We report a patient in North Carolina, USA, with Heartland virus infection whose diagnosis was complicated by previous Ehrlichia chaffeensis infection. We identified E. ewingii-infected and Bourbon virus-infected tick pools at the patient's residence. Healthcare providers should consider testing for tickborne viruses if ehrlichiosis is suspected.

Rocky Mountain spotted fever (RMSF) is a severe tickborne disease that can reach epidemic proportions in communities with certain social and ecologic risk factors. In some areas, the case-fatality rate of brown dog tick-associated RMSF is up to 50%. Because of the spread of brown dog tick-associated RMSF in the southwestern United States and northern Mexico, the disease has the potential to emerge and become endemic in other communities that have large populations of free-roaming dogs, brown dog ticks, limited resources, and low provider awareness of the disease. By using a One Health approach, interdisciplinary teams can identify communities at risk and prevent severe or fatal RMSF in humans before cases occur. We have developed a conceptual framework for RMSF prevention to enable communities to identify their RMSF risk level and implement prevention and control strategies.

With 762 laboratories, the Global Measles and Rubella Laboratory Network (GMRLN) is the largest laboratory network coordinated by the World Health Organization (WHO). Like the Global Polio Laboratory Network, the GMRLN has multiple tiers, including global specialized laboratories, regional reference laboratories, national laboratories, and, in some countries, subnational laboratories. Regional networks are supervised by regional laboratory coordinators reporting to a global coordinator at WHO headquarters. Laboratories in the GMRLN have strong links to national disease control and vaccination programs. The GMRLN's goal is to support member states in obtaining timely, complete, and reliable laboratory-based surveillance data for measles and rubella as part of the strategy for achieving measles and rubella elimination. Surveillance data are reported to the national program and are included in annual reports on the status of measles and rubella elimination to national verification committees for review by regional verification commissions. Quality within the GMRLN is ensured by monitoring performance through external quality assurance programs, confirmatory and quality control testing, accreditation, and coordination of corrective action and training where needed. The overall performance of the laboratories has remained high over the years despite many challenges, particularly the COVID-19 pandemic. The GMRLN is well-positioned to support high-quality laboratory-based surveillance for measles and rubella and to transition to supporting laboratory testing for other pathogens, including vaccine-preventable diseases.

Hard ticks (Acari: Ixodidae) have been historically identified by morphological methods which require highly specialized expertise and more recently by DNA-based molecular assays that involve high costs. Although both approaches provide complementary data for tick identification, each method has limitations which restrict their use on large-scale settings such as regional or national tick surveillance programs. To overcome those obstacles, the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been introduced as a cost-efficient method for the identification of various organisms, as it balances performance, speed, and high data output. Here we describe the use of this technology to validate the distinction of two closely related Dermacentor tick species based on the development of the first nationwide MALDI-TOF MS reference database described to date. The dataset obtained from this protein-based approach confirms that tick specimens collected from United States regions west of the Rocky Mountains and identified previously as Dermacentor variabilis are the recently described species, Dermacentor similis. Therefore, we propose that this integrative taxonomic tool can facilitate vector and vector-borne pathogen surveillance programs in the United States and elsewhere.

Bacterial zoonoses are established causes of severe febrile illness in East Africa. Within a fever etiology study, we applied a high-throughput 16S rRNA metagenomic assay validated for detecting bacterial zoonotic pathogens. We enrolled febrile patients admitted to 2 referral hospitals in Moshi, Tanzania, during September 2007-April 2009. Among 788 participants, median age was 20 (interquartile range 2-38) years. We performed PCR amplification of V1-V2 variable region 16S rRNA on cell pellet DNA, then metagenomic deep-sequencing and pathogenic taxonomic identification. We detected bacterial zoonotic pathogens in 10 (1.3%) samples: 3 with Rickettsia typhi, 1 R. conorii, 2 Bartonella quintana, 2 pathogenic Leptospira spp., and 1 Coxiella burnetii. One other sample had reads matching a Neoerhlichia spp. previously identified in a patient from South Africa. Our findings indicate that targeted 16S metagenomics can identify bacterial zoonotic pathogens causing severe febrile illness in humans, including potential novel agents.

