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Individuals with weaker neutralizing responses show reduced protection with SARS-CoV-2 variants. Booster vaccines are recommended for vaccinated individuals, but the uptake is low. We present the feasibility of utilizing point-of-care tests (POCT) to support evidence-based decision-making around COVID-19 booster vaccinations. Using infectious virus neutralization, ACE2 blocking, spike binding, and TCR sequencing assays, we investigated the dynamics of changes in the breadth and depth of blood and salivary antibodies as well as T-cell clonal response following mRNA vaccination in a cohort of healthcare providers. We evaluated the accuracy of two POCTs utilizing either blood or saliva to identify those in whom humoral immunity was inadequate. >4 months after two doses of mRNA vaccine, SARS-CoV-2 binding and neutralizing Abs (nAbs) and T-cell clones declined 40-80%, and 2/3rd lacked Omicron nAbs. After the third mRNA booster, binding and neutralizing Abs increased overall in the systemic compartment; notably, individuals with previously weak nAbs gained sharply. The third dose failed to stimulate secretory IgA, but salivary IgG closely tracked systemic IgG levels. Vaccine boosting increased Ab breadth against a divergent bat sarbecovirus, SHC014, although the TCR-beta sequence breadth was unchanged. Post 3rd booster dose, Ab avidity increased for the Wuhan and Delta strains, while avidity against Omicron and SHC014 increased to levels seen for Wuhan after the second dose. Negative results on POCTs strongly correlated with a lack of functional humoral immunity. The third booster dose helps vaccinees gain depth and breadth of systemic Abs against evolving SARS-CoV-2 and related viruses. Our findings show that POCTs are useful and easy-to-access tools to inform inadequate humoral immunity accurately. POCTs designed to match the circulating variants can help individuals with booster vaccine decisions and could serve as a population-level screening platform to preserve herd immunity.One Sentence SummarySARS-CoV-2 point-of-care antibody tests are valuable and easy-to-access tools to inform inadequate humoral immunity and to support informed decision-making regarding the current and future booster vaccination.

Background We compared postinfection severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) neutralizing antibody (nAb) responses among children and adults while the D614G-like strain and Alpha, Iota, and Delta variants circulated. Methods During August 2020–October 2021, households with adults and children were enrolled and followed in Utah, New York City, and Maryland. Participants collected weekly respiratory swabs that were tested for SARS-CoV-2 and had sera collected during enrollment and follow-up. Sera were tested for SARS-CoV-2 nAb by pseudovirus assay. Postinfection titers were characterized with biexponential decay models. Results Eighty participants had SARS-CoV-2 infection during the study (47 with D614G-like virus, 17 with B.1.1.7, and 8 each with B.1.617.2 and B.1.526 virus). Homologous nAb geometric mean titers (GMTs) trended higher in adults (GMT = 2320) versus children 0–4 (GMT = 425, P = .33) and 5–17 years (GMT = 396, P = .31) at 1–5 weeks postinfection but were similar from 6 weeks. Timing of peak titers was similar by age. Results were consistent when participants with self-reported infection before enrollment were included (n = 178). Conclusions The SARS-CoV-2 nAb titers differed in children compared to adults early after infection but were similar by 6 weeks postinfection. If postvaccination nAb kinetics have similar trends, vaccine immunobridging studies may need to compare nAb responses in adults and children 6 weeks or more after vaccination.

SARS-CoV-2 circulating variants coupled with waning immunity pose a significant threat to the long-term care (LTC) population. Our objective was to measure salivary IgG antibodies in residents and staff of an LTC facility to (1) evaluate IgG response in saliva post-natural infection and vaccination and (2) assess its feasibility to describe the seroprevalence over time.We performed salivary IgG sampling of all residents and staff who agreed to test in a 150-bed skilled nursing facility during three seroprevalence surveys between October 2020 and February 2021. The facility had SARS-CoV-2 outbreaks in May 2020 and November 2020, when 45 of 138 and 37 of 125 residents were infected, respectively; they offered two Federal vaccine clinics in January 2021. We evaluated quantitative IgG in saliva to the Nucleocapsid (N), Spike (S), and Receptor-binding domain (RBD) Antigens of SARS-CoV-2 over time post-infection and post-vaccination.One hundred twenty-four residents and 28 staff underwent saliva serologic testing on one or more survey visits. Over three surveys, the SARS-CoV-2 seroprevalence at the facility was 49%, 64%, and 81%, respectively. IgG to S, RBD, and N Antigens all increased post infection. Post vaccination, the infection naïve group did not have a detectable N IgG level, and N IgG levels for the previously infected did not increase post vaccination (p 0.001). Fully vaccinated subjects with prior COVID-19 infection had significantly higher RBD and S IgG responses compared with those who were infection-naïve prior to vaccination (p 0.001 for both).Positive SARS-COV-2 IgG in saliva was concordant with prior infection (Anti N, S, RBD) and vaccination (Anti S, RBD) and remained above positivity threshold for up to 9 months from infection. Salivary sampling is a non-invasive method of tracking immunity and differentiating between prior infection and vaccination to inform the need for boosters in LTC residents and staff.

