Development of an enteric pathogen multiplex immunoassay to measure antibody responses in blood and saliva for integrated serology applications.

Background: Enteric infections are a leading cause of global morbidity and mortality, with the highest burden of disease in young children in low- and middle-income countries. Comprehensive profiling of enteric infections, which requires intensive sampling and molecular and culture-based detection methods, may miss recent and historical infections. High-throughput antibody-based testing of blood or non-invasive specimens like saliva can fill this gap, especially in vulnerable populations.

Culturally targeted messaging and racial equity in SARS-CoV-2 antibody testing by multiplex salivary measurement: Protocol overview of a SeroNet investigation.

Better understanding racial disparities observed during the COVID-19 pandemic can be aided by SARS-CoV-2 serology testing. However, racial minorities may be underrepresented in serosurveillance efforts not only due to lack of testing accessibility, but also due to hesitancy towards participating in antibody testing programs stemming from medical mistrust. We designed a randomized control trial to evaluate how non-invasive salivary antibody testing and culturally targeted communication might be used to promote racial equity in uptake of SARS-CoV-2 serology testing during the COVID-19 pandemic.

Swine production intensity and swine-specific fecal contamination of household surfaces at residences of industrial livestock operation workers and community residents, North Carolina, USA.

In North Carolina (NC), industrial livestock operations (ILOs) that produce swine concentrate fecal waste in lagoons and sprayfields, which are disproportionately located in low-income communities of color. Although swine-specific fecal contamination of surface waters proximal to swine ILOs has been documented, less is known about contamination of homes proximal to swine ILOs. Up to 6 outdoor and 6 indoor surface settled dust samples were collected from households: 1) with >= 1 ILO worker (ILO-W); 2) neighboring ILOs without occupational exposure to livestock (ILO-N); and 3) in metropolitan areas of NC (Metro).

Inter-laboratory harmonization of microsphere immunoassays for SARS-CoV-2 antibody detection in contrived dried blood spots and oral fluids.

Unlabelled: Dried blood spots (DBS) and oral fluids (OF) are easily attainable biospecimen types that enabled population-scale antibody monitoring for SARS-CoV-2 exposure and vaccination. However, the degree to which the two different biospecimen types can be used interchangeably remains unclear. To address this question, we generated contrived DBS (cDBS) and contrived OF (cOF) from serum panels of SARS-CoV-2-infected, vaccinated, and uninfected individuals.

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

Background: Critically ill hospitalized patients 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.

Methods: In a cohort study of 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 more than 20 serological antibody measures with intubation or death due to COVID-19 was determined using machine learning algorithms.

Inter-laboratory harmonization of microsphere immunoassays for SARS-CoV-2 antibody detection in dried blood spots and oral fluids.

Dried blood spots (DBS) and oral fluids (OF) are easily attainable biospecimen types that have enabled population scale antibody monitoring for SARS-CoV-2 exposure and vaccination. However, the degree to which the two different biospecimen types can be used interchangeably remains unclear. To begin to address this question, we generated contrived DBS (cDBS) and OF (cOF) from serum panels from SARS-CoV-2 infected, vaccinated, and uninfected individuals.

Early, Robust Mucosal Secretory Immunoglobulin A but not Immunoglobulin G Response to Severe Acute Respiratory Syndrome Coronavirus 2 Spike in Oral Fluid Is Associated With Faster Viral Clearance and Coronavirus Disease 2019 Symptom Resolution.

Background: Efforts are underway to support the development of novel mucosal coronavirus disease 2019 (COVID-19) vaccines. However, there is limited consensus about the complementary role of mucosal immunity in disease progression and how to evaluate immunogenicity of mucosal vaccines. This study investigated the role of oral mucosal antibody responses in viral clearance and COVID-19 symptom duration.

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

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. We used a multiplex salivary SARS-CoV-2 IgG assay to determine infection-induced antibody prevalence among 236 adult (≥18 yr) North Carolina residents between February 2021 and August 2022.

COVID-19 point-of-care tests can identify low-antibody individuals: In-depth immunoanalysis of boosting benefits in a healthy cohort.

The recommended COVID-19 booster vaccine uptake is low. At-home lateral flow assay (LFA) antigen tests are widely accepted for detecting infection during the pandemic. Here, we present the feasibility and potential benefits of using LFA-based antibody tests as a means for individuals to detect inadequate immunity and make informed decisions about COVID-19 booster immunization.

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.

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.

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.

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.

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.

Unlabelled: 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.

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.

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.

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.

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).

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.

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.

Optimal decision theory for diagnostic testing: Minimizing indeterminate classes with applications to saliva-based SARS-CoV-2 antibody assays.

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.