Date Published: March 31, 2009
Publisher: Public Library of Science
Author(s): Alexander Moffett, Stavana Strutz, Nelson Guda, Camila González, Maria Cristina Ferro, Víctor Sánchez-Cordero, Sahotra Sarkar, Juerg Utzinger
Partial Text: The Disease Vector Database is a global, free, public, Web-accessible resource presenting data on the geographical distribution of infectious disease vectors and reservoirs. At present, the Database contains records for dengue and malaria vectors and Chagas disease and leishmaniasis vectors and reservoirs. Future versions of the Database will include parasite data. These data can be used for a variety of purposes including the construction of ecological niche models and disease risk maps. The Database permits downloading data in formats designed to facilitate such use, for instance, as input files for popular niche modeling software packages such as Maxent and GARP.
Vector-borne infectious diseases adversely affect the health of large numbers of people globally. Effective response to these diseases requires representations of risk, which often take the form of risk maps –, with geographic estimates of risk based on distributions of parasite, vector, and reservoir species in addition to human population, social organization, and behavior. The feasibility of constructing risk maps has increased substantially in recent years due to the widespread availability of digital environmental layers, geographic information system (GIS) platforms, and advances in ecological niche modeling, which makes it possible to produce maps even with very few parasite, reservoir, and vector presence records . Niche models have been used to predict the geographic distributions of Chagas disease and leishmaniasis vectors and reservoirs and dengue and malaria vectors 3–5.
There are some existing databases for disease vectors, mainly for malaria. However, compared to the effort being reported here, each of these databases has some limitations (though some provide useful additional data beyond the scope of the Database described here). In 1996, the Mapping Malaria Risk in Africa (MARA) collaboration (http://www.mara.org.za/) began to provide a repository of information on malaria-transmission intensities in Africa . Though the focus of the collaboration was on parasite data rather than on vector data, it currently contains 2,535 georeferenced records of malaria vectors. However, the records cover only the six members of the Anopheles gambiae complex, and there is no information from continents other than Africa. Koum and colleagues (2005)  created a database of malaria vectors with georeferenced information sampled from 19 African locations. However, the focus was on establishing the proper ontology for such a database and not on public use. The Walter Reed Army Institute and the Smithsonian Institution’s MosquitoMap Web site (http://www.mosquitomap.org/) contains distributional information on mosquito species.
Chagas disease, dengue, leishmaniasis, and malaria were selected for initial inclusion in our Database because of the epidemiologic importance of vector and reservoir control for the prevention of their transmission and the availability of data. For the Database, the vectors and reservoirs implicated in the four diseases were identified from reviews. There were three sources for the data. First, a number of the data points (for instance, ∼10% of the reservoir data and ∼75% of the leishmaniasis vector data) came from field records of collaborators collected over several decades. This will eventually be the most important source of new data. Second, the ISI Web of Knowledge and Google Scholar were searched using “distribution” along with the genus and name of each species. References from the publications identified on the basis of this search were also consulted for additional data. Third, records from public databases such as MANIS (for mammal reservoir data; http://manisnet.org/), MARA, and MosquitoMap were included.
The Web site enables the submission of data from an unlimited number of collaborators, who are then listed on the Web page. Data from the Disease Vector Database can be used in a variety of ways to help us understand the geographic risk of disease. Restricting attention to publicly available data, maps of occurrence records from the Database can be used to identify areas that need attention. For instance, the neotropics south of México in Central America have not been adequately sampled for Chagas disease vectors and reservoirs (see Figure 1). Data on potential leishmaniasis reservoirs are lacking from areas outside North America; data on vectors are incomplete except in Latin America. As additional existing data are incorporated into the Database, the geographic limitations will become less severe. Nevertheless, it is likely that there will remain significant areas with no data because they have not been surveyed. Compared to malaria and dengue, strikingly little data are publicly available for Chagas disease and leishmaniasis.