| pubmed-article:8733427 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:8733427 | lifeskim:mentions | umls-concept:C0026339 | lld:lifeskim |
| pubmed-article:8733427 | lifeskim:mentions | umls-concept:C0026336 | lld:lifeskim |
| pubmed-article:8733427 | lifeskim:mentions | umls-concept:C0019409 | lld:lifeskim |
| pubmed-article:8733427 | lifeskim:mentions | umls-concept:C1428114 | lld:lifeskim |
| pubmed-article:8733427 | lifeskim:mentions | umls-concept:C0014499 | lld:lifeskim |
| pubmed-article:8733427 | pubmed:issue | 1 | lld:pubmed |
| pubmed-article:8733427 | pubmed:dateCreated | 1996-10-24 | lld:pubmed |
| pubmed-article:8733427 | pubmed:abstractText | Spatial heterogeneity is believed to play an important role in the persistence and dynamics of epidemics of childhood diseases because asynchrony between populations within different regions allows global persistence, even if the disease dies out locally. A simple multi-patch (metapopulation) model for spatial heterogeneity in epidemics is analysed and we examine conditions under which patches become synchronized. We show that the patches in non-seasonal deterministic models often oscillate in phase for all but the weakest between patch coupling. Synchronization is also seen for stochastic models, although slightly stronger coupling is needed to overcome the random effects. We demonstrate that the inclusion of seasonal forcing in deterministic models can lead to the maintenance of phase differences between patches. Complex dynamic behaviour is observed in the seasonally forced spatial model, along with the coexistence of many different behaviours. Compared to the non-spatial model, chaotic solutions are observed for weaker seasonal forcing; these solutions have a more realistic minimum number of infectives. | lld:pubmed |
| pubmed-article:8733427 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:8733427 | pubmed:language | eng | lld:pubmed |
| pubmed-article:8733427 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:8733427 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:8733427 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:8733427 | pubmed:month | Mar | lld:pubmed |
| pubmed-article:8733427 | pubmed:issn | 0022-5193 | lld:pubmed |
| pubmed-article:8733427 | pubmed:author | pubmed-author:MayR MRM | lld:pubmed |
| pubmed-article:8733427 | pubmed:author | pubmed-author:LloydA LAL | lld:pubmed |
| pubmed-article:8733427 | pubmed:issnType | Print | lld:pubmed |
| pubmed-article:8733427 | pubmed:day | 7 | lld:pubmed |
| pubmed-article:8733427 | pubmed:volume | 179 | lld:pubmed |
| pubmed-article:8733427 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:8733427 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:8733427 | pubmed:pagination | 1-11 | lld:pubmed |
| pubmed-article:8733427 | pubmed:dateRevised | 2009-9-29 | lld:pubmed |
| pubmed-article:8733427 | pubmed:meshHeading | pubmed-meshheading:8733427-... | lld:pubmed |
| pubmed-article:8733427 | pubmed:meshHeading | pubmed-meshheading:8733427-... | lld:pubmed |
| pubmed-article:8733427 | pubmed:meshHeading | pubmed-meshheading:8733427-... | lld:pubmed |
| pubmed-article:8733427 | pubmed:meshHeading | pubmed-meshheading:8733427-... | lld:pubmed |
| pubmed-article:8733427 | pubmed:meshHeading | pubmed-meshheading:8733427-... | lld:pubmed |
| pubmed-article:8733427 | pubmed:meshHeading | pubmed-meshheading:8733427-... | lld:pubmed |
| pubmed-article:8733427 | pubmed:meshHeading | pubmed-meshheading:8733427-... | lld:pubmed |
| pubmed-article:8733427 | pubmed:year | 1996 | lld:pubmed |
| pubmed-article:8733427 | pubmed:articleTitle | Spatial heterogeneity in epidemic models. | lld:pubmed |
| pubmed-article:8733427 | pubmed:affiliation | Department of Zoology, University of Oxford, U.K. ALUN.LLOYD@ZOO.OX.AC.UK | lld:pubmed |
| pubmed-article:8733427 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:8733427 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
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