Biomedical subjects

Susanne Dahms

Publications and source records attributed to Susanne Dahms.

4 recordsLinked to original sources

PubMedDate not supplied

[Epidemiological model development using BSE as an example--observations from a statistical viewpoint].

Since first BSE cases in cattle born in Germany were recognized, questions have been raised concerning the future development of the disease and the epidemiological dynamics of BSE, and, consequently, modelling approaches that might answer these questions. The database for such modelling efforts is formed by BSE incidence numbers or incidence rates, broken down by age at onset of clinical disease, and by time of onset or time of birth, respectively, from available information gathered for suspect and confirmed BSE cases. To describe such data, statistical age-period-cohort-models and two epidemiologically/biologically oriented modelling approaches are discussed: the so-called three-factor-model used by the Central Veterinary Laboratory of the British Ministry for Agriculture, Fisheries and Food (MAFF) (now Department of the Environment and Rural Affairs (DEFRA)), and a back-calculation-model developed by a working group at the University of Oxford. Resulting model calculations are supposed to serve several purposes, including a prediction of future BSE incidence numbers, and, especially based on the "Oxford"-model, a back-calculation of the epidemic of BSE infections from the epidemic of clinically diseased BSE cases. Analysis of these approaches reveals some problems even to identify unique age, period, or birth cohort effects. An additional estimation of epidemiological components of BSE, for example the frequency distribution of incubation times, has to rely on further assumptions that cannot be validated by the model fit as such. Therefore, modelling results should be interpreted with caution. However, the limitations demonstrated by this discussion emphasize the need for specific studies to investigate certain aspects of the BSE epidemic, for example the distribution of times from infection to disease onset, and for the centralised collection of valid and detailed population data for cattle.

Age Factors↗

PubMedDate not supplied

[Prevalence of herd specific factors and limb disorders, and their associations in intensive swine production].

A longitudinal observational study in 180 pig breeding herds was performed to calculate prevalences of herd specific factors as well as typical limb disorders and to estimate their associations in a 2-step regression analysis. Regarding herd size, genetics, feeding and weight gain herds were distributed almost equal. The population density and the hygiene status were considered proper in most herds. In the farrowing units partially slatted floors of metal or plastic with slats > 9 mm, in the weaning units fully slatted floors of plastic, and in the rearing units fully slatted floors of concrete were most common. Less than 6% of the farms housed their pigs on solid concrete with straw bedding. Herd prevalences of fault floors varied between 18 and 43%. As a herd health problem (morbidity > 25%) claw hematomas and limb abrasions in just 1-week old piglets, overgrown claws and bursa swellings in weaned pigs, and bursa swellings in rearing pigs were wide spread. Leg deformations by osteopathy or arthritis occurred only sporadically. In the risk analysis claw hematomas of piglets were associated with slatted floors, particulary with slats < 10 mm. Abrasions were associated with concrete and rough floor surfaces at all. Overgrown claws and bursa swellings in weaned and in rearing pigs were associated with damaged, slippery or rough floor surfaces. Other associations were not detected. The quality of floor might be more important than the type of housing.

Animal Husbandry↗

PubMedDate not supplied

[Sampling plans and microbiological criteria as risk management options in recently developed food safety concerns].

In connection with the World Trade Organization SPS-Agreement new concepts for ensuring food safety have been discussed for some years now. Main topics have been quantitative risk analyses investigating relationships between microbial concentrations in foods and disease probabilities as well as the concept of food safety objectives developed by ICMSF. So far food safety demands have been defined as microbiological criteria. However, usually it is not transparent, whether sampling plans incorporated in such criteria are based on specific prescriptions with regard to decision reliability and tolerable food qualities. In addition, it is still to be discussed, which parts microbiological criteria can play in connection with new concepts of food risk management, for instance as an option to test whether food safety objectives are met or not. The performance of microbiological sampling plans, as visualized by operation characteristic curves, assumptions made in this context, and relationships between food safety objectives and microbiological criteria as well as implications for food safety issues are investigated in this paper.

Colony Count, Microbial↗

PubMedDate not supplied

[Dose-response-models and their implications for quantitative risk assessment for Campylobacter infections].

For some time now there have been several projects dealing with the assessment of campylobacteriosis risks for consumers. Dose-response relationships form a crucial part of such assessments, as they specify disease probabilities depending on different microbial concentrations in foods. Evaluation of such models, however, is difficult because of problems to find data on which reliable assumptions could be based. Ongoing risk analyses for Campylobacter mainly refer to a single administration study with human volunteers published by Black et al. (1988). However, whether results from this study can be transferred to target populations envisaged in risk assessments remains questionable for several reasons. In this paper some alternative dose-response models, their fit to the data of Black et al., and risk estimates resulting in a fictitious scenario are discussed and compared. Depending on the dose-response model assumed risk estimates can differ remarkably. Therefore it is hardly possible to make reliable quantifications of risks in reality, however, it can be determined how much they may vary assuming different scenarios.

Animals↗