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A Spatial-Temporal Approach to Differentiate Epidemic Risk Patterns
The purpose of disease mapping is to find spatial clustering and identify risk areas and potential epidemic initiators. Rather than relying on plotting either the case number or incidence rate, this chapter proposes three temporal risk indices: the probability of case occurrence (how often did uneve...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7121663/ http://dx.doi.org/10.1007/978-3-540-71318-0_16 |
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author | Wen, Tzai-hung Lin, Neal H Lin, Katherine Chun-min Fan, I-chun Su, Ming-daw King, Chwan-chuen |
author_facet | Wen, Tzai-hung Lin, Neal H Lin, Katherine Chun-min Fan, I-chun Su, Ming-daw King, Chwan-chuen |
author_sort | Wen, Tzai-hung |
collection | PubMed |
description | The purpose of disease mapping is to find spatial clustering and identify risk areas and potential epidemic initiators. Rather than relying on plotting either the case number or incidence rate, this chapter proposes three temporal risk indices: the probability of case occurrence (how often did uneven cases occur), the duration of an epidemic (how long did cases persist), and the intensity of a transmission (were the case of chronological significance). By integrating the three indicators using the local indicator of spatial autocorrelation (LISA) statistic, this chapter intends to develop a novel approach for evaluating spatial-temporal relationships with different risk patterns in the 2002 dengue epidemic, the worst outbreak in the past sixty years. With this approach, not only are hypotheses generated through the mapping processes in furthering investigation, but also procedures provided to identify spatial health risk levels with temporal characteristics. |
format | Online Article Text |
id | pubmed-7121663 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
record_format | MEDLINE/PubMed |
spelling | pubmed-71216632020-04-06 A Spatial-Temporal Approach to Differentiate Epidemic Risk Patterns Wen, Tzai-hung Lin, Neal H Lin, Katherine Chun-min Fan, I-chun Su, Ming-daw King, Chwan-chuen GIS for Health and the Environment Article The purpose of disease mapping is to find spatial clustering and identify risk areas and potential epidemic initiators. Rather than relying on plotting either the case number or incidence rate, this chapter proposes three temporal risk indices: the probability of case occurrence (how often did uneven cases occur), the duration of an epidemic (how long did cases persist), and the intensity of a transmission (were the case of chronological significance). By integrating the three indicators using the local indicator of spatial autocorrelation (LISA) statistic, this chapter intends to develop a novel approach for evaluating spatial-temporal relationships with different risk patterns in the 2002 dengue epidemic, the worst outbreak in the past sixty years. With this approach, not only are hypotheses generated through the mapping processes in furthering investigation, but also procedures provided to identify spatial health risk levels with temporal characteristics. 2007 /pmc/articles/PMC7121663/ http://dx.doi.org/10.1007/978-3-540-71318-0_16 Text en © Springer-Verlag Berlin Heidelberg New York 2007 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 Wen, Tzai-hung Lin, Neal H Lin, Katherine Chun-min Fan, I-chun Su, Ming-daw King, Chwan-chuen A Spatial-Temporal Approach to Differentiate Epidemic Risk Patterns |
title | A Spatial-Temporal Approach to Differentiate Epidemic Risk Patterns |
title_full | A Spatial-Temporal Approach to Differentiate Epidemic Risk Patterns |
title_fullStr | A Spatial-Temporal Approach to Differentiate Epidemic Risk Patterns |
title_full_unstemmed | A Spatial-Temporal Approach to Differentiate Epidemic Risk Patterns |
title_short | A Spatial-Temporal Approach to Differentiate Epidemic Risk Patterns |
title_sort | spatial-temporal approach to differentiate epidemic risk patterns |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7121663/ http://dx.doi.org/10.1007/978-3-540-71318-0_16 |
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