Scientists offer more accurate health risk prediction model to better inform beach closure decisions
An international team, led by researchers at the University of Miami (UM) Rosenstiel School of Marine and Atmospheric Science, has developed a new, timelier method to identify harmful bacteria levels on recreational beaches. The new model provides beach managers with a better prediction tool to identify when closures are required to protect beachgoers from harmful contaminates in the water.
"The development of this new model has allowed us, for the first time, to estimate contamination levels on beaches subject to nonpoint source pollution, in particular from beach sand and runoff from storms," said the study's authors.
The new method provides beach health managers with an easily accessible computer model to predict harmful bacteria levels from all potential pollution sources. The team optimized and validated their model using a 10-day monitoring dataset from the popular Virginia Beach in Miami, Florida. The predictive model uses information on waves, tides, rainfall and solar radiation to more accurately predict harmful bacteria concentration and movement along the shore allowing for improved beach management decision-making.
Federal and state laws require water monitoring of fecal indicator bacteria, such as enterococci and fecal coliform, at recreational beaches to protect beachgoers from harmful water contamination levels. Excess levels of these harmful bacteria prompt beach advisories and closures to minimize human health risks. Water contamination from fecal indicator bacteria can result from "point-source" pollution, such as a sewage outfall, or "nonpoint source" pollution from storm-water runoff, or animal and human inputs.
Current methods assess fecal bacteria contamination levels by direct sampling of water from beaches, as well as by using complex computer modeling. Direct sampling methods requires a one-day laboratory analysis to access the health risk to humans at a particular beach. Therefore, a 24 to 48 hours wait period after sampling is required before any beach closure or advisory is issued. In addition, the current computer-based model requires high computing power, which is often inaccessible to beach closure decision managers, and can only predict contaminates from known sources of pollution, such as sewage outfalls.
The National Science Foundation-funded study, titled "A predictive model for microbial counts on beaches where intertidal sand is a primary source," was published in the May 15 issue of the journal Marine Pollution Bulletin. The co-authors include: UM Rosenstiel School alumnus Zhixuan Feng of Woods Hole Oceanographic Institution; Ad Renier, Brian K. Haus, and John D. Wang of the UM Rosenstiel School of Marine and Atmospheric Science; Helena M. Solo-Gabriele of the UM School of Engineering; Lora E. Fleming of the university of Exeter Medical School. NSF Awards: OCE-0432368, OCE-0911373, OCE-1127813
About the University of Miami's Rosenstiel School
The University of Miami is one of the largest private research institutions in the southeastern United States. The University's mission is to provide quality education, attract and retain outstanding students, support the faculty and their research, and build an endowment for University initiatives. Founded in the 1940's, the Rosenstiel School of Marine & Atmospheric Science has grown into one of the world's premier marine and atmospheric research institutions. Offering dynamic interdisciplinary academics, the Rosenstiel School is dedicated to helping communities to better understand the planet, participating in the establishment of environmental policies, and aiding in the improvement of society and quality of life. For more information, visit: http://www.
Diana Udel | EurekAlert!
Mass spectrometry sheds new light on thallium poisoning cold case
14.12.2018 | University of Maryland
Protein involved in nematode stress response identified
14.12.2018 | University of Illinois College of Agricultural, Consumer and Environmental Sciences
The more objects we make "smart," from watches to entire buildings, the greater the need for these devices to store and retrieve massive amounts of data quickly without consuming too much power.
Millions of new memory cells could be part of a computer chip and provide that speed and energy savings, thanks to the discovery of a previously unobserved...
What if, instead of turning up the thermostat, you could warm up with high-tech, flexible patches sewn into your clothes - while significantly reducing your...
A widely used diabetes medication combined with an antihypertensive drug specifically inhibits tumor growth – this was discovered by researchers from the University of Basel’s Biozentrum two years ago. In a follow-up study, recently published in “Cell Reports”, the scientists report that this drug cocktail induces cancer cell death by switching off their energy supply.
The widely used anti-diabetes drug metformin not only reduces blood sugar but also has an anti-cancer effect. However, the metformin dose commonly used in the...
A research team from the University of Zurich has developed a new drone that can retract its propeller arms in flight and make itself small to fit through narrow gaps and holes. This is particularly useful when searching for victims of natural disasters.
Inspecting a damaged building after an earthquake or during a fire is exactly the kind of job that human rescuers would like drones to do for them. A flying...
Over the last decade, there has been much excitement about the discovery, recognised by the Nobel Prize in Physics only two years ago, that there are two types...
12.12.2018 | Event News
10.12.2018 | Event News
06.12.2018 | Event News
14.12.2018 | Power and Electrical Engineering
14.12.2018 | Physics and Astronomy
14.12.2018 | Physics and Astronomy