Evaluating biomedical feature fusion on machine learning's predictability and interpretability of COVID-19 severity types (preprint)

BackgroundAccurately differentiating severe from non-severe COVID-19 clinical types is critical for the healthcare system to optimize workflow, as severe patients require intensive care. Current techniques lack the ability to accurately predict COVID-19 patients clinical type, especially as SARS-CoV-2 continues to mutate. ObjectiveIn this work, we explore both predictability and interpretability of multiple state-of-the-art machine learning (ML) techniques trained and tested under different biomedical data types and COVID-19 variants. MethodsComprehensive patient-level data were collected from 362 patients (214 severe, 148 non-severe) with the original SARS-CoV-2 variant in 2020 and 1000 patients (500 severe, 500 non-severe) with the Omicron variant in 2022-2023. The data included 26 biochemical features from blood testing and 26 clinical features from each patients clinical characteristics and medical history. Different types of ML techniques, including penalized logistic regression (LR), random forest (RF), k-nearest neighbors (kNN), and support vector machines (SVM) were applied to build predictive models based on each data modality separately and together for each variant set. ResultsAll ML models performed similarly under different testing scenarios. The fused characteristic modality yielded the highest area under the curve (AUC) score achieving 0.914 on average. The second highest AUC was 0.876 achieved by the biochemical modality alone, followed by 0.825 achieved by clinical modality alone. All ML models were robust when cross-tested with original and Omicron variant patient data. Upon model interpretation, our models ranked elevated d-dimer (biochemical feature), elevated high sensitivity troponin I (biochemical feature), and age greater than 55 years (clinical feature) as the most predictive features of severe COVID-19. ConclusionsWe found ML to be a powerful tool for predicting severe COVID-19 based on comprehensive individual patient-level data. Further, ML models trained on the biochemical and clinical modalities together witness enhanced predictive power. The improved performance of these ML models when trained and cross-tested with Omicron variant data supports the robustness of ML as a tool for clinical decision support.

Quantitative summarization of High-touch Fomites for Healthcare Associated Infection (HAI) Risks: a systematic review (preprint)

Background Nearly 700,000 people in the U.S. acquire healthcare associated infections (HAIs) annually, and the situation might have worsened during the COVID-19 pandemic. Evidence has shown that fomites, such as environmental surfaces and medical devices, play a critical role in the transmission of HAI. Our study systematically reviews findings from studies that provided quantitative evidence on the contact pattern and/or rank of high-touch surfaces (HTS). Methods We systematically searched 4 major databases (PubMed, Web of Science, CINAHL and Cochrane Database) for articles published before June 30, 2023 based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines (international prospective register of systematic reviews registration CRD42023408483). Relevant search terms we used, including Fomites AND Contact Pattern (eg high-touch OR mutual-touch) AND Healthcare Setting (eg ICU OR Emergency Department) AND HAI (eg Clostridiodes difficile). We also searched for relevant articles in the reference list. Result A total of 2,826 studies were screened across all four databases with 7 studies meeting the eligibility criteria. The fomite which was most frequently touched was the bed rail. Frequently touched surfaces are supply carts, bed surfaces, patient files/notes, medication carts, bedside tables, and Intravenous pump. Other frequently contacted fomites were vital sign monitors, phones, curtains, computer/computer keyboards, chair and sink surfaces, blood pressure cuffs, computer mouse and light switch. Common mutually touched fomites were bedside rail, patients’ body, patient file, bedside table and hand washing faucet handles. Only 2 studies utilized a covert observational technique, the other 5 applied either direct observation or did not state explicitly. Conclusion Our study provides empirical data which is important for the prioritization in cleaning and disinfection practices, development of HAI prevention and control protocols, and the optimization of cleaning and disinfection resources. We suggest that more rigorous studies quantifying high-touch fomites, especially those including detailed contact duration, sequence and temporal variations, be conducted.

