Metagenomic next-generation sequencing to characterize potential etiologies of non-malarial fever in a cohort living in a high malaria burden area of Uganda.

Causes of non-malarial fevers in sub-Saharan Africa remain understudied. We hypothesized that metagenomic next-generation sequencing (mNGS), which allows for broad genomic-level detection of infectious agents in a biological sample, can systematically identify potential causes of non-malarial fevers. The 212 participants in this study were of all ages and were enrolled in a longitudinal malaria cohort in eastern Uganda. Between December 2020 and August 2021, respiratory swabs and plasma samples were collected at 313 study visits where participants presented with fever and were negative for malaria by microscopy. Samples were analyzed using CZ ID, a web-based platform for microbial detection in mNGS data. Overall, viral pathogens were detected at 123 of 313 visits (39%). SARS-CoV-2 was detected at 11 visits, from which full viral genomes were recovered from nine. Other prevalent viruses included Influenza A (14 visits), RSV (12 visits), and three of the four strains of seasonal coronaviruses (6 visits). Notably, 11 influenza cases occurred between May and July 2021, coinciding with when the Delta variant of SARS-CoV-2 was circulating in this population. The primary limitation of this study is that we were unable to estimate the contribution of bacterial microbes to non-malarial fevers, due to the difficulty of distinguishing bacterial microbes that were pathogenic from those that were commensal or contaminants. These results revealed the co-circulation of multiple viral pathogens likely associated with fever in the cohort during this time period. This study illustrates the utility of mNGS in elucidating the multiple potential causes of non-malarial febrile illness. A better understanding of the pathogen landscape in different settings and age groups could aid in informing diagnostics, case management, and public health surveillance systems.

SARS-CoV-2 Serology Across Scales: A Framework for Unbiased Estimation of Cumulative Incidence Incorporating Antibody Kinetics and Epidemic Recency.

Serosurveys are a key resource for measuring SARS-CoV-2 population exposure. A growing body of evidence suggests that asymptomatic and mild infections (together making up over 95% of all infections) are associated with lower antibody titers than severe infections. Antibody levels also peak a few weeks after infection and decay gradually. We developed a statistical approach to produce estimates of cumulative incidence from raw seroprevalence survey results that account for these sources of spectrum bias. We incorporate data on antibody responses on multiple assays from a post-infection longitudinal cohort, along with epidemic time series to account for the timing of a serosurvey relative to how recently individuals may have been infected. We applied this method to produce estimates of cumulative incidence from five large-scale SARS-CoV-2 serosurveys across different settings and study designs. We identify substantial differences between raw seroprevalence and cumulative incidence of over two-fold in the results of some surveys, and provide a tool for practitioners to generate cumulative incidence estimates with pre-set or custom parameter values. While unprecedented efforts have been launched to generate SARS-CoV-2 seroprevalence estimates over this past year, interpretation of results from these studies requires properly accounting for both population-level epidemiologic context and individual-level immune dynamics.

TNF-α+ CD4+ T cells dominate the SARS-CoV-2 specific T cell response in COVID-19 outpatients and are associated with durable antibodies.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific CD4+ T cells are likely important in immunity against coronavirus 2019 (COVID-19), but our understanding of CD4+ longitudinal dynamics following infection and of specific features that correlate with the maintenance of neutralizing antibodies remains limited. Here, we characterize SARS-CoV-2-specific CD4+ T cells in a longitudinal cohort of 109 COVID-19 outpatients enrolled during acute infection. The quality of the SARS-CoV-2-specific CD4+ response shifts from cells producing interferon gamma (IFNγ) to tumor necrosis factor alpha (TNF-α) from 5 days to 4 months post-enrollment, with IFNγ-IL-21-TNF-α+ CD4+ T cells the predominant population detected at later time points. Greater percentages of IFNγ-IL-21-TNF-α+ CD4+ T cells on day 28 correlate with SARS-CoV-2-neutralizing antibodies measured 7 months post-infection (⍴ = 0.4, p = 0.01). mRNA vaccination following SARS-CoV-2 infection boosts both IFNγ- and TNF-α-producing, spike-protein-specific CD4+ T cells. These data suggest that SARS-CoV-2-specific, TNF-α-producing CD4+ T cells may play an important role in antibody maintenance following COVID-19.

