Incidence of hepatitis C virus (HCV) infection in women of reproductive age is increasing, leading to rising numbers of women with HCV infection in pregnancy and concerns of perinatal transmission. In April 2020, the Centers for Disease Control and Prevention (CDC) began recommending HCV screening during each pregnancy. We describe maternal characteristics and timing of HCV testing among pregnant women identified with HCV infection. |

BACKGROUND: Pregnant women with coronavirus disease 2019 (COVID-19) are at increased risk for severe illness compared with nonpregnant women. Data to assess risk factors for illness severity among pregnant women with COVID-19 are limited. This study aimed to determine risk factors associated with COVID-19 illness severity among pregnant women with SARS-CoV-2 infection. METHODS: Pregnant women with SARS-CoV-2 infection confirmed by molecular testing were reported during March 29, 2020-March 5, 2021 through the Surveillance for Emerging Threats to Mothers and Babies Network (SET-NET). Criteria for illness severity (asymptomatic, mild, moderate-to-severe, or critical) were adapted from National Institutes of Health and World Health Organization criteria. Crude and adjusted risk ratios for moderate-to-severe or critical COVID-19 illness were calculated for selected demographic and clinical characteristics. RESULTS: Among 7,950 pregnant women with SARS-CoV-2 infection, moderate-to-severe or critical COVID-19 illness was associated with age 25 years and older, healthcare occupation, pre-pregnancy obesity, chronic lung disease, chronic hypertension, and pregestational diabetes mellitus. Risk of moderate-to-severe or critical illness increased with the number of underlying medical or pregnancy-related conditions. CONCLUSIONS: Older age and having underlying medical conditions were associated with increased risk of moderate-to-severe or critical COVID-19 illness among pregnant women. This information might help pregnant women understand their risk for moderate-to-severe or critical COVID-19 illness and inform targeted public health messaging.

BACKGROUND: Evidence on risk for adverse outcomes from COVID-19 among pregnant women is still emerging. We examined the association between COVID-19 at delivery and adverse pregnancy outcomes, maternal complications, and severe illness, whether these associations differ by race/ethnicity; and described discharge status by COVID-19 diagnosis and maternal complications. METHODS: Data from 703 hospitals in the Premier Healthcare Database during March-September 2020 were included. Adjusted risk ratios overall and stratified by race/ethnicity were estimated using Poisson regression with robust standard errors. Proportion not discharged home was calculated by maternal complications, stratified by COVID-19 diagnosis. RESULTS: Among 489,471 delivery hospitalizations, 6,550 (1.3%) had a COVID-19 diagnosis. In adjusted models, COVID-19 was associated with increased risk for: acute respiratory distress syndrome (adjusted risk ratio [aRR] = 34.4), death (aRR = 17.0), sepsis (aRR = 13.6), mechanical ventilation (aRR = 12.7), shock (aRR = 5.1), intensive care unit admission (aRR = 3.6), acute renal failure (aRR = 3.5), thromboembolic disease (aRR = 2.7), adverse cardiac event/outcome (aRR = 2.2) and preterm labor with preterm delivery (aRR = 1.2). Risk for any maternal complications or for any severe illness did not significantly differ by race/ethnicity. Discharge status did not differ by COVID-19; however, among women with concurrent maternal complications, a greater proportion of those with (versus without) COVID-19 were not discharged home. CONCLUSIONS: These findings emphasize the importance of implementing recommended mitigation strategies to reduce risk for SARS-CoV-2 infection and further inform counseling and clinical care for pregnant women during the COVID-19 pandemic.

