 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
| . |  |
. |
 by Staff Writers Paris (ESA) Dec 18, 2020
Climate data taken from Earth orbiting satellites, combined with machine learning techniques, are helping to better predict outbreaks of cholera and potentially save lives. Cholera is a waterborne disease caused by the ingestion of water or food contaminated with the bacterium Vibrio cholerae, which can be found in many coastal regions around the world, especially in densely populated tropical areas. The responsible pathogen generally lives under warm temperatures, moderate salinity and turbidity, and can be harboured by plankton and detritus in the water. Global warming and an increase in extreme weather events are driving outbreaks of cholera - a disease that affects 1.3 to 4 million people each year worldwide and causes up to 143 000 fatalities. A new study shows how cholera outbreaks in coastal regions of India can be predicted with an 89% success rate, in the first demonstration of using sea surface salinity for forecasting cholera. The research published yesterday in the International Journal of Environmental Research and Public Health focuses on predicting outbreaks of cholera around the northern Indian Ocean, where more than half of global cases of the disease were reported in the 2010-16 period. The relationship between the environmental drivers of cholera incidence are complex, and vary seasonally, with different lagged effects, for example from the monsoon season. Machine learning algorithms can help to overcome these issues by learning to recognise patterns across large datasets in order to make testable predictions. The study was led by Amy Campbell during a year-long graduate traineeship with the ESA Climate Office. Amy, along with her co-authors at the Plymouth Marine Laboratory (PML), used a machine learning algorithm popular in environmental science applications - the random forest classifier - which can recognise patterns across long datasets and make testable predictions. The algorithm was trained on disease outbreaks reported in coastal districts in India between 2010 and 2018, and learned the relationships with six satellite-based climate records generated by ESA's Climate Change Initiative (CCI). By including or removing environmental variables and sub-setting for different seasons, the algorithm identified key variables for predicting cholera outbreaks as land surface temperature, sea surface salinity, chlorophyll-a concentration and sea level difference from average (sea level anomaly). Amy Campbell said, "The model showed promising results, and there's a lot of scope for developing this work using different cholera surveillance datasets or in different locations. In our study, we tested different machine learning techniques and found the random forest classifier to be the best, but there are far more techniques that could be investigated. "It would be interesting to test the impact of including socio-economic datasets; remote sensing data could be used to develop records to account for human factors that are important for cholera incidence, such as access to water resources." The study and its new insights have contributed to the UKRI-NERC Pathways Of Dispersal for Cholera And Solution Tools (PODCAST) Project led by co-author Marie-Fanny Racault at PML, which is assessing the impact of climate warming and climate extremes on habitats suitable for Vibrio cholerae. The results from the study will be demonstrated at the UNFCCC's COP26 meeting in 2021 via a web-based forecasting tool as part of the PODCAST-DEMO project. This is supported by the ESA-Future Earth joint programme and carried out in collaboration with Future Earth's Health Knowledge-Action network.
UP42 to Offer Smart Satellite Data from Australia's LatConnect 60 on the UP42 Geospatial Marketplace Berlin, Germany (SPX) Dec 16, 2020 UP42 has announced that image data and information from the planned LatConnect 60 constellation of mid-inclined orbit remote sensing satellites will be available on the UP42 developer platform for Earth observation data and analytics. In early 2022, LatConnect 60 will launch its first two "smart" small satellites equipped with onboard Artificial Intelligence (AI) for data pre-processing and advanced tip-and-cue functionality. This on-board AI has the possibility to significantly reduce costs for r ... read more
|
|||||||||||||
|
|
| The content herein, unless otherwise known to be public domain, are Copyright 1995-2024 - Space Media Network. All websites are published in Australia and are solely subject to Australian law and governed by Fair Use principals for news reporting and research purposes. AFP, UPI and IANS news wire stories are copyright Agence France-Presse, United Press International and Indo-Asia News Service. ESA news reports are copyright European Space Agency. All NASA sourced material is public domain. Additional copyrights may apply in whole or part to other bona fide parties. All articles labeled "by Staff Writers" include reports supplied to Space Media Network by industry news wires, PR agencies, corporate press officers and the like. Such articles are individually curated and edited by Space Media Network staff on the basis of the report's information value to our industry and professional readership. Advertising does not imply endorsement, agreement or approval of any opinions, statements or information provided by Space Media Network on any Web page published or hosted by Space Media Network. General Data Protection Regulation (GDPR) Statement Our advertisers use various cookies and the like to deliver the best ad banner available at one time. All network advertising suppliers have GDPR policies (Legitimate Interest) that conform with EU regulations for data collection. By using our websites you consent to cookie based advertising. If you do not agree with this then you must stop using the websites from May 25, 2018. Privacy Statement. Additional information can be found here at About Us. |
del.icio.us
Digg
Reddit
Google
