Human African trypanosomiasis is a neglected tropical disease that is usually fatal without treatment. WHO has revised its rhodesiense human African trypanosomiasis treatment guidelines on the basis of an independent systematic literature review and following the GRADE methodology. This Review reports on the decision-making process and summarises the new recommendations and their potential implications for health-care professionals and policy makers. Due to data scarcity, all recommendations are conditional and based on very low certainty of evidence. Fexinidazole replaces suramin and melarsoprol as the first-line therapy in individuals aged 6 years and older with a bodyweight of 20 kg or more. As fexinidazole is effective in both stages of rhodesiense human African trypanosomiasis, a lumbar puncture for staging is no longer required. In settings in which first-choice drugs are not readily available, immediate interim treatment with pentamidine is suggested. The introduction of oral fexinidazole represents an advancement in the management of rhodesiense human African trypanosomiasis considering the life-threatening adverse reactions individuals can have to melarsoprol. However, children below the age or weight limits remain ineligible for treatment with fexinidazole.

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that develops during childhood and can last into adulthood. Data from the National Center for Health Statistics Rapid Surveys System collected during October-November 2023 were used to estimate the prevalence of ADHD diagnosis and treatment among U.S. adults. In 2023, an estimated 15.5 million U.S. adults (6.0%) had a current ADHD diagnosis based on self-report; approximately one half received the diagnosis at age ≥18 years. Approximately one third of adults with ADHD took a stimulant medication to treat their ADHD in the previous year, 71.5% of whom had difficulty getting their ADHD prescription filled because it was unavailable. Approximately one half of adults with ADHD have ever used telehealth for ADHD-related services. Telehealth might have benefits for persons with ADHD, including helping them access behavioral treatment or medication prescriptions for ADHD. This report provides national estimates of the prevalence and treatment of ADHD among U.S. adults to help guide clinical care and regulatory decision-making for ADHD among U.S. adults.

US public health preparedness and response to highly pathogenic avian influenza A(H5N1) viruses are assessed in this survey study conducted by the CDC. | eng

OBJECTIVE: To provide updated national prevalence estimates of diagnosed attention-deficit/hyperactivity disorder (ADHD), ADHD severity, co-occurring disorders, and receipt of ADHD medication and behavioral treatment among U.S. children and adolescents by demographic and clinical subgroups using data from the 2022 National Survey of Children's Health (NSCH). METHOD: This study used 2022 NSCH data to estimate the prevalence of ever diagnosed and current ADHD among U.S. children aged 3-17 years. Among children with current ADHD, ADHD severity, presence of current co-occurring disorders, and receipt of medication and behavioral treatment were estimated. Weighted estimates were calculated overall and for demographic and clinical subgroups (n = 45,169). RESULTS: Approximately 1 in 9 U.S. children have ever received an ADHD diagnosis (11.4%, 7.1 million children) and 10.5% (6.5 million) had current ADHD. Among children with current ADHD, 58.1% had moderate or severe ADHD, 77.9% had at least one co-occurring disorder, approximately half of children with current ADHD (53.6%) received ADHD medication, and 44.4% had received behavioral treatment for ADHD in the past year; nearly one third (30.1%) did not receive any ADHD-specific treatment. CONCLUSIONS: Pediatric ADHD remains an ongoing and expanding public health concern, as approximately 1 million more children had ever received an ADHD diagnosis in 2022 than in 2016. Estimates from the 2022 NSCH provide information on pediatric ADHD during the last full year of the COVID-19 pandemic and can be used by policymakers, government agencies, health care systems, public health practitioners, and other partners to plan for needs of children with ADHD.

Mental health encompasses a range of mental, emotional, social, and behavioral functioning and occurs along a continuum from good to poor. Previous research has documented that mental health among children and adolescents is associated with immediate and long-term physical health and chronic disease, health risk behaviors, social relationships, education, and employment. Public health surveillance of children's mental health can be used to monitor trends in prevalence across populations, increase knowledge about demographic and geographic differences, and support decision-making about prevention and intervention. Numerous federal data systems collect data on various indicators of children's mental health, particularly mental disorders. The 2013-2019 data from these data systems show that mental disorders begin in early childhood and affect children with a range of sociodemographic characteristics. During this period, the most prevalent disorders diagnosed among U.S. children and adolescents aged 3-17 years were attention-deficit/hyperactivity disorder and anxiety, each affecting approximately one in 11 (9.4%-9.8%) children. Among children and adolescents aged 12-17 years, one fifth (20.9%) had ever experienced a major depressive episode. Among high school students in 2019, 36.7% reported persistently feeling sad or hopeless in the past year, and 18.8% had seriously considered attempting suicide. Approximately seven in 100,000 persons aged 10-19 years died by suicide in 2018 and 2019. Among children and adolescents aged 3-17 years, 9.6%-10.1% had received mental health services, and 7.8% of all children and adolescents aged 3-17 years had taken medication for mental health problems during the past year, based on parent report. Approximately one in four children and adolescents aged 12-17 years reported having received mental health services during the past year. In federal data systems, data on positive indicators of mental health (e.g., resilience) are limited. Although no comprehensive surveillance system for children's mental health exists and no single indicator can be used to define the mental health of children or to identify the overall number of children with mental disorders, these data confirm that mental disorders among children continue to be a substantial public health concern. These findings can be used by public health professionals, health care providers, state health officials, policymakers, and educators to understand the prevalence of specific mental disorders and other indicators of mental health and the challenges related to mental health surveillance.

