Cluster randomized test-negative design (CR-TND) trials: a novel and efficient method to assess the efficacy of community level dengue interventions

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Title: Cluster randomized test-negative design (CR-TND) trials: a novel and efficient method to assess the efficacy of community level dengue interventions
Authors: Anders, K
Cutcher, Z
Kleinschmidt, I
Donnelly, CA
Ferguson, NM
Indriani, C
O'Neill, SL
Jewell, NP
Simmons, CP
Item Type: Journal Article
Abstract: Cluster randomized trials are the gold standard for assessing efficacy of community-level interventions, such as vector control strategies against dengue. We describe a novel cluster randomized trial methodology with a test-negative design, which offers advantages over traditional approaches. It utilizes outcome-based sampling of patients presenting with a syndrome consistent with the disease of interest, who are subsequently classified as test-positive cases or test-negative controls on the basis of diagnostic testing. We use simulations of a cluster trial to demonstrate validity of efficacy estimates under the test-negative approach. This demonstrates that, provided study arms are balanced for both test-negative and test-positive illness at baseline and that other test-negative design assumptions are met, the efficacy estimates closely match true efficacy. We also briefly discuss analytical considerations for an odds ratio-based effect estimate arising from clustered data, and outline potential approaches to analysis. We conclude that application of the test-negative design to certain cluster randomized trials could increase their efficiency and ease of implementation.
Issue Date: 7-May-2018
Date of Acceptance: 27-Apr-2018
ISSN: 1476-6256
Publisher: Oxford University Press (OUP)
Journal / Book Title: American Journal of Epidemiology
Copyright Statement: © The Author(s) 2018. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Sponsor/Funder: Medical Research Council (MRC)
Bill & Melinda Gates Foundation
National Institute for Health Research
Funder's Grant Number: MR/K010174/1B
Keywords: 11 Medical And Health Sciences
01 Mathematical Sciences
Publication Status: Accepted
Online Publication Date: 2018-05-07
Appears in Collections:Faculty of Medicine
Epidemiology, Public Health and Primary Care

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