During an outbreak investigation of infections following apheresis platelet transfusion, a potentially novel species in the Acinetobacter calcoaceticus-baumannii complex was identified. Here, we report the hybrid Nanopore-Illumina assembly resulting in a complete circular genome sequence of a strain of this species isolated from apheresis platelet product collected during the investigation.

We assessed the impact of pneumococcal conjugate vaccines on pneumococcal otitis media (OM) among children living in Navajo and White Mountain Apache Tribal lands. During the PCV7 era (2000-2009), the proportion of vaccine-type OM declined. However, vaccine-type OM (predominantly 3, 19A, and 19F) persisted in the PCV13 era (2010-2019).

OBJECTIVES: On July 28, 2022, eastern Kentucky experienced the state's deadliest flood in recorded history. In response to ongoing mental health concerns from community members who survived the flood, local health department directors in affected communities requested technical assistance from the Kentucky Department for Public Health and the Centers for Disease Control and Prevention. METHODS: Two simultaneous Community Assessments for Public Health Emergency Response (CASPERs) were conducted 6 weeks after the flood. Four counties were assessed in each CASPER. EpiInfo7 was used to calculate the unweighted and weighted frequencies and percentages to estimate the number and percentage of households with a particular response in each CASPER. RESULTS: Approximately a third (30.5%) of households in CASPER 1 and approximately 40% of households in CASPER 2 reported experiencing ≥1 mental health problems. Individual-level mental health questions from a modified 3-stage CASPER found approximately 15% of persons in both CASPERs reported a Patient Health Questionnaire-2 (PHQ-2) score ≥3 and approximately 20% of persons in both CASPERs reported Generalized Anxiety Disorder-2 (GAD-2) score ≥3. CONCLUSIONS: These findings indicated households experienced mental health problems after the flood. Depression and anxiety were prevalent among persons living in flood-affected areas. If ever needed, households preferred to receive mental health services in-person and locally.

OBJECTIVE: The resurgence of syphilis in the United States presents a significant public health challenge. Much of the information needed for syphilis surveillance resides in electronic health records (EHRs). In this manuscript, we describe a surveillance platform for automating the extraction of EHR data, known as SmartChart Suite, and the results from a pilot. MATERIALS AND METHODS: The SmartChart Suite framework has been developed in compliance with the HHS Health IT Alignment Policy. The platform's major functionalities are (1) data retrieval; (2) logical evaluation; (3) standardized data storage; and (4) results display. The SmartChart Suite was deployed in September 2023 at the Grady Health System in Atlanta, Georgia. We established a cohort of likely syphilis patients, randomly selected 50 medical records for manual and automated chart review, and analyzed the results. RESULTS: The SmartChart Suite was successfully deployed and integrated with the Epic EHR system at Grady. The overall performance results were precision of 97.6%, recall of 100.0%, and F-Score of 98.8. DISCUSSION: Automated abstraction of EHR data has significant potential to improve public health surveillance and case investigation processes while reducing the resource burden on health departments and reporters. The SmartChart Suite comprises a flexible open-source solution for registry development and maintenance across a wide spectrum of conditions and use cases. CONCLUSION: SmartChart Suite demonstrates the potential of automated chart abstraction to support disease surveillance. HHS-compliant open-source tools such as SmartChart Suite can support more efficient human review by providing accurate and relevant data for critical public health activities.

BACKGROUND: On July 28, 2022, floods in eastern Kentucky displaced over 600 individuals. With the goal of understanding mental health needs of affected families, we surveyed households living in flood evacuation shelters after the 2022 Kentucky floods. METHODS: Families experiencing displacement from the 2022 Kentucky floods currently living in three different temporary shelter locations were surveyed via convenience sampling. A rapid community needs assessment involving in-person interviews using modified two stage cluster methodology (CASPER) was conducted between September 6-9, 2022. RESULTS: Teams conducted 61 household interviews. Since the flood, 27.7% reported that their household received services from behavioral health and 19.6% received grief counseling. Experiencing agitation (36.7%), difficulty concentrating (47.5%), nightmares (62.3%), or suicidal thoughts/self-harm (6.6%) were reported by households surveyed. Over one-fourth (27.0%) of individuals surveyed reported being depressed nearly every day. Over 20% reported anhedonia (inability to feel pleasure) nearly every day. Over 75% of individuals surveyed reported being anxious several days or more over the last two weeks. Over one-third of individuals (34.0%) reported being unable to stop worrying nearly every day. Of those individuals surveyed, 36.1% reported barriers to mental health services. CONCLUSIONS: Symptoms of depressed mood, anhedonia, anxiety, and nightmares were prevalent in displaced families six weeks after the 2022 Kentucky floods. Providing and encouraging access to mental health services are important priorities during disaster recovery.

