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      Multiyear Climate Variability and Dengue—El Niño Southern Oscillation, Weather, and Dengue Incidence in Puerto Rico, Mexico, and Thailand: A Longitudinal Data Analysis

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          Abstract

          Michael Johansson and colleagues use wavelet analysis to show that there is limited evidence for a multiyear relationship between climate and dengue incidence in Puerto Rico, Mexico, and Thailand.

          Abstract

          Background

          The mosquito-borne dengue viruses are a major public health problem throughout the tropical and subtropical regions of the world. Changes in temperature and precipitation have well-defined roles in the transmission cycle and may thus play a role in changing incidence levels. The El Niño Southern Oscillation (ENSO) is a multiyear climate driver of local temperature and precipitation worldwide. Previous studies have reported varying degrees of association between ENSO and dengue incidence.

          Methods and Findings

          We analyzed the relationship between ENSO, local weather, and dengue incidence in Puerto Rico, Mexico, and Thailand using wavelet analysis to identify time- and frequency-specific association. In Puerto Rico, ENSO was transiently associated with temperature and dengue incidence on multiyear scales. However, only local precipitation and not temperature was associated with dengue on multiyear scales. In Thailand, ENSO was associated with both temperature and precipitation. Although precipitation was associated with dengue incidence, the association was nonstationary and likely spurious. In Mexico, no association between any of the variables was observed on the multiyear scale.

          Conclusions

          The evidence for a relationship between ENSO, climate, and dengue incidence presented here is weak. While multiyear climate variability may play a role in endemic interannual dengue dynamics, we did not find evidence of a strong, consistent relationship in any of the study areas. The role of ENSO may be obscured by local climate heterogeneity, insufficient data, randomly coincident outbreaks, and other, potentially stronger, intrinsic factors regulating transmission dynamics.

          Please see later in the article for the Editors' Summary

          Editors' Summary

          Background

          Every year, as many as 50–100 million people become infected with one of four closely related dengue viruses through the bite of a female Aedes aegypti mosquito that has acquired the virus by feeding on infected human blood. Dengue is endemic (always present) in many tropical and subtropical countries but its incidence (the number of new cases in a population over a given time period) follows a seasonal pattern. This is because the abundance of Ae. aegypti is regulated by rainfall, which provides breeding sites and stimulates egg hatching, and by temperature, which influences the insects' survival and their rate of development and reproduction. Temperature also affects the mosquitoes' ability to transmit dengue virus—higher temperatures increase transmission rates. Although some people who become infected with dengue have no symptoms, many develop dengue fever, a severe, flu-like illness that lasts a few days. Other people—more than half a million a year—develop dengue hemorrhagic fever, a potentially fatal condition. There is no vaccine to prevent dengue and no specific treatment for the disease, but standard medical care can prevent most deaths from dengue.

          Why Was This Study Done?

          As well as seasonal variations in the incidence of dengue, large dengue outbreaks (epidemics) occur every few years. To help with health care planning, public health officials would like a way to predict when these epidemics are likely to occur, but to develop such a system requires a good understanding of the factors that lead to major epidemics. Although variations in host–virus interactions (for example, changes in host immunity to dengue) almost certainly play an important role in the timing of dengue epidemics, interannual changes in temperature and rainfall could also be involved. One major cause of global interannual weather variation is the El Niño Southern Oscillation (ENSO), a climate cycle centered on the Pacific Ocean that repeats every 3–4 years. Previous studies have reported varying degrees of association between ENSO and dengue. In this study, the researchers reanalyze the relationship between ENSO, local weather, and dengue incidence in three dengue-endemic countries using “wavelet analysis.” This mathematical technique can separate the effects of seasonal weather variations on dengue incidence from those of interannual weather fluctuations.

          What Did the Researchers Do and Find?

          The researchers retrieved data on the incidence of dengue fever and dengue hemorrhagic fever in Puerto Rico, Thailand and Mexico since the mid 1980s from national surveillance systems. They also collected historical weather data for each country and information on ENSO. They then used these data and wavelet analysis to investigate the relationship between ENSO, local weather, and dengue incidence in each country on the annual scale and on the multiyear scale. On the annual scale, temperature, rainfall, and dengue incidence were strongly associated in all three countries. On the multiyear scale, ENSO was associated with temperature and with dengue incidence in Puerto Rico, but only for part of the study period. Only local rainfall was associated with the incidence of dengue in that country. The lack of a direct path of association from ENSO to either weather variable to dengue incidence suggests that the ENSO–dengue association may be a spurious result. In Thailand, ENSO was associated with both temperature and rainfall, and rainfall was associated with dengue incidence. However, detailed analysis suggests that this latter association was also probably spurious. Finally, there was no association between any of the variables in Mexico on the multiyear scale.

          What Do These Findings Mean?

          Although these findings show a strong associations between both temperature and rainfall and dengue incidence on the annual scale in Puerto Rico, Thailand, and Mexico, they provide little evidence for any relationship between ENSO, climate, and dengue incidence. Multiyear climate variability may play a role in interannual variations in dengue incidence, the researchers suggest, but their study does not provide any evidence for a strong and consistent relationship between climate variability and dengue incidence. It is possible that the effects of ENSO on dengue incidence are being masked by local variations in weather or by stronger factors regulating disease transmission such as host–virus or host–vector interactions. Future studies into the relationship between dengue outbreaks and multiyear climate variability will need to include these and other factors. For now, however, information on ENSO cannot be used to design an early warning system for dengue outbreaks.