Objectives Since waste from swine industrial livestock operations (ILOs) produces air pollutants associated with negative health outcomes among nearby residents, we assessed the impact of odorant emissions on sleep duration and awakenings. Design A repeated-measures design. Setting Sixteen residential communities in eastern North Carolina hosting swine ILOs. Participants Eighty participants residing in eastern North Carolina from 2003 to 2005. Intervention (if any) Not applicable. Measurements Study participants completed twice-daily diaries in which they rated the strength of hog odors and indicated whether they were asleep or awake per hour for 2 weeks. Simultaneously, a monitoring trailer placed in a central location in each community measured the atmospheric concentration of hydrogen sulfide (H2S). Subject-conditional fixed-effects regression models were used to estimate associations between 2 markers of swine ILO pollutant exposures (H2S and swine odor) and 2 self-reported sleep outcomes (nightly sleep duration and awakening from sleep). Results Among 80 participants, nightly (across a 12-hour period) swine odor was associated with lower nightly sleep duration (mean difference = −14.3 minutes, 95% confidence interval −25.0 to −3.3 minutes) compared to odor-free nights and detection of nightly hydrogen sulfide was associated with an increased risk of awakening (hazard ratio = 1.23, 95% confidence interval 0.98 to 1.55) compared to nights with no detection of hydrogen sulfide. Conclusions These results suggest that environmental odorants are important considerations for sleep health and highlight the importance of sleep as a potential mediator between environmental air pollution and health outcomes impacted by poor sleep.

BackgroundOral fluid (hereafter, saliva) is a non-invasive and attractive alternative to blood for SARS-CoV-2 IgG testing; however, the heterogeneity of saliva as a matrix poses challenges for immunoassay performance.ObjectivesTo optimize performance of a magnetic microparticle-based multiplex immunoassay (MIA) for SARS-CoV-2 IgG measurement in saliva, with consideration of: i) threshold setting and validation across different MIA bead batches; ii) sample qualification based on salivary total IgG concentration; iii) calibration to U.S. SARS-CoV-2 serological standard binding antibody units (BAU); and iv) correlations with blood-based SARS-CoV-2 serological and neutralizing antibody (nAb) assays.MethodsThe salivary SARS-CoV-2 IgG MIA included 2 nucleocapsid (N), 3 receptor-binding domain (RBD), and 2 spike protein (S) antigens. Gingival crevicular fluid (GCF) swab saliva samples were collected before December, 2019 (n=555) and after molecular test-confirmed SARS-CoV-2 infection from 113 individuals (providing up to 5 repeated-measures; n=398) and used to optimize and validate MIA performance (total n=953). Combinations of IgG responses to N, RBD and S and total salivary IgG concentration (μg/mL) as a qualifier of nonreactive samples were optimized and validated, calibrated to the U.S. SARS-CoV-2 serological standard, and correlated with blood-based SARS-CoV-2 IgG ELISA and nAb assays.ResultsThe sum of signal to cutoff (S/Co) to all seven MIA SARS-CoV-2 antigens and disqualification of nonreactive saliva samples with ≤15 μg/mL total IgG led to correct classification of 62/62 positives (sensitivity [Se]=100.0%; 95% confidence interval [CI]=94.8%, 100.0%) and 108/109 negatives (specificity [Sp]=99.1%; 95% CI=97.3%, 100.0%) at 8-million beads coupling scale and 80/81 positives (Se=98.8%; 95% CI=93.3%, 100.0%] and 127/127 negatives (Sp=100%; 95% CI=97.1%, 100.0%) at 20-million beads coupling scale. Salivary SARS-CoV-2 IgG crossed the MIA cutoff of 0.1 BAU/mL on average 9 days post-COVID-19 symptom onset and peaked around day 30. Among n=30 matched saliva and plasma samples, salivary SARS-CoV-2 MIA IgG levels correlated with corresponding-antigen plasma ELISA IgG (N: ρ=0.67, RBD: ρ=0.76, S: ρ=0.82; allpppConclusionsA salivary SARS-CoV-2 IgG MIA produced consistently high Se (>98.8%) and Sp (>99.1%) across two bead coupling scales and correlations with nAb responses that were similar to blood-based SARS-CoV-2 IgG ELISA data. This non-invasive salivary SARS-CoV-2 IgG MIA could increase engagement of vulnerable populations and improve broad understanding of humoral immunity (kinetics and gaps) within the evolving context of booster vaccination, viral variants and waning immunity.

Antinucleocapsid (anti-N) immunoglobulin G antibody responses were lower in plasma and oral fluid after severe acute respiratory syndrome coronavirus 2 infection in vaccinated patients compared with patients infected before vaccination or infected without vaccination. This raises questions about the long-term use of anti-N antibodies as a marker for natural infection for surveillance.

