Environmental exposures are ubiquitous and play a significant, and sometimes understated, role in public health as they can lead to the development of various chronic and infectious diseases. In an ideal world, there would be sufficient experimental data to determine the health effects of exposure to priority environmental contaminants. However, this is not the case, as emerging chemicals are continuously added to this list, furthering the data gaps. Recently, simulation science has evolved and can provide appropriate solutions using a multitude of computational methods and tools. In its quest to protect communities across the country from environmental health threats, ATSDR employs a variety of simulation science tools such as Physiologically Based Pharmacokinetic (PBPK) modeling, Quantitative Structure-Activity Relationship (QSAR) modeling, and benchmark dose (BMD) modeling, among others. ATSDR's use of such tools has enabled the agency to evaluate exposures in a timely, efficient, and effective manner. ATSDR's work in simulation science has also had a notable impact beyond the agency, as evidenced by external researchers' widespread appraisal and adaptation of the agency's methodology. ATSDR continues to advance simulation science tools and their applications by collaborating with researchers within and outside the agency, including other federal/state agencies, NGOs, the private sector, and academia.

CONTEXT: Public health programs promote numerous tickborne disease (TBD) prevention measures. However, measures are not frequently or consistently performed. OBJECTIVE: Describe barriers to consistent use of 4 commonly promoted TBD prevention measures. DESIGN: We conducted an online survey (n = 1883) evaluating behaviors regarding TBD prevention measures including conducting tick checks, applying insect repellents, showering/bathing, and applying chemical or natural pesticides to residential yards. Respondents could select reasons for never, rarely, or sometimes performing these measures. Descriptive analysis and logistic regression modeling evaluated associations between the 3 most cited barriers for each measure and select demographic variables. SETTING: The survey was administered to residents in high Lyme disease incidence counties of Connecticut and Maryland, 2016-2017. RESULTS: For tick checks (n = 800), the most cited barriers were forgetting (63%), not spending time in tick habitat (28%), and too much trouble (11%). For applying insect repellents (n = 1303), the most cited barriers were forgetting (38%), personal safety concerns (24%), and too much trouble (19%). For showering/bathing 2 hours after outdoor activity in tick habitat (n = 1080), the most cited barriers were being unaware of the prevention measure (51%), too much trouble (18%), and forgetting (18%). For applying chemical pesticides to yards (n = 1320), the most cited barriers were having environmental (45%), pet safety (31%), and personal safety concerns (28%). Lastly, for applying natural pesticides to yards (n = 1357), the most cited barriers were being unaware of natural pesticides (31%), having cost concerns (23%), and not being concerned about ticks on property (16%). CONCLUSIONS: Forgetting, too much trouble, unawareness, and safety concerns were primary barriers to using several TBD prevention measures. Education regarding effectiveness, safety, and timing may increase uptake of certain measures. These challenges can be difficult to address, highlighting the need for passive TBD prevention measures, such as a Lyme disease vaccine.

BACKGROUND: Scale up of proven malaria control interventions has not been sufficient to control malaria in Uganda, emphasizing the need to explore innovative new approaches. Improved housing is one such promising strategy. This paper describes housing characteristics and their association with malaria burden in a moderate to high transmission setting in Uganda. METHODS: Between October and November 2021, a household survey was conducted in 1500 randomly selected households in Jinja and Luuka districts. Information on demographics, housing characteristics, use of malaria prevention measures, and proxy indicators of wealth were collected for each household. A finger-prick blood sample was obtained for thick blood smears for malaria from all children aged 6 months to 14 years in the surveyed households. Febrile children had a malaria rapid diagnostics test (RDT) done; positive cases were managed according to national treatment guidelines. Haemoglobin was assessed in children aged < 5 years. Households were stratified as having modern houses (defined as having finished materials for roofs, walls, and floors and closed eaves) or traditional houses (those not meeting the definition of modern house). Associations between malaria burden and house type were estimated using mixed effects models and adjusted for age, wealth, and bed net use. RESULTS: Most (65.5%) of the households surveyed lived in traditional houses. Most of the houses had closed eaves (85.5%), however, the use of other protective features like window/vent screens and installed ceilings was limited (0.4% had screened windows, 2.8% had screened air vents, and 5.2% had ceiling). Overall, 3,443 children were included in the clinical survey, of which 31.4% had a positive smear. RDT test positivity rate was 56.6% among children with fever. Participants living in modern houses had a significantly lower parasite prevalence by microscopy (adjusted prevalence ratio [aPR = 0.80]; 95% confidence interval [CI] 0.71 - 0.90), RDT test positivity rate (aPR = 0.90, 95%CI 0.81 - 0.99), and anaemia (aPR = 0.80, 95%CI 0.65 - 0.97) compared to those in traditional houses. CONCLUSION: The study found that even after adjusting for wealth, higher quality housing had a moderate protective effect against malaria, on top of the protection already afforded by recently distributed nets.

The goals of the Association for Molecular Pathology (AMP) Clinical Practice Committee's Pharmacogenomics (PGx) Working Group are to define the key attributes of pharmacogenetic alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations for a minimum set of variant alleles (Tier 1) and an extended list of variant alleles (Tier 2) that will aid clinical laboratories when designing assays for PGx testing. The AMP PGx Working Group considered the functional impact of the variant alleles, allele frequencies in multiethnic populations, the availability of reference materials, and other technical considerations for PGx testing when developing these recommendations. The goal of this Working Group is to promote standardization of PGx testing across clinical laboratories. This document will focus on clinical DPYD PGx testing that may be applied to all DPD-related medications. These recommendations are not to be interpreted as prescriptive but to provide a reference guide.

Venous thromboembolism (VTE) is the leading cause of preventable death in hospitalized patients. Artificial intelligence (AI) and machine learning (ML) can support guidelines recommending an individualized approach to risk assessment and prophylaxis. We conducted electronic surveys asking clinician and healthcare informaticians about their perspectives on AI/ML for VTE prevention and management. Of 101 respondents to the informatician survey, most were 40 years or older, male, clinicians and data scientists, and had performed research on AI/ML. Of the 607 US-based respondents to the clinician survey, most were 40 years or younger, female, physicians, and had never used AI to inform clinical practice. Most informaticians agreed that AI/ML can be used to manage VTE (56.0%). Over one-third were concerned that clinicians would not use the technology (38.9%), but the majority of clinicians believed that AI/ML probably or definitely can help with VTE prevention (70.1%). The most common concern in both groups was a perceived lack of transparency (informaticians 54.4%; clinicians 25.4%). These two surveys revealed that key stakeholders are interested in AI/ML for VTE prevention and management, and identified potential barriers to address prior to implementation.

This paper describes the factors that support recovery of public health infrastructure (PHI), including conditions that facilitated or hindered recovery in United States (US) territories impacted by hurricanes Irma and Maria. A deductive approach was used to categorize data from five organizations that received crisis hurricane recovery (CHR) funds from the Centers for Disease Control and Prevention.* Spending was grouped into five infrastructure gaps: (1) human resources, (2) informatic upgrades, (3) equipment, (4) minor repairs, and (5) preventive maintenance. Unanticipated PHI costs, facilitators, and hinderances to PHI recovery were identified. Most (72 percent) of the $53,529,823 CHR funding was used to address infrastructure gaps in (1) human resources (56 percent), (2) informatics (16 percent), (3) equipment (13 percent), (4) minor repairs (10 percent), and (5) preventive maintenance (5 percent). Most of the requests (56 percent) to redirect funds were associated with unanticipated costs in initial work plans and budgets. The use of administrative partners, planning tools, dedicated staff, streamlined procedures, eg, contracts, and cost sharing facilitated PHI recovery. The most common hindrance to PHI recovery were delays in procurement and shipping. In summary, investments in dedicated funding to upgrade, repair, or replace critical structures and systems for infectious disease surveillance, laboratory capacity, vector control, environmental health inspections, and vaccine storage and administration in Puerto Rico and the US Virgin Islands after Hurricanes Irma and Maria contributed to their recovery capacity. These findings may inform funding and resource allocation considerations for PHI recovery in the US territories.

BACKGROUND: Human adenoviruses (HAdVs) can cause outbreaks of flu-like illness in university settings. Most infections in healthy young adults are mild; severe illnesses rarely occur. In Fall 2022, an adenovirus outbreak was identified in university students. METHODS: HAdV cases were defined as university students 17-26 years old who presented to the University Health Service or nearby emergency department with flu-like symptoms (eg, fever, cough, headache, myalgia, nausea) and had confirmed adenovirus infections by polymerase chain reaction (PCR). Demographic and clinical characteristics were abstracted from electronic medical records; clinical severity was categorized as mild, moderate, severe, or critical. We performed contact investigations among critical cases. A subset of specimens was sequenced to confirm the HAdV type. RESULTS: From 28 September 2022 to 30 January 2023, 90 PCR-confirmed cases were identified (51% female; mean age, 19.6 years). Most cases (88.9%) had mild illness. Seven cases required hospitalization, including 2 critical cases that required intensive care. Contact investigation identified 44 close contacts; 6 (14%) were confirmed HAdV cases and 8 (18%) reported symptoms but never sought care. All typed HAdV-positive specimens (n = 36) were type 4. CONCLUSIONS: While most students with confirmed HAdV had mild illness, 7 otherwise healthy students had severe or critical illness. Between the relatively high number of hospitalizations and proportion of close contacts with symptoms who did not seek care, the true number of HAdV cases was likely higher. Our findings illustrate the need to consider a wide range of pathogens, even when other viruses are known to be circulating.

Digital trace data and machine learning techniques are increasingly being adopted to predict suicide-related outcomes at the individual level; however, there is also considerable public health need for timely data about suicide trends at the population level. Although significant geographic variation in suicide rates exist by state within the United States, national systems for reporting state suicide trends typically lag by one or more years. We developed and validated a deep learning based approach to utilize real-time, state-level online (Mental Health America web-based depression screenings; Google and YouTube Search Trends), social media (Twitter), and health administrative data (National Syndromic Surveillance Program emergency department visits) to estimate weekly suicide counts in four participating states. Specifically, per state, we built a long short-term memory (LSTM) neural network model to combine signals from the real-time data sources and compared predicted values of suicide deaths from our model to observed values in the same state. Our LSTM model produced accurate estimates of state-specific suicide rates in all four states (percentage error in suicide rate of -2.768% for Utah, -2.823% for Louisiana, -3.449% for New York, and -5.323% for Colorado). Furthermore, our deep learning based approach outperformed current gold-standard baseline autoregressive models that use historical death data alone. We demonstrate an approach to incorporate signals from multiple proxy real-time data sources that can potentially provide more timely estimates of suicide trends at the state level. Timely suicide data at the state level has the potential to improve suicide prevention planning and response tailored to the needs of specific geographic communities.

Sickle cell disease (SCD) remains a public health priority in the United States because of its association with complex health needs, reduced life expectancy, lifelong disabilities, and high cost of care. A cross-sectional analysis was conducted to calculate the crude and race-specific birth prevalence for SCD using state newborn screening program records during 2016-2020 from 11 Sickle Cell Data Collection program states. The percentage distribution of birth mother residence within Social Vulnerability Index quartiles was derived. Among 3,305 newborns with confirmed SCD (including 57% with homozygous hemoglobin S or sickle β-null thalassemia across 11 states, 90% of whom were Black or African American [Black], and 4% of whom were Hispanic or Latino), the crude SCD birth prevalence was 4.83 per 10,000 (one in every 2,070) live births and 28.54 per 10,000 (one in every 350) non-Hispanic Black newborns. Approximately two thirds (67%) of mothers of newborns with SCD lived in counties with high or very high levels of social vulnerability; most mothers lived in counties with high or very high levels of vulnerability for racial and ethnic minority status (89%) and housing type and transportation (64%) themes. These findings can guide public health, health care systems, and community program planning and implementation that address social determinants of health for infants with SCD. Implementation of tailored interventions, including increasing access to transportation, improving housing, and advancing equity in high vulnerability areas, could facilitate care and improve health outcomes for children with SCD.

IMPORTANCE: Caring for children diagnosed with cancer may adversely affect the mental health (MH) of parents. OBJECTIVE: To characterize utilization of MH services among parents of children with vs without cancer using nationwide commercial claims data. DESIGN, SETTING, AND PARTICIPANTS: For this cross-sectional study, the Merative MarketScan Commercial Claims Database was used to identify continuously insured families of children treated for cancer (aged ≤21 years at diagnosis) during 2010 to 2018, compared with families who matched eligibility criteria but did not have a child with a cancer history. Parents were assessed from 18 months before to 12 months after their child's cancer diagnosis. Analyses were conducted from February 2022 to September 2023. EXPOSURES: Children's cancer diagnosis. MAIN OUTCOMES AND MEASURES: Outcomes included parents' MH-related visits during the first year following their child's cancer diagnosis. Logistic regressions compared outcomes between families of children with vs without cancer, adjusting for sociodemographic and clinical factors. RESULTS: This study included 4837 families of children with cancer (4210 mothers and 4016 fathers) and 24 185 families of children without cancer (21 444 mothers and 19 591 fathers) with continuous insurance enrollment. Most household leads were aged 35 to 54 years (3700 [76.5%] in families of children with cancer vs 17 812 [73.6%] in families of children without cancer) and resided in urban areas (4252 [87.9%] vs 21 156 [87.5%]). The probabilities of parents having anxiety-related visits (10.6% vs 7.0%), depression-related visits (8.4% vs 6.1%), and any MH-related visits (18.1% vs 13.3%) were higher in families of children with vs without cancer. Adjusted analyses showed absolute increases of 3.2 percentage points (95% CI, 2.3 to 4.0; 45.7% relative increase), 2.2 percentage points (95% CI, 1.4 to 3.0; 36.1% relative increase), and 4.2 percentage points (95% CI, 3.1 to 5.3; 31.3% relative increase) in the probabilities of 1 or both parents having anxiety-related visits, depression-related visits, and any MH-related visits, respectively, among families of children with vs without cancer. Such differences were greater in magnitude among mothers than fathers. CONCLUSIONS AND RELEVANCE: In this cohort study of privately insured parents, those caring for children with cancer had a higher likelihood of utilizing MH care than other parents. These findings underline the importance of interventions toward targeted counseling and support to better meet MH care needs among parents and caregivers of children with cancer.

Many SARS-CoV-2 infections are asymptomatic, thus reported cases underestimate actual cases. To improve estimates, we conducted surveillance for SARS-CoV-2 seroprevalence among pregnant women attending their first antenatal care visit (ANC1) from June 2021 through May 2022. We administered a questionnaire to collect demographic, risk factors, and COVID-19 vaccine status information and tested dried blood spots for SARS-CoV-2 antibodies. Although <1% of ANC1 participants reported having had COVID-19, monthly SARS-CoV-2 seroprevalence increased from 15.4% (95% CI: 10.5-21.5) in June 2021 to 65.5% (95% CI: 55.5-73.7) in May 2022. Although COVID-19 vaccination was available in March 2021, uptake remained low, reaching a maximum of 9.5% (95% CI: 5.7-14.8) in May 2022. Results of ANC1 serosurveillance provided prevalence estimates helpful in understanding this population case burden that was available through self-report and national case reports. To improve vaccine uptake, efforts to address fears and misconceptions regarding COVID-19 vaccines are needed.

Venous thromboembolism (VTE) is a leading cause of preventable in-hospital mortality. Monitoring VTE cases is limited by the challenges of manual chart review and diagnosis code interpretation. Natural language processing (NLP) can automate the process. Rule-based NLP methods are effective but time consuming. Machine learning (ML)-NLP methods present a promising solution. We conducted a systematic review and meta-analysis of studies published before May 2023 that use ML-NLP to identify VTE diagnoses in the electronic health records. Four reviewers screened all manuscripts, excluding studies that only used a rule-based method. A meta-analysis evaluated the pooled performance of each study's best performing model that evaluated for pulmonary embolism (PE) and/or deep vein thrombosis (DVT). Pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with confidence interval (CI) were calculated by DerSimonian and Laird method using a random-effects model. Study quality was assessed using an adapted TRIPOD tool. Thirteen studies were included in the systematic review and 8 had data available for meta-analysis. Pooled sensitivity was 0.931 (95% CI 0.881-0.962), specificity 0.984 (95% CI 0.967-0.992), PPV 0.910 (95% CI 0.865-0.941) and NPV 0.985 (95% CI 0.977-0.990). All studies met at least 13 of the 21 NLP-modified TRIPOD items, demonstrating fair quality. The highest performing models used vectorization rather than bag-of-words, and deep learning techniques such as convolutional neural networks. There was significant heterogeneity in the studies and only four validated their model on an external dataset. Further standardization of ML studies can help progress this novel technology towards real-world implementation.

BACKGROUND: Insecticide-treated nets (ITNs) contributed significantly to the decline in malaria since 2000. Their protective efficacy depends not only on access, use, and net integrity, but also location of people within the home environment and mosquito biting profiles. Anopheline mosquito biting and human location data were integrated to identify potential gaps in protection and better understand malaria transmission dynamics in Busia County, western Kenya. METHODS: Direct observation of human activities and human landing catches (HLC) were performed hourly between 1700 to 0700 h. Household members were recorded as home or away; and, if at home, as indoors/outdoors, awake/asleep, and under a net or not. Aggregated data was analysed by weighting hourly anopheline biting activity with human location. Standard indicators of human-vector interaction were calculated using a Microsoft Excel template. RESULTS: There was no significant difference between indoor and outdoor biting for Anopheles gambiae sensu lato (s.l.) (RR = 0.82; 95% CI 0.65-1.03); significantly fewer Anopheles funestus were captured outdoors than indoors (RR = 0.41; 95% CI 0.25-0.66). Biting peaked before dawn and extended into early morning hours when people began to awake and perform routine activities, between 0400-0700 h for An. gambiae and 0300-0700 h for An. funestus. The study population away from home peaked at 1700-1800 h (58%), gradually decreased and remained constant at 10% throughout the night, before rising again to 40% by 0600-0700 h. When accounting for resident location, nearly all bites within the peri-domestic space (defined as inside household structures and surrounding outdoor spaces) occurred indoors for unprotected people (98%). Using an ITN while sleeping was estimated to prevent 79% and 82% of bites for An. gambiae and An. funestus, respectively. For an ITN user, most remaining exposure to bites occurred indoors in the hours before bed and early morning. CONCLUSION: While use of an ITN was estimated to prevent most vector bites in this context, results suggest gaps in protection, particularly in the early hours of the morning when biting peaks and many people are awake and active. Assessment of additional human exposure points, including outside of the peri-domestic setting, are needed to guide supplementary interventions for transmission reduction.

