PubMed · 10605200
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M Mäkelä, H Varonen, J Teperi. 1996. [Systematic review].. https://pubmed.ncbi.nlm.nih.gov/10605200/
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In 1948, the WHO proposed that five countries, Norway among them, should study the incidence of cancer. Three years later the Norwegian Ministry of Health and Social Affairs issued instructions for the reporting of all cases of cancer to the new Cancer Registry of Norway. Its first director was Dr. Einar Pedersen, who was succeeded by Dr. Frøydis Langmark in 1983. Between 1957-61 and 1992-96, the number of cancer cases increased from 41,648 to 99,601. Most types of cancer were up; stomach cancer was an exception to this trend. The increase was highest for malignant melanoma and lung cancer, for both types higher among women than among men. There are considerable variations in cancer incidence between Norwegian counties, between the municipalities within the counties, and between urban and rural communities.
A model for the spread of an infection is analyzed for different population structures. The interactions within the population are described by small world networks, ranging from ordered lattices to random graphs. For the more ordered systems, there is a fluctuating endemic state of low infection. At a finite value of the disorder of the network, we find a transition to self-sustained oscillations in the size of the infected subpopulation.
Meta-analysis is a quantitative method available to epidemiologists, psychologists, social scientists and others who wish to produce a summary measure of the effect of exposure on disease, based on results from published studies along with a summary measure of uncertainty. The magnitude of the effect vary from study to study because of differences in the features of these studies (design, population, control of confounding variables etc.). From the various studies an estimator is formed by pooling the results found in each study in one summary measure. This summary (or pooled) measure is meaningful only if the magnitude of heterogeneity between study effects is small and can be explained by sampling variation. In this paper, we present HEpiMA, a new comprehensive and user-friendly software program for epidemiologic meta-analysis. HEpiMA has new features that are not available in other programs. The program carries out a complete study of heterogeneity of study effects with 11 hypothesis test results. In addition to model-based methods, the program also implements bootstrap methodology. New useful estimators of heterogeneity, Ri and CV(B), developed by the authors are given in the output. In addition to these unique features, the major advantage of this software is the option for direct entry of adjusted relative risk estimates of individual studies, the most common form of presentation of results in the epidemiologic literature. This program may also be useful for meta-analysts of clinical trials, in which the relative risk is the parameter of interest as it also allows the entry of crude data under the form of 2x2 tables.