OBJECTIVE: There is a need for a systematic method to implement the World Health Organization's Clinical Progression Scale (WHO-CPS), an ordinal clinical severity score for coronavirus disease 2019 patients, to electronic health record (EHR) data. We discuss our process of developing guiding principles mapping EHR data to WHO-CPS scores across multiple institutions. MATERIALS AND METHODS: Using WHO-CPS as a guideline, we developed the technical blueprint to map EHR data to ordinal clinical severity scores. We applied our approach to data from 2 medical centers. RESULTS: Our method was able to classify clinical severity for 100% of patient days for 2756 patient encounters across 2 institutions. DISCUSSION: Implementing new clinical scales can be challenging; strong understanding of health system data architecture was integral to meet the clinical intentions of the WHO-CPS. CONCLUSION: We describe a detailed blueprint for how to apply the WHO-CPS scale to patient data from the EHR.

Candida auris is a newly emerged multidrug-resistant fungus capable of causing invasive infections with high mortality. Despite intense efforts to understand how this pathogen rapidly emerged and spread worldwide, its environmental reservoirs are poorly understood. Here, we present a collaborative effort between the U.S. Centers for Disease Control and Prevention, the National Center for Biotechnology Information, and GridRepublic (a volunteer computing platform) to identify C. auris sequences in publicly available metagenomic datasets. We developed the MetaNISH pipeline that uses SRPRISM to align sequences to a set of reference genomes and computes a score for each reference genome. We used MetaNISH to scan ~300,000 SRA metagenomic runs from 2010 onwards and identified five datasets containing C. auris reads. Finally, GridRepublic has implemented a prospective C. auris molecular monitoring system using MetaNISH and volunteer computing.

The ongoing multi-country cholera outbreaks deserve greater attention and higher prioritisation globally.1 Since the early 1800s, there have been seven characterised global outbreaks of cholera. The seventh and current pandemic has been causing considerable illness effects since the early 1960s.2 Most recently, floods, droughts, natural disasters, and conflicts have displaced millions of people who have restricted access to clean water and live in settings with poor sewage management and increasing disease risk, further increasing the devasting effect of cholera around the globe.3 Currently, 1 billion people are at risk of contracting cholera and, concerningly, 28 countries with outbreaks in 2023, and 24 countries with active outbreaks were recorded by WHO by Sept 10, 2023 alone.4 In addition, recent outbreaks have had a high case fatality rate.5 The average cholera case fatality rate reported globally in 2021 was 1·9% (2·9% in Africa), a significant increase above the accepted target rate (<1%) and the highest recorded in over a decade.1, 5 Preliminary data suggest a similar trend for 2022 and 2023.1 Cholera is an old adversary that is both preventable and treatable.5 Despite widespread calls for strengthened pandemic preparedness and response, the global public health community are failing to apply lessons learned from COVID-19 to old challenges such as cholera. A key lesson learned from the COVID-19 pandemic is that early, rapid, and aggressive action is crucial in implementing public health interventions and countermeasure development.6

In 2021, non-Hispanic Asian (Asian) adults aged ≥18 years were the most likely to receive an influenza vaccination in the past 12 months (57.1%) followed by non-Hispanic White (White) (53.3%) adults; Hispanic or Latino (Hispanic) and non-Hispanic Black or African American (Black) adults were the least likely to receive an influenza vaccination (37.7% and 37.9%, respectively). Among adults with family incomes 100%–199% and ≥200% of FPL, Hispanic and Black adults were significantly less likely than Asian and White adults were to receive an influenza vaccination. Among adults with family incomes <100% of FPL, the differences among Hispanic, Black, and White adults were not statistically significant, but the percentage who had received an influenza vaccination in each of these groups was lower than the percentage among Asian adults. Vaccination coverage increased significantly with each increasing level of family income for White adults only.

While many transmission models have been developed for community spread of respiratory pathogens, less attention has been given to modeling the interdependence of disease introduction and spread seen in congregate settings, such as prisons or nursing homes. As demonstrated by the explosive outbreaks of COVID-19 seen in congregate settings, the need for effective outbreak prevention and mitigation strategies for these settings is critical. Here we consider how interventions that decrease the size of the susceptible populations, such as vaccination or depopulation, impact the expected number of infections due to outbreaks. Introduction of disease into the resident population from the community is modeled as a branching process, while spread between residents is modeled via a compartmental model. Control is modeled as a proportional decrease in both the number of susceptible residents and the reproduction number. We find that vaccination or depopulation can have a greater than linear effect on anticipated infections. For example, assuming a reproduction number of 3.0 for density-dependent COVID-19 transmission, we find that reducing the size of the susceptible population by 20% reduced overall disease burden by 47%. We highlight the California state prison system as an example for how these findings provide a quantitative framework for implementing infection control in congregate settings. Additional applications of our modeling framework include optimizing the distribution of residents into independent residential units, and comparison of preemptive versus reactive vaccination strategies.

