Detection, identification, and correction of a bias in an epidemiological study.

The relative lack of epidemiological studies of natural populations is partly due to the difficulty of obtaining samples that are both large enough and representative of the population. Here, we present the result of an epidemiological study (December 1992-August 1995) of feline immunodeficiency virus (FIV) in a free-roaming population of domestic cats (Felis catus), with a special emphasis on sample bias. Over five trapping periods, the prevalence of FIV in sampled cats steadily declined. Across these samples we consistently achieved a very large sampling fraction (approximately 60% of the population), the sex ratio, age and weight distributions remained stable with time in the samples, and the sex ratio was similar in the samples and the population. These indices would normally indicate that our samples were representative, suggesting the decline in FIV prevalence to be real. However, a concomitant ecological study of the whole population revealed an important bias in the samples, with an initial high probability of capturing a few individuals, which appeared significantly more likely to be FIV-infected, and then a lower probability of recapturing them. Since our protocol resulted in a non-random sampling, subsequent trappings were designed to avoid this bias, by also capturing individuals who had previously learned to escape capture. This modified capture regime revealed that FIV prevalence was in fact constant in the population. This study shows how samples of large size, which are stable and appear representative of the population, can still be biased. These results may have major implications for other studies based on trapping.