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      Projected local rain events due to climate change and the impacts on waterborne diseases in Vancouver, British Columbia, Canada

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          Abstract

          Background

          Climate change is increasing the number and intensity of extreme weather events in many parts of the world. Precipitation extremes have been linked to both outbreaks and sporadic cases of waterborne illness. We have previously shown a link between heavy rain and turbidity to population-level risk of sporadic cryptosporidiosis and giardiasis in a major Canadian urban population. The risk increased with 30 or more dry days in the 60 days preceding the week of extreme rain. The goal of this study was to investigate the change in cryptosporidiosis and giardiasis risk due to climate change, primarily change in extreme precipitation.

          Methods

          Cases of cryptosporidiosis and giardiasis were extracted from a reportable disease system (1997–2009). We used distributed lag non-linear Poisson regression models and projections of the exposure-outcome relationship to estimate future illness (2020–2099). The climate projections are derived from twelve statistically downscaled regional climate models. Relative Concentration Pathway 8.5 was used to project precipitation derived from daily gridded weather observation data (~ 6 × 10 km resolution) covering the central of three adjacent watersheds serving metropolitan Vancouver for the 2020s, 2040s, 2060s and 2080s.

          Results

          Precipitation is predicted to steadily increase in these watersheds during the wet season (Oct. -Mar.) and decrease in other parts of the year up through the 2080s. More weeks with extreme rain (>90th percentile) are expected. These weeks are predicted to increase the annual rates of cryptosporidiosis and giardiasis by approximately 16% by the 2080s corresponding to an increase of 55–136 additional cases per year depending upon the climate model used. The predicted increase in the number of waterborne illness cases are during the wet months. The range in future projections compared to historical monthly case counts typically differed by 10–20% across climate models but the direction of change was consistent for all models.

          Discussion

          If new water filtration measures had not been implemented in our study area in 2010–2015, the risk of cryptosporidiosis and giardiasis would have been expected to increase with climate change, particularly precipitation changes. In addition to the predicted increase in the frequency and intensity of extreme precipitation events, the frequency and length of wet and dry spells could also affect the risk of waterborne diseases as we observed in the historical period. These findings add to the growing evidence regarding the need to prepare water systems to manage and become resilient to climate change-related health risks.

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          Most cited references29

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          An Overview of CMIP5 and the Experiment Design

          The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.
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            RCP 8.5—A scenario of comparatively high greenhouse gas emissions

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              The Association Between Extreme Precipitation and Waterborne Disease Outbreaks in the United States, 1948–1994

              Rainfall and runoff have been implicated in site-specific waterborne disease outbreaks. Because upward trends in heavy precipitation in the United States are projected to increase with climate change, this study sought to quantify the relationship between precipitation and disease outbreaks. The US Environmental Protection Agency waterborne disease database, totaling 548 reported outbreaks from 1948 through 1994, and precipitation data of the National Climatic Data Center were used to analyze the relationship between precipitation and waterborne diseases. Analyses were at the watershed level, stratified by groundwater and surface water contamination and controlled for effects due to season and hydrologic region. A Monte Carlo version of the Fisher exact test was used to test for statistical significance. Fifty-one percent of waterborne disease outbreaks were preceded by precipitation events above the 90th percentile (P = .002), and 68% by events above the 80th percentile (P = .001). Outbreaks due to surface water contamination showed the strongest association with extreme precipitation during the month of the outbreak; a 2-month lag applied to groundwater contamination events. The statistically significant association found between rainfall and disease in the United States is important for water managers, public health officials, and risk assessors of future climate change.
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                Author and article information

                Contributors
                ttakaro@sfu.ca
                Journal
                Environ Health
                Environ Health
                Environmental Health
                BioMed Central (London )
                1476-069X
                30 December 2019
                30 December 2019
                2019
                : 18
                : 116
                Affiliations
                [1 ]ISNI 0000 0004 1936 7494, GRID grid.61971.38, Faculty of Health Sciences, , Simon Fraser University, ; 8888 University Dr. BLU 11300, Burnaby, British Columbia Canada
                [2 ]ISNI 0000 0001 0352 641X, GRID grid.418246.d, British Columbia Centre for Disease Control, ; Vancouver, British Columbia Canada
                [3 ]ISNI 0000 0001 2288 9830, GRID grid.17091.3e, School of Population and Public Health, , University of British Columbia, ; Vancouver, British Columbia Canada
                [4 ]ISNI 0000 0004 1936 9465, GRID grid.143640.4, Pacific Climate Impacts Consortium, , University of Victoria, ; Victoria, British Columbia Canada
                [5 ]ISNI 0000 0004 1936 9609, GRID grid.21613.37, George and Fay Yee Centre for Healthcare Innovation, , University of Manitoba, ; Winnipeg, Manitoba Canada
                [6 ]ISNI 0000 0004 0384 4428, GRID grid.417243.7, Vancouver Coastal Health, ; Vancouver, British Columbia Canada
                [7 ]ISNI 0000 0004 1936 7494, GRID grid.61971.38, Department of Geography, , Simon Fraser University, ; Burnaby, British Columbia Canada
                Author information
                http://orcid.org/0000-0002-5282-1519
                Article
                550
                10.1186/s12940-019-0550-y
                6937929
                31888648
                4519e805-ac5f-4d4f-9bdb-617712c6fe0b
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 6 August 2019
                : 6 December 2019
                Funding
                Funded by: Public Health Agency of Canada
                Award ID: NA
                Categories
                Research
                Custom metadata
                © The Author(s) 2019

                Public health
                waterborne disease,climate change,extreme precipitation,downscaled climate projections,future health impact

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