Should the Government Be Allowed to Take Control over Your Car as Part of a Disaster Management Plan?

Yipeng Lv, Zafar Zafari, Boshen Jiao, Casey Chun, Lulu Zhang, Zhaoxin Wang and Peter Alexander Muennig
Additional contact information
Yipeng Lv: The Department of Social Medicine and Health Service Management, School of Medicine, Shanghai Jiaotong University, Shanghai 200025, China
Zafar Zafari: Global Research Analytics for Population Health (GRAPH), Mailman School of Public Health, Columbia University, New York, NY 10027, USA
Boshen Jiao: Global Research Analytics for Population Health (GRAPH), Mailman School of Public Health, Columbia University, New York, NY 10027, USA
Casey Chun: Global Research Analytics for Population Health (GRAPH), Mailman School of Public Health, Columbia University, New York, NY 10027, USA
Lulu Zhang: The Department of Military Health Service Management, College of Military Health Service Management, Second Military Medical University, Shanghai 200433, China
Zhaoxin Wang: The Department of Social Medicine and Health Service Management, School of Medicine, Shanghai Jiaotong University, Shanghai 200025, China
Peter Alexander Muennig: Global Research Analytics for Population Health (GRAPH), Mailman School of Public Health, Columbia University, New York, NY 10027, USA

IJERPH, 2020, vol. 17, issue 21, 1-10

Abstract: Introduction: With the Safety Ensuring Lives Future Deployment and Research in Vehicle Evolution (SELF DRIVE) Act in the United States, there is a growing interest in autonomous vehicles (AVs). One avenue of innovation would be to use them to mobilize and coordinate response efforts during natural disasters. This study uses an earthquake response in an urban, developed setting as a hypothetical example case study. In this hypothetical scenario, private AVs would be mobilized to help rescue victims from collapsed structures. Methods: A Markov model compared an intervention arm with AVs to a status quo arm using a hypothetical cohort of American earthquake victims. The three possible health states were trapped but alive, rescued and alive, and dead. The cycle length of the Markov model was 6 h. Results: The cost of deploying AVs was $90,139 relative to $87,869 in status quo arm. Using AVs produced an incremental cost of $2269 (95% credible interval (CI) = $−12,985–$8959). Victims have 7.33 quality-adjusted life years (QALYs) in the intervention arm compared to 7.20 QALYs in the status quo arm, resulting in an incremental gain of 0.13 (95% CI = −0.73–2.19) QALYs. The incremental cost-effectiveness ratio (ICER) was $16,960/QALY gained (95% CI = cost-saving–$69,065/QALY). Discussion: The mobilization of private AVs in the setting of an earthquake has the potential to save money and reduce the loss of life. AVs may advance emergency management competencies.

Keywords: autonomous vehicles; disaster management; earthquake emergency rescue; risk reduction (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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