Wild birds often harbor infectious microorganisms. Some of these infectious microorganisms may present a risk to domestic animals and humans through spillover events. Detections of certain microorganisms have been shown to increase host susceptibility to infections by other microorganisms, leading to coinfections and altered host-to-host transmission patterns. However, little is known about the frequency of coinfections and its impact on wild bird populations. In order to verify whether avian influenza virus (AIV) natural infection in wild waterbirds was related to the excretion of other microorganisms, 73 AIV-positive samples (feces and cloacal swabs) were coupled with 73 AIV-negative samples of the same sampling characteristics and tested by real-time PCR specific for the following microorganisms: West Nile virus, avian avulavirus 1, Salmonella spp., Yersinia enterocolitica, Yersinia pseudotuberculosis, Mycobacterium avium subspecies, Mycobacterium tuberculosis complex, and Mycobacterium spp. Concurrent detections were found in 47.9% (35/73) of the AIV-positive samples and in 23.3% (17/73) of the AIV-negative samples (P = 0.003). Mycobacterium spp. and Salmonella spp. were found to be significantly more prevalent among the AIV-positive samples than among the AIV-negative samples (42.9% vs. 22.8%; P = 0.024 and 15.2% vs. 0.0%; P = 0.0015, respectively). Prevalence of concurrent detections differed significantly among sampling years (P = 0.001), host families (P = 0.002), host species (P = 0.003), AIV subtypes (P = 0.003), and type of sample (P = 0.009). Multiple concurrent detections (more than one of the tested microorganisms excluding AIV) were found in 9.6% (7/73) of all the AIV-positive samples, accounting for 20% (7/35) of the concurrent detection cases. In contrast, in AIV-negative samples we never detected more than one of the selected microorganisms. These results show that AIV detection was associated with the detection of the monitored microorganisms. Further studies of a larger field sample set or under experimental conditions are necessary to infer causality in these trends.