Background Congregate military populations remain at risk of SARS-CoV-2 outbreaks and the optimal surveillance approach in such settings remains unclear. We enrolled midshipmen at the United States Naval Academy (USNA) in a setting of frequent PCR screening use of prevention strategies. Methods Dried blood spots (DBS) and saliva were collected in August 2020, December 2020, February 2021 (saliva only) and April/May 2021 to measure anti-SARS-CoV-2 spike (S) and nucleoprotein (NP) IgG. COVID-19 vaccine history and records of SARS-CoV-2 PCR tests and routine asymptomatic screening assays were obtained from the USNA Brigade Medical Clinic. Attack rates were compared with cumulative frequencies of infections. Concordance of saliva and DBS anti-NP and anti-S IgG positivity was determined using Cohen’s kappa coefficient. Results The study enrolled 181 midshipmen. COVID-19 vaccinations were administered in March/April 2021. Samples were collected for 101 participants in August, 73 in December, 57 in February (saliva only), and 63 in April/May. In August, 17 (17%) participants showed evidence of SARS-CoV-2 infection based on anti-S IgG values from DBS and/or saliva. By December 2020, anti-S seroconversion was observed for 5 more based on DBS and/or saliva. By May 2021, 100% of participants were anti-S IgG seropositive after vaccination based on DBS and/or saliva; 48% of participants had seroconverted to anti-NP IgG. Among participants with both DBS and saliva samples, a coefficient of 0.64 showed substantial agreement between anti-S IgG results in August and perfect agreement in December (Table 1). DBS and saliva results for anti-NP IgG were in perfect agreement through December and in substantial agreement in May (0.68, Table 2). Prior to vaccination in March/April 2021, 4/48 of participants had at least one documented SARS-CoV-2 PCR positive result (Table 3). Cumulative PCR test positivity concordance with DBS seroconversion was 37.5% and 60% for anti-S IgG and anti-NP IgG, respectively. Conclusion There was a substantive SARS-CoV-2 attack rate before vaccination; all vaccinees mounted an anti-S IgG response in blood. We note high agreement between DBS and saliva for IgG measurement. Serology-based surveillance identified substantially more SARS-CoV-2 infections than PCR screening. Disclosures Jitendrakumar Modi, MD, GlaxoSmithKline: I am a paid speaker for GSK. I do not speak for their flu brand. Timothy H. Burgess, MD, MPH, AstraZeneca: The HJF, in support of the USU IDCRP, was funded to conduct or augment unrelated Phase III Mab and vaccine trials as part of US Govt. COVID19 response Simon Pollett, MBBS, Astra Zeneca: The HJF, in support of the USU IDCRP, was funded to conduct or augment unrelated Phase III Mab and vaccine trials as part of US Govt. COVID19 response Mark P. Simons, PhD, AstraZeneca: The HJF, in support of the USU IDCRP, was funded to conduct or augment unrelated Phase III Mab and vaccine trials as part of US Govt. COVID19 response.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has emphasized the importance and challenges of correctly interpreting antibody test results. Identification of positive and negative samples requires a classification strategy with low error rates, which is hard to achieve when the corresponding measurement values overlap. Additional uncertainty arises when classification schemes fail to account for complicated structure in data. We address these problems through a mathematical framework that combines high dimensional data modeling and optimal decision theory. Specifically, we show that appropriately increasing the dimension of data better separates positive and negative populations and reveals nuanced structure that can be described in terms of mathematical models. We combine these models with optimal decision theory to yield a classification scheme that better separates positive and negative samples relative to traditional methods such as confidence intervals (CIs) and receiver operating characteristics. We validate the usefulness of this approach in the context of a multiplex salivary SARS-CoV-2 immunoglobulin G assay dataset. This example illustrates how our analysis: (i) improves the assay accuracy (e.g. lowers classification errors by up to 42 % compared to CI methods); (ii) reduces the number of indeterminate samples when an inconclusive class is permissible (e.g. by 40 % compared to the original analysis of the example multiplex dataset); and (iii) decreases the number of antigens needed to classify samples. Our work showcases the power of mathematical modeling in diagnostic classification and highlights a method that can be adopted broadly in public health and clinical settings.

Industrial livestock operations (ILOs), particularly processing facilities, emerged as centers of coronavirus disease 2019 (COVID-19) outbreaks in spring 2020. Confirmed cases of COVID-19 underestimate true prevalence. To investigate prevalence of antibodies against SARS-CoV-2, we enrolled 279 participants in North Carolina from February 2021 to July 2022: 90 from households with at least one ILO worker (ILO), 97 from high-ILO intensity areas (ILO neighbors – ILON), and 92 from metropolitan areas (Metro). Participants provided a saliva swab we analyzed for SARS-CoV-2 IgG using a multiplex immunoassay. Prevalence of infection-induced IgG (positive for nucleocapsid and receptor binding domain) was higher among ILO (63%) compared to ILON (42.9%) and Metro (48.7%) participants (prevalence ratio [PR] =1.38; 95% confidence interval [CI]: 1.06, 1.80; ref. ILON and Metro combined). Prevalence of infection-induced IgG was also higher among ILO participants compared to an Atlanta healthcare worker cohort (PR=2.45, 95% CI: 1.8, 3.3) and a general population cohort in North Carolina (PRs 6.37-10.67). Infection-induced IgG prevalence increased over the study period. Participants reporting not masking in public in the past two weeks had higher infection-induced IgG prevalence (78.6%) compared to participants reporting masking (49.3%) (PR=1.59; 95% CI: 1.19, 2.13). Lower education, more people per bedroom, Hispanic/Latino ethnicity, and more contact with people outside the home were also associated with higher infection-induced IgG prevalence. Similar proportions of ILO (51.6%), ILON (48.4%), and Metro (55.4%) participants completed the COVID-19 primary vaccination series; median completion was more than four months later for ILO compared to ILON and Metro participants.ImportanceFew studies have measured COVID-19 seroprevalence in North Carolina, especially among rural, Black, and Hispanic/Latino communities that have been heavily affected. Antibody results show high rates of COVID-19 among industrial livestock operation workers and their household members. Antibody results add to evidence of health disparities in COVID-19 by socioeconomic status and ethnicity. Associations between masking and physical distancing with antibody results also add to evidence of the effectiveness of these prevention strategies. Delays in the timing of receipt of COVID-19 vaccination reinforce the importance of dismantling vaccination barriers, especially for industrial livestock operation workers and their household members.

