Spatial modelling of disease using data- and knowledge-driven approaches.

[1]  J. Grinnell Field Tests of Theories Concerning Distributional Control , 1917, The American Naturalist.

[2]  G. E. Hutchinson,et al.  Homage to Santa Rosalia or Why Are There So Many Kinds of Animals? , 1959, The American Naturalist.

[3]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .

[4]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[5]  George E. P. Box,et al.  Empirical Model‐Building and Response Surfaces , 1988 .

[6]  Derek J. Pike,et al.  Empirical Model‐building and Response Surfaces. , 1988 .

[7]  K. De Jong Learning with Genetic Algorithms: An Overview , 1988 .

[8]  David R. B. Stockwell,et al.  Induction of sets of rules from animal distribution data: a robust and informative method of data analysis , 1992 .

[9]  J. Franklin Predictive vegetation mapping: geographic modelling of biospatial patterns in relation to environmental gradients , 1995 .

[10]  Eastman J. Ronald,et al.  RASTER PROCEDURES FOR MULTI-CRITERIA/MULTI-OBJECTIVE DECISIONS , 1995 .

[11]  Yoav Freund,et al.  Experiments with a New Boosting Algorithm , 1996, ICML.

[12]  J. Ronald Eastman,et al.  GIS and Uncertainly Management: New Directions in Software Development , 1997 .

[13]  G. Ridgeway The State of Boosting ∗ , 1999 .

[14]  Jacek Malczewski,et al.  GIS and Multicriteria Decision Analysis , 1999 .

[15]  David R. B. Stockwell,et al.  The GARP modelling system: problems and solutions to automated spatial prediction , 1999, Int. J. Geogr. Inf. Sci..

[16]  Antoine Guisan,et al.  Predictive habitat distribution models in ecology , 2000 .

[17]  Jacek Malczewski,et al.  On the Use of Weighted Linear Combination Method in GIS: Common and Best Practice Approaches , 2000, Trans. GIS.

[18]  G. De’ath,et al.  CLASSIFICATION AND REGRESSION TREES: A POWERFUL YET SIMPLE TECHNIQUE FOR ECOLOGICAL DATA ANALYSIS , 2000 .

[19]  Andrew B. Lawson,et al.  Statistical Methods in Spatial Epidemiology , 2001 .

[20]  David R. B. Stockwell,et al.  Effects of sample size on accuracy of species distribution models , 2002 .

[21]  D. Chessel,et al.  ECOLOGICAL-NICHE FACTOR ANALYSIS: HOW TO COMPUTE HABITAT-SUITABILITY MAPS WITHOUT ABSENCE DATA? , 2002 .

[22]  A. Hirzel,et al.  Modeling Habitat Suitability for Complex Species Distributions by Environmental-Distance Geometric Mean , 2003, Environmental management.

[23]  A. Peterson,et al.  Lutzomyia vectors for cutaneous leishmaniasis in Southern Brazil: ecological niche models, predicted geographic distributions, and climate change effects. , 2003, International journal for parasitology.

[24]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[25]  Jeroen P. van der Sluijs,et al.  A framework for dealing with uncertainty due to model structure error , 2004 .

[26]  M. Araújo,et al.  An evaluation of methods for modelling species distributions , 2004 .

[27]  A. Peterson,et al.  Distribution of Members of Anopheles quadrimaculatus Say s.l. (Diptera: Culicidae) and Implications for Their Roles in Malaria Transmission in the United States , 2004, Journal of medical entomology.

[28]  A. Guisan,et al.  An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data , 2004 .

[29]  Jacek Malczewski,et al.  GIS-based land-use suitability analysis: a critical overview , 2004 .

[30]  Miroslav Dudík,et al.  A maximum entropy approach to species distribution modeling , 2004, ICML.

[31]  Leo Breiman,et al.  Bagging Predictors , 1996, Machine Learning.

[32]  A. Peterson,et al.  Geographic and ecologic distributions of the Anopheles gambiae complex predicted using a genetic algorithm. , 2004, The American journal of tropical medicine and hygiene.

[33]  Ricardo Scachetti Pereira,et al.  Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species. , 2004, Revista da Sociedade Brasileira de Medicina Tropical.

[34]  A. Prasad,et al.  Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction , 2006, Ecosystems.

[35]  C. Sutton Classification and Regression Trees, Bagging, and Boosting , 2005 .

[36]  A. Peterson,et al.  INTERPRETATION OF MODELS OF FUNDAMENTAL ECOLOGICAL NICHES AND SPECIES' DISTRIBUTIONAL AREAS , 2005 .

[37]  T. Dawson,et al.  Selecting thresholds of occurrence in the prediction of species distributions , 2005 .

[38]  David R. B. Stockwell,et al.  The use of the GARP genetic algorithm and internet grid computing in the Lifemapper world atlas of species biodiversity , 2005, ArXiv.

[39]  J. Fitzpatrick,et al.  Genetic Algorithms in Noisy Environments , 2005, Machine Learning.

