The GLOBE Program’s GLOBE Observer Mosquito Habitat Mapper is a no-cost citizen scientist data collection tool compatible with Android and iOS devices. Available in 14 languages and 126 countries, it supports mosquito vector surveillance, mitigation, and education by interested individuals and as part of participatory community surveillance programs. For low-resource communities where mosquito control services are inadequate, the Mosquito Habitat Mapper supports local health action, empowerment, and environmental justice. The tangible benefits to human health supported by the Mosquito Habitat Mapper have encouraged its wide adoption, with more than 32,000 observations submitted from 84 countries. The Mosquito Habitat Mapper surveillance and data collection tool is complemented by an open database, a map visualization interface, data processing and analysis tools, and a supporting education and outreach campaign. The mobile app tool and associated research and education assets can be rapidly deployed in the event of a pandemic or local disease outbreak, contributing to global readiness and resilience in the face of mosquito-borne disease. Here, we describe the app, the Mosquito Habitat Mapper information system, examples of Mosquito Habitat Mapper deployment in scientific research, and the outreach campaign that supports volunteer training and STEM education of students worldwide.
Most of Earth’s mosquito-borne illnesses are transmitted by mosquitoes
in one of three genera: Anopheles, Aedes, and Culex. Mosquitos of such
genera are located in all continents but Antarctica and infect millions
of humans with parasitic viruses yearly. However, a special concern is
reserved for Anopheles mosquitoes for their unique ability to carry and
transmit Malaria, a disease that, according to WHO, infects more than
200 million and kills over 500,000 humans annually (Malaria, 2022).
While it is most prevalent in Africa, Southeast Asia, and Central
America, Malaria could soon spread to northern and southern latitudes
with a changing global climate. Therefore, it is crucial to track the
extent of the Anopheles range and identify any changes that could have
detrimental consequences on public health. One way this can be done is
using the GLOBE Observer Mosquito Habitat Mapper (MHM) tool, which
allows global users free access to photograph mosquito larvae, attempt
to identify their genus, and upload said images to a worldwide database
that records the location at which they were taken. While citizen
science data is extremely helpful for mosquito research, it can be
difficult for citizens with minimal training to classify the genus of
their discovered larva correctly. A large portion of mosquito photos
uploaded to the GLOBE MHM database are either unidentified or
misidentified. Therefore, this research paper aims to devise and assess
how the MHM database can be appropriately classified to create an
accurate dataset with all Anopheles larvae photos classified by their
proper genus.Besides being a vector of Malaria, another unique
characteristic of theAnopheles mosquito is the absence of a siphon, so
by scanning for this trait among MHM larvae photographs and noting
positive matches, researchers created a dataset of mosquito larvae that
could become vectors of Malaria as adults (Image Reference #1). This
data set could then be used to train AImodels utilizing Convolutional
Neural Networks (CNN) or VisionTransformers (ViT) to classify the MHM
database autonomously in the near future.
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