Poster Session 2
Category: Infectious Diseases
Poster Session 2
Sara I. Jones, MD (she/her/hers)
Clinical Fellow
Duke University School of Medicine
Durham, North Carolina, United States
Lillian Boettcher, MD (she/her/hers)
Clinical Fellow, Division of Maternal-Fetal Medicine
Duke University School of Medicine
Durham, North Carolina, United States
Hannah Kelly, MD
Duke University School of Medicine
Durham, North Carolina, United States
Chun Xu, MS
Duke University Medical Center
Durham, North Carolina, United States
Tracy Truong, MS
Biostatistician
Duke University Medical Center
Durham, North Carolina, United States
Elizabeth Livingston, MD
Duke University Medical Center
Durham, North Carolina, United States
Sarah K. Dotters-Katz, MD
Associate Professor of Obstetrics and Gynecology
Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Duke University
Duke University/Durham, North Carolina, United States
We performed an interrupted time series analysis (ITS) of patients who delivered between 2010 and 2019 using the Centers for Disease Control and Prevention Natality Database. Patients were included if they resided in a state with at least one county affected by a Major Disaster Declaration of a hurricane, earthquake, or fire for at least 1 week, as recorded by the Federal Emergency Management Agency with public assistance requested. We used an ITS quasi-Poisson regression model to estimate the monthly prevalence of active syphilis, chlamydia, and gonorrhea infection at delivery and assess trends over the year before and after each disaster type. The primary outcome was difference between observed and counterfactual (projected assuming the disaster had not occurred) rates at 1 month post-disaster for each infection. Models were adjusted for maternal age, categorical BMI, race, ethnicity, insurance, education status, marital status, and United States region.
Results:
15,448,550 deliveries were evaluated from 25 states experiencing a Major Disaster Declaration for a hurricane, earthquake, or fire between 2010 and 2019. At 1 month following the disaster, syphilis prevalence was higher than expected after a major fire (adjusted rate ratio [aRR] 1.16; 95% CI:1.05,1.29; p=0.006) and hurricane (aRR 1.10; 95% CI:1.00,1.21; p=0.047) (Figure 1). At the same time point, the observed prevalence of chlamydia was also higher than expected following a major fire (aRR 1.04; 95% CI 1.01-1.06; p=0.015) (Figure 2). No statistically significant differences were seen for rates of gonorrhea following any disaster type.
Conclusion:
The prevalence of new perinatal sexually transmitted infection increases following local natural disasters, exceeding rates expected had the disaster not occurred. This information may be useful to guide post-disaster resource allocation, screening, and advocacy for climate action.