Humoral immune response to SARS-CoV-2 in pregnant and nonpregnant women following infection.

BACKGROUND: Immune changes that occur during pregnancy may place pregnant women at an increased risk for severe disease following viral infections like SARS-CoV-2. Whether these immunologic changes modify the immune response to SARS-CoV-2 infection during pregnancy is not well understood. OBJECTIVE: This study aimed to compare the humoral immune response to SARS-CoV-2 infection in pregnant and nonpregnant women. The immune response following vaccination for SARS-CoV-2 was also explored. STUDY DESIGN: In this cohort study, 24 serum samples from 20 patients infected with SARS-CoV-2 during pregnancy were matched by number of days after a positive test with 46 samples from 40 nonpregnant women of reproductive age. Samples from 9 patients who were vaccinated during pregnancy were also examined. Immunoglobulin G and immunoglobulin M levels were measured. Trends in the log antibody levels over time and mean antibody levels were assessed using generalized estimating equations. RESULTS: The median number of days from first positive test to sampling was 6.5 in the pregnant group (range, 3-97) and 6.0 among nonpregnant participants (range, 2-97). No significant differences in demographic or sampling characteristics were noted between the groups. No differences in immunoglobulin G or immunoglobulin M levels over time or mean antibody levels were noted among pregnant and nonpregnant participants following SARS-CoV-2 infection for any of the SARS-CoV-2 antigen targets examined (spike, spike receptor-binding domain, spike N-terminal domain, and nucleocapsid). Participants who were vaccinated during pregnancy had higher immunoglobulin G levels than pregnant patients who tested positive for all SARS-CoV-2 targets except nucleocapsid antibodies (all P<.001) and had lower immunoglobulin M spike (P<.05) and receptor-binding domain (P<.01) antibody levels. CONCLUSION: This study suggests that the humoral response following SARS-CoV-2 infection does not seem to differ between pregnant women and their nonpregnant counterparts. These findings should reassure patients and healthcare providers that pregnant patients seem to mount a nondifferential immune response to SARS-CoV-2.

Humoral immune response to SARS-CoV-2 in pregnant and non-pregnant women following infection

Background Immune changes that occur during pregnancy may place pregnant women at an increased risk for severe disease following viral infections like SARS-CoV-2. Whether these immunological changes modify immune response to SARS-CoV-2 infection during pregnancy is not well understood. Objective The objective of the present study is to compare humoral immune response to SARS-CoV-2 infection in pregnant and non-pregnant women. Immune response following vaccination for SARS-CoV-2 was also explored. Study Design In the present cohort study, 24 serum samples from 20 patients infected with SARS-CoV-2 during pregnancy were matched on number of days post positive test to 46 samples from 40 non-pregnant women of reproductive age. Samples from nine patients vaccinated during pregnancy were also examined. Immunoglobulin G (IgG) and immunoglobulin M (IgM) antibody levels were measured. Trends in log antibody levels over time and mean antibody levels were assessed using generalized estimating equations. Results Median number of days from first positive test to sampling was 6.5 in the pregnant group (range 3-97) and 6.0 among non-pregnant participants (range 2-97). No significant differences in demographic or sampling characteristics were noted between groups. No differences in IgG or IgM levels over time or mean antibody levels were noted in pregnant and non-pregnant participants following SARS-CoV-2 infection for any of the SARS-CoV-2 antigens targets examined [Spike, Spike Receptor Binding Domain (RBD), Spike N-Terminal Domain (NTD), and Nucleocapsid]. Participants vaccinated during pregnancy had higher IgG levels than pregnant positive patients for all SARS-CoV-2 targets except Nucleocapsid (all p < 0.001), as well as lower IgM Spike (p < 0.05) and RBD (p < 0.01) antibody levels. Conclusions The present study suggests that humoral response following SARS-CoV-2 infection does not appear to differ in pregnant women compared to their non-pregnant counterparts. These findings should reassure patients and healthcare providers that pregnant patients appear to mount a non-differential immune response to SARS-CoV-2.

Perceived COVID-19 risk and testing experiences in the San Ysidro U.S./Mexico border region.

