title: A review of back-calculation techniques  and their potential to inform mitigation  strategies with application to  non-transmissible acute infectious  diseases.
abstract: Back-calculation is a process whereby generally unobservable features of an event leading to a disease outbreak can be inferred either in real-time or shortly after the end of the outbreak. These features might include the time when persons were exposed and the source of the outbreak. Such inferences are important as they can help to guide the targeting of mitigation strategies and to evaluate the potential effectiveness of such strategies. This article reviews the process of back-calculation with a particular emphasis on more recent applications concerning deliberate and naturally occurring aerosolized releases. The techniques can be broadly split into two themes: the simpler temporal models and the more sophisticated spatio-temporal models. The former require input data in the form of cases' symptom onset times, whereas the latter require additional spatial information such as the cases' home and work locations. A key aspect in the back-calculation process is the incubation period distribution, which forms the initial topic for consideration. Links between atmospheric dispersion modelling, within-host dynamics and back-calculation are outlined in detail. An example of how back-calculation can inform mitigation strategies completes the review by providing improved estimates of the duration of antibiotic prophylaxis that would be required in the response to an inhalational anthrax outbreak.
authors.forename: Joseph R
authors.initials: JR
authors.lastname: Egan
authors.forename: Ian M
authors.initials: IM
authors.lastname: Hall
mesh_terms: D000818:Animals; D003140:Communicable Disease Control / Q000379:methods* / Q000706:statistics & numerical data*; D003141:Communicable Diseases / Q000453:epidemiology* / Q000635:transmission; D003198:Computer Simulation; D004196:Disease Outbreaks / Q000517:prevention & control* / Q000706:statistics & numerical data*; D005240:Feasibility Studies; D006801:Humans; D015994:Incidence; D015233:Models, Statistical; D011159:Population Surveillance / Q000379:methods; D018570:Risk Assessment / Q000379:methods; D062211:Spatio-Temporal Analysis