Background: The Eastern European country of Georgia initiated a nationwide hepatitis C virus (HCV) elimination program in 2015 to address a high burden of infection. Screening for HCV infection through antibody testing was integrated into multiple existing programs, including the National Tuberculosis Program (NTP). We sought to evaluate loss to follow-up (LTFU) from the hepatitis C care cascade among persons diagnosed with active tuberculosis (TB) disease. Method(s): Using national ID numbers, we merged databases of the HCV elimination program, NTP, and national death registry from January 1, 2015, to September 30, 2020. We estimated the proportion of patients with and without TB who were LTFU at each step of the HCV care cascade and explored temporal changes. Result(s): Among 11,985 patients with active TB, 9,065 (76%) were tested for HCV antibodies, and 1,665 (18%) had a positive result; LTFU from hepatitis C care was common, with 20% of patients with a positive antibody test not undergoing viremia testing, and 43% of patients with viremia not starting treatment for hepatitis C. Overall, among persons with confirmed viremic HCV infection, only 28% of patients with TB had a documented cure from HCV infection, compared to 55% among patients without TB. LTFU after positive antibody testing substantially decreased in the last three years, from 32% among patients diagnosed with TB in 2017 to 12% among those diagnosed in 2019. Conclusion(s): LTFU from hepatitis C care after a positive antibody or viremia test was high and more common among patients with TB than in those without TB. Better integration of TB and hepatitis C care systems can potentially reduce LTFU and improve patient outcomes. Existing large-scale programs for both TB and hepatitis C in Georgia create a unique opportunity for such integration to contribute to hepatitis C elimination efforts. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

BACKGROUND: The Eastern European country of Georgia initiated a nationwide hepatitis C virus (HCV) elimination program in 2015 to address a high burden of infection. Screening for HCV infection through antibody testing was integrated into multiple existing programs, including the National Tuberculosis Program (NTP). We sought to compare the hepatitis C care cascade among patients with and without tuberculosis (TB) diagnosis in Georgia between 2015 and 2019 and to identify factors associated with loss to follow-up (LTFU) in hepatitis C care among patients with TB. METHODS AND FINDINGS: Using national ID numbers, we merged databases of the HCV elimination program, NTP, and national death registry from January 1, 2015 to September 30, 2020. The study population included 11,985 adults (aged ≥18 years) diagnosed with active TB from January 1, 2015 through December 31, 2019, and 1,849,820 adults tested for HCV antibodies between January 1, 2015 and September 30, 2020, who were not diagnosed with TB during that time. We estimated the proportion of patients with and without TB who were LTFU at each step of the HCV care cascade and explored temporal changes. Among 11,985 patients with active TB, 9,065 (76%) patients without prior hepatitis C treatment were tested for HCV antibodies, of which 1,665 (18%) had a positive result; LTFU from hepatitis C care was common, with 316 of 1,557 (20%) patients with a positive antibody test not undergoing viremia testing and 443 of 1,025 (43%) patients with viremia not starting treatment for hepatitis C. Overall, among persons with confirmed viremic HCV infection, due to LTFU at various stages of the care cascade only 28% of patients with TB had a documented cure from HCV infection, compared to 55% among patients without TB. LTFU after positive antibody testing substantially decreased in the last 3 years, from 32% among patients diagnosed with TB in 2017 to 12% among those diagnosed in 2019. After a positive HCV antibody test, patients without TB had viremia testing sooner than patients with TB (hazards ratio [HR] = 1.46, 95% confidence intervals [CI] [1.39, 1.54], p < 0.001). After a positive viremia test, patients without TB started hepatitis C treatment sooner than patients with TB (HR = 2.05, 95% CI [1.87, 2.25], p < 0.001). In the risk factor analysis adjusted for age, sex, and case definition (new versus previously treated), multidrug-resistant (MDR) TB was associated with an increased risk of LTFU after a positive HCV antibody test (adjusted risk ratio [aRR] = 1.41, 95% CI [1.12, 1.76], p = 0.003). The main limitation of this study was that due to the reliance on existing electronic databases, we were unable to account for the impact of all confounding factors in some of the analyses. CONCLUSIONS: LTFU from hepatitis C care after a positive antibody or viremia test was high and more common among patients with TB than in those without TB. Better integration of TB and hepatitis C care systems can potentially reduce LTFU and improve patient outcomes both in Georgia and other countries that are initiating or scaling up their nationwide hepatitis C control efforts and striving to provide personalized TB treatment.

COVID-19 outbreaks in congregate settings remain a serious threat to the health of disproportionately affected populations such as people experiencing incarceration or homelessness, the elderly, and essential workers. An individual-based model accounting for individual infectiousness over time, staff work schedules, and testing and isolation schedules was developed to simulate community transmission of SARS-CoV-2 to staff in a congregate facility and subsequent transmission within the facility that could cause an outbreak. Systematic testing strategies in which staff are tested on the first day of their workweek were found to prevent up to 16% more infections than testing strategies unrelated to staff schedules. Testing staff at the beginning of their workweek, implementing timely isolation following testing, limiting test turnaround time, and increasing test frequency in high transmission scenarios can supplement additional mitigation measures to aid outbreak prevention in congregate settings.

