Using geographic information systems and decision support systems for the prediction, prevention, and control of vector-borne diseases

Eisen, Lars; Eisen, Rebecca J.

doi:10.1146/annurev-ento-120709-144847

Cited by 194Vector-borne infectious diseasesMosquito-borne diseases and controlData-Driven Disease Surveillance

Using geographic information systems and decision support systems for the prediction, prevention, and control of vector-borne diseases

Eisen, Lars, Eisen, Rebecca J.·2011·Annual Review of Entomology

DOI 10.1146/annurev-ento-120709-144847

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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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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.
“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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Mabaso, M., Craig, M., Vounatsou, P., & Smith, T. A. (2005) · Tropical Medicine & International Health · doi:10.1111/j.1365-3156.2005.01462.x · Cited by 74 · see citing works
Geographic Information Systems and Spatial Analysis of AdultIxodes scapularis(Acari: Ixodidae) in the Middle Atlantic Region of the U.S.A.
Bunnell, J. E., Price, S. D., Das, A., Shields, T. M., & Glass, G. E. (2003) · Journal of Medical Entomology · doi:10.1603/0022-2585-40.4.570 · Cited by 72 · see citing works
Landscape and Land Cover Factors Influence the Presence of Aedes and Anopheles Larvae
Vanwambeke, S., Somboon, P., Harbach, R. E., Isenstadt, M., Lambin, É. F., Walton, C., & Butlin, R. K. (2007) · Journal of Medical Entomology · doi:10.1603/0022-2585(2007)44[133:lalcfi]2.0.co;2 · Cited by 71 · see citing works
Spread pattern of the first dengue epidemic in the city of Salvador, Brazil
Barreto, F. R., Teixeira, M. G., Costa, M. D. C. N., Carvalho, M. S., & Barreto, M. L. (2008) · BMC Public Health · doi:10.1186/1471-2458-8-51 · Cited by 70 · see citing works
Current practices in the spatial analysis of cancer: flies in the ointment.
Jacquez, G. M. (2004) · International Journal of Health Geographics · doi:10.1186/1476-072x-3-22 · Cited by 70 · see citing works
Spatio‐temporal modelling of rates for the construction of disease maps
MacNab, Y. C., & Dean, C. B. (2002) · Statistics in Medicine · doi:10.1002/sim.1021 · Cited by 69 · see citing works
Developing an Evidence-Based Decision Support System for Rational Insecticide Choice in the Control of African Malaria Vectors
Coleman, M. M., SHARP, B. L., Seocharan, I., & Hemingway, J. (2006) · Journal of Medical Entomology · doi:10.1603/0022-2585(2006)43[663:daedss]2.0.co;2 · Cited by 68 · see citing works
PREDICTING DENSITY OF IXODES PACIFICUS NYMPHS IN DENSE WOODLANDS IN MENDOCINO COUNTY, CALIFORNIA, BASED ON GEOGRAPHIC INFORMATION SYSTEMS AND REMOTE SENSING VERSUS FIELD-DERIVED DATA
Eisen, R. J., Eisen, L., & Lane, R. S. (2006) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2006.74.632 · Cited by 68 · see citing works
Self-citation
Impact of vector control on a dengue fever outbreak in Trinidad, West Indies, in 1998
Chadee, D. D., Williams, F. L. R., & Kitron, U. D. (2005) · Tropical Medicine & International Health · doi:10.1111/j.1365-3156.2005.01449.x · Cited by 67 · see citing works
Two Clustering Diffusion Patterns Identified from the 2001–2003 Dengue Epidemic, Kaohsiung, Taiwan
Kan, C.-C., Lee, P.-F., Wen, T., Chao, D., Wu, M.-H., Lin, N. H., Huang, S. Y.-J., Shang, C., Fan, I.-C., Shu, P., et al. (2008) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2008.79.344 · Cited by 66 · see citing works
Developing a spatial-statistical model and map of historical malaria prevalence in Botswana using a staged variable selection procedure
Craig, M., SHARP, B. L., Mabaso, M., & Kleinschmidt, I. (2007) · International Journal of Health Geographics · doi:10.1186/1476-072x-6-44 · Cited by 61 · see citing works
Combining mosquito vector and human disease data for improved assessment of spatial West Nile virus disease risk.
