Skip to content


  • Opinion
  • Open Access
  • Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Simulations for designing and interpreting intervention trials in infectious diseases

  • 1, 2Email authorView ORCID ID profile,
  • 3,
  • 4,
  • 5,
  • 6,
  • 7,
  • 8,
  • 9,
  • 2,
  • 10,
  • 11,
  • 12,
  • 9,
  • 13,
  • 14,
  • 15, 16,
  • 17,
  • 18, 19 and
  • 14
BMC Medicine201715:223

Received: 10 October 2017

Accepted: 5 December 2017

Published: 29 December 2017

Back to article

Open Peer Review reports

Pre-publication versions of this article are available by contacting

Original Submission
10 Oct 2017 Submitted Original manuscript
31 Oct 2017 Reviewed Reviewer Report - Thomas Churcher
6 Nov 2017 Reviewed Reviewer Report - Martial Ndeffo Mbah
9 Nov 2017 Author responded Author comments - M Elizabeth Halloran
Resubmission - Version 2
9 Nov 2017 Submitted Manuscript version 2
5 Dec 2017 Editorially accepted
29 Dec 2017 Article published 10.1186/s12916-017-0985-3

How does Open Peer Review work?

Open peer review is a system where authors know who the reviewers are, and the reviewers know who the authors are. If the manuscript is accepted, the named reviewer reports are published alongside the article. Pre-publication versions of the article are available by contacting

You can find further information about the peer review system here.

Authors’ Affiliations

Vaccine and Infectious Disease Division, Fred Hutchinson Research Center, Seattle, USA
Department of Biostatistics, School of Public Health, University of Washington, Seattle, USA
Department of Mathematics and Statistics, University of Turku, Turku, Finland
Department of Global Health, Milken Institute School of Public Health, The George Washington University, Washington DC, USA
Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, USA
Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, USA
Department of Biostatistics, The Fielding School of Public Health, UCLA, Los Angeles, USA
Mahidol Oxford Tropical Medicine Research Unit, Bangkok, Thailand
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, USA
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
Paul G. Allen School for Global Animal Health, Washington State University, Pullman, USA
Department of Biostatistics, University of Florida, Gainesville, USA
Development Research Group, The World Bank, Washington DC, USA
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, USA
Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Basel, Switzerland
University of Basel, Basel, Switzerland
Network Science Institute, Northeastern University, Boston, USA
Modelling and Economics Unit, Public Health England, Colindale, UK
TB Modelling Group, Centre for Mathematical Modelling of Infectious Diseases, TB Centre and Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK