Exploring Natural Immune Responses to Shigella Exposure Using Multiplex Bead Assays on Dried Blood Spots in High-Burden Countries: Protocol From a Multisite Diarrhea Surveillance Study.

Background: Molecular diagnostics on human fecal samples have identified a larger burden of shigellosis than previously appreciated by culture. Evidence of fold changes in immunoglobulin G (IgG) to conserved and type-specific Shigella antigens could be used to validate the molecular assignment of type-specific Shigella as the etiology of acute diarrhea and support polymerase chain reaction (PCR)-based microbiologic end points for vaccine trials. Methods: We will test dried blood spots collected at enrollment and 4 weeks later using bead-based immunoassays for IgG to invasion plasmid antigen B and type-specific lipopolysaccharide O-antigen for Shigella flexneri 1b, 2a, 3a, and 6 and Shigella sonnei in Shigella-positive cases and age-, site-, and season-matched test-negative controls from all sites in the Enterics for Global Health (EFGH) Shigella surveillance study. Fold antibody responses will be compared between culture-positive, culture-negative but PCR-attributable, and PCR-positive but not attributable cases and test-negative controls. Age- and site-specific seroprevalence distributions will be identified, and the association between baseline antibodies and Shigella attribution will be estimated. Conclusions: The integration of these assays into the EFGH study will help support PCR-based attribution of acute diarrhea to type-specific Shigella, describe the baseline seroprevalence of conserved and type-specific Shigella antibodies, and support correlates of protection for immunity to Shigella diarrhea. These insights can help support the development and evaluation of Shigella vaccine candidates.

SARS-CoV-2 antibody prevalence by industry, workplace characteristics, and workplace infection prevention and control measures, North Carolina, 2021 to 2022.

Background: The COVID-19 pandemic has disproportionately affected workers in certain industries and occupations, and the workplace can be a high risk setting for SARS-CoV-2 transmission. In this study, we measured SARS-CoV-2 antibody prevalence and identified work-related risk factors in a population primarily working at industrial livestock operations. Methods: We used a multiplex salivary SARS-CoV-2 IgG antibody assay to determine infection-induced antibody prevalence among 236 adult (≥18 years) North Carolina residents between February 2021 and August 2022. We used the National Institute for Occupational Safety and Health Industry and Occupation Computerized Coding System (NIOCCS) to classify employed participants' industry and compared infection-induced IgG prevalence by participant industry and with the North Carolina general population. We also combined antibody results with reported SARS-CoV-2 molecular test positivity and vaccination history to identify evidence of prior infection. We used logistic regression to estimate odds ratios of prior infection by potential work-related risk factors, adjusting for industry and date. Results: Most participants (55%) were infection-induced IgG positive, including 71% of animal slaughtering and processing industry workers, which is 1.5 to 4.3 times higher compared to the North Carolina general population, as well as higher than molecularly-confirmed cases and the only other serology study we identified of animal slaughtering and processing workers. Considering questionnaire results in addition to antibodies, the proportion of participants with evidence of prior infection increased slightly, to 61%, including 75% of animal slaughtering and processing workers. Participants with more than 1000 compared to 10 or fewer coworkers at their jobsite had higher odds of prior infection (adjusted odds ratio [aOR] 4.5, 95% confidence interval [CI] 1.0 to 21.0). Conclusions: This study contributes evidence of the severe and disproportionate impacts of COVID-19 on animal processing and essential workers and workers in large congregate settings. We also demonstrate the utility of combining non-invasive biomarker and questionnaire data for the study of workplace exposures.

Urinary IL-6 and IL-8 as predictive markers in bladder urothelial carcinoma: A pilot study.