Potential impact of annual vaccination with reformulated COVID-19 vaccines: lessons from the U.S. COVID-19 Scenario Modeling Hub (preprint)

ImportanceCOVID-19 continues to cause significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear. ObjectiveTo project COVID-19 hospitalizations and deaths from April 2023-April 2025 under two plausible assumptions about immune escape (20% per year and 50% per year) and three possible CDC recommendations for the use of annually reformulated vaccines (no vaccine recommendation, vaccination for those aged 65+, vaccination for all eligible groups). DesignThe COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023-April 15, 2025 under six scenarios representing the intersection of considered levels of immune escape and vaccination. State and national projections from eight modeling teams were ensembled to produce projections for each scenario. SettingThe entire United States. ParticipantsNone. ExposureAnnually reformulated vaccines assumed to be 65% effective against strains circulating on June 15 of each year and to become available on September 1. Age and state specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster. Main outcomes and measuresEnsemble estimates of weekly and cumulative COVID-19 hospitalizations and deaths. Expected relative and absolute reductions in hospitalizations and deaths due to vaccination over the projection period. ResultsFrom April 15, 2023-April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November-January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% PI: 1,438,000-4,270,000) hospitalizations and 209,000 (90% PI: 139,000-461,000) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% CI: 104,000-355,000) fewer hospitalizations and 33,000 (95% CI: 12,000-54,000) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000-598,000) fewer hospitalizations and 49,000 (95% CI: 29,000-69,000) fewer deaths. Conclusion and RelevanceCOVID-19 is projected to be a significant public health threat over the coming two years. Broad vaccination has the potential to substantially reduce the burden of this disease. Key pointsO_ST_ABSQuestionC_ST_ABSWhat is the likely impact of COVID-19 from April 2023-April 2025 and to what extent can vaccination reduce hospitalizations and deaths? FindingsUnder plausible assumptions about viral evolution and waning immunity, COVID-19 will likely cause annual epidemics peaking in November-January over the two-year projection period. Though significant, hospitalizations and deaths are unlikely to reach levels seen in previous winters. The projected health impacts of COVID-19 are reduced by 10-20% through moderate use of reformulated vaccines. MeaningCOVID-19 is projected to remain a significant public health threat. Annual vaccination can reduce morbidity, mortality, and strain on health systems.

Informing pandemic response in the face of uncertainty. An evaluation of the U.S. COVID-19 Scenario Modeling Hub (preprint)

Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible under defined scenarios that specify the future state of critical epidemic drivers, with the additional benefit that such scenarios can be used to anticipate the comparative effect of control measures. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make 6-month ahead projections of the number of SARS-CoV-2 cases, hospitalizations and deaths. The SMH released nearly 1.8 million national and state-level projections between February 2021 and November 2022. SMH performance varied widely as a function of both scenario validity and model calibration. Scenario assumptions were periodically invalidated by the arrival of unanticipated SARS-CoV-2 variants, but SMH still provided projections on average 22 weeks before changes in assumptions (such as virus transmissibility) invalidated scenarios and their corresponding projections. During these periods, before emergence of a novel variant, a linear opinion pool ensemble of contributed models was consistently more reliable than any single model, and projection interval coverage was near target levels for the most plausible scenarios (e.g., 79% coverage for 95% projection interval). SMH projections were used operationally to guide planning and policy at different stages of the pandemic, illustrating the value of the hub approach for long-term scenario projections.

Infoveillance study on the dynamic associations between CDC social media contents and epidemic measures during COVID-19 (preprint)

