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Background: The Surveillance for Emerging Threats to Pregnant People and Infants Network (SET‐NET) collects data abstracted from medical records and birth defects registries on pregnant people and their infants to understand outcomes associated with prenatal exposures. We developed an automated process to categorize possible birth defects for prenatal COVID‐19, hepatitis C, and syphilis surveillance. By employing keyword searches, fuzzy matching, natural language processing (NLP), and machine learning (ML), we aimed to decrease the number of cases needing manual clinician review. Methods: SET‐NET captures International Classification of Diseases, 10th Revision, Clinical Modification (ICD‐10‐CM) codes and free text describing birth defects. For unstructured data, we used keyword searches, and then conducted fuzzy matching with a cut‐off match score of ≥90%. Finally, we employed NLP and ML by testing three predictive models to categorize birth defect data. Results: As of June 2023, 8326 observations containing data on possible birth defects were submitted to SET‐NET. The majority (n = 6758 [81%]) were matched to an ICD‐10‐CM code and 1568 (19%) were unable to be matched. Through keyword searches and fuzzy matching, we categorized 1387/1568 possible birth defects. Of the remaining 181 unmatched observations, we correctly categorized 144 (80%) using a predictive model. Conclusions: Using automated approaches allowed for categorization of 99.6% of reported possible birth defects, which helps detect possible patterns requiring further investigation. Without employing these analytic approaches, manual review would have been needed for 1568 observations. These methods can be employed to quickly and accurately sift through data to inform public health responses. [ABSTRACT FROM AUTHOR]

Background: Multiple studies have described increased risk of severe coronavirus disease (COVID‐19) among pregnant women compared to nonpregnant women. The risk in middle‐income countries where the distributions of age groups and preexisting conditions may differ is less known. Objectives: To determine whether pregnant women with SARS‐CoV‐2 infection are at increased risk for severe COVID‐19 compared to nonpregnant women in Colombia. Methods: We analysed national surveillance data from Colombia, of women aged 15–44 years with laboratory‐confirmed infection with SARS‐CoV‐2 by molecular or antigen testing, from 6 March 2020 to 12 December 2020. An enhanced follow‐up of pregnant women with COVID‐19 was established to monitor pregnancy and birth outcomes. Results: Of 371,363 women aged 15–44 years with laboratory‐confirmed SARS‐CoV‐2 infection, 1.5% (n = 5614) were reported as pregnant; among those, 2610 (46.5%) were considered a complete pregnancy for reporting purposes at the time of analysis. Hospitalisation (23.9%) and death (1.3%) occurred more frequently among pregnant symptomatic women compared to nonpregnant symptomatic women (2.9% and 0.3%, respectively). Compared to nonpregnant symptomatic women, pregnant symptomatic women were at increased risk of hospitalisation (adjusted risk ratio [RR] 2.19, 95% confidence interval [CI] 2.07, 2.32) and death (RR 1.82, 95% CI 1.60, 2.07), after adjusting for age, type of health insurance and presence of certain underlying medical conditions. Among complete pregnancies, 55 (2.1%) were pregnancy losses, 72 (2.8%) resulted in term low birthweight infants and 375 (14.4%) were preterm deliveries. Conclusions: Although pregnant women were infrequently reported with laboratory‐confirmed SARS‐CoV‐2 infection, pregnant symptomatic women with COVID‐19 were at increased risk for hospitalisation and death compared to nonpregnant symptomatic women. Almost all infections we reported on were third‐trimester infections; ongoing follow‐up is needed to determine pregnancy outcomes among women infected earlier in pregnancy. Healthcare providers should counsel pregnant women about preventive measures to protect from SARS‐CoV‐2 infection and when to seek care. [ABSTRACT FROM AUTHOR]

Background: Zika virus (ZIKV) infection during pregnancy can cause infant brain and eye abnormalities and has been associated with adverse neurodevelopmental outcomes in exposed infants. Evidence is limited on ZIKV's effects on children infected postnatally within the first year of life.Objective: To determine whether any adverse neurodevelopmental outcomes occurred in early childhood for children infected postnatally with ZIKV during infancy, given the neurotoxicity of ZIKV infection and the rapid brain development that occurs in infancy and early childhood.Methods: The Colombia Instituto Nacional de Salud (INS) conducted health and developmental screenings between September and November 2017 to evaluate 60 children at ages 20-30 months who had laboratory-confirmed symptomatic postnatal ZIKV infection at ages 1-12 months. We examined the frequency of adverse neurologic, hearing, eye, and developmental outcomes as well as the relationship between age at Zika symptom onset and developmental outcomes.Results: Nine of the 60 (15.0%) children had adverse outcomes on the neurologic, hearing, or eye examination. Six of the 47 (12.8%) children without these adverse findings, and who received a valid developmental screening, had an alert score in the hearing-language domain which signals the need for additional developmental evaluation.Conclusion: Neurologic, hearing, eye, and developmental findings suggest reassuring results. Since the full spectrum of neurodevelopmental outcomes in children postnatally infected with ZIKV remains unknown, routine paediatric care is advised to monitor the development of these children to ensure early identification of any adverse neurodevelopmental outcomes. [ABSTRACT FROM AUTHOR]