Seroprevalence of Antibodies to SARS-CoV-2 in Rural Households in Eastern Uganda, 2020-2022.

Importance: Estimating the true burden of SARS-CoV-2 infection has been difficult in sub-Saharan Africa owing to asymptomatic infections and inadequate testing capacity. Antibody responses from serologic surveys can provide an estimate of SARS-CoV-2 exposure at the population level. Objective: To estimate SARS-CoV-2 seroprevalence, attack rates, and reinfection in eastern Uganda using serologic surveillance from 2020 to early 2022. Design, Setting, and Participants: This cohort study was conducted in the Tororo and Busia districts of eastern Uganda. Plasma samples from participants in the Program for Resistance, Immunology, Surveillance, and Modeling of Malaria in Uganda Border Cohort were obtained at 4 sampling intervals: October to November 2020, March to April 2021, August to September 2021, and February to March 2022. Each participant contributed up to 4 time points for SARS-CoV-2 serology, with almost half of all participants contributing at all 4 time points, and almost 90% contributing at 3 or 4 time points. Information on SARS-CoV-2 vaccination status was collected from participants, with the earliest reported vaccinations in the cohort occurring in May 2021. Main Outcomes and Measures: The main outcomes of this study were antibody responses to the SARS-CoV-2 spike protein as measured with a bead-based serologic assay. Individual-level outcomes were aggregated to population-level SARS-CoV-2 seroprevalence, attack rates, and boosting rates. Estimates were weighted by the local age distribution according to census data. Results: A total of 1483 samples from 441 participants living in 76 households were tested. Of the 441 participants, 245 (55.6%) were female, and their mean (SD) age was 16.04 (16.04) years. By the end of the Delta wave and before widespread vaccination, adjusted SARS-CoV-2 seroprevalence was 67.7% (95% credible interval [CrI], 62.5%-72.6%) in the study population. During the subsequent Omicron wave, 84.8% (95% CrI, 67.9%-93.7%) of unvaccinated, previously seronegative individuals were infected for the first time, and 50.8% (95% CrI, 40.6%-59.7%) of unvaccinated, already seropositive individuals were likely reinfected, leading to an overall seropositivity of 96.0% (95% CrI, 93.4%-97.9%) in this population. These results suggest a lower probability of reinfection in individuals with higher preexisting antibody levels. There was evidence of household clustering of SARS-CoV-2 seroconversion. No significant associations were found between SARS-CoV-2 seroconversion and gender, household size, or recent Plasmodium falciparum malaria exposure. Conclusions and Relevance: In this cohort study in a rural population in eastern Uganda, there was evidence of very high SARS-CoV-2 infection rates throughout the pandemic inconsistent with national level case data and high reinfection rates during the Omicron wave.

Infectiousness of SARS-CoV-2 breakthrough infections and reinfections during the Omicron wave.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) breakthrough infections in vaccinated individuals and reinfections in previously infected individuals have become increasingly common. Such infections highlight a broader need to understand the contribution of vaccination, including booster doses, and natural immunity to the infectiousness of individuals with SARS-CoV-2 infections, especially in high-risk populations with intense transmission, such as in prisons. Here we show that both vaccine-derived and naturally acquired immunity independently reduce the infectiousness of persons with Omicron variant SARS-CoV-2 infections in a prison setting. Analyzing SARS-CoV-2 surveillance data from December 2021 to May 2022 across 35 California state prisons with a predominately male population, we estimate that unvaccinated Omicron cases had a 36% (95% confidence interval (CI): 31-42%) risk of transmitting infection to close contacts, as compared to a 28% (25-31%) risk among vaccinated cases. In adjusted analyses, we estimated that any vaccination, prior infection alone and both vaccination and prior infection reduced an index case's risk of transmitting infection by 22% (6-36%), 23% (3-39%) and 40% (20-55%), respectively. Receipt of booster doses and more recent vaccination further reduced infectiousness among vaccinated cases. These findings suggest that, although vaccinated and/or previously infected individuals remain highly infectious upon SARS-CoV-2 infection in this prison setting, their infectiousness is reduced compared to individuals without any history of vaccination or infection. This study underscores benefit of vaccination to reduce, but not eliminate, transmission.

Early immune markers of clinical, virological, and immunological outcomes in patients with COVID-19: a multi-omics study.

