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      Hierarchical Bayesian Spatio–Temporal Analysis of Climatic and Socio–Economic Determinants of Rocky Mountain Spotted Fever

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          Abstract

          This study aims to examine the spatio-temporal dynamics of Rocky Mountain spotted fever (RMSF) prevalence in four contiguous states of Midwestern United States, and to determine the impact of environmental and socio–economic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatio–temporal interaction effect in the case reports submitted to the state health departments in the region. Various socio–economic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a main–effects Bayesian model in progressive steps to evaluate important drivers of RMSF space-time patterns in the region. Our results show a steady increase in RMSF incidence over the study period to newer geographic areas, and the posterior probabilities of county-specific trends indicate clustering of high risk counties in the central and southern parts of the study region. At the spatial scale of a county, the prevalence levels of RMSF is influenced by poverty status, average relative humidity, and average land surface temperature (>35°C) in the region, and the relevance of these factors in the context of climate–change impacts on tick–borne diseases are discussed.

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          Most cited references25

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          Impact of regional climate change on human health.

          The World Health Organisation estimates that the warming and precipitation trends due to anthropogenic climate change of the past 30 years already claim over 150,000 lives annually. Many prevalent human diseases are linked to climate fluctuations, from cardiovascular mortality and respiratory illnesses due to heatwaves, to altered transmission of infectious diseases and malnutrition from crop failures. Uncertainty remains in attributing the expansion or resurgence of diseases to climate change, owing to lack of long-term, high-quality data sets as well as the large influence of socio-economic factors and changes in immunity and drug resistance. Here we review the growing evidence that climate-health relationships pose increasing health risks under future projections of climate change and that the warming trend over recent decades has already contributed to increased morbidity and mortality in many regions of the world. Potentially vulnerable regions include the temperate latitudes, which are projected to warm disproportionately, the regions around the Pacific and Indian oceans that are currently subjected to large rainfall variability due to the El Niño/Southern Oscillation sub-Saharan Africa and sprawling cities where the urban heat island effect could intensify extreme climatic events.
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            Climate change and vector-borne diseases: a regional analysis.

            Current evidence suggests that inter-annual and inter-decadal climate variability have a direct influence on the epidemiology of vector-borne diseases. This evidence has been assessed at the continental level in order to determine the possible consequences of the expected future climate change. By 2100 it is estimated that average global temperatures will have risen by 1.0-3.5 degrees C, increasing the likelihood of many vector-borne diseases in new areas. The greatest effect of climate change on transmission is likely to be observed at the extremes of the range of temperatures at which transmission occurs. For many diseases these lie in the range 14-18 degrees C at the lower end and about 35-40 degrees C at the upper end. Malaria and dengue fever are among the most important vector-borne diseases in the tropics and subtropics; Lyme disease is the most common vector-borne disease in the USA and Europe. Encephalitis is also becoming a public health concern. Health risks due to climatic changes will differ between countries that have developed health infrastructures and those that do not. Human settlement patterns in the different regions will influence disease trends. While 70% of the population in South America is urbanized, the proportion in sub-Saharan Africa is less than 45%. Climatic anomalies associated with the El Niño-Southern Oscillation phenomenon and resulting in drought and floods are expected to increase in frequency and intensity. They have been linked to outbreaks of malaria in Africa, Asia and South America. Climate change has far-reaching consequences and touches on all life-support systems. It is therefore a factor that should be placed high among those that affect human health and survival.
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              Effects of Climate Change on Ticks and Tick-Borne Diseases in Europe

              Zoonotic tick-borne diseases are an increasing health burden in Europe and there is speculation that this is partly due to climate change affecting vector biology and disease transmission. Data on the vector tick Ixodes ricinus suggest that an extension of its northern and altitude range has been accompanied by an increased prevalence of tick-borne encephalitis. Climate change may also be partly responsible for the change in distribution of Dermacentor reticulatus. Increased winter activity of I. ricinus is probably due to warmer winters and a retrospective study suggests that hotter summers will change the dynamics and pattern of seasonal activity, resulting in the bulk of the tick population becoming active in the latter part of the year. Climate suitability models predict that eight important tick species are likely to establish more northern permanent populations in a climate-warming scenario. However, the complex ecology and epidemiology of such tick-borne diseases as Lyme borreliosis and tick-borne encephalitis make it difficult to implicate climate change as the main cause of their increasing prevalence. Climate change models are required that take account of the dynamic biological processes involved in vector abundance and pathogen transmission in order to predict future tick-borne disease scenarios.
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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
                4 March 2016
                2016
                : 11
                : 3
                : e0150180
                Affiliations
                [1 ]Kansas State Veterinary Diagnostic Laboratory, Department of Diagnostic Medicine and Pathobiology, Kansas State University, Manhattan, Kansas, United States of America
                [2 ]Department of Geography, Kansas State University, Manhattan, Kansas, United States of America
                [3 ]Bureau of Epidemiology and Public Health Informatics, Kansas Department of Health and Environment, Topeka, Kansas, United States of America
                [4 ]Center for Excellence in Vector Borne Diseases, Department of Diagnostic Medicine and Pathobiology, Kansas State University, Manhattan, Kansas, United States of America
                Cary Institute of Ecosystem Studies, UNITED STATES
                Author notes

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

                Conceived and designed the experiments: RKR DGG GAA RRG. Performed the experiments: RKR DGG. Analyzed the data: RKR. Contributed reagents/materials/analysis tools: DGG DN. Wrote the paper: RKR DGG GAA RRG.

                Article
                PONE-D-15-50642
                10.1371/journal.pone.0150180
                4778859
                26942604
                e6be670c-ad5e-492d-b4f2-7176b7dee3ad
                © 2016 Raghavan 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
                : 20 November 2015
                : 10 February 2016
                Page count
                Figures: 5, Tables: 6, Pages: 17
                Funding
                This study was supported in part by the PHS grant number AI070908 from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, USA. This article is a contribution (Contribution no. 16-222-J) from the Kansas Agricultural Experiment Station. Publication cost for this article was provided by the K-State Open Access Publishing (KOAPF) program. 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
                Infectious diseases
                Bacterial diseases
                Rocky Mountain spotted fever
                Earth Sciences
                Atmospheric Science
                Meteorology
                Humidity
                Physical Sciences
                Materials Science
                Material Properties
                Surface Properties
                Surface Temperature
                Medicine and Health Sciences
                Epidemiology
                Disease Vectors
                Ticks
                Biology and Life Sciences
                Organisms
                Animals
                Invertebrates
                Arthropoda
                Arachnida
                Ixodes
                Ticks
                People and places
                Geographical locations
                North America
                United States
                Missouri
                Research and Analysis Methods
                Research Design
                Survey Research
                Census
                People and places
                Geographical locations
                North America
                United States
                Medicine and Health Sciences
                Epidemiology
                Disease Vectors
                Custom metadata
                This study used retrospective epidemiological data collected on human subjects which were reported to the state health departments of Kansas, Missouri, Arkansas and Oklahoma. Explicit permission was not available from these departments and the Internal Review Board at Kansas State University's Office of Research Compliance to redistribute epidemiological data. Interested individuals may contact Kansas Department of Health and Environment (785 296-1415), Missouri Department of Health and Senior Services (573 368-2449), Arkansas Department of Health (501 280-4433), and Oklahoma State Department of Health (405 271-5600) directly with data requests. The lead author requested data for this study from these departments using the telephone numbers provided.

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                Uncategorized

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