Background: Health agencies have been widely adopting social media to disseminate important information, educate the public on emerging health issues, and understand public opinions. The Centers for Disease Control and Prevention (CDC) has been one of the leading agencies that utilizes social media platforms during the COVID-19 pandemic to communicate with the public and mitigate the disease in the United States. It is crucial to understand the relationships between CDC's social media communication and the actual epidemic metrics to improve public health agencies' communication strategies during health emergencies. Objective: The aim of this study was to identify key topics in tweets posted by CDC during the pandemic, to investigate the temporal dynamics between these key topics and the actual COVID-19 epidemic measures, and to make recommendations for CDC's digital health communication strategies for future health emergencies. Methods: Two types of data were collected: 1) a total of 17,524 COVID-19-related English tweets posted by the CDC between December 7, 2019 and January 15, 2022; 2) COVID-19 epidemic measures in the U.S. from the public GitHub repository of Johns Hopkins University from January 2020 to July 2022. Latent Dirichlet allocation (LDA) topic modeling was applied to identify key topics from all COVID-19-related tweets posted by CDC, and the final topics were determined by domain experts. Various multivariate time series analysis techniques were applied between each of the identified key topics and actual COVID-19 epidemic measures to quantify the dynamic associations between these two types of time series data. Results: Four major topics from CDC's COVID-19 tweets were identified: 1) information on prevention of health outcomes of COVID-19; 2) pediatric intervention and family safety; 3) updates of the epidemic situation of COVID-19; 4) research and community engagement to curb COVID-19. Multivariate analyses showed that there were significant variabilities of progression between CDC's topics and the actual COVID-19 epidemic measures. Some CDC's topics showed substantial associations with the COVID-19 measures over different time spans throughout the pandemic, expressing similar temporal dynamics between these two types of time series data. Conclusions: Our study is the first to comprehensively investigate the dynamic associations between topics discussed by CDC on Twitter and the COVID-19 epidemic measures in the U.S. We identified four major topic themes via topic modeling and explored how each of these topics was associated with each major epidemic measure by performing various multivariate time series analyses. We recommend that it is critical for public health agencies, such as CDC, to disseminate and update timely and accurate information to the public and align major topics with the key epidemic measures over time. We suggest that social media can help public health agencies to inform the public on health emergencies and to mitigate them effectively.

The real-world effectiveness of an intranasal spray A8G6 antibody cocktail in the post-exposure prophylaxis of COVID-19 (preprint)

BackgroundDue to the continuous appearance of novel SARS-CoV-2 variants that are resistant to approved antibodies and leading to the epidemic rebound, several approved neutralizing antibodies have been paused for their usage against COVID-19. Previously, we identified A8G6, an antibody combination of two synergic SARS-CoV-2 neutralizing antibodies 55A8 and 58G6, that showed broad neutralizing activities against Omicron variants. When administrated by the nasal spray delivery system, A8G6 showed promising efficacy in COVID-19 animal models and also showed favorable safety profile in preclinical models as well as in a first-in-human trial. The aim of this study is to evaluate the real-world efficacy of A8G6 neutralizing antibody nasal spray in post-exposure prevention of COVID-19. MethodsFrom November 27, 2022 to January 31, 2023, an open-label, non-randomized, two-arm, blank-controlled, investigator-initiated trial was conducted in Chongqing, China. High-risk healthy participants (18-65 years) within 72 hours after close contact to SARS-CoV-2 infected individuals were recruited and received a three-dose (1.4 mg/dose) A8G6 nasal spray treatment daily or no treatment (blank control) for 7 consecutive days. The primary end points were 1) the occurrence of positive SARS-CoV-2 RT-PCR cases in A8G6 treated group vs blank control group at the end of day 7; 2) time to SARS-CoV-2 positive conversion at the end of day 7. The secondary end points were 1) viral load of SARS-CoV-2 when participants became SARS-CoV-2 positive; 2) the time from SARS-CoV-2 infection to negative COVID-19 conversion. Safety end point of the nasal spray AG86 was analyzed by recording adverse events during the whole course of this trial. This study was registered with Chictr.org (ChiCTR2200066416). FindingsOf 513 enrolled participants, 173 in the A8G6 treatment group and 340 in the blank-control group were included in the analysis. SARS-CoV-2 infection occurred in 151/340 (44.4%) subjects in the blank control group and 12/173 (6.9%) subjects with the A8G6 treatment group. The result indicates that the intranasal spray A8G6 reduces the risk of SARS-CoV-2 infection (HR=0.12, 95% CI, 0.07-0.22; p<0.001). The prevention efficacy of the A8G6 treatment within 72-hours exposure was calculated to be 84.4% (95% CI: 74.4%-90.4%). Moreover, compared to the blank-control group, the time from the SARS-CoV-2 negative to the positive COVID-19 conversion was significantly longer in the AG86 treatment group (mean time: 3.4 days in the A8G6 treatment group vs 2.6 days in the control group, p=0.019). In the secondary end-point analysis, the A8G6 nasal treatment had no effects on the viral load at baseline SARS-CoV-2 RT-PCR positivity and the time of the negative COVID-19 conversion (viral clearance). Finally, 5 participants (3.1%) in the treatment group reported general adverse effects. We did not observe any severe adverse effects related to the A8G6 treatment in this study. InterpretationIn this study, the intranasal spray AG86 antibody cocktail showed potent efficacy for prevention of SARS-CoV-2 infection in close contacts of COVID-19 patients. FundingChongqing Biomedical R&D Major Special Project, Project (No. CSTB2022TIAD-STX0013), Chongqing Science and Health Joint Medical High-end Talent Project (No. 2022GDRC012), Science and Technology Research Program of Chongqing Municipal Education Commission (No. KJZD-K202100402), CQMU Program for Youth Innovation in Future Medicine (No. W0073). Research in contextO_ST_ABSEvidence before the studyC_ST_ABSTwo potent neutralizing antibodies 55A8 and 58G6 against SARS-CoV-2 were identified from the plasma of COVID-19 convalescent patients. In our previous studies, the synergetic neutralization of the antibody combination of 55A8 and 58G6 (A8G6) had been shown in structural mechanism, as well as in vitro and in vivo. Pre-clinical evaluation of A8G6 nasal spray showed promising efficacy against Omicron BA.4/5 infection in golden syrian hamsters challenged with live virus. In a first-in-human trial, A8G6 also showed favorable safety profile and nasal concentration over IC90 of neutralization activity against Omicron BA.4/5. The preliminary data showed that the intranasal spray A8G6 had the excellent efficacy, safety and druggability to protect against COVID-19. Added value of this studyThis is the first human trial showing that a nasal spray of neutralizing antibody cocktail is efficacious in preventing SARS-CoV-2 infection but is not efficacious in the post-infection treatment of COVID-19. In the Omicron wave of the COVID-19 pandemic in China in November, 2022, COVID-19 close contacts receiving the A8G6 treatment in the designated quarantine hotels showed a significantly lower incidence of SARS-CoV-2 infection. Additionally, the A8G6 treatment delayed time from exposure to the diagnosis of the COVID-19 positivity (median time: 3.4 days in the treatment group vs 2.6 days in the control group). Furthermore, we analyzed the effects of the A8G6 treatment on the clinical status of close contacts who became infected with SARS-CoV-2. Results suggests that there were no significant differences in viral load of SARS-CoV-2 at the beginning of positive infection and the time of the viral clearance between A8G6 treatment and blank control groups. Overall, the trial result is consistent with the mechanism of action of nasal spray antibody cocktail for the prevention of SARS-CoV-2 infection. Finally, low safety risk of the nasal spray A8G6 was also shown in the trial. Implications of all the available evidenceWe observed the use of A8G6 to reduce the risk of SARS-CoV-2 infection. This study provided supporting evidences for the real-world effectiveness and safety of the nasal spray A8G6 among high-risk close contacts in the post-exposure prevention of COVID-19 during the Omicron BA.5.2 wave in China. This is the first proof of concept of using nasal spray neutralizing antibody for the prevention of viral infection. It implicates that the promising efficacy of the nasal spray A8G6 makes it possible for the fast-acting prevention in future COVID-19 waves.

Safety and immunogenicity of a broad-spectrum mosaic vaccine as a booster dose against SARS-CoV-2 Omicron and other circulating variants (preprint)