Haematospirillum jordaniae is a gram-negative bacterium that has been identified in the blood of septic patients. The environmental source or potential zoonotic host of this bacterium, recently described as a human bacterial pathogen is unknown. An increasing number of H. jordaniae clinical infections identified by our laboratory suggested the need for an assay to detect this organism in order to aid clinical teams and practitioners with faster identification and treatment thus improving patient prognosis. Described here is a real-time qualitative PCR assay designed using gene targets identified from the analysis of 14 H. jordaniae genomes sequenced by the Center for Disease Control and Prevention's (CDC) Special Bacterial Reference Laboratory (SBRL) culture collection. The assay was validated on clinical EDTA whole blood samples as well as on plasma and determined to be effective at detecting as few as 10 copies per microliter (10,000 copies per mL, 4 log/mL) for whole blood samples and 1 copy per microliter (1,000 copies per mL, 3 log mL) for plasma samples.

Amblyomma maculatum Koch, the Gulf Coast tick, is expanding northward from its original range in the southeastern United States. In 2013, its most northern collection was in Delaware. Amblyomma maculatum has since been found in Connecticut, Illinois, and New York. It is the vector of the human pathogen Rickettsia parkeri, the causative agent of R. parkeri rickettsiosis. We report the first finding of an established population of A. maculatum in Salem County, NJ, with a R. parkeri infection prevalence rate of 23.8%. Our finding of A. maculatum is consistent with other recent findings in the northeastern United States in that specimens were found in open areas devoid of tree canopy. This discovery demonstrates the importance of tick surveillance in order to identify expanding tick populations and the pathogens they may transmit.

The brown dog tick, Rhipicephalus sanguineus sensu lato (s.l.), is an important vector for Rickettsia rickettsii, causative agent of Rocky Mountain spotted fever. Current public health prevention and control efforts to protect people involve preventing tick infestations on domestic animals and in and around houses. Primary prevention tools rely on acaricides, often synthetic pyrethroids (SPs); resistance to this chemical class is widespread in ticks and other arthropods. Rhipicephalus sanguineus s.l. is a complex that likely contains multiple unique species and although the distribution of this complex is global, there are differences in morphology, ecology, and perhaps vector competence among these major lineages. Two major lineages within Rh. sanguineus s.l., commonly referred to as temperate and tropical, have been documented from multiple locations in North America, but are thought to occupy different ecological niches. To evaluate potential acaricide resistance and better define the distributions of the tropical and temperate lineages throughout the US and in northern Mexico, we employed a highly multiplexed amplicon sequencing approach to characterize sequence diversity at: 1) three loci within the voltage-gated sodium channel (VGSC) gene, which contains numerous genetic mutations associated with resistance to SPs; 2) a region of the gamma-aminobutyric acid-gated chloride channel gene (GABA-Cl) containing several mutations associated with dieldrin/fipronil resistance in other species; and 3) three mitochondrial genes (COI, 12S, and 16S). We utilized a geographically diverse set of Rh sanguineus s.l. collected from domestic pets in the US in 2013 and a smaller set of ticks collected from canines in Baja California, Mexico in 2021. We determined that a single nucleotide polymorphism (T2134C) in domain III segment 6 of the VGSC, which has previously been associated with SP resistance in Rh. sanguineus s.l., was widespread and abundant in tropical lineage ticks (>50 %) but absent from the temperate lineage, suggesting that resistance to SPs may be common in the tropical lineage. We found evidence of multiple copies of GABA-Cl in ticks from both lineages, with some copies containing mutations associated with fipronil resistance in other species, but the effects of these patterns on fipronil resistance in Rh. sanguineus s.l. are currently unknown. The tropical lineage was abundant and geographically widespread, accounting for 79 % of analyzed ticks and present at 13/14 collection sites. The temperate and tropical lineages co-occurred in four US states, and as far north as New York. None of the ticks we examined were positive for Rickettsia rickettsii or Rickettsia massiliae.

The use of data analytics has seen widespread application in fields such as medicine and supply chain management, but their application in occupational safety has only recently become more common. The purpose of this scoping review was to summarize studies that employed analytics within establishments to reveal insights about work-related injuries or fatalities. Over 300 articles were reviewed to survey the objectives, scope and methods used in this emerging field. We conclude that the promise of analytics for providing actionable insights to address occupational safety concerns is still in its infancy. Our review shows that most articles were focused on method development and validation, including studies that tested novel methods or compared the utility of multiple methods. Many of the studies cited various challenges in overcoming barriers caused by inadequate or inefficient technical infrastructures and unsupportive data cultures that threaten the accuracy and quality of insights revealed by the analytics.

