A review of Cyclospora cayetanensis in animals

Cyclosporiasis is a global, emerging disease in humans caused by Cyclospora cayetanensis. The role of animals in the epidemiology of cyclosporiasis is not fully understood. We conducted a narrative review of the published literature on C. cayetanensis in animals. MEDLINE® (Web of Science™ ), Agricola (ProQuest), CABI Global Health (1979 to December 2020) and Food Science and Technology Abstracts (EBSCOhost) (1979 to February 2020) were searched. Studies of C. cayetanensis in or on any species of animal were eligible. Thirteen relevant studies were found. C. cayetanensis was found in wild and farmed Mediterranean mussels (Mytilus galloprovincialis), wild grooved carpet shell clams (Ruditapes decussatus) and in the faeces of dogs (domestic and street), wild chickens, wild rhesus macaques (Macaca mulatta), chimpanzees (Pan troglodytes) from a wildlife research centre, and Cynomolgus monkeys (Macaca fascicularis) from an experimental primate research centre. As the small intestines of the naturally exposed animals were not biopsied, existence of a natural animal reservoir of C. cayetanensis could not be confirmed. Animals shedding oocysts in their faeces may be paratenic hosts. Investigators were able to successfully infect the following animals with C. cayetanensis: oysters, Asian freshwater clams (Corbicula fluminea), Swiss albino mice and guinea pigs. Future non-laboratory studies of animals should use PCR coupled with DNA sequencing to confirm that the species found is C. cayetanensis. The potential role of animals in the transport of oocysts and contamination of food, water, and soil could be explored through future primary research.

Odds Ratio or Prevalence Ratio? An Overview of Reported Statistical Methods and Appropriateness of Interpretations in Cross-sectional Studies with Dichotomous Outcomes in Veterinary Medicine

One of the most commonly observational study designs employed in veterinary is the cross-sectional study with binary outcomes. To measure an association with exposure, the use of prevalence ratios (PR) or odds ratios (OR) are possible. In human epidemiology, much has been discussed about the use of the OR exclusively for case–control studies and some authors reported that there is no good justification for fitting logistic regression when the prevalence of the disease is high, in which OR overestimate the PR. Nonetheless, interpretation of OR is difficult since confusing between risk and odds can lead to incorrect quantitative interpretation of data such as “the risk is X times greater,” commonly reported in studies that use OR. The aims of this study were (1) to review articles with cross-sectional designs to assess the statistical method used and the appropriateness of the interpretation of the estimated measure of association and (2) to illustrate the use of alternative statistical methods that estimate PR directly. An overview of statistical methods and its interpretation using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted and included a diverse set of peer-reviewed journals among the veterinary science field using PubMed as the search engine. From each article, the statistical method used and the appropriateness of the interpretation of the estimated measure of association were registered. Additionally, four alternative models for logistic regression that estimate directly PR were tested using our own dataset from a cross-sectional study on bovine viral diarrhea virus. The initial search strategy found 62 articles, in which 6 articles were excluded and therefore 56 studies were used for the overall analysis. The review showed that independent of the level of prevalence reported, 96% of articles employed logistic regression, thus estimating the OR. Results of the multivariate models indicated that logistic regression was the method that most overestimated the PR. The findings of this study indicate that although there are methods that directly estimate PR, many studies in veterinary science do not use these methods and misinterpret the OR estimated by the logistic regression.