| Abstract |
Background: Preterm birth, defined as birth at <37 weeks of gestation, is the leading cause of neonatal death globally and, together with low birthweight, the second leading cause of infant mortality in the United States. There is mounting evidence that COVID-19 infection during pregnancy is associated with an increased risk of preterm birth; however, data remain limited by trimester of infection. The ability to study COVID-19 infection during the earlier stages of pregnancy has been limited by available sources of data. The objective of this study was to use self-reports in large-scale, longitudinal social media data to assess the association between trimester of COVID-19 infection and preterm birth.
Methods: In this retrospective cohort study, we used natural language processing and machine learning, followed by manual validation, to identify pregnant Twitter users and to search their longitudinal collection of publicly available tweets for reports of COVID-19 infection during pregnancy and, subsequently, a preterm birth or term birth (i.e., a gestational age ≥37 weeks) outcome. Among the users who reported their pregnancy on Twitter, we also identified a 1:1 age-matched control group, consisting of users with a due date prior to January 1, 2020-that is, without COVID-19 infection during pregnancy. We calculated the odds ratios (ORs) with 95% confidence intervals (CIs) to compare the overall rates of preterm birth for pregnancies with and without COVID-19 infection and by timing of infection: first trimester (weeks 1-13), second trimester (weeks 1427), or third trimester (weeks 28-36).
Results: Through August 2022, we identified 298 Twitter users who reported COVID-19 infection during pregnancy, a preterm birth or term birth outcome, and maternal age: 94 (31.5%) with first-trimester infection, 110 (36.9%) second-trimester infection, and 95 (31.9%) third-trimester infection. In total, 26 (8.8%) of these 298 users reported preterm birth: 8 (8.5%) were infected during the first trimester, 7 (6.4%) were infected during the second trimester, and 12 (12.6%) were infected during the third trimester. In the 1:1 age-matched control group, 13 (4.4%) of the 298 users reported preterm birth. Overall, the risk of preterm birth was significantly higher for pregnancies with COVID-19 infection compared to those without (OR 2.1, 95% CI 1.06-4.16). In particular, the risk of preterm birth was significantly higher for pregnancies with COVID-19 infection during the third trimester (OR 3.17, CI 1.39-7.21).
Conclusion: The results of our study suggest that COVID-19 infection particularly during the third trimester is associated with an increased risk of preterm birth.
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