Hostname: page-component-546b4f848f-hhr79 Total loading time: 0 Render date: 2023-06-03T06:55:08.949Z Has data issue: false Feature Flags: { "useRatesEcommerce": true } hasContentIssue false

Systematic Review and Evaluation of Mathematical Attack Models of Human Inhalational Anthrax for Supporting Public Health Decision Making and Response

Published online by Cambridge University Press:  04 June 2020

Xin Chen*
Biosecurity Program, The Kirby Institute, UNSW Sydney, NSW, Australia
Prateek Bahl
School of Mechanical and Manufacturing Engineering, UNSW Sydney, NSW, Australia
Charitha de Silva
School of Mechanical and Manufacturing Engineering, UNSW Sydney, NSW, Australia
David Heslop
School of Public Health and Community Medicine, UNSW Sydney, NSW, Australia
Con Doolan
School of Mechanical and Manufacturing Engineering, UNSW Sydney, NSW, Australia
Samsung Lim
School of Civil and Environmental Engineering, UNSW Sydney, NSW, Australia
C. Raina MacIntyre
Biosecurity Program, The Kirby Institute, UNSW Sydney, NSW, Australia College of Health Solutions and College of Public Service and Community Solutions, Arizona State University, Tempe, ArizonaUSA
Correspondence: Xin Chen, MPH, Biosecurity Program, Kirby Institute, Level 6, Wallace Wurth Building, UNSW Sydney, NSW, 2052, Australia, E-mail:



Anthrax is a potential biological weapon and can be used in an air-borne or mail attack, such as in the attack in the United States in 2001. Planning for such an event requires the best available science. Since large-scale experiments are not feasible, mathematical modelling is a crucial tool to inform planning. The aim of this study is to systematically review and evaluate the approaches to mathematical modelling of inhalational anthrax attack to support public health decision making and response.


A systematic review of inhalational anthrax attack models was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. The models were reviewed based on a set of defined criteria, including the inclusion of atmospheric dispersion component and capacity for real-time decision support.


Of 13 mathematical modelling studies of human inhalational anthrax attacks, there were six studies that took atmospheric dispersion of anthrax spores into account. Further, only two modelling studies had potential utility for real-time decision support, and only one model was validated using real data.


The limited modelling studies available use widely varying methods, assumptions, and data. Estimation of attack size using different models may be quite different, and is likely to be under-estimated by models which do not consider weather conditions. Validation with available data is crucial and may improve models. Further, there is a need for both complex models that can provide accurate atmospheric dispersion modelling, as well as for simpler modelling tools that provide real-time decision support for epidemic response.

Systematic Review
© World Association for Disaster and Emergency Medicine 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)


