Mosquito Alert
Contents
Mosquito Alert¶
Mosquito Alert is a citizen science system aimed at investigating and managing disease-carrying mosquitoes. It has been operational since 2014, with most participants initially located in Spain and participation expanding worldwide, particularly in Europe since 2020. It uses mobile phones and the Internet to bring together citizens, scientists, and public health authorities to fight against MBDs. Mosquito Alert combines authoritative data with citizen science methodologies for data quality assessment and modelling, enabling large-scale estimates of mosquito population dynamics and the human-mosquito interactions through which MBDs are transmitted across a range of scales.
The data set presented here was collected through the Mosquito Alert mobile phone application. Citizen scientists provide geo-localized reports and images of targeted mosquito species, breeding sites and biting behaviour. Mosquito Alert also includes a module for sending samples to reference research labs in Europe that can be launched when and where considered necessary, allowing these labs to perform vector specialised identification and screening analyses. In addition, the app collects anonymous information on the geographic distribution of participants in order to correct for sampling effort biases. The application also includes a participant scoring and a notification system that provides scientific and educational contents to participants. These features are expected to increase engagement and encourage frequent and extensive participation.
The five target species that citizen scientists can report are *Ae. albopictus, Ae. aegypti, Ae. japonicus, Ae. koreicus, and Cx. pipiens. The targeted Aedes species are relatively easy to identify in photographs, whereas Culex pipiens can be difficult to distinguish from other Culex species. App tutorials and communication with citizen scientists are used to facilitate the identification and reporting of the targeted species. Adult mosquito reports containing photos are validated independently by three expert entomologists from the Digital Entomological Network in a web‐based private platform, the digital Entolab. In addition to these species of interest, expert entomologists also identify other species of mosquitoes (not targeted) and even other insect groups. These identifications are also valuable from an educational perspective, as they help citizen scientists understand differences between targeted and non-targeted mosquitoes/insects. Since manual inspection of digital images is not a scalable option, the Mosquito Alert database of expert‐validated images has been used to train a deep learning model to find Ae. albopictus and the other target species (work in progress). This artificial intelligence system will not only be a helpful pre‐selector for the expert validation process but also an automated classifier giving quick feedback to the app participants, which is expected to contribute to long‐term motivation.
In this dataset we must differentiate two periods: the period 2014-2020 (August) and the period 2020 (September)-2021. During the period 2014-2020 the project was mainly focused in Spain, funded from various national sources, and therefore, most of the reports are from there. During this period the system was looking for two invasive species: Ae. albopictus and Ae. aegypti. This mosquito surveillance tool has so far yielded valuable results. It has served to monitor the spread of Ae. albopictus in Spain and to investigate mosquito species dispersal mechanisms. It was also the source of the first-ever confirmed observation of Ae. japonicus in Spain and it has served as the basis for estimating the Ae. japonicus distribution in northern Spain. Mosquito Alert also provided the first record of Ae. (Fredwardsius) vittatus in northwestern Spain and it has contributed to mosquito biodiversity knowledge more broadly. In addition to all this, Mosquito Alert provides direct links between researchers, public health authorities and the general public, serving as a valuable means for promoting public awareness and education about MBDs.
From September 2020 to 2021 the project increased the number of targeted mosquito species to the five listed above, and expanded across Europe with the support of European funding (AIM-COST OC-2017-1-22105, CA17108; VEO SC1-BHC-13-2019,874735). These projects have facilitated the required changes to increase the number of targeted species, scale the system at European level, and promote the development of a Digital Entomological Network of experts, boosting the dissemination of activities across Europe to promote data collection and direct interaction with citizen scientists in different countries. In 2020 and 2021, the digital citizen science surveillance through Mosquito Alert was carried out in combination with pan-European harmonised field entomological sampling (AIMSurv campaigns) under the framework of AIM-COST Action. Data outputs of these activities are presented in this special issue, being the results of citizen science activities part of the whole Mosquito Alert dataset.
The project is coordinated by the Spanish National Research Council (CSIC; CEAB-CSIC), the Centre for Ecological Research and Forestry Applications (CREAF) and the Pompeu Fabra University (UPF).
Funding¶
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.