The recovery of a Haemaphysalis longicornis Neumann (Acari: Ixodidae) tick from a dog in Benton County, Arkansas, in 2018 triggered a significant environmental sampling effort in Hobbs State Park Conservation Area. The objective of the investigation was to assess the tick population density and diversity, as well as identify potential tick-borne pathogens that could pose a risk to public health. During a week-long sampling period in August of 2018, a total of 6,154 ticks were collected, with the majority identified as Amblyomma americanum (L), (Acari: Ixodidae) commonly known as the lone star tick. No H. longicornis ticks were found despite the initial detection of this species in the area. This discrepancy highlights the importance of continued monitoring efforts to understand the dynamics of tick populations and their movements. The investigation also focused on pathogen detection, with ticks being pooled by species, age, and sex before being processed with various bioassays. The results revealed the presence of several tick-borne pathogens, including agents associated with ehrlichiosis (n = 12), tularemia (n = 2), and Bourbon virus (BRBV) disease (n = 1), as well as nonpathogenic rickettsial and anaplasmosis organisms. These findings emphasize the importance of public health messaging to raise awareness of the risks associated with exposure to tick-borne pathogens. Prevention measures, such as wearing protective clothing, using insect repellent, and conducting regular tick checks, should be emphasized to reduce the risk of tick-borne diseases. Continued surveillance efforts and research are also essential to improve our understanding of tick-borne disease epidemiology and develop effective control strategies.

BACKGROUND: In northern Tanzania, Q fever, spotted fever group (SFG) rickettsioses, and typhus group (TG) rickettsioses are common causes of febrile illness. We sought to describe the prevalence and risk factors for these zoonoses in a pastoralist community. METHODS: Febrile patients ≥2 years old presenting to Endulen Hospital in the Ngorongoro Conservation Area were enrolled from August 2016 through October 2017. Acute and convalescent blood samples were collected, and a questionnaire was administered. Sera were tested by immunofluorescent antibody (IFA) IgG assays using Coxiella burnetii (Phase II), Rickettsia africae, and Rickettsia typhi antigens. Serologic evidence of exposure was defined by an IFA titre ≥1:64; probable cases by an acute IFA titre ≥1:128; and confirmed cases by a ≥4-fold rise in titre between samples. Risk factors for exposure and acute case status were evaluated. RESULTS: Of 228 participants, 99 (43.4%) were male and the median (interquartile range) age was 27 (16-41) years. Among these, 117 (51.3%) had C. burnetii exposure, 74 (32.5%) had probable Q fever, 176 (77.2%) had SFG Rickettsia exposure, 134 (58.8%) had probable SFG rickettsioses, 11 (4.8%) had TG Rickettsia exposure, and 4 (1.8%) had probable TG rickettsioses. Of 146 participants with paired sera, 1 (0.5%) had confirmed Q fever, 8 (5.5%) had confirmed SFG rickettsioses, and none had confirmed TG rickettsioses. Livestock slaughter was associated with acute Q fever (adjusted odds ratio [OR] 2.54, 95% confidence interval [CI] 1.38-4.76) and sheep slaughter with SFG rickettsioses case (OR 4.63, 95% CI 1.08-23.50). DISCUSSION: Acute Q fever and SFG rickettsioses were detected in participants with febrile illness. Exposures to C. burnetii and to SFG Rickettsia were highly prevalent, and interactions with livestock were associated with increased odds of illness with both pathogens. Further characterisation of the burden and risks for these diseases is warranted.

The Gram-negative Elizabethkingia express multiple antibiotic resistance and cause severe opportunistic infections. Vancomycin is commonly used to treat Gram-positive infections and has also been used to treat Elizabethkingia infections, even though Gram-negative organisms possess a vancomycin permeability barrier. Elizabethkingia anophelis appeared relatively vancomycin-susceptible and challenge with this drug led to morphological changes indicating cell lysis. In stark contrast, vancomycin growth challenge revealed that E. anophelis populations refractory to vancomycin emerged. In addition, E. anophelis vancomycin-selected mutants arose at high frequencies and demonstrated elevated vancomycin resistance and reduced susceptibility to other antimicrobials. All mutants possessed a SNP in a gene (vsr1 = vancomycin-susceptibility regulator 1) encoding a PadR family transcriptional regulator located in the putative operon vsr1-ORF551, which is conserved in other Elizabethkingia spp as well. This is the first report linking a padR homologue (vsr1) to antimicrobial resistance in a Gram-negative organism. We provide evidence to support that vsr1 acts as a negative regulator of vsr1-ORF551 and that vsr1-ORF551 upregulation is observed in vancomycin-selected mutants. Vancomycin-selected mutants also demonstrated reduced cell length indicating that cell wall synthesis is affected. ORF551 is a membrane-spanning protein with a small phage shock protein conserved domain. We hypothesize that since vancomycin-resistance is a function of membrane permeability in Gram-negative organisms, it is likely that the antimicrobial resistance mechanism in the vancomycin-selected mutants involves altered drug permeability.

Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.

BACKGROUND: The nutritional status of children with cystic fibrosis (CF), as assessed by their body mass index percentile (BMIp), is a critical determinant of long-term health outcomes. While the intestinal microbiome plays an important role in nutrition, little is known regarding the relationship of the microbiome and BMIp in children with CF. METHODS: Pediatric patients (< 18 years old) with CF and healthy comparison patients (HCs) were enrolled in the study and stool samples obtained. BMIp was categorized as Green Zone (BMIp > 50th), Yellow Zone (BMIp 25th-49th) and Red Zone (BMIp < 25th). Intestinal microbiome assessment was performed via 16S rRNA gene sequencing; microbial richness, diversity, and differential species abundance were assessed. RESULTS: Stool samples were collected from 107 children with CF and 50 age-matched HCs. Compared to HCs, children with CF were found to have lower bacterial richness, alpha-diversity, and a different microbial composition. When evaluating them by their BMIp color zone, richness and alpha-diversity were lowest in those in the Red Zone. In addition, an unclassified amplicon sequence variant (ASV) of Blautia, a known butyrate-producing anaerobe, was of lowest abundance in children in the Red Zone. CONCLUSION: Children with CF have a dysbiotic intestinal microbiome with specific changes that accompany changes in BMIp. Longitudinal assessments of the microbiome and its metabolic activities over time are needed to better understand how improvements in the microbiome may improve nutrition and enhance long-term survival in children with CF.

Haemaphysalis longicornis (Neumann) is an invasive ixodid tick originating from eastern Asia which recently has become established in the United States. In its native range, this tick can transmit several pathogens to animals and humans, but little is known about its ability to acquire and transmit pathogens native to the United States. Geographic overlap with ticks such as Dermacentor variabilis (Say), a known vector of Rickettsia rickettsii, makes investigation into the interactions between H. longicornis and D. variabilis of interest to the public health community. Previous studies have shown that H. longicornis can serve as a competent vector of R. rickettsii under laboratory settings, but there is little information on its ability to acquire this pathogen via other biologically relevant routes, such as co-feeding. Here, we assess the ability of H. longicornis nymphs to acquire R. rickettsii through co-feeding with infected D. variabilis adults on a vertebrate animal model under laboratory conditions. The median infection prevalence in engorged H. longicornis nymphs across 8 cohorts was 0% with an interquartile range (IQR) of 4.13%. Following transstadial transmission, the median infection prevalence in flat females was 0.7% (IQR = 2.4%). Our results show that co-feeding transmission occurs at low levels in the laboratory between these 2 species. However, based on the relatively low transmission rates, this may not be a likely mechanism of R. rickettsii introduction to H. longicornis.