Background: The great majority of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) infections are mild and uncomplicated, but some individuals with initially mild COVID-19 progressively develop more severe symptoms. Furthermore, there is substantial heterogeneity in SARS-CoV-2-specific memory immune responses following infection. There remains a critical need to identify host immune biomarkers predictive of clinical and immunological outcomes in SARS-CoV-2-infected patients. Methods: Leveraging longitudinal samples and data from a clinical trial (N=108) in SARS-CoV-2-infected outpatients, we used host proteomics and transcriptomics to characterize the trajectory of the immune response in COVID-19 patients. We characterized the association between early immune markers and subsequent disease progression, control of viral shedding, and SARS-CoV-2-specific T cell and antibody responses measured up to 7 months after enrollment. We further compared associations between early immune markers and subsequent T cell and antibody responses following natural infection with those following mRNA vaccination. We developed machine-learning models to predict patient outcomes and validated the predictive model using data from 54 individuals enrolled in an independent clinical trial. Results: We identify early immune signatures, including plasma RIG-I levels, early IFN signaling, and related cytokines (CXCL10, MCP1, MCP-2, and MCP-3) associated with subsequent disease progression, control of viral shedding, and the SARS-CoV-2-specific T cell and antibody response measured up to 7 months after enrollment. We found that several biomarkers for immunological outcomes are shared between individuals receiving BNT162b2 (Pfizer-BioNTech) vaccine and COVID-19 patients. Finally, we demonstrate that machine-learning models using 2-7 plasma protein markers measured early within the course of infection are able to accurately predict disease progression, T cell memory, and the antibody response post-infection in a second, independent dataset. Conclusions: Early immune signatures following infection can accurately predict clinical and immunological outcomes in outpatients with COVID-19 using validated machine-learning models. Funding: Support for the study was provided from National Institute of Health/National Institute of Allergy and Infectious Diseases (NIH/NIAID) (U01 AI150741-01S1 and T32-AI052073), the Stanford's Innovative Medicines Accelerator, National Institutes of Health/National Institute on Drug Abuse (NIH/NIDA) DP1DA046089, and anonymous donors to Stanford University. Peginterferon lambda provided by Eiger BioPharmaceuticals.

Using sero-epidemiology to monitor disparities in vaccination and infection with SARS-CoV-2.

As SARS-CoV-2 continues to spread and vaccines are rolled-out, the "double burden" of disparities in exposure and vaccination intersect to determine patterns of infection, immunity, and mortality. Serology provides a unique opportunity to measure prior infection and vaccination simultaneously. Leveraging algorithmically-selected residual sera from two hospital networks in the city of San Francisco, cross-sectional samples from 1,014 individuals from February 4-17, 2021 were each tested on two assays (Ortho Clinical Diagnostics VITROS Anti-SARS-CoV-2 and Roche Elecsys Anti-SARS-CoV-2), capturing the first year of the epidemic and early roll-out of vaccination. We estimated, using Bayesian estimation of infection and vaccination, that infection risk of Hispanic/Latinx residents was five times greater than of White residents aged 18-64 (95% Credible Interval (CrI): 3.2-10.3), and that White residents over 65 were twice as likely to be vaccinated as Black/African American residents (95% CrI: 1.1-4.6). We found that socioeconomically-deprived zipcodes had higher infection probabilities and lower vaccination coverage than wealthier zipcodes. While vaccination has created a 'light at the end of the tunnel' for this pandemic, ongoing challenges in achieving and maintaining equity must also be considered.

COVID-19 Vaccination and Estimated Public Health Impact in California.

