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Using Geographic Information Systems and Decision Support Systems for the Prediction, Prevention, and Control of Vector-Borne Diseases
Abstract
Emerging and resurging vector-borne diseases cause significant morbidity and mortality, especially in the developing world. We focus on how advances in mapping, Geographic Information System, and Decision Support System technologies, and progress in spatial and space-time modeling, can be harnessed to prevent and control these diseases. Major themes, which are addressed using examples from tick-borne Lyme borreliosis; flea-borne plague; and mosquito-borne dengue, malaria, and West Nile virus disease, include (a) selection of spatial and space-time modeling techniques, (b) importance of using high-quality and biologically or epidemiologically relevant data, (c) incorporation of new technologies into operational vector and disease control programs, (d) transfer of map-based information to stakeholders, and (e) adaptation of technology solutions for use in resource-poor environments. We see great potential for the use of new technologies and approaches to more effectively target limited surveillance, prevention, and control resources and to reduce vector-borne and other infectious diseases.
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“In some cases GIS/GPS assisted surveillance and control operations can result in increased efficiency and precision, better mosquito control, and can provide automatic documentation for permitting and other reporting/regulatory purposes thus conserving resources and reducing the environmental impact of mosquito control [113].”
From North American Wetlands and Mosquito Control (2012) · cites this paper as [113]
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A Temporal-Spatial Analysis of Malaria Transmission in Adama, Ethiopia
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Self-citationAre RNA Viruses Candidate Agents for the Next Global Pandemic? A Review
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Metadata
- Authors
- Eisen, L., & Eisen, R. J.
- Affiliations
- Colorado State University (US)
- Centers for Disease Control and Prevention (US)
- Venue
- Annual Review of Entomology
- Publisher
- Annual Reviews
- Published
- 2011-01-07
- Volume
- 56
- Issue
- 1
- Pages
- 41-61
- ISSN
- 0066-4170 (ISSN-L)
- 1545-4487
- OpenAlex
- W2121362530
- Cited by
- 194
- References
- 126
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 5 · 2023: 6 · 2022: 15 · 2021: 13 · 2020: 12 · 2019: 17 · 2018: 14 · 2017: 13 · 2016: 16 · 2015: 13 · 2014: 20 · 2013: 16 · 2012: 13
- FWCI
- 1.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Entomology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (n01ai25489-12-0-1)
- National Institute of Allergy and Infectious Diseases (N01-AI-25489)
- Topics
- Life Sciences › Immunology and Microbiology › Parasitology › Vector-borne infectious diseases
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mosquito-borne diseases and control
- Health Sciences › Medicine › Epidemiology › Data-Driven Disease Surveillance
- Keywords
- vector-borne diseases, geographic information systems, decision support system, spatial modeling, spatio-temporal modeling, Lyme disease, plague, dengue, malaria, West Nile virus, vector control, disease surveillance, resource-limited settings
- MeSH terms
- Animals, Communicable Disease Control, Communicable Diseases, Decision Support Techniques, Disease Vectors, Humans
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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