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Climate Cycles and Forecasts of Cutaneous Leishmaniasis, a Nonstationary Vector-Borne Disease
BACKGROUND: Cutaneous leishmaniasis (CL) is one of the main emergent diseases in the Americas. As in other vector-transmitted diseases, its transmission is sensitive to the physical environment, but no study has addressed the nonstationary nature of such relationships or the interannual patterns of...
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2006
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1539092/ https://www.ncbi.nlm.nih.gov/pubmed/16903778 http://dx.doi.org/10.1371/journal.pmed.0030295 |
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author | Chaves, Luis Fernando Pascual, Mercedes |
author_facet | Chaves, Luis Fernando Pascual, Mercedes |
author_sort | Chaves, Luis Fernando |
collection | PubMed |
description | BACKGROUND: Cutaneous leishmaniasis (CL) is one of the main emergent diseases in the Americas. As in other vector-transmitted diseases, its transmission is sensitive to the physical environment, but no study has addressed the nonstationary nature of such relationships or the interannual patterns of cycling of the disease. METHODS AND FINDINGS: We studied monthly data, spanning from 1991 to 2001, of CL incidence in Costa Rica using several approaches for nonstationary time series analysis in order to ensure robustness in the description of CL's cycles. Interannual cycles of the disease and the association of these cycles to climate variables were described using frequency and time-frequency techniques for time series analysis. We fitted linear models to the data using climatic predictors, and tested forecasting accuracy for several intervals of time. Forecasts were evaluated using “out of fit” data (i.e., data not used to fit the models). We showed that CL has cycles of approximately 3 y that are coherent with those of temperature and El Niño Southern Oscillation indices (Sea Surface Temperature 4 and Multivariate ENSO Index). CONCLUSIONS: Linear models using temperature and MEI can predict satisfactorily CL incidence dynamics up to 12 mo ahead, with an accuracy that varies from 72% to 77% depending on prediction time. They clearly outperform simpler models with no climate predictors, a finding that further supports a dynamical link between the disease and climate. |
format | Text |
id | pubmed-1539092 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-15390922006-09-18 Climate Cycles and Forecasts of Cutaneous Leishmaniasis, a Nonstationary Vector-Borne Disease Chaves, Luis Fernando Pascual, Mercedes PLoS Med Research Article BACKGROUND: Cutaneous leishmaniasis (CL) is one of the main emergent diseases in the Americas. As in other vector-transmitted diseases, its transmission is sensitive to the physical environment, but no study has addressed the nonstationary nature of such relationships or the interannual patterns of cycling of the disease. METHODS AND FINDINGS: We studied monthly data, spanning from 1991 to 2001, of CL incidence in Costa Rica using several approaches for nonstationary time series analysis in order to ensure robustness in the description of CL's cycles. Interannual cycles of the disease and the association of these cycles to climate variables were described using frequency and time-frequency techniques for time series analysis. We fitted linear models to the data using climatic predictors, and tested forecasting accuracy for several intervals of time. Forecasts were evaluated using “out of fit” data (i.e., data not used to fit the models). We showed that CL has cycles of approximately 3 y that are coherent with those of temperature and El Niño Southern Oscillation indices (Sea Surface Temperature 4 and Multivariate ENSO Index). CONCLUSIONS: Linear models using temperature and MEI can predict satisfactorily CL incidence dynamics up to 12 mo ahead, with an accuracy that varies from 72% to 77% depending on prediction time. They clearly outperform simpler models with no climate predictors, a finding that further supports a dynamical link between the disease and climate. Public Library of Science 2006-08 2006-08-15 /pmc/articles/PMC1539092/ /pubmed/16903778 http://dx.doi.org/10.1371/journal.pmed.0030295 Text en © 2006 Chaves and Pascual. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Chaves, Luis Fernando Pascual, Mercedes Climate Cycles and Forecasts of Cutaneous Leishmaniasis, a Nonstationary Vector-Borne Disease |
title | Climate Cycles and Forecasts of Cutaneous Leishmaniasis, a Nonstationary Vector-Borne Disease |
title_full | Climate Cycles and Forecasts of Cutaneous Leishmaniasis, a Nonstationary Vector-Borne Disease |
title_fullStr | Climate Cycles and Forecasts of Cutaneous Leishmaniasis, a Nonstationary Vector-Borne Disease |
title_full_unstemmed | Climate Cycles and Forecasts of Cutaneous Leishmaniasis, a Nonstationary Vector-Borne Disease |
title_short | Climate Cycles and Forecasts of Cutaneous Leishmaniasis, a Nonstationary Vector-Borne Disease |
title_sort | climate cycles and forecasts of cutaneous leishmaniasis, a nonstationary vector-borne disease |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1539092/ https://www.ncbi.nlm.nih.gov/pubmed/16903778 http://dx.doi.org/10.1371/journal.pmed.0030295 |
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