BACKGROUNDThe rising breakthrough infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, especially Omicron and its sub-lineages, have raised an urgent need to develop broad-spectrum vaccines against coronavirus disease 2019 (COVID-19). We have developed a mosaic-type recombinant vaccine candidate, named NVSI-06-09, having immune potentials against a broad range of SARS-CoV-2 variants. METHODSAn ongoing randomized, double-blind, controlled phase 2 trial was conducted to evaluate the safety and immunogenicity of NVSI-06-09 as a booster dose in subjects aged 18 years and older from the United Arab Emirates (UAE), who had completed two or three doses of BBIBP-CorV vaccinations at least 6 months prior to the enrollment. The participants were randomly assigned with 1:1 to receive a booster dose of NVSI-06-09 or BBIBP-CorV. The primary outcomes were immunogenicity and safety against SARS-CoV-2 Omicron variant, and the exploratory outcome was cross-immunogenicity against other circulating strains. RESULTSA total of 516 participants received booster vaccination. Interim results showed a similar safety profile between NVSI-06-09 and BBIBP-CorV booster groups, with low incidence of adverse reactions of grade 1 or 2. For immunogenicity, by day 14 after the booster vaccination, the fold rises in neutralizing antibody geometric mean titers (GMTs) from baseline level elicited by NVSI-06-09 were remarkably higher than those by BBIBP-CorV against the prototype strain (19.67 vs 4.47-fold), Omicron BA.1.1 (42.35 vs 3.78-fold), BA.2 (25.09 vs 2.91-fold), BA.4 (22.42 vs 2.69-fold), and BA.5 variants (27.06 vs 4.73-fold). Similarly, the neutralizing GMTs boosted by NVSI-06-09 against Beta and Delta variants were also 6.60-fold and 7.17-fold higher than those boosted by BBIBP-CorV. CONCLUSIONSA booster dose of NVSI-06-09 was well-tolerated and elicited broad-spectrum neutralizing responses against SARS-CoV-2 prototype strain and immune-evasive variants, including Omicron and its sub-lineages. The immunogenicity of NVSI-06-09 as a booster vaccine was superior to that of BBIBP-CorV. (Funded by LIBP and BIBP of Sinopharm; ClinicalTrials.gov number, NCT05293548).

COVID-19 Endemic Plan: Impact of Vaccination and Non-pharmaceutical Interventions with Viral Variants and Waning Immunity Using an Agent-Based Simulation (preprint)

Backgrounds: Despite the widespread distribution of SARS-CoV-2 vaccines, the COVID-19 pandemic continues with highly contagious variants and waning immunity. Low disease severity of the Omicron variant gives society hope that the COVID-19 pandemic could end. Methods: We develop an agent-based simulation to explore the impact of COVID-19 vaccine willingness, booster vaccination schedule, vaccine effectiveness, and non-pharmaceutical interventions (NPIs) on reducing COVID-19 deaths while considering immunity duration and disease severity against the Omicron variant. The model is calibrated to the greater Seattle area in year 2020 by observing local epidemic data. The simulation is run to the end of year 2024 to observe long-term effects. Results: Results show that an NPI policy that maintains low levels of NPIs can reduce mortality by 35.1% compared to fully opening the society. A threshold NPI policy is especially helpful when the disease severity of the Omicron variant is high, or booster vaccines are not scheduled. A periodic booster schedule is needed to achieve the goal of lowering the number of deaths from COVID-19 to the level of influenza and pneumonia. Except for one scenario, 80% or more vaccine willingness is also needed to achieve this goal. Conclusions: We find that a periodic booster vaccination schedule and mild disease severity of the Omicron variant play a crucial role in reducing deaths by the end of year 2024. If a booster schedule is not planned and the Omicron variant is not mild, NPI policies that limit society from fully opening are required to control the outbreak.

Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: a multi-model study (preprint)

Background: SARS-CoV-2 vaccination of persons aged 12 years and older has reduced disease burden in the United States. The COVID-19 Scenario Modeling Hub convened multiple modeling teams in September 2021 to project the impact of expanding vaccine administration to children 5-11 years old on anticipated COVID-19 burden and resilience against variant strains. Methods: Nine modeling teams contributed state- and national-level projections for weekly counts of cases, hospitalizations, and deaths in the United States for the period September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of: 1) presence vs. absence of vaccination of children ages 5-11 years starting on November 1, 2021; and 2) continued dominance of the Delta variant vs. emergence of a hypothetical more transmissible variant on November 15, 2021. Individual team projections were combined using linear pooling. The effect of childhood vaccination on overall and age-specific outcomes was estimated by meta-analysis approaches. Findings: Absent a new variant, COVID-19 cases, hospitalizations, and deaths among all ages were projected to decrease nationally through mid-March 2022. Under a set of specific assumptions, models projected that vaccination of children 5-11 years old was associated with reductions in all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios where children were not vaccinated. This projected effect of vaccinating children 5-11 years old increased in the presence of a more transmissible variant, assuming no change in vaccine effectiveness by variant. Larger relative reductions in cumulative cases, hospitalizations, and deaths were observed for children than for the entire U.S. population. Substantial state-level variation was projected in epidemic trajectories, vaccine benefits, and variant impacts. Conclusions: Results from this multi-model aggregation study suggest that, under a specific set of scenario assumptions, expanding vaccination to children 5-11 years old would provide measurable direct benefits to this age group and indirect benefits to the all-age U.S. population, including resilience to more transmissible variants.