Racial and ethnic disparities in COVID-19 incidence are pronounced in underserved U.S./Mexico border communities. Working and living environments in these communities can lead to increased risk of COVID-19 infection and transmission, and this increased risk is exacerbated by lack of access to testing. As part of designing a community and culturally tailored COVID-19 testing program, we surveyed community members in the San Ysidro border region. The purpose of our study was to characterize knowledge, attitudes, and beliefs of prenatal patients, prenatal caregivers, and pediatric caregivers at a Federally Qualified Health Center (FHQC) in the San Ysidro region regarding perceived risk of COVID-19 infection and access to testing. A cross-sectional survey was used to collect information on experiences accessing COVID-19 testing and perceived risk of COVID-19 infection within San Ysidro between December 29, 2020 and April 2, 2021. A total of 179 surveys were analyzed. Most participants identified as female (85%) and as Mexican/Mexican American (75%). Over half (56%) were between the age of 25 and 34 years old. Perceived Risk: 37% reported moderate to high risk of COVID-19 infection, whereas 50% reported their risk low to none. Testing Experience: Approximately 68% reported previously being tested for COVID-19. Among those tested, 97% reported having very easy or easy access to testing. Reasons for not testing included limited appointment availability, cost, not feeling sick, and concern about risk of infection while at a testing facility. This study is an important first step to understand the COVID-19 risk perceptions and testing access among patients and community members living near the U.S./Mexico border in San Ysidro, California.

COVID-19 testing strategies that fail to incorporate culturally competent methods to reach traditionally underserved communities can lead to persistent transmission and increased infection rates. During the early stages of the COVID-19 pandemic, we surveyed 179 people living in a community with high burden of COVID-19 infection about their perception of infection risk and their experiences accessing testing. Capturing and understanding these community perceptions on COVID-19 risk are vital when developing a testing program that is accessible and appropriate for the target population. In our study, we found half of survey respondents thought their risk of COVID-19 infection as low to none and over half of respondents stated they had already been tested for COVID-19. These findings provide insight to the beliefs of individuals who live and seek health care in communities with high rates of COVID-19 infection and will help guide the design and implementation of culturally tailored testing strategies.

Using ethnographic approaches to document, evaluate, and facilitate virtual community-engaged implementation research.

BACKGROUND: Community Advisory Boards (CABs) have been frequently used to engage diverse partners to inform research projects. Yet, evaluating the quality of engagement has not been routine. We describe a multi-method ethnographic approach documenting and assessing partner engagement in two "virtual" CABs, for which we conducted all meetings remotely. METHODS: Two research projects for increasing equitable COVID-19 testing, vaccination, and clinical trial participation for underserved communities involved remote CAB meetings. Thirty-three partners representing 17 community groups participated in 15 sessions across the two CABs facilitated by a social change organization. We developed ethnographic documentation forms to assess multiple aspects of CAB member engagement (e.g., time spent speaking, modality used, types of interactions). Documenters were trained to observe CAB sub-groups via virtual sessions. Debriefing with the documentation team after CAB meetings supported quality assurance and process refinement. CAB members completed a brief validated survey after each meeting to assess the quality and frequency of engagement. Content and rapid thematic analysis were used to analyze documentation data. Quantitative data were summarized as frequencies and means. Qualitative and quantitative findings were triangulated. RESULTS: A total of 4,540 interactions were identified across 15 meetings. The most frequent interaction was providing information (44%), followed by responding (37-38%). The quality and frequency of stakeholder engagement were rated favorably (average 4.7 of 5). Most CAB members (96%) reported good/excellent engagement. Specific comments included appreciation for the diversity of perspectives represented by the CAB members and suggestions for improved live interpretation. Debriefing sessions led to several methodological refinements for the documentation process and forms. CONCLUSION: We highlight key strategies for documenting and assessing community engagement. Our methods allowed for rich ethnographic data collection that refined our work with community partners. We recommend ongoing trainings, including debriefing sessions and routinely reviewed assessment of data to strengthen meaningful community engagement.

Safer at school early alert: an observational study of wastewater and surface monitoring to detect COVID-19 in elementary schools.