Data System. Federal health surveys, like the National Health Interview Survey (NHIS), represent important surveillance mechanisms for collecting timely, representative data that can be used to monitor the health and health care of the US population. Data Collection/Processing. Conducted by the National Center for Health Statistics (NCHS), NHIS uses an address-based, complex clustered sample of housing units, yielding data representative of the civilian noninstitutionalized US population. Survey redesigns that reduce survey length and eliminate proxy reporting may reduce respondent burden and increase participation. Such were goals in 2019, when NCHS implemented a redesigned NHIS questionnaire that also focused on topics most relevant and appropriate for surveillance of child and adult health. Data Analysis/Dissemination. Public-use microdata files and selected health estimates and detailed documentation are released online annually. Public Health Implications. Declining response rates may lead to biased estimates and weaken users' ability to make valid conclusions from the data, hindering public health efforts. The 2019 NHIS questionnaire redesign was associated with improvements in the survey's response rate, declines in respondent burden, and increases in data quality and survey relevancy. (Am J Public Health. Published online ahead of print February 9, 2023:e1-e8. https://doi.org/10.2105/AJPH.2022.307197).

OBJECTIVE: The Baby Pediatric Symptom Checklist (BPSC) is a screening tool developed for detecting behavioral or emotional concerns among parents of children younger than 18 months. Nationally representative survey data have not yet been used to assess the validity of the BPSC, nor to evaluate its appropriateness for use among children between 18 and 23 months old. The current study assesses the validity of the BPSC using data from the National Health Interview Survey (NHIS). METHODS: Data from the 2019 NHIS were used to evaluate the 12-item BPSC screening tool among a nationally representative sample of children 2-23 months. Confirmatory factor analysis (CFA) and differential item functioning (DIF) were used to assess construct and predictive validity and test how response items differed by selected sociodemographics. Quantile regression was used to calculate 50(th), 70(th), and 90(th) percentiles for age-based normative curves of the previously established domains of irritability, inflexibility, and difficulty with routines. RESULTS: A three-factor CFA produced comparable results to the original study. Tests of DIF did not reveal any significant effects for the child's sex, race and Hispanic origin, household urbanization level, number of children in family, or respondent type (mother, father, other). In addition, DIF was not found between children aged 2-17 months and 18-23 months. Age-based normative data were calculated for each subscale. CONCLUSIONS: The use of the BPSC in a nationally representative survey produced findings comparable to those of the original-validation study. The NHIS can be used to track BPSC scores over time at the population-level.

BACKGROUND: Hepatitis C virus (HCV) infection causes dysregulation and suppression of immune pathways involved in the control of tuberculosis (TB) infection. However, data on the role of chronic hepatitis C as a risk factor for active TB are lacking. We sought to evaluate the association between HCV infection and the development of active TB. METHODS: We conducted a cohort study in Georgia among adults tested for HCV antibodies (January 2015 - September 2o2o) and followed longitudinally for the development of newly diagnosed active TB. Data were obtained from the Georgian National programs of hepatitis C and TB. The exposures of interest were untreated and treated HCV infection. Cox proportional hazards model was used to calculate adjusted hazards ratios. RESULTS: A total of 1,828,808 adults were included (median follow-up time: 26 months, IQR: 13-39 months). Active TB was diagnosed in 3,163 (0.17%) individuals after a median of 6 months follow-up (IQR: 1-18 months). The incidence rate per 100,000 person-years was 296 among persons with untreated HCV infection, 109 among those with treated HCV infection, and 65 among HCV-negative persons. In multivariable analysis, both untreated (aHR=2.9, 95%CI: 2.4-3.4) and treated (aHR=1.6, 95%CI: 1.4-2.0) HCV infection were associated with a higher hazard of active TB, compared to HCV-negative persons. CONCLUSIONS: Adults with HCV infection, particularly untreated individuals, were at higher risk of developing active TB disease. Screening for latent TB infection and active TB disease should be part of clinical evaluation of people with HCV infection, especially in high TB burden areas.

PURPOSE: The COVID-19 pandemic caused disruptions to children's daily lives due in part to stay-at-home orders and school closures, reducing interactions with both peers and extended family. Yet, few studies with nationally representative data have explored the potential association of the COVID-19 pandemic and children's mental health. METHODS: The current study analyzed data from the 2019 and 2020 National Health Interview Survey (NHIS) to describe changes in the prevalence of symptoms of anxiety and depression before and during the first year of the pandemic among children aged 5-17 years. Changes in prevalence by child- and family-level characteristics were also examined. RESULTS: During the COVID-19 pandemic, nearly one in six children aged 5-17 years had daily or weekly symptoms of anxiety or depression, a significant increase from before the COVID-pandemic (16.7% (95% CI:15.0-18.6) vs. 14.4% (95% CI:13.4-15.3)). Males, children 5-11 years, non-Hispanic children, children living in families in large metropolitan areas, incomes at or below the federal poverty level, and whose highest educated parent had more than a HS education, also showed statistically significant increases in anxiety and depression symptoms. CONCLUSIONS: NHIS data may be used to monitor this increase in mental health symptomatology and assist in identifying children at risk.

