Patterned Outcomes, Unpatterned Counterfactuals, and Spurious Results: Perinatal Health Outcomes Following COVID-19
Author(s) -
Alison Gemmill,
Joan A. Casey,
Claire E. Margerison,
Jennifer Zeitlin,
Ralph Catalano,
Tim A. Bruckner
Publication year - 2022
Publication title -
american journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.33
H-Index - 256
eISSN - 1476-6256
pISSN - 0002-9262
DOI - 10.1093/aje/kwac110
Subject(s) - covid-19 , spurious relationship , counterfactual conditional , medicine , coronavirus infections , virology , psychology , statistics , disease , outbreak , counterfactual thinking , infectious disease (medical specialty) , mathematics , social psychology
The epidemiologic literature estimating the indirect or secondary effects of the coronavirus disease 2019 (COVID-19) pandemic on pregnant people and gestation continues to grow. Our assessment of this scholarship, however, leads us to suspect that the methods most commonly used may lead researchers to spurious inferences. This suspicion arises because the methods do not account for temporal patterning in perinatal outcomes when deriving counterfactuals, or estimates of the outcomes had the pandemic not occurred. We illustrate the problem in 2 ways. First, using monthly data from US birth certificates, we describe temporal patterning in 5 commonly used perinatal outcomes. Notably, for all but 1 outcome, temporal patterns appear more complex than much of the emerging literature assumes. Second, using data from France, we show that using counterfactuals that ignore this complexity produces spurious results. We recommend that subsequent investigations on COVID-19 and other perturbations use widely available time-series methods to derive counterfactuals that account for strong temporal patterning in perinatal outcomes.
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