          Additional Information

          Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000168.

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          Most cited references18

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          Dengue virus-mosquito interactions.

          The mosquito Aedes aegypti is more widely dispersed now than at any time in the past, placing billions of humans at risk of infection with one or more of the four dengue viruses. This review presents and discusses information on mosquito-dengue infection dynamics and describes the prominent role that temperature and rainfall play in controlling dengue viral transmission including discussions of the effect of interannual climate variations and the predicted effect of global warming. Complementary human determinants of dengue epidemiology include viremia titer, variation in viremic period, enhanced viremias, and threshold viremia. Topics covered include epidemiological phenomena such as traveling waves, the generation of genetic diversity of dengue viruses following virgin soil introductions and in hyperendemic settings, and evidence for and against viral virulence as a determinant of the severity of dengue infections. Also described is the crucial role of monotypic and heterotypic herd immunity in shaping dengue epidemic behavior.
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            Dynamic life table model for Aedes aegypti (Diptera: Culicidae): analysis of the literature and model development.

            The container-inhabiting mosquito simulation model (CIMSiM) is a weather-driven, dynamic life table simulation model of Aedes aegypti (L.). It is designed to provide a framework for related models of similar mosquitoes which inhibit artificial and natural containers. CIMSiM is an attempt to provide a mechanistic, comprehensive, and dynamic accounting of the multitude of relationships known to play a role in the life history of these mosquitoes. Development rates of eggs, larvae, pupae, and the gonotrophic cycle are based on temperature using an enzyme kinetics approach. Larval weight gain and food depletion are based on the differential equations of Gilpin & McClelland compensated for temperature. Survivals are a function of weather, habitat, and other factors. The heterogeneity of the larval habitat is depicted by modeling the immature cohorts within up to nine different containers, each of which represents an important type of mosquito-producing container in the field. The model provides estimates of the age-specific density of each life stage within a representative 1-ha area. CIMSiM is interactive and runs on IBM-compatible personal computers. The user specifies a region of the world of interest; the model responds with lists of countries and associated cities where historical data on weather, larval habitat, and human densities are available. Each location is tied to an environmental file containing a description of the significant mosquito-producing containers in the area and their characteristics. In addition to weather and environmental information, CIMSiM uses biological files that include species-specific values for each of the parameters used in the model. Within CIMSiM, it is possible to create new environmental and biological files or modify existing ones to allow simulations to be tailored to particular locations or to parameter sensitivity studies. The model also may be used to evaluate any number and combination of standard and novel control methods.
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              Ecological and immunological determinants of dengue epidemics.

              The management of infectious diseases is an increasingly important public health issue, the effective implementation of which is often complicated by difficulties in teasing apart the relative roles of extrinsic and intrinsic factors influencing transmission. Dengue, a vector-borne strain polymorphic disease, is one such infection where transmission dynamics are affected by environmental variables as well as immune-mediated serotype interactions. To understand how alternative hypotheses concerning dengue infection and transmission may explain observed multiannual cycles in disease incidence, we adopt a theoretical approach that combines both ecological and immunological mechanisms. We demonstrate that, contrary to perceived wisdom, patterns generated solely by antibody-dependent enhancement or heterogeneity in virus virulence are not consistent with serotype-specific notification data in important ways. Furthermore, to generate epidemics with the characteristic signatures observed in data, we find that a combination of seasonal variation in vector demography and, crucially, a short-lived period of cross-immunity is sufficient. We then show how understanding the persistence and eradication of dengue serotypes critically depends on the alternative assumed mechanisms.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, USA )
                1549-1277
                1549-1676
                November 2009
                November 2009
                17 November 2009
                : 6
                : 11
                : e1000168
                Affiliations
                [1 ]Dengue Branch, Division of Vector-Borne Infectious Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico, United States of America
                [2 ]W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
                [3 ]Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
                University of Georgia, United States of America
                Author notes

                ICMJE criteria for authorship read and met: MAJ DATC GEG. Agree with the manuscript's results and conclusions: MAJ DATC GEG. Designed the experiments/the study: MAJ DATC GEG. Analyzed the data: MAJ GEG. Collected data/did experiments for the study: MAJ. Wrote the first draft of the paper: MAJ GEG. Contributed to the writing of the paper: MAJ DATC GEG.

                Article
                09-PLME-RA-0539R2
                10.1371/journal.pmed.1000168
                2771282
                19918363
                41e575cb-6d77-46ca-9498-c144b3101ac6
                This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
                History
                : 27 February 2009
                : 6 October 2009
                Page count
                Pages: 9
                Categories
                Research Article
                Ecology/Global Change Ecology
                Infectious Diseases/Neglected Tropical Diseases
                Infectious Diseases/Tropical and Travel-Associated Diseases
                Infectious Diseases/Viral Infections
                Mathematics/Statistics
                Public Health and Epidemiology/Epidemiology
                Public Health and Epidemiology/Global Health
                Public Health and Epidemiology/Infectious Diseases

                Medicine
                Medicine

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