Importance: Despite widespread vaccination against COVID-19 in the United States, there are limited empirical data quantifying their public health impact in the population. Objective: To estimate the number of COVID-19 cases, hospitalizations, and deaths directly averted because of COVID-19 vaccination in California. Design, Setting, and Participants: This modeling study used person-level data provided by the California Department of Public Health (CDPH) on COVID-19 cases, hospitalizations, and deaths as well as COVID-19 vaccine administration from January 1, 2020, to October 16, 2021. A statistical model was used to estimate the number of COVID-19 cases that would have occurred in the vaccine era (November 29, 2020, to October 16, 2021) in the absence of vaccination based on the ratio of the number of cases among the unvaccinated (aged <12 years) and vaccine-eligible groups (aged ≥12 years) before vaccine introduction. Vaccine-averted COVID-19 cases were estimated by finding the difference between the projected and observed number of COVID-19 cases. Averted COVID-19 hospitalizations and deaths were assessed by applying estimated hospitalization and case fatality risks to estimates of vaccine-averted COVID-19 cases. As a sensitivity analysis, a second independent model was developed to estimate the number of vaccine-averted COVID-19 outcomes by applying published data on vaccine effectiveness to data on COVID-19 vaccine administration and estimated risk of COVID-19 over time. Exposure: COVID-19 vaccination. Main Outcomes and Measures: Number of COVID-19 cases, hospitalizations, and deaths estimated to have been averted because of COVID-19 vaccination. Results: There were 4 585 248 confirmed COVID-19 cases, 240 718 hospitalizations, and 70 406 deaths in California from January 1, 2020, to October 16, 2021, during which 27 164 680 vaccine-eligible individuals aged 12 years and older were reported to have received at least 1 dose of a COVID-19 vaccine in the vaccine era (79.5% of the eligible population). The primary model estimated that COVID-19 vaccination averted 1 523 500 (95% prediction interval [PI], 976 800-2 230 800) COVID-19 cases in California, corresponding to a 72% (95% PI, 53%-91%) relative reduction in cases because of vaccination. COVID-19 vaccination was estimated to have averted 72 930 (95% PI, 53 250-99 160) hospitalizations and 19 430 (95% PI, 14 840-26 230) deaths during the study period. The alternative model identified comparable findings. Conclusions and Relevance: This study provides evidence of the public health benefit of COVID-19 vaccination in the United States and further supports the urgency for continued vaccination.

Risk factor targeting for vaccine prioritization during the COVID-19 pandemic.

A key public health question during any disease outbreak when limited vaccine is available is who should be prioritized for early vaccination. Most vaccine prioritization analyses only consider variation in risk of infection and death by a single risk factor, such as age. We provide a more granular approach with stratification by demographics, risk factors, and location. We use this approach to compare the impact of different COVID-19 vaccine prioritization strategies on COVID-19 cases, deaths and disability-adjusted life years (DALYs) over the first 6 months of vaccine rollout, using California as a case example. We estimate the proportion of cases, deaths and DALYs averted relative to no vaccination for strategies prioritizing vaccination by a single risk factor and by multiple risk factors (e.g. age, location). When targeting by a single risk factor, we find that age-based targeting averts the most deaths (62% for 5 million individuals vaccinated) and DALYs (38%) and targeting essential workers averts the least deaths (31%) and DALYs (24%) over the first 6 months of rollout. However, targeting by two or more risk factors simultaneously averts up to 40% more DALYs. Our findings highlight the potential value of multiple-risk-factor targeting of vaccination against COVID-19 and other infectious diseases, but must be balanced with feasibility for policy.

Persistence, Magnitude, and Patterns of Postacute Symptoms and Quality of Life Following Onset of SARS-CoV-2 Infection: Cohort Description and Approaches for Measurement.

BACKGROUND: There is mounting evidence for the presence of postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC), but there is limited information on the spectrum, magnitude, duration, and patterns of these sequelae as well as their influence on quality of life. METHODS: We assembled a cohort of adults with a documented history of SARS-CoV-2 RNA positivity at ≥2 weeks past onset of coronavirus disease 2019 (COVID-19) symptoms or, if asymptomatic, first positive test. At 4-month intervals, we queried physical and mental health symptoms and quality of life. RESULTS: Of the first 179 participants enrolled, 10 were asymptomatic during the acute phase of SARS-CoV-2 infection, 125 were symptomatic but not hospitalized, and 44 were symptomatic and hospitalized. During the postacute phase, fatigue, shortness of breath, concentration problems, headaches, trouble sleeping, and anosmia/dysgeusia were most common through 8 months of observation. Symptoms were typically at least somewhat bothersome and sometimes exhibited a waxing-and-waning course. Some participants experienced symptoms of depression, anxiety, and post-traumatic stress, as well as difficulties with performance of usual activities. The median visual analogue scale rating of general health was lower at 4 and 8 months compared with pre-COVID-19. Two clusters of symptom domains were identified. CONCLUSIONS: Many participants report bothersome symptoms following onset of COVID-19 with variable patterns of persistence and impact on quality of life. The substantial variability suggests the existence of multiple subphenotypes of PASC. A rigorous approach to the prospective measurement of symptoms and functional manifestations sets the stage for the next phase of research focusing on the pathophysiologic causes of the various subgroups of PASC.

