Performance of the inFLUenza Patient-Reported Outcome Plus (FLU-PRO Plus) Instrument in Patients With Coronavirus Disease 2019

Background

The inFLUenza Patient-Reported Outcome Plus (FLU-PRO Plus) is a patient-reported outcome data collection instrument assessing symptoms of viral respiratory tract infections across 8 body systems. This study evaluated the measurement properties of FLU-PRO Plus in a study enrolling individuals with coronavirus disease 2019 (COVID-19).

Methods

Data from a prospective cohort study (EPICC) in US Military Health System beneficiaries evaluated for COVID-19 was utilized. Adults with symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with FLU-PRO Plus survey information within 1 week of symptom onset were included. Reliability of FLU-PRO Plus was estimated using intraclass correlation coefficient (ICC; 2 days' reproducibility). Known-groups validity was assessed using patient global assessment (PGA) of disease severity. Patient report of return to usual health was used to assess responsiveness (day 1-6/7).

Results

Two hundred twenty-six SARS-CoV-2-positive participants were included in the analysis. Reliability among those who reported no change in their symptoms from one day to the next was high for most domains (ICC range, 0.68-0.94 for day 1 to day 2). Construct validity was demonstrated by moderate to high correlation between the PGA rating of disease severity and domain and total scores (eg, total scores correlation: 0.69 [influenza-like illness severity], 0.69 [interference in daily activities], and -0.58 [physical health]). In addition, FLU-PRO Plus demonstrated good known-groups validity, with increasing domain and total scores observed with increasing severity ratings.

Conclusions

FLU-PRO Plus performs well in measuring signs and symptoms in SARS-CoV-2 infection with excellent construct validity, known-groups validity, and responsiveness to change. Standardized data collection instruments facilitate meta-analyses, vaccine effectiveness studies, and other COVID-19 research activities.

Anatomical site, viral RNA abundance, and time of sampling correlate with molecular detection of SARS-CoV-2 during infection

Background

Nasopharyngeal (NP) swabs are the standard for SARS-CoV-2 diagnosis. If less invasive alternatives to NP swabs (eg, oropharyngeal [OP] or nasal swabs [NS]) are comparably sensitive, the use of these techniques may be preferable in terms of comfort, convenience, and safety.

Methods

This study compared the detection of SARS-CoV-2 in swab samples collected on the same day among participants with at least one positive PCR test.

Results

Overall, 755 participants had at least one set of paired swabs. Concordance between NP and other swab types was 75% (NS), 72% (OP), 54% (rectal swabs [RS]), and 78% (NS/OP combined). Kappa values were moderate for the NS, OP, and NS/OP comparisons (0.50, 0.45, and 0.54, respectively). Highest sensitivity relative to NP (0.87) was observed with a combination of NS/OP tests (positive if either NS or OP was positive). Sensitivity of the non-NP swab types was highest in the first week postsymptom onset and decreased thereafter. Similarly, virus RNA quantity was highest in the NP swabs as compared with NS, OP, and RS within two weeks postsymptom onset. OP and NS performance decreased as virus RNA quantity decreased. No differences were noted between NS specimens collected at home or in clinic.

Conclusions

NP swabs detected more SARS-CoV-2 cases than non-NP swabs, and the sensitivity of the non-NP swabs decreased with time postsymptom onset. While other swabs may be simpler to collect, NP swabs present the best chance of detecting SARS-CoV-2 RNA, which is essential for clinical care as well as genomic surveillance.

337. SARS-CoV-2 Viral Load Does Not Predict Incident Venous Thromboembolism in COVID-19

Background

The risk factors of venous thromboembolism (VTE) in COVID-19 warrant further study. We leveraged a cohort in the Military Health System (MHS) to identify clinical and virological predictors of incident deep venous thrombosis (DVT), pulmonary embolism (PE), and other VTE within 90-days after COVID-19 onset.

Methods

PCR or serologically-confirmed SARS-CoV-2 infected MHS beneficiaries were enrolled via nine military treatment facilities (MTF) through April 2021. Case characteristics were derived from interview and review of the electronic medical record (EMR) through one-year follow-up in outpatients and inpatients. qPCR was performed on upper respiratory swab specimens collected post-enrollment to estimate SARS-CoV-2 viral load. The frequency of incident DVT, PE, or other VTE by 90-days post-COVID-19 onset were ascertained by ICD-10 code. Correlates of 90-day VTE were determined through multivariate logistic regression, including age and sampling-time-adjusted log10-SARS-CoV-2 GE/reaction as a priori predictors in addition to other demographic and clinical covariates which were selected through stepwise regression.

Results

1473 participants with SARS-CoV-2 infection were enrolled through April 2021. 21% of study participants were inpatients; the mean age was 41 years (SD = 17.0 years). The median Charlson Comorbidity Index score was 0 (IQR = 0 - 1, range = 0 - 13). 27 (1.8%) had a prior history of VTE. Mean maximum viral load observed was 1.65 x 10⁷ genome equivalents/reaction. 36 (2.4%) of all SARS-CoV-2 cases (including inpatients and outpatients), 29 (9.5%) of COVID-19 inpatients, and 7 (0.6%) of outpatients received an ICD-10 diagnosis of any VTE within 90 days after COVID-19 onset. Logistic regression identified hospitalization (aOR = 11.1, p = 0.003) and prior VTE (aOR = 6.2 , p = 0.009) as independent predictors of VTE within 90 days of symptom onset. Neither age (aOR = 1.0, p = 0.50), other demographic covariates, other comorbidities, nor SARS-CoV-2 viral load (aOR = 1.1, p = 0.60) were associated with 90-day VTE.

Conclusion

VTE was relatively frequent in this MHS cohort. SARS-CoV-2 viral load did not increase the odds of 90-day VTE. Rather, being hospitalized for SARS-CoV-2 and prior VTE history remained the strongest predictors of this complication.

Disclosures

Simon Pollett, MBBS, Astra Zeneca (Other Financial or Material Support, HJF, in support of USU IDCRP, funded under a CRADA to augment the conduct of an unrelated Phase III COVID-19 vaccine trial sponsored by AstraZeneca as part of USG response (unrelated work)) Ryan C. Maves, MD, EMD Serono (Advisor or Review Panel member)Heron Therapeutics (Advisor or Review Panel member) David A. Lindholm, MD, American Board of Internal Medicine (Individual(s) Involved: Self): Member of Auxiliary R&D Infectious Disease Item-Writer Task Force. No financial support received. No exam questions will be disclosed ., Other Financial or Material Support David Tribble, M.D., DrPH, Astra Zeneca (Other Financial or Material Support, HJF, in support of USU IDCRP, funded under a CRADA to augment the conduct of an unrelated Phase III COVID-19 vaccine trial sponsored by AstraZeneca as part of USG response (unrelated work))

461. Classical Antigen Presenting Cell Activation Correlates with T Cell Immunity and COVID-19 Severity

Background

The initial response of immune cells against respiratory viruses often determines the severity and duration of disease. The early trajectory of the immune response during infection with SARS-CoV-2 remains poorly understood. Dysregulation of innate immune factors that facilitate viral clearance and the adaptive response, such as type I interferons, have been implicated in severe COVID-19. However, collection of biological samples during the first seven days post-symptom onset has posed a logistical challenge, limiting our knowledge surrounding the immune responses that drive protection versus immunopathology.

Methods

From March 2020, Military Health System beneficiaries presenting with a positive SARS-CoV-2 test, a COVID-19 like illness, or a high-risk SARS-CoV-2 exposure at nine military medical treatment facilities across the United States were eligible for enrollment in our longitudinal cohort study, which included collection of respiratory sample, sera, plasma, and peripheral blood mononuclear cells (PBMCs). Twenty-five SARS-CoV-2 infected study participants provided samples with in the first seven days of symptom onset, fifteen of whom were hospitalized with COVID-19. We employed multiparameter spectral flow cytometry to comprehensively analyze the early trajectory of the innate and adaptive immune responses.

Results

We discovered that early activation of critical antigen presenting cell subsets was impaired upon comparing inpatients with outpatients, correlating with decreased antigen-experienced T cell responses. Specifically, we noted reduced expression of key costimulatory molecules, CD80 and CD86, on conventional dendritic cells that are required for viral antigen-specific T cell priming. Reduction in CD38, a marker of activation was also observed on inpatient dendritic cell subsets.

Conclusion

Reduced antigen presenting cell activation and expression of ligands that facilitate T cell engagement may impede the efficient clearance of SARS-CoV-2, coinciding with more severe disease in our cohort. Further analysis of the functional activation of early innate immune responses triggered by SARS-CoV-2 may unveil new immune biomarkers and therapeutic targets to predict and prevent severe disease associated with inadequate T cell immunity.

Disclosures

Simon Pollett, MBBS, Astra Zeneca (Other Financial or Material Support, HJF, in support of USU IDCRP, funded under a CRADA to augment the conduct of an unrelated Phase III COVID-19 vaccine trial sponsored by AstraZeneca as part of USG response (unrelated work))

458. A Machine Learning Approach Identifies Distinct Early-Symptom Cluster Phenotypes Which Correlate with Severe SARS-CoV-2 Outcomes

Background

The novel coronavirus disease 2019 (COVID-19) pandemic remains a global challenge. Accurate COVID-19 prognosis remains an important aspect of clinical management. While many prognostic systems have been proposed, most are derived from analyses of individual symptoms or biomarkers. Here, we take a machine learning approach to first identify discrete clusters of early stage-symptoms which may delineate groups with distinct symptom phenotypes. We then sought to identify whether these groups correlate with subsequent disease severity.

Methods

The Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential (EPICC) study is a longitudinal cohort study with data and biospecimens collected from nine military treatment facilities over 1 year of follow-up. Demographic and clinical characteristics were measured with interviews and electronic medical record review. Early symptoms by organ-domain were measured by FLU-PRO-plus surveys collected for 14 days post-enrollment, with surveys completed a median 14.5 (Interquartile Range, IQR = 13) days post-symptom onset. Using these FLU-PRO-plus responses, we applied principal component analysis followed by unsupervised machine learning algorithm k-means to identify groups with distinct clusters of symptoms. We then fit multivariate logistic regression models to determine how these early-symptom clusters correlated with hospitalization risk after controlling for age, sex, race, and obesity.

Results

Using SARS-CoV-2 positive participants (n = 1137) from the EPICC cohort (Figure 1), we transformed reported symptoms into domains and identified three groups of participants with distinct clusters of symptoms. Logistic regression demonstrated that cluster-2 was associated with an approximately three-fold increased odds [3.01 (95% CI: 2-4.52); P < 0.001] of hospitalization which remained significant after controlling for other factors [2.97 (95% CI: 1.88-4.69); P < 0.001].

Conclusion

Our findings have identified three distinct groups with early-symptom phenotypes. With further validation of the clusters’ significance, this tool could be used to improve COVID-19 prognosis in a precision medicine framework and may assist in patient triaging and clinical decision-making.

Disclaimer

Disclosures

David A. Lindholm, MD, American Board of Internal Medicine (Individual(s) Involved: Self): Member of Auxiliary R&D Infectious Disease Item-Writer Task Force. No financial support received. No exam questions will be disclosed ., Other Financial or Material Support Ryan C. Maves, MD, EMD Serono (Advisor or Review Panel member)Heron Therapeutics (Advisor or Review Panel member) Simon Pollett, MBBS, Astra Zeneca (Other Financial or Material Support, HJF, in support of USU IDCRP, funded under a CRADA to augment the conduct of an unrelated Phase III COVID-19 vaccine trial sponsored by AstraZeneca as part of USG response (unrelated work))

385. SARS-CoV-2 Infections Among Military Personnel Deployed on the USNS COMFORT to New York City During the COVID-19 Pandemic and One-Year Follow-Up

Background

The USNS COMFORT deployed to New York City to augment the inpatient health care capacity in March 2020. The aim of this study was to determine the prevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection among US Navy personnel upon return from deployment, and to identify incident cases of SARS-CoV-2 infection during 1 year of follow-up.

Methods

Crewmembers, the majority of whom were health care workers (HCW), were enrolled following deployment, in May 2020. PCR results from symptomatic crewmembers during deployment, and Day 0 and Day 14 post-deployment screening swabs conducted on all crewmembers, per military order, were abstracted. A questionnaire and serum were collected on Day 14 post-deployment. SARS-CoV-2 infection was defined as a positive SARS-CoV-2 spike glycoprotein immunoglobulin G antibody (IgG) or PCR. COVID-19 related medical encounters, PCR and antibody testing results within 1 year following deployment were abstracted from the Military Health System Data Repository (MDR). There was adequate provision of personal protective equipment (PPE) in the hospital and the COVID-19 vaccine roll-out for HCW began in December 2020.

Results

Of the 1200 crewmembers, 449 were enrolled and completed the questionnaire and screening swabs, and 432 (96.2%) completed the Day 14 blood draw (Table 1). The cumulative prevalence of SARS-CoV-2 infection was 3.01% (13/432; 95% CI, 1.61%–5.09%). One of 17 subjects did not complete the blood draw and was PCR positive on Day 14. 433/449 (96.4%) had a PCR performed during the follow-up period (i.e. after the Day 14 post-deployment visit until Feb 2021), for HCW screening or symptomatic illness (median number of tests: 2 [IQR: 1, 2; range: 1,6]). 25 of 433 (5.8%) were PCR positive (Fig 1). 19 (76.0%) occurred in corpsmen, 23 (92.0%) were symptomatic and none were hospitalized. One asymptomatic re-infection occurred in a crewmember who was PCR negative and IgG positive at Day 14 post-deployment.