Since 2008, Mainland China has undergone widespread outbreaks of hand, foot, and mouth disease (HFMD). In order to determine the characteristics of epidemics and enteroviruses (EV) associated with HFMD in Tianjin, in northern China, epidemiological and virological data from routine surveillance were collected and analyzed. In Tianjin, a persistent epidemic of HFMD was demonstrated during 2008-2013, involving 102,705 mild, 179 severe, and 16 fatal cases. Overall, 8234 specimens were collected from 7829 HFMD patients for EV detection during 2008-2013. Enterovirus 71 (EV-A71) and coxsackievirus A16 (CV-A16) were the dominant serotypes during 2008-2012, and they were replaced by CV-A6 as the major causative agent in 2013. Phylogenetic analysis based on complete VP1 nucleotide sequences revealed that multiple CV-A6 lineages co-circulated in Tianjin, which grouped together with strains from China and other countries and split into two distinct clusters (clusters 1 and 2). Most Tianjin strains grouped in cluster 1 and were closely related to strains from several eastern and southern provinces of China during 2012 and 2013. Estimates from Bayesian MCMC analysis suggested that multiple lineages had been transmitted silently before the outbreaks at an estimated evolutionary rate of 4.10 × 10(-3) substitutions per site per year without a specific distribution of rate variances among lineages. The sudden outbreak of CV-A6 in Tianjin during 2013 is attributed to indigenous CV-A6 lineages, which were linked to the wide spread of endemic strains around eastern and southern China.

PURPOSE: Database linkage between cancer registries and clinical trial consortia has the potential to elucidate referral patterns of children and adolescents with newly diagnosed cancer, including enrollment into cancer clinical trials. This study's primary objective was to assess the feasibility of this linkage approach. METHODS: Patients younger than 20 years diagnosed with incident cancer during 2012-2017 in the Kentucky Cancer Registry (KCR) were linked with patients enrolled in a Children's Oncology Group (COG) study. Matched patients between databases were described by sex, age, race and ethnicity, geographical location when diagnosed, and cancer type. Logistic regression modeling identified factors associated with COG study enrollment. Timeliness of patient identification by KCR was reported through the Centers for Disease Control and Prevention's Early Case Capture (ECC) program. RESULTS: Of 1,357 patients reported to KCR, 47% were determined by matching to be enrolled in a COG study. Patients had greater odds of enrollment if they were age 0-4 years (v 15-19 years), reported from a COG-affiliated institution, and had renal cancer, neuroblastoma, or leukemia. Patients had lower odds of enrollment if Hispanic (v non-Hispanic White) or had epithelial (eg, thyroid, melanoma) cancer. Most (59%) patients were reported to KCR within 10 days of pathologic diagnosis. CONCLUSION: Linkage of clinical trial data with cancer registries is a feasible approach for tracking patient referral and clinical trial enrollment patterns. Adolescents had lower enrollment compared with younger age groups, independent of cancer type. Population-based early case capture could guide interventions designed to increase cancer clinical trial enrollment.

Hospital-associated venous thromboembolism (VTE) is a major public health challenge, and while thromboprophylaxis is known to be effective, it remains misused [1]. Clinicians face enormous complexity when determining who should receive thromboprophylaxis. To better understand current practices around VTE prophylaxis in adult hospitalized patients, we previously surveyed 607 clinicians across the United States between 2021 and 2022 [2]. Overall, 48% of respondents reported patients at their institution are not on appropriate VTE prophylaxis almost all the time. The majority reported that technology such as artificial intelligence (AI) may help improve rates of appropriate prophylaxis. However, only 35% reported using existing risk assessment models (RAMs); 68% reported using their own clinical assessment instead. Therefore, we invited survey respondents to participate in focus groups to better understand how they approach VTE prophylaxis, with a focus on their perspectives regarding using AI decision support.

Malaria remains a leading cause of childhood morbidity and mortality in sub-Saharan Africa, particularly among children under 5 years of age. To help address this challenge, the WHO recommends chemoprevention for certain populations. For children and infants, the WHO recommends seasonal malaria chemoprevention (SMC), perennial malaria chemoprevention (PMC; formerly intermittent preventive treatment in infants [IPTi]), and, more recently, intermittent preventive treatment in school children (IPTsc). This review describes the contextual factors, including feasibility, acceptability, health equity, financial considerations, and values and preferences, that impact implementation of these strategies. A systematic search was conducted on July 5, 2022, and repeated April 13, 2023, to identify relevant literature. Two reviewers independently screened titles for eligibility, extracted data from eligible articles, and identified and summarized themes. Of 6,295 unique titles identified, 65 were included. The most frequently evaluated strategy was SMC (n = 40), followed by IPTi (n = 18) and then IPTsc (n = 6). Overall, these strategies were highly acceptable, although with IPTsc, there were community concerns with providing drugs to girls of reproductive age and the use of nonmedical staff for drug distribution. For SMC, door-to-door delivery resulted in higher coverage, improved caregiver acceptance, and reduced cost. Lower adherence was noted when caregivers were charged with giving doses 2 and 3 unsupervised. For SMC and IPTi, travel distances and inclement weather limited accessibility. Sensitization and caregiver education efforts, retention of high-quality drug distributors, and improved transportation were key to improving coverage. Additional research is needed to understand the role of community values and preferences in chemoprevention implementation.