Diagnostic approaches that combine the high sensitivity and specificity of laboratory-based digital detection with the ease of use and affordability of point-of-care (POC) technologies could revolutionize disease diagnostics. This is especially true in infectious disease diagnostics, where rapid and accurate pathogen detection is critical to curbing the spread of disease. We have pioneered an innovative label-free digital detection platform that utilizes Interferometric Reflectance Imaging Sensor (IRIS) technology. IRIS leverages light interference from an optically transparent thin film, eliminating the need for complex optical resonances to enhance the signal by harnessing light interference and the power of signal averaging in shot-noise-limited operation In our latest work, we have further improved our previous 'Single-Particle' IRIS (SP-IRIS) technology by allowing the construction of the optical signature of target nanoparticles (whole virus) from a single image. This new platform, 'Pixel-Diversity' IRIS (PD-IRIS), eliminated the need for z-scan acquisition, required in SP-IRIS, a time-consuming and expensive process, and made our technology more applicable to POC settings. Using PD-IRIS, we quantitatively detected the Monkeypox virus (MPXV), the etiological agent for Monkeypox (Mpox) infection. MPXV was captured by anti-A29 monoclonal antibody (mAb 69-126-3) on Protein G spots on the sensor chips and were detected at a limit-of-detection (LOD) - of 200 PFU/mL (∼3.3 aM). PD-IRIS was superior to the laboratory-based ELISA (LOD - 1800 PFU/mL) used as a comparator. The specificity of PD-IRIS in MPXV detection was demonstrated using Herpes simplex virus, type 1 (HSV-1), and Cowpox virus (CPXV). This work establishes the effectiveness of PD-IRIS and opens possibilities for its advancement in clinical diagnostics of Mpox at POC. Moreover, PD-IRIS is a modular technology that can be adapted for the multiplex detection of pathogens for which high-affinity ligands are available that can bind their surface antigens to capture them on the sensor surface.

Hospital surfaces are known to contribute to the spread of healthcare-associated antimicrobial pathogens. Environmental sampling can help locate reservoirs and determine intervention strategies, although sampling and detection can be labor intensive. Composite approaches may help reduce time and costs associated with sampling and detection. We investigated optimum surface areas for sampling antimicrobial-resistant organisms (AROs) with a single side of cellulose sponge, created theoretical composites (TC) by adding recovery results from multiple optimum areas, then compared the TC to the standard Centers for Disease Control and Prevention sampling method (one sponge using all sides, whole tool; (WT)). Five AROs were evaluated: carbapenemase-producing KPC+ Klebsiella pneumoniae (KPC), Acinetobacter baumannii (AB), methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus faecalis (VRE) and Clostridioides difficile spores (CD). Steel coupons comprising four surface areas (323; 645; 1,290 and 2,258 cm2) were inoculated, dried, and sampled with one sampling pass using the larger side (face) or the smaller side (edge) of a pre-moistened cellulose sponge tool. Based on the optimum areas determined for each organism, composite areas were 1,290 cm2 for MRSA and VRE, 1,936 cm2 for AB, 2,580 cm2 for CD spores and 3,870 cm2 for KPC. Total colony forming units (CFU) recovered using a composite approach was greater or comparable than using multiple WT samplings (over the same area as the composite) for MRSA, VRE and AB (130%; 144% and 95%) yet less than if using multiple WT samplings for KP and CD (47% and 66%). We propose a conservative composite sampling strategy if the target organism is unknown; 323 cm2 sampling area for each of the four sides of the sponge, (1290 cm2 total). The conservative composite sampling strategy improved the recovery of KP (from 47% to 85% of multiple WT samplings), while MRSA, VRE, AB and CD (131%; 144%; 97% and 66%) remained within 5% to that of the optimum area TC.

