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Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America

BACKGROUND: Worldwide, dengue is an unrelenting economic and health burden. Dengue outbreaks have become increasingly common, which place great strain on health infrastructure and services. Early warning models could allow health systems and vector control programmes to respond more cost-effectively...

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Autores principales: Bowman, Leigh R., Tejeda, Gustavo S., Coelho, Giovanini E., Sulaiman, Lokman H., Gill, Balvinder S., McCall, Philip J., Olliaro, Piero L., Ranzinger, Silvia R., Quang, Luong C., Ramm, Ronald S., Kroeger, Axel, Petzold, Max G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4922573/
https://www.ncbi.nlm.nih.gov/pubmed/27348752
http://dx.doi.org/10.1371/journal.pone.0157971
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author Bowman, Leigh R.
Tejeda, Gustavo S.
Coelho, Giovanini E.
Sulaiman, Lokman H.
Gill, Balvinder S.
McCall, Philip J.
Olliaro, Piero L.
Ranzinger, Silvia R.
Quang, Luong C.
Ramm, Ronald S.
Kroeger, Axel
Petzold, Max G.
author_facet Bowman, Leigh R.
Tejeda, Gustavo S.
Coelho, Giovanini E.
Sulaiman, Lokman H.
Gill, Balvinder S.
McCall, Philip J.
Olliaro, Piero L.
Ranzinger, Silvia R.
Quang, Luong C.
Ramm, Ronald S.
Kroeger, Axel
Petzold, Max G.
author_sort Bowman, Leigh R.
collection PubMed
description BACKGROUND: Worldwide, dengue is an unrelenting economic and health burden. Dengue outbreaks have become increasingly common, which place great strain on health infrastructure and services. Early warning models could allow health systems and vector control programmes to respond more cost-effectively and efficiently. METHODOLOGY/PRINCIPAL FINDINGS: The Shewhart method and Endemic Channel were used to identify alarm variables that may predict dengue outbreaks. Five country datasets were compiled by epidemiological week over the years 2007–2013. These data were split between the years 2007–2011 (historic period) and 2012–2013 (evaluation period). Associations between alarm/ outbreak variables were analysed using logistic regression during the historic period while alarm and outbreak signals were captured during the evaluation period. These signals were combined to form alarm/ outbreak periods, where 2 signals were equal to 1 period. Alarm periods were quantified and used to predict subsequent outbreak periods. Across Mexico and Dominican Republic, an increase in probable cases predicted outbreaks of hospitalised cases with sensitivities and positive predictive values (PPV) of 93%/ 83% and 97%/ 86% respectively, at a lag of 1–12 weeks. An increase in mean temperature ably predicted outbreaks of hospitalised cases in Mexico and Brazil, with sensitivities and PPVs of 79%/ 73% and 81%/ 46% respectively, also at a lag of 1–12 weeks. Mean age was predictive of hospitalised cases at sensitivities and PPVs of 72%/ 74% and 96%/ 45% in Mexico and Malaysia respectively, at a lag of 4–16 weeks. CONCLUSIONS/SIGNIFICANCE: An increase in probable cases was predictive of outbreaks, while meteorological variables, particularly mean temperature, demonstrated predictive potential in some countries, but not all. While it is difficult to define uniform variables applicable in every country context, the use of probable cases and meteorological variables in tailored early warning systems could be used to highlight the occurrence of dengue outbreaks or indicate increased risk of dengue transmission.
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spelling pubmed-49225732016-07-18 Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America Bowman, Leigh R. Tejeda, Gustavo S. Coelho, Giovanini E. Sulaiman, Lokman H. Gill, Balvinder S. McCall, Philip J. Olliaro, Piero L. Ranzinger, Silvia R. Quang, Luong C. Ramm, Ronald S. Kroeger, Axel Petzold, Max G. PLoS One Research Article BACKGROUND: Worldwide, dengue is an unrelenting economic and health burden. Dengue outbreaks have become increasingly common, which place great strain on health infrastructure and services. Early warning models could allow health systems and vector control programmes to respond more cost-effectively and efficiently. METHODOLOGY/PRINCIPAL FINDINGS: The Shewhart method and Endemic Channel were used to identify alarm variables that may predict dengue outbreaks. Five country datasets were compiled by epidemiological week over the years 2007–2013. These data were split between the years 2007–2011 (historic period) and 2012–2013 (evaluation period). Associations between alarm/ outbreak variables were analysed using logistic regression during the historic period while alarm and outbreak signals were captured during the evaluation period. These signals were combined to form alarm/ outbreak periods, where 2 signals were equal to 1 period. Alarm periods were quantified and used to predict subsequent outbreak periods. Across Mexico and Dominican Republic, an increase in probable cases predicted outbreaks of hospitalised cases with sensitivities and positive predictive values (PPV) of 93%/ 83% and 97%/ 86% respectively, at a lag of 1–12 weeks. An increase in mean temperature ably predicted outbreaks of hospitalised cases in Mexico and Brazil, with sensitivities and PPVs of 79%/ 73% and 81%/ 46% respectively, also at a lag of 1–12 weeks. Mean age was predictive of hospitalised cases at sensitivities and PPVs of 72%/ 74% and 96%/ 45% in Mexico and Malaysia respectively, at a lag of 4–16 weeks. CONCLUSIONS/SIGNIFICANCE: An increase in probable cases was predictive of outbreaks, while meteorological variables, particularly mean temperature, demonstrated predictive potential in some countries, but not all. While it is difficult to define uniform variables applicable in every country context, the use of probable cases and meteorological variables in tailored early warning systems could be used to highlight the occurrence of dengue outbreaks or indicate increased risk of dengue transmission. Public Library of Science 2016-06-27 /pmc/articles/PMC4922573/ /pubmed/27348752 http://dx.doi.org/10.1371/journal.pone.0157971 Text en © 2016 Bowman et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Bowman, Leigh R.
Tejeda, Gustavo S.
Coelho, Giovanini E.
Sulaiman, Lokman H.
Gill, Balvinder S.
McCall, Philip J.
Olliaro, Piero L.
Ranzinger, Silvia R.
Quang, Luong C.
Ramm, Ronald S.
Kroeger, Axel
Petzold, Max G.
Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America
title Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America
title_full Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America
title_fullStr Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America
title_full_unstemmed Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America
title_short Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America
title_sort alarm variables for dengue outbreaks: a multi-centre study in asia and latin america
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4922573/
https://www.ncbi.nlm.nih.gov/pubmed/27348752
http://dx.doi.org/10.1371/journal.pone.0157971
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