1. TEMPLATE DESIGN © 2008 www.PosterPresentations.com System Dynamic Modeling & Decision Tree Analysis to capture uncertainties of intervention choices and weather patterns on West Nile Virus disease outcomes Karen Yee 1, Dr. Nathaniel Osgood 2, Judith Wright 3, and Dr. Lisa Lix 1 Introduction Human Cases of WNV in Canada 2002-2007 Human Diagnosis and Clinical ManifestationSystem Dynamic (SD) Modeling Mosquito and Human WNV Disease Progression PHC 1, 2, 3, 4, 6 Decision Tree Analysis PHC 2, 3, 6 Relevant Public Health Competencies (PHC) Contact information Karen Yee, MPH Candidate School of Public Health. Health Sciences Building 107 Wiggins Road. University of Saskatchewan Saskatoon, SK. S7N 5E5; Email: karen.yee@usask.ca karen.yee@usask.ca Summary School of Public Health, University of Saskatchewan 1 Department of Computer Science, University of Saskatchewan 2 Saskatoon Public Health Observatory, Public Health Services, Saskatoon Health Region 3 Source: Penn State University Organizes decisions/actions into a logical tree structure taking into account uncertainties and consequences. Consequences (outcomes) can be derived from running the SD model on particular scenarios of decisions that are made when faced with uncertainty. Backward induction will enable the decision maker to identify the optimal decision rules to bring about the most desired outcome. Takes into consideration present and historical uncertainties (e.g., temperature) SD modeling is a computer tool used to understand complex issues and problems often associated with many causal forces that create the problem or positively/negatively contribute to it. Takes into account delays (e.g., time from contact to symptoms of a disease), interactions (e.g., chronic diseases with infectious diseases), feedbacks (e.g., behavioral changes from altered risk perceptions), nonlinear relationships (e.g., risk, costs), and heterogeneities (e.g., differences in infection rates between sexes) SD models are not about forecasting the future, but rather on how actions in the present can trigger plausible reactions over time New insights (e.g., on clinical disease progression of WNV) and changing conditions (e.g., weather patterns) or goals (e.g., target host for vaccination) are incorporated into SD models Computer simulation showing the proportion of humans hospitalized for meningitis and encephalitis as the infectious mosquito density is raised 3 (red line) and 6 fold (blue line) from baseline (green line). Key Public Health of Canada Competencies addressed during the WNV portion of this project with Saskatoon Public Health Observatory, Public Health Services SHR & Dr. Nathaniel Osgood include: 1.0 Public Health Sciences; 2.0 Assessment and Analysis 3.0 Policy and Program Planning, Implementation and Evaluation; 4.0 Partnerships, Collaboration and Advocacy 6.0 Communication Saskatchewan suffered the highest incidence of WNV in the country in 2003 and 2007 Saskatoon Health Region (SHR) reported 6.5% and 25% of the provincial cases in 2003 and 2007, respectively Source: PHAC, 2006 West Nile Virus (WNV) belongs to a group of disease-causing viruses called flaviviruses, which include yellow fever, Japanese encephalitis and dengue Found in both tropic and temperate regions Two genetic lineages:  lineage 1 strains are found in North America, Europe, Africa, Asia, and Australia; Can lead to severe inflammation of spinal cord (meningitis) and/or brain (encephalitis).  lineage 2 strains have been isolated only in sub-Saharan Africa and Madagascar. Little severe human disease. WNV Transmission Cycle WNV Control Planning PHC 3, 4, 6 WNV control in Saskatchewan: Integrative pest management (IPM) approach  larval source reduction  surveillance and monitoring of larval vector species  public messages about increasing disease transmission, and personal protective equipment (e.g., use of DEET repellent, wearing long sleeves, and avoiding outdoor activities at dusk/dawn).  use of ultra-low volume (ULV) malathion spraying for the control of adult mosquitoes (adulticiding) as last resort. WNV sensitivity registry feasibility study : involved collecting information on sensitivity registries and telephone information lines for SHR to assist them in making informed decisions on the usefulness of each for fulfill the obligation to protect the public’s health in the context of adult mosquito control programs. Source: www.azstarnet.com/metro/295104www.azstarnet.com/metro/295104 Source: www.comosquitocontrol.com/www.comosquitocontrol.com/ Mosquito_Biology.html Source: unknown This project provides: multiple stakeholders with useful information & computer tools for understanding the dynamics of WNV ability to use current and historic uncertainty to make informed decisions on optimal intervention measures for improved health outcomes. an in-depth review of sensitivity registries and telephone information lines for informing the public regarding adulticiding should it ever be necessary to control for WNV amalgamated mosquito trap data from 2003-present in a format suitable for easy communication of health risk to the public WNV Surveillance & Risk Communication PHC 2, 3, 4, 6 This research was kindly supported by the Research Alliance for the Prevention of Infectious Disease (RAPID) Network created through a grant from the Saskatchewan Heath Research Foundation Mosquito Adult Mosquito Pupa Mosquito Larvae Birds : Passive - specimens turned in by public to Canadian Cooperative Wildlife Health Centre are tested for WNV Mosquitoes : Larval testing  presence & geographic location of Culex tarsalis mosquito (this species of primary concern in Saskatchewan for transmission of WNV) Adult trapping  presence of C. tarsalis in proportion to other mosquito species Pool testing  testing batches of Culex mosquitoes for WNV Environment : Growing degree days  the # of days the average nightly temperature above 15°C, ideal for mosquito breeding; 300-350 GDD enough heat accumulation for 4 to 5 generations of mosquitoes over the summer Horses : Passive - veterinary reports Humans : Active - physician reporting (reportable disease) Incubation period of WNV is believed to range from 3 to 14 days 80% of WNV infections asymptomatic > 95% symptomatic infections are non-neurological (e.g., West Nile Fever) < 1% symptomatic infections are neurological (e.g. meningitis and/or encephalitis) Highest risk of transmission to humans when: 1) WNV in birds; 2) WNV in C. tarsalis ; 3) increase in average # C. tarsalis / trap night; 4) % C. tarsalis high relative to other mosquito species Risk communication include weekly average # C. tarsalis, minimum infection rate, maximum likelihood estimate, & risk index provided to SHR weekly from province. Part of this project involved amalgamating 2003-present data relevant for SHR into a single database for easy public messaging & surveillance.