Seroprevalence of anti-SARS-CoV-2 antibodies in Colombia, 2020: A population-based study.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to cause very high morbidity and mortality throughout Latin American countries. However, few population-based seroprevalence surveys have been conducted to quantify attack rates and characterize drivers of transmission. METHODS: We conducted a population-based cross-sectional study to assess the seroprevalence of antibodies against SARS-CoV-2 in ten cities in Colombia between September and December 2020. The study involved multi-stage cluster sampling at each city. Participants provided a serum sample and answered a demographic and risk factor questionnaire. Prior infection by SARS-CoV-2 was ascertained using the "SARS-CoV-2 Total (COV2T) Advia Centaur - Siemens" chemiluminescence assay. FINDINGS: A total of 17863 participants from 7320 households participated in the study. Seroprevalence varied substantially between cities, ranging from 26% (95%CI 23-29 %) in Medellín to 68% (95%CI 62-74 %) in Guapi. There were no differences in seroprevalence by sex, but seropositivity was higher in certain ethnic groups. There was substantial heterogeneity in seroprevalence within cities, driven to a large extent by a strong association between socioeconomic stratum and seropositivity. INTERPRETATION: Colombia has been one of the Latin American countries most affected by the COVID-19 pandemic. This study documented very high attack rates in several Colombian cities by the end of 2020 and identified key drivers of heterogeneities including ethnicity and socioeconomic stratum. Few studies of seroprevalence of SARS-CoV-2 have been conducted in Latin America, and therefore this study contributes to the fundamental understanding of the pandemic in the region. FUNDING: The study was sponsored by, Ministerio de Ciencia y Tecnología e Innovación -CT361/2020, Ministerio de Salud y Protección Social, Fundación Universitaria del Norte, Imperial College of London, Universidad Nacional de Colombia (Sede Medellín), Universidad de Córdoba, California University, Unidad Nacional de Gestión del Riesgo, Centro de Atención y Diagnóstico de Enfermedades Infecciosas -CDI-, Centro Internacional de Entrenamiento e Investigaciones Médicas -CIDEIM-, Departamento Administrativo Nacional de Estadística - DANE, Fondo Nacional de Turismo -FONTUR-, Secretarías de Salud Departamentales, Distritales y Municipales and Instituto Nacional de Salud.

Persistence, Magnitude and Patterns of Post-acute Symptoms and Quality of Life Following Onset of SARS-CoV-2 Infection: Cohort Description and Approaches for Measurement

BACKGROUND There is mounting evidence for the presence of post-acute sequelae of SARS-CoV-2 infection (PASC), but there is limited information on the spectrum, magnitude, duration, and patterns of these sequelae as well as their influence on quality of life. METHODS We assembled a cohort of adults with documented history of SARS-CoV-2 RNA-positivity who were ≥ 2 weeks past onset of COVID-19 symptoms or, if asymptomatic, first positive test. At 4-month intervals, we queried physical and mental health symptoms and quality of life. RESULTS Of the first 179 participants enrolled, 10 were asymptomatic during the acute phase of SARS-CoV-2 infection, 125 symptomatic but not hospitalized, and 44 symptomatic and hospitalized. During the post-acute phase, fatigue, shortness of breath, concentration problems, headaches, trouble sleeping and anosmia/dysgeusia were most common through 8 months of observation. Symptoms were typically at least somewhat bothersome and sometimes exhibited a waxing-and-waning course. Some participants experienced symptoms of depression, anxiety, and post-traumatic stress, as well as difficulties with performance of usual activities. The median visual analogue scale rating of general health was lower at 4 and 8 months compared to pre-COVID-19. Two clusters of symptom domains were identified. CONCLUSION Many participants report bothersome symptoms following onset of COVID-19 with variable patterns of persistence and impact on quality of life. The substantial variability suggests the existence of multiple sub-phenotypes of PASC. A rigorous approach to the prospective measurement of symptoms and functional manifestations sets the stage for the next phase of research focusing on the pathophysiologic causes of the various sub-groups of PASC.

Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco.