Objectives: To (1) determine associations between maternal risk conditions and severe adverse outcomes that may benefit from risk-appropriate care and (2) assess whether associations between risk conditions and outcomes vary by level of maternal care (LoMC). Methods: We used the 2017-2019 National Inpatient Sample (NIS) to calculate associations between maternal risk conditions and severe adverse outcomes. Risk conditions included severe preeclampsia, placenta accreta spectrum (PAS) conditions, and cardiac conditions. Outcomes included disseminated intravascular coagulation (DIC) with blood products transfusion or shock, pulmonary edema or acute respiratory distress syndrome (ARDS), stroke, acute renal failure, and a composite cardiac outcome. Then we used 2019 delivery hospitalization data from five states linked to hospital LoMC. We calculated associations between risk conditions and outcomes overall and stratified by LoMC and assessed for effect modification by LoMC. Results: We found positive measures of association between risk conditions and outcomes. Among patients with severe preeclampsia or PAS, the magnitudes of the associations with DIC with blood products transfusion or shock, pulmonary edema or ARDS, and acute renal failure were lower in Level III/IV compared with <Level III facilities. Among patients with cardiac conditions, the magnitudes of the associations with these outcomes, along with stroke, were also lower in Level III/IV compared with <Level III facilities. The proportion of patients with risk conditions that delivered in <Level III facilities was 19.8-46.8%. Conclusions: Odds of severe adverse outcomes among women with selected risk conditions were lower for births occurring at higher-level facilities, supporting the benefit of risk-appropriate care.

BACKGROUND: Native Hawaiian and Pacific Islander (NHPI) adults have historically been grouped with Asian adults in U.S. mortality surveillance. Starting in 2018, the 1997 race and ethnicity standards from the U.S. Office of Management and Budget were adopted by all states on death certificates, enabling national-level estimates of cardiovascular disease (CVD) mortality for NHPI adults independent of Asian adults. OBJECTIVE: To describe CVD mortality among NHPI adults. DESIGN: Race-stratified age-standardized mortality rates (ASMRs) and rate ratios were calculated using final mortality data from the National Vital Statistics System for 2018 to 2022. SETTING: Fifty states and the District of Columbia. PARTICIPANTS: Adults aged 35 years or older at the time of death. MEASUREMENTS: CVD deaths were identified from International Classification of Diseases, 10th Revision codes indicating CVD (I00 to I99) as the underlying cause of death. RESULTS: From 2018 to 2022, 10 870 CVD deaths (72.6% from heart disease; 19.0% from cerebrovascular disease) occurred among NHPI adults. The CVD ASMR for NHPI adults (369.6 deaths per 100 000 persons [95% CI, 362.4 to 376.7]) was 1.5 times higher than for Asian adults (243.9 deaths per 100 000 persons [CI, 242.6 to 245.2]). The CVD ASMR for NHPI adults was the third highest in the country, after Black adults (558.8 deaths per 100 000 persons [CI, 557.4 to 560.3]) and White adults (423.6 deaths per 100 000 persons [CI, 423.2 to 424.1]). LIMITATION: Potential misclassification of underlying cause of death or race group. CONCLUSION: NHPI adults have a high rate of CVD mortality, which was previously masked by aggregation of the NHPI population with the Asian population. The results of this study support the need for continued disaggregation of the NHPI population in public health research and surveillance to identify opportunities for intervention. PRIMARY FUNDING SOURCE: National Institute of General Medical Sciences, National Institutes of Health.

The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss requirements for an effective surveillance system to support decision making during a pandemic, drawing on the lessons of COVID-19 in the U.S., while looking to jurisdictions in the U.S. and beyond to learn lessons about the value of specific data types. In this report, we define the range of decisions for which surveillance data are required, the data elements needed to inform these decisions and to calibrate inputs and outputs of transmission-dynamic models, and the types of data needed to inform decisions by state, territorial, local, and tribal health authorities. We define actions needed to ensure that such data will be available and consider the contribution of such efforts to improving health equity.

Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021-22 and 2022-23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021-22 and 12 out of 18 models in 2022-23. Averaging across all forecast targets, the FluSight ensemble is the 2(nd) most accurate model measured by WIS in 2021-22 and the 5(th) most accurate in the 2022-23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

BACKGROUND: Community-based mask wearing has been shown to reduce the transmission of SARS-CoV-2. However, few studies have conducted an economic evaluation of mask mandates, specifically in public transportation settings. This study evaluated the cost-effectiveness of implementing mask mandates for subway passengers in the United States by evaluating its potential to reduce COVID-19 transmission during subway travel. MATERIALS AND METHODS: We assessed the health impacts and costs of subway mask mandates compared to mask recommendations based on the number of infections that would occur during subway travel in the U.S. Using a combined box and Wells-Riley infection model, we estimated monthly infections, hospitalizations, and deaths averted under a mask mandate scenario as compared to a mask recommendation scenario. The analysis included costs of implementing mask mandates and COVID-19 treatment from a limited societal perspective. The cost-effectiveness (net cost per averted death) of mandates was estimated for three different periods based on dominant SARS-CoV-2 variants: Alpha, Beta, and Gamma (November 2020 to February 2021); Delta (July to October 2021); and early Omicron (January to March 2022). RESULTS: Compared with mask recommendations only, mask mandates were cost-effective across all periods, with costs per averted death less than a threshold of $11.4 million (ranging from cost-saving to $3 million per averted death). Additionally, mask mandates were more cost-effective during the early Omicron period than the other two periods and were cost saving in January 2022. Our findings showed that mandates remained cost-effective when accounting for uncertainties in input parameters (e.g., even if mandates only resulted in small increases in mask usage by subway ridership). CONCLUSIONS: The findings highlight the economic value of mask mandates on subways, particularly during high virus transmissibility periods, during the COVID-19 pandemic. This study may inform stakeholders on mask mandate decisions during future outbreaks of novel viral respiratory diseases.

