Optimal response against bioterror attack on airport terminal

• Published in: European journal of operational research Vol. 219; no. 2; pp. 415 - 424
• Main Authors: Berman, Oded, Gavious, Arieh, Menezes, Mozart B.C.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.06.2012; Elsevier; Elsevier Sequoia S.A
• Subjects: Airports; Allocations; Applied sciences; Biological & chemical terrorism; Biological and medical sciences; Bioterror; Decision making models; Economy. Management; Emergencies; Epidemics; Epidemiology; Exact sciences and technology; Firm modelling; General aspects; Governments; Health and social institutions; Mathematical programming; Medical sciences; Operational research and scientific management; Operational research. Management science; Optimization; OR in health services; OR in medicine; Parameter estimation; Penalty methods; Public health. Hygiene; Public health. Hygiene-occupational medicine; Resource allocation; Studies; Terminals; Transportation terminals; Vaccines; OR in medicine; Penalty methods; Bioterror; OR in health services; Resource allocation; Parameter estimation; Vaccination; Epidemiology; Modeling; Penalty method; Optimal allocation; Cost function; System identification; Human resource management; Epidemic; Human capital; Terrorism; Aggression; Government; Hospital management; Staff management; Bioterrorism; Terminal; Medicine; Airport; Emergency
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/j.ejor.2011.12.036

► We considered a potential bioterror attack on an airport with subsequent resource allocation. ► The problem of minimizing the expected number of deaths and its min–max counterpart is addressed. ► Marginal analysis algorithms can solve the problem given estimates of the total number of initially infected passengers. ► It is presented a case study using data from the Long Beach Airport and twelve departing flights. ► We showed that the use of myopic policies could be very inefficient. We consider a potential bioterror attack on an airport. After the attack is identified, the government is faced with the problem of how to allocate limited emergency resources (human resources, vaccines, etc.) efficiently. The government is assumed to make a one-time resource allocation decision. The optimal allocation problem is discussed and it is shown how available information on the number of infected passengers can be incorporated into the model. Estimation for parameters of the cost function (number of deaths after the epidemic is over) is provided based on known epidemic models. The models proposed in the paper are demonstrated with a case study using real airport data.