Epidemiological Studies Based on Small Sample Sizes – A Statistician's Point of View

<p/> <p>We consider 3 basic steps in a study, which have relevance for the statistical analysis. They are: study design, data quality, and statistical analysis. While statistical analysis is often considered an important issue in the literature and the choice of statistical method receives much attention, less emphasis seems to be put on study design and necessary sample sizes. Finally, a very important step, namely assessment and validation of the quality of the data collected seems to be completely overlooked.</p> <p>Examples from veterinary epidemiological research and recommendations for each step are given together with relevant references to the literature.</p

Spatial pattern in prevalence of paratuberculosis infection diagnosed with misclassification in Danish dairy herds in 2009 and 2013

AbstractParatuberculosis is a chronic infection of economic importance to the dairy industry. The infection may be latent for years, which makes diagnostic misclassification a general challenge. The objective of this study was to identify the spatial pattern in infection prevalence, when results were adjusted for covariate information and diagnostic misclassification. Furthermore, we compared the estimated spatial pattern with the spatial pattern obtained without adjustment for misclassification. The study included 1242 herds in 2009 and 979 herds in 2013. The within-herd prevalence was modelled using a hierarchical logistic regression model and included a spatial component modelled by a continuous Gaussian field. The Stochastic Partial Differential Equation (SPDE) approach and Integrated Nested Laplace Approximation (INLA) were used for Bayesian inference. We found a significant spatial component, and our results suggested that the estimated range of influence and the overall location of areas with increased prevalence are not very sensitive to diagnostic misclassification

Norovirus epidemiology in community and health care settings and association with patient age, denmark

Norovirus (NoV) is a major cause of gastroenteritis. NoV genotype II.4 (GII.4) is the predominant genotype in health care settings but the reason for this finding is unknown. Stool samples containing isolates with a known NoV genotype from 2,109 patients in Denmark (patients consulting a general practitioner or outpatient clinic, inpatients, and patients from foodborne outbreaks) were used to determine genotype distribution in relation to age and setting. NoV GII.4 was more prevalent among inpatients than among patients in community settings or those who became infected during foodborne outbreaks. In community and health care settings, we found an association between infection with GII.4 and increasing age. Norovirus GII.4 predominated in patients ≥ 60 years of age and in health care settings. A larger proportion of children than adults were infected with NoV GII.3 or GII.P21. Susceptibility to NoV infection might depend on patient age and infecting NoV genotype. Cohort studies are warranted to test this hypothesis

Joint mapping of cardiovascular diseases:comparing the geographic patterns in incident acute myocardial infarction, stroke and atrial fibrillation, a Danish register-based cohort study 2014–15

BACKGROUND: Disease mapping aims at identifying geographic patterns in disease. This may provide a better understanding of disease aetiology and risk factors as well as enable targeted prevention and allocation of resources. Joint mapping of multiple diseases may lead to improved insights since e.g. similarities and differences between geographic patterns may reflect shared and disease-specific determinants of disease. The objective of this study was to compare the geographic patterns in incident acute myocardial infarction (AMI), stroke and atrial fibrillation (AF) using the unique, population-based Danish register data. METHODS: Incident AMI, stroke and AF was modelled by a multivariate Poisson model including a disease-specific random effect of municipality modelled by a multivariate conditionally autoregressive (MCAR) structure. Analyses were adjusted for age, sex and income. RESULTS: The study included 3.5 million adults contributing 6.8 million person-years. In total, 18,349 incident cases of AMI, 28,006 incident cases of stroke, and 39,040 incident cases of AF occurred. Estimated municipality-specific standardized incidence rates ranged from 0.76 to 1.35 for AMI, from 0.79 to 1.38 for stroke, and from 0.85 to 1.24 for AF. In all diseases, geographic variation with clusters of high or low risk of disease after adjustment was seen. The geographic patterns displayed overall similarities between the diseases, with stroke and AF having the strongest resemblances. The most notable difference was observed in Copenhagen (high risk of stroke and AF, low risk of AMI). AF showed the least geographic variation. CONCLUSION: Using multiple-disease mapping, this study adds to the results of previous studies by enabling joint evaluation and comparison of the geographic patterns in AMI, stroke and AF. The simultaneous mapping of diseases displayed similarities and differences in occurrence that are non-assessable in traditional single-disease mapping studies. In addition to reflecting the fact that AF is a strong risk factor for stroke, the results suggested that AMI, stroke and AF share some, but not all environmental risk factors after accounting for age, sex and income (indicator of lifestyle and health behaviour). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12942-021-00294-w