As the worldwide COVID-19 pandemic unfolded, the clinical and public health community raced to understand SARS-CoV-2 infection and develop life-saving vaccines. Pregnant persons were disproportionately impacted, experiencing more severe illness and adverse pregnancy outcomes. And yet, when COVID-19 vaccines became available in late 2020, safety and efficacy data were not available to inform their use during pregnancy because pregnant persons were excluded from pre-authorization clinical trials. Concerns about vaccine safety during pregnancy and misinformation linking vaccination and infertility circulated widely, creating a lack of vaccine confidence. Many pregnant people initially chose not to get vaccinated, and while vaccination rates rose after safety and effectiveness data became available, COVID-19 vaccine acceptance was suboptimal and varied across racial and ethnic distribution of the pregnant population. The COVID-19 pandemic experience provided valuable insights that can inform current and future approaches to maternal vaccination against.

During the COVID-19 pandemic, candidate COVID-19 vaccines were being developed for potential use in the United States on an unprecedented, accelerated schedule. It was anticipated that once available, under U.S. Food and Drug Administration (FDA) Emergency Use Authorization (EUA) or FDA approval, COVID-19 vaccines would be broadly used and potentially administered to millions of individuals in a short period of time. Intensive monitoring in the post-EUA/licensure period would be necessary for timely detection and assessment of potential safety concerns. To address this, the Centers for Disease Control and Prevention (CDC) convened an Advisory Committee on Immunization Practices (ACIP) work group focused solely on COVID-19 vaccine safety, consisting of independent vaccine safety experts and representatives from federal agencies - the ACIP COVID-19 Vaccine Safety Technical Work Group (VaST). This report provides an overview of the organization and activities of VaST, summarizes data reviewed as part of the comprehensive effort to monitor vaccine safety during the COVID-19 pandemic, and highlights selected actions taken by CDC, ACIP, and FDA in response to accumulating post-authorization safety data. VaST convened regular meetings over the course of 29 months, from November 2020 through April 2023; through March 2023 FDA issued EUAs for six COVID-19 vaccines from four different manufacturers and subsequently licensed two of these COVID-19 vaccines. The independent vaccine safety experts collaborated with federal agencies to ensure timely assessment of vaccine safety data during this time. VaST worked closely with the ACIP COVID-19 Vaccines Work Group; that work group used safety data and VaST's assessments for benefit-risk assessments and guidance for COVID-19 vaccination policy. Safety topics reviewed by VaST included those identified in safety monitoring systems and other topics of scientific or public interest. VaST provided guidance to CDC's COVID-19 vaccine safety monitoring efforts, provided a forum for review of data from several U.S. government vaccine safety systems, and assured that a diverse group of scientists and clinicians, external to the federal government, promptly reviewed vaccine safety data. In the event of a future pandemic or other biological public health emergency, the VaST model could be used to strengthen vaccine safety monitoring, enhance public confidence, and increase transparency through incorporation of independent, non-government safety experts into the monitoring process, and through strong collaboration among federal and other partners.

