AIMSurv: First pan-European harmonized surveillance of Aedes invasive mosquito species of relevance for human vector-borne diseases

Human and animal vector-borne diseases, particularly mosquito-borne diseases, are emerging or re-emerging worldwide. Six Aedes invasive mosquito (AIM) species were introduced to Europe since the 1970s: Aedes aegypti, Ae. albopictus, Ae. japonicus, Ae. koreicus, Ae. atropalpus and Ae. triseriatus. Here, we report the results of AIMSurv2020, the first pan-European surveillance effort for AIMs. Implemented by 42 volunteer teams from 24 countries. And presented in the form of a dataset named “AIMSurv Aedes Invasive Mosquito species harmonized surveillance in Europe. AIM-COST Action. Project ID: CA17108”. AIMSurv2020 harmonizes field surveillance methodologies for sampling different AIMs life stages, frequency and minimum length of sampling period, and data reporting. Data include minimum requirements for sample types and recommended requirements for those teams with more resources. Data are published as a Darwin Core archive in the Global Biodiversity Information Facility- Spain, comprising a core file with 19,130 records (EventID) and an occurrences file with 19,743 records (OccurrenceID). AIM species recorded in AIMSurv2020 were Ae. albopictus, Ae. japonicus and Ae. koreicus, as well as native mosquito species

Epidemiological study on the incidence of haemorrhagic fever with renal syndrome in five Western Balkan countries for a 10-year period: 2006–2015

Background: Large-scale epidemics of haemorrhagic fever with renal syndrome (HFRS) have been reported mostly in Asia and Europe, with around 100,000 people affected each year. In the Southeast Europe, Balkan region, HFRS is endemic disease with approximately 100 cases per year. Our aim was to describe epidemiological characteristics of HFRS in five Western Balkan (WB) countries and to describe correlation between HFRS incidence and major meteorological event that hit the area in May 2014. Methods: National surveillance data of HFRS from Bosnia and Herzegovina, Croatia, Montenegro, North Macedonia and Serbia obtained from 1 January 2006 to 31 December 2015 were collected and analysed. Results: In a 10-year period, a total of 1,065 HFRS patients were reported in five WB countries. Cumulative incidence rate ranged from 0.05 to 15.80 per 100.000 inhabitants (in North Macedonia and Montenegro respectively). Increasing number of HFRS cases was reported with a peak incidence in three specific years (2008, 2012, and 2014). Average incidence for the entire area was higher in males than females (5.63 and 1.90 per 100.000 inhabitants respectively). Summer was the season with the highest number of cases and an average incidence rate of 1.74/100.000 inhabitants across 10-year period. Haemorrhagic fever with renal syndrome incidence was significantly increased (7.91/100.000 inhabitants) in 2014, when a few months earlier, severe floods affected several WB countries. A strong significant negative correlation (r = −.84, p < .01) between the monthly incidence of HFRS and the number of months after May's floods was demonstrated for the total area of WB. Conclusion: Our findings demonstrate that the HFRS incidence had similar distribution (general, age, sex and seasonality) across majority of the included countries. Summer was the season with the highest recorded incidence. Common epidemic years were detected in all observed countries as well as a negative correlation between the monthly incidence of HFRS and the number of months after May's cyclone

Assessment of expertise in morphological identification of mosquito species (Diptera, Culicidae) using photomicrographs

International audienceAccurate identification of insect species is an indispensable and challenging requirement for every entomologist, particularly if the species is involved in disease outbreaks. The European MediLabSecure project designed an identification (ID) exercise available to any willing participant with the aim of assessing and improving knowledge in mosquito taxonomy. The exercise was based on high-definition photomicrographs of mosquitoes (26 adult females and 12 larvae) collected from the western Palaearctic. Sixty-five responses from Europe, North Africa and the Middle East were usable. The study demonstrated that the responders were better at identifying females (82% correct responses) than larvae (63%). When the responders reported that they were sure of the accuracy of their ID, the success rate of ID increased (92% for females and 88% for larvae). The top three tools used for ID were MosKeyTool (72% of responders), the ID key following Becker et al. [2010. Mosquitoes and their control, 2nd edn. Berlin: Springer] (38%), and the CD-ROM of Schaffner et al. [2001. Les moustiques d’Europe: logiciel d’identification et d’enseignement – The mosquitoes of Europe: an identification and training programme. Montpellier: IRD; EID] (32%), while other tools were used by less than 10% of responders. Responders reporting the identification of mosquitoes using the MosKeyTool were significantly better (80% correct responses) than non-MosKeyTool users (69%). Most responders (63%) used more than one ID tool. The feedback from responders in this study was positive, with the exercise being perceived as halfway between educational training and a fun quiz. It raised the importance of further expanding training in mosquito ID for better preparedness of mosquito surveillance and control programmes

