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- Publisher Website: 10.1080/10824009609480483
- Scopus: eid_2-s2.0-84962378344
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Article: Gis based spatial network models of schistosomiasis infection
| Title | Gis based spatial network models of schistosomiasis infection |
|---|---|
| Authors | |
| Issue Date | 1996 |
| Citation | Geographic Information Sciences, 1996, v. 2, n. 1-2, p. 51-57 How to Cite? |
| Abstract | It is known from experience of field epidemiologists that spatial factors play an important role in schistosomiasis transmission. This study applied a Geographic Information System (GIS) to assist understandings and control of schistosomiasis transmission in a mountainous region of Sichuan Province in southwestern China. The spatial network approach was shown to be useful in conjunction with the analytical and modeling capability of the GIS in exploring the epidemiology and spatial risk factors associated with schistosomiasis. The results showed statistically the significant spatial relationships among risk factors and the simple spatial regressive and autoregressive models predict the risk of schistosomiasis infection well. We promise for the development of public health intervention strategies and control programs. © 1996 Taylor & Francis Group, LLC. |
| Persistent Identifier | http://hdl.handle.net/10722/296772 |
| ISSN |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Zhou, Yi | - |
| dc.contributor.author | Maszle, Don | - |
| dc.contributor.author | Gong, Peng | - |
| dc.contributor.author | Spear, R. C. | - |
| dc.contributor.author | Gu, Xueguang | - |
| dc.date.accessioned | 2021-02-25T15:16:39Z | - |
| dc.date.available | 2021-02-25T15:16:39Z | - |
| dc.date.issued | 1996 | - |
| dc.identifier.citation | Geographic Information Sciences, 1996, v. 2, n. 1-2, p. 51-57 | - |
| dc.identifier.issn | 1082-4006 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/296772 | - |
| dc.description.abstract | It is known from experience of field epidemiologists that spatial factors play an important role in schistosomiasis transmission. This study applied a Geographic Information System (GIS) to assist understandings and control of schistosomiasis transmission in a mountainous region of Sichuan Province in southwestern China. The spatial network approach was shown to be useful in conjunction with the analytical and modeling capability of the GIS in exploring the epidemiology and spatial risk factors associated with schistosomiasis. The results showed statistically the significant spatial relationships among risk factors and the simple spatial regressive and autoregressive models predict the risk of schistosomiasis infection well. We promise for the development of public health intervention strategies and control programs. © 1996 Taylor & Francis Group, LLC. | - |
| dc.language | eng | - |
| dc.relation.ispartof | Geographic Information Sciences | - |
| dc.title | Gis based spatial network models of schistosomiasis infection | - |
| dc.type | Article | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1080/10824009609480483 | - |
| dc.identifier.scopus | eid_2-s2.0-84962378344 | - |
| dc.identifier.volume | 2 | - |
| dc.identifier.issue | 1-2 | - |
| dc.identifier.spage | 51 | - |
| dc.identifier.epage | 57 | - |
| dc.identifier.issnl | 1082-4006 | - |