Introduction Occupational activities related to industrial hog operation (IHO) worker lung function are not well defined. Therefore, we aimed to identify IHO work activities associated with diminished respiratory function and the effectiveness, if any, of personal protective equipment (PPE) use on IHOs. Methods From 2014 to 2015, 103 IHO workers were enrolled and followed for 16 weeks. At each biweekly visit, work activities and PPE use were self-reported via questionnaire and lung function measurements were collected via spirometry. Generalized linear and linear fixed-effects models were fitted to cross-sectional and longitudinal data. Results Increasing years worked on an IHO were associated with diminished lung function, but baseline and longitudinal work activities were largely inconsistent in direction and magnitude. Unexpectedly, a -0.3 L (95% confidence interval: -0.6, -0.04) difference in forced expiratory volume in the first second (FEV1 ) was estimated when workers wore PPE consistently (≥80% of the time at work) versus those weeks they did not. In post-hoc analyses, we found that coveralls and facemasks were worn less consistently when workers experienced worse barn conditions and had more contact with pigs, but coveralls were worn more consistently as cleaning activities increased. Conclusions Similar to past studies, baseline estimates were likely obscured by healthy worker effect bias, but showed decrements in worker lung function as years of work increased. A challenge to disentangling the effect of work activities on lung function was the discovery that IHO workers used PPE differently according to the work task. These data suggest that interventions may be targeted toward improving barn conditions so that workers can consistently utilize IHO-provided PPE.

Background Global efforts are needed to elucidate the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the underlying cause of coronavirus disease 2019 (COVID-19), including seroprevalence, risk factors, and long-term sequelae, as well as immune responses after vaccination across populations and the social dimensions of prevention and treatment strategies. Methods In the United States, the National Cancer Institute in partnership with the National Institute of Allergy and Infectious Diseases, established the SARS-CoV-2 Serological Sciences Network (SeroNet) as the nation’s largest coordinated effort to study coronavirus disease 2019. The network comprises multidisciplinary researchers bridging gaps and fostering collaborations among immunologists, epidemiologists, virologists, clinicians and clinical laboratories, social and behavioral scientists, policymakers, data scientists, and community members. In total, 49 institutions form the SeroNet consortium to study individuals with cancer, autoimmune disease, inflammatory bowel diseases, cardiovascular diseases, human immunodeficiency virus, transplant recipients, as well as otherwise healthy pregnant women, children, college students, and high-risk occupational workers (including healthcare workers and first responders). Results Several studies focus on underrepresented populations, including ethnic minorities and rural communities. To support integrative data analyses across SeroNet studies, efforts are underway to define common data elements for standardized serology measurements, cellular and molecular assays, self-reported data, treatment, and clinical outcomes. Conclusions In this paper, we discuss the overarching framework for SeroNet epidemiology studies, critical research questions under investigation, and data accessibility for the worldwide scientific community. Lessons learned will help inform preparedness and responsiveness to future emerging diseases.

Transmission of livestock-associated Staphylococcus aureus clonal complex 9 (LA-SA CC9) between pigs raised on industrial hog operations (IHOs) and humans in the United States is poorly understood. We analyzed whole-genome sequences from 32 international S. aureus CC9 isolates and 49 LA-SA CC9 isolates from IHO pigs and humans who work on or live near IHOs in 10 pig-producing counties in North Carolina, USA. Bioinformatic analysis of sequence data from the 81 isolates demonstrated 3 major LA-SA CC9 clades. North Carolina isolates all fell within a single clade (C3). High-resolution phylogenetic analysis of C3 revealed 2 subclades of intermingled IHO pig and human isolates differing by 0–34 single-nucleotide polymorphisms. Our findings suggest that LA-SA CC9 from pigs and humans share a common source and provide evidence of transmission of antimicrobial-resistant LA-SA CC9 between IHO pigs and humans who work on or live near IHOs in North Carolina.

Recent advances in molecular source tracking make answering questions from residents regarding their exposure to microbial contaminants from industrial hog operations (IHOs) possible. Associations between residential distance to IHOs and exposure can be addressed by measuring livestock-associated (Staphylococcus aureus) and pig-specific bacteria in the air, on household surfaces, and in participants' nasal and saliva swabs.Here we assess the mechanics, feasibility, capacity-building, and lessons learned during a pilot study employing this novel technology in community-based participatory research of bacterial exposure and human health.Together, our team of academics and community members designed a field- and laboratory-based pilot study. Air samples, surface and human swabs, and questionnaires from households at varying distances from IHOs were collected. Data were assessed for completeness and quality by two independent reviewers. These metrics were defined as: missingness (completeness), incorrect data type (validity), out of range (validity), and outliers (accuracy).While critical field equipment was obtained, and knowledge exchange occurred, leading to an increased capacity for future work, after review, 38 of 49 households were deemed eligible for inclusion in the study. Of eligible participants, 98% of required electronic survey questions were complete and 100% were valid; an improvement over prior work which employed paper surveys. While all human microbial and air samples were collected from eligible households (n = 231), (5%) of environmental swabs were reported missing.Using community-appropriate sampling protocols, a pilot study of residential exposure to bacteria from IHOs was completed. While high-quality data was collected from those eligible, we learned the necessity of early and continual data review.

