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      Dengue Virus in Sub-tropical Northern and Central Viet Nam: Population Immunity and Climate Shape Patterns of Viral Invasion and Maintenance

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          Abstract

          Dengue virus transmission occurs in both epidemic and endemic cycles across tropical and sub-tropical regions of the world. Incidence is particularly high in much of Southeast Asia, where hyperendemic transmission plagues both urban and rural populations. However, endemicity has not been established in some areas with climates that may not support year-round viral transmission. An understanding of how dengue viruses (DENV) enter these environments and whether the viruses persist in inapparent local transmission cycles is central to understanding how dengue emerges in areas at the margins of endemic transmission. Dengue is highly endemic in tropical southern Vietnam, while increasingly large seasonal epidemics have occurred in northern Viet Nam over the last decade. We have investigated the spread of DENV-1 throughout Vietnam to determine the routes by which the virus enters northern and central regions of the country. Phylogeographic analysis of 1,765 envelope (E) gene sequences from Southeast Asia revealed frequent movement of DENV between neighboring human populations and strong local clustering of viral lineages. Long-distance migration of DENV between human population centers also occurred regularly and on short time-scales, indicating human-mediated viral invasion into northern Vietnam. Human populations in southern Vietnam were found to be the primary source of DENV circulating throughout the country, while central and northern Vietnam acted as sink populations, likely due to reduced connectedness to other populations in the case of the central regions and to the influence of temperature variability on DENV replication and vector survival and competence in the north. Finally, phylogeographic analyses suggested that viral movement follows a gravity model and indicates that population immunity and physical and economic connections between populations may play important roles in shaping patterns of DENV transmission.

          Author Summary

          Reports from sub-tropical regions of the world suggest a growing risk of introduction and establishment of dengue viruses (DENV) in new locales. Recent dengue epidemics in northern Viet Nam present an opportunity to study how DENV invades and spreads in these environments. The proximity of this region to tropical areas experiencing year-round endemic DENV transmission makes it an ideal site for studying the effects of human population movement and climate on DENV emergence. We performed a phylogenetic analysis using DENV-1 envelope gene sequences from Southeast Asia. We show that DENV are regularly imported into northern and central Viet Nam from southern Vietnam, and that increasingly large seasonal epidemics in the north are caused by newly introduced viruses each year. While tropical Vietnam maintains localized virus populations for multiple years, cool winter temperatures in sub-tropical northern Viet Nam may reduce mosquito populations and virus replication to levels that are not conducive to year-round DENV transmission. Finally, we found that the dispersal of DENV across the region is well-described using human movement and immunity data, and believe that increased epidemiological, entomological, and virological surveillance are needed to understand the processes by which endemic DENV transmission becomes established in new populations.

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          Most cited references37

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          Improving the accuracy of demographic and molecular clock model comparison while accommodating phylogenetic uncertainty.

          Recent developments in marginal likelihood estimation for model selection in the field of Bayesian phylogenetics and molecular evolution have emphasized the poor performance of the harmonic mean estimator (HME). Although these studies have shown the merits of new approaches applied to standard normally distributed examples and small real-world data sets, not much is currently known concerning the performance and computational issues of these methods when fitting complex evolutionary and population genetic models to empirical real-world data sets. Further, these approaches have not yet seen widespread application in the field due to the lack of implementations of these computationally demanding techniques in commonly used phylogenetic packages. We here investigate the performance of some of these new marginal likelihood estimators, specifically, path sampling (PS) and stepping-stone (SS) sampling for comparing models of demographic change and relaxed molecular clocks, using synthetic data and real-world examples for which unexpected inferences were made using the HME. Given the drastically increased computational demands of PS and SS sampling, we also investigate a posterior simulation-based analogue of Akaike's information criterion (AIC) through Markov chain Monte Carlo (MCMC), a model comparison approach that shares with the HME the appealing feature of having a low computational overhead over the original MCMC analysis. We confirm that the HME systematically overestimates the marginal likelihood and fails to yield reliable model classification and show that the AICM performs better and may be a useful initial evaluation of model choice but that it is also, to a lesser degree, unreliable. We show that PS and SS sampling substantially outperform these estimators and adjust the conclusions made concerning previous analyses for the three real-world data sets that we reanalyzed. The methods used in this article are now available in BEAST, a powerful user-friendly software package to perform Bayesian evolutionary analyses.
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            Impact of daily temperature fluctuations on dengue virus transmission by Aedes aegypti.