Serosurveillance provides a unique opportunity to quantify the proportion of the population that has been exposed to pathogens. Here, we developed and piloted Serosurveillance for Continuous, ActionabLe Epidemiologic Intelligence of Transmission (SCALE-IT), a platform through which we systematically tested remnant samples from routine blood draws in two major hospital networks in San Francisco for SARS-CoV-2 antibodies during the early months of the pandemic. Importantly, SCALE-IT allows for algorithmic sample selection and rich data on covariates by leveraging electronic medical record data. We estimated overall seroprevalence at 4.2%, corresponding to a case ascertainment rate of only 4.9%, and identified important heterogeneities by neighborhood, homelessness status, and race/ethnicity. Neighborhood seroprevalence estimates from SCALE-IT were comparable to local community-based surveys, while providing results encompassing the entire city that have been previously unavailable. Leveraging this hybrid serosurveillance approach has strong potential for application beyond this local context and for diseases other than SARS-CoV-2.

Long-term SARS-CoV-2-specific immune and inflammatory responses in individuals recovering from COVID-19 with and without post-acute symptoms.

We describe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific T cell responses, soluble markers of inflammation, and antibody levels and neutralization capacity longitudinally in 70 individuals with PCR-confirmed SARS-CoV-2 infection. Participants represent a spectrum of illness and recovery, including some with persistent viral shedding in saliva and many experiencing post-acute sequelae of SARS-CoV-2 infection (PASC). T cell responses remain stable for up to 9 months. Whereas the magnitude of early CD4+ T cell immune responses correlates with severity of initial infection, pre-existing lung disease is independently associated with higher long-term SARS-CoV-2-specific CD8+ T cell responses. Among participants with PASC 4 months following coronavirus disease 2019 (COVID-19) symptom onset, we observe a lower frequency of CD8+ T cells expressing CD107a, a marker of degranulation, in response to Nucleocapsid (N) peptide pool stimulation, and a more rapid decline in the frequency of N-specific interferon-γ-producing CD8+ T cells. Neutralizing antibody levels strongly correlate with SARS-CoV-2-specific CD4+ T cell responses.

SARS-CoV-2 antibody magnitude and detectability are driven by disease severity, timing, and assay.

Interpretation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurveillance studies is limited by poorly defined performance of antibody assays over time in individuals with different clinical presentations. We measured antibody responses in plasma samples from 128 individuals over 160 days using 14 assays. We found a consistent and strong effect of disease severity on antibody magnitude, driven by fever, cough, hospitalization, and oxygen requirement. Responses to spike protein versus nucleocapsid had consistently higher correlation with neutralization. Assays varied substantially in sensitivity during early convalescence and time to seroreversion. Variability was dramatic for individuals with mild infection, who had consistently lower antibody titers, with sensitivities at 6 months ranging from 33 to 98% for commercial assays. Thus, the ability to detect previous infection by SARS-CoV-2 is highly dependent on infection severity, timing, and the assay used. These findings have important implications for the design and interpretation of SARS-CoV-2 serosurveillance studies.

Comparison of infection control strategies to reduce COVID-19 outbreaks in homeless shelters in the United States: a simulation study.

BACKGROUND: COVID-19 outbreaks have occurred in homeless shelters across the US, highlighting an urgent need to identify the most effective infection control strategy to prevent future outbreaks. METHODS: We developed a microsimulation model of SARS-CoV-2 transmission in a homeless shelter and calibrated it to data from cross-sectional polymerase chain reaction (PCR) surveys conducted during COVID-19 outbreaks in five homeless shelters in three US cities from March 28 to April 10, 2020. We estimated the probability of averting a COVID-19 outbreak when an exposed individual is introduced into a representative homeless shelter of 250 residents and 50 staff over 30 days under different infection control strategies, including daily symptom-based screening, twice-weekly PCR testing, and universal mask wearing. RESULTS: The proportion of PCR-positive residents and staff at the shelters with observed outbreaks ranged from 2.6 to 51.6%, which translated to the basic reproduction number (R0) estimates of 2.9-6.2. With moderate community incidence (~ 30 confirmed cases/1,000,000 people/day), the estimated probabilities of averting an outbreak in a low-risk (R0 = 1.5), moderate-risk (R0 = 2.9), and high-risk (R0 = 6.2) shelter were respectively 0.35, 0.13, and 0.04 for daily symptom-based screening; 0.53, 0.20, and 0.09 for twice-weekly PCR testing; 0.62, 0.27, and 0.08 for universal masking; and 0.74, 0.42, and 0.19 for these strategies in combination. The probability of averting an outbreak diminished with higher transmissibility (R0) within the simulated shelter and increasing incidence in the local community. CONCLUSIONS: In high-risk homeless shelter environments and locations with high community incidence of COVID-19, even intensive infection control strategies (incorporating daily symptom screening, frequent PCR testing, and universal mask wearing) are unlikely to prevent outbreaks, suggesting a need for non-congregate housing arrangements for people experiencing homelessness. In lower-risk environments, combined interventions should be employed to reduce outbreak risk.

