- Abstract:
-
Background
Interventions in infectious diseases can have both direct effects on individuals who receive the intervention as well as indirect effects in the population. In addition, intervention combinations can have complex interactions at the population level, which are often difficult to adequately assess with standard study designs and analytical methods.
Discussion
Herein, we urge the adoption of a new paradigm for the design and interpretation of intervention...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Publisher's version
- Files:
-
-
(pdf, 580.9kb)
-
- Publisher copy:
- 10.1186/s12916-017-0985-3
-
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- Publisher:
- BioMed Central Publisher's website
- Journal:
- BMC Medicine Journal website
- Volume:
- 15
- Issue:
- 1
- Pages:
- 223
- Publication date:
- 2017-12-29
- Acceptance date:
- 2017-12-05
- DOI:
- EISSN:
-
1741-7015
- ISSN:
-
1741-7015
- Pubs id:
-
pubs:817185
- URN:
-
uri:3f0b1d1e-8495-4489-872c-c8cfc76ce5b4
- UUID:
-
uuid:3f0b1d1e-8495-4489-872c-c8cfc76ce5b4
- Local pid:
- pubs:817185
- Language:
- English
- Keywords:
- Copyright holder:
- Cooper et al
- Copyright date:
- 2017
- Notes:
- © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- License:
- CC BY
Journal article
Simulations for designing and interpreting intervention trials in infectious diseases
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