The explosive outbreaks of COVID-19 seen in congregate settings such as prisons and nursing homes, has highlighted a critical need for effective outbreak prevention and mitigation strategies for these settings. Here we consider how different types of control interventions impact the expected number of symptomatic infections due to outbreaks. Introduction of disease into the resident population from the community is modeled as a stochastic point process coupled to a branching process, while spread between residents is modeled via a deterministic compartmental model that accounts for depletion of susceptible individuals. Control is modeled as a proportional decrease in the number of susceptible residents, the reproduction number, and/or the proportion of symptomatic infections. This permits a range of assumptions about the density dependence of transmission and modes of protection by vaccination, depopulation and other types of control. We find that vaccination or depopulation can have a greater than linear effect on the expected number of cases. For example, assuming a reproduction number of 3.0 with density-dependent transmission, we find that preemptively reducing the size of the susceptible population by 20% reduced overall disease burden by 47%. In some circumstances, it may be possible to reduce the risk and burden of disease outbreaks by optimizing the way a group of residents are apportioned into distinct residential units. The optimal apportionment may be different depending on whether the goal is to reduce the probability of an outbreak occurring, or the expected number of cases from outbreak dynamics. In other circumstances there may be an opportunity to implement reactive disease control measures in which the number of susceptible individuals is rapidly reduced once an outbreak has been detected to occur. Reactive control is most effective when the reproduction number is not too high, and there is minimal delay in implementing control. We highlight the California state prison system as an example for how these findings provide a quantitative framework for understanding disease transmission in congregate settings. Our approach and accompanying interactive website (https://phoebelu.shinyapps.io/DepopulationModels/) provides a quantitative framework to evaluate the potential impact of policy decisions governing infection control in outbreak settings.

OBJECTIVE: To provide state-level estimates of diagnosed ADHD and associated treatment among children in the United States in 2016 to 2019. METHOD: This study used the National Survey of Children's Health to produce national and state-level estimates of lifetime diagnosis and current ADHD among all children aged 3 to 17 years (n=114,476), and national and state-level estimates of medication and behavioral treatment use among children with current ADHD. RESULTS: The state-level estimates of diagnosed ADHD ranged from 6.1% to 16.3%. Among children with current ADHD, state-level estimates of ADHD medication usage ranged from 37.8% to 81.4%, and state-level estimates of behavioral treatment ranged from 38.8% to 61.8%. CONCLUSION: There was substantial state-level variation for indicators of ADHD diagnosis and associated treatment. These state-level results can be used by policymakers, public health practitioners, health care providers, and other stakeholders to help address the service needs of children with ADHD in their states.

High-quality data are accurate, relevant, and timely. Large national health surveys have always balanced the implementation of these quality dimensions to meet the needs of diverse users. The COVID-19 pandemic shifted these balances, with both disrupted survey operations and a critical need for relevant and timely health data for decision-making. The National Health Interview Survey (NHIS) responded to these challenges with several operational changes to continue production in 2020. However, data files from the 2020 NHIS were not expected to be publicly available until fall 2021. To fill the gap, the National Center for Health Statistics (NCHS) turned to 2 online data collection platforms-the Census Bureau's Household Pulse Survey (HPS) and the NCHS Research and Development Survey (RANDS)-to collect COVID-19‒related data more quickly. This article describes the adaptations of NHIS and the use of HPS and RANDS during the pandemic in the context of the recently released Framework for Data Quality from the Federal Committee on Statistical Methodology. (Am J Public Health. 2021;111(12):2167-2175. https://doi.org/10.2105/AJPH.2021.306516).

INTRODUCTION: We describe epidemiology and outcomes of confirmed SARS-CoV-2 infection and positive admissions among children <18 years in South Africa, an upper-middle income setting with high inequality. METHODS: Laboratory and hospital COVID-19 surveillance data, 28 January - 19 September 2020 was used. Testing rates were calculated as number of tested for SARS-CoV-2 divided by population at risk; test positivity rates were calculated as positive tests divided by total number of tests. In-hospital case fatality ratio (CFR) was calculated based on hospitalized positive admissions with outcome data who died in-hospital and whose death was judged SARS-CoV-2 related by attending physician. FINDINGS: 315 570 children aged <18 years were tested for SARS-CoV-2; representing 8.9% of all 3 548 738 tests and 1.6% of all children in the country. Of children tested, 46 137 (14.6%) were positive. Children made up 2.9% (n = 2007) of all SARS-CoV-2 positive admissions to sentinel hospitals. Among children, 47 died (2.6% case-fatality). In-hospital deaths were associated with male sex [adjusted odds ratio (aOR) 2.18 (95% confidence intervals [CI] 1.08-4.40)] vs female; age <1 year [aOR 4.11 (95% CI 1.08-15.54)], age 10-14 years [aOR 4.20 (95% CI1.07-16.44)], age 15-17 years [aOR 4.86 (95% 1.28-18.51)] vs age 1-4 years; admission to a public hospital [aOR 5.07(95% 2.01-12.76)] vs private hospital and ≥1 underlying conditions [aOR 12.09 (95% CI 4.19-34.89)] vs none. CONCLUSIONS: Children with underlying conditions were at greater risk of severe SARS-CoV-2 outcomes. Children > 10 years, those in certain provinces and those with underlying conditions should be considered for increased testing and vaccination.