Progress of study on biology, epidemiology and prevention strategies for SARS-CoV-2 lambda variant

The emergence of SARS-COV-2 caused the global pandemic crisis.As the pandemic evolves, the mutation of novel coronavirus genome continues, resulting in several novel coronavirus variants. For example, Alpha (B.1.1.7), Beta (B.1.351), Gamma (p.1), Delta (B.1.617.2) and Lambda (C.37) variants may cause changes in biological characteristics of the virus, such as pathogenicity and infectivity, which may lead immune escape from vaccine protection and antibodies, even bring greater harm to epidemic prevention and control and also disease treatment. In this paper, the pandemic characteristics and relevant prevention and control measures of lambda variant are reviewed.

Projected resurgence of COVID-19 in the United States in July-December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination (preprint)

What is already known about this topic?The highly transmissible SARS-CoV-2 Delta variant has begun to cause increases in cases, hospitalizations, and deaths in parts of the United States. With slowed vaccination uptake, this novel variant is expected to increase the risk of pandemic resurgence in the US in July--December 2021. What is added by this report?Data from nine mechanistic models project substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant. These resurgences, which have now been observed in most states, were projected to occur across most of the US, coinciding with school and business reopening. Reaching higher vaccine coverage in July--December 2021 reduces the size and duration of the projected resurgence substantially. The expected impact of the outbreak is largely concentrated in a subset of states with lower vaccination coverage. What are the implications for public health practice?Renewed efforts to increase vaccination uptake are critical to limiting transmission and disease, particularly in states with lower current vaccination coverage. Reaching higher vaccination goals in the coming months can potentially avert 1.5 million cases and 21,000 deaths and improve the ability to safely resume social contacts, and educational and business activities. Continued or renewed non-pharmaceutical interventions, including masking, can also help limit transmission, particularly as schools and businesses reopen.

Structure and computation-guided design of a mutation-integrated trimeric RBD candidate vaccine with broad neutralization against SARS-CoV-2 (preprint)

The spike (S) protein receptor-binding domain (RBD) of SARS-CoV-2 is an attractive target for COVID-19 vaccine developments, which naturally exists in a trimeric form. Here, guided by structural and computational analyses, we present a mutation-integrated trimeric form of RBD (mutI tri-RBD) as a broadly protective vaccine candidate, in which three RBDs were individually grafted from three different circulating SARS-CoV-2 strains including the prototype, Beta (B.1.351) and Kappa (B.1.617). The three RBDs were then connected end-to-end and co-assembled to possibly mimic the native trimeric arrangements in the natural S protein trimer. The recombinant expression of the mutI tri-RBD, as well as the homo-tri-RBD where the three RBDs were all truncated from the prototype strain, by mammalian cell exhibited correct folding, strong bio-activities, and high stability. The immunization of both the mutI tri-RBD and homo-tri-RBD plus aluminum adjuvant induced high levels of specific IgG and neutralizing antibodies against the SARS-CoV-2 prototype strain in mice. Notably, regarding to the immune-escape Beta (B.1.351) variant, mutI tri-RBD elicited significantly higher neutralizing antibody titers than homo-tri-RBD. Furthermore, due to harboring the immune-resistant mutations as well as the evolutionarily convergent hotspots, the designed mutI tri-RBD also induced strong broadly neutralizing activities against various SARS-CoV-2 variants, especially the variants partially resistant to homo-tri-RBD. Homo-tri-RBD has been approved by the China National Medical Products Administration to enter clinical trial (No. NCT04869592), and the superior broad neutralization performances against SARS-CoV-2 support the mutI tri-RBD as a more promising vaccine candidate for further clinical developments.

Evaluation of the role and usefulness of clinical pharmacists at the Fangcang Hospital during COVID-19 outbreak.