Elizabethkingia anophelis is an emerging global multidrug-resistant opportunistic pathogen. We assessed the diversity among 13 complete genomes and 23 draft genomes of E. anophelis derived from various environmental settings and human infections from different geographic regions around the world over past decades from 1950s. Thirty-one of these 36 strains harbor integrative and conjugative elements (ICEs). A total of 52 ICEs were identified, and categorized into three ICE types based on the architecture of signature genes in the conjugation module. The type II and III ICEs were found to integrate into regions adjacent to tRNA genes, while type I ICEs used a variety of integration sites, inserting into intergenic regions or even directly into a gene, sometimes disrupting gene function. Integrases such as tyrosine recombinases, serine recombinases and DDE transposases were found in most ICEs. The ICEs carry various cargo genes including transcription regulators and those involved in antibiotic resistance. The CRISPR-Cas system was found in nine strains, including four strains in which CRISPR-Cas machinery and ICEs co-exist. ICE distribution in the strains showed no geographic or temporal patterns. The ICEs in E. anophelis differ in gene structure and sequence from CTnDOT, a well-studied ICE prevalent in Bacteroides spp. This is the first set of ICEs identified in the family Flavobacteriaceae. As a prevalent type of mobile genetic elements in various strains of E. anophelis around the world, the categorization of ICEs will facilitate further investigations such as virulence, genome epidemiology and adaptation genomics of E. anophelis.Importance Elizabethkingia anophelis is an opportunistic human pathogen, and the genetic diversity between strains from around the world becomes apparent as more genomes are sequenced. The Integrative Conjugative Element (ICE), found in many bacterial species, contains genes for transfer via conjugation and integration into the chromosome, along with various cargo genes. ICEs are identified in 31 of 36 strains and categorized into three types based on architecture of modular genes, integrases, and integration sites. ICE distribution in different strains displays no spatial and temporal patterns. Several ICE-containing strains also possessed CRISPR-Cas units, considered to be the bacterial adaptive immune system providing protection against phage and predatory mobile genetic elements. This co-existence suggests that ICEs are beneficial or at least not harmful to the bacterial cells they inhabit. ICEs as a component of the mobile genetic repertoire enable recipients to resist antibiotics, survive disinfecting agents, and adapt to various ecological niches.

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Objective Studies suggest infants may be at increased risk of severe COVID-19 relative to older children, but few data exist regarding the incidence of COVID-19 episodes and associated risk factors. We estimate incidence rates and describe characteristics associated with medically attended COVID-19 episodes among infants younger than 6 months of age. Methods We analyzed electronic medical record data from a cohort of infants born March 1, 2020-February 28, 2021. Data from three health care delivery systems included demographic characteristics, maternal and infant outpatient visit and hospitalization diagnoses, and SARSCoV-2 test results. Medically attended COVID-19 episodes were defined by positive SARSCoV-2 clinical tests and/or COVID-19 diagnosis codes during medical care visits. Unadjusted and site-adjusted incidence rates by infant month of age, low and high SARS-CoV-2 circulation periods and maternal COVID-19 diagnosis were calculated. Results Among 18,192 infants aged <6 months whose mothers received prenatal care within the three systems, 173 (1.0%) had medically attended COVID-19 episodes. Incidence rates were highest among infants aged under 1 month (2.0 per 1,000 person-weeks) and 1 month (2.0 per 1,000 person-weeks) compared with older infants. Incidence rates were also higher for infants born to women with postpartum COVID-19 compared with women without known COVID-19 and women diagnosed with COVID-19 during pregnancy. Conclusion Most medically attended COVID-19 episodes in infants aged <6 months were outpatient care encounters. Infants of women with postpartum COVID-19 had a higher risk of medically attended COVID-19 than infants born to mothers who were diagnosed during pregnancy or never diagnosed underscoring the importance of COVID-19 prevention measures for their household members and caregivers to prevent infections in infants. 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: Historically, malaria has been the predominant cause of acute febrile illness (AFI) in sub-Saharan Africa. However, during the last two decades, malaria incidence has declined due to concerted public health control efforts, including the widespread use of rapid diagnostic tests leading to increased recognition of non-malarial AFI etiologies. Our understanding of non-malarial AFI is limited due to lack of laboratory diagnostic capacity. We aimed to determine the etiology of AFI in three distinct regions of Uganda. METHODS: A prospective clinic-based study that enrolled participants from April 2011 to January 2013 using standard diagnostic tests. Participant recruitment was from St. Paul's Health Centre (HC) IV, Ndejje HC IV, and Adumi HC IV in the western, central and northern regions, which differ by climate, environment, and population density. A Pearson's chi-square test was used to evaluate categorical variables, while a two-sample t-test and Krukalis-Wallis test were used for continuous variables. RESULTS: Of the 1281 participants, 450 (35.1%), 382 (29.8%), and 449 (35.1%) were recruited from the western, central, and northern regions, respectively. The median age (range) was 18 (2-93) years; 717 (56%) of the participants were female. At least one AFI pathogen was identified in 1054 (82.3%) participants; one or more non-malarial AFI pathogens were identified in 894 (69.8%) participants. The non-malarial AFI pathogens identified were chikungunya virus, 716 (55.9%); Spotted Fever Group rickettsia (SFGR), 336 (26.2%) and Typhus Group rickettsia (TGR), 97 (7.6%); typhoid fever (TF), 74 (5.8%); West Nile virus, 7 (0.5%); dengue virus, 10 (0.8%) and leptospirosis, 2 (0.2%) cases. No cases of brucellosis were identified. Malaria was diagnosed either concurrently or alone in 404 (31.5%) and 160 (12.5%) participants, respectively. In 227 (17.7%) participants, no cause of infection was identified. There were statistically significant differences in the occurrence and distribution of TF, TGR and SFGR, with TF and TGR observed more frequently in the western region (p = 0.001; p < 0.001) while SFGR in the northern region (p < 0.001). CONCLUSION: Malaria, arboviral infections, and rickettsioses are major causes of AFI in Uganda. Development of a Multiplexed Point-of-Care test would help identify the etiology of non-malarial AFI in regions with high AFI rates.

Background: Pregnant individuals are at increased risk of coronavirus disease 2019 (COVID-19) hospitalization and death, and primary and booster COVID-19 vaccination is recommended for this population. Method(s): Among a cohort of pregnant individuals who received prenatal care at 3 healthcare systems in the United States, we estimated the cumulative incidence of hospitalization with symptomatic COVID-19 illness. We also identified factors associated with COVID-19 hospitalization using a multivariable Cox proportional hazards model with pregnancy weeks as the timescale and a time-varying adjustor that accounted for severe acute respiratory syndrome coronavirus 2 circulation; model covariates included site, age, race, ethnicity, insurance status, prepregnancy weight status, and selected underlying medical conditions. Data were collected primarily through medical record extraction. Result(s): Among 19 456 pregnant individuals with an estimated due date during 1 March 2020-28 February 2021, 75 (0.4%) were hospitalized with symptomatic COVID-19. Factors associated with hospitalization for symptomatic COVID-19 were Hispanic ethnicity (adjusted hazard ratio [aHR], 2.7 [95% confidence interval {CI}, 1.3-5.5]), Native Hawaiian or Pacific Islander race (aHR, 12 [95% CI, 3.2-45.5]), age <25 years (aHR, 3.1 [95% CI, 1.3-7.6]), prepregnancy obesity (aHR, 2.1 [95% CI, 1.1-3.9]), diagnosis of a metabolic disorder (aHR, 2.2 [95% CI, 1.2-3.8]), lung disease excluding asthma (aHR, 49 [95% CI, 28-84]), and cardiovascular disease (aHR, 2.6 [95% CI, 1.5-4.7]). Conclusion(s): Although hospitalization with symptomatic COVID-19 was uncommon, pregnant individuals should be aware of risk factors associated with severe illness when considering COVID-19 vaccination. Copyright © 2022 Published by Oxford University Press on behalf of Infectious Diseases Society of America. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Limited data significantly hinders our capability of biothreat assessment of novel bacterial strains. Integration of data from additional sources that can provide context about the strain can address this challenge. Datasets from different sources, however, are generated with a specific objective and which makes integration challenging. Here, we developed a deep learning-based approach called the neural network embedding model (NNEM) that integrates data from conventional assays designed to classify species with new assays that interrogate hallmarks of pathogenicity for biothreat assessment. We used a dataset of metabolic characteristics from a de-identified set of known bacterial strains that the Special Bacteriology Reference Laboratory (SBRL) of the Centers for Disease Control and Prevention (CDC) has curated for use in species identification. The NNEM transformed results from SBRL assays into vectors to supplement unrelated pathogenicity assays from de-identified microbes. The enrichment resulted in a significant improvement in accuracy of 9% for biothreat. Importantly, the dataset used in our analysis is large, but noisy. Therefore, the performance of our system is expected to improve as additional types of pathogenicity assays are developed and deployed. The proposed NNEM strategy thus provides a generalizable framework for enrichment of datasets with previously collected assays indicative of species.

