Early Warning System for West Nile Virus outbreaks based on Satellite Earth Observation Data

2020 ◽  
Author(s):  
Elisavet Parselia ◽  
Charalambos Kontoes ◽  
Ioannis Kioutsioukis ◽  
Spiros Mourelatos ◽  
Christos Hadjichristodoulou ◽  
...  
Keyword(s):  
West Nile Virus ◽  
Satellite Data ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Well Being ◽  
Earth Observation ◽  
Machine Learning Algorithms ◽  
Observation Data ◽  
West Nile

<p>The aim of this study is the development of an operational Early Warning System (EWS) that will utilize new and enhanced satellite Earth Observation (EO) sensors with the purpose of forecasting and risk mapping the West Nile Virus (WNV) outbreaks. Satellite EO data were leveraged to estimate environmental variables that influence the transmission cycle of the pathogen that leads to WNV, a mosquito-borne disease (MBD). The system was trained with epidemiological and entomological data from the region of Central Macedonia, the most epidemic-prone region in Greece regarding the WNV. The satellite derived environmental parameters of the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI), the Land Surface Temperature (LST), precipitation data as well as proximity to water bodies were coupled with meteorological data and were used as explanatory variables for the models. The management and analysis of the big satellite data was conducted with the Open Data Cube (ODC), providing an open and freely accessible exploitation architecture. Statistical and machine learning algorithms were used for short-term forecast, while dynamical models were utilized for the seasonal forecast.The system explores the analysis of big satellite data and proves its scalability by replicating the same models in different geographic regions; e.g the northeastern Italian region of Veneto. This EWS will be used as a tool for helping local decision-makers to improve health system responses, take preventive measures in order to curtail the spread of WNV in Europe and address the relevant priorities of the Sustainable Development Goals (SDGs) such as good health and well-being (SDG 3) and climate action (SDG 13).</p>

scholarly journals Dead Bird Surveillance as an Early Warning System for West Nile Virus

2001 ◽  
Vol 7 (4) ◽  
pp. 631-635 ◽  
Author(s):  
Millicent Eidson ◽  
Laura Kramer ◽  
Ward Stone ◽  
Yoichiro Hagiwara ◽  
Kate Schmit ◽  
...  
Keyword(s):  
West Nile Virus ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
West Nile ◽  
Dead Bird

scholarly journals Satellite Earth Observation Data in Epidemiological Modeling of Malaria, Dengue and West Nile Virus: A Scoping Review

2019 ◽  
Vol 11 (16) ◽  
pp. 1862 ◽  
Author(s):  
Elisavet Parselia ◽  
Charalampos Kontoes ◽  
Alexia Tsouni ◽  
Christos Hadjichristodoulou ◽  
Ioannis Kioutsioukis ◽  
...  
Keyword(s):  
West Nile Virus ◽  
Scoping Review ◽  
Earth Observation ◽  
Machine Learning Algorithms ◽  
Observation Data ◽  
Epidemiological Models ◽  
West Nile ◽  
Epidemiological Modeling ◽  
Transmission Cycle ◽  
Earth Observation Data

Earth Observation (EO) data can be leveraged to estimate environmental variables that influence the transmission cycle of the pathogens that lead to mosquito-borne diseases (MBDs). The aim of this scoping review is to examine the state-of-the-art and identify knowledge gaps on the latest methods that used satellite EO data in their epidemiological models focusing on malaria, dengue and West Nile Virus (WNV). In total, 43 scientific papers met the inclusion criteria and were considered in this review. Researchers have examined a wide variety of methodologies ranging from statistical to machine learning algorithms. A number of studies used models and EO data that seemed promising and claimed to be easily replicated in different geographic contexts, enabling the realization of systems on regional and national scales. The need has emerged to leverage furthermore new powerful modeling approaches, like artificial intelligence and ensemble modeling and explore new and enhanced EO sensors towards the analysis of big satellite data, in order to develop accurate epidemiological models and contribute to the reduction of the burden of MBDs.

Building a climate service to support an Εarly Warning System for the West Nile Virus disease in Greece

2020 ◽  
Author(s):  
Eleni Katragkou ◽  
Maria Chara Karypidou ◽  
Stergios Kartsios ◽  
Sandra Gewehr ◽  
Spiros Mourelatos
Keyword(s):  
West Nile Virus ◽  
Early Warning ◽  
Early Warning System ◽  
Mosquito Control ◽  
Virus Disease ◽  
Empirical Relationship ◽  
Warning System ◽  
West Nile ◽  
Study Region ◽  
Climate Service

<p>According to the National Public Health Organization in Greece, cases of West Nile Virus (WNV) infection in humans and animals have been recorded in various areas over Greece during the years 2010-2014 and 2017-2019 (https://eody.gov.gr). In this work we present a climate service which supports an Early Warning System (EWS) for the mosquito-borne WNV disease, operated for the first time over the Region of Central Macedonia in Greece. The EWS is based on a platform fed by time-dependent data (climate information and mosquito population data (Culex sp.)) and time invariant data (topography, density of mosquito breeding sites taken from field campaigns and distance to water-related land cover categories). The climate data are produced on a daily basis by the WRF-AUTH-MC weather forecast model over a 2x2 Km grid covering the Region of Central Macedonia, which operates from April to October (mosquito circulation period). Mosquito samples are collected every 2 weeks by the company ECODEVELOPMENT, using CO<sub>2</sub> mosquito traps. The mosquito data along with the climatic and static environmental information are utilized within a Generalized Linear Model (GLM). Based on an empirical relationship derived from the GLM, the overall environmental suitability for the Culex mosquito is assessed over the study region. The work is performed in the framework of the German-Greek bilateral project “Establishment of an Early Warning System for mosquito borne diseases” (http://www.wnvalert.eu/), which is focusing on improved measures on proactive mosquito control and disease prevention activities.</p>

scholarly journals Evaluation of a West Nile virus surveillance and early warning system in Greece, based on domestic pigeons