BACKGROUND: Cytokines are known to be a key a factor in numerous malignancies and to exert an important regulatory role in the tumor microenvironment. Interest has grown in understanding how cytokines modulate the tumor microenvironment and which cytokines may serve as markers of the tumor process; however, a complete picture of the cytokine landscape in bladder cancer remains unclear. METHODS: Fresh urine specimens with sufficient volume were collected at random intervals. The urine concentrations of IL-8 (CXCL8), CCL18, and CXCL9 were determined using the standard commercially available enzyme immunoassay. The urine concentrations of IL-6 were determined using the high sensitivity enzyme immunoassay kit. Urinary cytokine concentrations were normalized with urinary creatinine concentrations. RESULTS: Significantly elevated concentrations of IL-6 and IL-8 were detected in the urine from patients with urothelial carcinoma on follow-up compared to patients with benign follow-up. The presence of both IL-6 and IL-8 in the urine samples from the high grade urothelial carcinoma (HGUC) cohort revealed a clear discrimination when compared to samples from patients with benign follow-up. The presence of the combination of both IL-6 and IL-8 had a sensitivity of 90.0% and a specificity of 81.25%. Similar data were obtained when receiver operating characteristic analysis was performed on both IL-6 and IL-8 concentrations in the urine from patients with HGUC vs. the hematuria cohort. CONCLUSIONS: The presence of IL-6 and IL-8 in urine specimens may have predictive value for urothelial carcinoma. However, a large longitudinal study is required to statistically eliminate confounding factors and support this theory.

Industrial Hog Operation Workers' Perspectives on Occupational Exposure to Zoonotic Pathogens: A Qualitative Pilot Study in North Carolina, USA.

Industrial hog operation (IHO) workers face a range of occupational hazards, including exposure to zoonotic pathogens such as livestock-associated antimicrobial-resistant Staphylococcus aureus and swine-origin influenza viruses with epidemic or pandemic potential. To better understand this population's occupational exposure to zoonotic pathogens, we conducted a community-driven qualitative research study in eastern North Carolina. We completed in-depth interviews with ten IHO workers and used thematic analysis to identify and analyze patterns of responses. Workers described direct and indirect occupational contact with hogs, with accompanying potential for dermal, ingestion, and inhalation exposures to zoonotic pathogens. Workers also described potential take-home pathways, wherein they could transfer livestock-associated pathogens and other contaminants from IHOs to their families and communities. Findings warrant future research, and suggest that more restrictive policies on antimicrobials, stronger health and safety regulations, and better policies and practices across all IHOs could afford greater protection against worker and take-home zoonotic pathogen exposures.

Clinical Assessment of SARS-CoV-2 Antibodies in Oral Fluids Following Infection and Vaccination.

BACKGROUND: SARS-CoV-2 variants continue to circulate globally, even within highly vaccinated populations. The first-generation SARS-CoV-2 vaccines elicit neutralizing immunoglobin G (IgG) antibodies that prevent severe COVID-19 but induce only weak antibody responses in mucosal tissues. There is increasing recognition that secretory immunoglobin A (SIgA) antibodies in the upper respiratory tract and oral cavity are critical in interrupting virus shedding, transmission, and progression of disease. To fully understand the immune-related factors that influence SARS-CoV-2 dynamics at the population level, it will be necessary to monitor virus-specific IgG and SIgA in systemic and mucosal compartments. CONTENT: Oral fluids and saliva, with appropriate standardized collection methods, constitute a readily accessible biospecimen type from which both systemic and mucosal antibodies can be measured. Serum-derived IgG and immunoglobin A (IgA) are found in gingival crevicular fluids and saliva as the result of transudation, while SIgA, which is produced in response to mucosal infection and vaccination, is actively transported across salivary gland epithelia and present in saliva and passive drool. In this mini-review, we summarize the need for the implementation of standards, highly qualified reagents, and best practices to ensure that clinical science is both rigorous and comparable across laboratories and institutions. We discuss the need for a better understanding of sample stability, collection methods, and other factors that affect measurement outcomes and interlaboratory variability. SUMMARY: The establishment of best practices and clinical laboratory standards for the assessment of SARS-CoV-2 serum and mucosal antibodies in oral fluids is integral to understanding immune-related factors that influence COVID-19 transmission and persistence within populations.