[40]  T. Hastie,et al.  Variation in demersal fish species richness in the oceans surrounding New Zealand: an analysis using boosted regression trees , 2006 .

[41]  Mark S. Boyce,et al.  Modelling distribution and abundance with presence‐only data , 2006 .

[42]  A. Townsend Peterson,et al.  Novel methods improve prediction of species' distributions from occurrence data , 2006 .

[43]  J. Malone,et al.  Ecological niche modeling for visceral leishmaniasis in the state of Bahia, Brazil, using genetic algorithm for rule-set prediction and growing degree day-water budget analysis. , 2006, Geospatial health.

[44]  L. Beckett,et al.  Analysis of Genetic Algorithm for Rule-Set Production (GARP) Modeling Approach for Predicting Distributions of Fleas Implicated as Vectors of Plague, Yersinia pestis, in California , 2006, Journal of medical entomology.

[45]  T. Dawson,et al.  Model‐based uncertainty in species range prediction , 2006 .

[46]  J. Malczewski,et al.  Ordered weighted averaging with fuzzy quantifiers: GIS-based multicriteria evaluation for land-use suitability analysis , 2006 .

[47]  Robert P. Anderson,et al.  Maximum entropy modeling of species geographic distributions , 2006 .

[48]  Jane Elith,et al.  Error and uncertainty in habitat models , 2006 .

[49]  A. Peterson,et al.  Ecologic Niche Modeling and Spatial Patterns of Disease Transmission , 2006, Emerging infectious diseases.

[50]  D. White,et al.  Predicting climate‐induced range shifts: model differences and model reliability , 2006 .

[51]  D. Pfeiffer,et al.  Application of knowledge-driven spatial modelling approaches and uncertainty management to a study of Rift Valley fever in Africa , 2006, International journal of health geographics.

[52]  L. P. Lounibos,et al.  Spread of the tiger: global risk of invasion by the mosquito Aedes albopictus. , 2007, Vector borne and zoonotic diseases.

[53]  P. Hernandez,et al.  Predicting species distributions in poorly-studied landscapes , 2008, Biodiversity and Conservation.

[54]  Pham Van Ky,et al.  Malaria in central Vietnam: analysis of risk factors by multivariate analysis and classification tree models , 2008, Malaria Journal.

[55]  M. Hugh-jones,et al.  Modeling the geographic distribution of Bacillus anthracis, the causative agent of anthrax disease, for the contiguous United States using predictive ecological [corrected] niche modeling. , 2007, The American journal of tropical medicine and hygiene.

[56]  N. Best,et al.  Spatial risk assessment of Rift Valley fever in Senegal. , 2007, Vector borne and zoonotic diseases.

[57]  G. De’ath Boosted trees for ecological modeling and prediction. , 2007, Ecology.

[58]  A. Estrada-Peña,et al.  Climate Niches of Tick Species in the Mediterranean Region: Modeling of Occurrence Data, Distributional Constraints, and Impact of Climate Change , 2007, Journal of medical entomology.

[59]  Peterson At Ecological niche modelling and understanding the geography of disease transmission. , 2007 .

[60]  J. Rudant,et al.  Determining areas that require indoor insecticide spraying using Multi Criteria Evaluation, a decision-support tool for malaria vector control programmes in the Central Highlands of Madagascar , 2007, International journal of health geographics.

[61]  Peter A. Vanrolleghem,et al.  Uncertainty in the environmental modelling process - A framework and guidance , 2007, Environ. Model. Softw..

[62]  William H. Majoros,et al.  Methods for Computational Gene Prediction: Machine-learning methods , 2007 .

[63]  A. W. Sweeney,et al.  Analysis of environmental factors influencing the range of anopheline mosquitoes in northern Australia using a genetic algorithm and data mining methods , 2007 .

[64]  Omri Allouche,et al.  A comparative evaluation of presence‐only methods for modelling species distribution , 2007 .

[65]  S. Sarkar,et al.  Malaria in Africa: Vector Species' Niche Models and Relative Risk Maps , 2007, PloS one.

[66]  Miroslav Dudík,et al.  Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation , 2008 .

[67]  K. Bollmann,et al.  Living on the edge - modelling habitat suitability for species at the edge of their fundamental niche , 2008 .

[68]  Julian D Olden,et al.  Machine Learning Methods Without Tears: A Primer for Ecologists , 2008, The Quarterly Review of Biology.

[69]  D. Rogers,et al.  Spatial variation in risk , 2008 .

[70]  D. Rogers,et al.  Spatial Analysis in Epidemiology , 2008 .

[71]  A. Peterson,et al.  Predictable ecology and geography of avian influenza (H5N1) transmission in Nigeria and West Africa. , 2008, Transactions of the Royal Society of Tropical Medicine and Hygiene.

[72]  J Elith,et al.  A working guide to boosted regression trees. , 2008, The Journal of animal ecology.

[73]  R. Real,et al.  AUC: a misleading measure of the performance of predictive distribution models , 2008 .

[74]  A. Peterson,et al.  Effects of sample size on the performance of species distribution models , 2008 .

