Understanding the circumstances and conditions surrounding disaster‐attributed deaths may contribute to designing and implementing emergency preparedness and response programmes. This paper introduces a three‐step cluster analysis of multiple binary variables to investigate mortality patterns related to tropical cyclones. It is designed to overcome the difficulties of performing cluster analysis in a disaster database that is composed in part of nominal variables and is unavoidably incomplete owing to missing information. The first step in the process codes all variables as binary data in order to accommodate the nominal variables. The second step calculates Spearman's rank correlation coefficients for pairs of variables. And the third step subjects the correlation coefficients to cluster analysis. Data related to 1,575 deaths attributed to tropical cyclones (also known as typhoons) that struck Taiwan between 2000 and 2015 are used to illustrate the method. The results yield two distinct groups of variables that are worthy of further exploration. 相似文献
Objectives: The objective of this study was to evaluate and injury surveillance (IS) system’s ability to monitor road traffic deaths and the coverage of road traffic injury and death surveillance in Phuket, Thailand.
Methods: U.S. Centers for Disease Control and Prevention guidelines on surveillance system evaluation were used to qualitatively and quantitatively evaluate IS. Interviews with key stakeholders focused on IS’s usefulness, simplicity, flexibility, acceptability, and stability. Active case finding of 2014 road traffic deaths in all paper and electronic hospital record systems was used to assess system sensitivity, positive predictive value, and data quality. Electronic data matching software was used to determine the implications of combining IS data with other provincial-level data sources (e.g., death certificates, electronic vehicle insurance claim system).
Results: Evaluation results indicated that IS was useful, flexible, acceptable, and stable, with a high positive predictive value (99%). Simplicity was limited due to the burden of collecting data on all injuries and use of paper-based data collection forms. Sensitivity was low, with IS only identifying 55% of hospital road traffic death cases identified during active case finding; however, IS cases were representative of cases identified. Data accuracy and completeness varied across data fields. Combining IS with active case finding, death certificates, and the electronic vehicle insurance claim system more than doubled the number of road traffic death cases identified in Phuket.
Conclusion: An efficient and comprehensive road traffic injury and death surveillance system is critical for monitoring Phuket’s road traffic burden. The hospital-based IS system is a useful system for monitoring road traffic deaths and assessing risk behaviors. However, the complexity of data collection and limited coverage hinders the ability of IS to fully represent road traffic deaths in Phuket Province. Combining data sources could improve coverage and should be considered. 相似文献