Routine asymptomatic testing strategies for airline travel during the COVID-19 pandemic: a simulation study.

BACKGROUND: Routine viral testing strategies for SARS-CoV-2 infection might facilitate safe airline travel during the COVID-19 pandemic and mitigate global spread of the virus. However, the effectiveness of these test-and-travel strategies to reduce passenger risk of SARS-CoV-2 infection and population-level transmission remains unknown. METHODS: In this simulation study, we developed a microsimulation of SARS-CoV-2 transmission in a cohort of 100 000 US domestic airline travellers using publicly available data on COVID-19 clinical cases and published natural history parameters to assign individuals one of five health states of susceptible to infection, latent period, early infection, late infection, or recovered. We estimated a per-day risk of infection with SARS-CoV-2 corresponding to a daily incidence of 150 infections per 100 000 people. We assessed five testing strategies: (1) anterior nasal PCR test within 3 days of departure, (2) PCR within 3 days of departure and 5 days after arrival, (3) rapid antigen test on the day of travel (assuming 90% of the sensitivity of PCR during active infection), (4) rapid antigen test on the day of travel and PCR test 5 days after arrival, and (5) PCR test 5 days after arrival. Strategies 2 and 4 included a 5-day quarantine after arrival. The travel period was defined as 3 days before travel to 2 weeks after travel. Under each scenario, individuals who tested positive before travel were not permitted to travel. The primary study outcome was cumulative number of infectious days in the cohort over the travel period without isolation or quarantine (population-level transmission risk), and the key secondary outcome was the number of infectious people detected on the day of travel (passenger risk of infection). FINDINGS: We estimated that in a cohort of 100 000 airline travellers, in a scenario with no testing or screening, there would be 8357 (95% uncertainty interval 6144-12831) infectious days with 649 (505-950) actively infectious passengers on the day of travel. The pre-travel PCR test reduced the number of infectious days from 8357 to 5401 (3917-8677), a reduction of 36% (29-41) compared with the base case, and identified 569 (88% [76-92]) of 649 actively infectious travellers on the day of flight; the addition of post-travel quarantine and PCR reduced the number of infectious days to 2520 days (1849-4158), a reduction of 70% (64-75) compared with the base case. The rapid antigen test on the day of travel reduced the number of infectious days to 5674 (4126-9081), a reduction of 32% (26-38) compared with the base case, and identified 560 (86% [83-89]) actively infectious travellers; the addition of post-travel quarantine and PCR reduced the number of infectious days to 3124 (2356-495), a reduction of 63% (58-66) compared with the base case. The post-travel PCR alone reduced the number of infectious days to 4851 (3714-7679), a reduction of 42% (35-49) compared with the base case. INTERPRETATION: Routine asymptomatic testing for SARS-CoV-2 before travel can be an effective strategy to reduce passenger risk of infection during travel, although abbreviated quarantine with post-travel testing is probably needed to reduce population-level transmission due to importation of infection when travelling from a high to low incidence setting. FUNDING: University of California, San Francisco.

Characterization and Biomarker Analyses of Post-COVID-19 Complications and Neurological Manifestations.