OBJECTIVE: To examine the relationship between coronavirus disease 2019 (COVID-19) diagnosis at delivery and adverse maternal health and pregnancy outcomes during pre-Delta, Delta, and Omicron variant predominance, with a focus on the time period of Omicron variant predominance. METHODS: We conducted a cross-sectional observational study with data from delivery hospitalizations in the Premier Healthcare Database from February 2020 to August 2023. The pre-Delta (February 2020-June 2021), Delta (July 2021-December 2021), and Omicron (January 2022-August 2023) periods of variant predominance were examined. Exposure to COVID-19 was identified by having a diagnostic code for COVID-19 during the delivery hospitalization. Adjusted prevalence ratios (aPRs) were calculated to compare the risks of adverse maternal and pregnancy outcomes for women with and without COVID-19 diagnoses at the time of delivery for each variant period. RESULTS: Among 2,990,973 women with delivery hospitalizations, 1.9% (n=56,618) had COVID-19 diagnoses noted at delivery admission discharge, including 26,053 during the Omicron period. Across all variant time periods, the prevalence of many adverse maternal and pregnancy outcomes during the delivery hospitalization was significantly higher for pregnant women with COVID-19 compared with pregnant women without COVID-19. In adjusted models, COVID-19 during the Omicron period was associated with significant increased risks for maternal sepsis (COVID-19: 0.4% vs no COVID-19: 0.1%; aPR 3.32, 95% CI, 2.70-4.08), acute respiratory distress syndrome (0.6% vs 0.1%; aPR 6.19, 95% CI, 5.26-7.29), shock (0.2% vs 0.1%; aPR 2.14, 95% CI, 1.62-2.84), renal failure (0.5% vs 0.2%; aPR 2.08, 95% CI, 1.73-2.49), intensive care unit admission (2.7% vs 1.7%; aPR 1.64, 95% CI, 1.52-1.77), mechanical ventilation (0.3% vs 0.1%; aPR 3.15, 95% CI, 2.52-3.93), in-hospital death (0.03% vs 0.01%; aPR 5.00, 95% CI, 2.30-10.90), stillbirth (0.7% vs 0.6%; aPR 1.17, 95% CI, 1.01-1.36), and preterm delivery (12.3% vs 9.6%; aPR 1.28, 95% CI, 1.24-1.33). CONCLUSION: Despite the possibility of some level of immunity due to previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, vaccination, or testing differences, risks of adverse outcomes associated with COVID-19 diagnosis at delivery remained elevated during the Omicron variant time period.

Leptospirosis, the most widespread zoonotic disease in the world, is broadly understudied in multi-host wildlife systems. Knowledge gaps regarding Leptospira circulation in wildlife, particularly in densely populated areas, contribute to frequent misdiagnoses in humans and domestic animals. We assessed Leptospira prevalence levels and risk factors in five target wildlife species across the greater Los Angeles region: striped skunks (Mephitis mephitis), raccoons (Procyon lotor), coyotes (Canis latrans), Virginia opossums (Didelphis virginiana), and fox squirrels (Sciurus niger). We sampled more than 960 individual animals, including over 700 from target species in the greater Los Angeles region, and an additional 266 sampled opportunistically from other California regions and species. In the five target species seroprevalences ranged from 5 to 60%, and infection prevalences ranged from 0.8 to 15.2% in all except fox squirrels (0%). Leptospira phylogenomics and patterns of serologic reactivity suggest that mainland terrestrial wildlife, particularly mesocarnivores, could be the source of repeated observed introductions of Leptospira into local marine and island ecosystems. Overall, we found evidence of widespread Leptospira exposure in wildlife across Los Angeles and surrounding regions. This indicates exposure risk for humans and domestic animals and highlights that this pathogen can circulate endemically in many wildlife species even in densely populated urban areas.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naïve baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work.Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below. CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook. CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation. COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health. Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information&amp; Data Science Pilot Project. Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation. DDS-NBDS: NSF III-1812699. EPIFORECASTS-ENSEMBLE1: Wellcome Trust (210758/Z/18/Z) GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowments, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. &amp; Charlene Zalesky, and Claudia &amp; Paul Raines GT-DeepCOVID: CDC MInD-Healthcare U01CK000531-Supplement. NSF (Expeditions CCF-1918770, CAREER IIS-2028586, RAPID IIS-2027862, Medium IIS-1955883, NRT DGE-1545362), CDC MInD program, ORNL and funds/computing resources from Georgia Tech and GTRI. IHME: This work was supported by the Bill &amp; Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096). IowaStateLW-STEM: Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1916204, NSF CCF-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics. JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, US Office of Foreign Disaster Assistance, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers fo Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, &amp; Infectious Disease Initiative (26798 Seed Grant). LANL-GrowthRate: LANL LDRD 20200700ER. MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01. NotreDame-mobility and NotreDame-FRED: NSF RAPID DEB 2027718 UA-EpiCovDA: NSF RAPID Grant # 2028401. UCSB-ACTS: NSF RAPID IIS 2029626. UCSD-NEU: Google Faculty Award, DARPA W31P4Q-21-C-0014, COVID Supplement CDC-HHS-6U01IP001137-01. UMass-MechBayes: NIGMS R35GM119582, NSF 1749854. UMich-RidgeTfReg: The University of Michigan Physics Department and the University of Michigan Office of Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:UMass-Amherst IRBAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data and code referred to in the manuscript are publicly available. https://github.com/reichlab/covid19-forecast-hub/ https://github.com/reichlab/covidEnsembles https://zoltardata.com/project/44

