 10.1146/annurev.physchem.58.032806.104637eng
hcfmusp.relation.referenceGILLESPIE DT, 1976, J COMPUT PHYS, V22, P403, DOI 10.1016/0021-9991(76)90041-3eng
hcfmusp.relation.referenceGillespie DT, 2001, J CHEM PHYS, V115, P1716, DOI 10.1063/1.1378322eng
hcfmusp.relation.referenceGILLESPIE DT, 1977, J PHYS CHEM-US, V81, P2340, DOI 10.1021/j100540a008eng
hcfmusp.relation.referenceGreen DM, 2009, PREV VET MED, V91, P261, DOI 10.1016/j.prevetmed.2009.05.031eng
hcfmusp.relation.referenceGrenfell BT, 2001, NATURE, V414, P716, DOI 10.1038/414716aeng
hcfmusp.relation.referenceGrimm V, 2005, SCIENCE, V310, P987, DOI 10.1126/science.1116681eng
hcfmusp.relation.referenceGrimm V., 2005, INDIVIDUAL BASED MODeng
hcfmusp.relation.referenceGrimm V, 2006, ECOL MODEL, V198, P115, DOI 10.1016/j.ecolmodel.2006.04.023eng
hcfmusp.relation.referenceGrimm V, 2010, ECOL MODEL, V221, P2760, DOI 10.1016/j.ecolmodel.2010.08.019eng
hcfmusp.relation.referenceGrisi JHH, 2013, PREV VET MED, V110, P304, DOI 10.1016/j.prevetmed.2012.12.013eng
hcfmusp.relation.referenceHarvey N, 2007, PREV VET MED, V82, P176, DOI 10.1016/j.prevetmed.2007.05.019eng
hcfmusp.relation.referenceKane MJ, 2013, J STAT SOFTW, V55, P1eng
hcfmusp.relation.referenceKao RR, 2007, J R SOC INTERFACE, V4, P907, DOI 10.1098/rsif.2007.1129eng
hcfmusp.relation.referenceKeeling M, 2005, THEOR POPUL BIOL, V67, P1, DOI 10.1016/j.tpb.2004.08.002eng
hcfmusp.relation.referenceLongini IM, 2004, AM J EPIDEMIOL, V159, P623, DOI 10.1093/aje/kwh092eng
hcfmusp.relation.referenceMills CE, 2004, NATURE, V432, P904, DOI 10.1038/nature03063eng
hcfmusp.relation.referenceMonk N, 2012, CPIB SUMMER SCH 2012eng
hcfmusp.relation.referenceNegreiros RL, 2010, THESISeng
hcfmusp.relation.referenceNoremark M, 2014, BMC VET RES, V10, DOI 10.1186/1746-6148-10-71eng
hcfmusp.relation.referenceNoremark M, 2011, PREV VET MED, V99, P78, DOI 10.1016/j.prevetmed.2010.12.009eng
hcfmusp.relation.referenceNoremark M, 2009, ACTA VET SCAND, V51, DOI 10.1186/1751-0147-51-37eng
hcfmusp.relation.referenceOsgood N, 2007, 2007 INT C SYST DYNeng
hcfmusp.relation.referencePineda-Krch M, 2008, J STAT SOFTW, V25eng
hcfmusp.relation.referenceR Development Core Team, 2008, R LANG ENV STAT COMPeng
hcfmusp.relation.referenceRahmandad H, 2008, MANAGE SCI, V54, P998, DOI 10.1287/mnsc.1070.0787eng
hcfmusp.relation.referenceRasamoelina-Andriamanivo H, 2014, ACTA TROP, V135, P10, DOI 10.1016/j.actatropica.2014.03.008eng
hcfmusp.relation.referenceRautureau S, 2011, TRANSBOUND EMERG DIS, V58, P110, DOI 10.1111/j.1865-1682.2010.01187.xeng
hcfmusp.relation.referenceShirley MDF, 2005, ECOL COMPLEX, V2, P287, DOI 10.1016/j.ecocom.2005.04.005eng
hcfmusp.relation.referenceSoetaert K, 2010, J STAT SOFTW, V33, P1, DOI 10.18637/jss.v033.i09eng
hcfmusp.relation.referenceStevenson MA, 2013, PREV VET MED, V109, P10, DOI 10.1016/j.prevetmed.2012.08.015eng
hcfmusp.relation.referenceThakur KK, 2016, TRANSBOUND EMERG DIS, V63, pE14, DOI 10.1111/tbed.12225eng
hcfmusp.relation.referenceVan Rossum G, 2011, PYTH PROGR LANGeng
hcfmusp.relation.referenceVincenot CE, 2011, ECOL INFORM, V6, P177, DOI 10.1016/j.ecoinf.2011.04.002eng
hcfmusp.relation.referenceVincenot CE, 2011, ECOL MODEL, V222, P210, DOI 10.1016/j.ecolmodel.2010.09.029eng
hcfmusp.relation.referenceWickham H, 2009, USE R, P1, DOI 10.1007/978-0-387-98141-3eng
hcfmusp.relation.referenceWickham H, 2007, J STAT SOFTW, V21, P1eng
hcfmusp.scopus.lastupdate2024-05-17
relation.isAuthorOfPublicationf1485056-4675-4efb-b309-170254049c73
relation.isAuthorOfPublication.latestForDiscoveryf1485056-4675-4efb-b309-170254049c73
Arquivos
Pacote Original
Agora exibindo 1 - 1 de 1
Imagem de Miniatura
Nome:
art_MARQUES_hybridModels_An_R_Package_for_the_Stochastic_Simulation_2020.PDF
Tamanho:
1006.57 KB
Formato:
Adobe Portable Document Format
Descrição:
publishedVersion (English)
Baixar
Coleções
Artigos e Materiais de Revistas Científicas - FM/MPT
Artigos e Materiais de Revistas Científicas - LIM/01