After the 2015 documentation of global eradication of wild poliovirus type 2,* Sabin type 2 oral poliovirus vaccine (OPV) was withdrawn from routine immunization (RI) in all OPV-using countries in 2016, in a global synchronized switch from trivalent OPV (containing vaccine virus serotypes 1, 2, and 3) to bivalent OPV (containing serotypes 1 and 3), to reduce the rare risks for type 2 vaccine-associated paralytic poliomyelitis. Concurrently, the Global Polio Eradication Initiative (GPEI) recommended that all OPV-using countries introduce ≥1 dose of inactivated poliovirus vaccine (IPV) into RI programs; IPV protects against paralysis caused by all three serotypes but cannot be transmitted from person to person or cause paralysis. Use of OPV, especially in areas with low vaccination coverage, is associated with low risk of emergence of vaccine-derived polioviruses (VDPVs). As susceptible persons in new birth cohorts accumulated after withdrawal of OPV type 2, population immunity against infection with serotype 2 declined (1), facilitating the emergence of circulating VDPV type 2 (cVDPV2). During the previous 7 years, cVDPV2 outbreaks required response supplementary immunization activities (SIAs) with monovalent type 2 OPV (mOPV2); however, if SIAs were not of sufficiently high quality and did not achieve high enough coverage, new emergences of cVDPV2 occurred.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.

BACKGROUND: Accurate diagnostic and prognostic predictions of venous thromboembolism (VTE) are crucial for VTE management. Artificial intelligence (AI) enables autonomous identification of the most predictive patterns from large complex data. Although evidence regarding its performance in VTE prediction is emerging, a comprehensive analysis of performance is lacking. AIMS: To systematically review the performance of AI in the diagnosis and prediction of VTE and compare it to clinical risk assessment models (RAMs) or logistic regression models. METHODS: A systematic literature search was performed using PubMed, MEDLINE, EMBASE, and Web of Science from inception to April 20, 2021. Search terms included "artificial intelligence" and "venous thromboembolism." Eligible criteria were original studies evaluating AI in the prediction of VTE in adults and reporting one of the following outcomes: sensitivity, specificity, positive predictive value, negative predictive value, or area under receiver operating curve (AUC). Risks of bias were assessed using the PROBAST tool. Unpaired t-test was performed to compare the mean AUC from AI versus conventional methods (RAMs or logistic regression models). RESULTS: A total of 20 studies were included. Number of participants ranged from 31 to 111 888. The AI-based models included artificial neural network (six studies), support vector machines (four studies), Bayesian methods (one study), super learner ensemble (one study), genetic programming (one study), unspecified machine learning models (two studies), and multiple machine learning models (five studies). Twelve studies (60%) had both training and testing cohorts. Among 14 studies (70%) where AUCs were reported, the mean AUC for AI versus conventional methods were 0.79 (95% CI: 0.74-0.85) versus 0.61 (95% CI: 0.54-0.68), respectively (p < .001). However, the good to excellent discriminative performance of AI methods is unlikely to be replicated when used in clinical practice, because most studies had high risk of bias due to missing data handling and outcome determination. CONCLUSION: The use of AI appears to improve the accuracy of diagnostic and prognostic prediction of VTE over conventional risk models; however, there was a high risk of bias observed across studies. Future studies should focus on transparent reporting, external validation, and clinical application of these models.

BACKGROUND: Venous thromboembolism (VTE) is a leading cause of preventable mortality among hospitalized patients, but appropriate risk assessment and thromboprophylaxis remain underutilized or misapplied. OBJECTIVES: We conducted an electronic survey of US health care providers to explore attitudes, practices, and barriers related to thromboprophylaxis in adult hospitalized patients and at discharge. RESULTS: A total of 607 US respondents completed the survey: 63.1% reported working in an academic hospital, 70.7% identified as physicians, and hospital medicine was the most frequent specialty (52.1%). The majority of respondents agreed that VTE prophylaxis is important (98.8%; 95% CI: 97.6%-99.5%) and that current measures are safe (92.6%; 95% CI: 90.2%-94.5%) and effective (93.8%; 95% CI: 91.6%-95.6%), but only half (52.0%; 95% CI: 47.9%-56.0%) believed that hospitalized patients at their institution are on appropriate VTE prophylaxis almost all the time. One-third (35.4%) reported using a risk assessment model (RAM) to determine VTE prophylaxis need; 44.9% reported unfamiliarity with RAMs. The most common recommendation for improving rates of appropriate thromboprophylaxis was to leverage technology. A majority of respondents (84.5%) do not reassess a patient's need for VTE prophylaxis at discharge, and a minority educates patients about the risk (16.2%) or symptoms (18.9%) of VTE at discharge. CONCLUSION: Despite guideline recommendations to use RAMs, the majority of providers in our survey do not use them. A majority of respondents believed that technology could help improve VTE prophylaxis rates. A majority of respondents do not reassess the risk of VTE at discharge or educate patients about this risk of VTE at discharge.

