Search is a time-critical event: When search and rescue missions may become futile

被引:40
|
作者
Adams, Annette L.
Schmidt, Terri A.
Newgard, Craig D.
Federiuk, Carol S.
Christie, Michael
Scorvo, Sean
DeFreest, Melissa
机构
[1] Oregon Hlth & Sci Univ, Ctr Policy & Res Emergency Med, Portland, OR 97239 USA
[2] Oregon Hlth & Sci Univ, Ctr Policy & Res Emergency Med, Dept Emergency Med, Portland, OR USA
[3] Oregon Hlth & Sci Univ, Ctr Policy & Res Emergency Med, Dept Publ Hlth & Prevent Med, Portland, OR USA
[4] Corvallis Clin, Corvallis, OR USA
[5] Stanford Univ, Dept Surg, Div Emergency Med, Palo Alto, CA 94304 USA
关键词
search and rescue; EMS; wilderness medicine; classification and regression tree;
D O I
10.1580/06-WEME-OR-035R1.1
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Objectives.-The purpose of this study was to derive and validate a rule for duration of search (ie, search time) that maximizes survivors and after which a search and rescue (SAR) mission may be considered for termination. Methods.-This was a retrospective cohort study of all SAR missions initiated in Oregon over a 7-year period, which were documented in a population-based administrative database. The following types of search missions were excluded from analysis: redundant reports of a single search; lost helicopters and airplanes: support of organized events; law-enforcement searches; searches for persons actively avoiding rescued body recovery missions; and cases without outcome information. The cohort was divided into a derivation cohort (searches from 1997-2000) and a validation cohort (2001-2003). The primary Outcome was survival. Variables considered in the model included age, gender, minimum and maximum daily temperatures, precipitation, search time, and whether the search involved an air or water incident. Missing data were handled using Multiple imputation. Classification and regression tree (CART) methods were used to derive the model. Results.-The derivation cohort included 1040 searches involving 1509 victims, 70 (4.6%) of whom died. The validation cohort included 1262 searches involving 1778 victims; 115 (6.5%) died. Search time was the only variable retained in the final model, with a cut-point of 51 hours. The derivation model was 98.9% sensitive; the same model run using the validation cohort was 99.3% sensitive. Conclusions.-This time-based model may aid search managers in the decision about starting a search or changing search tactics for missing persons.
引用
收藏
页码:95 / 101
页数:7
相关论文
共 50 条
  • [31] Cyborg cockroach could help in search-and-rescue missions
    Wilkins, Alex
    NEW SCIENTIST, 2023, 246 (3457) : 13 - 13
  • [32] LSAR: Multi-UAV Collaboration for Search and Rescue Missions
    Alotaibi, Ebtehal Turki
    Alqefari, Shahad Saleh
    Koubaa, Anis
    IEEE ACCESS, 2019, 7 : 55817 - 55832
  • [33] Human body detection and geolocalization for UAV search and rescue missions
    Rudol, Piotr
    Doherty, Patrick
    2008 IEEE AEROSPACE CONFERENCE, VOLS 1-9, 2008, : 3171 - 3178
  • [34] Hindering Search and Rescue Missions with Selective Wireless Jamming Attacks
    Koushyar, Javad Mokhtari
    Guirguis, Mina
    Atia, George
    2024 IEEE CONFERENCE ON COGNITIVE AND COMPUTATIONAL ASPECTS OF SITUATION MANAGEMENT, COGSIMA, 2024, : 24 - 30
  • [35] Effective Learning Algorithms for Search and Rescue Missions in Unknown Environments
    Roudneshin, Masoud
    Sizkouhi, Amir Mohammad Moradi
    Aghdam, Amir G.
    2019 IEEE 7TH INTERNATIONAL CONFERENCE ON WIRELESS FOR SPACE AND EXTREME ENVIRONMENTS (WISEE 2019), 2019, : 76 - 80
  • [36] Distilling Support Opportunities to Improve Urban Search and Rescue Missions
    de Greet, Tjerk
    Oomes, A. H. J.
    Neerincx, Mark A.
    HUMAN-COMPUTER INTERACTION, PT IV: INTERACTING IN VARIOUS APPLICATION DOMAINS, 2009, 5613 : 703 - 712
  • [37] Multi-robot Task Allocation for Search and Rescue Missions
    Hussein, Ahmed
    Adel, Mohamed
    Bakr, Mohamed
    Shehata, Omar M.
    Khamis, Alaa
    EUROPEAN WORKSHOP ON ADVANCED CONTROL AND DIAGNOSIS, PTS 1-8, 2014, 570
  • [38] Autonomous Transportation and Deployment with Aerial Robots for Search and Rescue Missions
    Bernard, Markus
    Kondak, Konstantin
    Maza, Ivan
    Ollero, Anibal
    JOURNAL OF FIELD ROBOTICS, 2011, 28 (06) : 914 - 931
  • [39] Underwater target detection with hyperspectral imagery for search and rescue missions
    Eken, Isa Cem
    Cetin, Yasemin Yardimci
    ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XXIV, 2018, 10644
  • [40] An adaptive middleware for supporting time-critical event response
    Zhu, Qian
    Agrawal, Gagan
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2009, 12 (01): : 87 - 100