Pathogenic paths? A time geographical approach in medical geography
Sammanfattning: Medical geography usually attempts to disentangle and explain the ecological and causal contexts of health, disease and environment by mapping spatial patterns of cases and potential pathogenic factors. However, many diseases are believed to show after long periods of latency , spanning years and even decades between initial exposure and clinical onset. In view of high spatial human mobility - in terms of migration, commuting and occasional travelling - and environmental change, the actual spatial patterns of cases may be erroneous, due to a time-space lag effect. This assumption calls for an adequate methodology, by which a higher degree of spatial and temporal precision can be achieved. It is suggested in the thesis that time geography could provide the necessary intellectual framework for such an approach. A selection of epidemiological situations are presented in time geographical terms. The concept of an epidemiological landscape is introduced and elaborated in time geographical concepts. Empirical data for testing the approach have been provided by the Department for Community and Preventive Medicine in Linköping, Sweden. As a background to the test, the population dynamics of one Swedish county (Östergötland) are analyzed, based on individual data. The first test concerns a group of 29 ALS (amyotrophic lateral sclerosis) cases which were registered in the municipality of Linköping during the 1980s. The second example focuses some 60 leukaemia patients who were resident in Linköping when their disease was diagnosed during the latter years of the 1980s. The life paths of the patients have been traced and documented step by step from the date and place of birth until the onset of disease. Thus, it has been demonstrated that a substantial number of the patients have migrated from near or far to the place where they happened to live at the time of onset. These results evoke new questions concerning the adequate spatial and temporal views for epidemiological purposes. They also direct attention to the white spots of the epidemiological landscape , i.e. information gaps caused by time-space lag. Conceivably, the results could serve as starting points for further research, which may involve not only geography but also genetics and geneaology.
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