INTRODUCTION: Public health responses often lack the infrastructure to capture the impact of public health emergencies on pregnant women and infants, with limited mechanisms for linking pregnant women with their infants nationally to monitor long-term effects. In 2019, the Centers for Disease Control and Prevention (CDC), in close collaboration with state, local, and territorial health departments, began a 5-year initiative to establish population-based mother-baby linked longitudinal surveillance, the Surveillance for Emerging Threats to Mothers and Babies Network (SET-NET). OBJECTIVES: The objective of this report is to describe an expanded surveillance approach that leverages and modernizes existing surveillance systems to address the impact of emerging health threats during pregnancy on pregnant women and their infants. METHODS: Mother-baby pairs are identified through prospective identification during pregnancy and/or identification of an infant with retrospective linking to maternal information. All data are obtained from existing data sources (e.g., electronic medical records, vital statistics, laboratory reports, and health department investigations and case reporting). RESULTS: Variables were selected for inclusion to address key surveillance questions proposed by CDC and health department subject matter experts. General variables include maternal demographics and health history, pregnancy and infant outcomes, maternal and infant laboratory results, and child health outcomes up to the second birthday. Exposure-specific modular variables are included for hepatitis C, syphilis, and Coronavirus Disease 2019 (COVID-19). The system is structured into four relational datasets (maternal, pregnancy outcomes and birth, infant/child follow-up, and laboratory testing). DISCUSSION: SET-NET provides a population-based mother-baby linked longitudinal surveillance approach and has already demonstrated rapid adaptation to COVID-19. This innovative approach leverages existing data sources and rapidly collects data and informs clinical guidance and practice. These data can help to reduce exposure risk and adverse outcomes among pregnant women and their infants, direct public health action, and strengthen public health systems.

Studies suggest that pregnant women might be at increased risk for severe illness associated with coronavirus disease 2019 (COVID-19) (1,2). This report provides updated information about symptomatic women of reproductive age (15-44 years) with laboratory-confirmed infection with SARS-CoV-2, the virus that causes COVID-19. During January 22-October 3, CDC received reports through national COVID-19 case surveillance or through the National Notifiable Diseases Surveillance System (NNDSS) of 1,300,938 women aged 15-44 years with laboratory results indicative of acute infection with SARS-CoV-2. Data on pregnancy status were available for 461,825 (35.5%) women with laboratory-confirmed infection, 409,462 (88.7%) of whom were symptomatic. Among symptomatic women, 23,434 (5.7%) were reported to be pregnant. After adjusting for age, race/ethnicity, and underlying medical conditions, pregnant women were significantly more likely than were nonpregnant women to be admitted to an intensive care unit (ICU) (10.5 versus 3.9 per 1,000 cases; adjusted risk ratio [aRR] = 3.0; 95% confidence interval [CI] = 2.6-3.4), receive invasive ventilation (2.9 versus 1.1 per 1,000 cases; aRR = 2.9; 95% CI = 2.2-3.8), receive extracorporeal membrane oxygenation (ECMO) (0.7 versus 0.3 per 1,000 cases; aRR = 2.4; 95% CI = 1.5-4.0), and die (1.5 versus 1.2 per 1,000 cases; aRR = 1.7; 95% CI = 1.2-2.4). Stratifying these analyses by age and race/ethnicity highlighted disparities in risk by subgroup. Although the absolute risks for severe outcomes for women were low, pregnant women were at increased risk for severe COVID-19-associated illness. To reduce the risk for severe illness and death from COVID-19, pregnant women should be counseled about the importance of seeking prompt medical care if they have symptoms and measures to prevent SARS-CoV-2 infection should be strongly emphasized for pregnant women and their families during all medical encounters, including prenatal care visits. Understanding COVID-19-associated risks among pregnant women is important for prevention counseling and clinical care and treatment.

Pregnant women with coronavirus disease 2019 (COVID-19) are at increased risk for severe illness and might be at risk for preterm birth (1-3). The full impact of infection with SARS-CoV-2, the virus that causes COVID-19, in pregnancy is unknown. Public health jurisdictions report information, including pregnancy status, on confirmed and probable COVID-19 cases to CDC through the National Notifiable Diseases Surveillance System.* Through the Surveillance for Emerging Threats to Mothers and Babies Network (SET-NET), 16 jurisdictions collected supplementary information on pregnancy and infant outcomes among 5,252 women with laboratory-confirmed SARS-CoV-2 infection reported during March 29-October 14, 2020. Among 3,912 live births with known gestational age, 12.9% were preterm (<37 weeks), higher than the reported 10.2% among the general U.S. population in 2019 (4). Among 610 infants (21.3%) with reported SARS-CoV-2 test results, perinatal infection was infrequent (2.6%) and occurred primarily among infants whose mother had SARS-CoV-2 infection identified within 1 week of delivery. Because the majority of pregnant women with COVID-19 reported thus far experienced infection in the third trimester, ongoing surveillance is needed to assess effects of infections in early pregnancy, as well the longer-term outcomes of exposed infants. These findings can inform neonatal testing recommendations, clinical practice, and public health action and can be used by health care providers to counsel pregnant women on the risks of SARS-CoV-2 infection, including preterm births. Pregnant women and their household members should follow recommended infection prevention measures, including wearing a mask, social distancing, and frequent handwashing when going out or interacting with others or if there is a person within the household who has had exposure to COVID-19.(†).

