Correction: Effects of local and regional climatic fluctuations on dengue outbreaks in southern Taiwan.
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ABSTRACT:
SUBMITTER: PLOS ONE Staff
PROVIDER: S-EPMC5509367 | biostudies-literature | 2017
REPOSITORIES: biostudies-literature
Publications
Correction: Effects of local and regional climatic fluctuations on dengue outbreaks in southern Taiwan.
PloS one 20170713 7
[This corrects the article DOI: 10.1371/journal.pone.0178698.]. ...[more]
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Project description:BackgroundSouthern 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 findingsHistorical 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/significanceOur 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.
| S-EPMC5456348 | biostudies-literature
Project description: Not available
| S-EPMC5180368 | biostudies-literature
Project description:BackgroundDengue fever is the most common arboviral infection in humans, with viral transmissions occurring in more than 100 countries in tropical regions. A global strategy for dengue prevention and control was established more than 10 years ago. However, the factors that drive the transmission of the dengue virus and subsequent viral infection continue unabated. The largest dengue outbreaks in Taiwan since World War II occurred in two recent successive years: 2014 and 2015.MethodsWe performed a systematic analysis to detect and recognize spatial and temporal clustering patterns of dengue incidence in geographical areas of Taiwan, using the map-based pattern recognition procedure and scan test. Our aim was to recognize geographical heterogeneity patterns of varying dengue incidence intensity and detect hierarchical incidence intensity clusters.ResultsUsing the map-based pattern recognition procedure, we identified and delineated two separate hierarchical dengue incidence intensity clusters that comprise multiple mutually adjacent geographical units with high dengue incidence rates. We also found that that dengue incidence tends to peak simultaneously and homogeneously among the neighboring geographic units with high rates in the same cluster.ConclusionBeyond significance testing, this study is particularly desired by and useful for health authorities who require optimal characteristics of disease incidence patterns on maps and over time. Among the integrated components for effective prevention and control of dengue and dengue hemorrhagic fever are active surveillance and community-based integrated mosquito control, for which this study provides valuable inferences. Effective dengue prevention and control programs in Taiwan are critical, and have the added benefit of controlling the potential emergence of Zika.
| S-EPMC5987425 | biostudies-literature
Project description:Dengue fever is a viral disease transmitted by mosquitoes. In recent decades, dengue fever has spread throughout the world. In 2014 and 2015, southern Taiwan experienced its most serious dengue outbreak in recent years. Some statistical models have been established in the past, however, these models may not be suitable for predicting huge outbreaks in 2014 and 2015. The control of dengue fever has become the primary task of local health agencies. This study attempts to predict the occurrence of dengue fever in order to achieve the purpose of timely warning. We applied a newly developed autoregressive model (AR model) to assess the association between daily weather variability and daily dengue case number in 2014 and 2015 in Kaohsiung, the largest city in southern Taiwan. This model also contained additional lagged weather predictors, and developed 5-day-ahead and 15-day-ahead predictive models. Our results indicate that numbers of dengue cases in Kaohsiung are associated with humidity and the biting rate (BR). Our model is simple, intuitive and easy to use. The developed model can be embedded in a "real-time" schedule, and the data (at present) can be updated daily or weekly based on the needs of public health workers. In this study, a simple model using only meteorological factors performed well. The proposed real-time forecast model can help health agencies take public health actions to mitigate the influences of the epidemic.
| S-EPMC7384612 | biostudies-literature
Project description:Tree neighbourhood modelling has significantly contributed to our understanding of the mechanisms structuring communities. Investigations into the impact of neighbouring crowding on tree performance have generally been conducted at local scales, missing important regional-scale context such as the suitability of the climate for each species. Favourable climates may enhance tree performance, but this may come at the cost of increased neighbourhood crowding and competition negatively impacting survival and growth. Through the synthesis of continental-scale forest inventory and trait datasets from the northeast USA and Puerto Rico we present an analytical approach that elucidates the important interactions between local competitive and regional climatic contexts. Our results show strong asymmetries in competitive interactions and significant niche differences that are dependent on habitat suitability. The strong interaction between local neighbourhood and regional climate highlights the need for models that consider the interaction between these two processes that have been previously ignored.
| S-EPMC5454270 | biostudies-literature
Project description:Empirical research has shown that climate-related variables, the decline in economic well-being, and the mutual reinforcement of positive checks are the primary drivers of epidemic outbreaks in recent human history. However, their relative importance in causing the outbreak of epidemics is rarely examined quantitatively in a single study. I sought to address this issue by analyzing the 1402 epidemic incidents in China between 1841 and 1911, which partially overlaps partly with the Third Pandemic period. Fine-grained historical big data, multiple regression, and wavelet coherence analysis were employed. Statistical results show that economic fluctuations drove the country-wide epidemics outbreaks in China in inter-annual and decadal time scales. Economic fluctuations could cause short-term hardship and long-term impoverishment to the underprivileged social groups since a large portion of the Chinese population lived at the subsistence level in the past. The fluctuations might have sustained the repeated waves of epidemic outbreaks during the Third Pandemic period.Supplementary informationThe online version contains supplementary material available at 10.1007/s10745-021-00272-7.
