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Identification of causal intervention effects under contagion

Author

Listed:
  • Cai Xiaoxuan

    (Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America)

  • Loh Wen Wei

    (Department of Data Analysis, University of Ghent, Ghent, Belgium)

  • Crawford Forrest W.

    (Department of Biostatistics, Yale School of Public Health; Department of Statistics & Data Science, Yale University; Department of Ecology and Evolutionary Biology, Yale University; Yale School of Management, New Haven, Connecticut, United States of America)

Abstract

Defining and identifying causal intervention effects for transmissible infectious disease outcomes is challenging because a treatment – such as a vaccine – given to one individual may affect the infection outcomes of others. Epidemiologists have proposed causal estimands to quantify effects of interventions under contagion using a two-person partnership model. These simple conceptual models have helped researchers develop causal estimands relevant to clinical evaluation of vaccine effects. However, many of these partnership models are formulated under structural assumptions that preclude realistic infectious disease transmission dynamics, limiting their conceptual usefulness in defining and identifying causal treatment effects in empirical intervention trials. In this paper, we propose causal intervention effects in two-person partnerships under arbitrary infectious disease transmission dynamics, and give nonparametric identification results showing how effects can be estimated in empirical trials using time-to-infection or binary outcome data. The key insight is that contagion is a causal phenomenon that induces conditional independencies on infection outcomes that can be exploited for the identification of clinically meaningful causal estimands. These new estimands are compared to existing quantities, and results are illustrated using a realistic simulation of an HIV vaccine trial.

Suggested Citation

  • Cai Xiaoxuan & Loh Wen Wei & Crawford Forrest W., 2021. "Identification of causal intervention effects under contagion," Journal of Causal Inference, De Gruyter, vol. 9(1), pages 9-38, January.
  • Handle: RePEc:bpj:causin:v:9:y:2021:i:1:p:9-38:n:2
    DOI: 10.1515/jci-2019-0033
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    References listed on IDEAS

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