Identification

Name

Cholera Environmental Signatures

Contact people
(1) Alen Agheksanterian, aa5@math.umbc.edu
(2) Rita Colwell, rcolwell@umiacs.umd.edu
(3) Matthias Gobbert, gobbert@math.umbc.edu
Created

2013-11-13 21:29:58+00:00

Modified

2015-12-01 19:56:33.288957+00:00

Overview

Types
(1) Anomaly Detection
Overview

This model takes a historical approach in demonstrating that environmental signatures can predict cholera epidemics. Satellite derived datasets were used to model the relationship between these related environmental factors and cholera dynamics in Kolkata and Matlab, Bangladesh.

Question

Which environmental factors are associated with cholera epidemics in the northern Bay of Bengal?

Purpose

Prediction

Scope

Specific disease application

Goals
(1) Early detection
(2) Early warning
Decision support

Unknown

Based on
Methods
(1) Regression
Products
(1) Contact network
(2) Disease incidence
Documents
(1) Document de Magny GC, Murtugudde R, Sapiano MRP, Nizam A, Brown CW, et al.: Environmental signatures asso… (2008)
Notes
General notes

"Because the three environmental datasets show a strong seasonal pattern, anomalies were computed to remove the effect of the annual cycle, which can result in spurious relationships between cotrending variables."

Application

Diseases
(1) Cholera
Locations
(1) Location Matlab
Status current
(2) Location Kolkata
Status current

Utility and readiness

Readiness

Study

Organizations
(1) Organization National Oceanic and Atmospheric Administration (NOAA)
Role Funding support
(2) Organization National Institutes of Health (NIH)
Role Funding support
(3) Organization Oceans and Human Health Initiative
Role Funding support
(4) Organization International Centre for Diarrhoeal Disease, Research, Bangladesh (ICDDR,b )
Role
Independently tested

No

Compared to model

No

Compared to reality

Yes

Verification & validation notes

Validation: to evaluate the models computed on the whole dataset, cross-validations predictions were also made from the model by predicting cholera cases for each year using the final model structure, i.e., with only significant parameters, but estimating coefficients on the data set without data for the year under consideration.The model was verified.

Sensitivity analysis

Yes

Availability

Developer contacted

No

Input

Input datasets
(1) Name Monthly accumulations of cholera cases from patients admitted to the ICCDR, B or the Infectious Diseases Hospital of the National Institute of Cholera nd Enteric Diseases
Category Laboratory Records
Subject Disease: Epidemiological
URL
Notes
(2) Name Satellite-derived data for sea surface temperature, CHL , and local rainfall from the Sea-viewing Wide Field of View project
Category Established Databases
Subject Environment: Climate
URL
Notes