Funding was requested to analyze and model cholera epidemics. In order to accomplish this task, the team will analyze spatio-temporal data from cholera outbreaks in Haiti (2010), Angola (2006) and London (1832); develop mathematical theory for coupled patch models of waterborne disease; and develop models to predict disease spread under different scenarios. The study will explore the contribution of humans (direct) and of environmental (delayed) pathways to disease transmission and investigate how heterogeneity in water quality, which is ubiquitous in developing countries, affects cholera disease dynamics. This project will advance understanding of the factors governing the spatial spread of cholera, examine how the arrangement and connectivity between cholera risk hot spots influence disease spread and develop a modeling framework for rapid response to a cholera crisis.
The proposed study has clear practical and theoretical significance for understanding and predicting not only cholera transmission, but other waterborne diseases as well, reaching beyond the specific study system. The team will develop mathematical theory for coupled patch models of waterborne diseases and advance understanding of the effects of movement of individuals and of water to cholera transmission. The team will also explore inclusion of data from early stages of an outbreak on parameter estimates and whether information on water quality and availability and on types of sanitation facilities available can be used to improve knowledge of model parameters before the disease has reached a given area.
This study will result in the training of undergraduates and graduate students, and include outreach to the Columbus Science Pub (public), Cornell's Summer Math Institute (undergraduates) and the UCLA Math Circle (grades K-12). This project will strengthen international scientific collaboration through interaction with scientists and students from the University of Toronto.
The research from this study will provide society benefits through improved understanding of the factors influencing the ability of cholera to invade, spread and persist in a region. The proposed study will provide a tool to predict disease spread under different scenarios for rapid response to a cholera crisis and evaluate the efficacy of different intervention strategies on containing cholera spatial spread. The team will interact and communicate their research findings to the Centers for Disease Control and the National Biosurveillance Integration Center within the Department of Homeland Security. They will collaborate with the United Nations University Institute for Water, Environment and Health to compile a database of time series data from cholera outbreaks worldwide, in association with data on water quality, water availability, and sanitation facilities from several outbreak locales.
Dataset | Latest Version Date | Current State |
---|---|---|
Angola weekly cholera incidence at the province level collected from 2016-02-13 to 2016-05-29 (Cholera_Disease_Dyn project) | 2017-11-28 | Final no updates expected |
Cholera and rainfall data collected in Haiti from 2010-2011 (Cholera Disease Dynamics project) | 2016-05-04 | Final no updates expected |
Principal Investigator: Professor Joseph Tien
Ohio State University
Co-Principal Investigator: Marisa C Eisenberg
University of Michigan
Co-Principal Investigator: Professor David N Fisman
University of Toronto (U of T)
Contact: Professor Joseph Tien
Ohio State University
Data Management Plan (24.01 KB)
05/19/2022