            Most studies on the ability of insect populations to transmit pathogens consider only constant temperatures and do not account for realistic daily temperature fluctuations that can impact vector-pathogen interactions. Here, we show that diurnal temperature range (DTR) affects two important parameters underlying dengue virus (DENV) transmission by Aedes aegypti. In two independent experiments using different DENV serotypes, mosquitoes were less susceptible to virus infection and died faster under larger DTR around the same mean temperature. Large DTR (20 °C) decreased the probability of midgut infection, but not duration of the virus extrinsic incubation period (EIP), compared with moderate DTR (10 °C) or constant temperature. A thermodynamic model predicted that at mean temperatures 18 °C, larger DTR reduces DENV transmission. The negative impact of DTR on Ae. aegypti survival indicates that large temperature fluctuations will reduce the probability of vector survival through EIP and expectation of infectious life. Seasonal variation in the amplitude of daily temperature fluctuations helps to explain seasonal forcing of DENV transmission at locations where average temperature does not vary seasonally and mosquito abundance is not associated with dengue incidence. Mosquitoes lived longer and were more likely to become infected under moderate temperature fluctuations, which is typical of the high DENV transmission season than under large temperature fluctuations, which is typical of the low DENV transmission season. Our findings reveal the importance of considering short-term temperature variations when studying DENV transmission dynamics.
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              Correlating viral phenotypes with phylogeny: accounting for phylogenetic uncertainty.

              Many recent studies have sought to quantify the degree to which viral phenotypic characters (such as epidemiological risk group, geographic location, cell tropism, drug resistance state, etc.) are correlated with shared ancestry, as represented by a viral phylogenetic tree. Here, we present a new Bayesian Markov-Chain Monte Carlo approach to the investigation of such phylogeny-trait correlations. This method accounts for uncertainty arising from phylogenetic error and provides a statistical significance test of the null hypothesis that traits are associated randomly with phylogeny tips. We perform extensive simulations to explore and compare the behaviour of three statistics of phylogeny-trait correlation. Finally, we re-analyse two existing published data sets as case studies. Our framework aims to provide an improvement over existing methods for this problem.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Negl Trop Dis
                PLoS Negl Trop Dis
                plos
                plosntds
                PLoS Neglected Tropical Diseases
                Public Library of Science (San Francisco, USA )
                1935-2727
                1935-2735
                December 2013
                5 December 2013
                : 7
                : 12
                : e2581
                Affiliations
                [1 ]Centre for Immunity, Infection and Evolution, University of Edinburgh, Edinburgh, United Kingdom
                [2 ]Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
                [3 ]Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
                [4 ]Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Hanoi, Vietnam
                [5 ]National Institute of Hygiene and Epidemiology, Hanoi, Vietnam
                [6 ]Military Institute of Hygiene and Epidemiology, Hanoi, Vietnam
                [7 ]Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
                [8 ]Marie Bashir Institute for Emerging Diseases and Biosecurity, School of Biological Sciences and Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia
                [9 ]Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
                [10 ]Queensland University of Technology, Brisbane, Australia
                [11 ]Australian Army Malaria Institute, Brisbane, Australia
                University of California, Davis, United States of America
                Author notes

                There were no conflicts of interest. The views expressed in this article are those of the authors and do not represent the official policy or position of the Australian Department of Defence, the U.S. Department of the Army, U.S. Department of Defense, or the U.S. Government.

                Conceived and designed the experiments: MAR CPS AF ECH JGA. Performed the experiments: CPS AF LMQ NTTT LHY NXT. Analyzed the data: MAR. Contributed reagents/materials/analysis tools: CPS AF LMQ NTTT LHY RVG NXT. Wrote the paper: MAR CPS AF ECH JGA.

                Article
                PNTD-D-13-01017
                10.1371/journal.pntd.0002581
                3854975
                24340118
                dc19e1d2-203c-490d-aa2d-ba3d4168ca78
                Copyright @ 2013

                This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 25 March 2013
                : 29 October 2013
                Page count
                Pages: 12
                Funding
                Funding to MAR was provided by a National Science Foundation Graduate Research Fellowship and by the Wellcome Trust of the United Kingdom through the Vietnamese Initiative on Zoonotic InfectiONS (WT-VIZIONS). This study was supported by grants from the National Health and Medical Research Council of Australia (including an Australia Fellowship to ECH), the U.S. Global Emerging Infections Surveillance and Response System, and the National Institutes of Health (grant R01 GM087405 to ECH). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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