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Article: Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases

TitleRemote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases
Authors
KeywordsSpatial connectivity
Spatio-temporal modeling
Biological invasion
Prevention and control of infectious diseases
Issue Date2006
Citation
Science in China, Series C: Life Sciences, 2006, v. 49, n. 6, p. 573-582 How to Cite?
AbstractSimilar to species immigration or exotic species invasion, infectious disease transmission is strengthened due to the globalization of human activities. Using schistosomiasis as an example, we propose a conceptual model simulating the spatio-temporal dynamics of infectious diseases. We base the model on the knowledge of the interrelationship among the source, media, and the hosts of the disease. With the endemics data of schistosomiasis in Xichang, China, we demonstrate that the conceptual model is feasible; we introduce how remote sensing and geographic information systems techniques can be used in support of spatio-temporal modeling; we compare the different effects caused to the entire population when selecting different groups of people for schistosomiasis control. Our work illustrates the importance of such a modeling tool in supporting spatial decisions. Our modeling method can be directly applied to such infectious diseases as the plague, lyme disease, and hemorrhagic fever with renal syndrome. The application of remote sensing and geographic information systems can shed light on the modeling of other infectious disease and invasive species studies. © 2006 Science in China Press.
Persistent Identifierhttp://hdl.handle.net/10722/296604
ISSN
2011 Impact Factor: 1.610
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorGong, Peng-
dc.contributor.authorXu, Bing-
dc.contributor.authorLiang, Song-
dc.date.accessioned2021-02-25T15:16:15Z-
dc.date.available2021-02-25T15:16:15Z-
dc.date.issued2006-
dc.identifier.citationScience in China, Series C: Life Sciences, 2006, v. 49, n. 6, p. 573-582-
dc.identifier.issn1006-9305-
dc.identifier.urihttp://hdl.handle.net/10722/296604-
dc.description.abstractSimilar to species immigration or exotic species invasion, infectious disease transmission is strengthened due to the globalization of human activities. Using schistosomiasis as an example, we propose a conceptual model simulating the spatio-temporal dynamics of infectious diseases. We base the model on the knowledge of the interrelationship among the source, media, and the hosts of the disease. With the endemics data of schistosomiasis in Xichang, China, we demonstrate that the conceptual model is feasible; we introduce how remote sensing and geographic information systems techniques can be used in support of spatio-temporal modeling; we compare the different effects caused to the entire population when selecting different groups of people for schistosomiasis control. Our work illustrates the importance of such a modeling tool in supporting spatial decisions. Our modeling method can be directly applied to such infectious diseases as the plague, lyme disease, and hemorrhagic fever with renal syndrome. The application of remote sensing and geographic information systems can shed light on the modeling of other infectious disease and invasive species studies. © 2006 Science in China Press.-
dc.languageeng-
dc.relation.ispartofScience in China, Series C: Life Sciences-
dc.subjectSpatial connectivity-
dc.subjectSpatio-temporal modeling-
dc.subjectBiological invasion-
dc.subjectPrevention and control of infectious diseases-
dc.titleRemote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases-
dc.typeArticle-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1007/s11427-006-2015-0-
dc.identifier.pmid17312996-
dc.identifier.pmcidPMC7089397-
dc.identifier.scopuseid_2-s2.0-33846557975-
dc.identifier.volume49-
dc.identifier.issue6-
dc.identifier.spage573-
dc.identifier.epage582-
dc.identifier.eissn1862-2798-
dc.identifier.isiWOS:000242546100008-
dc.identifier.issnl1006-9305-

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