In diagnostic testing, establishing an indeterminate class is an effective way to identify samples that cannot be accurately classified. However, such approaches also make testing less efficient and must be balanced against overall assay performance. We address this problem by reformulating data classification in terms of a constrained optimization problem that (i) minimizes the probability of labeling samples as indeterminate while (ii) ensuring that the remaining ones are classified with an average target accuracy X. We show that the solution to this problem is expressed in terms of a bathtub-type principle that holds out those samples with the lowest local accuracy up to an X-dependent threshold. To illustrate the usefulness of this analysis, we apply it to a multiplex, saliva-based SARS-CoV-2 antibody assay and demonstrate up to a 30 % reduction in the number of indeterminate samples relative to more traditional approaches.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has emphasized the importance and challenges of correctly interpreting antibody test results. Identification of positive and negative samples requires a classification strategy with low error rates, which is hard to achieve when the corresponding measurement values overlap. Additional uncertainty arises when classification schemes fail to account for complicated structure in data. We address these problems through a mathematical framework that combines high dimensional data modeling and optimal decision theory. Specifically, we show that appropriately increasing the dimension of data better separates positive and negative populations and reveals nuanced structure that can be described in terms of mathematical models. We combine these models with optimal decision theory to yield a classification scheme that better separates positive and negative samples relative to traditional methods such as confidence intervals (CIs) and receiver operating characteristics. We validate the usefulness of this approach in the context of a multiplex salivary SARS-CoV-2 immunoglobulin G assay dataset. This example illustrates how our analysis: (i) improves the assay accuracy (e.g. lowers classification errors by up to 42 % compared to CI methods); (ii) reduces the number of indeterminate samples when an inconclusive class is permissible (e.g. by 40 % compared to the original analysis of the example multiplex dataset); and (iii) decreases the number of antigens needed to classify samples. Our work showcases the power of mathematical modeling in diagnostic classification and highlights a method that can be adopted broadly in public health and clinical settings., Comment: 14 pages, 4 figures, 1 table, 6 supplemental figures; fixed typos/updated table, corrected PDF in Appendix

Industrial hog operation (IHO) workers can be occupationally exposed to Staphylococcus aureus and may carry the bacteria in their nares. Workers may persistently carry S. aureus or transition between different states of nasal carriage over time: no nasal carriage, nasal carriage of a human-associated strain, and nasal carriage of a livestock-associated strain. We aimed to develop a mathematical model to predict the proportion of IHO workers in each nasal carriage state over time, accounting for IHO worker mask use. We also examined data sufficiency requirements to inform development of models that produce reliable predictions. We used nasal carriage data from a cohort of 101 IHO workers in North Carolina, sampled every two weeks for 4 months, to develop a three state Markov model that describes the transition dynamics of IHO worker nasal carriage status over the study period and at steady state. We also stratified models by mask use to examine its impact on worker transition dynamics. If conditions remain the same, our models predicted that 49.1% of workers will have no nasal carriage of S. aureus, 28.2% will carry livestock-associated S. aureus, and 22.7% will carry human-associated S. aureus at steady state. In stratified models, at steady state, workers who reported only occasional mask (

Antimicrobial use (AMU) in animal agriculture contributes to antimicrobial resistance (AMR) in humans, which imposes significant health and economic costs on society. Economists call these costs negative externalities, societal costs that are not properly reflected in market prices. We review the relevant literature and develop a model to quantify the external costs of AMU in animal agriculture on AMR in humans. Parameters required for this estimate include ( a) the health and economic burden of AMR in humans,( b) the impact of AMU in animal agriculture on AMR in animals, ( c) the fraction of AMR in humans attributable to animal agriculture, and ( d) AMU in animals. We use a well-documented historic case to estimate an externality cost of about US$1,500 per kilogram of fluoroquinolones administered in US broiler chicken production. Enhanced data collection, particularly on the third and fourth parameters, is urgently needed to quantify more fully the externalities of AMU in animal agriculture.

Infectious disease surveillance systems support early warning, promote preparedness, and inform public health response. Pathogens that have human, animal, and environmental reservoirs should be monitored through systems that incorporate a One Health approach. In 2016, Thailand's federal government piloted an avian influenza (AI) surveillance system that integrates stakeholders from human, animal, and environmental sectors, at the central level and in four provinces to monitor influenza A viruses within human, waterfowl, and poultry populations. This research aims to describe and evaluate Thailand's piloted AI surveillance system to inform strategies for strengthening and building surveillance systems relevant to One Health. We assessed this surveillance system using the United States Centers for Disease Control and Prevention's (U.S. CDC) "Guidelines for Evaluating Public Health Surveillance Systems" and added three novel metrics: transparency, interoperability, and security. In-depth key informant interviews were conducted with representatives among six Thai federal agencies and departments, the One Health coordinating unit, a corporate poultry producer, and the Thai Ministry of Public Health-U.S. CDC Collaborating Unit. Thailand's AI surveillance system demonstrated strengths in acceptability, simplicity, representativeness, and flexibility, and exhibited challenges in data quality, stability, security, interoperability, and transparency. System efforts may be strengthened through increasing laboratory integration, improving pathogen detection capabilities, implementing interoperable systems, and incorporating sustainable capacity building mechanisms. This innovative piloted surveillance system provides a strategic framework that can be used to develop, integrate, and bolster One Health surveillance approaches to combat emerging global pathogen threats and enhance global health security.

