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      The Driving Force for 2014 Dengue Outbreak in Guangdong, China

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          Abstract

          Dengue fever has rapidly spread in recent decades to become the most globally expansive viral vector-borne disease. In mainland China, a number of dengue outbreaks have been reported since 1978, but the worst epidemic in decades, involving 45230 cases and 76 imported cases, resulting in six deaths in Guangdong province, emerged in 2014. Reasons for this ongoing surge in dengue, both imported and autochthonous, are currently unclear and demand urgent investigation. Here, a seasonally-driven dynamic epidemiological model was used to simulate dengue transmission data recorded from the unprecedented outbreak. Sensitivity analysis demonstrate that delayed mosquito control, the continuous importations between the end of April to the early of July, the transmission of asymptomatic dengue infections, and the abnormally high precipitation from May to August might be the causal factors for the unprecedented outbreak. Our results suggested that the earlier and more frequent control measures in targeting immature and adult mosquitoes were effective in preventing larger outbreaks, and enhanced frontier health and quarantine from the end of April to the early of July for international communications and travelers.

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          Most cited references34

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          Reaction kinetics of poikilotherm development.

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            Vectorial Capacity of Aedes aegypti: Effects of Temperature and Implications for Global Dengue Epidemic Potential

            Dengue is a mosquito-borne viral disease that occurs mainly in the tropics and subtropics but has a high potential to spread to new areas. Dengue infections are climate sensitive, so it is important to better understand how changing climate factors affect the potential for geographic spread and future dengue epidemics. Vectorial capacity (VC) describes a vector's propensity to transmit dengue taking into account human, virus, and vector interactions. VC is highly temperature dependent, but most dengue models only take mean temperature values into account. Recent evidence shows that diurnal temperature range (DTR) plays an important role in influencing the behavior of the primary dengue vector Aedes aegypti. In this study, we used relative VC to estimate dengue epidemic potential (DEP) based on the temperature and DTR dependence of the parameters of A. aegypti. We found a strong temperature dependence of DEP; it peaked at a mean temperature of 29.3°C when DTR was 0°C and at 20°C when DTR was 20°C. Increasing average temperatures up to 29°C led to an increased DEP, but temperatures above 29°C reduced DEP. In tropical areas where the mean temperatures are close to 29°C, a small DTR increased DEP while a large DTR reduced it. In cold to temperate or extremely hot climates where the mean temperatures are far from 29°C, increasing DTR was associated with increasing DEP. Incorporating these findings using historical and predicted temperature and DTR over a two hundred year period (1901–2099), we found an increasing trend of global DEP in temperate regions. Small increases in DEP were observed over the last 100 years and large increases are expected by the end of this century in temperate Northern Hemisphere regions using climate change projections. These findings illustrate the importance of including DTR when mapping DEP based on VC.
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              Non-linear regression of biological temperature-dependent rate models based on absolute reaction-rate theory.

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2016
                18 November 2016
                : 11
                : 11
                : e0166211
                Affiliations
                [1 ]Complex Systems Research Center, Shanxi University, Taiyuan, Shan’xi, People’s Republic of China
                [2 ]School of Computer and Information Technology, Shanxi University, Taiyuan, Shan’xi, People’s Republic of China
                [3 ]Department of Disease Control, London School of Hygiene and Tropical Medicine, London, United Kingdom
                [4 ]LAMPS and Department of Mathematics and Statistics, York University, Toronto, Canada
                [5 ]Institute of Disease Control and Prevention, Academy of Military Medical Science, Beijing, People’s Republic of China
                Lanzhou University of Technology, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Data curation: ML WYZ.

                • Formal analysis: ML GQS.

                • Investigation: WYZ.

                • Methodology: ML GQS ZJ.

                • Validation: ML.

                • Writing – original draft: ML GQS ZJ.

                • Writing – review & editing: ML GQS LY HPZ ZJ WYZ.

                Article
                PONE-D-16-36070
                10.1371/journal.pone.0166211
                5115708
                27861514
                cc83ac00-9ec0-4e87-a22c-3f9581fc4a76
                © 2016 Li et al

                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 credited.

                History
                : 8 September 2016
                : 16 October 2016
                Page count
                Figures: 11, Tables: 3, Pages: 19
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 11331009
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 11671241
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 11601292
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 11301490
                Award Recipient :
                The project was funded by the National Natural Science Foundation of China under Grants (11331009, 11671241, 11601292, 11501340, 11501339 and 11301490), Research Project Supported by Shanxi Scholarship No. 2013-3, Natural Science Foundation of 369 Shanxi Province Grant No. 201601D021002, 131 Talents of Shanxi University, Program for the Outstanding Innovative Teams (OIT) of Higher Learning Institutions of Shanxi, and International Exchange Program of Postdoctor in Fudan University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Tropical Diseases
                Neglected Tropical Diseases
                Dengue Fever
                Medicine and Health Sciences
                Infectious Diseases
                Viral Diseases
                Dengue Fever
                People and Places
                Geographical Locations
                Asia
                China
                People and Places
                Demography
                Death Rates
                Biology and Life Sciences
                Population Biology
                Population Metrics
                Death Rates
                Medicine and Health Sciences
                Epidemiology
                Disease Vectors
                Insect Vectors
                Mosquitoes
                Biology and Life Sciences
                Organisms
                Animals
                Invertebrates
                Arthropoda
                Insects
                Mosquitoes
                Medicine and Health Sciences
                Infectious Diseases
                Infectious Disease Control
                Medicine and Health Sciences
                Epidemiology
                Infectious Disease Epidemiology
                Medicine and Health Sciences
                Infectious Diseases
                Infectious Disease Epidemiology
                Biology and Life Sciences
                Developmental Biology
                Life Cycles
                Larvae
                Biology and life sciences
                Organisms
                Viruses
                RNA viruses
                Flaviviruses
                Dengue Virus
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Viral Pathogens
                Flaviviruses
                Dengue Virus
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Viral Pathogens
                Flaviviruses
                Dengue Virus
                Biology and Life Sciences
                Organisms
                Viruses
                Viral Pathogens
                Flaviviruses
                Dengue Virus
                Custom metadata
                All relevant model and meteorological data are within the paper and its Supporting Information files. Data on reported Guangdong dengue fever cases was acquired through the China Information System for Disease Control and Prevention.

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                Uncategorized

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