The project is implemented within the frame of the CNCS grant "Geospatial approach to the ecology, distribution and vectorial role of parasitic Arthropoda" (PCE 236/2011). The project has two main aims: (1) to develop multi-user web-based application (the interface is at for displaying the global distribution of ectoparasitic Arthropoda and (2) to gather new data on the diversity, host-association and distribution of parasitic arthropods.


Project coordinator: Andrei D. MIHALCA, DVM, MSc, PhD
Biologist: Attila D. SÁNDOR, MSc, PhD
Data-input and modelling: Cristian DOMȘA, MSc, PhD
Data-input and field assistant: Gianluca D'AMICO, DVM, PhD student

Time frame for implementation

October 2011-September 2014.

Scientific context and motivation

Arthropoda is the most diverse group of extant organisms, comprising over 80% of all known animal species. Although only relatively few groups are parasitic, their medical and social importance is huge, mostly because of the vector competence in the transmission of human and animal pathogens. Vector-borne diseases kill annually millions of people and livestock worldwide, especially in tropical and sub-tropical areas (i.e. malaria, trypanosomiases, yellow fever, dengue fever, theleriosis). Nevertheless, vector-borne pathogens in temperate areas are also responsible for debilitating conditions in humans and animals (i.e. Lyme borreliosis, tick borne encephalitis, anaplasmosis etc).
The most important parasitic Arthropoda of humans and animals include mosquitoes (Culicidae), sandflies (Phlebotominae), biting midges (Ceratopogonidae), biting flies (Simulidae, Tabanidae, Glossinidae), fleas (Siphonaptera), lice (Phthiraptera), myiases causing dipterans (Oestridae, Calliphoridae, Sarcophagidae), kissing bugs (Triatominae), ticks (Ixodidae, Argasidae), mites (Sarcoptidae, Trombiculidae).
The geographic distribution of parasitic Arthropoda and reservoir hosts gives the distribution of vector-borne pathogens and diseases. New ecological conditions essentially contribute to emergence of diseases into new territories or re-emergences of old diseases. Due to natural and anthropogenic climate change, vector and pathogen distribution change in relatively short time (Randolph, 2008; Reiter, 2008; Stone, 2008). Understanding the dynamics of the geographical distribution of vectors facilitates the development of predictive models in human and animal health. Moreover, an analytical geographical approach to distribution of parasitic Arthropoda and their host association, combined with genetic data, contribute to a more complex understanding of phylogenetic and co-evolutionary interrelations of parasites and hosts.

The data on the geographical distribution of parasites is most often presented without information on host associations. Moreover, there is no interactive free database available on parasite-host associations. With this view, our aim is to create a freely accessible multi-user/multi-task online database with georeferenced data on parasitic Arthropoda-host associations. The online database is intended to be created using GIS tools with a variety of formats available for user. Scientists around the world will be allowed and encouraged to permanently submit georeferenced data on their research or to digitalize older references. The potential users of this free database will include researchers, students, scholars, medical and veterinary personnel, health officers, epidemiologists, climatologists, officials etc.


Objective 1. Development of a multi-user/multi-task web-based application for geospatial management of host-parasitic Arthropoda interactions.
This will be the first ever database of its kind. Due to its web-based platform it will be freely available worldwide, requiring only a computer and an internet connection. The user friendly interface will allow easy browsing and data management.

Objective 2. Conversion and archiving of historical records on parasitic Arthropoda into georeferenced data.
A lot of valuable scientific data is available in various printed serials and book, in various languages around the world. However, even if location of parasites-host association is clearly stated, no georeferenced data is available. Our team intends to convert in the three years of the project cca. 50.000 parasitic arthropod-host associations into georeferenced entries in the database. Meanwhile, the database will be presented in various scientific meetings worldwide and we estimate a significant number of data to be achieved from registered users.

Objective 3. Expansion of geospatial data on distribution, ecology and host associations of parasitic Arthropoda.
During the three years of the project, the team members will collect samples of parasitic arthropods in various georeferenced locations. Parasites and hosts will be identified and introduced in the database.

Objective 4. Development of a new geospatial modeling tool to facilitate research on vector-borne diseases.
The main outcome of such a database is the possibility of creating prediction models. Correlating distribution data with climatic and ecological information, modeling software will be able to create prediction maps for future or for current missing data. There are indications that certain arthropod vectors/parasites are favored by certain micro-habitat types. Environmental geographical information systems-remote sensing (GIS/RS)-based data, overlaid with georeferenced occurrence data will offer useful predictors of presence/absence for these species. By combining the above-mentioned GIS/RS-based data with logistic regression models for habitat suitability of host-seeking parasites one may provide a scaled distribution map of parasitic Arthropoda abundance. By using georeferenced data we can easily detect changes in distribution due to climate change or habitat/land-use alteration as parasite occurrences are easily corroborated with remote sensing and/or real-time vegetation data.

Project financed by UEFISCDI

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