This study investigates the impact of changes in local industry, urban development, and proximity to suspected emission sources on airborne metal concentration in Baltimore, Maryland between 2001 and 2019 with particular focus on the urban industrial community of Curtis Bay in South Baltimore.Integrated PMPMDeclines in airborne Cr, Ni, Pb, and Zn concentration since 2001 appear to coincide with industrial decline highlighting the success of remediation and redevelopment efforts. Remaining spatial variability is related to vehicular traffic and proximity to a municipal incinerator which should be focal areas for future intervention to reduce metal exposure disparities in Baltimore City.

Serological tests play an important role in the fight against Coronavirus Disease 2019 (COVID-19), including monitoring the dynamic immune response after vaccination, identifying past infection and determining community infection rate. Conventional methods for serological testing, such as enzyme-linked immunosorbent assays and chemiluminescence immunoassays, provide reliable and sensitive antibody detection but require sophisticated laboratory infrastructure and/or lengthy assay time. Conversely, lateral flow immunoassays are suitable for rapid point-of-care tests but have limited sensitivity. Here, we describe the development of a rapid and sensitive magnetofluidic immuno-PCR platform that can address the current gap in point-of-care serological testing for COVID-19. Our magnetofluidic immuno-PCR platform automates a magnetic bead-based, single-binding, and one-wash immuno-PCR assay in a palm-sized magnetofluidic device and delivers results in ∼30 min. In the device, a programmable magnetic arm attracts and transports magnetically-captured antibodies through assay reagents pre-loaded in a companion plastic cartridge, and a miniaturized thermocycler and a fluorescence detector perform immuno-PCR to detect the antibodies. We evaluated our magnetofluidic immuno-PCR with 108 clinical serum/plasma samples and achieved 93.8% (45/48) sensitivity and 98.3% (59/60) specificity, demonstrating its potential as a rapid and sensitive point-of-care serological test for COVID-19.

BACKGROUND AND AIM: Arsenic methylation—the conversion of inorganic arsenic (iAs) to less toxic monomethyl (MMA) and dimethyl (DMA) species—could modify the developmental and reproductive toxicity ...

BackgroundSustained molecular detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in the upper respiratory tract (URT) in mild to moderate coronavirus disease 2019 (COVID-19) is common. We sought to identify host and immune determinants of prolonged SARS-CoV-2 RNA detection.MethodsNinety-five symptomatic outpatients self-collected midturbinate nasal, oropharyngeal (OP), and gingival crevicular fluid (oral fluid) samples at home and in a research clinic a median of 6 times over 1–3 months. Samples were tested for viral RNA, virus culture, and SARS-CoV-2 and other human coronavirus antibodies, and associations were estimated using Cox proportional hazards models.ResultsViral RNA clearance, as measured by SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR), in 507 URT samples occurred a median (interquartile range) 33.5 (17–63.5) days post–symptom onset. Sixteen nasal-OP samples collected 2–11 days post–symptom onset were virus culture positive out of 183 RT-PCR-positive samples tested. All participants but 1 with positive virus culture were negative for concomitant oral fluid anti-SARS-CoV-2 antibodies. The mean time to first antibody detection in oral fluid was 8–13 days post–symptom onset. A longer time to first detection of oral fluid anti-SARS-CoV-2 S antibodies (adjusted hazard ratio [aHR], 0.96; 95% CI, 0.92–0.99; P = .020) and body mass index (BMI) ≥25 kg/m2 (aHR, 0.37; 95% CI, 0.18–0.78; P = .009) were independently associated with a longer time to SARS-CoV-2 viral RNA clearance. Fever as 1 of first 3 COVID-19 symptoms correlated with shorter time to viral RNA clearance (aHR, 2.06; 95% CI, 1.02–4.18; P = .044).ConclusionsWe demonstrate that delayed rise of oral fluid SARS-CoV-2-specific antibodies, elevated BMI, and absence of early fever are independently associated with delayed URT viral RNA clearance.

Lyme disease is the most common vector-borne disease in the United States. Electronic health record (EHR)-based research on Lyme disease is limited. We used Geisinger EHR data from 479,344 primary care patients in 38 Pennsylvania counties in 2006–2014 to compare EHR-based Lyme disease incidence rates to surveillance incidence rates, evaluate individual and community risk factors for incident Lyme disease, and to characterize the proportion of cases with diagnoses consistent with post-treatment Lyme disease syndrome in the EHR (PTLDSEHR). We primarily identified Lyme disease cases using diagnosis codes, serologic testing order codes, and medication orders but also completed subgroup analyses among those with positive serology and those with both diagnosis code and antibiotic treatment. We compared annual incidence rates from the EHR to surveillance by age, sex, and county. In case-control analyses, we compared cases to randomly selected controls (5:1) frequency-matched on year, age, and sex. We identified 9657 cases of Lyme disease, including 1791 cases with positive serology and 4992 cases with both diagnosis code and antibiotic treatment. Annual incidence rates in the EHR were 4.25–7.43 times higher than surveillance. In adjusted analyses, white non-Hispanic race/ethnicity (vs. black, Hispanic, or other) was associated with higher odds of Lyme disease (odds ratio [OR]: 2.06, 95% confidence interval [CI]: 1.73–2.44). Medical Assistance insurance use (always vs. never; OR: 0.77, 95% CI: 0.68–0.88), and higher community-level socioeconomic deprivation (quartile 4 vs. 1 OR: 0.50 (95% CI: 0.42–0.59) were associated with lower odds of Lyme disease. Within 4–52 weeks after Lyme disease diagnosis, 20.8% (n = 735) of cases with a diagnosis code and treatment had a diagnosis of malaise or fatigue, pain, or cognitive difficulties not present in the past 26 weeks. These results highlight the utility of EHR data for epidemiologic research on Lyme disease for case-finding, surveillance, risk factor evaluation, and characterization of PTLDS using EHR data.

