The pitfalls of field trials in fish vaccinology

Field trials are essential for accurately assessing the worth of a vaccine under actual conditions of use. Compared with the laboratory, the dynamics of the host, pathogen, and environment in a production setting can produce both subtle and dramatic differences on the performance of the vaccine and the immune response. Because of this, field trials are conducted by manufacturers in vaccine development and are required by many national regulatory agencies to evaluate safety and/or efficacy before granting vaccine licenses. Aquaculture producers, veterinarians and fish health professionals can use field trials to analyse the cost-benefit of a vaccination programme for a facility, or to compare competitive products. Vaccine field trials are more than merely using the products in the field. Small efficacy effects can result in considerable cost reductions to the fish farmer. Proper field trial design, conduct and analysis is critical to detecting these effects. However, field trials are also fraught with many pitfalls that can result in failure or misleading conclusions. The discussion regarding possible pitfalls of vaccine field trials in aquaculture is divided into two parts: 1) the art and 2) the science of successful field trials. The art of successful field trials involves dealing with the "people" aspect which is necessary for initial and continuing compliance. Meticulous planning is essential, including a written protocol to which everyone agrees by signature. The bottom line to the art of field trials is anticipation and discussion of all possible eventualities together with constant communication with the farmer and site supervisor. The science of successful fields trials involves anticipating and realizing the logistical and statistical difficulties in design and implementation. Problems often encountered are: lack of stated quantifiable purpose; low power of the test due to inherent small sample size, large variation and small margin of effect; lack of estimate for anticipated results in controls and unpredictable challenges; non-blinding design with bias and unequal treatment; one or few measures of outcome; lack of redundancy in sites selected; poor statistical design and analysis with violation of assumptions; herd effects; inability to assess long-term effects through several production cycles; and manufacturer/producer expense.