Pregnant women might be at increased risk for severe coronavirus disease 2019 (COVID-19) (1,2). The COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) (3) collects data on hospitalized pregnant women with laboratory-confirmed SARS-CoV-2, the virus that causes COVID-19; to date, such data have been limited. During March 1-August 22, 2020, approximately one in four hospitalized women aged 15-49 years with COVID-19 was pregnant. Among 598 hospitalized pregnant women with COVID-19, 54.5% were asymptomatic at admission. Among 272 pregnant women with COVID-19 who were symptomatic at hospital admission, 16.2% were admitted to an intensive care unit (ICU), and 8.5% required invasive mechanical ventilation. During COVID-19-associated hospitalizations, 448 of 458 (97.8%) completed pregnancies resulted in a live birth and 10 (2.2%) resulted in a pregnancy loss. Testing policies based on the presence of symptoms might miss COVID-19 infections during pregnancy. Surveillance of pregnant women with COVID-19, including those with asymptomatic infections, is important to understand the short- and long-term consequences of COVID-19 for mothers and newborns. Identifying COVID-19 in women during birth hospitalizations is important to guide preventive measures to protect pregnant women, parents, newborns, other patients, and hospital personnel. Pregnant women and health care providers should be made aware of the potential risks for severe COVID-19 illness, adverse pregnancy outcomes, and ways to prevent infection.

As of June 16, 2020, the coronavirus disease 2019 (COVID-19) pandemic has resulted in 2,104,346 cases and 116,140 deaths in the United States.* During pregnancy, women experience immunologic and physiologic changes that could increase their risk for more severe illness from respiratory infections (1,2). To date, data to assess the prevalence and severity of COVID-19 among pregnant U.S. women and determine whether signs and symptoms differ among pregnant and nonpregnant women are limited. During January 22-June 7, as part of COVID-19 surveillance, CDC received reports of 326,335 women of reproductive age (15-44 years) who had positive test results for SARS-CoV-2, the virus that causes COVID-19. Data on pregnancy status were available for 91,412 (28.0%) women with laboratory-confirmed infections; among these, 8,207 (9.0%) were pregnant. Symptomatic pregnant and nonpregnant women with COVID-19 reported similar frequencies of cough (>50%) and shortness of breath (30%), but pregnant women less frequently reported headache, muscle aches, fever, chills, and diarrhea. Chronic lung disease, diabetes mellitus, and cardiovascular disease were more commonly reported among pregnant women than among nonpregnant women. Among women with COVID-19, approximately one third (31.5%) of pregnant women were reported to have been hospitalized compared with 5.8% of nonpregnant women. After adjusting for age, presence of underlying medical conditions, and race/ethnicity, pregnant women were significantly more likely to be admitted to the intensive care unit (ICU) (aRR = 1.5, 95% confidence interval [CI] = 1.2-1.8) and receive mechanical ventilation (aRR = 1.7, 95% CI = 1.2-2.4). Sixteen (0.2%) COVID-19-related deaths were reported among pregnant women aged 15-44 years, and 208 (0.2%) such deaths were reported among nonpregnant women (aRR = 0.9, 95% CI = 0.5-1.5). These findings suggest that among women of reproductive age with COVID-19, pregnant women are more likely to be hospitalized and at increased risk for ICU admission and receipt of mechanical ventilation compared with nonpregnant women, but their risk for death is similar. To reduce occurrence of severe illness from COVID-19, pregnant women should be counseled about the potential risk for severe illness from COVID-19, and measures to prevent infection with SARS-CoV-2 should be emphasized for pregnant women and their families.