BACKGROUND: Studies suggest infants may be at increased risk of severe coronavirus disease 2019 (COVID-19) relative to older children, but few data exist regarding the incidence of COVID-19 episodes and associated risk factors. We estimate incidence rates and describe characteristics associated with medically attended COVID-19 episodes among infants younger than 6 months of age. METHODS: We analyzed electronic medical record data from a cohort of infants born March 1, 2020-February 28, 2021. Data from 3 health care delivery systems included demographic characteristics, maternal and infant outpatient visit and hospitalization diagnoses and severe acute respiratory syndrome coronavirus syndrome 2 (SARS-CoV-2) test results. Medically attended COVID-19 episodes were defined by positive SARS-CoV-2 clinical tests and/or COVID-19 diagnosis codes during medical care visits. Unadjusted and site-adjusted incidence rates by infant month of age, low and high SARS-CoV-2 circulation periods and maternal COVID-19 diagnosis were calculated. RESULTS: Among 18,192 infants <6 months of age whose mothers received prenatal care within the 3 systems, 173 (1.0%) had medically attended COVID-19 episodes. Incidence rates were highest among infants under 1 month of age (2.0 per 1000 person-weeks) and 1 month (2.0 per 1000 person-weeks) compared with older infants. Incidence rates were also higher for infants born to women with postpartum COVID-19 compared with women without known COVID-19 and women diagnosed with COVID-19 during pregnancy. CONCLUSIONS: Infants of women with postpartum COVID-19 had a higher risk of medically attended COVID-19 than infants born to mothers who were diagnosed during pregnancy or never diagnosed underscoring the importance of COVID-19 prevention measures for their household members and caregivers to prevent infections in infants.

Anaplasmosis is increasingly common in the United States, with cases being reported over an expanding geographic area. To monitor for changes in risk of human infection, the U.S. Centers for Disease Control and Prevention monitors the distribution and abundance of host-seeking vector ticks (Ixodes scapularis and Ixodes pacificus) and their infection with Anaplasma phagocytophilum. While several variants of A. phagocytophilum circulate in I. scapularis, only the human-active variant (Ap-ha) appears to be pathogenic in humans. Failure to differentiate between human and non-human variants may artificially inflate estimates of the risk of human infection. Efforts to differentiate the Ap-ha variant from the deer variant (Ap-V1) in ticks typically rely on traditional PCR assays coupled with sequencing of PCR products. However, laboratories are increasingly turning to Next Generation Sequencing (NGS) to increase testing efficiency, retain high sensitivity, and increase specificity compared with traditional PCR assays. We describe a new NGS assay with novel targets that accurately segregate the Ap-ha variant from other non-human variants and further identify unique clades within the human and non-human variants. Recognizing that not all investigators have access to NGS technology, we also developed a PCR assay based on one of the novel targets so that variants can be visualized using agarose gel electrophoresis without the need for subsequent sequencing. Such an assay may be used to improve estimates of human risk of developing anaplasmosis in North America.

Influenza testing and case-confirmation rates in pregnant populations have not been reported during the coronavirus disease 2019 (COVID-19) pandemic. Using electronic medical record data from a cohort of nearly 20,000 pregnancies in the United States, this retrospective cohort study examines the frequency of acute respiratory or febrile illness encounters, influenza testing, and influenza positivity during the 2020-2021 influenza season, which occurred during the COVID-19 pandemic, compared with the 2019-2020 influenza season, which largely did not. The ratios of influenza tests to acute respiratory or febrile illness visits were similar in the 2019-2020 and 2020-2021 influenza seasons (approximately 1:8 and 1:9, respectively) but were low and varied by study site. Although influenza testing in pregnant patients continued in the 2020-2021 season, when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) circulation was widespread in the United States, no cases of influenza were identified in our study cohort.

BACKGROUND: Identifying SARS-CoV-2 infections during peripartum hospitalizations is important to guide care, implement prevention measures, and understand infection burden. METHODS: This cross-sectional analysis used electronic health record data from hospitalizations during which pregnancies ended (peripartum hospitalizations) among a cohort of pregnant persons at 3 U.S. integrated healthcare networks (Sites 1-3). Maternal demographic, medical encounter, SARS-CoV-2 testing, and pregnancy and neonatal outcome information was extracted for persons with estimated delivery and pregnancy end dates during March 2020-February 2021 and ≥1 prenatal care record. Site-stratified multivariable logistic regression was used to identify factors associated with testing and compare pregnancy and neonatal outcomes among persons tested. RESULTS: Among 17,858 pregnant persons, 10,863 (60.8%) had peripartum SARS-CoV-2 testing; 222/10,683 (2.0%) had positive results. Testing prevalence varied by site and was lower during March-May 2020. Factors associated with higher peripartum SARS-CoV-2 testing odds were Asian race (adjusted odds ratio [aOR]: 1.36; 95% CI: 1.03-1.79; referent: White) (Site 1), Hispanic or Latina ethnicity (aOR: 1.33; 95% CI: 1.08-1.64) (Site 2), peripartum Medicaid coverage (aOR: 1.33; 95% CI: 1.06-1.66) (Site 1), and preterm hospitalization (aOR: 1.69; 95% CI: 1.19-2.39 [Site 1]; aOR: 1.39; 95% CI: 1.03-1.88 [Site 2]). CONCLUSIONS: Findings highlight potential disparities in SARS-CoV-2 peripartum testing by demographic and pregnancy characteristics. Testing practice variations should be considered when interpreting studies relying on convenience samples of pregnant persons testing positive for SARS-CoV-2. Efforts to address testing differences between groups could improve equitable testing practices and care for pregnant persons with SARS-CoV-2 infections.