BACKGROUND: Fangcang Hospitals (cabin hospitals) played a key role in isolation and control of the infection sources during COVID-19 epidemic. Many patients at Fangcang Hospitals had complications or mental stress. As the doctors, nurses and paramedics presented in the emergency, there was a growing demand for clinical pharmacists to provide pharmaceutical care for the affected patients with chronic diseases via telemedicine. OBJECTIVE: This study was a retrospective study to evaluate the usefulness of clinical prevention and control measures of clinical pharmacists at Jianghan Fangcang Hospital. Besides, this study proposed innovative strategies for developing pharmacy services to ensure the medication compliance, accuracy and cure rates under the epidemic. METHODS: A total of 374 patients filled in the questionnaires and 349 patients were enrolled in this study. Patients who refused to receive pharmaceutical care were not included in this study. The pharmaceutical care included medication education via broadcast station, medication reconciliation, optimisation of drug use, monitor of adverse drug events and psychological comfort via WeChat one-to-one service. The data were collected from patients' interviews and the questionnaires of inpatients and discharged patients. RESULTS: In Jianghan Fangcang Hospital, many patients had complications with hypertension (12.9%), hyperlipidaemia (9.2%), thyroid disease (8.9%), diabetes (7.2%), heart disease (3.4%), nephropathy (1.7%), cancer (1.1%) and other diseases (12.6%). After 35 days' pharmacy service, about 200 different questions had been solved by our clinical pharmacists, including drug usage (65.38%), medication reconciliation (55.13%), drug precautions (23.1%), adverse drug reactions (35.9%) and psychological counselling (32.05%). Most patients were satisfied with clinical pharmacist service (66.7% great, 18.0% good). CONCLUSION: The results of the retrospective study indicated that clinical pharmacist can effectively reduce and prevent drug-related, life-related and COVID-19-related problems for COVID-19 patients, which is important for the disease recovery. This study also demonstrated that clinical pharmacist played a key role for patients' healthcare during the pandemic.

Comprehensive Landscape of Heparin Therapy for COVID-19.

The pandemic coronavirus disease 2019 (COVID-19), caused by the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is rapidly spreading globally. Clinical observations found that systemic symptoms caused by SARS-CoV-2 infection are attenuated when using the anticoagulant agent heparin, indicating that heparin may play other roles in managing COVID-19, in addition to prevention of pulmonary thrombosis. Several biochemical studies show strong binding of heparin and heparin-like molecules to the Spike protein, which resulted in inhibition of viral infection to cells. The clinical observations and in vitro studies argue for a potential multiple-targeting effects of heparin. However, adverse effects of heparin administration and some of the challenges using heparin therapy for SARS-CoV-2 infection need to be considered. This review discusses the pharmacological mechanisms of heparin regarding its anticoagulant, anti-inflammatory and direct antiviral activities, providing current evidence concerning the effectiveness and safety of heparin therapy for this major public health emergency.

COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support (preprint)

Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes.

Analysis of Influencing Factors and Pharmaceutical Care of Patients with COVID-19 in Fangcang Shelter Hospital.

PURPOSE: In December 2019, coronavirus disease 2019 (COVID-19) was first identified in Wuhan, and rapidly spread throughout China. Patients with mild symptoms were admitted to Fangcang shelter hospitals for centralized quarantine. We aimed to clarify the medication usage, related adverse reactions, and pharmaceutical interventions in patients with mild COVID-19. PATIENTS AND METHODS: We innovatively carried out targeted pharmacy services. We provided online and off-line pharmaceutical services to patients in the Fangcang shelter hospital. The use of medication, related adverse reactions, and the effects of pharmaceutical intervention were analyzed. RESULTS: Lower blood lymphocyte count was proposed as the most significant risk factor in patients with mild illness. All patients received antiviral treatment (arbidol, oseltamivir, and ribavirin); 78.4% of patients received antibiotic therapy (moxifloxacin, levofloxacin, and cefdinir); patients in the moderate disease group received more antibiotic therapy than those in the mild disease group. Most of the patients were treated with traditional Chinese medicine. Patients with moderate disease preferred to receive sedative hypnotic therapy. Diarrhea, nausea and vomiting, insomnia, arrhythmia, and constipation were the most common adverse reactions. The rate of mild-to-moderate illness in the pharmaceutical intervention and non-intervention groups was 20.6% and 31.7%, respectively. CONCLUSION: Most patients with mild illness were treated with antiviral, antibiotic, and Chinese medicine therapy. However, attention should be paid to patients with mild illness presenting with hypertension and low lymphocyte count at the onset; these patients are more likely to develop moderate or severe disease. Moreover, there were many drug-related problems in Fangcang shelter hospital; pharmaceutical care might contribute to alleviate the progress of the patient's condition. Pharmacists should be prepared to provide skilled and effective services to patients, with the aim to ensure medication safety and promote the overall control of the COVID-19 pandemic.