Community-driven research and capacity building to address environmental justice concerns with industrial air pollution in Curtis Bay, South Baltimore.

Introduction: Curtis Bay (CB) is an environmental justice (EJ) community in South Baltimore. With a high concentration of industrial polluters and compounding non-chemical stressors, CB has experienced socioeconomic, quality of life, and health burdens for over 100 years. Today, these polluters include the open-air CSX Coal Terminal, waste-to-energy incinerators, and heavy diesel traffic through residential areas. The Community of Curtis Bay Association, Free Your Voice, and South Baltimore Community Land Trust are local organizations enacting a vision for equitable, healthy, and community-led development without industrial encroachment. In response to community-identified EJ concerns and an explosion at the CSX Coal Terminal, CB community groups partnered with academic researchers to develop a community-driven hyperlocal air monitoring and capacity building approach. This paper describes this approach to characterizing hyperlocal air quality in CB, building bridges between community residents and regulatory agencies, and nurturing a cohesive and effective community-academic partnership toward EJ. Methods: Using hyperlocal air monitoring, we are collecting real-time air pollution (particulate matter, black carbon, and ground-level gas species) and meteorological data from 15 low-cost sensors in residential and industrial areas of CB. We also use trail cameras to record activities at the CSX Coal Terminal. We merge air pollution and industrial activity data to evaluate the following: overall air quality in CB, multi-air pollutant profiles of elevated events, spatiotemporal changes in air quality in the community, patterns of industrial activity, and potential correlations between air quality and observed industrial activity. Members of our partnership also lead a high school course educating students about the history and ongoing efforts of the EJ movement in their community. Students in this course learn how to employ qualitative and quantitative data collection and analysis methods to bring scientific support to community EJ concerns. Results and Discussion: Our hyperlocal air monitoring network and community-academic partnership are continuing to evolve and have already demonstrated the ability to respond to community-identified EJ issues with real-time data while developing future EJ leaders. Our reflections can assist other community and academic groups in developing strong and fruitful partnerships to address similar EJ issues.

Application of machine learning models to identify serological predictors of COVID-19 severity and outcomes.

Critically ill people with COVID-19 have greater antibody titers than those with mild to moderate illness, but their association with recovery or death from COVID-19 has not been characterized. In 178 COVID-19 patients, 73 non-hospitalized and 105 hospitalized patients, mucosal swabs and plasma samples were collected at hospital enrollment and up to 3 months post-enrollment (MPE) to measure virus RNA, cytokines/chemokines, binding antibodies, ACE2 binding inhibition, and Fc effector antibody responses against SARS-CoV-2. The association of demographic variables and >20 serological antibody measures with intubation or death due to COVID-19 was determined using machine learning algorithms. Predictive models revealed that IgG binding and ACE2 binding inhibition responses at 1 MPE were positively and C1q complement activity at enrollment was negatively associated with an increased probability of intubation or death from COVID-19 within 3 MPE. Serological antibody measures were more predictive than demographic variables of intubation or death among COVID-19 patients.

The SeroNet Clinical and Translational Serology Task Force (CTTF) SARS-CoV-2 mucosal immunity methodological considerations and best practices workshop.

SARS-CoV-2 persists in certain populations, even with vaccination and boosters. Emerging evidence suggests that reductions in virus transmission and infection will likely require involvement of the mucosal immune system, especially secretory antibodies in the upper respiratory tract. The Clinical and Translational Serology Task Force (CTTF) within The National Cancer Institute (NCI)'s Serological Sciences Network for COVID-19 (SeroNet) hosted a workshop to review the status of development and standardization of mucosal sample collection methods and assays, identify challenges, and develop action plans to bridge gaps. Speakers presented data underscoring a role for secretory IgA in protection, mucosal markers as correlates of protection, methods for tracking and assessing mucosal antibodies, and lessons learned from other infectious agents. Perspectives from regulators and industry were put forward to guide mucosal vaccine development. Methodological considerations for optimizing collection protocols and assays and harmonizing data were highlighted. Rigorous studies, standardized protocols, controls, standards, and assay validation were identified as necessary to gain momentum in expanding SARS-CoV-2 vaccines to the mucosa.