Importance Devising control strategies against diseases such as COVID-19 require understanding of contextual social mixing and contact patterns. There has been no standardized multi-site social contact study conducted in workplace settings in the United States that can be used to broadly inform pandemic preparedness policy in these settings.Objective The study aimed to characterize the patterns of social contacts and mixing across workplace environments, including on-site or when teleworking.Design This was a cross-sectional non-probability survey that used standardized social contact diaries to collect data. Employees were requested to record their physical and non-physical contacts in a diary over two consecutive days, documented at the end of each day. Employees from each company were enrolled through email and electronic diaries sent as individual links. Data were collected from April to June 2020.Setting Two multinational consulting companies and one university administrative department, all located in Georgia, USA.Participants Employees opted into the study by accepting the invitation on a link sent via email.Main Outcome The outcome was median number of contacts per person per day. This was stratified by day of data collection, age, sex, race and ethnicity.Results Of 3,835 employees approached, 357 (9.3%) completed the first day of contact diary of which 304 completed both days of contact diary. There was a median of 2 contacts (IQR: 1-4, range: 0-21) per respondent on both day one and two. The majority (55%) of contacts involved conversation only, occurred at home (64%), and cumulatively lasted more than 4 hours (38%). Most contacts were repeated, and within same age groups, though participants aged 30-59 years reported substantial inter-generational mixing with children.Conclusion Participating employees in 3 surveyed workplaces reported few contacts, similar to studies from the UK and China when shelter-in-place orders were in effect during the pandemic. Many contacts were repeated which may limit the spread of infection. Future rounds are planned to assess changes in contact patterns when employees resume work in the office after the lockdown due to COVID-19 pandemic.Competing Interest StatementThe authors have declared no competing interest.Funding StatementCenters for Disease Control and Prevention, Atlanta, Georgia (Comprehensively profiling social mixing patterns in workplace settings to model pandemic influenza transmission; U01-CK000572)Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Ethical approval was given by Yale University (IRB number 2000026906).All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll de-identified data and code used for analysis are available in Github through the link provided. https://github.com/lopmanlab/corpmix

Leptospirosis is the most widespread zoonotic disease in the world, yet it is broadly understudied in multi-host wildlife systems. Knowledge gaps regarding Leptospira circulation in wildlife, particularly in densely populated areas, contribute to frequent misdiagnoses in humans and domestic animals. We assessed Leptospira prevalence levels and risk factors in five target wildlife species across the greater Los Angeles region: striped skunks (Mephitis mephitis), Northern raccoons (Procyon lotor), coyotes (Canis latrans), Virginia opossums (Didelphis virginiana), and fox squirrels (Sciurus niger). We sampled more than 960 individual animals, including over 700 from target species in the greater Los Angeles region, and an additional 260 sampled opportunistically from other regions and species. In the five target species, seroprevalences ranged from 5-60% and active infection prevalences ranged from 0.8-15.2% in all except fox squirrels (0%). Patterns of serologic reactivity suggest that mainland terrestrial wildlife, particularly mesocarnivores, could be the source of repeated observed introductions of Leptospira into local marine and island ecosystems. Overall, we found evidence of widespread Leptospira exposure in wildlife across Los Angeles and surrounding regions. This indicates exposure risk for humans and domestic animals and highlights that this pathogen can circulate endemically in many wildlife species even in densely populated urban areas. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.

We read with interest the recent article by Kingsmore et al., who suggest that universal newborn rapid whole-genome sequencing is attractive for “comprehensive” newborn screening (NBS).1 Existing US NBS programs are based on mandated routine testing of newborns; evidence-based decision-making processes exist for this testing.2 Whether policy makers also consider routine rapid whole-genome sequencing of newborns to be warranted may depend on the resolution of a number of evidentiary, ethical, legal, social, and economic issues.3 Kingsmore et al. suggest that sequencing can complement existing public-health NBS programs but acknowledge the challenge of reconciling universal or near-universal genomic screening with informed parental consent and the allowable secondary use of genomic information.1

In this study, we report the detection of a G6P[14] rotavirus strain from a human stool sample within the United States. The full genotype constellation of the G6P[14] strain was identified as G6-P[14]-I2-R2-C2-M2-A11-N2-T6-E2-H3.

