Species-specific and Indication-based Use of Antimicrobials in Dogs, Cats, Cattle and Horses in Finland : Data collected using three different methods

Increasing antimicrobial resistance in bacteria has led to the need for better understanding of antimicrobial usage patterns. In 1999, the World Organisation for Animal Health (OIE) recommended that an international ad hoc group should be established to address human and animal health risks related to antimicrobial resistance and the contribution of antimicrobial usage in veterinary medicine. In European countries the need for continuous recording of the usage of veterinary antimicrobials as well as for animal species-specific and indication-based data on usage has been acknowledged. Finland has been among the first countries to develop prudent use guidelines in veterinary medicine, as the Ministry of Agriculture and Forestry issued the first animal species-specific indication-based recommendations for antimicrobial use in animals in 1996. These guidelines have been revised in 2003 and 2009. However, surveillance on the species-specific use of antimicrobials in animals has not been performed in Finland. This thesis provides animal species-specific information on indication-based antimicrobial usage. Different methods for data collection have been utilized. Information on antimicrobial usage in animals has been gathered in four studies (studies A-D). Material from studies A, B and C have been used in an overlapping manner in the original publications I-IV. Study A (original publications I & IV) presents a retrospective cross-sectional survey on prescriptions for small animals at the Veterinary Teaching Hospital of the University of Helsinki. Prescriptions for antimicrobial agents (n = 2281) were collected and usage patterns, such as the indication and length of treatment, were reviewed. Most of the prescriptions were for dogs (78%), and primarily for the treatment of skin and ear infections most of which were treated with cephalexin for a median period of 14 days. Prescriptions for cats (18%) were most often for the treatment of urinary tract infections with amoxicillin for a median length of 10 days. Study B (original publication II) was a retrospective cross-sectional survey where prescriptions for animals were collected from 17 University Pharmacies nationwide. Antimicrobial prescriptions (n = 1038) for mainly dogs (65%) and cats (19%) were investigated. In this study, cephalexin and amoxicillin were also the most frequently used drugs for dogs and cats, respectively. In study C (original publications III & IV), the indication-based usage of antimicrobials of practicing veterinarians was analyzed by using a prospective questionnaire. Randomly selected practicing veterinarians in Finland (n = 262) recorded all their antimicrobial usage during a 7-day study period. Cattle (46%) with mastitis were the most common patients receiving antimicrobial treatment, generally intramuscular penicillin G or intramammary treatment with ampicillin and cloxacillin. The median length of treatment was four days, regardless of the route of administration. Antimicrobial use in horses was evaluated in study D, the results of which are previously unpublished. Firstly, data collected with the prospective questionnaire from the practicing veterinarians showed that horses (n = 89) were frequently treated for skin or wound infections by using penicillin G or trimethoprim-sulfadiazine. The mean duration of treatment was five to seven days. Secondly, according to retrospective data collected from patient records, horses (n = 74) that underwent colic surgery at the Veterinary Teaching Hospital of the University of Helsinki were generally treated according to national and hospital recommendations; penicillin G and gentamicin was administered preoperatively and treatment was continued for a median of three days postoperatively. In conclusion, Finnish veterinarians followed well the national prudent use guidelines. Narrow-spectrum antimicrobials were preferred and, for instance, fluoroquinolones were used sparingly. Prescription studies seemed to give good information on antimicrobials usage, especially when combined with complementary information from patient records. A prospective questionnaire study provided a fair amount of valuable data on several animal species. Electronic surveys are worthwhile exploiting in the future.

Bayesian Inference for Retrospective Population Genetics Models Using Markov Chain Monte Carlo Methods

Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.