Evaluating SARS-CoV-2 Saliva and Dried Blood Spot Surveillance Strategies in a Congregate Population.

The optimal approach to COVID-19 surveillance in congregate populations remains unclear. Our study at the US Naval Academy in Annapolis, Maryland, USA, assessed the concordance of antibody prevalence in longitudinally collected dried blood spots and saliva in a setting of frequent PCR-based testing. Our findings highlight the utility of salivary-based surveillance.

Anthropometric measures and arsenic methylation among pregnant women in rural northern Bangladesh.

INTRODUCTION: Arsenic methylation converts inorganic arsenic (iAs) to monomethyl (MMA) and dimethyl (DMA) arsenic compounds. Body mass index (BMI) has been positively associated with arsenic methylation efficiency (higher DMA%) in adults, but evidence in pregnancy is inconsistent. We estimated associations between anthropometric measures and arsenic methylation among pregnant women in rural northern Bangladesh. METHODS: We enrolled pregnant women (n = 784) (median [IQR] gestational week: 14 [13, 15]) in Gaibandha District, Bangladesh from 2018 to 2019. Anthropometric measures were BMI, subscapular and triceps skinfold thicknesses, and mid-upper arm circumference (MUAC), fat area (MUAFA), and muscle area (MUAMA). Arsenic methylation measures were urinary iAs, MMA, and DMA divided by their sum and multiplied by 100 (iAs%, MMA%, and DMA%), primary methylation index (MMA/iAs; PMI), and secondary methylation index (DMA/MMA; SMI). In complete cases (n = 765 [97.6%]), we fitted linear, beta, and Dirichlet regression models to estimate cross-sectional differences in iAs%, MMA%, DMA%, PMI, and SMI per IQR-unit difference in each anthropometric measure, adjusting for drinking water arsenic, age, gestational age, education, living standards index, and plasma folate, vitamin B12, and homocysteine. RESULTS: Median (IQR) BMI, subscapular skinfold thickness, triceps skinfold thickness, MUAC, MUAFA, and MUAMA were 21.5 (19.4, 23.8) kg/m2, 17.9 (13.2, 24.2) mm, 14.2 (10.2, 18.7) mm, 25.9 (23.8, 28.0) cm, 15.3 (10.5, 20.3) cm2, and 29.9 (25.6, 34.2) cm2, respectively. Median (IQR) iAs%, MMA%, DMA%, PMI, and SMI were 12.0 (9.3, 15.2)%, 6.6 (5.3, 8.3)%, 81.0 (77.1, 84.6)%, 0.6 (0.4, 0.7), and 12.2 (9.3, 15.7), respectively. In both unadjusted and adjusted linear models, all anthropometric measures were negatively associated with iAs%, MMA%, and PMI and positively associated with DMA% and SMI. For example, fully adjusted mean differences (95% CI) in DMA% per IQR-unit difference in BMI, subscapular skinfolds thickness, triceps skinfold thickness, MUAC, MUAFA, and MUAMA were 1.72 (1.16, 2.28), 1.58 (0.95, 2.21), 1.74 (1.11, 2.37), 1.45 (0.85, 2.06), 1.70 (1.08, 2.31), and 0.70 (0.13, 1.27) pp, respectively. CONCLUSIONS: Anthropometric measures were positively associated with arsenic methylation efficiency among pregnant women in the early second trimester.

A Saliva-Based Serological and Behavioral Analysis of SARS-CoV-2 Antibody Prevalence in Howard County, Maryland.