Winters, A. M., Bolling, B., Beaty, B., Blair, C., Eisen, R., Meyer, A. M., Pape, W. J., Moore, C. G., & Eisen, L. (2008) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2008.78.654 · Cited by 60 · see citing works
Self-citation
Disease cluster detection: a critique and a Bayesian proposal
Lawson, A. B. (2006) · Statistics in Medicine · doi:10.1002/sim.2417 · Cited by 52 · see citing works
A Spatial Model of Shared Risk for Plague and Hantavirus Pulmonary Syndrome in the Southwestern United States
Eisen, R. J., Glass, G. E., Eisen, L., Cheek, J. E., Enscore, R. E., Ettestad, P., & Gage, K. L. (2007) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2007.77.999 · Cited by 52 · see citing works
Self-citation
Human Plague in the Southwestern United States, 1957–2004: Spatial Models of Elevated Risk of Human Exposure to Yersinia pestis
Eisen, R. J., Enscore, R. E., Biggerstaff, B. J., Reynolds, P. J., Ettestad, P., Brown, T., Pape, J., Tanda, D. T., Levy, C. E., Engelthaler, D. M., et al. (2007) · Journal of Medical Entomology · doi:10.1603/0022-2585(2007)44[530:hpitsu]2.0.co;2 · Cited by 52 · see citing works
Self-citation
Residence-Linked Human Plague in New Mexico: A Habitat-Suitability Model
Eisen, R. J., Reynolds, P. J., Ettestad, P., Brown, T., Enscore, R. E., Biggerstaff, B. J., Cheek, J. E., Bueno, R., Targhetta, J., Montenieri, J. A., et al. (2007) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2007.77.121 · Cited by 51 · see citing works
Self-citation
The spatial distribution of Anopheles gambiae sensu stricto and An. arabiensis (Diptera: Culicidae) in Mali
Sogoba, N., Vounatsou, P., Bagayoko, M. M., Doumbia, S., Dolo, G., Gosoniu, L., Traore, S. F., Touré, Y. T., & Smith, T. A. (2007) · Geospatial health · doi:10.4081/gh.2007.269 · Cited by 49 · see citing works
Predictive Spatial Models for Risk of West Nile Virus Exposure in Eastern and Western Colorado
Winters, A., Eisen, R. J., Lozano‐Fuentes, S., Moore, C. G., Pape, W. J., & Eisen, L. (2008) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2008.79.581 · Cited by 47 · see citing works
Self-citation
Application of spatial technology in malaria research & control: some new insights.
