Identification

Name

Maxent Modeling of Plague

Contact people
(1) Peng Gong, Professor and Co-Director, gong@nature.berkeley.edu
Created

2014-08-18 21:50:24+00:00

Modified

2015-12-04 01:10:48.137956+00:00

Overview

Types
(1) Disease Dynamics
(2) Risk Mapping
Overview

Maxent, a machine-learning method can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (Spermophilus beecheyi) as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC) statistics. Additionally, model results were compared to locations of positive and negative coyote (Canis latrans) samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance.

Question

What will the impacts of climate change be on the emergence of infectious diseases, including plague?

Purpose

Prediction

Goals
(1) Baseline awareness
Decision support

No

Based on
Products
(1) Spatial risk map
(2) Spatio-temporal risk map
Documents
(1) Document Holt AC, Salkeld DJ, Fritz CL, Tucker JR, Gong P: Spatial analysis of plague in California: Nich… (2009)
Notes
(2) Document Phillips SJ, Dudik M, Schapire RE: A maximum entropy approach to species distribution modeling (2004)
Notes

Application

Diseases
(1) Plague
Locations
(1) Location California
Status

Utility and readiness

Readiness

Configurable Generic Framework

Organizations
(1) Organization University of California (UC)
Role

Input

Input datasets
(1) Name Worldclim bioclimatic variables
Category Established Databases
Subject
URL www.webcitation.org/query.php?url=http://www.worldclim.org&refdoi=10.1186/1476-072x-8-38
Notes