Table 1. Characteristics of the overall cohort and by SARS-CoV-2 infection

Figure 1. Number of PCR tests (bar graph) and positivity rate (red line) by month in 449 USNS COMFORT crewmembers during 1-year follow-up after return from deployment

Conclusion

The post-deployment prevalence of SARS-CoV-2 infection was low. A high proportion of HCW underwent PCR testing during 1-year follow-up but a low incidence of infection was observed. This was likely from community transmission as nosocomial transmission was mitigated by adequate PPE and vaccine roll-out.

Disclosures

All Authors: No reported disclosures

677. Compliance and Performance Characteristics of Subject Collected Versus Health-care Worker Collected Nasal Swabs for Respiratory Viral Surveillance

Background

Self-collection of mid-nasal swabs (SCNS) at home is a convenient alternative to health-care worker-collected nasal swabs (HCWC) for determining the pathogen-specific epidemiology of influenza-like illness (ILI). We evaluated the compliance and performance characteristics of SCNS vs. HCWC for respiratory pathogens during 2019-2020 flu season.

Methods

Adult Military Health System (MHS) beneficiaries were enrolled in an influenza vaccine effectiveness trial (PAIVED). Following vaccination, subjects were instructed on SCNS and completion of a symptom diary and were contacted weekly to ascertain ILI symptoms (fever, sore throat, and/or cough). In the event of an ILI, subjects completed the symptom diary and SCNS and were scheduled a clinic visit for HCWC. Swabs were tested with the Luminex NxTAG® Respiratory Pathogen Panel. We evaluated compliance with swab collection, positive percent agreement (PPA) of SCNS using PCR detection from either HCWC or SCNS as the reference standard, and agreement between paired swabs using the Cohen Kappa coefficient (Κ).

Results

1808 ILI were reported by 972 participants enrolled during the study period. Compliance with HCWC was higher than SCNS (58% [1042] vs. 42% [766]; p< 0.001). SCNS were associated with a shorter interval from symptom onset (median: 4 days [IQR:2-6 days] vs. clinic collect: 7 days [IQR:4-9 days]; p < 0.001). 663 paired swabs were available for 609 participants (Table 1). The overall detection rate was higher in SCNS (36%) than HCWC (26%; p< 0.001) (Figure 1). The overall PPA was 85.7% and a PPA of approximately 80% of greater was observed for influenza, rhino/enterovirus, parainfluenza and respiratory syncytial virus. Agreement between paired swabs was poor due to the lower detection rates in HCWC.

Table 1. Demographics and swab collection data for 609 participants who provided 663 paired swabs

Conclusion

SCNS were associated with higher detection rates compared to HCWC, likely due to the shorter interval between symptom onset and swab collection. Strategies to improve compliance with SCNS and minimize the interval between symptom onset and swab collection are needed to optimize detection of respiratory pathogens in this MHS cohort.

Disclosures

Ryan C. Maves, MD, EMD Serono (Advisor or Review Panel member)Heron Therapeutics (Advisor or Review Panel member) Jitu Modi, MD, GSK (Speaker's Bureau)

05. Pragmatic Assessment of Influenza Vaccine Effectiveness in the DoD (PAIVED): Updates from Year 3 of Multi-Site Trial

Background

The SARS-CoV-2 pandemic has spotlighted respiratory infections and the value of effective vaccines. The SARS-CoV-2 vaccine has been remarkably effective; however, influenza vaccine effectiveness has been reported to be lower among active duty military populations than in the general public (18% vs 36%). The Pragmatic Assessment of Influenza Vaccine Effectiveness in the DoD (PAIVED) study compares 3 FDA-licensed influenza vaccine types (egg-based, cell-based, and recombinant) to assess differences in immunogenicity and effectiveness in adults.

Methods

Participants in the 3rd year of PAIVED (2020/21 influenza season) were enrolled from October 2020 through January 2021. Participants received weekly surveys about influenza-like-illnesses (ILI) experienced in the past week; if they reported an ILI, they were queried about symptom duration and severity, and asked to self-collect a nasal swab and dried blood sample. Four weeks later, more information about symptom duration and illness burden was obtained via telephone interview, and the participant collected a second blood sample.

Results

PAIVED year 3 enrolled 3,269 participants (Table 1). 278 participants reported 1 ILI , while 60 reported 2 ILIs, and 18 reported 3 ILIs. No pathogen was identified for most processed ILI samples (78%); the most common viruses were SARS-CoV-2 (25, 12%), rhinovirus (24, 12%), and seasonal coronaviruses (4, 2%). No influenza has been identified thus far. Among those participants who had convalescent ILI visits (275), the median duration of the reported ILIs was 9 days (IQR 5, 15), with a median of 4 days (IQR 2, 7) of limited activity, and 2 days (IQR 0, 3) with fever. Three individuals were hospitalized.

Conclusion

There have been relatively low rates of ILI identified in this study during this season, with only 11% of the participants reporting an ILI so far, consistent with low rates of non-COVID-19 ILI reported elsewhere during the current pandemic. We anticipate some influenza cases may be identified as more samples are processed. Planned analyses include calculating comparative influenza vaccine effectiveness to inform future vaccine purchasing decisions, as well as comparing serological response to the different vaccines.

Disclosures

Ryan C. Maves, MD, EMD Serono (Advisor or Review Panel member)Heron Therapeutics (Advisor or Review Panel member) Jitu Modi, MD, GSK (Speaker’s Bureau)

438. Phenotypic Differences Between Distinct Immune Biomarker Clusters During the ‘Hyperinflammatory’ Middle-Phase of COVID-19

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections peak during an inflammatory ‘middle’ phase and lead to severe illness predominately among those with certain comorbid noncommunicable diseases (NCDs). We used network machine learning to identify inflammation biomarker patterns associated with COVID-19 among those with NCDs.

Methods

SARS-CoV-2 RT-PCR positive subjects who had specimens available within 15-28 days post-symptom onset were selected from the DoD/USU EPICC COVID-19 cohort study. Plasma levels of 15 inflammation protein biomarkers were measured using a broad dynamic range immunoassay on samples collected from individuals with COVID-19 at 8 military hospitals across the United States. A network machine learning algorithm, topological data analysis (TDA), was performed using results from the ‘hyperinflammatory’ middle phase. Backward selection stepwise logistic regression was used to identify analytes associated with each cluster. NCDs with a significant association (0.05 significance level) across clusters using Fisher’s exact test were further evaluated comparing the NCD frequency in each cluster against all other clusters using a Kruskal-Wallis test. A sensitivity analysis excluding mild disease was also performed.