Background Norovirus is a leading cause of acute gastroenteritis worldwide. Routine norovirus diagnosis requires stool collection. The goal of this study was to develop and validate a noninvasive method to diagnose norovirus to complement stool diagnostics and to facilitate studies on transmission. Methods A multiplex immunoassay to measure salivary immunoglobulin G (IgG) responses to 5 common norovirus genotypes (GI.1, GII.2, GII.4, GII.6, and GII.17) was developed. The assay was validated using acute and convalescent saliva samples collected from Peruvian children, This study describes the performance of a multiplex immunoassay to measure salivary immunoglobulin G responses to multiple norovirus genotypes. The assay diagnosed recent norovirus infections at the genotype level with 71% sensitivity and 96% specificity compared to stool-based polymerase chain reaction diagnosis.

The term “ag-gag” refers to state laws that intentionally limit public access to information about agricultural production practices, particularly livestock production. Originally created in the 1990s, these laws have recently experienced a resurgence in state legislatures. We discuss the recent history of ag-gag laws in the United States and question whether such ag-gag laws create a “chilling effect” on reporting and investigation of occupational health, community health, and food safety concerns related to industrial food animal production. We conclude with a discussion of the role of environmental and occupational health professionals to encourage critical evaluation of how ag-gag laws might influence the health, safety, and interests of day-to-day agricultural laborers and the public living proximal to industrial food animal production.

We evaluated the durability of IgG responses specific to SARS-CoV-2 nucleocapsid (N), receptor binding domain (RBD), and spike (S) antigens in saliva up to 8 months after RT-PCR-confirmed COVID-19 using a multiplex salivary assay. We estimated a half-life of 64 days (d) (95% CI: 49, 80 d) for N, 100 d for RBD (95% CI: 58, 141 d), and 148 d (95% CI: 62, 238 d) for S IgG responses in saliva, consistent with half-life estimates previously reported in blood. Saliva can serve as an alternative to blood to monitor humoral immune responses on a large scale following SARS-CoV-2 infection and vaccination for surveillance and assessment of population immunity.

Background Nepal’s poultry industry has increased with a growing middle class, which has translated to an increase in antimicrobial consumption and thus a rise in antimicrobial resistance (AMR). Describing and understanding antimicrobial use practices among commercial poultry producers in Nepal may help minimize the risks of AMR development in both humans and animals and determine the effectiveness of relevant policies. Methods From July to August 2018, poultry farmers were randomly recruited from Nepal’s Chitwan District to participate in a cross-sectional study. The lead producer in each poultry operation was administered a quantitative structured-survey via a 30-min interview. Participants were asked to provide demographics, production practices, and knowledge about their antimicrobial use practices. Descriptive data analysis was performed to obtain frequencies and compare practices. Results In total, 150 commercial poultry producers of whom raised between 300 and 40,000 birds completed the interviews. Only 33% (n = 49) of producers reported knowing what AMR was, and among them only 50% (n = 25) consulted a veterinarian for treatment options. Antimicrobial administration for growth promotion was still employed by 13% of poultry producers. Similarly, critically important antimicrobial drugs, specifically colistin, were identified at 35% of participating operations. Producers reported low overall understanding and compliance of withdrawal periods (n = 41; 27%), which may result in both AMR development and adverse health reactions among consumers who ingest antimicrobial residues. Although Nepal has publicized antimicrobial use policies and awareness campaigns to instill healthy production practices, most producers (82%) were unaware of them. Conclusion Many Nepalese poultry producers lack overall antimicrobial use and AMR awareness, which is evidenced by low antimicrobial withdrawal period compliance, use of antimicrobials for growth promotion, and the sustained use of critically important antimicrobials. Improved outreach and educational capacities, paired with increased veterinary resources and extensive monitoring in operations and retail meat products, may increase AMR awareness and policy enforcement.

How weather affects tick development and behavior and human Lyme disease remains poorly understood. We evaluated relations of temperature and humidity during critical periods for the tick lifecycle with human Lyme disease. We used electronic health records from 479,344 primary care patients in 38 Pennsylvania counties in 2006-2014. Lyme disease cases (n = 9657) were frequency-matched (5:1) by year, age, and sex. Using daily weather data at ~4 km2 resolution, we created cumulative metrics hypothesized to promote (warm and humid) or inhibit (hot and dry) tick development or host-seeking during nymph development (March 1-May 31), nymph activity (May 1-July 30), and prior year larva activity (Aug 1-Sept 30). We estimated odds ratios (ORs) of Lyme disease by quartiles of each weather variable, adjusting for demographic, clinical, and other weather variables. Exposure-response patterns were observed for higher cumulative same-year temperature, humidity, and hot and dry days (nymph-relevant), and prior year hot and dry days (larva-relevant), with same-year hot and dry days showing the strongest association (4th vs. 1st quartile OR = 0.40; 95% confidence interval [CI] = 0.36, 0.43). Changing temperature and humidity could increase or decrease human Lyme disease risk.