As the SARS-CoV-2 pandemic continues, reports have demonstrated neurologic sequelae following COVID-19 recovery. Mechanisms to explain long-term neurological sequelae are unknown and need to be identified. Plasma from 24 individuals recovering from COVID-19 at 1 to 3 months after initial infection were collected for cytokine and antibody levels and neuronal-enriched extracellular vesicle (nEV) protein cargo analyses. Plasma cytokine IL-4 was increased in all COVID-19 participants. Volunteers with self-reported neurological problems (nCoV, n = 8) had a positive correlation of IL6 with age or severity of the sequalae, at least one co-morbidity and increased SARS-CoV-2 antibody compared to those COVID-19 individuals without neurological issues (CoV, n = 16). Protein markers of neuronal dysfunction including amyloid beta, neurofilament light, neurogranin, total tau, and p-T181-tau were all significantly increased in the nEVs of all participants recovering from COVID-19 compared to historic controls. This study suggests ongoing peripheral and neuroinflammation after COVID-19 infection that may influence neurological sequelae by altering nEV proteins. Individuals recovering from COVID-19 may have occult neural damage while those with demonstrative neurological symptoms additionally had more severe infection. Longitudinal studies to monitor plasma biomarkers and nEV cargo are warranted to assess persistent neurodegeneration and systemic effects.

Universal Polymerase Chain Reaction and Antibody Testing Demonstrate Little to No Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 in a Rural Community.

BACKGROUND: Limited systematic surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the early months of the US epidemic curtailed accurate appraisal of transmission intensity. Our objective was to perform case detection of an entire rural community to quantify SARS-CoV-2 transmission using polymerase chain reaction (PCR) and antibody testing. METHODS: We conducted a cross-sectional survey of SARS-CoV-2 infection in the rural town of Bolinas, California (population 1620), 4 weeks after shelter-in-place orders. Participants were tested between April 20 and 24, 2020. Prevalence by PCR and seroprevalence from 2 forms of antibody testing were performed in parallel (Abbott ARCHITECT immunoglobulin [Ig]G and in-house IgG enzyme-linked immunosorbent assay). RESULTS: Of 1891 participants, 1312 were confirmed Bolinas residents (>80% community ascertainment). Zero participants were PCR positive. Assuming 80% sensitivity, it would have been unlikely to observe these results (P < .05) if there were >3 active infections in the community. Based on antibody results, estimated prevalence of prior infection was 0.16% (95% credible interval [CrI], 0.02%-0.46%). The positive predictive value (PPV) of a positive result on both tests was 99.11% (95% CrI, 95.75%-99.94%), compared with PPV 44.19%-63.32% (95% CrI, 3.25%-98.64%) if 1 test was utilized. CONCLUSIONS: Four weeks after shelter-in-place, SARS-CoV-2 infection in a rural Northern California community was extremely rare. In this low-prevalence setting, use of 2 antibody tests increased seroprevalence estimate precision. This was one of the first community-wide studies to successfully implement synchronous PCR and antibody testing, particularly in a rural setting. Widespread testing remains an underpinning of effective disease control in conjunction with consistent uptake of public health measures.

Universal PCR and antibody testing demonstrate little to no transmission of SARS-CoV-2 in a rural community.

BACKGROUND: The absence of systematic surveillance for SARS-CoV-2 has curtailed accurate appraisal of transmission intensity. Our objective was to perform case detection of an entire rural community to quantify SARS-CoV-2 transmission using PCR and antibody testing. METHODS: We conducted a cross-sectional survey of the prevalence and cumulative incidence of SARS-CoV-2 infection in the rural town of Bolinas, California (population 1,620), four weeks following shelter-in-place orders. Residents and county essential workers were tested between April 20th-24th, 2020. Prevalence by PCR and seroprevalence combining data from two forms of antibody testing were performed in parallel (Abbott ARCHITECT IgG to nucleocapsid protein and in-house IgG ELISA to the receptor binding domain). RESULTS: Of 1,891 participants, 1,312 were confirmed Bolinas residents (>80% community ascertainment). Zero participants were PCR positive. Assuming 80% sensitivity, it would have been unlikely to observe these results (p<0.05) if there were >3 active infections in the community. Based on antibody results, estimated prevalence of prior infection was 0.16% (95% CrI: 0.02%, 0.46%). Seroprevalence estimates using only one of the two tests would have been higher, with greater uncertainty. The positive predictive value (PPV) of a positive result on both tests was 99.11% (95% CrI: 95.75%, 99.94%), compared to PPV 44.19%-63.32% (95% CrI range 3.25%-98.64%) if only one test was utilized. CONCLUSIONS: Four weeks following shelter-in-place, active and prior SARS-CoV-2 infection in a rural Northern California community was extremely rare. In this low prevalence setting, use of two antibody tests increased the PPV and precision of seroprevalence estimates.