Results

The analysis population (n=129, 33.3% female, median 41.3 years of age) included 77 ambulatory, 31 inpatient, 16 ICU-level, and 5 fatal cases. TDA identified 5 unique clusters (Figure 1). Stepwise regression with a Bonferroni-corrected cutoff adjusted for severity identified representative analytes for each cluster (Table 1). The frequency of diabetes (p=0.01), obesity (p< 0.001), and chronic pulmonary disease (p< 0.001) differed among clusters. When restricting to hospitalized patients, obesity (8 of 11), chronic pulmonary disease (6 of 11), and diabetes (6 of 11) were more prevalent in cluster C than all other clusters.

Cluster differences in comorbid diseases and severity by cluster. 1A: bar plot of diabetes prevalence; 1B: bar plot of chronic lung disease ; 1C: bar plot of obesity prevalence; 1D: prevalence of steroid treatment ; 1E: Topologic data analysis network with clusters labeled; 1F: Bar plot of ordinal levels of severity.

Conclusion

Machine learning clustering methods are promising analytical tools for identifying inflammation marker patterns associated with baseline risk factors and severe illness due to COVID-19. These approaches may offer new insights for COVID19 prognosis, therapy, and prevention.

Disclosures

Simon Pollett, MBBS, Astra Zeneca (Other Financial or Material Support, HJF, in support of USU IDCRP, funded under a CRADA to augment the conduct of an unrelated Phase III COVID-19 vaccine trial sponsored by AstraZeneca as part of USG response (unrelated work))

34. Long-term clinical outcomes following SARS-CoV-2 infection include persistent symptoms and cardiovascular disease beyond 3 months post-infection

Background

The long-term health effects after SARS-CoV-2 infection remain poorly understood. We evaluated health and healthcare usage after SARS-CoV-2 infection via surveys and longitudinal electronic medical record (EMR) review within the Military Health System (MHS).

Methods

We studied MHS beneficiaries enrolled in the Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential (EPICC) cohort from March to December 2020. COVID-19 illness symptom severity and duration were derived from surveys initiated in late 2020. In addition, multi-year healthcare encounter history before and after onset of COVID-19 symptoms was collected from the MHS EMR. Odds of organ-system clinical diagnoses within the 3 months pre- and post-symptom onset were calculated using generalized linear models, controlling for age, sex, and race, and including participant as a random effect.

Results

1,015 participants were included who were SARS-CoV-2 positive, symptomatic, and had 3-month follow-up data available in the EMR (Table 1). 625 of these participants had survey data collected more than 28 days post-symptom onset, among whom 17% and 6% reported persistent symptoms at 28-84 days, and 85+ days, respectively. 9.6% had not resumed normal activities by one month. The most frequently reported symptoms persisting beyond 28 days were dyspnea, loss of smell and/or taste, fatigue, and exercise intolerance (Figure 1A). When compared with the period 61 to 90 days prior to symptom onset, the first month post-symptom onset period was associated with increases of pulmonary (aOR = 57, 95% CI 28-112), renal (aOR = 29, 95% CI 10-84), cardiovascular (aOR = 7, 95% CI 5-11), and neurological diagnoses (aOR = 3, 95% CI 2-4) (Figures 1B and 1C). Cardiovascular disease diagnoses remained elevated through 3 months (aOR = 2, 95% CI 1-3).

Table 1. Characteristics of SARS-CoV-2+ EPICC participants, and illness duration among those with 28+ days post-symptom onset survey data collection.

Figure 1

Fig1A. Symptoms reported by EPICC participants with illnesses longer than 28 days; 1B. Percent of participants with organ system specific diagnoses on each day, 90 days pre- and post-symptom onset; 1C. Odds of organ system specific diagnoses within each month, +/- 3 months of symptom onset, were calculated using generalized linear models, controlling for age, sex, and race and included participants as a random effect. Odds shown are relative to the earliest period included in the model, 61-90 days before onset.

Conclusion

In this MHS cohort, a significant proportion of participants had persistent symptoms and cardiovascular disease diagnoses 3 months after COVID-19 illness onset. These findings emphasize the long-term morbidity of COVID-19 and the importance of mitigating SARS-CoV-2 infections. Further analyses will evaluate demographic, clinical, and biomarker predictors of medium-to-long term organ-specific post-acute sequelae.

Disclosures

Simon Pollett, MBBS, Astra Zeneca (Other Financial or Material Support, HJF, in support of USU IDCRP, funded under a CRADA to augment the conduct of an unrelated Phase III COVID-19 vaccine trial sponsored by AstraZeneca as part of USG response (unrelated work)) Ryan C. Maves, MD, EMD Serono (Advisor or Review Panel member)Heron Therapeutics (Advisor or Review Panel member) David A. Lindholm, MD, American Board of Internal Medicine (Individual(s) Involved: Self): Member of Auxiliary R&D Infectious Disease Item-Writer Task Force. No financial support received. No exam questions will be disclosed ., Other Financial or Material Support

1338. Before and After: The Impact of the COVID-19 Pandemic on Influenza-Like Illness Trends in PAIVED

Background

The Pragmatic Assessment of Influenza Vaccine Effectiveness in the DoD (PAIVED) is a multicenter study assessing influenza vaccine effectiveness in active duty service members, retirees, and dependents. PAIVED recently completed its third year and offers a unique opportunity to examine influenza-like illness (ILI) trends prior to and during the COVID-19 pandemic in a prospective, well-defined cohort.

Methods

During the 2018-19, 2019-20, and 2020-21 influenza seasons, PAIVED enrolled DoD beneficiaries presenting for annual influenza vaccination. After collecting baseline demographic data, participants were randomized to receive egg-based, cell-based, or recombinant-derived influenza vaccine. Weekly throughout the influenza season of enrollment, participants were surveyed electronically for ILI, defined as (1) having cough or sore throat, plus (2) feeling feverish/having chills or having body aches/fatigue. Participants with ILI completed a daily symptom diary for seven days and submitted a nasal swab for pathogen detection.

Results

Over the three seasons, there were 10,656 PAIVED participants: 1514 (14.2%) in 2018-19, 5876 (55.1%) in 2019-20, and 3266 (30.6%) in 2020-21. The majority were male (68-73% per year) with a mean age of 34±14.8 years at enrollment. 2266 participants reported a total of 2673 unique ILIs. The highest percentage of participants with ILI was in 2019-20 (28.2%), versus 19.6% in 2018-19 and 9.6% in 2020-21. Figure 1 depicts the percent of individuals reporting ILI by week of the season for each of the PAIVED seasons. Notably, after March 21, 2020, the weekly incidence of participants reporting ILI never exceeded 1%.

Figure 1. Percent of PAIVED participants reporting ILI by week of season.