2014 ◽  
Vol 37 (2) ◽  
pp. 131-141 ◽  
Author(s):  
Serafeim C. Chaintoutis ◽  
Chrysostomos I. Dovas ◽  
Maria Papanastassopoulou ◽  
Sandra Gewehr ◽  
Kostas Danis ◽  
...  
Keyword(s):  
West Nile Virus ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
West Nile ◽  
Virus Surveillance ◽  
Domestic Pigeons

scholarly journals Towards an Early Warning System for Forecasting Human West Nile Virus Incidence

PLoS Currents ◽  
2014 ◽  
Author(s):  
Carrie A Manore ◽  
Justin Davis ◽  
Rebecca C. Christofferson ◽  
Dawn Wesson ◽  
James M Hyman ◽  
...  
Keyword(s):  
West Nile Virus ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
West Nile ◽  
Human West Nile Virus ◽  
Virus Incidence

scholarly journals Dead Bird Clusters as an Early Warning System for West Nile Virus Activity

2003 ◽  
Vol 9 (6) ◽  
pp. 641-646 ◽  
Author(s):  
Farzad Mostashari ◽  
Martin Kulldorff ◽  
Jessica J. Hartman ◽  
James R. Miller ◽  
Varuni Kulasekera
Keyword(s):  
West Nile Virus ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
West Nile ◽  
Dead Bird ◽  
Virus Activity

scholarly journals Towards an Early Warning System for Forecasting Human West Nile Virus Incidence

PLoS Currents ◽  
2014 ◽  
Author(s):  
Carrie A. Manore ◽  
Justin K. Davis ◽  
Rebecca C. Christofferson ◽  
Dawn M. Wesson ◽  
James M. Hyman ◽  
...  
Keyword(s):  
West Nile Virus ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
West Nile ◽  
Human West Nile Virus ◽  
Virus Incidence

scholarly journals SARS-CoV-2: fate in water environments and sewage surveillance as an early warning system

2021 ◽  
Author(s):  
Deepak Panchal ◽  
Purusottam Tripathy ◽  
Om Prakash ◽  
Abhishek Sharma ◽  
Sukdeb Pal
Keyword(s):  
Wastewater Treatment ◽  
Early Warning ◽  
Disease Surveillance ◽  
Early Warning System ◽  
Warning System ◽  
Quality Criteria ◽  
Well Being ◽  
Coliform Bacteria ◽  
Surveillance Systems ◽  
Water Quality Criteria

Abstract Coronavirus disease has emerged as one of the greatest threats to human well-being. Currently, the whole world is fighting against this pandemic that transmit either through exposure to virus laden respiratory or water droplets or by touching the virus contaminated surfaces. The viral load in feces of an infected patient varies according to the severity of the disease. Subsequent detection of viral genome (SARS-COV-2) in human feces and sewage systems is an emerging concern for public health. This also dictates to reinforce the existing sewage/wastewater treatment facilities. Rapid monitoring is the key to prevent and control the current mass transmission. Wastewater-Based Epidemiology (WBE) is a potential epidemiology tool that can act as a complementary approach for current infectious disease surveillance systems and an early warning system for disease outbreaks. In a developing country like India, inadequate wastewater treatment systems, low-operational facility and relaxed surface water quality criteria even in terms of fecal coliform bacteria are the major challenges for WBE. Herein, we review the occurrence, transmission, survival of SARS-CoV-2, disinfection and potential of sewage surveillance as an early warning system for COVID-19 spread. We also discuss the challenges of open-defecation practices affecting sewage-surveillance in real-time in densely populated developing countries like India.

scholarly journals The use of rapid assessment for flood hazard map development in upper citarum river basin

2018 ◽  
Vol 229 ◽  
pp. 04011
Author(s):  
Idham Riyando Moe ◽  
Akbar Rizaldi ◽  
Mohammad Farid ◽  
Arie Setiadi Moerwanto ◽  
Arno Adi Kuntoro
Keyword(s):  
River Basin ◽  
Early Warning ◽  
Early Warning System ◽  
Flood Hazard ◽  
Rapid Assessment ◽  
Warning System ◽  
Observation Data ◽  
Hazard Map ◽  
Material Loss ◽  
Flood Hazard Map

Flood is a natural disaster that can occur at any time and anywhere. The flood disaster causes material and non-material loss, then in order to increase the resilience to disaster, an early warning system is needed. The data is indispensable as a reference to make an early warning system. Unfortunately, flood assessment in purpose to record the data is often conducted much later after the event occurs. Therefore, this research was conducted to do modelling of flood hazard map is quantitatively and validated with observation data as a form of rapid flood assessment. The location of this study is in the Upper Citarum River Basin, around Bandung basin. The model is well done if the result shows the location of the flood as illustrated as the observational data. The result shows fair agreement with observed data where some points of inundated areas are captured and the location of inundated areas from modelling result looks similar to the inundated area from observation data.

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