The Global control of FMD - Tools, ideas and ideals – Erice, Italy 14-17 October 2008
Appendix 61
FACTORS INFLUENCING GLOBAL FMD REPORTING AND RISK R. Garabed1, 2*, W. Johnson3, A. Perez1, 4 and M. Thurmond1 1
Center for Animal Disease Modeling and Surveillance, School of Veterinary Medicine, University of California, One Shields Avenue, Davis, CA 95616, USA 2 Present Address: Department of Veterinary Preventive Medicine, The Ohio State University, A100G Sisson Hall, 1920 Coffey Rd, Columbus, OH 43210, USA 3 Department of Statistics, Donald Bren School of Information and Computer Sciences, University of California Irvine, Bren Hall 2019, Irvine, CA 92697, USA 4 CONICET and Facultad de Ciencias Veterinarias UNR, Ov. Lagos y Ruta 33, Casilda, 2170, Argentina
ABSTRACT The quality of FMD surveillance and reporting varies globally and over time. Though information about FMD risk varies, harmonious measures are needed for active surveillance programs and development of global disease transmission models. As an alternative to the use of small regional studies and expert opinion estimates, we present models that use available and incomplete data to predict global risk and explore factors related to FMD risk and reporting. Our global models are used to predict true FMD risk and to compare the prediction to reported FMD risk. Maps of the models’ two FMD risk estimates represent differences in perceived FMD risk based on reporting. Traits associated with both FMD reporting and FMD presence varied by geographic region and might provide unconventional targets for intervention. The different prediction model formulae suggest traits of countries and local areas that might contribute to differences in FMD reporting and presence. 1. INTRODUCTION As is evident in regional FMD situation updates published by FAO EMPRES and EUFMD (2007) and in incidence reports voluntarily submitted to OIE (2008), the quality of FMD surveillance and reporting varies globally and over time. Because information about FMD risk varies, harmonious measures are needed for active surveillance programs. Knowing the number of expected cases in an area is critical for planning surveillance sampling and vaccination. In addition, consistent measures of baseline risk are necessary to develop global transmission models and to measure the progress of control programs. To derive consistent estimates in the face of inconsistent reporting, designers of vaccination and surveillance programs and developers of trade policy have necessarily 1) asked ‘experts’ to make recommendations extrapolated from their knowledge (Wint and Sumption, 2005), 2) had researchers collect data on FMD risk in small regions, or 3) assumed a worst-case scenario (ECHCP, 2007). Though the second technique (collecting data) is the most accurate method, time, expense, international politics, privacy issues, and possible danger to research teams argue against global use of this method. Techniques one and three can be sufficient for trade purposes, but their accuracy may be insufficient for active global surveillance and disease eradication. As an alternative, we present models that use available and incomplete data to provide a standardized approach to predicting global risk. In addition, these models have been used to explore for factors related to FMD risk and reporting. 2. METHODS The global case-control models were fit using expert opinion, data on FMD presence and absence, and publically available predictor data. The population at risk for FMD in each month in these
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