BACKGROUND: We describe the epidemiology of COVID-19 in South Africa following importation and during implementation of stringent lockdown measures. METHODS: Using national surveillance data including demographics, laboratory test data, clinical presentation, risk exposures (travel history, contacts and occupation) and outcomes of persons undergoing COVID-19 testing or hospitalised with COVID-19 at sentinel surveillance sites, we generated and interpreted descriptive statistics, epidemic curves, and initial reproductive numbers (Rt). FINDINGS: From 4 March to 30 April 2020, 271,670 SARS-CoV-2 PCR tests were performed (462 tests/100,000 persons). Of these, 7,892 (2.9%) persons tested positive (median age 37 years (interquartile range 28-49 years), 4,568 (58%) male, cumulative incidence of 13.4 cases/100,000 persons). Hospitalization records were found for 1,271 patients (692 females (54%)) of whom 186 (14.6%) died. Amongst 2,819 cases with data, 489/2819 (17.3%) travelled internationally within 14 days prior to diagnosis, mostly during March 2020 (466 (95%)). Cases diagnosed in April compared with March were younger (median age, 37 vs. 40 years), less likely female (38% vs. 53%) and resident in a more populous province (98% vs. 91%). The national initial R(t) was 2.08 (95% confidence interval (CI): 1.71-2.51). INTERPRETATION: The first eight weeks following COVID-19 importation were characterised by early predominance of imported cases and relatively low mortality and transmission rates. Despite stringent lockdown measures, the second month following importation was characterised by community transmission and increasing disease burden in more populous provinces.

Recent studies indicate an increase in the percentage of adults who reported clinically relevant symptoms of anxiety and depression during the COVID-19 pandemic (1-3). For example, based on U.S. Census Bureau Household Pulse Survey (HPS) data, CDC reported significant increases in symptoms of anxiety and depressive disorders among adults aged ≥18 years during August 19, 2020-February 1, 2021, with the largest increases among adults aged 18-29 years and among those with less than a high school education (1). To assess more recent national trends, as well as state-specific trends, CDC used HPS data (4) to assess trends in reported anxiety and depression among U.S. adults in all 50 states and the District of Columbia (DC) during August 19, 2020-June 7, 2021 (1). Nationally, the average anxiety severity score increased 13% from August 19-31, 2020, to December 9-21, 2020 (average percent change [APC] per survey wave = 1.5%) and then decreased 26.8% from December 9-21, 2020, to May 26-June 7, 2021 (APC = -3.1%). The average depression severity score increased 14.8% from August 19-31, 2020, to December 9-21, 2020 (APC = 1.7%) and then decreased 24.8% from December 9-21, 2020, to May 26-June 7, 2021 (APC = -2.8%). State-specific trends were generally similar to national trends, with both anxiety and depression scores for most states peaking during the December 9-21, 2020, or January 6-18, 2021, survey waves. Across the entire study period, the frequency of anxiety and depression symptoms was positively correlated with the average number of daily COVID-19 cases. Mental health services and resources, including telehealth behavioral services, are critical during the COVID-19 pandemic.

BACKGROUND: The interaction between COVID-19, non-communicable diseases, and chronic infectious diseases such as HIV and tuberculosis is unclear, particularly in low-income and middle-income countries in Africa. South Africa has a national HIV prevalence of 19% among people aged 15-49 years and a tuberculosis prevalence of 0·7% in people of all ages. Using a nationally representative hospital surveillance system in South Africa, we aimed to investigate the factors associated with in-hospital mortality among patients with COVID-19. METHODS: In this cohort study, we used data submitted to DATCOV, a national active hospital surveillance system for COVID-19 hospital admissions, for patients admitted to hospital with laboratory-confirmed SARS-CoV-2 infection between March 5, 2020, and March 27, 2021. Age, sex, race or ethnicity, and comorbidities (hypertension, diabetes, chronic cardiac disease, chronic pulmonary disease and asthma, chronic renal disease, malignancy in the past 5 years, HIV, and past and current tuberculosis) were considered as risk factors for COVID-19-related in-hospital mortality. COVID-19 in-hospital mortality, the main outcome, was defined as a death related to COVID-19 that occurred during the hospital stay and excluded deaths that occurred because of other causes or after discharge from hospital; therefore, only patients with a known in-hospital outcome (died or discharged alive) were included. Chained equation multiple imputation was used to account for missing data and random-effects multivariable logistic regression models were used to assess the role of HIV status and underlying comorbidities on COVID-19 in-hospital mortality. FINDINGS: Among the 219 265 individuals admitted to hospital with laboratory-confirmed SARS-CoV-2 infection and known in-hospital outcome data, 51 037 (23·3%) died. Most commonly observed comorbidities among individuals with available data were hypertension in 61 098 (37·4%) of 163 350, diabetes in 43 885 (27·4%) of 159 932, and HIV in 13 793 (9·1%) of 151 779. Tuberculosis was reported in 5282 (3·6%) of 146 381 individuals. Increasing age was the strongest predictor of COVID-19 in-hospital mortality. Other factors associated were HIV infection (adjusted odds ratio 1·34, 95% CI 1·27-1·43), past tuberculosis (1·26, 1·15-1·38), current tuberculosis (1·42, 1·22-1·64), and both past and current tuberculosis (1·48, 1·32-1·67) compared with never tuberculosis, as well as other described risk factors for COVID-19, such as male sex; non-White race; underlying hypertension, diabetes, chronic cardiac disease, chronic renal disease, and malignancy in the past 5 years; and treatment in the public health sector. After adjusting for other factors, people with HIV not on antiretroviral therapy (ART; adjusted odds ratio 1·45, 95% CI 1·22-1·72) were more likely to die in hospital than were people with HIV on ART. Among people with HIV, the prevalence of other comorbidities was 29·2% compared with 30·8% among HIV-uninfected individuals. Increasing number of comorbidities was associated with increased COVID-19 in-hospital mortality risk in both people with HIV and HIV-uninfected individuals. INTERPRETATION: Individuals identified as being at high risk of COVID-19 in-hospital mortality (older individuals and those with chronic comorbidities and people with HIV, particularly those not on ART) would benefit from COVID-19 prevention programmes such as vaccine prioritisation as well as early referral and treatment. FUNDING: South African National Government.

