In-situ and Remote Sensing Networks for Environmental Monitoring and Global Assessment of Leptospirosis Outbreaks

AbstractLeptospirosis is a disease that affects human population and can claim many victims with large outbreaks associated with natural disasters. This work focuses on the technological aspects for inexpensive climate monitoring techniques based on ground and satellite sensors for obtaining information prior to disease outbreaks in under-developed regions and on water-quality sensors that can lead to radical changes in our ability to detect and abate this disease. The remote deployment of such sensors in areas where outbreaks can occur can help in enhancingin real-time the spatial and temporal resolution of information and allows unattended operation that will be particularly useful for monitoring under extreme climate events. Such types of monitoring advancements, when coupled with regular geographical, population and habitat monitoring can assess the hazards and risks to local population prior to a disease outbreak. Then in the eventual aftermath, it can assist in identification of affected geographical locations where abatement solutions will be required, and eventually in the assessment of the effectiveness of control measures. This work explores recent releases of open global observation data and a range of in-situ environmental monitoring tools of increasing complexity for measuring several parameters andfor detecting contaminants and pathogens that were previously irresolvable due to the high degree of complexityinthe diagnosis of this disease

Urban case studies : general discussion

Urban case studies: general discussio

Rapid tests for diagnosis of leptospirosis: Current tools and emerging technologies

Leptospirosis is an emerging zoonosis with a worldwide distribution but is more commonly found in impoverished populations in developing countries and tropical regions with frequent flooding. The rapid detection of leptospirosis is a critical step to effectively manage the disease and to control outbreaks in both human and animal populations. Therefore, there is a need for accurate and rapid diagnostic tests and appropriate surveillance and alert systems to identify outbreaks. This review describes current in-house methods and commercialized tests for the rapid diagnosis of acute leptospirosis. It focuses on diagnostic tests that can be performed with minimal training and limited equipment in less-developed and newly industrialized countries, particularly in resource-limited settings and with results in minutes to less than 4 hours. We also describe recent technological advances in the field of diagnostic tests that could allow for the development of innovative rapid tests in the near futur

End-user perspective of low-cost sensors for outdoor air pollution monitoring

Low-cost sensor technology can potentially revolutionise the area of air pollution monitoring by providing high-density spatiotemporal pollution data. Such data can be utilised for supplementing traditional pollution monitoring, improving exposure estimates, and raising community awareness about air pollution. However, data quality remains a major concern that hinders the widespread adoption of low-cost sensor technology. Unreliable data may mislead unsuspecting users and potentially lead to alarming consequences such as reporting acceptable air pollutant levels when they are above the limits deemed safe for human health. This article provides scientific guidance to the end-users for effectively deploying low-cost sensors for monitoring air pollution and people's exposure, while ensuring reasonable data quality. We review the performance characteristics of several low-cost particle and gas monitoring sensors and provide recommendations to end-users for making proper sensor selection by summarizing the capabilities and limitations of such sensors. The challenges, best practices, and future outlook for effectively deploying low-cost sensors, and maintaining data quality are also discussed. For data quality assurance, a two-stage sensor calibration process is recommended, which includes laboratory calibration under controlled conditions by the manufacturer supplemented with routine calibration checks performed by the end-user under final deployment conditions. For large sensor networks where routine calibration checks are impractical, statistical techniques for data quality assurance should be utilised. Further advancements and adoption of sophisticated mathematical and statistical techniques for sensor calibration, fault detection, and data quality assurance can indeed help to realise the promised benefits of a low-cost air pollution sensor network. (C) 2017 Elsevier B.V. All rights reserved.This work is led by the University of Surrey's GCARE team under the iSCAPE (Improving Smart Control of Air Pollution in Europe) project, which is funded through the European Community's H2020 Programme under the Grant Agreement No. 689954.pollution exposure; human health; outdoor pollution sensing; environmental sensing; real-time exposur

Integrated Systems for Forecasting Urban Meteorology, Air Pollution and Population Exposure

Urban air pollution is associated with significant adverse health effects. Model-based abatement strategies are required and developed for the growing urban populations. In the initial development stage, these are focused on exceedances of air quality standards caused by high short-term pollutant concentrations. Prediction of health effects and implementation of urban air quality information and abatement systems require accurate forecasting of air pollution episodes and population exposure, including modeling of emissions, meteorology, atmospheric dispersion and chemical reaction of pollutants, population mobility, and indoor-outdoor relationship of the pollutants. In the past, these different areas have been treated separately by different models and even institutions. Progress in computer resources and ensuing improvements in numerical weather prediction, air chemistry, and exposure modelling recently allow a unification and integration of the disjunctive models and approaches. The current work presents a novel approach that integrates the latest developments in meteorological, air quality, and population exposure modelling into Urban Air Quality Information and Forecasting Systems in the context of the European Union FUMAPEX project. The suggested integrated strategy is demonstrated for examples of the systems in three Nordic cities: Helsinki and Oslo for assessment and forecasting of urban air pollution and Copenhagen for urban emergency preparedness.JRC.H-Institute for environment and sustainability (Ispra