Conclusion

The low incidence of reported ILI in PAIVED participants during the COVID-19 pandemic is consistent with national influenza surveillance reports of influenza and outpatient ILI activity, suggesting that mitigation measures taken to reduce transmission of SARS-CoV-2 reduced the spread of other respiratory viruses.

Disclaimer

Disclosures

Ryan C. Maves, MD, EMD Serono (Advisor or Review Panel member)Heron Therapeutics (Advisor or Review Panel member) Jitu Modi, MD, GSK (Speaker’s Bureau)

450. Type I Interferon Autoantibodies Are Detected in Those with Critical COVID-19, Including a Young Female Patient

Background

Approximately 10-20% of patients with critical COVID-19 harbor neutralizing autoantibodies (auto-Abs) that target type I interferons (IFN), a family of cytokines that induce critical innate immune defense mechanisms upon viral infection. Studies to date indicate that these auto-Abs are mostly detected in men over age 65.

Methods

We screened for type I IFN serum auto-Abs in sera collected < 21 days post-symptom onset in a subset of 103 COVID-19 inpatients and 24 outpatients drawn from a large prospective cohort study of SARS-CoV-2 infected patients enrolled across U.S. Military Treatment Facilities. The mean age of this n = 127 subset of study participants was 55.2 years (SD = 15.2 years, range 7.7 – 86.2 years), and 86/127 (67.7%) were male.

Results

Among those hospitalized 49/103 (47.6%) had severe COVID-19 (required at least high flow oxygen), and nine subjects died. We detected neutralizing auto-Abs against IFN-α, IFN-ω, or both, in four inpatients (3.9%, 8.2% of severe cases), with no auto-Abs detected in outpatients. Three of these patients were white males over the age of 62, all with multiple comorbidities; two of whom died and the third requiring high flow oxygen therapy. The fourth patient was a 36-year-old Hispanic female with a history of obesity who required mechanical ventilation during her admission for COVID-19.

Conclusion

These findings support the association between type I IFN auto-antibody production and life-threatening COVID-19. With further validation, reliable high-throughput screening for type I IFN auto-Abs may inform diagnosis, pathogenesis and treatment strategies for COVID-19, particularly in older males. Our finding of type I IFN auto-Ab production in a younger female prompts further study of this autoimmune phenotype in a broader population.

Disclosures

David A. Lindholm, MD, American Board of Internal Medicine (Individual(s) Involved: Self): Member of Auxiliary R&D Infectious Disease Item-Writer Task Force. No financial support received. No exam questions will be disclosed ., Other Financial or Material Support David Tribble, M.D., DrPH, Astra Zeneca (Other Financial or Material Support, HJF, in support of USU IDCRP, funded under a CRADA to augment the conduct of an unrelated Phase III COVID-19 vaccine trial sponsored by AstraZeneca as part of USG response (unrelated work)) Simon Pollett, MBBS, Astra Zeneca (Other Financial or Material Support, HJF, in support of USU IDCRP, funded under a CRADA to augment the conduct of an unrelated Phase III COVID-19 vaccine trial sponsored by AstraZeneca as part of USG response (unrelated work))

Predictive Value of an Age-Based Modification of the National Early Warning System in Hospitalized Patients With COVID-19

BACKGROUND

Early recognition of high-risk patients with coronavirus disease 2019 (COVID-19) may improve outcomes. Although many predictive scoring systems exist, their complexity may limit utility in COVID-19. We assessed the prognostic performance of the National Early Warning Score (NEWS) and an age-based modification (NEWS+age) among hospitalized COVID-19 patients enrolled in a prospective, multicenter US Military Health System (MHS) observational cohort study.

METHODS

Hospitalized adults with confirmed COVID-19 not requiring invasive mechanical ventilation at admission and with a baseline NEWS were included. We analyzed each scoring system's ability to predict key clinical outcomes, including progression to invasive ventilation or death, stratified by baseline severity (low [0-3], medium [4-6], and high [≥7]).

RESULTS

Among 184 included participants, those with low baseline NEWS had significantly shorter hospitalizations (P < .01) and lower maximum illness severity (P < .001). Most (80.2%) of low NEWS vs 15.8% of high NEWS participants required no or at most low-flow oxygen supplementation. Low NEWS (≤3) had a negative predictive value of 97.2% for progression to invasive ventilation or death; a high NEWS (≥7) had high specificity (93.1%) but low positive predictive value (42.1%) for such progression. NEWS+age performed similarly to NEWS at predicting invasive ventilation or death (NEWS+age: area under the receiver operating characteristics curve [AUROC], 0.69; 95% CI, 0.65-0.73; NEWS: AUROC, 0.70; 95% CI, 0.66-0.75).

CONCLUSIONS

NEWS and NEWS+age showed similar test characteristics in an MHS COVID-19 cohort. Notably, low baseline scores had an excellent negative predictive value. Given their easy applicability, these scoring systems may be useful in resource-limited settings to identify COVID-19 patients who are unlikely to progress to critical illness.

Clinical, immunological and virological SARS-CoV-2 phenotypes in obese and non-obese military health system beneficiaries

Background

The mechanisms underlying the association between obesity and coronavirus disease 2019 (COVID-19) severity remain unclear. After verifying that obesity was a correlate of severe COVID-19 in US Military Health System (MHS) beneficiaries, we compared immunological and virological phenotypes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in both obese and nonobese participants.

Methods

COVID-19–infected MHS beneficiaries were enrolled, and anthropometric, clinical, and demographic data were collected. We compared the SARS-CoV-2 peak IgG humoral response and reverse-transcription polymerase chain reaction viral load in obese and nonobese patients, stratified by hospitalization, utilizing logistic regression models.

Results

Data from 511 COVID-19 patients were analyzed, among whom 24% were obese and 14% severely obese. Obesity was independently associated with hospitalization (adjusted odds ratio [aOR], 1.91; 95% confidence interval [CI], 1.15–3.18) and need for oxygen therapy (aOR, 3.39; 95% CI, 1.61–7.11). In outpatients, severely obese had a log₁₀ (1.89) higher nucleocapsid (N1) genome equivalents (GE)/reaction and log₁₀ (2.62) higher N2 GE/reaction than nonobese (P = 0.03 and P < .001, respectively). We noted a correlation between body mass index and peak anti-spike protein IgG in inpatients and outpatients (coefficient = 5.48, P < .001).

Conclusions

Obesity is a strong correlate of COVID-19 severity in MHS beneficiaries. These findings offer new pathophysiological insights into the relationship between obesity and COVID-19 severity.

Influences on catch-up growth using relative versus absolute metrics: evidence from the MAL-ED cohort study

BACKGROUND

Poor growth in early childhood has been considered irreversible after 2-3 years of age and has been associated with morbidity and mortality over the short-term and with poor economic and cognitive outcomes over the long-term. The MAL-ED cohort study was performed in eight low-income settings with the goal of evaluating relationships between the child's environment and experience (dietary, illness, and pathogen exposure, among others) and their growth and development. The goal of this analysis is to determine whether there are differences in the factors associated with growth from 24 to 60 months using two different metrics.