The objective of the study was to estimate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence in the Howard County, Maryland, general population and demographic subpopulations attributable to natural infection or coronavirus disease 2019 (COVID-19) vaccination and to identify self-reported social behaviors that may affect the likelihood of recent or past SARS-CoV-2 infection. A cross-sectional, saliva-based serological study of 2,880 residents of Howard County, Maryland, was carried out from July through September 2021. Natural SARS-CoV-2 infection prevalence was estimated by inferring infections among individuals according to anti-nucleocapsid immunoglobin G levels and calculating averages weighted by sample proportions of various demographics. Antibody levels between BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) recipients were compared. Antibody decay rate was calculated by fitting exponential decay curves to cross-sectional indirect immunoassay data. Regression analysis was carried out to identify demographic factors, social behaviors, and attitudes that may be linked to an increased likelihood of natural infection. The estimated overall prevalence of natural infection in Howard County, Maryland, was 11.9% (95% confidence interval, 9.2% to 15.1%), compared with 7% reported COVID-19 cases. Antibody prevalence indicating natural infection was highest among Hispanic and non-Hispanic Black participants and lowest among non-Hispanic White and non-Hispanic Asian participants. Participants from census tracts with lower average household income also had higher natural infection rates. After accounting for multiple comparisons and correlations between participants, none of the behavior or attitude factors had significant effects on natural infection. At the same time, recipients of the mRNA-1273 vaccine had higher antibody levels than those of BNT162b2 vaccine recipients. Older study participants had overall lower antibody levels compared with younger study participants. The true prevalence of SARS-CoV-2 infection is higher than the number of reported COVID-19 cases in Howard County, Maryland. A disproportionate impact of infection-induced SARS-CoV-2 positivity was observed across different ethnic/racial subpopulations and incomes, and differences in antibody levels across different demographics were identified. Taken together, this information may inform public health policy to protect vulnerable populations. IMPORTANCE We employed a highly innovative noninvasive multiplex oral fluid SARS-CoV-2 IgG assay to ascertain our seroprevalence estimates. This laboratory-developed test has been applied in NCI's SeroNet consortium, possesses high sensitivity and specificity according to FDA Emergency Use Authorization guidelines, correlates strongly with SARS-CoV-2 neutralizing antibody responses, and is Clinical Laboratory Improvement Amendments-approved by the Johns Hopkins Hospital Department of Pathology. It represents a broadly scalable public health tool to improve understanding of recent and past SARS-CoV-2 exposure and infection without drawing any blood. To our knowledge, this is the first application of a high-performance salivary SARS-CoV-2 IgG assay to estimate population-level seroprevalence, including identifying COVID-19 disparities. We also are the first to report differences in SARS-CoV-2 IgG responses by COVID-19 vaccine manufacturers (BNT162b2 [Pfizer-BioNTech] and mRNA-1273 [Moderna]). Our findings demonstrate remarkable consistency with those of blood-based SARS-CoV-2 IgG assays in terms of differences in the magnitude of SARS-CoV-2 IgG responses between COVID-19 vaccines.

Severe Acute Respiratory Syndrome Coronavirus 2 Neutralizing Antibody Responses After Community Infections in Children and Adults.

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.

Longitudinal Analysis of Humoral and Cellular Immune Response Following SARS-CoV-2 Vaccination Supports Utilizing Point-Of-Care Tests to Enhance COVID-19 Booster Uptake.

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 Summary: SARS-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.

Modeling in higher dimensions to improve diagnostic testing accuracy: Theory and examples for multiplex saliva-based SARS-CoV-2 antibody assays.

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.

Methodological approaches to optimize multiplex oral fluid SARS-CoV-2 IgG assay performance and correlation with serologic and neutralizing antibody responses.

BACKGROUND: Oral 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. OBJECTIVES: To 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. METHODS: The 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. RESULTS: The 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 = 0.76, RBD: ρ = 0.83, S: ρ = 0.82; all p < 0.001). Correlations of plasma SARS-CoV-2 nAb assay area under the curve (AUC) with salivary MIA IgG (N: ρ = 0.68, RBD: ρ = 0.78, S: ρ = 0.79; all p < 0.001) and with plasma ELISA IgG (N: ρ = 0.76, RBD: ρ = 0.79, S: ρ = 0.76; p < 0.001) were similar. CONCLUSIONS: A 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.

