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Title: | Disease mapping method comparing the spatial distribution of a disease with a control disease | Authors: | PETROF, Oana NEYENS, Thomas VRANCKX, Maren Nuyts, Valerie Nemery, Benoit Nackaerts, Kristiaan FAES, Christel |
Issue Date: | 2022 | Publisher: | WILEY | Source: | Biometrical journal, 64 (4) , p. 733-757 | Abstract: | Small-area methods are being used in spatial epidemiology to understand the effect of location on health and detect areas where the risk of a disease is significantly elevated. Disease mapping models relate the observed number of cases to an expected number of cases per area. Expected numbers are often calculated by internal standardization, which requires both accurate population numbers and disease rates per gender and/or age group. However, confidentiality issues or the absence of high-quality information about the characteristics of a population-at-risk can hamper those calculations. Based on methods in point process analysis for situations without accurate population data, we propose the use of a case-control approach in the context of lattice data, in which an unrelated, spatially unstructured disease is used as a control disease. We correct for the uncertainty in the estimation of the expected values, which arises by using the control-disease's observed number of cases as a representation of a fraction of the total population. We apply our methods to a Belgian study of mesothelioma risk, where pancreatic cancer serves as the control disease. The analysis results are in close agreement with those coming from traditional disease mapping models based on internally standardized expected counts. The simulation study results confirm our findings for different spatial structures. We show that the proposed method can adequately address the problem of inaccurate or unavailable population data in disease mapping analysis. | Notes: | Petrof, O (corresponding author), Hasselt Univ, Data Sci Inst, I BioStat, Martelarenlaan 42, B-3500 Hasselt, Belgium. oana.petrof@uhasselt.be |
Keywords: | BYM model;case-control study;disease mapping;mesothelioma;standardization | Document URI: | http://hdl.handle.net/1942/36807 | ISSN: | 0323-3847 | e-ISSN: | 1521-4036 | DOI: | 10.1002/bimj.202000246 | ISI #: | 000753889800001 | Rights: | 2022 Wiley-VCH GmbH This article has earned an Open Data badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available in the Supporting Information section. This article has earned an open data badge “Reproducible Research” for making publicly available the code necessary to reproduce the reported results. The results reported in this article are partially reproducible due to data confidentiality issues. | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2023 |
Appears in Collections: | Research publications |
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