METHODS

Across six MAL-ED sites, 942 children had anthropometry data at 24 and 60 months, as well as information about socioeconomic status, maternal height, gut permeability (lactulose-mannitol z-score (LMZ)), dietary intake from 9 to 24 months, and micronutrient status. Anthropometric changes were in height- or weight-for-age z-score (HAZ, WAZ), their absolute difference from the growth standard median (HAD (cm), WAD (kg)), as well as recovery from stunting/underweight. Outcomes were modeled using multivariate regression.

RESULTS

At 24 months, almost half of the cohort was stunted (45%) and 21% were underweight. Among those who were stunted at 24 months (n = 426), 185 (43%) were no longer stunted at 60 months. Most children increased their HAZ from 24 to 60 months (81%), whereas fewer (33%) had positive changes in their HAD. Linear regression models indicate that girls improved less than boys from 24 to 60 months (HAZ: -0.21 (95% CI -0.27, -0.15); HAD: -0.75 (-1.07, -0.43)). Greater intestinal permeability (higher LMZ) at 0-24 months was associated with lower relative and absolute changes from 24 to 60 months (HAZ: -0.10 (-0.16, -0.04); HAD: -0.47 (-0.73, -0.21)). Maternal height (per 10 cm) was positively associated with changes (HAZ: 0.09 (0.03, 0.15); HAD: 0.45 (0.15, 0.75)). Similar relationships were identified for changes in WAZ and WAD.

CONCLUSIONS

The study children demonstrated improved growth from 24 to 60 months of age, but only a subset had positive changes in HAD and WAD. The same environmental factors were associated with growth from 24 to 60 months regardless of metric used (change in HAZ or HAD, or WAZ and WAD).

Effects of human immunodeficiency virus status on symptom severity in influenza-like illness in an otherwise healthy adult outpatient cohort

The impact of HIV on influenza-like illness (ILI) has been incompletely described in the era of combination antiretroviral therapy, particularly in the post-H1N1 pandemic period. This analysis informs on ILI in an otherwise healthy, predominantly outpatient cohort of adults with HIV in the USA. From September 2010 to March 2015, this multisite observational cohort study enrolled otherwise healthy adults presenting to a participating US military medical center with ILI, a subset of whom were HIV positive. Demographics, clinical data, and self-reported symptom severity were ascertained, and enrollees completed a daily symptom diary for up to 10 days. 510 men were included in the analysis; 50 (9.8%) were HIV positive. Subjects with HIV were older and less likely to be on active duty. Rhinovirus and influenza A were the most commonly identified pathogens. Moderate–severe diarrhea (p<0.001) and fatigue (p=0.01) were more frequently reported by HIV-positive men. HIV positivity was associated with higher gastrointestinal scores, but not other measures of ILI symptom severity, after controlling for age, race, military status, and influenza season. Few were hospitalized. HIV-positive subjects had more influenza B (p=0.04) and were more likely to receive antivirals (32% vs 6%, p<0.01). Antiviral use was not significantly associated with symptom scores when accounting for potential confounders. In this predominantly outpatient cohort of adult men, HIV had minimal impact on ILI symptom severity. Despite similar illness severity, a higher percentage of subjects with HIV reported undergoing antiviral treatment for ILI, likely reflecting differences in prescribing practices.Trial registration number: NCT01021098.

Comparable Disease Severity by Influenza Virus Subtype in the Acute Respiratory Infection Consortium Natural History Study

INTRODUCTION

Since the influenza A/H1N1 pandemic of 2009 to 2010, numerous studies have described the clinical course and outcome of the different subtypes of influenza (A/H1N1, A/H3N2, and B). A recent systematic literature review concluded that there were no appreciable differences in either clinical presentation or disease severity among these subtypes, but study parameters limit the applicability of these results to military populations. We sought to evaluate differences in disease severity among influenza subtypes in a cohort of healthy, primarily outpatient adult U.S. Department of Defense beneficiaries.

MATERIALS AND METHODS

From 2009 to 2014, we enrolled otherwise healthy adults age 18 to 65 years with influenza-like illness in an observational cohort study based in 5 U.S. military medical centers. Serial nasopharyngeal swabs were collected for determination of etiology and viral shedding by polymerase chain reaction. The presence and severity of symptoms was assessed by interview and patient diary.

RESULTS

Over a 5-year period, a total of 157 adults with laboratory-confirmed influenza and influenza subtype were enrolled. Of these, 69 (44%) were positive for influenza A(H1N1), 69 (44%) for influenza A(H3N2), and 19 (12%) for influenza B. About 61% were male, 64% were active duty military personnel, and 72% had received influenza vaccine in the past 8 months. Almost 10% were hospitalized with influenza. Seasonal influenza virus distribution among enrollees mirrored that of nationwide trends each year of study. Individuals with A/H1N1 had upper respiratory composite scores that were lower than those with A/H3N2. Multivariate models indicated that individuals with A(H1N1) and B had increased lower respiratory symptom scores when compared to influenza A(H3N2) (A[H1N1]: 1.51 [95% CI 0.47, 2.55]; B: 1.46 [95% CI 0.09, 2.83]), whereas no other differences in symptom severity scores among influenza A(H1N1), influenza A(H3N2), and influenza B infection were observed. Overall, influenza season (maximum in 2012-2013 season) and female sex of the participant were found to be associated with increased influenza symptom severity.

CONCLUSIONS

Our study of influenza in a cohort of otherwise healthy, outpatient adult Department of Defense beneficiaries over 5 influenza seasons revealed few differences between influenza A(H1N1), influenza A(H3N2), and influenza B infection with respect to self-reported disease severity or clinical outcomes. This study highlights the importance of routine, active, and laboratory-based surveillance to monitor ongoing trends and severity of influenza in various populations to inform prevention measures.

