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      Effects of local and regional climatic fluctuations on dengue outbreaks in southern Taiwan

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      Author(s): 1 , * , 2 , 3 , 1
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      Publication date (Electronic):
      Journal: PLoS ONE
      Publisher: Public Library of Science

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          Abstract

          Background

          Southern Taiwan has been a hotspot for dengue fever transmission since 1998. During 2014 and 2015, Taiwan experienced unprecedented dengue outbreaks and the causes are poorly understood. This study aims to investigate the influence of regional and local climate conditions on the incidence of dengue fever in Taiwan, as well as to develop a climate-based model for future forecasting.

          Methodology/Principle findings

          Historical time-series data on dengue outbreaks in southern Taiwan from 1998 to 2015 were investigated. Local climate variables were analyzed using a distributed lag non-linear model (DLNM), and the model of best fit was used to predict dengue incidence between 2013 and 2015. The cross-wavelet coherence approach was used to evaluate the regional El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) effects on dengue incidence and local climate variables. The DLNM results highlighted the important non-linear and lag effects of minimum temperature and precipitation. Minimum temperature above 23°C or below 17°C can increase dengue incidence rate with lag effects of 10 to 15 weeks. Moderate to high precipitation can increase dengue incidence rates with a lag of 10 or 20 weeks. The model of best fit successfully predicted dengue transmission between 2013 and 2015. The prediction accuracy ranged from 0.7 to 0.9, depending on the number of weeks ahead of the prediction. ENSO and IOD were associated with nonstationary inter-annual patterns of dengue transmission. IOD had a greater impact on the seasonality of local climate conditions.

          Conclusions/Significance

          Our findings suggest that dengue transmission can be affected by regional and local climatic fluctuations in southern Taiwan. The climate-based model developed in this study can provide important information for dengue early warning systems in Taiwan. Local climate conditions might be influenced by ENSO and IOD, to result in unusual dengue outbreaks.

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          Most cited references57

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          Impact of daily temperature fluctuations on dengue virus transmission by Aedes aegypti.

          Louis Lambrechts, Krijn Paaijmans, Thanyalak Fansiri … (2011)
          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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            The epidemiology of dengue in the americas over the last three decades: a worrisome reality.

            José San Martín, Olivia Brathwaite, Betzana Zambrano … (2010)
            We have reported the epidemic patterns of dengue disease in the Region of the Americas from 1980 through 2007. Dengue cases reported to the Pan American Health Organization were analyzed from three periods: 1980-1989 (80s), 1990-1999 (90s), and 2000-2007 (2000-7). Age distribution data were examined from Brazil, Venezuela, Honduras, and Mexico. Cases increased over time: 1,033,417 (80s) to 2,725,405 (90s) to 4,759,007 (2000-7). The highest concentrations were reported in the Hispanic Caribbean (39.1%) in the 80s shifting to the Southern Cone in the 90s (55%) and 2000-7 (62.9%). From 1980 through 1987, 242 deaths were reported compared with 1,391 during 2000-7. The most frequently isolated serotypes were DENV-1 and DENV-2 (90s) and DENV-2 and DENV-3 (2000-7). The highest incidence was observed among adolescents and young adults; dengue hemorrhagic fever incidence was highest among infants in Venezuela. Increasing dengue morbidity/mortality was observed in the Americas in recent decades.
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              Malaria early warnings based on seasonal climate forecasts from multi-model ensembles.

              S. Connor, T Phindela, Juan F Reyes … (2006)
              The control of epidemic malaria is a priority for the international health community and specific targets for the early detection and effective control of epidemics have been agreed. Interannual climate variability is an important determinant of epidemics in parts of Africa where climate drives both mosquito vector dynamics and parasite development rates. Hence, skilful seasonal climate forecasts may provide early warning of changes of risk in epidemic-prone regions. Here we discuss the development of a system to forecast probabilities of anomalously high and low malaria incidence with dynamically based, seasonal-timescale, multi-model ensemble predictions of climate, using leading global coupled ocean-atmosphere climate models developed in Europe. This forecast system is successfully applied to the prediction of malaria risk in Botswana, where links between malaria and climate variability are well established, adding up to four months lead time over malaria warnings issued with observed precipitation and having a comparably high level of probabilistic prediction skill. In years in which the forecast probability distribution is different from that of climatology, malaria decision-makers can use this information for improved resource allocation.
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                Author and article information