IMPORTANCE: Immunodeficiency-related, vaccine-derived rubella virus (RuV) as an antigenic trigger of cutaneous and visceral granulomas is a rare, recently described phenomenon in children and young adults treated with immunosuppressant agents. OBJECTIVE: To perform a comprehensive clinical, histologic, immunologic, molecular, and genomic evaluation to elucidate the potential cause of an adult patient's atypical cutaneous granulomas. DESIGN, SETTING, AND PARTICIPANTS: A prospective evaluation of skin biopsies, nasopharyngeal swabs, and serum samples submitted to the Centers for Disease Control and Prevention was conducted to assess for RuV using real-time reverse-transcriptase polymerase chain reaction (RT-PCR) and viral genomic sequencing. The samples were obtained from a man in his 70s with extensive cutaneous granulomas mimicking both cutaneous sarcoidosis (clinically) and CD8+ granulomatous cutaneous T-cell lymphoma (histopathologically). The study was conducted from September 2019 to February 2021. MAIN OUTCOMES AND MEASURES: Identification and genotyping of a novel immunodeficiency-related RuV-associated granulomatous dermatitis. RESULTS: Immunohistochemistry for RuV capsid protein and RT-PCR testing for RuV RNA revealed RuV in 4 discrete skin biopsies from different body sites. In addition, RuV RNA was detected in the patient's nasopharyngeal swabs by RT-PCR. The full viral genome was sequenced from the patient's skin biopsy (RVs/Philadelphia.PA.USA/46.19/GR, GenBank Accession #MT249313). The patient was ultimately diagnosed with a novel RuV-associated granulomatous dermatitis. CONCLUSIONS AND RELEVANCE: The findings of this study suggest that clinicians and pathologists may consider RuV-associated granulomatous dermatitis during evaluation of a patient because it might have implications for the diagnosis of cutaneous sarcoidosis, with RuV serving as a potential antigenic trigger, and for the diagnosis of granulomatous cutaneous T-cell lymphoma, with histopathologic features that may prompt an evaluation for immunodeficiency and/or RuV.

The spread of disease and increase in deaths during large outbreaks of transmissible diseases is often associated with fear and grief (1). Social restrictions, limits on operating nonessential businesses, and other measures to reduce pandemic-related mortality and morbidity can lead to isolation and unemployment or underemployment, further increasing the risk for mental health problems (2). To rapidly monitor changes in mental health status and access to care during the COVID-19 pandemic, CDC partnered with the U.S. Census Bureau to conduct the Household Pulse Survey (HPS). This report describes trends in the percentage of adults with symptoms of an anxiety disorder or a depressive disorder and those who sought mental health services. During August 19, 2020-February 1, 2021, the percentage of adults with symptoms of an anxiety or a depressive disorder during the past 7 days increased significantly (from 36.4% to 41.5%), as did the percentage reporting that they needed but did not receive mental health counseling or therapy during the past 4 weeks (from 9.2% to 11.7%). Increases were largest among adults aged 18-29 years and among those with less than a high school education. HPS data can be used in near real time to evaluate the impact of strategies that address mental health status and care of adults during the COVID-19 pandemic and to guide interventions for groups that are disproportionately affected.