Background: Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown. Methods: The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 to March 2021. Findings: In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88%-98%); 67% were associated with a positive wastewater sample (95% CI: 57%-77%), and 40% were associated with a positive surface sample (95% CI: 29%-52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples. Interpretation: Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy. Funding: County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.

Engaging Underserved Communities in COVID-19 Health Equity Implementation Research: An Analysis of Community Engagement Resource Needs and Costs.

Background: Meaningful community engagement is instrumental to effective implementation and sustainment of equitable public health interventions. Significant resources are necessary to ensure that community engagement takes place in culturally sensitive, trusted ways that optimize positive public health outcomes. However, the types and costs of resources best suited to enable meaningful community engagement in implementation research are not well-documented. This study's objectives are (1) to describe a pragmatic method for systematically tracking and documenting resources utilized for community engagement activities, (2) report resources across phases of implementation research, and (3) provide recommendations for planning and budgeting for community engagement in health equity implementation research. Methods: Community engagement partners completed a tracking log of their person-hours for community engagement activities across three phases of community engagement (startup, early, maintenance) in two implementation research projects to promote equity in COVID-19 testing and vaccination for underserved communities. Both projects completed a six-session Theory of Change (i.e., a facilitated group discussion about current and desired conditions that culminated with a set of priorities for strategic change making) over 4 months with respective Community Advisory Boards (CAB) that included community organizers, promotores, federally qualified health center providers and administrators, and public health researchers. The reported person-hours that facilitated community member engagement were documented and summarized within and across project phases. Results: For both projects, the startup phase required the highest number of person-hours (M = 60), followed by the maintenance (M = 53) and early phase (M = 47). Within the startup phase, a total of 5 community engagement activities occurred with identifying and inviting CAB members incurring the greatest number of person-hours (M = 19). Within the early phase, a total of 11 community engagement activities occurred with coordinating and leading live interpretation (Spanish) during CAB sessions incurring the greatest number of person-hours (M = 10). The maintenance phase included 11 community engagement activities with time dedicated to written translation of CAB materials into Spanish incurring the greatest number of person-hours (M = 10). Conclusions: Study findings indicate that the most significant investment of resources is required in the startup period. Needed resources decreased, albeit with a greater diversity of activities, in later phases of community engagement with Spanish language translation requiring most in the later stage of the study. This study contributes to the community engagement and implementation science literature by providing a pragmatic tracking and measurement approach and recommendations for planning for and assessing costs to facilitate meaningful community engagement in public health implementation research.

Sentinel Cards Provide Practical SARS-CoV-2 Monitoring in School Settings.

A promising approach to help students safely return to in person learning is through the application of sentinel cards for accurate high resolution environmental monitoring of SARS-CoV-2 traces indoors. Because SARS-CoV-2 RNA can persist for up to a week on several indoor surface materials, there is a need for increased temporal resolution to determine whether consecutive surface positives arise from new infection events or continue to report past events. Cleaning sentinel cards after sampling would provide the needed resolution but might interfere with assay performance. We tested the effect of three cleaning solutions (BZK wipes, Wet Wipes, RNase Away) at three different viral loads: "high" (4 × 104 GE/mL), "medium" (1 × 104 GE/mL), and "low" (2.5 × 103 GE/mL). RNase Away, chosen as a positive control, was the most effective cleaning solution on all three viral loads. Wet Wipes were found to be more effective than BZK wipes in the medium viral load condition. The low viral load condition was easily reset with all three cleaning solutions. These findings will enable temporal SARS-CoV-2 monitoring in indoor environments where transmission risk of the virus is high and the need to avoid individual-level sampling for privacy or compliance reasons exists. IMPORTANCE Because SARS-CoV-2, the virus that causes COVID-19, persists on surfaces, testing swabs taken from surfaces is useful as a monitoring tool. This approach is especially valuable in school settings, where there are cost and privacy concerns that are eliminated by taking a single sample from a classroom. However, the virus persists for days to weeks on surface samples, so it is impossible to tell whether positive detection events on consecutive days are a persistent signal or new infectious cases and therefore whether the positive individuals have been successfully removed from the classroom. We compare several methods for cleaning "sentinel cards" to show that this approach can be used to identify new SARS-CoV-2 signals day to day. The results are important for determining how to monitor classrooms and other indoor environments for SARS-CoV-2 virus.

