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

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Bowman, Leigh, Tejeda, Gustavo S, Coelho, Giovanini E, Sulaiman, Lokman H, Gill, Balvinder S, McCall, Philip ORCID: https://orcid.org/0000-0002-0007-3985, Olliaro, Piero L, Ranzinger, Silvia R, Quang, Luong C, Ramm, Ronald S, Kroeger, Axel and Petzold, Max G (2016) 'Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America.'. PLoS ONE, Vol 11, Issue 6, e0157971.

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Abstract

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.

Item Type: Article
Subjects: WA Public Health > WA 105 Epidemiology
WA Public Health > Statistics. Surveys > WA 950 Theory or methods of medical statistics. Epidemiologic methods
WB Practice of Medicine > Medical Climatology > WB 700 Medical climatology. Geography of disease
WC Communicable Diseases > Virus Diseases > Infectious Mononucleosis. Arbovirus Infections > WC 528 Dengue
Faculty: Department: Clinical Sciences & International Health > International Public Health Department
Biological Sciences > Vector Biology Department
Digital Object Identifer (DOI): https://doi.org/10.1371/journal.pone.0157971
Depositing User: Jessica Jones
Date Deposited: 29 Jun 2016 09:30
Last Modified: 06 Feb 2018 13:12
URI: https://archive.lstmed.ac.uk/id/eprint/5955

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