Characteristics associated with the transition to partial breastfeeding prior to 6 months of age: Data from seven sites in a birth cohort study

The WHO recommends exclusive breastfeeding for the first 6 months of life. However, the transition of the infants' diet to partial breastfeeding with the addition of animal milks and/or solids typically occurs earlier than this. Here, we explored factors associated with the timing of an early transition to partial breastfeeding across seven sites of a birth cohort study in which twice weekly information on infant feeding practices was collected. Infant (size, sex, illness and temperament), maternal (age, education, parity and depressive symptoms), breastfeeding initiation practices (time of initiation, colostrum and pre‐lacteal feeding) and household factors (food security, crowding, assets, income and resources) were considered. Three consecutive caregiver reports of feeding animal milks and/or solids (over a 10‐day period) were characterized as a transition to partial breastfeeding, and Cox proportional hazard models with time (in days) to partial breastfeeding were used to evaluate associations with both fixed and time‐varying characteristics. Overall, 1470 infants were included in this analysis. Median age of transition to partial breastfeeding ranged from 59 days (South Africa and Tanzania) to 178 days (Bangladesh). Overall, higher weight‐for‐length z‐scores were associated with later transitions to partial breastfeeding, as were food insecurity, and infant cough in the past 30 days. Maternal depressive symptoms (evaluated amongst 1227 infants from six sites) were associated with an earlier transition to partial breastfeeding. Relative thinness or heaviness within each site was related to breastfeeding transitions, as opposed to absolute z‐scores. Further research is needed to understand relationships between local perceptions of infant body size and decisions about breastfeeding.

Antigen-based multiplex strategies to discriminate SARS-CoV-2 natural and vaccine induced immunity from seasonal human coronavirus humoral responses

Sensitive and specific SARS-CoV-2 antibody assays remain critical for community and hospital-based SARS-CoV-2 sero-surveillance. With the rollout of SARS-CoV-2 vaccines, such assays must be able to distinguish vaccine from natural immunity to SARS-CoV-2 and related human coronaviruses. Here, we developed and implemented multiplex microsphere-based immunoassay strategies for COVD-19 antibody studies that incorporates spike protein trimers of SARS-CoV-2 and the endemic seasonal human coronaviruses (HCoV), enabling high throughout measurement of pre-existing cross-reactive antibodies. We varied SARS-CoV-2 antigen compositions within the multiplex assay, allowing direct comparisons of the effects of spike protein, receptor-binding domain protein (RBD) and nucleocapsid protein (NP) based SARS-CoV-2 antibody detection. Multiplex immunoassay performance characteristics are antigen-dependent, and sensitivities and specificities range 92-99% and 94-100%, respectively, for human subject samples collected as early as 7-10 days from symptom onset. SARS-CoV-2 spike and RBD had a strong correlative relationship for the detection of IgG. Correlation between detectable IgG reactive with spike and NP also had strong relationship, however, several PCR-positive and spike IgG-positive serum samples were NP IgG-negative. This spike and NP multiplex immunoassay has the potential to be useful for differentiation between vaccination and natural infection induced antibody responses. We also assessed the induction of de novo SARS-CoV-2 IgG cross reactions with SARS-CoV and MERS-CoV spike proteins. Furthermore, multiplex immunoassays that incorporate spike proteins of SARS-CoV-2 and HCoVs will permit investigations into the influence of HCoV antibodies on COVID-19 clinical outcomes and SARS-CoV-2 antibody durability.

SARS-CoV-2 Infections and Serologic Responses Among Military Personnel Deployed on the USNS COMFORT to New York City During the COVID-19 Pandemic

BACKGROUND

Coronavirus disease 2019 (COVID-19) presents a unique challenge to United States Navy hospital ships. The aim of this study was to determine the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among US Navy personnel deployed on the USNS COMFORT to augment the inpatient health care capacity in New York City.

METHODS

This was a cross-sectional study conducted on USNS COMFORT crewmembers returning to Norfolk, Virginia, following deployment. Participants completed an electronic questionnaire and provided a serum sample at Day 14 post-deployment. Polymerase chain reaction (PCR) results from testing of symptomatic crewmembers during deployment and Day 0 and Day 14 post-deployment screening swabs conducted on all crewmembers, per military order, were abstracted. SARS-CoV-2 infection was defined as a positive SARS-CoV-2 spike glycoprotein immunoglobulin G antibody or PCR result.

RESULTS

Of the ship's total complement of 1200 crewmembers, 450 were enrolled: 432 (96.0%) completed the questionnaire and provided a serum sample. The median age of participants (interquartile range) was 30 (24-39) years, 50.8% were female, 58.6% were White, and 14.0% were Black; 80.1% had a clinical role during deployment. The cumulative prevalence of SARS-CoV-2 infection was 3.01% (13/432; 95% CI, 1.61%-5.09%). Twelve of 13 infections occurred in health care providers, and 8 of 13 were asymptomatic. The antibody profile of infected crewmembers varied by suspected timing of infection.

CONCLUSIONS

We observed a low prevalence of SARS-CoV-2 infection among USNS COMFORT crewmembers despite the inherent risk of a shipboard deployment to an area with high rates of community transmission. Our findings suggest that early infection control measures mitigated the spread of SARS-CoV-2 among crewmembers.

1512. Influenza vaccine effectiveness wanes over the influenza season: results from five military treatment facilities

Background

Influenza vaccination can reduce influenza burden, but questions have arisen about the duration of vaccine protection. While the timing of vaccination varies, annual receipt of influenza vaccine is mandated for active duty military personnel. The goal of this analysis is to determine if influenza vaccine effectiveness decreases over time. A secondary goal of this analysis is to determine if repeated influenza vaccination is associated with risk for influenza.

Methods

Otherwise healthy individuals presenting for treatment of acute respiratory infections at 5 military treatment facilities from 2009 to 2018 were enrolled in the Acute Respiratory Infection Consortium (ARIC) study. Individuals with complete demographics, influenza vaccination in the two years prior to illness, and influenza laboratory results were included in this analysis (n=1,273). Multivariate logistic regression was used to calculate the odds of an influenza diagnosis according to time since influenza vaccination, categorized in 90-day periods. The model also included age, race, month of diagnosis, influenza season, and whether the participant received 4+ influenza vaccinations in the past 5 years.

Results

One hundred and ninety-two individuals (15%) had laboratory confirmed influenza (Table 1). Participants were mostly active duty, male, and white. Over half of the participants received 4+ influenza vaccinations in the past 5 years. Participants who were vaccinated 90-179 and 180+ days ago had greater odds of being diagnosed with influenza than did individuals who were vaccinated &lt; 90 days prior to illness onset (Table 2). Participants who were 18-24 years old had lower odds of influenza than individuals in other age groups. Vaccine experience (vaccinated against influenza for at least four of the past five years), race, and ethnicity were not statistically significantly associated with influenza diagnosis.

Table 1. Characteristics of individuals included in the analysis of waning influenza vaccine effectiveness in the ARIC study

Conclusion

Influenza vaccination was most effective 14-89 days post-vaccination and effectiveness decreased thereafter. Repeat influenza vaccination, however, was not significantly associated with greater odds of influenza. The waning effectiveness of influenza vaccination indicates additional consideration be given to the timing of vaccination.