Ocular syphilis is a serious complication of Treponema pallidum infection that can occur at any stage of syphilis and affect any eye structure. It remains unknown if certain T. pallidum strains are associated with ocular infections; therefore, we performed genotyping and whole genome sequencing (WGS) to characterize strains from patients with ocular syphilis. Seventy-five ocular or non-ocular specimens from 55 ocular syphilis patients in 14 states within the United States were collected between February 2016 and November 2020. Sufficient T. pallidum DNA was available from nine patients for genotyping and three for WGS. Genotyping was done using the augmented Centers for Disease Control and Prevention typing scheme, and WGS was performed on Illumina platforms. Multilocus sequence typing allelic profiles were predicted from whole genome sequence data. T. pallidum DNA was detected in various specimens from 17 (30.9%) of the 55 patients, and typing was done on samples from 9 patients. Four complete strain types (14d10/g, 14b9/g, 14d9/g, and 14e9/f) and five partial types were identified. WGS was successful on samples from three patients and all three strains belonged to the SS14 clade of T. pallidum. Our data reveal that multiple strain types are associated with ocular manifestations of syphilis. While genotyping and WGS were challenging due to low amounts of T. pallidum DNA in specimens, we successfully performed WGS on cerebrospinal fluid, vitreous fluid, and whole blood.IMPORTANCESyphilis is caused by the spirochete Treponema pallidum. Total syphilis rates have increased significantly over the past two decades in the United States, and the disease remains a public health concern. In addition, ocular syphilis cases has also been on the rise, coinciding with the overall increase in syphilis rates. We conducted a molecular investigation utilizing traditional genotyping and whole genome sequencing over a 5-year period to ascertain if specific T. pallidum strains are associated with ocular syphilis. Genotyping and phylogenetic analysis show that multiple T. pallidum strain types are associated with ocular syphilis in the United States.

OBJECTIVES: Despite clinical relevance, commercially available molecular tools for accurate β-lactamase detection are limited. In this study, we evaluated the performance of the ARM-D® β-lactamase Kit, a commercially available multiplex PCR assay designed to detect nine β-lactamase genes, including the five major plasmid-mediated carbapenemases, ESBL, or AmpC genes circulating in the United States. METHODS: A diverse collection of 113 Gram-negative isolates, including 42 with multiple β-lactamases was selected from the U.S. Centers for Disease Control and Prevention (CDC) & Food and Drug Administration (FDA) Antibiotic Resistance Isolate Bank, to represent the most frequently detected bacterial species carrying plasmid-mediated β-lactam resistance genes. RESULTS: Results were compared with whole genome sequence data. Of 164 β-lactamase gene targets with 49 unique variants, all were detected correctly without any cross-reactivity. The sensitivity and specificity were 100% (164/164) and 99.9% (852/853), respectively. CONCLUSION: The ARM-D® β-lactamase Kit detected a wide range of β-lactamase genotypes at a low upfront cost. The Streck assay represents a suitable, comprehensive tool for the detection of key β-lactamase resistance genes of public health concern in the United States.

CONTEXT: In the northeastern United States, recommendations to prevent diseases spread by black-legged ticks (Ixodes scapularis) and lone star ticks (Amblyomma americanum) often rely on individuals to use personal protection or yard-based strategies. The 4-Poster deer treatment stations (4-Posters) suppress tick populations by treating deer hosts with acaricide, potentially offering a community-wide approach for reducing tick-borne diseases in endemic areas. The 4-Poster deployment logistics in mainland community settings are not well documented but are needed for future public health tick control efforts. PROGRAM: As part of a public health research effort to design a population-based 4-Poster effectiveness study aimed at reducing tick-borne disease incidence, TickNET researchers partnered with the Town of Ridgefield (Connecticut) to understand the feasibility and operational logistics of deploying 4-Posters on public land within a residential community to inform future public health interventions by municipalities or vector control agencies. IMPLEMENTATION: We deployed three 4-Posters on a municipal property from July to December 2020 and used motion-activated cameras to record wildlife activity nearby. We documented per-device operational details, costs, materials consumed, and animal activity. EVALUATION: Operation of 4-Posters was feasible, and device challenges were easily remedied. Deer visitation and heavy nontarget animal use were documented at all devices. Unexpectedly, monthly corn consumption was not correlated with monthly deer-view days. The monthly cost per device was US $1279 or US $305 per hectare with an average 21 minutes of weekly service time. DISCUSSION: Use of 4-Posters by communities, public health agencies, or vector control programs may be a practicable addition to tick management programs in tick-borne disease endemic areas in the Northeast. Such programs should carefully consider local and state regulations, follow manufacturer and pesticide label guidelines, and include wildlife monitoring. High labor costs incurred in this project could be mitigated by training vector control agency or municipality staff to service 4-Posters.

