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Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases
Similar 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 mode...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Science in China Press
2006
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089397/ https://www.ncbi.nlm.nih.gov/pubmed/17312996 http://dx.doi.org/10.1007/s11427-006-2015-0 |
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author | Gong, Peng Xu, Bing Liang, Song |
author_facet | Gong, Peng Xu, Bing Liang, Song |
author_sort | Gong, Peng |
collection | PubMed |
description | Similar 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. |
format | Online Article Text |
id | pubmed-7089397 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | Science in China Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-70893972020-03-23 Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases Gong, Peng Xu, Bing Liang, Song Sci China C Life Sci Article Similar 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. Science in China Press 2006 /pmc/articles/PMC7089397/ /pubmed/17312996 http://dx.doi.org/10.1007/s11427-006-2015-0 Text en © Science in China Press 2006 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Gong, Peng Xu, Bing Liang, Song Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases |
title | Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases |
title_full | Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases |
title_fullStr | Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases |
title_full_unstemmed | Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases |
title_short | Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases |
title_sort | remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089397/ https://www.ncbi.nlm.nih.gov/pubmed/17312996 http://dx.doi.org/10.1007/s11427-006-2015-0 |
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