                Contributors
                Andrew S Azman: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 2 June 2017
                Publication date Collection: 2017
                Volume: 12
                Issue: 6
                Electronic Location Identifier: e0178698
                Affiliations
                [1 ]Department of Molecular Parasitology and Tropical Diseases, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
                [2 ]Centro de Investigaciones en Enfermedades Tropicales, Universidad de Costa Rica, San Pedro de Montes de Oca, Costa Rica
                [3 ]Programa de Investigación en Enfermedades Tropicales (PIET), Escuela de Medicina Veterinaria, Universidad Nacional, Heredia, Costa Rica
                Johns Hopkins Bloomberg School of Public Health, UNITED STATES
                Author notes

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

                • Conceptualization: TWC LFC.

                • Data curation: TWC PJC.

                • Formal analysis: TWC.

                • Funding acquisition: TWC.

                • Investigation: TWC LFC.

                • Methodology: TWC LFC.

                • Software: TWC PJC.

                • Visualization: TWC LFC.

                • Writing – original draft: TWC.

                Author information
                http://orcid.org/0000-0001-8359-8172
                Article
                Publisher ID: PONE-D-17-18770
                DOI: 10.1371/journal.pone.0178698
                PMC ID: 5456348
                PubMed ID: 28575035
                SO-VID: 2495724c-2e80-4a2e-bdd7-019dc68a1ff8
                Copyright © © 2017 Chuang et al
                License:

                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
                Date received : 9 December 2016
                Date accepted : 17 May 2017
                Page count
                Figures: 8, Tables: 1, Pages: 20
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100004663, Ministry of Science and Technology, Taiwan;
                Award ID: MOST 104-2119-M-038-002
                Award Recipient :
                ORCID: http://orcid.org/0000-0001-8359-8172
                Funded by: funder-id http://dx.doi.org/10.13039/501100004700, Taipei Medical University;
                Award ID: NTPU-TMU-103-01
                Award Recipient :
                ORCID: http://orcid.org/0000-0001-8359-8172
                This study was funded by the Ministry of Science and Technology, Taiwan (MOST104-2119-M-038-002) and the University System of Taipei Joint Research Program (NTPU-TMU-103-01). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Research Article
                Subject: People and Places
                Subject: Geographical Locations
                Subject: Asia
                Subject: Taiwan
                Subject: Earth Sciences
                Subject: Atmospheric Science
                Subject: Meteorology
                Subject: Rain
                Subject: Earth sciences
                Subject: Atmospheric science
                Subject: Climatology
                Subject: El Ni単o-Southern Oscillation
                Subject: Earth sciences
                Subject: Marine and aquatic sciences
                Subject: Oceanography
                Subject: El Ni単o-Southern Oscillation
                Subject: Medicine and Health Sciences
                Subject: Tropical Diseases
                Subject: Neglected Tropical Diseases
                Subject: Dengue Fever
                Subject: Medicine and Health Sciences
                Subject: Infectious Diseases
                Subject: Viral Diseases
                Subject: Dengue Fever
                Subject: Earth Sciences
                Subject: Atmospheric Science
                Subject: Meteorology
                Subject: Research and Analysis Methods
                Subject: Mathematical and Statistical Techniques
                Subject: Statistical Methods
                Subject: Forecasting
                Subject: Physical Sciences
                Subject: Mathematics
                Subject: Statistics (Mathematics)
                Subject: Statistical Methods
                Subject: Forecasting
                Subject: Medicine and Health Sciences
                Subject: Infectious Diseases
                Subject: Infectious Disease Control
                Subject: Earth Sciences
                Subject: Atmospheric Science
                Subject: Meteorology
                Subject: Humidity
                Custom metadata
                Data Availability Data are available from the Taiwan CDC Institutional Data Access / Ethics Committee for researchers who meet the criteria for access to confidential data. Contact Info: timmy5471@ 123456cdc.gov.tw (Mrs. Yuan-Li Yeh).

                ScienceOpen disciplines: Uncategorized
                Data availability:
                ScienceOpen disciplines: Uncategorized

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