OBJECTIVE: To assess the frequency of hepatitis C virus (HCV) testing among a population-based cohort of perinatally exposed children and identify factors associated with testing. METHODS: Using a population-based surveillance cohort of perinatally exposed children born from 2018 to 2020 from 4 US jurisdictions (Georgia; Massachusetts; Allegheny County, Pennsylvania; and Los Angeles County, California), we describe the frequency, timing, and type of HCV testing among children and identify characteristics associated with having an HCV test result by the age of 2 to 3 years. Data were obtained from electronic laboratory reporting, vital records, and medical records. RESULTS: Of 803 perinatally exposed children, 7 (1%) died before the age of 24 months. Of 796 children, health departments were unable to find medical records or laboratory reports for 181 (23%). Among those with medical record abstraction at 24 months or testing reported before the age of 3 years (n = 615), 50% had an HCV test. The majority (70% of those tested) were tested for HCV antibodies at the age of 18 months or later, although 9% had an HCV nucleic acid test at ages 2 to <6 months. No characteristics examined were found to be significantly associated with having testing reported. CONCLUSIONS: In this surveillance report, we identify the gaps in current testing among children perinatally exposed to hepatitis C. Provider education and resources for health departments for follow-up and linkage to care can improve the identification of children requiring treatment, a vital piece of HCV elimination.

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.

During May 10-December 31, 2022, a total of 29,980 confirmed and probable(†) U.S. monkeypox (mpox) cases were reported to CDC, predominantly in cisgender adult men reporting recent same-gender sexual partners (1). Urban-rural differences in health (2) and diagnosis of HIV (3,4) and other sexually transmitted infections (5) are well documented nationally. This report describes urban-rural differences in mpox incidence (cases per 100,000 population) among persons aged 15-64 years, by gender and race and ethnicity. Urbanicity was assessed using the 2013 National Center for Health Statistics (NCHS) Urban-Rural Classification Scheme for Counties (2). Substantial differences in incidence by urbanicity, gender, and race and ethnicity were observed; most (71.0%) cases occurred in persons residing in large central urban areas. Among the cases in large central urban areas, most (95.7%) were in cisgender men. The overall incidence of mpox in the United States was 13.5 per 100,000 persons aged 15-64 years and peaked in August in both urban and rural areas. Among cisgender men, incidence in rural areas was approximately 4% that in large central urban areas (risk ratio [RR] = 0.04). Among cisgender women, incidence in rural areas was approximately 11% that in large central urban areas (RR = 0.11). In both urban and rural areas, incidence among non-Hispanic Black or African American (Black) and Hispanic or Latino (Hispanic) persons was consistently higher than that among non-Hispanic White (White) persons; RRs between Black and White persons were highest in rural areas. Support and maintenance of mpox surveillance and prevention efforts including vaccinations should focus on urban areas with the highest incidence of mpox during the 2022 outbreak; however, surveillance and prevention efforts should include all genders, persons of color, and persons residing in both urban and rural areas who are at increased risk for mpox.