OBJECTIVE: To estimate the prevalence of microcephaly and central nervous system (CNS) defects during the Zika virus (ZIKV) epidemic in Colombia and proportion attributable to congenital ZIKV infection. STUDY DESIGN: Clinical and laboratory data for cases of microcephaly and/or CNS defects reported to national surveillance between 2015 and 2017 were reviewed and classified by a panel of clinical subject matter experts. Maternal and fetal/infant biologic specimens were tested for congenital infection and chromosomal abnormalities. Infants/fetuses with microcephaly and/or CNS defects (cases) were classified into broad etiologic categories (teratogenic, genetic, multifactorial, and unknown). Cases classified as potentially attributable to congenital ZIKV infection were stratified by strength of evidence for ZIKV etiology (strong, moderate, or limited) using a novel strategy considering birth defects unique or specific to ZIKV or other infections and laboratory evidence. RESULTS: Among 858 reported cases with sufficient information supporting a diagnosis of microcephaly or CNS defects, 503 were classified as potentially attributable to congenital ZIKV infection. Of these, the strength of evidence was considered strong in 124 (24.7%) cases; moderate in 232 (46.1%) cases; and limited in 147 (29.2%). Of the remaining, 355 (41.4%) were attributed to etiologies other than ZIKV infection (syphilis, toxoplasmosis, rubella, cytomegalovirus, herpes 1 and herpes 2 viruses only, n = 32 [3.7%]; genetic, n = 16 [1.9%]; multifactorial, n = 42 [4.9%]; unknown, n = 265 [30.9%]). CONCLUSIONS: Fifty-eight percent of cases of microcephaly and/or CNS defects were potentially attributable to congenital ZIKV infection; however, the strength of evidence varied considerably. This surveillance protocol might serve as a model approach for investigation and etiologic classification of complex congenital conditions.

BACKGROUND: Diabetes is associated with an increased risk for many birth defects and is likely to have an increasing impact on birth defect prevalence due to the rise in diabetes in the United States in recent decades. One of the first analyses in which specific birth defects were assessed for their relationship with both pregestational and gestational diabetes used data from the initial six years of the National Birth Defects Prevention Study. That analysis reported strong associations for pregestational diabetes with several birth defects, but few exposures among some of the less common birth defects led to unstable estimates with wide confidence intervals. Since that analysis, the study continued to collect data for another eight years, including information on approximately 19,000 additional cases and 6,900 additional controls. OBJECTIVES: Our objective was to use data from the National Birth Defects Prevention Study, the largest population-based birth defects case-control study in the United States, to provide updated and more precise estimates of the association between diabetes and birth defects, including some defects not previously assessed. STUDY DESIGN: We analyzed data on deliveries from October 1997 through December 2011. Mothers of case and control infants were interviewed about their health conditions and exposures during pregnancy, including diagnosis of pregestational (type 1 or type 2) diabetes before the index pregnancy or gestational diabetes during the index pregnancy. Using logistic regression, we separately assessed the association between pregestational and gestational diabetes with specific categories of structural birth defects for which there were at least three exposed case infants. For birth defect categories for which there were at least five exposed case infants, we calculated odds ratios adjusted for maternal body mass index, age, education, race/ethnicity, and study site; for defect categories with three or four exposed cases we calculated crude odds ratios. RESULTS: Pregestational diabetes was reported by 0.6 percent of mothers of control infants (71 / 11,447) and 2.5 percent of mothers of case infants (775 / 31,007). Gestational diabetes during the index pregnancy was reported by 4.7 percent of mothers of control infants (536 / 11,447) and 5.3 percent of mothers of case infants (1,653 / 31,007). Pregestational diabetes was associated with strong, statistically significant odds ratios (range: 2.5 to 80.2) for 46 of 50 birth defects considered. The largest odds ratio was observed for sacral agenesis (adjusted OR [aOR]: 80.2; 95% CI: 46.1, 139.3). A greater than 10-fold increased risk was also observed for holoprosencephaly (aOR: 13.1; 95% CI: 7.0, 24.5), longitudinal limb deficiency (aOR: 10.1; 95% CI: 6.2, 16.5), heterotaxy (aOR: 12.3; 95% CI: 7.3, 20.5), truncus arteriosus (aOR: 14.9; 95% CI: 7.6, 29.3), atrioventricular septal defect (aOR: 10.5; 95% CI: 6.2, 17.9), and single ventricle complex (aOR: 14.7; 95% CI: 8.9, 24.3).For gestational diabetes, statistically significant odds ratios were fewer (12 of 56) and of smaller magnitude (range: 1.3 to 2.1; 0.5 for gastroschisis). CONCLUSIONS: Pregestational diabetes is associated with markedly increased risk for many specific births defects. Because glycemic control before pregnancy is associated with a reduced risk for birth defects, ongoing quality care for persons with diabetes is an important opportunity for prevention.

BACKGROUND: Ebstein anomaly is a rare congenital heart defect (CHD) that, when severe, requires corrective surgery or other catheter-based intervention in the first year of life. Due to its rarity, risk factors for Ebstein anomaly remain largely unknown. Using national data, we examined 18 potential risk factors for Ebstein anomaly. METHODS: Using 1997-2011 data from the National Birth Defects Prevention Study, a population-based case-control study, we calculated crude and adjusted odds ratios and 95% confidence intervals for paternal age, maternal socio-demographics, reproductive history, and modifiable risk factors, and infant characteristics reported by mothers of 135 Ebstein anomaly cases and 11,829 controls. RESULTS: Mothers of Ebstein anomaly cases had 4.1 (95% confidence interval: 1.8, 9.5) times the odds of reporting a family history of CHD compared with mothers of controls. Ebstein anomaly was associated with maternal second-hand cigarette smoke exposure at home (odds ratio = 2.2 [95% confidence interval: 1.1, 4.4]), but not maternal cigarette smoking (odds ratio = 1.3 [95% confidence interval: 0.8, 2.1]). Odds were elevated, but the 95% confidence interval included 1.0, for maternal marijuana use (odds ratio = 1.8 [95% confidence interval: 0.9, 3.8]) and paternal age >/=40 years at delivery (odds ratio = 1.9 [95% confidence interval: 1.0, 3.5]). CONCLUSIONS: Maternal exposure to second-hand cigarette smoke at home and a family history of CHD were associated with elevated odds of Ebstein anomaly. Genetic analyses could clarify the potential heritability of Ebstein anomaly.

Importance: Zika virus (ZIKV) infection during pregnancy is a cause of congenital microcephaly and severe fetal brain defects, and it has been associated with other adverse pregnancy and birth outcomes. Objective: To estimate the number of pregnant women infected with ZIKV in Puerto Rico and the number of associated congenital microcephaly cases. Design, Setting, and Participants: We conducted a modeling study from April to July 2016. Using parameters derived from published reports, outcomes were modeled probabilistically using Monte Carlo simulation. We used uncertainty distributions to reflect the limited information available for parameter values. Given the high level of uncertainty in model parameters, interquartile ranges (IQRs) are presented as primary results. Outcomes were modeled for pregnant women in Puerto Rico, which currently has more confirmed ZIKV cases than any other US location. Exposure: Zika virus infection in pregnant women. Main Outcomes and Measures: Number of pregnant women infected with ZIKV and number of congenital microcephaly cases. Results: We estimated an IQR of 5900 to 10300 pregnant women (median, 7800) might be infected during the initial ZIKV outbreak in Puerto Rico. Of these, an IQR of 100 to 270 infants (median, 180) may be born with microcephaly due to congenital ZIKV infection from mid-2016 to mid-2017. In the absence of a ZIKV outbreak, an IQR of 9 to 16 cases (median, 12) of congenital microcephaly are expected in Puerto Rico per year. Conclusions and Relevance: The estimate of 5900 to 10300 pregnant women that might be infected with ZIKV provides an estimate for the number of infants that could potentially have ZIKV-associated adverse outcomes. Including baseline cases of microcephaly, we estimated that an IQR of 110 to 290 total cases of congenital microcephaly, mostly attributable to ZIKV infection, could occur from mid-2016 to mid-2017 in the absence of effective interventions. The primary limitation in this analysis is uncertainty in model parameters. Multivariate sensitivity analyses indicated that the cumulative incidence of ZIKV infection and risk of microcephaly given maternal infection in the first trimester were the primary drivers of both magnitude and uncertainty in the estimated number of microcephaly cases. Increased information on these parameters would lead to more precise estimates. Nonetheless, the results underscore the need for urgent actions being undertaken in Puerto Rico to prevent congenital ZIKV infection and prepare for affected infants.

BACKGROUND: -Because of advancements in care, there has been a decline in mortality from congenital heart defects (CHD) over the last several decades. However, there are no current empirical data documenting the number of people living with CHD in the United States (US). Our aim was to estimate the CHD prevalence across all age groups in the US in the year 2010. METHODS: -The age-, sex-, and severity-specific observed prevalence of CHD in Quebec, Canada in the year 2010 was assumed to equal the CHD prevalence in the non-Hispanic white population in the US in 2010. A race-ethnicity adjustment factor, reflecting differential survival between racial-ethnic groups through age 5 for persons with a CHD and that in the general US population, was applied to the estimated non-Hispanic white rates to derive CHD prevalence estimates among US non-Hispanic blacks and Hispanics. Confidence intervals for the estimated CHD prevalence rates and case counts were derived using a combination of Taylor series approximations and Monte Carlo simulation. RESULTS: -We estimated that approximately 2.4 million people (1.4 million adults, 1 million children) were living with CHD in the US in 2010. Nearly 300,000 of these individuals had severe CHD. CONCLUSIONS: -Our estimates highlight the need for two important efforts: (1) planning for health services delivery to meet the needs of the growing population of adults with CHD and; (2) the development of surveillance data across the lifespan to provide empirical estimates of the prevalence of CHD across all age groups in the US.

