Leveraging Contact Network Information in Clustered Randomized Studies of Contagion Processes.
PRAGUE, Melanie
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
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Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
PRAGUE, Melanie
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
< Reduce
Statistics In System biology and Translational Medicine [SISTM]
Bordeaux population health [BPH]
Language
EN
Article de revue
This item was published in
Observational Studies. 2023, vol. 9, n° 2, p. 157-175
English Abstract
In a randomized study, leveraging covariates related to the outcome (e.g. disease status) may produce less variable estimates of the effect of exposure. For contagion processes operating on a contact network, transmission ...Read more >
In a randomized study, leveraging covariates related to the outcome (e.g. disease status) may produce less variable estimates of the effect of exposure. For contagion processes operating on a contact network, transmission can only occur through ties that connect affected and unaffected individuals; the outcome of such a process is known to depend intimately on the structure of the network. In this paper, we investigate the use of contact network features as efficiency covariates in exposure effect estimation. Using augmented generalized estimating equations (GEE), we estimate how gains in efficiency depend on the network structure and spread of the contagious agent or behavior. We apply this approach to simulated randomized trials using a stochastic compartmental contagion model on a collection of model-based contact networks and compare the bias, power, and variance of the estimated exposure effects using an assortment of network covariate adjustment strategies. We also demonstrate the use of network-augmented GEEs on a clustered randomized trial evaluating the effects of wastewater monitoring on COVID-19 cases in residential buildings at the the University of California San Diego.Read less <
English Keywords
Network
Contagion
Statistics