Mosquito Alert Dataset

The Mosquito Alert dataset includes occurrence records of adult mosquitoes. The records were collected through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Each record presented in the database is linked to a photograph submitted by a citizen scientist and validated by entomological experts to determine if it provides evidence of the presence of any of five targeted mosquito vectors of top concern in Europe (i.e. Aedes albopictus, Aedes aegypti, Aedes japonicus, Aedes koreicus, Culex pipiens). The temporal coverage of the database is from 2014 through 2022 and the spatial coverage is worldwide. Most of the records from 2014 to 2020 are from Spain, reflecting the fact that the project was funded by Spanish national and regional funding agencies. Since autumn 2020 the data has expanded to include substantial records from other countries in Europe, particularly the Netherlands, Italy, and Hungary, thanks to a human volunteering network of entomologists coordinated by the AIM-COST Action and to technological developments through the VEO project to increase scalability. Among many possible applications, Mosquito Alert dataset facilitates the development of citizen-based early warning systems for mosquito-borne disease risk. This dataset can be further re-used for modelling vector exposure risk or training machine-learning detection and classification routines on the linked images, to help experts in data validation and build up automated alert systems

Mosquito Alert Dataset

The Mosquito Alert dataset includes occurrence records of adult mosquitoes. The records were collected through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Each record presented in the database is linked to a photograph submitted by a citizen scientist and validated by entomological experts to determine if it provides evidence of the presence of any of five targeted mosquito vectors of top concern in Europe (i.e. Aedes albopictus, Aedes aegypti, Aedes japonicus, Aedes koreicus, Culex pipiens). The temporal coverage of the database is from 2014 through 2022 and the spatial coverage is worldwide. Most of the records from 2014 to 2020 are from Spain, reflecting the fact that the project was funded by Spanish national and regional funding agencies. Since autumn 2020 the data has expanded to include substantial records from other countries in Europe, particularly the Netherlands, Italy, and Hungary, thanks to a human volunteering network of entomologists coordinated by the AIM-COST Action and to technological developments through the VEO project to increase scalability. Among many possible applications, Mosquito Alert dataset facilitates the development of citizen-based early warning systems for mosquito-borne disease risk. This dataset can be further re-used for modelling vector exposure risk or training machine-learning detection and classification routines on the linked images, to help experts in data validation and build up automated alert systems

Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset

Este artículo contiene 13 páginas, 2 figuras.The Mosquito Alert dataset includes occurrence records of adult mosquitoes collected worldwide in 2014–2020 through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Records are linked to citizen science-submitted photographs and validated by entomologists to determine the presence of five targeted European mosquito vectors: Aedes albopictus, Ae. aegypti, Ae. japonicus, Ae. koreicus, and Culex pipiens. Most records are from Spain, reflecting Spanish national and regional funding, but since autumn 2020 substantial records from other European countries are included, thanks to volunteer entomologists coordinated by the AIM-COST Action, and to technological developments to increase scalability. Among other applications, the Mosquito Alert dataset will help develop citizen science-based early warning systems for mosquito-borne disease risk. It can also be reused for modelling vector exposure risk, or to train machine-learning detection and classification routines on the linked images, to assist with data validation and establishing automated alert systems.This work was supported by: • 2021–2022 Fair Computational Epidemiology (FACE); Plataforma Temática Interdisciplinar PTI+ Salud Global, Consejo Superior de Investigaciones Científicas (CSIC); Grant No.: N/A. • 2020–2025 Human-Mosquito Interaction Project: Host-vector networks, mobility and the socio-ecological context of mosquito-borne disease; European Research Council (ERC); Grant No.: 853271. • 2020–2021 Strengthening Barcelona’s Defenses Against Disease-Vector Mosquitoes: Automatically Calibrated Citizen-Based Surveillance, Barcelona Ciència; Ajuntament de Barcelona, Institut de Cultura; Grant No.: BCNPC/00041. • 2020–2024 VEO: Versatile Emerging infectious disease Observatory, H2020 SC1-BHC-13-2019; European Commission (EC); Grant No.: 874735. • 2020–2025 Preparing for vector-borne virus outbreaks in a changing world: a One Health Approach; Dutch National Research Agenda (NWA); Grant No.: NWA/00686468. • 2019–2021 Big Mosquito Bytes: Community-Driven Big Data Intelligence to Fight Mosquito-Borne Disease; Fundació “La Caixa”, Health Research 2018 “la Caixa” Banking Foundation; Grant No.: HR19-00336. • 2018–2022 Aedes Invasive Mosquitoes (AIM), COST ACTION OC-2017-1-22105; European Cooperation in Science and Technology (COST); Grant No.: CA17108. • 2018 Mosquito Alert: programa para investigar y controlar mosquitos vectores de enfermedades como el Dengue, el Chikungunya y el Zika; Fundació “La Caixa”; Grant No.: N/A. • 2017–2019 Plataforma Integral per al Control de l’Arbovirosis a Catalunya (PICAT); Departament de Salut, Programa PERIS 2016–2020, Generalitat de Catalunya; Grant No.: 00466. • 2016–2018 Ciència ciutadana per a la millora de la gestió i els models predictius de dispersió i distribució real de mosquit tigre a la Província de Girona; Diputació de Salut de Girona (DIPSALUT); Grant No.: N/A. • 2016 Nuevas herramientas de participación en ciencia ciudadana: laboratorios de validación y cocreación para AtrapaelTigre.com; Fundación Española para la Ciencia y la Tecnología (FECYT); Grant No.: FCT-15-9515. • 2016–2017 Mosquito Alert: programa para investigar y controlar mosquitos vectores de enfermedades como el Dengue, el Chikungunya y el Zika; Fundació “La Caixa”; Grant No.: N/A. • 2016–2017 Ciència ciutadana per a la millora de la gestió i els models predictius de dispersió i distribució real de mosquit tigre a la Província de Girona; Diputació de Salut de Girona (DIPSALUT); Grant No.: N/A. • 2015–2016 Citizens-based early warning systems for invasive species and disease vectors: The case of the Asian Tiger mosquito; Fundació “La Caixa” and Centre de Recerca Ecològica i Aplicacions Forestals (CREAF); Grant No.: N/A. • 2014–2016 Invasión del mosquito tigre en España: Salud pública y cambio global; Ministerio de Economía y Competitividad, Plan Estatal I+D+I; Grant No.: CGL2013-43139-R. • 2014 Diseño e implementación de un sistema ciudadano de alerta y seguimiento del mosquito tigre: ciencia en sociedad (Atrapa el Tigre 2.0); Fundación Española para la Ciencia y la Tecnología (FECYT); Grant No.: FCT-13-701955.Peer reviewe

Mosquito Alert - Leveraging Citizen Science to Create a GBIF Mosquito Occurrence Dataset

The Mosquito Alert dataset includes occurrence records of adult mosquitoes collected worldwide in 2014–2020 through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Records are linked to citizen science-submitted photographs and validated by entomologists to determine the presence of five targeted European mosquito vectors: Aedes albopictus, Ae. aegypti, Ae. japonicus, Ae. koreicus, and Culex pipiens. Most records are from Spain, reflecting Spanish national and regional funding, but since autumn 2020 substantial records from other European countries are included, thanks to volunteer entomologists coordinated by the AIM-COST Action, and to technological developments to increase scalability. Among other applications, the Mosquito Alert dataset will help develop citizen science-based early warning systems for mosquito-borne disease risk. It can also be reused for modelling vector exposure risk, or to train machine-learning detection and classification routines on the linked images, to assist with data validation and establishing automated alert systems