The overall goal of the proposed study is to examine, build, and test a predictive model that defines the relationships between climate change, land use and cover change, social systems, and ecological disturbance on the ecological distribution of tsetse flies and African Trypanosomiasis or sleeping sickness across Kenya. This study responds to the announcement by specifically employing an interdisciplinary team to develop and deploy an innovative advanced spatial simulation system, """"""""ATcast,"""""""" that integrates dynamic multi-scale, multi-agent models, geographical and epidemiological methods, and a regional climate model. The information produced will directly affect on-going tsetse control programs and make a substantial contribution to understanding broader patterns of human-environment impacts, ecologically related changes, disease emergence, transmission, prevention and control, and future risk. The proposed study will enhance the scientific understanding of human impacts on ecological systems, how these changes influence the potential for disease emergence and transmission, and what models can be generated using new and existing climate, landscape, social, and organismal data to predict, or associate, disease epidemiology with ecological processes at multiple spatial, social, and biophysical scales of organization. African Trypanosomiasis or sleeping sickness is a major threat to human health in Africa. We will examine, build, and test a predictive model that defines the relationships between climate change, land use and cover change, social systems, and disturbance on the distribution of tsetse flies and sleeping sickness across Kenya. This study will enhance the scientific understanding of climate change and human impacts on ecological systems, and how these changes influence disease ecology.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21GM084704-04
Application #
7924783
Study Section
Special Emphasis Panel (ZDA1-GXM-A (27))
Program Officer
Anderson, James J
Project Start
2007-09-25
Project End
2012-08-31
Budget Start
2010-09-01
Budget End
2012-08-31
Support Year
4
Fiscal Year
2010
Total Cost
$279,829
Indirect Cost
Name
Michigan State University
Department
Miscellaneous
Type
Schools of Arts and Sciences
DUNS #
193247145
City
East Lansing
State
MI
Country
United States
Zip Code
48824
Langley, Shaun A; Messina, Joseph P; Moore, Nathan (2017) Using meta-quality to assess the utility of volunteered geographic information for science. Int J Health Geogr 16:40
Lin, Shengpan; DeVisser, Mark H; Messina, Joseph P (2015) An agent-based model to simulate tsetse fly distribution and control techniques: a case study in Nguruman, Kenya. Ecol Modell 314:80-89
Lin, Shengpan; Moore, Nathan J; Messina, Joseph P et al. (2013) Evaluation of MODIS surrogates for meteorological humidity data in east Africa. Int J Remote Sens 34:4669-4679
Messina, Joseph P; Moore, Nathan J; DeVisser, Mark H et al. (2012) Climate Change and Risk Projection: Dynamic Spatial Models of Tsetse and African Trypanosomiasis in Kenya. Ann Assoc Am Geogr 102:1038-1048
McCord, Paul F; Messina, Joseph P; Campbell, David J et al. (2012) Tsetse Fly Control in Kenya's Spatially and Temporally Dynamic Control Reservoirs: A Cost Analysis. Appl Geogr 34:189-204
Grady, Sue C; Messina, Joseph P; McCord, Paul F (2011) Population vulnerability and disability in Kenya's tsetse fly habitats. PLoS Negl Trop Dis 5:e957
Langley, Shaun A; Messina, Joseph P (2011) Embracing the Open-Source Movement for the Management of Spatial Data: A Case Study of African Trypanosomiasis in Kenya. J Map Geogr Libr 7:87-113
Moore, Nathan; Messina, Joseph (2010) A landscape and climate data logistic model of tsetse distribution in Kenya. PLoS One 5:e11809
DeVisser, Mark H; Messina, Joseph P (2009) Optimum land cover products for use in a Glossina-morsitans habitat model of Kenya. Int J Health Geogr 8:39