INTRODUCTION Respiratory disease among industrial hog operation (IHO) workers is well documented; however, it remains unclear whether specific work activities are more harmful and if personal protective equipment (PPE), as used by workers, can reduce adverse health outcomes. METHODS IHO workers (n = 103) completed baseline and up to eight bi-weekly study visits. Workers reported typical (baseline) and transient (bi-weekly) work activities, PPE use, and physical health symptoms. Baseline and longitudinal associations were assessed using generalized logistic and fixed-effects logistic regression models, respectively. RESULTS At baseline, reports of ever versus never drawing pig blood, applying pesticides, and increasing years worked at any IHO were positively associated with reports of eye, nose, and/or throat irritation. Over time, transient exposures, associated with dustiness in barns, cleaning of barns, and pig contact were associated with increased odds of sneezing, headache, and eye or nose irritation, particularly in the highest categories of exposure. When PPE was used, workers had lower odds of symptoms interfering with sleep (odds ratio [OR]: 0.1; 95% confidence interval [CI]: 0.01-0.8), and eye or nose irritation (OR: 0.1; 95% CI: 0.02-0.9). Similarly, when they washed their hands eight times or more per shift (median frequency) versus less frequently, the odds of any respiratory symptom were reduced (OR: 0.3; 95% CI: 0.1-0.8). CONCLUSIONS In this healthy volunteer worker population, increasingly unfavorable IHO activities were associated with self-reported eye, nose, throat, and respiratory health symptoms. Strong protective associations were seen between PPE use and handwashing and the odds of symptoms, warranting further investigation.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of an ongoing pandemic that has infected over 36 million and killed over 1 million people. Informed implementation of government public health policies depends on accurate data on SARS-CoV-2 immunity at a population scale. We hypothesized that detection of SARS-CoV-2 salivary antibodies could serve as a noninvasive alternative to serological testing for monitoring of SARS-CoV-2 infection and seropositivity at a population scale., Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of an ongoing pandemic that has infected over 36 million and killed over 1 million people. Informed implementation of government public health policies depends on accurate data on SARS-CoV-2 immunity at a population scale. We hypothesized that detection of SARS-CoV-2 salivary antibodies could serve as a noninvasive alternative to serological testing for monitoring of SARS-CoV-2 infection and seropositivity at a population scale. We developed a multiplex SARS-CoV-2 antibody immunoassay based on Luminex technology that comprised 12 CoV antigens, mostly derived from SARS-CoV-2 nucleocapsid (N) and spike (S). Saliva and sera collected from confirmed coronavirus disease 2019 (COVID-19) cases and from the pre-COVID-19 era were tested for IgG, IgA, and IgM to the antigen panel. Matched saliva and serum IgG responses (n = 28) were significantly correlated. The salivary anti-N IgG response resulted in the highest sensitivity (100%), exhibiting a positive response in 24/24 reverse transcription-PCR (RT-PCR)-confirmed COVID-19 cases sampled at >14 days post-symptom onset (DPSO), whereas the salivary anti-receptor binding domain (RBD) IgG response yielded 100% specificity. Temporal kinetics of IgG in saliva were consistent with those observed in blood and indicated that most individuals seroconvert at around 10 DPSO. Algorithms employing a combination of the IgG responses to N and S antigens result in high diagnostic accuracy (100%) by as early as 10 DPSO. These results support the use of saliva-based antibody testing as a noninvasive and scalable alternative to blood-based antibody testing.

Avian influenza (AI) is a global health obstacle of critical concern as novel viruses are capable of initiating a pandemic. Recent spillover events of AI into human populations have occurred at human-poultry food system interfaces. As Nepal's poultry sector transitions to more intensified commercial production systems, it is important to examine the epidemiology of AI and the knowledge, attitudes and practices (KAP) of poultry sector workers. We conducted a cross-sectional KAP study utilizing a structured survey to interview 150 commercial poultry farmers in Chitwan District, Nepal. All commercial poultry farmers had knowledge of AI previous to the study and the majority farmers were able to identify farm-farm and poultry-human transmission mechanisms of AI. Farmers had more knowledge surrounding poultry AI symptoms as compared to human AI symptoms. Most farmers believe that AI is serious, contagious and a threat to everyone, yet only half believe it can be prevented. Individual-level personal protective equipment (PPE) uptake, such as facemask, glove and boot usage, on the enrolled farms was low and farm-level biosecurity practices varied greatly. Nine commercial poultry farms (6%) self-reported having an HPAI outbreak and 60 farms (40%) self-reported having an LPAI outbreak in the past 5 years. Layer farms had higher odds (OR: 5.4, 95% CI: 2.3–12.8) of self-reported LPAI as compared broiler farms. Poultry sector farmers face multiple obstacles when attempting to report AI to government authorities such as the fear of flock culling and the perceived lack of monetary compensation for culling. Our study provides updated KAP surrounding AI of farmers and self-reported AI farm-level epidemiology in Nepal's highest density commercial poultry production district. Commercial poultry farmers are fairly knowledgeable on AI, but do not take further protective practice efforts to implement their knowledge and prevent AI. Due to the potential role that human-poultry interfaces may play in AI emergence, it is critical to collaborate with the commercial poultry industry when planning and conducting AI pandemic preparedness mechanisms., Highlights • Farmers had more knowledge surrounding poultry avian influenza symptoms as compared to human avian influenza symptoms. • Farmer personal protective equipment (PPE) uptake, such as facemask, glove and boot usage, was low. • 6% of poultry farms self-reported having an HPAI outbreak and 40% self-reported having an LPAI outbreak in the past 5 years. • Layer farms had higher odds of self-reported LPAI as compared broiler farms. • Poultry farmers fear potential flock culling and lack of monetary compensation for culling when reporting avian influenza.