Implementation of Practical Surface SARS-CoV-2 Surveillance in School Settings.

Surface sampling for SARS-CoV-2 RNA detection has shown considerable promise to detect exposure of built environments to infected individuals shedding virus who would not otherwise be detected. Here, we compare two popular sampling media (VTM and SDS) and two popular workflows (Thermo and PerkinElmer) for implementation of a surface sampling program suitable for environmental monitoring in public schools. We find that the SDS/Thermo pipeline shows superior sensitivity and specificity, but that the VTM/PerkinElmer pipeline is still sufficient to support surface surveillance in any indoor setting with stable cohorts of occupants (e.g., schools, prisons, group homes, etc.) and may be used to leverage existing investments in infrastructure. IMPORTANCE The ongoing COVID-19 pandemic has claimed the lives of over 5 million people worldwide. Due to high density occupancy of indoor spaces for prolonged periods of time, schools are often of concern for transmission, leading to widespread school closings to combat pandemic spread when cases rise. Since pediatric clinical testing is expensive and difficult from a consent perspective, we have deployed surface sampling in SASEA (Safer at School Early Alert), which allows for detection of SARS-CoV-2 from surfaces within a classroom. In this previous work, we developed a high-throughput method which requires robotic automation and specific reagents that are often not available for public health laboratories such as the San Diego County Public Health Laboratory (SDPHL). Therefore, we benchmarked our method (Thermo pipeline) against SDPHL's (PerkinElmer) more widely used method for the detection and prediction of SARS-CoV-2 exposure. While our method shows superior sensitivity (false-negative rate of 9% versus 27% for SDPHL), the SDPHL pipeline is sufficient to support surface surveillance in indoor settings. These findings are important since they show that existing investments in infrastructure can be leveraged to slow the spread of SARS-CoV-2 not in just the classroom but also in prisons, nursing homes, and other high-risk, indoor settings.

SARS-CoV-2 Distribution in Residential Housing Suggests Contact Deposition and Correlates with Rothia sp.

Monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces is emerging as an important tool for identifying past exposure to individuals shedding viral RNA. Our past work demonstrated that SARS-CoV-2 reverse transcription-quantitative PCR (RT-qPCR) signals from surfaces can identify when infected individuals have touched surfaces and when they have been present in hospital rooms or schools. However, the sensitivity and specificity of surface sampling as a method for detecting the presence of a SARS-CoV-2 positive individual, as well as guidance about where to sample, has not been established. To address these questions and to test whether our past observations linking SARS-CoV-2 abundance to Rothia sp. in hospitals also hold in a residential setting, we performed a detailed spatial sampling of three isolation housing units, assessing each sample for SARS-CoV-2 abundance by RT-qPCR, linking the results to 16S rRNA gene amplicon sequences (to assess the bacterial community at each location), and to the Cq value of the contemporaneous clinical test. Our results showed that the highest SARS-CoV-2 load in this setting is on touched surfaces, such as light switches and faucets, but a detectable signal was present in many untouched surfaces (e.g., floors) that may be more relevant in settings, such as schools where mask-wearing is enforced. As in past studies, the bacterial community predicts which samples are positive for SARS-CoV-2, with Rothia sp. showing a positive association. IMPORTANCE Surface sampling for detecting SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is increasingly being used to locate infected individuals. We tested which indoor surfaces had high versus low viral loads by collecting 381 samples from three residential units where infected individuals resided, and interpreted the results in terms of whether SARS-CoV-2 was likely transmitted directly (e.g., touching a light switch) or indirectly (e.g., by droplets or aerosols settling). We found the highest loads where the subject touched the surface directly, although enough virus was detected on indirectly contacted surfaces to make such locations useful for sampling (e.g., in schools, where students did not touch the light switches and also wore masks such that they had no opportunity to touch their face and then the object). We also documented links between the bacteria present in a sample and the SARS-CoV-2 virus, consistent with earlier studies.

The ViReflow pipeline enables user friendly large scale viral consensus genome reconstruction.

Throughout the COVID-19 pandemic, massive sequencing and data sharing efforts enabled the real-time surveillance of novel SARS-CoV-2 strains throughout the world, the results of which provided public health officials with actionable information to prevent the spread of the virus. However, with great sequencing comes great computation, and while cloud computing platforms bring high-performance computing directly into the hands of all who seek it, optimal design and configuration of a cloud compute cluster requires significant system administration expertise. We developed ViReflow, a user-friendly viral consensus sequence reconstruction pipeline enabling rapid analysis of viral sequence datasets leveraging Amazon Web Services (AWS) cloud compute resources and the Reflow system. ViReflow was developed specifically in response to the COVID-19 pandemic, but it is general to any viral pathogen. Importantly, when utilized with sufficient compute resources, ViReflow can trim, map, call variants, and call consensus sequences from amplicon sequence data from 1000 SARS-CoV-2 samples at 1000X depth in < 10 min, with no user intervention. ViReflow's simplicity, flexibility, and scalability make it an ideal tool for viral molecular epidemiological efforts.

Co-creating a Theory of Change to advance COVID-19 testing and vaccine uptake in underserved communities.

OBJECTIVES: To describe the use of a Theory of Change to meaningfully engage community members from or support underserved communities in two National Institutes of Health-funded implementation science projects aimed at promoting equitable access to COVID-19 testing and vaccination for underserved communities. STUDY SETTING: Both projects focused on Latino, Black, and immigrant and refugee communities in South/Central San Diego and/or individuals accessing care at a federally qualified health center near the US/Mexico border during December 2020-April 2021. STUDY DESIGN: By using a participatory action research design, Community Advisory Boards (CABs) were established for each project with 11 and 22 members. CAB members included community organizers, promotores de salud (community health workers), clinic providers and administrators, and public health researchers. The CABs were guided through a seven-session Theory of Change process, focused on identifying necessary conditions that must exist to eliminate COVID-19 disparities along with specified actions to create those conditions and a blueprint for assessing the impact of those actions. DATA COLLECTION: Each session lasted 2 h hosted virtually and was augmented by interactive web-based activities. There was a live interpreter who facilitated the participation of Spanish-speaking CAB members. A Theory of Change for each project was completed in approximately 4 months. PRINCIPAL FINDINGS: Nine necessary conditions were identified related to (1) accessible and available services; (2) culturally and linguistically competent programming; (3) investment in trusted community and faith leaders; (4) social safety nets to provide ancillary services. Corresponding actions to create these conditions and measures to indicate success in creating these conditions were operationalized by the CAB. CONCLUSIONS: While resource-intensive, a CAB-led Theory of Change process yielded a rich opportunity to engage diverse groups that typically are not invited to inform these processes.

Analysis of SARS-CoV-2 RNA Persistence across Indoor Surface Materials Reveals Best Practices for Environmental Monitoring Programs.

Environmental monitoring in public spaces can be used to identify surfaces contaminated by persons with coronavirus disease 2019 (COVID-19) and inform appropriate infection mitigation responses. Research groups have reported detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces days or weeks after the virus has been deposited, making it difficult to estimate when an infected individual may have shed virus onto a SARS-CoV-2-positive surface, which in turn complicates the process of establishing effective quarantine measures. In this study, we determined that reverse transcription-quantitative PCR (RT-qPCR) detection of viral RNA from heat-inactivated particles experiences minimal decay over 7 days of monitoring on eight out of nine surfaces tested. The properties of the studied surfaces result in RT-qPCR signatures that can be segregated into two material categories, rough and smooth, where smooth surfaces have a lower limit of detection. RT-qPCR signal intensity (average quantification cycle [Cq]) can be correlated with surface viral load using only one linear regression model per material category. The same experiment was performed with untreated viral particles on one surface from each category, with essentially identical results. The stability of RT-qPCR viral signal demonstrates the need to clean monitored surfaces after sampling to establish temporal resolution. Additionally, these findings can be used to minimize the number of materials and time points tested and allow for the use of heat-inactivated viral particles when optimizing environmental monitoring methods. IMPORTANCE Environmental monitoring is an important tool for public health surveillance, particularly in settings with low rates of diagnostic testing. Time between sampling public environments, such as hospitals or schools, and notifying stakeholders of the results should be minimal, allowing decisions to be made toward containing outbreaks of coronavirus disease 2019 (COVID-19). The Safer At School Early Alert program (SASEA) (https://saseasystem.org/), a large-scale environmental monitoring effort in elementary school and child care settings, has processed >13,000 surface samples for SARS-CoV-2, detecting viral signals from 574 samples. However, consecutive detection events necessitated the present study to establish appropriate response practices around persistent viral signals on classroom surfaces. Other research groups and clinical labs developing environmental monitoring methods may need to establish their own correlation between RT-qPCR results and viral load, but this work provides evidence justifying simplified experimental designs, like reduced testing materials and the use of heat-inactivated viral particles.