Center for Disease Control and Prevention (CDC). Bioterrorism Agents/Diseases. Accessed March 11, 2016.Google Scholar
Toth, DJ, Gundlapalli, AV, Schell, WA, et al.Quantitative models of the dose-response and time course of inhalational anthrax in humans. PLoS Pathog. 2013;9(8):e1003555.CrossRefGoogle ScholarPubMed
Inglesby, TV, O’Toole, T, Henderson, DA, et al.Anthrax as a biological weapon, 2002: updated recommendations for management. JAMA. 2002;287(17):22362252.CrossRefGoogle ScholarPubMed
Friedlander, AM, Grabenstein, JD, Brachman, PS.11 - Anthrax Vaccines.” In: Plotkin, SA, Orenstein, WA, Offit, PA, Edwards, KM, (eds). Plotkin’s Vaccines (Seventh Edition). Amsterdam, The Netherlands: Elsevier; 2018:134-148.e137.Google Scholar
Meselson, M, Guillemin, J, Hugh-Jones, M, et al.The Sverdlovsk anthrax outbreak of 1979. Science. 1994;266(5188):12021208.CrossRefGoogle ScholarPubMed
Jernigan, DB, Raghunathan, PL, Bell, BP, et al.Investigation of bioterrorism-related anthrax, United States, 2001: epidemiologic findings. Emerg Infect Dis. 2002;8(10):1019.CrossRefGoogle ScholarPubMed
Bresnitz, EA, DiFerdinando, GT.Lessons from the anthrax attacks of 2001 The New Jersey experience. Clinics in Occupational and Environmental Medicine. 2002;2(2):227252.CrossRefGoogle Scholar
Moher, D, Liberati, A, Tetzlaff, J, Altman, DG; Prisma Group. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.CrossRefGoogle ScholarPubMed
Braithwaite, RS, Fridsma, D, Roberts, MS.The cost-effectiveness of strategies to reduce mortality from an intentional release of aerosolized anthrax spores. Med Decis Making. 2006;26(2):182193.CrossRefGoogle ScholarPubMed
Carley, KM, Fridsma, DB, Casman, E, et al.BioWar: scalable agent-based model of bio attacks. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans. 2006;36(2):252265.CrossRefGoogle Scholar
Ho, J, Duncan, S.Estimating aerosol hazards from an anthrax letter. Journal of Aerosol Science. 2005;36(5-6):701719.CrossRefGoogle Scholar
Isukapalli, SS, Lioy, PJ, Georgopoulos, PG.Mechanistic modeling of emergency events: assessing the impact of hypothetical releases of anthrax. Risk Anal. 2008;28(3):723740.CrossRefGoogle ScholarPubMed
Legrand, J, Egan, JR, Hall, IM, Cauchemez, S, Leach, S, Ferguson, NM.Estimating the location and spatial extent of a covert anthrax release. PLoS Computat Biol. 2009;5(1):e1000356.CrossRefGoogle ScholarPubMed
Nicogossian, A, Schintler, LA, Boybeyi, Z.Modeling urban atmospheric anthrax spore’s dispersion: Assessment of health impacts and policy implications. World Medical & Health Policy. 2011;3(3):116.Google Scholar
Nordin, JD, Goodman, MJ, Kulldorff, M, et al.Simulated anthrax attacks and syndromic surveillance. Emerg Infect Dis. 2005;11(9):13941398.CrossRefGoogle ScholarPubMed
Rainisch, G, Meltzer, MI, Shadomy, S, Bower, WA, Hupert, N.Modeling tool for decision support during early days of an anthrax event. Emerg Infect Dis. 2017;23(1):46.CrossRefGoogle ScholarPubMed
Reshetin, VP, Regens, JL.Simulation modeling of anthrax spore dispersion in a bioterrorism incident. Risk Anal. 2003;23(6):11351145.CrossRefGoogle Scholar
Walden, J, Kaplan, EH.Estimating time and size of bioterror attack. Emerg Infect Dis. 2004;10(7):1202.CrossRefGoogle ScholarPubMed
Webb, GF, Blaser, MJ.Mail-borne transmission of anthrax: modeling and implications. Proceedings of the National Academy of Sciences. 2002;99(10):70277032.CrossRefGoogle Scholar
Wein, LM, Craft, DL.Evaluation of public health interventions for anthrax: a report to the secretary’s council on public health preparedness. Biosecur Bioterror. 2005;3(4):348356.CrossRefGoogle ScholarPubMed
Wein, LM, Craft, DL, Kaplan, EH.Emergency response to an anthrax attack. Proc Natl Acad Sci USA. 2003;100(7):43464351.CrossRefGoogle Scholar
Reshetin, V, Regens, D.Evaluation of malignant anthrax spore dispersion in high-rise buildings. Journal of Engineering Physics and Thermophysics. 2004;77(6):11551166.CrossRefGoogle Scholar
Heslop, DJ, Chughtai, AA, Bui, CM, MacIntyre, CR.Publicly available software tools for decision-makers during an emergent epidemic—systematic evaluation of utility and usability. Epidemics. 2017;21:112.CrossRefGoogle ScholarPubMed
Army, US. A study of the vulnerability of subway passengers in New York City to covert action with biological agents. Miscellaneous Publication. 1968;25.Google Scholar
Bresnitz, EA, Ziskin, LZ.An epidemiologist’s view of bioterrorism. N J Med. 2004;101(9 Suppl):26-31: quiz 32-33.Google ScholarPubMed