Saxena, R., Nagpal, B. N., Srivastava, A., Gupta, S., & Dash, A. P. (2009) · PubMed · Cited by 44 · see citing works
Predicting Potential Risk Areas of Human Plague for the Western Usambara Mountains, Lushoto District, Tanzania
Neerinckx, S., Peterson, A. T., Gulinck, H., Deckers, J., Kimaro, D. N., & Leirs, H. (2010) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2010.09-0426 · Cited by 43 · see citing works
A Temporal-Spatial Analysis of Malaria Transmission in Adama, Ethiopia
Peterson, I., Borrell, L. N., El-Sadr, W. M., & Teklehaimanot, A. (2009) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2009.08-0662 · Cited by 42 · see citing works
Spatio-temporal patterns in county-level incidence and reporting of Lyme disease in the northeastern United States, 1990–2000
Waller, L. A., Goodwin, B. J., Wilson, M. L., Ostfeld, R. S., Marshall, S. L., & Hayes, E. B. (2007) · Environmental and Ecological Statistics · doi:10.1007/s10651-006-0002-z · Cited by 40 · see citing works
Towards Web-based representation and processing of health information
Gao, S., Mioc, D., Yi, X., Anton, F., Oldfield, E., & Coleman, D. (2009) · International Journal of Health Geographics · doi:10.1186/1476-072x-8-3 · Cited by 39 · see citing works
Assessing Human Risk of Exposure to Plague Bacteria in Northwestern Uganda Based on Remotely Sensed Predictors
Eisen, R. J., Griffith, K., Borchert, J. N., MacMillan, K., Apangu, T., Owor, N., Acayo, S., Acidri, R., Zielinski-Gutiérrez, E., Winters, A., et al. (2010) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2010.09-0737 · Cited by 39 · see citing works
Self-citation
Application of GIS in Modelling of Dengue Risk based on Socio-Cultural Data: Case of Jalor, Rajasthan, India
Bohra, A., Andrianasolo, H., & Luang, K. (2001) · Cited by 39 · see citing works
The use of GIS in ovitrap monitoring for dengue control in Singapore.
AiLeen, T., & RenJin, S. (2000) · Cited by 38 · see citing works
An example of decision support for trypanosomiasis control using a geographical information system in eastern Zambia.
Robinson, T. P., Harris, R. S., Hopkins, J. S., & Williams, B. G. (2002) · International Journal of Geographical Information Systems · doi:10.1080/13658810110095057 · Cited by 37 · see citing works
Modelling a discrete spatial response using generalized linear mixed models: application to Lyme disease vectors
Das, A., Lele, S. R., Glass, G. E., Shields, T., & Patz, J. A. (2002) · International Journal of Geographical Information Systems · doi:10.1080/13658810110099134 · Cited by 36 · see citing works
Evaluation of Environmental Data for Identification of Anopheles (Diptera: Culicidae) Aquatic Larval Habitats in Kisumu and Malindi, Kenya
Jacob, B. G., Arheart, K. L., Griffith, D. A., Mbogo, C. M., Githeko, A. K., Regens, J. L., Githure, J. I., Novak, R. J., & Beier, J. C. (2005) · Journal of Medical Entomology · doi:10.1093/jmedent/42.5.751 · Cited by 34 · see citing works
Spatial distribution of the chromosomal forms of anopheles gambiae in Mali
Sogoba, N., Vounatsou, P., Bagayoko, M. M., Doumbia, S., Dolo, G., Gosoniu, L., Traore, S. F., Smith, T. A., & Touré, Y. T. (2008) · Malaria Journal · doi:10.1186/1475-2875-7-205 · Cited by 33 · see citing works
Spatial Risk Models for Human Plague in the West Nile Region of Uganda
Winters, A., Staples, J. E., Ogen-Odoi, A., Mead, P. S., Griffith, K., Owor, N., Babi, N., Enscore, R. E., Eisen, L., Gage, K. L., et al. (2009) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2009.80.1014 · Cited by 33 · see citing works
Self-citation
Quantitative Assessment of the Benefits of Specific Information Technologies Applied to Clinical Studies in Developing Countries