BACKGROUND: Most tuberculosis (TB) disease in the U.S. is attributed to reactivation of remotely acquired latent TB infection (LTBI) in non-U.S.-born persons who were likely infected with Mycobacterium tuberculosis in their countries of birth. Information on LTBI prevalence by country of birth could help guide local providers and health departments to scale up the LTBI screening and preventive treatment needed to advance progress towards TB elimination. METHODS: 13 805 non-U.S.-born persons at high risk of TB infection or progression to TB disease were screened for LTBI at 16 clinical sites located across the United States with a tuberculin skin test, QuantiFERON ® Gold In-Tube test, and T-SPOT ®.TB test. Bayesian latent class analysis was applied to test results to estimate LTBI prevalence and associated credible intervals (CRI) for each country or world region of birth. RESULTS: Among the study population, the estimated LTBI prevalence was 31% (95% CRI 26% - 35%). Country-of-birth-level LTBI prevalence estimates were highest for persons born in Haiti, Peru, Somalia, Ethiopia, Vietnam, and Bhutan, ranging from 42%-55%. LTBI prevalence estimates were lowest for persons born in Colombia, Malaysia, and Thailand, ranging from 8%-13%. CONCLUSIONS: LTBI prevalence in persons born outside the United States varies widely by country. These estimates can help target community outreach efforts to the highest risk groups.

OBJECTIVE: Bibliometric analyses are commonly used to measure the productivity of researchers or institutions but rarely used to assess the scientific contribution of national surveys/datasets. We applied bibliometric methods to quantify the contributions of the National Survey of Children's Health (NSCH) and the National Survey of Children with Special Health Care Needs (NS-CSHCN) to the body of pediatric health-related research. We also examined dissemination to non-research audiences by analyzing media coverage of statistics and research produced from the surveys. METHODS: We conducted a search of the Web of Science database to identify peer-reviewed articles related to the NSCH and NS-CSHCN published between 2002 and 2019. We summarized information about citation counts, publishing journals, key research areas, and institutions using the surveys. We used the Lexis Advance database Nexis to assess media coverage. RESULTS: The publication set included 716 NSCH/NS-CSHCN journal articles published between 2002 and June 2019. These publications have in turn been cited 22,449 times, including in 1,614 review articles. Over 180 journals have published NSCH/NS-CSHCN articles, and the most commonly covered research areas are in pediatrics; public, environmental and occupational health; psychology; and health care sciences and services. Over 500 institutions have used NSCH/NS-CSHCN data to publish journal articles, and over 950 news media articles have cited statistics or research produced by the surveys. CONCLUSIONS: NSCH/NS-CSHCN data are widely used by government, academic, and media institutions. Bibliometric methods provide a systematic approach to quantify and describe the contributions to the scientific literature made possible with these data.

BACKGROUND: Sixty cases of rabies in international travellers from 1990 to 2012 were previously reviewed. We present here an update of rabies cases in international travellers from 2013 to 2019. METHODS: We systematically reviewed the existing literature and collected 23 cases of rabies in individuals who crossed an international border between the time of infection and diagnosis, or who were infected following expatriation or migration. RESULTS: Most cases were in male adult travellers and diagnosed in Europe and the Middle East, with most exposures in Asia or in Africa. Migrants originating from rabies-endemic low-and-middle income countries and their descendants accounted for two thirds of cases. Other cases were in tourists, business travellers and expatriates. Median travel duration (excluding migration trip) was 60 days (range 7-240 days). Most cases were due to dog bites and most common clinical presentation was furious rabies. In most patients (74%), no rabies post-exposure prophylaxis (RPEP) was administered before rabies symptoms appeared. Other patients received incomplete RPEP series. CONCLUSION: Rabies should be suspected in any patient with encephalitis or paralysis who travelled to, or migrated from a rabies-endemic country. Comprehensive information about a rabies risk should be given to travellers to rabies endemic countries, notably migrants visiting friends and relatives.

BACKGROUND: An outbreak of listeriosis was identified in South Africa in 2017. The source was unknown. METHODS: We conducted epidemiologic, trace-back, and environmental investigations and used whole-genome sequencing to type Listeria monocytogenes isolates. A case was defined as laboratory-confirmed L. monocytogenes infection during the period from June 11, 2017, to April 7, 2018. RESULTS: A total of 937 cases were identified, of which 465 (50%) were associated with pregnancy; 406 of the pregnancy-associated cases (87%) occurred in neonates. Of the 937 cases, 229 (24%) occurred in patients 15 to 49 years of age (excluding those who were pregnant). Among the patients in whom human immunodeficiency virus (HIV) status was known, 38% of those with pregnancy-associated cases (77 of 204) and 46% of the remaining patients (97 of 211) were infected with HIV. Among 728 patients with a known outcome, 193 (27%) died. Clinical isolates from 609 patients were sequenced, and 567 (93%) were identified as sequence type 6 (ST6). In a case-control analysis, patients with ST6 infections were more likely to have eaten polony (a ready-to-eat processed meat) than those with non-ST6 infections (odds ratio, 8.55; 95% confidence interval, 1.66 to 43.35). Polony and environmental samples also yielded ST6 isolates, which, together with the isolates from the patients, belonged to the same core-genome multilocus sequence typing cluster with no more than 4 allelic differences; these findings showed that polony produced at a single facility was the outbreak source. A recall of ready-to-eat processed meat products from this facility was associated with a rapid decline in the incidence of L. monocytogenes ST6 infections. CONCLUSIONS: This investigation showed that in a middle-income country with a high prevalence of HIV infection, L. monocytogenes caused disproportionate illness among pregnant girls and women and HIV-infected persons. Whole-genome sequencing facilitated the detection of the outbreak and guided the trace-back investigations that led to the identification of the source.