The Pregnancy, Arsenic, and Immune Response (PAIR) Study in rural northern Bangladesh.

BACKGROUND: Arsenic exposure and micronutrient deficiencies may alter immune reactivity to influenza vaccination in pregnant women, transplacental transfer of maternal antibodies to the foetus, and maternal and infant acute morbidity. OBJECTIVES: The Pregnancy, Arsenic, and Immune Response (PAIR) Study was designed to assess whether arsenic exposure and micronutrient deficiencies alter maternal and newborn immunity and acute morbidity following maternal seasonal influenza vaccination during pregnancy. POPULATION: The PAIR Study recruited pregnant women across a large rural study area in Gaibandha District, northern Bangladesh, 2018-2019. DESIGN: Prospective, longitudinal pregnancy and birth cohort. METHODS: We conducted home visits to enrol pregnant women in the late first or early second trimester (11-17 weeks of gestational age). Women received a quadrivalent seasonal inactivated influenza vaccine at enrolment. Follow-up included up to 13 visits between enrolment and 3 months postpartum. Arsenic was measured in drinking water and maternal urine. Micronutrient deficiencies were assessed using plasma biomarkers. Vaccine-specific antibody titres were measured in maternal and infant serum. Weekly telephone surveillance ascertained acute morbidity symptoms in women and infants. PRELIMINARY RESULTS: We enrolled 784 pregnant women between October 2018 and March 2019. Of 784 women who enrolled, 736 (93.9%) delivered live births and 551 (70.3%) completed follow-up visits to 3 months postpartum. Arsenic was detected (≥0.02 µg/L) in 99.7% of water specimens collected from participants at enrolment. The medians (interquartile ranges) of water and urinary arsenic at enrolment were 5.1 (0.5, 25.1) µg/L and 33.1 (19.6, 56.5) µg/L, respectively. Water and urinary arsenic were strongly correlated (Spearman's ⍴ = 0.72) among women with water arsenic ≥ median but weakly correlated (⍴ = 0.17) among women with water arsenic < median. CONCLUSIONS: The PAIR Study is well positioned to examine the effects of low-moderate arsenic exposure and micronutrient deficiencies on immune outcomes in women and infants. REGISTRATION: NCT03930017.

Reconsideration of Antinucleocapsid IgG Antibody as a Marker of SARS-CoV-2 Infection Postvaccination for Mild COVID-19 Patients.

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.

SARS-CoV-2 Antibody Prevalence among Industrial Livestock Operation Workers and Nearby Community Residents, North Carolina, 2021 to 2022.

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 the 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). More metro (55.4%) compared to ILO (51.6%) and ILON participants (48.4%) completed the COVID-19 primary vaccination series; the median completion date was more than 4 months later for ILO compared to ILON and metro participants, although neither difference was statistically significant. Participants provided a saliva swab we analyzed for SARS-CoV-2 IgG using a multiplex immunoassay. The prevalence of infection-induced IgG (positive for nucleocapsid and receptor binding domain) was higher among ILO (63%) than ILON (42.9%) and metro (48.7%) participants (prevalence ratio [PR], 1.38; 95% confidence interval [CI], 1.06 to 1.80; reference category ILON and metro combined). The prevalence of infection-induced IgG was also higher among ILO participants than among an Atlanta health care worker cohort (PR, 2.45; 95% CI, 1.80 to 3.33) and a general population cohort in North Carolina (PRs, 6.37 to 10.67). The infection-induced IgG prevalence increased over the study period. Participants reporting not masking in public in the past 2 weeks had higher infection-induced IgG prevalence (78.6%) than participants reporting masking (49.3%) (PR, 1.59; 95% CI, 1.19 to 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. IMPORTANCE Few 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 related to 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.

Modeling in higher dimensions to improve diagnostic testing accuracy: theory and examples for multiplex saliva-based SARS-CoV-2 antibody assays.

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.

Enhancing global health security in Thailand: Strengths and challenges of initiating a One Health approach to avian influenza surveillance.

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.