GH004
Climate based infectious disease early warning system
Session ID#: 81044
Session Description:
Climate variability such as El Nino/Southern Oscillation and Indian Ocean Dipole influence the abundance of vectors that in turn affect the spread of the diseases like malaria in many parts of the world. In addition to the pathogens, survival of the host is also directly influenced by climate conditions and indirectly through the climate induced environmental conditions. Many of these climate and environmental factors are also responsible for water-borne infections like diarrhea and airborne diseases like flu. Therefore, appropriately attributing the outbreaks in infectious diseases to climatic variables and quantifying those relationships to a number of outbreaks would be important in the directions of preparing climate based early warning systems for infectious diseases. This session will discuss those mechanisms of climate-disease connections and developments of mitigation measures. We encourage abstract submissions on the topics of climate link to infectious diseases, disease monitoring and climate-based early warning systems for infectious diseases.
Index Terms:
0230 Impacts of climate change: human health [GEOHEALTH]
0240 Public health [GEOHEALTH]
0245 Vector born diseases [GEOHEALTH]
4215 Climate and interannual variability [OCEANOGRAPHY: GENERAL]
Primary Convener: Swadhin K Behera, JAMSTEC Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan
Conveners: Kristie Ebi, University of Washington, Seattle, United States, Masahiro Hashizume, Nagasaki University, Nagasaki, Japan and Glenn McGregor, Durham University, Department of Geography, Durham, United Kingdom
Primary Liaison: Swadhin K Behera, JAMSTEC Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan
Disease Forecast Model Intercomparison Project: A Case Study with West Nile Virus in New York and Connecticut (495351)
Alexander C Keyel1, Oliver Elison Timm2, P Bryon Backenson3, Kathleen McDonough3, Philip M. Armstrong4, Theodore G. Andreadis5, Mathias F Vuille6 and Laura Kramer3, (1)Department of Health New York State, Albany, NY, United States, (2)State University of New York at Albany, Department of Atmospheric and Environmental Sciences, Albany, NY, United States, (3)New York State Department of Health, Albany, United States, (4)Connecticut Agricultural Experimental Station, Department of Environmental Sciences, New Haven, CT, United States, (5)Connecticut Agricultural Experimental Station, New Haven, CT, United States, (6)University at Albany, State University of New York, Department of Atmospheric and Environmental Sciences, Albany, NY, United States
On-demand Model Validation Built into Infectious Disease Early Warning Systems: Malaria Forecasts in Ethiopia with R package epidemiar (502604)
Dawn M Nekorchuk1, Justin Davis2, Worku Awoke3, Abere Mihretie4, Aklilu Getinet4, Mastewal Worku5, Teklehaimanot Gebrehiwot6 and Michael C Wimberly7, (1)University of Oklahoma Norman Campus, Norman, OK, United States, (2)University of Oklahoma Norman Campus, Geography and Environmental Sustainability, Norman, OK, United States, (3)Bahir Dar University, School of Public Health, Bahir Dar, Ethiopia, (4)Health, Development, and Anti-Malaria Association, Addis Ababa, Ethiopia, (5)Amhara Public Health Institute, Bahir Dar, Ethiopia, (6)Amhara National Regional State Health Bureau, Bahir Dar, Ethiopia, (7)University of Oklahoma, Department of Geography and Environmental Sustainability, Norman, OK, United States
Modeling Malaria in South Africa for Understanding Present and Future Variations (529595)
Venkata Ratnam Jayanthi1, Swadhin K Behera1, Francois Engelbrecht2 and Adrian Mark Tompkins3, (1)JAMSTEC Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan, (2)University of Witwatersrand, Global Change Institute, Pretoria, South Africa, (3)Abdus Salam International Center for Theoretical Physics, Trieste, Italy
The impact of ENSO 2015-16 on vector-borne diseases: from Zika virus transmission in Latin America to malaria vectors in Tanzania. (535380)
Cyril Caminade1, Katharina Kreppel2, Nicodem Govella3, Joanne Turner1, Soeren Metelmann1, Jenny Hesson4, Marcus S.C. Blagrove1, Tom Solomon1, Heather M Ferguson5, Andrew P Morse1 and Matthew Baylis1, (1)University of Liverpool, Liverpool, United Kingdom, (2)Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania, (3)Ifakara Health Institute, Dar es Salaam, Tanzania, (4)Uppsala University, Upsala, Sweden, (5)University of Glasgow, Glasgow, United Kingdom
Sensitivity of Malaria Transmission Dynamics to VECTRI Parameters (580220)
Abhishek Anand1, Vaibhav Kumar2, Ruchi Singh Parihar3, Saroj K. Mishra4 and Sandeep Sahany4, (1)Indian Institute of Technology Delhi, New Delhi, India, (2)Indian Institute of Technology, Delhi, DST Centre of Excellence in Climate Modeling, Delhi, India, (3)Indian Institute of Technology Delhi, Centre for Atmospheric Sciences, Delhi, India, (4)Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India
Impact of Future Climate Change on Potential Malaria Transmission Dynamics over Odisha using VECTRI Model (586227)
Ruchi Singh Parihar1, Prasanta Kumar Bal2, Saroj K. Mishra3 and Sandeep Sahany3, (1)Indian Institute of Technology Delhi, Centre for Atmospheric Sciences, Delhi, India, (2)Indian Institute of Technology Delhi, Centre for Amospheric Sciences, Delhi, India, (3)Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India