BACKGROUND: Pathogen detection has changed with increased use of culture-independent diagnostic tests (CIDTs). CIDTs do not yield isolates, which are necessary to detect outbreaks using whole-genome sequencing. The Foodborne Diseases Active Surveillance Network (FoodNet) monitors clinical laboratory testing practices to improve interpretation of surveillance data and assess availability of isolates. We describe changes in practices over 8 years. METHODS: During 2012-2019, 10 FoodNet sites collected standardized data about practices in clinical laboratories (range, 664-723 laboratories) for select enteric pathogens. We assessed changes in practices. RESULTS: During 2012-2019, the percentage of laboratories that used only culture methods decreased, with the largest declines for Vibrio (99%-57%) and Yersinia (99%-60%). During 2019, the percentage of laboratories using only CIDTs was highest for Shiga toxin-producing Escherichia coli (43%), Campylobacter (34%), and Vibrio (34%). From 2015 to 2019, the percentage of laboratories that performed reflex culture after a positive CIDT decreased, with the largest declines for Shigella (75%-42%) and Salmonella (70%-38%). The percentage of laboratories that routinely submitted isolates to a public health laboratory decreased for all bacterial pathogens examined from 2015 to 2019. CONCLUSIONS: By increasing use of CIDTs and decreasing reflex culture, clinical laboratories have transferred the burden of isolate recovery to public health laboratories. Until technologies allow for molecular subtyping directly from a patient specimen, state public health laboratories should consider updating enteric disease reporting requirements to include submission of isolates or specimens. Public health laboratories need resources for isolate recovery.

Feral swine, Sus scrofa L., have become a nuisance to landowners across the United States by damaging agriculture, property, and ecosystems. Additionally, these animals have been found to host various ixodid ticks including Amblyomma americanum (L.), Amblyomma maculatum Koch, Dermacentor variabilis (Say), and Ixodes scapularis Say, which can maintain and transmit several rickettsial pathogens to livestock, wildlife, and humans. Though previous research has identified the maintenance cycle of several rickettsial pathogens in ticks and native wildlife, little is known about the role S. scrofa plays in supporting ixodid ticks and the pathogens these ticks could be harboring. This study sought to identify rickettsial agents (Rickettsiales: Anaplasmataceae and Rickettsiaceae) in ticks collected from S. scrofa obtained in Florida and South Carolina. Overall, ticks from four species (A. americanum, D. variabilis, I. scapularis, and A. maculatum) totaling 258 collected individuals were obtained from S. scrofa (n = 45). We found an Ehrlichia chaffeensis Anderson et al. infection prevalence in A. americanum of 2.7% and 2.9% in Florida and South Carolina, respectively. A Rickettsia parkeri Lackman et al. prevalence of 100% and 33% was found in A. maculatum from Florida and South Carolina, respectively. Additionally, a 0.9% infection prevalence of R. parkeri was identified in A. americanum collected in South Carolina. A 1.9% Ehrlichia ewingii Anderson et al. infection prevalence was documented in collected A. americanum in South Carolina. Further studies are warranted to better understand the role S. scrofa plays in the natural maintenance of rickettsial agents in various regions of the United States. © 2022 Georgia Entomological Society Inc.. All rights reserved.

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases(1-3). SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing(4,5). Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

BACKGROUND: Neurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome. METHODS: We conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models. RESULTS: We included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67-82]), than encephalopathy (54% [42-65]). Intensive care use was high (38% [35-41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27-32]. The hazard of death was comparatively lower for patients in the WHO European region. INTERPRETATION: Neurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission.