1,753 research outputs found
Discrete versus continuous domain models for disease mapping
The main goal of disease mapping is to estimate disease risk and identify
high-risk areas. Such analyses are hampered by the limited geographical
resolution of the available data. Typically the available data are counts per
spatial unit and the common approach is the Besag--York--Molli{\'e} (BYM)
model. When precise geocodes are available, it is more natural to use
Log-Gaussian Cox processes (LGCPs). In a simulation study mimicking childhood
leukaemia incidence using actual residential locations of all children in the
canton of Z\"urich, Switzerland, we compare the ability of these models to
recover risk surfaces and identify high-risk areas. We then apply both
approaches to actual data on childhood leukaemia incidence in the canton of
Z\"urich during 1985-2015. We found that LGCPs outperform BYM models in almost
all scenarios considered. Our findings suggest that there are important gains
to be made from the use of LGCPs in spatial epidemiology.Comment: 28 pages, 4 figures, 2 Table
Economic Analysis and Statistical Disclosure Limitation
This paper explores the consequences for economic research of methods used by data publishers to protect the privacy of their respondents. We review the concept of statistical disclosure limitation for an audience of economists who may be unfamiliar with these methods. We characterize what it means for statistical disclosure limitation to be ignorable. When it is not ignorable, we consider the effects of statistical disclosure limitation for a variety of research designs common in applied economic research. Because statistical agencies do not always report the methods they use to protect confidentiality, we also characterize settings in which statistical disclosure limitation methods are discoverable; that is, they can be learned from the released data. We conclude with advice for researchers, journal editors, and statistical agencies
Confidentiality considerations for use of social-spatial data on the social determinants of health: Sexual and reproductive health case study
Understanding whether and how the places where people live, work, and play are associated with health behaviors and health is essential to understanding the social determinants of health. However, social-spatial data which link a person and their attributes to a geographic location (e.g., home address) create potential confidentiality risks. Despite the growing body of literature describing approaches to protect individual confidentiality when utilizing social-spatial data, peer-reviewed manuscripts displaying identifiable individual point data or quasi-identifiers (attributes associated with the individual or disease that narrow identification) in maps persist, suggesting that knowledge has not been effectively translated into public health research practices. Using sexual and reproductive health as a case study, we explore the extent to which maps appearing in recent peer-reviewed publications risk participant confidentiality. Our scoping review of sexual and reproductive health literature published and indexed in PubMed between January 1, 2013 and September 1, 2015 identified 45 manuscripts displaying participant data in maps as points or small-population geographic units, spanning 26 journals and representing studies conducted in 20 countries. Notably, 56% (13/23) of publications presenting point data on maps either did not describe approaches used to mask data or masked data inadequately. Furthermore, 18% (4/22) of publications displaying data using small-population geographic units included at least two quasi-identifiers. These findings highlight the need for heightened education for researchers, reviewers, and editorial teams. We aim to provide readers with a primer on key confidentiality considerations when utilizing linked social-spatial data for visualizing results. Given the widespread availability of place-based data and the ease of creating maps, it is critically important to raise awareness on when social-spatial data constitute protected health information, best practices for masking geographic identifiers, and methods of balancing disclosure risk and scientific utility. We conclude with recommendations to support the preservation of confidentiality when disseminating results
Monitoring fisheries within the Reef 2050 Integrated Monitoring and Reporting Program: final report of the fisheries expert group
This report provides a suite of recommendations for monitoring fishery systems as part of the Reef 2050 Integrated Monitoring and Reporting Program (RIMReP). These recommendations were based on a desktop analysis of peer-reviewed literature, technical reports and other scientific publications, expert knowledge and advice from members of the various RIMReP Expert Groups and outcomes from a series of workshops and meetings
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