An Interpretable Machine Learning Framework for Accurate Severe vs Non-Severe COVID-19 Clinical Type Classification (preprint)

Effectively and efficiently diagnosing COVID-19 patients with accurate clinical type is essential to achieve optimal outcomes for the patients as well as reducing the risk of overloading the healthcare system. Currently, severe and non-severe COVID-19 types are differentiated by only a few features, which do not comprehensively characterize the complicated pathological, physiological, and immunological responses to SARS-CoV-2 invasion in different types. In this study, we recruited 214 confirmed COVID-19 patients in non-severe and 148 in severe type, from Wuhan, China. The patients’ comorbidity and symptoms (including 26 features), and laboratory testing results (26 features) upon admission were acquired as two input modalities. Exploratory analyses demonstrated that these features differed substantially between two clinical types. Machine learning random forest (RF) models based on features in each modality were developed and validated to classify COVID-19 clinical types. Using comorbidity/symptom and laboratory results as input independently, RF models achieved >90% and >95% predictive accuracy, respectively. Input features’ importance based on Gini impurity were further evaluated and top five features from each modality were identified (age, hypertension, cardiovascular disease, gender, diabetes; D-Dimer, hsTNI, absolute neutrophil count, IL-6, and LDH, in descending order). Combining top 10 multimodal features, RF model achieved >99% predictive accuracy. These findings shed light on how the human body reacts to SARS-CoV-2 invasion as a unity and provide insights on effectively evaluating COVID-19 patient’s severity and developing personalized treatment plans accordingly. We suggest that symptoms and comorbidities can be used as an initial screening tool for triaging, while laboratory results are applied when accuracy is the priority.Funding Statement: This study was jointly supported by the National Science Foundation for Young Scientists of China (81703201), the Natural Science Foundation for Young Scientists of Jiangsu Province (BK20171076), the Jiangsu Provincial Medical Innovation Team (CXTDA2017029), the Jiangsu Provincial Medical Youth Talent program (QNRC2016548), the Jiangsu Preventive Medicine Association program (Y2018086), the Lifting Program of Jiangsu Provincial Scientific and Technological Association, and the Jiangsu Government Scholarship for Overseas Studies.Declaration of Interests: The authors declare no competing interests in this study.Ethics Approval Statement: Patient-specific identifying information (e.g., name, address of residence) was removed from data collected for this study. This study was evaluated and approved by the IRB committee of Union Hospital, Wuhan, China (approval number: 2020-IEC-J-345).

The Potential of Low Molecular Weight Heparin to Mitigate Cytokine Storm in Severe COVID-19 Patients: A Retrospective Cohort Study.

On March 11, 2020, the World Health Organization declared its assessment of coronavirus disease 2019 (COVID-19) as a global pandemic. However, specific anti-severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) drugs are still under development, and patients are managed by multiple complementary treatments. We performed a retrospective analysis to compare and evaluate the effect of low molecular weight heparin (LMWH) treatment on disease progression. For this purpose, the clinical records and laboratory indicators were extracted from electronic medical records of 42 patients with COVID-19 (21 of whom were treated with LMWH, and 21 without LMWH) hospitalized (Union Hospital of Huazhong University of Science and Technology) from February 1 to March 15, 2020. Changes in the percentage of lymphocytes before and after LMWH treatment were significantly different from those in the control group (P = 0.011). Likewise, changes in the levels of D-dimer and fibrinogen degradation products in the LMWH group before and after treatment were significantly different from those in the control group (P = 0.035). Remarkably, IL-6 levels were significantly reduced after LMWH treatment (P = 0.006), indicating that, besides other beneficial properties, LMWH may exert an anti-inflammatory effect and attenuate in part the "cytokine storm" induced by the virus. Our results support the use of LMWH as a potential therapeutic drug for the treatment of COVID-19, paving the way for a subsequent well-controlled clinical study.