Systematic Review and Evaluation of Mathematical Attack Models of Human Inhalational Anthrax for Supporting Public Health Decision Making and Response. Issue 4 (4th August 2020)

• Record Type: Journal Article
• Authors: Chen, Xin; Bahl, Prateek; de Silva, Charitha; Heslop, David; Doolan, Con; Lim, Samsung; MacIntyre, C. Raina
• Is Part Of: Prehospital and disaster medicine. Volume 35:Issue 4(2020)
• Page Start: 412
• Page End: 419
• Publication Date: 2020-08-04
• Subjects: anthrax, -- biological warfare agents, -- bioterrorism, -- inhalation anthrax, -- mathematical models; Emergency medical services -- Periodicals; Emergency medicine -- Periodicals; Disaster medicine -- Periodicals; 616.025
• DOI: 10.1017/S1049023X20000734
• Languages: English
• ISSNs: 1049-023X

Abstract

Abstract: Background: 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. Methods: 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. Results: 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. Conclusion: 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.