Spatially heterogeneous landscape factors such as urbanisation can have substantial effects on the severity and spread of wildlife diseases. However, research linking patterns of pathogen transmission to landscape features remains rare. Using a combination of phylogeographic and machine learning approaches, we tested the influence of landscape and host factors on feline immunodeficiency virus (FIV(Lru)) genetic variation and spread among bobcats (Lynx rufus) sampled from coastal southern California. We found evidence for increased rates of FIV(Lru) lineage spread through areas of higher vegetation density. Furthermore, single-nucleotide polymorphism (SNP) variation among FIV(Lru) sequences was associated with host genetic distances and geographic location, with FIV(Lru) genetic discontinuities precisely correlating with known urban barriers to host dispersal. An effect of forest land cover on FIV(Lru) SNP variation was likely attributable to host population structure and differences in forest land cover between different populations. Taken together, these results suggest that the spread of FIV(Lru) is constrained by large-scale urban barriers to host movement. Although urbanisation at fine spatial scales did not appear to directly influence virus transmission or spread, we found evidence that viruses transmit and spread more quickly through areas containing higher proportions of natural habitat. These multiple lines of evidence demonstrate how urbanisation can change patterns of contact-dependent pathogen transmission and provide insights into how continued urban development may influence the incidence and management of wildlife disease.

Aircraft cabins have high-performance ventilation systems, yet typically hold many persons in close proximity for long durations. The current study estimated airborne virus exposure and infection reductions when middle seats are vacant compared to full occupancy and when passengers wear surgical masks in aircraft. Tracer particle data reported by U.S. Transportation Command (TRANSCOM) and CFD simulations reported by Boeing were used along with NIOSH data, to build nonlinear regression models with particle exposure and distance from particle source as variables. These models that estimate exposure at given distances from the viral source were applied to evaluate exposure reductions from vacant middle seats. Reductions averaged 54% for the seat row where an infectious passenger is located and 36% for a 24-row cabin containing one infectious passenger, with middle seats vacant. Analysis of the TRANSCOM data showed that universal masking (surgical masks) reduced exposures by 62% and showed masking and physical distancing provide further reductions when practiced together. For a notional scenario involving 10 infectious passengers, compared with no intervention, masking, distancing, and both would prevent 6.2, 3.8, and 7.6 secondary infections, respectively, using the Wells–Riley equation. These results suggest distancing alone, masking alone, and these practiced together reduce SARS CoV-2 exposure risk in increasing order of effectiveness, when an infectious passenger is present. © 2022 The Authors. Engineering Reports published by John Wiley & Sons Ltd. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

AIM: To describe the education and employment transition experience of young adults with spina bifida (YASB) and investigate factors associated with employment. METHOD: We queried education and employment data from the US National Spina Bifida Patient Registry from 2009 to 2019. We applied generalized estimating equations models to analyze sociodemographic and disease-related factors associated with employment. RESULTS: A total of 1909 participants (850 males, 1059 females) aged 18 to 26 years contributed 4379 annual visits. Nearly 84% had myelomeningocele and, at last visit, the median age was 21 years (mean 21 years 5 months, SD 2 years 10 months). A total of 41.8% had at least some post-high school education, and 23.9% were employed. In a multivariable regression model, employment was significantly associated with education level, lower extremity functional level, bowel continence, insurance, and history of non-shunt surgery. This large, national sample of YASB demonstrated low rates of post-secondary education attainment and employment and several potentially modifiable factors associated with employment. INTERPRETATION: Specific sociodemographic, medical, and functional factors associated with employment are important for clinicians to consider when facilitating transition for YASB into adulthood. Additional research is needed to understand the impact of cognitive functioning and social determinants of health on transition success in YASB.

Foundational high-resolution geospatial data products for population, settlements, infrastructure, and boundaries may greatly enhance the efficient planning of resource allocation during health sector interventions. To ensure the relevance and sustainability of such products, government partners must be involved from the beginning in their creation, improvement, and/or management, so they can be successfully applied to public health campaigns, such as malaria control and prevention. As an example, Zambia had an ambitious strategy of reaching the entire population with malaria vector control campaigns by late 2020 or early 2021, but they lacked the requisite accurate and up-to-date data on infrastructure and population distribution. To address this gap, the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) program, Akros, and other partners developed maps and planning templates to aid Zambia's National Malaria Elimination Program (NMEP) in operationalizing its strategy.