| S-EPMC8527977 | biostudies-literature
Project description:BackgroundChina's Guangdong Province experienced a major dengue outbreak in 2014. Here we investigate if the weather conditions contributing to the outbreak can be elucidated by multi-scale models.MethodsA multi-scale modelling framework, parameterized by available weather, vector and human case data, was used to examine the integrative effect of temperature and precipitation variation on the effective reproduction number (ERN) of dengue fever.ResultsWith temperature in the range of 25-30 °C, increasing precipitation leads to an increase in the ERN with an average lag of 10 days. With monthly precipitation fixed, the more regular the pattern of rainfall (i.e. higher numbers of rainy days), the larger is the total number of adult mosquitoes. A rainfall distribution peaking in June and July produces a large ERN, beneficial to transmission. Climate conditions conducive to major outbreaks within a season are a combination of relatively high temperature, high precipitation peaking in June and July, and uninterrupted drizzle or regular rainfall.ConclusionsEvaluating a set of weather conditions favourable to a future major dengue outbreak requires near-future prediction of temperature variation, total rainfall and its peaking times. Such information permits seasonal rapid response management decisions due to the lags between the precipitation events and the realisation of the ERN.
| S-EPMC6341621 | biostudies-literature
Project description:Most research on the effects of environmental change in freshwaters has focused on incremental changes in average conditions, rather than fluctuations or extreme events such as heatwaves, cold snaps, droughts, floods or wildfires, which may have even more profound consequences. Such events are commonly predicted to increase in frequency, intensity and duration with global climate change, with many systems being exposed to conditions with no recent historical precedent. We propose a mechanistic framework for predicting potential impacts of environmental fluctuations on running-water ecosystems by scaling up effects of fluctuations from individuals to entire ecosystems. This framework requires integration of four key components: effects of the environment on individual metabolism, metabolic and biomechanical constraints on fluctuating species interactions, assembly dynamics of local food webs, and mapping the dynamics of the meta-community onto ecosystem function. We illustrate the framework by developing a mathematical model of environmental fluctuations on dynamically assembling food webs. We highlight (currently limited) empirical evidence for emerging insights and theoretical predictions. For example, widely supported predictions about the effects of environmental fluctuations are: high vulnerability of species with high per capita metabolic demands such as large-bodied ones at the top of food webs; simplification of food web network structure and impaired energetic transfer efficiency; and reduced resilience and top-down relative to bottom-up regulation of food web and ecosystem processes. We conclude by identifying key questions and challenges that need to be addressed to develop more accurate and predictive bio-assessments of the effects of fluctuations, and implications of fluctuations for management practices in an increasingly uncertain world.
| S-EPMC4843695 | biostudies-literature
Project description:Severe dengue fever is usually associated with secondary infection by a dengue virus (DENV) serotype (1 to 4) that is different to the serotype of the primary infection. Dengue outbreaks only occur following importations of DENV in Cairns, Australia. However, the majority of imported cases do not result in autochthonous transmission in Cairns. Although DENV transmission is strongly associated with the El Niño-Southern Oscillation (ENSO) climate cycle and local weather conditions, the frequency and potential risk factors of infections with the different DENV serotypes, including whether or not they differ, is unknown. This study used a classification tree model to identify the hierarchical interactions between Southern Oscillation Index (SOI), local weather factors, the presence of imported serotypes and the occurrence of the four autochthonous DENV serotypes from January 2000-December 2009 in Cairns. We found that the 12-week moving average of SOI and the 2-week moving average of maximum temperature were the most important factors influencing the variation in the weekly occurrence of the four DENV serotypes, the likelihoods of the occurrence of the four DENV serotypes may be unequal under the same environmental conditions, and occurrence may be influenced by changes in global and local environmental conditions in Cairns.
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Project description:This research examines the climatic origins of the diffusion of Neolithic agriculture across countries and archaeological sites. The theory suggests that a foraging society's history of climatic shocks shaped the timing of its adoption of farming. Specifically, as long as climatic disturbances did not lead to a collapse of the underlying resource base, the rate at which hunter-gatherers were climatically propelled to experiment with their habitats determined the accumulation of tacit knowledge complementary to farming. Consistent with the proposed hypothesis, the empirical investigation demonstrates that, conditional on biogeographic endowments, climatic volatility has a hump-shaped effect on the timing of the adoption of agriculture.
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