Disclaimer

Disclosures

All Authors: No reported disclosures

1501. Pragmatic Assessment of Influenza Vaccine Effectiveness in the DoD (PAIVED): Updates from Year 2 of multi-site trial

Background

Despite nearly universal influenza vaccination for active duty military personnel, breakthrough influenza infections occur. We are reporting on the second year of the Pragmatic Assessment of Influenza Vaccine Effectiveness in the DoD (PAIVED), comparing three FDA-licensed influenza vaccine types (egg-based, cell -based, and recombinant) to assess differences in immunogenicity and effectiveness.

Methods

Participants in the second year of PAIVED were enrolled from Oct 2019 through Jan 2020 at 9 military facilities. Participants received weekly inquiries about influenza-like-illnesses (ILI) experienced in the past week, and if the participant reported having a cough or sore throat and a) muscle/body aches or fatigue and/or b) being feverish or having chills, they were scheduled for a clinic visit. During this visit, a blood sample and a nasal swab were collected, as well as information about symptom duration and severity. A second (convalescent) visit was conducted approximately 4 weeks later, which involved collecting additional information about the duration of symptoms and illness burden, as well as a second blood draw. Due to the COVID-19 pandemic, acute and convalescent visits were disrupted at most sites in March and April due to COVID-19 precautions.

Results

PAIVED year 2 enrolled 5,892 participants who completed demographic forms (Table 1). Among those who reported any ILIs, most reported one ILI (1,345), while 264 reported two ILIs, and 42 reported three ILIs. Nasal swabs were processed from 273 ILIs at four sites (Fig 1), and 14 cases of influenza were identified thus far. The median duration of ILIs was ten days, with a median of three days of limited activity, and two days with fever. Nine individuals were hospitalized.

Table 1. Demographic characteristics of individuals enrolled in PAIVED 2019/20

Figure 1. Lab results as of 5/15 (N=273 samples)

Conclusion

Over 25% of participants reported an ILI, and 5% of the nasal swabs that have been tested thus far have been positive for influenza. While most samples have not yet been analyzed, we have identified some breakthrough cases of influenza among vaccinated participants. Planned analyses include comparative vaccine effectiveness in order to inform future vaccine purchasing decisions.

Disclaimer

Disclosures

All Authors: No reported disclosures

Introducing a drift and diffusion framework for childhood growth research

Background: Growth trajectories are highly variable between children, making epidemiological analyses challenging both to the identification of malnutrition interventions at the population level and also risk assessment at individual level. We introduce stochastic differential equation (SDE) models into child growth research. SDEs describe flexible dynamic processes comprising: drift - gradual smooth changes - such as physiology or gut microbiome, and diffusion - sudden perturbations, such as illness or infection. Methods: We present a case study applying SDE models to child growth trajectory data from the Haydom, Tanzania and Venda, South Africa sites within the MAL-ED cohort. These data comprise n=460 children aged 0-24 months. A comparison with classical curve fitting (linear mixed models) is also presented. Results: The SDE models offered a wide range of new flexible shapes and parameterizations compared to classical additive models, with performance as good or better than standard approaches. The predictions from the SDE models suggest distinct longitudinal clusters that form distinct 'streams' hidden by the large between-child variability. Conclusions: Using SDE models to predict future growth trajectories revealed new insights in the observed data, where trajectories appear to cluster together in bands, which may have a future risk assessment application. SDEs offer an attractive approach for child growth modelling and potentially offer new insights.

A betacoronavirus multiplex microsphere immunoassay detects early SARS-CoV-2 seroconversion and controls for pre-existing seasonal human coronavirus antibody cross-reactivity

With growing concern of persistent or multiple waves of SARS-CoV-2 in the United States, sensitive and specific SARS-CoV-2 antibody assays remain critical for community and hospital-based SARS-CoV-2 surveillance. Here, we describe the development and application of a multiplex microsphere-based immunoassay (MMIA) for COVD-19 antibody studies, utilizing serum samples from non-human primate SARS-CoV-2 infection models, an archived human sera bank and subjects enrolled at five U.S. military hospitals. The MMIA incorporates prefusion stabilized spike glycoprotein trimers of SARS-CoV-2, SARS-CoV-1, MERS-CoV, and the seasonal human coronaviruses HCoV-HKU1 and HCoV-OC43, into a multiplexing system that enables simultaneous measurement of off-target pre-existing cross-reactive antibodies. We report the sensitivity and specificity performances for this assay strategy at 98% sensitivity and 100% specificity for subject samples collected as early as 10 days after the onset of symptoms. In archival sera collected prior to 2019 and serum samples from subjects PCR negative for SARS-CoV-2, we detected seroprevalence of 72% and 98% for HCoV-HKU1 and HCoV-0C43, respectively. Requiring only 1.25 μL of sera, this approach permitted the simultaneous identification of SARS-CoV-2 seroconversion and polyclonal SARS-CoV-2 IgG antibody responses to SARS-CoV-1 and MERS-CoV, further demonstrating the presence of conserved epitopes in the spike glycoprotein of zoonotic betacoronaviruses. Application of this serology assay in observational studies with serum samples collected from subjects before and after SARS-CoV-2 infection will permit an investigation of the influences of HCoV-induced antibodies on COVID-19 clinical outcomes.

A betacoronavirus multiplex microsphere immunoassay detects early SARS-CoV-2 seroconversion and controls for pre-existing seasonal human coronavirus antibody cross-reactivity

With growing concern of persistent or multiple waves of SARS-CoV-2 in the United States, sensitive and specific SARS-CoV-2 antibody assays remain critical for community and hospital-based SARS-CoV-2 surveillance. Here, we describe the development and application of a multiplex microsphere-based immunoassay (MMIA) for COVD-19 antibody studies, utilizing serum samples from non-human primate SARS-CoV-2 infection models, an archived human sera bank and subjects enrolled at five U.S. military hospitals. The MMIA incorporates prefusion stabilized spike glycoprotein trimers of SARS-CoV-2, SARS-CoV-1, MERS-CoV, and the seasonal human coronaviruses HCoV-HKU1 and HCoV-OC43, into a multiplexing system that enables simultaneous measurement of off-target pre-existing cross-reactive antibodies. We report the sensitivity and specificity performances for this assay strategy at 98% sensitivity and 100% specificity for subject samples collected as early as 10 days after the onset of symptoms. In archival sera collected prior to 2019 and serum samples from subjects PCR negative for SARS-CoV-2, we detected seroprevalence of 72% and 98% for HCoV-HKU1 and HCoV-0C43, respectively. Requiring only 1.25 uL of sera, this approach permitted the simultaneous identification of SARS-CoV-2 seroconversion and polyclonal SARS-CoV-2 IgG antibody responses to SARS-CoV-1 and MERS-CoV, further demonstrating the presence of conserved epitopes in the spike glycoprotein of zoonotic betacoronaviruses. Application of this serology assay in observational studies with serum samples collected from subjects before and after SARS-CoV-2 infection will permit an investigation of the influences of HCoV-induced antibodies on COVID-19 clinical outcomes.