[75]  Arthur P. Dempster,et al.  New Methods for Reasoning Towards PosteriorDistributions Based on Sample Data , 1966, Classic Works of the Dempster-Shafer Theory of Belief Functions.

[76]  A. Townsend Peterson,et al.  Rethinking receiver operating characteristic analysis applications in ecological niche modeling , 2008 .

[77]  D. Rogers,et al.  Spatial risk assessment and management of disease , 2008 .

[78]  Arthur P. Dempster,et al.  Upper and Lower Probabilities Induced by a Multivalued Mapping , 1967, Classic Works of the Dempster-Shafer Theory of Belief Functions.

[79]  D. Pfeiffer,et al.  Use of data mining techniques to investigate disease risk classification as a proxy for compromised biosecurity of cattle herds in Wales , 2008, BMC veterinary research.

[80]  A. Peterson,et al.  Geographic distribution and ecological niche of plague in sub-Saharan Africa , 2008, International journal of health geographics.

[81]  M. Wells,et al.  Modeling of Spatially Referenced Environmental and Meteorological Factors Influencing the Probability of Listeria Species Isolation from Natural Environments , 2009, Applied and Environmental Microbiology.

[82]  Yohay Carmel,et al.  Uses and Misuses of Multicriteria Decision Analysis (MCDA) in Environmental Decision Making , 2009, Risk analysis : an official publication of the Society for Risk Analysis.

[83]  A. Peterson,et al.  Ecology and geography of avian influenza (HPAI H5N1) transmission in the Middle East and northeastern Africa , 2009, International journal of health geographics.

[84]  J. Elith,et al.  Do they? How do they? WHY do they differ? On finding reasons for differing performances of species distribution models , 2009 .

[85]  Steven J. Phillips,et al.  Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. , 2009, Ecological applications : a publication of the Ecological Society of America.

[86]  F. Simard,et al.  Habitat suitability and ecological niche profile of major malaria vectors in Cameroon , 2009, Malaria Journal.

[87]  Robert Tibshirani,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.

[88]  M. Hugh-jones,et al.  Modeling the Potential Distribution of Bacillus anthracis under Multiple Climate Change Scenarios for Kazakhstan , 2010, PloS one.

[89]  S. Mak,et al.  Ecological Niche Modeling of Lyme Disease in British Columbia, Canada , 2010, Journal of medical entomology.

[90]  J. Franklin Mapping species distributions: Implementation of species distribution models , 2010 .

[91]  A. Peterson,et al.  Range-wide determinants of plague distribution in North America. , 2010, The American journal of tropical medicine and hygiene.

[92]  R. Sugumaran,et al.  Ecological Niche Modeling of Potential West Nile Virus Vector Mosquito Species in Iowa , 2010, Journal of insect science.

[93]  J. Franklin Mapping species distributions: Classification, similarity and other methods for presence-only data , 2010 .

[94]  M. Gilbert,et al.  Ecological Modeling of the Spatial Distribution of Wild Waterbirds to Identify the Main Areas Where Avian Influenza Viruses are Circulating in the Inner Niger Delta, Mali , 2010, EcoHealth.

[95]  David M. Frank,et al.  Chagas Disease Risk in Texas , 2010, PLoS neglected tropical diseases.

[96]  Caroline W. Kabaria,et al.  The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic précis , 2010, Parasites & Vectors.

[97]  Abdelhamid A. Elnaggar,et al.  Application of Remote-sensing Data and Decision-Tree Analysis to Mapping Salt-Affected Soils over Large Areas , 2009, Remote. Sens..

[98]  Jennifer A. Miller,et al.  Mapping Species Distributions: Spatial Inference and Prediction , 2010 .

[99]  S. Sarkar,et al.  Climate Change and Risk of Leishmaniasis in North America: Predictions from Ecological Niche Models of Vector and Reservoir Species , 2010, PLoS neglected tropical diseases.

[100]  B. Klinkenberg,et al.  Ecological Niche Modeling of Cryptococcus gattii in British Columbia, Canada , 2009, Environmental health perspectives.

[101]  P. Masuoka,et al.  Ecological niche model of Phlebotomus alexandri and P. papatasi (Diptera: Psychodidae) in the Middle East , 2010, International journal of health geographics.

[102]  A. Tran,et al.  Environmental risk mapping of canine leishmaniasis in France , 2010, Parasites & Vectors.

[103]  Calum R. Wilson,et al.  IXth International Symposium on Thysanoptera and Tospoviruses, 31 August - 4 September 2009 , 2010 .

[104]  M. Kulkarni,et al.  High Resolution Niche Models of Malaria Vectors in Northern Tanzania: A New Capacity to Predict Malaria Risk? , 2010, PloS one.

[105]  M. Gilbert,et al.  Persistence of Highly Pathogenic Avian Influenza H5N1 Virus Defined by Agro-Ecological Niche , 2010, EcoHealth.

[106]  Peter Brewer,et al.  openModeller: a generic approach to species’ potential distribution modelling , 2011, GeoInformatica.