FACTORS INFLUENCING GLOBAL FMD REPORTING AND RISK Rebecca Garabed, Wes Johnson, Andrés Perez and Mark Thurmond Center for Animal Disease Modeling and Surveillance University of California, Davis, U.S.A.
Background Global FMD surveillance and reporting Current knowledge about FMD risk 8 36 3 8 5 2 2 7 9 3 6 2
Background The need for standardized risk measures for: transmission models planning for control and eradication measuring progress identifying unpredicted risk and lack of risk Need to know why knowledge is so disparate
Objectives Create a statistical model that will predict homogeneously the FMD risk around the world using available data. Use the model to identify factors associated with FMD reporting or lack of reporting in different geographic regions.
Conclusions and Recommendations Factors influencing FMD risk and FMD reporting are different and vary by geographic region. Predicted targets for intervention: Africa education, political voice and accountability, geographic coverage of surveillance programs Americas and Australia regional inertia Europe and Middle East education, funding for reporting, and seasonal consistency in surveillance Asia surveillance before animal movement and border control
Methods Bayesian logistic regression FMD im ~ Bernoulli (r im ) logit(r im ) = log(ρ s ) + x im β + z jy θ Model varies by region Uses expert opinion and occurrence data Fit twice. Predicts true FMD risk 2. Predicts risk of reported FMD Model internally validated
Predicted Risk of FMD for January 998 True FMD Risk Reported FMD Risk
Selected Factors Different Between True and Reported FMD (increases risk, decreases risk) Africa True: bovine density, voice and accountability, prior FMD status positive, literacy rate, GPD Reported: human density, voice and accountability, prior FMD status not free, land border length, distance from case last month Americas and Australia True: bovine density, positive and not-free borders, prior not-free or positive FMD status Reported: pig density, pig meat deficit, land border length, distance to case last year
Selected Factors Different Between True and Reported FMD (increases risk, decreases risk) FMD Europe and Middle East True: small ruminant density, human density, water borders, literacy rate, female literacy rate Reported: small ruminant density, human density, bovine meat deficit, distance to case one year ago, border length, political stability, GDP Asia True: pig density, border length, Eid, literacy rate, prior FMD status positive Reported: small ruminant density, buffalo density, human density, sheep and goat meat deficit, border length, Eid, distance to case one year ago
Summary Conclusions Africa - improved political voice and education might decrease FMD risk and improve reporting. Reporting was limited by access to animals and surveillance was related to specific outbreaks. Americas and Australia regional inertia and incentive to control FMD in export cattle seemed to drive true FMD risk, while reporting of FMD was better in areas with high density of pigs. Surveillance seemed to be consistent throughout the year.
Summary Conclusions Europe and Middle East control programs in areas with high density of small ruminants appeared to be effective. Improved education and funding for FMD reporting might improve FMD risk. Surveillance appeared to be seasonal. Asia areas with swine were important for disease risk, while disease was more likely to be recognized in areas with buffalo. Places that imported meat were more likely to report FMD and surveillance appeared to be seasonal. Border control might improve reporting and disease control.
Thank you Audience and Organizers Collaborators staff at the UC Davis FMD Lab. Experts Funding provided by The National Center for Medical Intelligence and UC Davis School of Veterinary Medicine
Current Address Department of Veterinary Preventive Medicine The Ohio State University 920 Coffey Road Columbus, OH 4320 USA