The 4-Poster Tick Control Deer Feeder (4-poster) device applies acaricide to white-tailed deer (Odocoileus virginianus) and can reduce populations of the blacklegged tick (Ixodes scapularis), which transmits the agents of Lyme disease, anaplasmosis, babesiosis, and Powassan virus disease in the Northeastern United States. While 4-poster devices have the potential to provide community-wide management of blacklegged ticks in Lyme disease endemic areas, no recent study has assessed their acceptability among residents. We conducted a survey of residents from 16 counties with high annual average Lyme disease incidence (≥ 10 cases per 100,000 persons between 2013 and 2017) in Connecticut and New York to understand perceptions and experiences related to tickborne diseases, support or concerns for placement of 4-poster devices in their community, and opinions on which entities should be responsible for tick control on private properties. Overall, 37% of 1652 respondents (5.5% response rate) would support placement of a 4-poster device on their own property, 71% would support placement on other private land in their community, and 90% would support placement on public land. Respondents who were male, rented their property, resided on larger properties, or were very or extremely concerned about encountering ticks on their property were each more likely to support placement of 4-poster devices on their own property. The primary reason for not supporting placement of a 4-poster device on one's own property was the need for weekly service visits from pest control professionals, whereas the top reason for not supporting placement on other land (private or public) was safety concerns. Most respondents (61%) felt property owners should be responsible for tick control on private properties. Communities considering 4-poster devices as part of a tick management strategy should consider targeting owners of larger properties and placing devices on public lands.

Mortality among patients with COVID-19 and respiratory failure is high and there are no known lower airway biomarkers that predict clinical outcome. We investigated whether bacterial respiratory infections and viral load were associated with poor clinical outcome and host immune tone. We obtained bacterial and fungal culture data from 589 critically ill subjects with COVID-19 requiring mechanical ventilation. On a subset of the subjects that underwent bronchoscopy, we also quantified SARS-CoV-2 viral load, analyzed the microbiome of the lower airways by metagenome and metatranscriptome analyses and profiled the host immune response. We found that isolation of a hospital-acquired respiratory pathogen was not associated with fatal outcome. However, poor clinical outcome was associated with enrichment of the lower airway microbiota with an oral commensal ( Mycoplasma salivarium ), while high SARS-CoV-2 viral burden, poor anti-SARS-CoV-2 antibody response, together with a unique host transcriptome profile of the lower airways were most predictive of mortality. Collectively, these data support the hypothesis that 1) the extent of viral infectivity drives mortality in severe COVID-19, and therefore 2) clinical management strategies targeting viral replication and host responses to SARS-CoV-2 should be prioritized.

Mortality among patients with COVID-19 and respiratory failure is high and there are no known lower airway biomarkers that predict clinical outcome. We investigated whether bacterial respiratory infections and viral load were associated with poor clinical outcome and host immune tone. We obtained bacterial and fungal culture data from 589 critically ill subjects with COVID-19 requiring mechanical ventilation. On a subset of the subjects that underwent bronchoscopy, we also quantified SARS-CoV-2 viral load, analyzed the microbiome of the lower airways by metagenome and metatranscriptome analyses and profiled the host immune response. We found that isolation of a hospital-acquired respiratory pathogen was not associated with fatal outcome. However, poor clinical outcome was associated with enrichment of the lower airway microbiota with an oral commensal ( Mycoplasma salivarium ), while high SARS-CoV-2 viral burden, poor anti-SARS-CoV-2 antibody response, together with a unique host transcriptome profile of the lower airways were most predictive of mortality. Collectively, these data support the hypothesis that 1) the extent of viral infectivity drives mortality in severe COVID-19, and therefore 2) clinical management strategies targeting viral replication and host responses to SARS-CoV-2 should be prioritized.

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.

The goals of the Association for Molecular Pathology Clinical Practice Committee's Pharmacogenomics (PGx) Working Group are to define the key attributes of pharmacogenetic alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations for a minimum panel of variant alleles (tier 1) and an extended panel of variant alleles (tier 2) that will aid clinical laboratories when designing assays for PGx testing. The Association for Molecular Pathology PGx Working Group considered functional impact of the variant alleles, allele frequencies in multiethnic populations, the availability of reference materials, and other technical considerations for PGx testing when developing these recommendations. The goal of this Working Group is to promote standardization of PGx gene/allele testing across clinical laboratories. This document will focus on clinical CYP3A4 and CYP3A5 PGx testing that may be applied to all CYP3A4- and CYP3A5-related medications. These recommendations are not to be interpreted as prescriptive but to provide a reference guide.