Avilés, W., Ortega, O. R. D. R., Kuan, G. M., Coloma, J., & Harris, E. (2008) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2008.78.311 · Cited by 29 · see citing works
Spatial Risk Assessments Based on Vector-Borne Disease Epidemiologic Data: Importance of Scale for West Nile Virus Disease in Colorado
Winters, A., Eisen, R. J., Delorey, M. J., Fischer, M., Nasci, R. S., Zielinski-Gutiérrez, E., Moore, C. G., Pape, W. J., & Eisen, L. (2010) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.2010.09-0648 · Cited by 27 · see citing works
Self-citation
GIS and multiple-criteria evaluation for the optimisation of tsetse fly eradication programmes
Symeonakis, E., Robinson, T., & Drake, N. (2006) · Environmental Monitoring and Assessment · doi:10.1007/s10661-006-9210-0 · Cited by 24 · see citing works
New Initiatives in Dengue Control in Singapore
Teng, T. B. (2001) · Cited by 15 · see citing works
Evaluation of Environmental Data for Identification of Anopheles (Diptera: Culicidae) Aquatic Larval Habitats in Kisumu and Malindi, Kenya
Jacob, B. G., Arheart, K. L., Griffith, D. A., et al. (2005) · Journal of Medical Entomology · doi:10.1603/0022-2585(2005)042[0751:eoedfi]2.0.co;2 · Cited by 13 · see citing works
Changing blood lead levels and DNA damage (comet assay) among immigrant women in Taiwan
Wu, W., Liou, S.-H., Lin, K.-J., Liu, T.-E., Liu, S., Chen, C., Sung, F., & Wu, T.-N. (2009) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2009.07.025 · Cited by 12 · see citing works
Spatiotemporal Bayesian Analysis of Lyme Disease in New York State, 1990-2000
Chen, H., Stratton, H. H., Caraco, T. B., & White, D. J. (2006) · Journal of Medical Entomology · doi:10.1603/0022-2585(2006)43[777:sbaold]2.0.co;2 · Cited by 12 · see citing works

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Larval source management for malaria control in Africa: myths and reality
Fillinger, U., & Lindsay, S. W. (2011) · Malaria Journal · doi:10.1186/1475-2875-10-353 · Cited by 277 · see citing works
Transmission of Flea-Borne Zoonotic Agents
Eisen, R. J., & Gage, K. L. (2012) · Annual Review of Entomology · doi:10.1146/annurev-ento-120710-100717 · Cited by 239 · see citing works
Self-citation
Are RNA Viruses Candidate Agents for the Next Global Pandemic? A Review
Carrasco-Hernandez, R., Jácome, R., López‐Vidal, Y., & de León, S. P. (2017) · ILAR Journal · doi:10.1093/ilar/ilx026 · Cited by 226 · see citing works
Surveillance of Dengue Fever Virus: A Review of Epidemiological Models and Early Warning Systems
Racloz, V., Ramsey, R., Tong, S., & Hu, W. (2012) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0001648 · Cited by 191 · see citing works
Management of arthropod vector data – Social and ecological dynamics facing the One Health perspective
Benelli, G., & Duggan, M. F. (2018) · Acta Tropica · doi:10.1016/j.actatropica.2018.02.015 · Cited by 124 · see citing works
The landscape epidemiology of echinococcoses
Restrepo, A. C., Yang, Y. R., McManus, D. P., Gray, D. J., Giraudoux, P., Barnes, T. S., Williams, G. M., Magalhães, R. J. S., Hamm, N., & Clements, A. (2016) · Infectious Diseases of Poverty · doi:10.1186/s40249-016-0109-x · Cited by 119 · see citing works
Spatially explicit multi-criteria decision analysis for managing vector-borne diseases
Hongoh, V., Hoen, A. G., Aenishaenslin, C., Waaub, J., Bélanger, D., & Michel, P. (2011) · International Journal of Health Geographics · doi:10.1186/1476-072x-10-70 · Cited by 112 · see citing works
Building Resilience against Climate Effects—A Novel Framework to Facilitate Climate Readiness in Public Health Agencies
Marinucci, G., Luber, G., Uejio, C. K., Saha, S., & Hess, J. J. (2014) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph110606433 · Cited by 111 · see citing works
Mosquitoes (Culicidae)
Foster, W. A., & Walker, E. D. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-814043-7.00015-7 · Cited by 114 · see citing works
The Eye of the Tiger, the Thrill of the Fight: Effective Larval and Adult Control Measures Against the Asian Tiger Mosquito,Aedes albopictus(Diptera: Culicidae), in North America
Faraji, A., & Ünlü, I. (2016) · Journal of Medical Entomology · doi:10.1093/jme/tjw096 · Cited by 98 · see citing works
Geographic patterns and environmental factors associated with human yellow fever presence in the Americas
Hamrick, P. N., Aldighieri, S., Machado, G., Galan, D. I., Vilca, L. M., Uriona, S., & Schneider, M. C. (2017) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0005897 · Cited by 95 · see citing works
Visualizing the impact of space-time uncertainties on dengue fever patterns
Delmelle, E. M., Dony, C. C., Casas, I., Jia, M., & Tang, W. (2014) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2013.871285 · Cited by 89 · see citing works
Spatial analysis and mapping of malaria risk in an endemic area, south of Iran: A GIS based decision making for planning of control
Hanafi‐Bojd, A. A., Vatandoost, H., Oshaghi, M. A., Charrahy, Z., Haghdoost, A. A., Zamani, G., Abedi, F., Sedaghat, M. M., Soltani, M., Shahi, M., et al. (2012) · Acta Tropica · doi:10.1016/j.actatropica.2012.01.003 · Cited by 89 · see citing works
Land cover affects microclimate and temperature suitability for arbovirus transmission in an urban landscape
Wimberly, M. C., Davis, J. K., Evans, M., McMahon, A., Newberry, P. M., Solano, N., & Murdock, C. C. (2020) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0008614 · Cited by 88 · see citing works
North American Wetlands and Mosquito Control
Rey, J., Walton, W., Wolfe, R., Connelly, C., O'Connell, S., Berg, J., Sakolsky-Hoopes, G., & Laderman, A. (2012) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph9124537 · Cited by 85 · see citing works
A Gaussian process based big data processing framework in cluster computing environment
Manogaran, G., & Lopez, D. (2017) · Cluster Computing · doi:10.1007/s10586-017-0982-5 · Cited by 83 · see citing works
Geostatistical tools for the study of insect spatial distribution: practical implications in the integrated management of orchard and vineyard pests
Sciarretta, A., & Trematerra, P. (2014) · Plant Protection Science · doi:10.17221/40/2013-pps · Cited by 83 · see citing works
Space-time clusters and co-occurrence of chikungunya and dengue fever in Colombia from 2015 to 2016
Desjardins, M. R., Whiteman, A., Casas, I., & Delmelle, E. M. (2018) · Acta Tropica · doi:10.1016/j.actatropica.2018.04.023 · Cited by 74 · see citing works
Using GIS for Disease Mapping and Clustering in Jeddah, Saudi Arabia
Murad, A. A., & Khashoggi, B. F. (2020) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi9050328 · Cited by 70 · see citing works
Towards a resource‐based habitat approach for spatial modelling of vector‐borne disease risks
Hartemink, N., Vanwambeke, S., Purse, B. V., Gilbert, M., & Dyck, H. V. (2014) · Biological reviews/Biological reviews of the Cambridge Philosophical Society · doi:10.1111/brv.12149 · Cited by 64 · see citing works
Ecological Niche Modeling and Land Cover Risk Areas for Rift Valley Fever Vector, Culex tritaeniorhynchus Giles in Jazan, Saudi Arabia
Sallam, M. F., Ahmed, A. M. A., ABDEL-DAYEM, M. S., & Abdullah, M. A. R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0065786 · Cited by 59 · see citing works
Integrated Mosquito Management: Is Precision Control a Luxury or Necessity?
Fouet, C., & Kamdem, C. (2018) · Trends in Parasitology · doi:10.1016/j.pt.2018.10.004 · Cited by 60 · see citing works
Where Does Human Plague Still Persist in Latin America?
Schneider, M. C., Nájera, P., Aldighieri, S., Galan, D. I., Bertherat, E., Ruiz, A., Dumit, E. M., Gabastou, J.-M., & Espinal, M. (2014) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0002680 · Cited by 55 · see citing works
Prediction of High Incidence of Dengue in the Philippines
Buczak, A. L., Baugher, B. D., Babin, S. M., Ramac-Thomas, L. C., Guven, E., Elbert, Y., Koshute, P. T., Velasco, J. M., Roque, V. G., Tayag, E. A., et al. (2014) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0002771 · Cited by 56 · see citing works
First assessment of potential distribution and dispersal capacity of the emerging invasive mosquito Aedes koreicus in Northeast Italy
Marcantonio, M., Metz, M., Baldacchino, F., Arnoldi, D., Montarsi, F., Capelli, G., Carlin, S., Neteler, M., & Rizzoli, A. P. (2016) · Parasites & Vectors · doi:10.1186/s13071-016-1340-9 · Cited by 54 · see citing works
A web-based geospatial toolkit for the monitoring of dengue fever
Delmelle, E. M., Zhu, H., Tang, W., & Casas, I. (2014) · Applied Geography · doi:10.1016/j.apgeog.2014.05.007 · Cited by 49 · see citing works
A systematic review of spatial decision support systems in public health informatics supporting the identification of high risk areas for zoonotic disease outbreaks
Beard, R., Wentz, E. A., & Scotch, M. (2018) · International Journal of Health Geographics · doi:10.1186/s12942-018-0157-5 · Cited by 47 · see citing works
Models and Surveillance Systems to Detect and Predict West Nile Virus Outbreaks
Barker, C. M. (2019) · Journal of Medical Entomology · doi:10.1093/jme/tjz150 · Cited by 47 · see citing works
Multi-Disease Data Management System Platform for Vector-Borne Diseases
Eisen, L., Coleman, M., Lozano‐Fuentes, S., McEachen, N., Orlans, M., & Coleman, M. M. (2011) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0001016 · Cited by 46 · see citing works
Self-citation
Improvement of Disease Prediction and Modeling through the Use of Meteorological Ensembles: Human Plague in Uganda
Moore, S. M., Monaghan, A. J., Griffith, K., Apangu, T., Mead, P. S., & Eisen, R. J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0044431 · Cited by 46 · see citing works
Self-citation
Accelerating the discovery of space-time patterns of infectious diseases using parallel computing
Hohl, A., Delmelle, E. M., Tang, W., & Casas, I. (2016) · Spatial and Spatio-temporal Epidemiology · doi:10.1016/j.sste.2016.05.002 · Cited by 45 · see citing works
Spatiotemporal patterns ofAedes aegyptipopulations in Cairns, Australia: assessing drivers of dengue transmission
Duncombe, J., Clements, A., Davis, J., Hu, W., Weinstein, P., & Ritchie, S. A. (2013) · Tropical Medicine & International Health · doi:10.1111/tmi.12115 · Cited by 44 · see citing works
Environmental risk factors for the incidence of cutaneous leishmaniasis in an endemic area of Iran: A GIS-based approach
Ramezankhani, R., Hosseini, A., Sajjadi, N., Khoshabi, M., & Ramezankhani, A. (2017) · Spatial and Spatio-temporal Epidemiology · doi:10.1016/j.sste.2017.03.003 · Cited by 42 · see citing works
Impacts of climate change on water-related mosquito-borne diseases in temperate regions: A systematic review of literature and meta-analysis
Gizaw, Z., Salubi, E. A., Pietroniro, A., & Schuster‐Wallace, C. J. (2024) · Acta Tropica · doi:10.1016/j.actatropica.2024.107324 · Cited by 46 · see citing works
Mapping the Serological Prevalence Rate of West Nile fever in Equids, Tunisia
Bargaoui, R., Lecollinet, S., & Lancelot, R. (2013) · Transboundary and Emerging Diseases · doi:10.1111/tbed.12077 · Cited by 41 · see citing works
Tracking the distribution and impacts of diseases with biological records and distribution modelling
Purse, B. V., & Golding, N. (2015) · Biological Journal of the Linnean Society · doi:10.1111/bij.12567 · Cited by 40 · see citing works
Haemoplasmas in wild rodents: Routes of transmission and infection dynamics
Cohen, C., Shemesh, M., Garrido, M., Messika, I., Einav, M., Khokhlova, I. S., Tasker, S., & Hawlena, H. (2018) · Molecular Ecology · doi:10.1111/mec.14826 · Cited by 39 · see citing works
Mosquitoes & vulnerable spaces: Mapping local knowledge of sites for dengue control in Seremban and Putrajaya Malaysia
Dickin, S., Schuster‐Wallace, C. J., & Elliott, S. J. (2013) · Applied Geography · doi:10.1016/j.apgeog.2013.11.003 · Cited by 37 · see citing works
Smuggling across the Border: How Arthropod-Borne Pathogens Evade and Exploit the Host Defense System of the Skin
Bernard, Q., Jaulhac, B., & Boulanger, N. (2014) · Journal of Investigative Dermatology · doi:10.1038/jid.2014.36 · Cited by 37 · see citing works
Reality mining: A prediction algorithm for disease dynamics based on mobile big data
Chen, Y., Crespi, N., Ortiz, A. M., & Shu, L. (2016) · Information Sciences · doi:10.1016/j.ins.2016.07.075 · Cited by 37 · see citing works
Analysing water-borne diseases susceptibility in Kolkata Municipal Corporation using WQI and GIS based Kriging interpolation
Ali, S. A., & Ahmad, A. (2019) · GeoJournal · doi:10.1007/s10708-019-10015-3 · Cited by 38 · see citing works
Disease Prediction Models and Operational Readiness
Corley, C. D., Pullum, L., Hartley, D., Benedum, C. M., Noonan, C. F., Rabinowitz, P. M., & Lancaster, M. J. (2014) · PLoS ONE · doi:10.1371/journal.pone.0091989 · Cited by 36 · see citing works
Responses of Amblyomma americanum and Dermacentor variabilis to odorants that attract haematophagous insects
Carr, A. L., Roe, R. M., Arellano, C., Sonenshine, D. E., Schal, C., & Apperson, C. S. (2012) · Medical and Veterinary Entomology · doi:10.1111/j.1365-2915.2012.01024.x · Cited by 36 · see citing works
Recent and future environmental suitability to dengue fever in Brazil using species distribution model
Cardoso‐Leite, R., Vilarinho, A. C., Novaes, M. C., Tonetto, A. F., Vilardi, G. C., & Ferreira, R. G. N. (2014) · Transactions of the Royal Society of Tropical Medicine and Hygiene · doi:10.1093/trstmh/trt115 · Cited by 34 · see citing works
The Potential Distribution ofPhlebotomus papatasi(Diptera: Psychodidae) in Libya Based on Ecological Niche Model
ABDEL-DAYEM, M. S., Annajar, B. B., Hanafi, H. A., & Obenauer, P. J. (2012) · Journal of Medical Entomology · doi:10.1603/me11225 · Cited by 33 · see citing works
Livestock host composition rather than land use or climate explains spatial patterns in bluetongue disease in South India
Chanda, M. M., Carpenter, S. T., Prasad, G., Sedda, L., Henrys, P. A., Gajendragad, M. R., & Purse, B. V. (2019) · Scientific Reports · doi:10.1038/s41598-019-40450-8 · Cited by 33 · see citing works
Determining the spatial autocorrelation of dengue vector populations: influences of mosquito sampling method, covariables, and vector control
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Authors: Eisen, L., & Eisen, R. J.
Affiliations: Colorado State University (US)
Centers for Disease Control and Prevention (US)
ORCID: Eisen, Lars
Eisen, Rebecca J.
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
DOI: 10.1146/annurev-ento-120709-144847
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

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Using geographic information systems and decision support systems for the prediction, prevention, and control of vector-borne diseases

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