Literature DB >> 22195067

Simulation Analysis Platform (SnAP): a tool for evaluation of public health surveillance and disease control strategies.

David L Buckeridge1, Christian Jauvin, Anya Okhmatovskaia, Aman D Verma.   

Abstract

Increasingly, researchers use simulation to generate realistic population health data to evaluate surveillance and disease control methods. This evaluation approach is attractive because real data are often not available to describe the full range of population health trajectories that may occur. Simulation models, especially agent-based models, tend to have many parameters and it is often difficult for researchers to evaluate the effect of the multiple parameter values on model outcomes. In this paper, we describe Simulation Analysis Platform (SnAP) - a software infrastructure for automatically deploying and analyzing multiple runs of a simulation model in a manner that efficiently explores the influence of parameter uncertainty and random error on model outcomes. SnAP is designed to be efficient, scalable, extensible, and portable. We describe the design decisions taken to meet these requirements, present the design of the platform, and describe results from an example application of SnAP.

Mesh:

Year:  2011        PMID: 22195067      PMCID: PMC3243283     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  15 in total

1.  Statewide system of electronic notifiable disease reporting from clinical laboratories: comparing automated reporting with conventional methods.

Authors:  P Effler; M Ching-Lee; A Bogard; M C Ieong; T Nekomoto; D Jernigan
Journal:  JAMA       Date:  1999-11-17       Impact factor: 56.272

2.  Infectious disease outbreaks related to drinking water in Canada, 1974-2001.

Authors:  Corinne J Schuster; Andrea G Ellis; William J Robertson; Dominique F Charron; Jeff J Aramini; Barbara J Marshall; Diane T Medeiros
Journal:  Can J Public Health       Date:  2005 Jul-Aug

Review 3.  Outbreak detection through automated surveillance: a review of the determinants of detection.

Authors:  David L Buckeridge
Journal:  J Biomed Inform       Date:  2006-10-05       Impact factor: 6.317

4.  Cryptosporidiosis surveillance and water-borne outbreaks in Europe.

Authors:  J C Semenza; G Nichols
Journal:  Euro Surveill       Date:  2007-05-01

5.  A comparison of the completeness and timeliness of automated electronic laboratory reporting and spontaneous reporting of notifiable conditions.

Authors:  J Marc Overhage; Shaun Grannis; Clement J McDonald
Journal:  Am J Public Health       Date:  2008-01-02       Impact factor: 9.308

6.  A simulation model of waterborne gastro-intestinal disease outbreaks: description and initial evaluation.

Authors:  Anya Okhmatovskaia; Aman D Verma; Benoit Barbeau; Annie Carriere; Romain Pasquet; David L Buckeridge
Journal:  AMIA Annu Symp Proc       Date:  2010-11-13

7.  A large outbreak of campylobacteriosis associated with a municipal water supply in Finland.

Authors:  M Kuusi; J P Nuorti; M L Hänninen; M Koskela; V Jussila; E Kela; I Miettinen; P Ruutu
Journal:  Epidemiol Infect       Date:  2005-08       Impact factor: 2.451

8.  Gastroenteritis: a waterborne outbreak affecting 1600 people in a small Danish town.

Authors:  E Laursen; O Mygind; B Rasmussen; T Rønne
Journal:  J Epidemiol Community Health       Date:  1994-10       Impact factor: 3.710

9.  Implementing syndromic surveillance: a practical guide informed by the early experience.

Authors:  Kenneth D Mandl; J Marc Overhage; Michael M Wagner; William B Lober; Paola Sebastiani; Farzad Mostashari; Julie A Pavlin; Per H Gesteland; Tracee Treadwell; Eileen Koski; Lori Hutwagner; David L Buckeridge; Raymond D Aller; Shaun Grannis
Journal:  J Am Med Inform Assoc       Date:  2003-11-21       Impact factor: 4.497

Review 10.  Evaluation of reporting timeliness of public health surveillance systems for infectious diseases.

Authors:  Ruth Ann Jajosky; Samuel L Groseclose
Journal:  BMC Public Health       Date:  2004-07-26       Impact factor: 3.295

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  4 in total

1.  Using hierarchical mixture of experts model for fusion of outbreak detection methods.

Authors:  Nastaran Jafarpour; Doina Precup; Masoumeh Izadi; David Buckeridge
Journal:  AMIA Annu Symp Proc       Date:  2013-11-16

2.  Lessons from a decade of individual-based models for infectious disease transmission: a systematic review (2006-2015).

Authors:  Lander Willem; Frederik Verelst; Joke Bilcke; Niel Hens; Philippe Beutels
Journal:  BMC Infect Dis       Date:  2017-09-11       Impact factor: 3.090

3.  Waterborne Disease Outbreak Detection: A Simulation-Based Study.

Authors:  Damien Mouly; Sarah Goria; Michael Mounié; Pascal Beaudeau; Catherine Galey; Anne Gallay; Christian Ducrot; Yann Le Strat
Journal:  Int J Environ Res Public Health       Date:  2018-07-17       Impact factor: 3.390

4.  The use of mixture density networks in the emulation of complex epidemiological individual-based models.

Authors:  Christopher N Davis; T Deirdre Hollingsworth; Quentin Caudron; Michael A Irvine
Journal:  PLoS Comput Biol       Date:  2020-03-16       Impact factor: 4.475

  4 in total

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