Early Warning System for West Nile Virus Risk Areas, California, USA

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 CO2 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 &#8220;Establishment of an Early Warning System for mosquito borne diseases&#8221; (http://www.wnvalert.eu/), which is focusing on improved measures on proactive mosquito control and disease prevention activities.

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

Comparative Immunology Microbiology and Infectious Diseases ◽

10.1016/j.cimid.2014.01.004 ◽

2014 ◽

Vol 37 (2) ◽

pp. 131-141 ◽

Cited By ~ 46

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

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

PLoS Currents ◽

10.1371/currents.outbreaks.ed6f0f8a61d20ae5f32aaa5c2b8d3c23 ◽

2014 ◽

Cited By ~ 3

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

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

Emerging Infectious Diseases ◽

10.3201/eid0906.020794 ◽

2003 ◽

Vol 9 (6) ◽

pp. 641-646 ◽

Cited By ~ 159

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

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

10.5194/egusphere-egu2020-20612 ◽

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

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).

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

PLoS Currents ◽

10.1371/currents.outbreaks.f0b3978230599a56830ce30cb9ce0500 ◽

2014 ◽

Cited By ~ 9

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

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Identification of suitable areas for West Nile virus outbreaks in equid populations for application in surveillance plans: the example of the Castile and Leon region of Spain

Epidemiology and Infection ◽

10.1017/s0950268811002366 ◽

2011 ◽

Vol 140 (9) ◽

pp. 1617-1631 ◽

Cited By ~ 10

Author(s):

V. RODRÍGUEZ-PRIETO ◽

B. MARTÍNEZ-LÓPEZ ◽

M. MARTÍNEZ ◽

M. J. MUÑOZ ◽

J. M. SÁNCHEZ-VIZCAÍNO

Keyword(s):

West Nile Virus ◽

Early Detection ◽

Early Warning System ◽

Warning System ◽

American Continent ◽

West Nile ◽

Rapid Spread ◽

Time Periods ◽

Severity Of The Disease ◽

And Control

SUMMARYThe introduction and rapid spread of West Nile virus (WNV) into new areas such as the American continent, associated also with the severity of the disease in humans and equids has increased concerns regarding the need to better prevent and control future WNV incursions. WNV outbreaks in equids usually occur under specific climatic and environmental conditions and, typically, before detection of WNV cases in humans. Targeting surveillance strategies in areas and time periods identified as suitable for WNV outbreaks in equids may act as an early-warning system to prevent disease in both equids and humans. This study used a GIS-based framework to identify suitable areas and time periods for WNV outbreak occurrence in one of the most important areas of equid production in Spain, i.e. Castile and Leon. Methods and results presented here may help to improve the early detection and control of future WNV outbreaks in Spain and other regions.

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Towards an automatic early warning system of flood hazards based on precipitation forecast: the case of the Miño River (NW Spain)

Natural Hazards and Earth System Science ◽

10.5194/nhess-19-2583-2019 ◽

2019 ◽

Vol 19 (11) ◽

pp. 2583-2595 ◽

Cited By ~ 5

Author(s):

José González-Cao ◽

Orlando García-Feal ◽

Diego Fernández-Nóvoa ◽

José Manuel Domínguez-Alonso ◽

Moncho Gómez-Gesteira

Keyword(s):

Early Warning ◽

Early Warning System ◽

Warning System ◽

Precipitation Forecast ◽

Flood Hazards ◽

Nw Spain ◽

Forecast Horizon ◽

Flood Prediction ◽

Rainfall Forecast ◽

Risk Areas

Abstract. An early warning system for flood prediction based on precipitation forecast is presented. The system uses rainfall forecast provided by MeteoGalicia in combination with a hydrologic (Hydrologic Modeling System, HEC-HMS) and a hydraulic (Iber+) model. The upper reach of the Miño River and the city of Lugo (NW Spain) are used as a study area. Starting from rainfall forecast, HEC-HMS calculates the streamflow and Iber+ is automatically executed for some previously defined risk areas when a certain threshold is exceeded. The analysis based on historical extreme events shows that the system can provide accurate results in less than 1 h for a forecast horizon of 3 d and report an alert situation to decision makers.

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Towards an Automatic Early Warning System of Flood Hazards based on Precipitation Forecast: The case of the Miño River (NW Spain)

10.5194/nhess-2019-200 ◽

2019 ◽

Author(s):

José González-Cao ◽

Orlando García-Feal ◽

Diego Fernández-Nóvoa ◽

José Manuel Domínguez-Alonso ◽

Moncho Gómez-Gesteira

Keyword(s):

Early Warning ◽

Early Warning System ◽

Warning System ◽

Precipitation Forecast ◽

Flood Hazards ◽

Nw Spain ◽

Forecast Horizon ◽

Flood Prediction ◽

Rainfall Forecast ◽

Risk Areas

Abstract. An Early Warning System for flood prediction based on precipitation forecast is presented. The system uses rainfall forecast provided MeteoGalicia in combination with a hydrologic (HEC-HMS) and a hydraulic (Iber+) models. The upper reach of the Miño River and the city of Lugo (NW Spain) are used as a study area. Starting from rainfall forecast, HEC-HMS calculates the streamflow and Iber+ is automatically executed when a certain threshold is exceeded for some previously defined risk areas. The analysis based on historical extreme events shows that the system can provide accurate results in less than one hour for a forecast horizon of 3 days and report an alert situation to decision-makers.

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