Fumonisin exposure is common in populations where maize is a dietary staple, such as in Guatemala, and has been associated with negative health outcomes including neural tube defects. The objective of this study was to estimate fumonisin B1 (FB1) exposure among Guatemalan reproductive-age women and develop a better understanding of the dietary and sociodemographic risk factors for exposure. A cross-sectional study in 18 municipalities in Guatemala was conducted. Midwives and study nurses enrolled consenting women and collected individual and household demographic and socioeconomic data. A food frequency questionnaire was administered to estimate quantity and types of food products consumed. A urine sample was collected and urinary fumonisin B1 (uFB1) concentration was measured. A univariable analysis was conducted to identify predictors of low/high uFB1. Multivariable logistic regression was used to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs). In total, 775 women had analyzable urine samples. Higher uFB1 levels were associated with speaking Mayan (OR = 2.33, 95% CI:1.44-3.77), less than high school education (OR = 1.61, 95% CI:1.12-2.30), increasing dietary proportion of maize-based foods (OR = 1.02, 95% CI:1.01-1.03), and consumption of tostadas (fried tortillas) (OR = 1.11, 95% CI:1.02-1.22). Lower uFB1 levels were associated with consumption of highly processed maize-based foods (OR = 0.93, 95% CI:0.87-0.99). Tortillas were the most frequently consumed maize-based food among study participants and significantly associated with high uFB1 exposure in the univariable but not multivariable analysis. Consumption of >4,750 grams/week of maize-based foods, >5,184 g/week of locally produced maize-based foods, and >110 servings/week of tortillas were also significantly associated with high uFB1 exposure in univariable analysis. Populations with low socioeconomic status/education levels and high consumption of maize-based foods had higher fumonisin exposure. Interventions aimed at reducing the risk of exposure to mycotoxins through maize in Guatemala, including the increased consumption of non-maize-based foods, should be further explored.

Before the introduction of vaccines, group A rotaviruses (RVA) were the leading cause of acute gastroenteritis in children worldwide. The National Rotavirus Strain Surveillance System (NRSSS) was established in 1996 by the Centers for Disease Control and Prevention (CDC) to perform passive RVA surveillance in the USA. We report the distribution of RVA genotypes collected through NRSSS during the 2009-2016 RVA seasons and retrospectively examine the genotypes detected through the NRSSS since 1996. During the 2009-2016 RVA seasons, 2134 RVA-positive fecal specimens were sent to the CDC for analysis of the VP7 and VP4 genes by RT-PCR genotyping assays and sequencing. During 2009-2011, RVA genotype G3P[8] dominated, while G12P[8] was the dominant genotype during 2012-2016. Vaccine strains were detected in 1.7% of specimens and uncommon/unusual strains, including equine-like G3P[8] strains, were found in 1.9%. Phylogenetic analyses showed limited VP7 and VP4 sequence variation within the common genotypes with 1-3 alleles/lineages identified per genotype. A review of 20 years of NRSSS surveillance showed two changes in genotype dominance, from G1P[8] to G3P[8] and then G3P[8] to G12P[8]. A better understanding of the long-term effects of vaccine use on epidemiological and evolutionary dynamics of circulating RVA strains requires continued surveillance.

Population-based estimates of survival among individuals with Duchenne muscular dystrophy (DMD) living in the United States are lacking. It is also unclear whether the association between glucocorticoid use and all-cause mortality persists in the context of other common treatments (cardiac medication, cough-assist, bilevel positive airway pressure, and scoliosis surgery) observed to delay mortality. Among 526 individuals identified by the Muscular Dystrophy Surveillance, Tracking, and Research Network, the estimated median survival time from birth was 23.7 years. Current glucocorticoid users had a lower hazard of mortality than non-users. Individuals who ever had scoliosis surgery had a lower hazard of mortality than individuals who did not have scoliosis surgery. Individuals who ever used cough assist had a lower hazard of mortality than individuals who never used cough assist. Non-Hispanic Black individuals had a higher hazard of mortality than non-Hispanic White individuals. No differences in hazards of mortality were observed between ever versus never use of cardiac medication and ever versus never use of bilevel positive airway pressure. The glucocorticoid observation is consistent with the 2018 Care Considerations statement that glucocorticoid use continues in the non-ambulatory phase. Our observations may inform the clinical care of individuals living with DMD.

SignificanceThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.

Cryptosporidium parvum is a parasitic zoonotic pathogen responsible for diarrheal illness in humans and animals worldwide. We report an investigation of a cryptosporidiosis outbreak in raccoons and wildlife rehabilitation workers at a Virginia facility. Fifteen (31%) of 49 facility personnel experienced symptoms meeting the case definition, including four laboratory-confirmed cases. Seven juvenile raccoons were reported to have diarrhoea; six had laboratory-confirmed cryptosporidiosis. Cryptosporidium parvum of the same molecular subtype (IIaA16G3R2) was identified in two human cases and six raccoons. Raccoon illness preceded human illness by 11days, suggesting possible zoonotic transmission from raccoons to humans. This appears to be the first report of a human cryptosporidiosis outbreak associated with exposure to raccoons infected with C.parvum. Raccoons might be an under-recognized reservoir for human C.parvum infections. Further study is needed to explore the prevalence of cryptosporidial species in raccoons and their role as a wildlife reservoir.