Literature DB >> 12828240

Extending backcalculation to analyse BSE data.

C A Donnelly1, N M Ferguson, A C Ghani, R M Anderson.   

Abstract

We review the origins of backcalculation (or back projection) methods developed for the analysis of AIDS (acquired immunodeficiency syndrome) incidence data. These techniques have been used extensively for >15 years to deconvolute clinical case incidence, given knowledge of the incubation period distribution, to obtain estimates of past HIV (human immunodeficiency virus) infection incidence and short-term predictions of future AIDS incidence. Adaptations required for the analysis of bovine spongiform encephalopathy (BSE) incidence included: stratification of BSE incidence by age as well as birth cohort; allowance for incomplete survival between infection and the onset of clinical signs of disease; and decomposition of the age- and time-related infection incidence into a time-dependent feed risk component and an age-dependent exposure/susceptibility function. The most recent methodological developments focus on the incorporation of data from clinically unaffected cattle screened using recently developed tests for preclinical BSE infection. Backcalculation-based predictions of future BSE incidence obtained since 1996 are examined. Finally, future directions of epidemiological analysis of BSE epidemics are discussed taking into account ongoing developments in the science of BSE and possible changes in BSE-related policies.

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Year:  2003        PMID: 12828240     DOI: 10.1191/0962280203sm337ra

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  6 in total

Review 1.  A review of back-calculation techniques and their potential to inform mitigation strategies with application to non-transmissible acute infectious diseases.

Authors:  Joseph R Egan; Ian M Hall
Journal:  J R Soc Interface       Date:  2015-05-06       Impact factor: 4.118

Review 2.  Tooling-up for infectious disease transmission modelling.

Authors:  Marc Baguelin; Graham F Medley; Emily S Nightingale; Kathleen M O'Reilly; Eleanor M Rees; Naomi R Waterlow; Moritz Wagner
Journal:  Epidemics       Date:  2020-05-13       Impact factor: 4.396

3.  Near real-time surveillance of the SARS-CoV-2 epidemic with incomplete data.

Authors:  P M De Salazar; F Lu; J A Hay; D Gómez-Barroso; P Fernández-Navarro; E Martínez; J Astray-Mochales; R Amillategui; A García-Fulgueiras; M D Chirlaque; A Sánchez-Migallón; A Larrauri; M J Sierra; M Lipsitch; F Simón; M Santillana; M A Hernán
Journal:  medRxiv       Date:  2021-01-26

4.  Near real-time surveillance of the SARS-CoV-2 epidemic with incomplete data.

Authors:  Pablo M De Salazar; Fred Lu; James A Hay; Diana Gómez-Barroso; Pablo Fernández-Navarro; Elena V Martínez; Jenaro Astray-Mochales; Rocío Amillategui; Ana García-Fulgueiras; Maria D Chirlaque; Alonso Sánchez-Migallón; Amparo Larrauri; María J Sierra; Marc Lipsitch; Fernando Simón; Mauricio Santillana; Miguel A Hernán
Journal:  PLoS Comput Biol       Date:  2022-03-31       Impact factor: 4.475

5.  Host culling as an adaptive management tool for chronic wasting disease in white-tailed deer: a modelling study.

Authors:  Gideon Wasserberg; Erik E Osnas; Robert E Rolley; Michael D Samuel
Journal:  J Appl Ecol       Date:  2009-04       Impact factor: 6.528

6.  Early efforts in modeling the incubation period of infectious diseases with an acute course of illness.

Authors:  Hiroshi Nishiura
Journal:  Emerg Themes Epidemiol       Date:  2007-05-11
  6 in total

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