Dataset on optimization and development of a point-of-care glucometer-based SARS-CoV-2 detection assay using aptamers.

We present supplementary data for the published article, "Hitting the diagnostic sweet spot: Point-of-care SARS-CoV-2 salivary antigen testing with an off-the-shelf glucometer" [1]. The assay described is designed to be performed at home or in a clinic without expensive instrumentation or professional training. SARS-CoV-2 is detected by an aptamer-based assay that targets the Nucleocapsid (N) or Spike (S) antigens. Binding of the N or S protein to their respective aptamer results in the competitive release of a complementary antisense-invertase enzyme complex. The released enzyme then catalyzes the conversion of sucrose to glucose that is measured by an off-the-shelf glucometer. The data presented here describe the optimization of the assay parameters and their contribution to developing this aptamer-based assay to detect SARS-CoV-2. The assay performance was checked in a standard buffer, contrived samples, and patient samples validated with well-established scientific methods. The resulting dataset can be used to further develop glucometer-based assays for diagnosing other communicable and non-communicable diseases.

Emergence of an early SARS-CoV-2 epidemic in the United States.

The emergence of the COVID-19 epidemic in the United States (U.S.) went largely undetected due to inadequate testing. New Orleans experienced one of the earliest and fastest accelerating outbreaks, coinciding with Mardi Gras. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large-scale events accelerate transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana had limited diversity compared to other U.S. states and that one introduction of SARS-CoV-2 led to almost all of the early transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras, and the festival dramatically accelerated transmission. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate epidemics.

Emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States.

The highly transmissible B.1.1.7 variant of SARS-CoV-2, first identified in the United Kingdom, has gained a foothold across the world. Using S gene target failure (SGTF) and SARS-CoV-2 genomic sequencing, we investigated the prevalence and dynamics of this variant in the United States (US), tracking it back to its early emergence. We found that, while the fraction of B.1.1.7 varied by state, the variant increased at a logistic rate with a roughly weekly doubling rate and an increased transmission of 40%-50%. We revealed several independent introductions of B.1.1.7 into the US as early as late November 2020, with community transmission spreading it to most states within months. We show that the US is on a similar trajectory as other countries where B.1.1.7 became dominant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.

Hitting the diagnostic sweet spot: Point-of-care SARS-CoV-2 salivary antigen testing with an off-the-shelf glucometer.

Significant barriers to the diagnosis of latent and acute SARS-CoV-2 infection continue to hamper population-based screening efforts required to contain the COVID-19 pandemic in the absence of widely available antiviral therapeutics or vaccines. We report an aptamer-based SARS-CoV-2 salivary antigen assay employing only low-cost reagents ($3.20/test) and an off-the-shelf glucometer. The test was engineered around a glucometer as it is quantitative, easy to use, and the most prevalent piece of diagnostic equipment globally, making the test highly scalable with an infrastructure that is already in place. Furthermore, many glucometers connect to smartphones, providing an opportunity to integrate with contact tracing apps, medical providers, and electronic health records. In clinical testing, the developed assay detected SARS-CoV-2 infection in patient saliva across a range of viral loads - as benchmarked by RT-qPCR - within 1 h, with 100% sensitivity (positive percent agreement) and distinguished infected specimens from off-target antigens in uninfected controls with 100% specificity (negative percent agreement). We propose that this approach provides an inexpensive, rapid, and accurate diagnostic for distributed screening of SARS-CoV-2 infection at scale.