Conducting research to identify modifiable risk factors for birth defects is difficult for a variety of reasons. While some challenges are familiar to researchers across many disciplines, the confluence of issues affecting birth defects research may not be well understood by those outside of the field. This article describes several methodological challenges to the study of birth defects and ways these challenges might be addressed: (1) ascertainment, definition and classification of birth defects; (2) exposure assessment on modifiable risk factors; (3) analytical challenges related to small numbers and multiple statistical tests; (4) the role of genetics, including the collection of specimens and analysis of genetic data; and (5) challenges in translating research and demonstrating public health impact. Understanding these issues is important for researchers planning studies, reviewers evaluating the scientific merit of results from these studies, and consumers of the research, including fellow researchers, policy makers, health care providers, and families.

CONTEXT: Maternal pregestational diabetes (PGDM) is a risk factor for development of congenital heart defects (CHDs). Glycemic control before pregnancy reduces the risk of CHDs. A meta-analysis was used to estimate summary ORs and mathematical modeling was used to estimate population attributable fractions (PAFs) and the annual number of CHDs in the U.S. potentially preventable by establishing glycemic control before pregnancy. EVIDENCE ACQUISITION: A systematic search of the literature through December 2012 was conducted in 2012 and 2013. Case-control or cohort studies were included. Data were abstracted from 12 studies for a meta-analysis of all CHDs. EVIDENCE SYNTHESIS: Summary estimates of the association between PGDM and CHDs and 95% credible intervals (95% CrIs) were developed using Bayesian random-effects meta-analyses for all CHDs and specific CHD subtypes. Posterior estimates of this association were combined with estimates of CHD prevalence to produce estimates of PAFs and annual prevented cases. Ninety-five percent uncertainty intervals (95% UIs) for estimates of the annual number of preventable cases were developed using Monte Carlo simulation. Analyses were conducted in 2013. The summary OR estimate for the association between PGDM and CHDs was 3.8 (95% CrI=3.0, 4.9). Approximately 2670 (95% UI=1795, 3795) cases of CHDs could potentially be prevented annually if all women in the U.S. with PGDM achieved glycemic control before pregnancy. CONCLUSIONS: Estimates from this analysis suggest that preconception care of women with PGDM could have a measureable impact by reducing the number of infants born with CHDs.

BACKGROUND: Hispanics in the US have a higher prevalence of neural tube defect (NTD) -affected pregnancies than non-Hispanic whites, and lower median total folic acid (FA) intake. FA fortification of corn masa flour (CMF) is a policy-level intervention for NTD prevention; however, the impact on NTD prevalence has not been estimated. METHODS: We developed a model to estimate the percentage reduction in prevalence of spina bifida and anencephaly (NTDs) that could occur with FA fortification of CMF. Model inputs included estimates of the percentage reduction in United States NTD prevalence attributed to FA fortification of enriched cereal grain products (1995-1996 vs. 1998-2002), the increase in median FA intake after enriched cereal grain product fortification, and the estimated increase in median FA intake that could occur with CMF fortification at the same level as enriched cereal grain products (140 mug/100 g). We used Monte Carlo simulation to quantify uncertainty. We stratified analyses by racial/ethnic group and rounded results to the nearest 10. RESULTS: We estimated CMF fortification could prevent 30 Hispanic infants from having spina bifida (95% uncertainty interval: 0, 80) and 10 infants from having anencephaly (95% uncertainty interval: 0, 40) annually. The estimated impact among non-Hispanic whites and blacks was smaller. CONCLUSION: CMF fortification with FA could prevent from 0 to 120 infants, with the most likely value of approximately 40, from having spina bifida or anencephaly among Hispanics, the population most likely to benefit from the proposed intervention. While this estimated reduction is unlikely to be discernible using current birth defect surveillance methods, it still suggests an important benefit to the target population. Birth Defects Research (Part A) 97:649-657, 2013. (c) 2013 Wiley Periodicals, Inc.