Using Location Intelligence to Evaluate the COVID-19 Vaccination Campaign in the United States: Spatiotemporal Big Data Analysis.

BACKGROUND: Highly effective COVID-19 vaccines are available and free of charge in the United States. With adequate coverage, their use may help return life back to normal and reduce COVID-19-related hospitalization and death. Many barriers to widespread inoculation have prevented herd immunity, including vaccine hesitancy, lack of vaccine knowledge, and misinformation. The Ad Council and COVID Collaborative have been conducting one of the largest nationwide targeted campaigns ("It's Up to You") to communicate vaccine information and encourage timely vaccination across the United States. More than 300 major brands, digital and print media companies, and community-based organizations support the campaigns to reach distinct audiences. OBJECTIVE: The goal of this study was to use aggregated mobility data to assess the effectiveness of the campaign on COVID-19 vaccine uptake. METHODS: Campaign exposure data were collected from the Cuebiq advertising impact measurement platform consisting of about 17 million opted-in and deidentified mobile devices across the country. A Bayesian spatiotemporal hierarchical model was developed to assess campaign effectiveness through estimating the association between county-level campaign exposure and vaccination rates reported by the Centers for Disease Control and Prevention. To minimize potential bias in exposure to the campaign, the model included several control variables (eg, age, race or ethnicity, income, and political affiliation). We also incorporated conditional autoregressive residual models to account for apparent spatiotemporal autocorrelation. RESULTS: The data set covers a panel of 3104 counties from 48 states and the District of Columbia during a period of 22 weeks (March 29 to August 29, 2021). Officially launched in February 2021, the campaign reached about 3% of the anonymous devices on the Cuebiq platform by the end of March, which was the start of the study period. That exposure rate gradually declined to slightly above 1% in August 2021, effectively ending the study period. Results from the Bayesian hierarchical model indicate a statistically significant positive association between campaign exposure and vaccine uptake at the county level. A campaign that reaches everyone would boost the vaccination rate by 2.2% (95% uncertainty interval: 2.0%-2.4%) on a weekly basis, compared to the baseline case of no campaign. CONCLUSIONS: The "It's Up to You" campaign is effective in promoting COVID-19 vaccine uptake, suggesting that a nationwide targeted mass media campaign with multisectoral collaborations could be an impactful health communication strategy to improve progress against this and future pandemics. Methodologically, the results also show that location intelligence and mobile phone-based monitoring platforms can be effective in measuring impact of large-scale digital campaigns in near real time.

Novel Affibody Molecules Specifically Bind to SARS-CoV-2 Spike Protein and Efficiently Neutralize Delta and Omicron Variants.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been an unprecedented public health disaster in human history, and its spike (S) protein is the major target for vaccines and antiviral drug development. Although widespread vaccination has been well established, the viral gene is prone to rapid mutation, resulting in multiple global spread waves. Therefore, specific antivirals are needed urgently, especially those against variants. In this study, the domain of the receptor binding motif (RBM) and fusion peptide (FP) (amino acids [aa] 436 to 829; denoted RBMFP) of the SARS-CoV-2 S protein was expressed as a recombinant RBMFP protein in Escherichia coli and identified as being immunogenic and antigenically active. Then, the RBMFP proteins were used for phage display to screen the novel affibody. After prokaryotic expression and selection, four novel affibody molecules (Z14, Z149, Z171, and Z327) were obtained. Through surface plasmon resonance (SPR) and pseudovirus neutralization assay, we showed that affibody molecules specifically bind to the RBMFP protein with high affinity and neutralize against SARS-CoV-2 pseudovirus infection. Especially, Z14 and Z171 displayed strong neutralizing activities against Delta and Omicron variants. Molecular docking predicted that affibody molecule interaction sites with RBM overlapped with ACE2. Thus, the novel affibody molecules could be further developed as specific neutralization agents against SARS-CoV-2 variants. IMPORTANCE SARS-CoV-2 and its variants are threatening the whole world. Although a full dose of vaccine injection showed great preventive effects and monoclonal antibody reagents have also been used for a specific treatment, the global pandemic persists. So, developing new vaccines and specific agents are needed urgently. In this work, we expressed the recombinant RBMFP protein as an antigen, identified its antigenicity, and used it as an antigen for affibody phage-display selection. After the prokaryotic expression, the specific affibody molecules were obtained and tested for pseudovirus neutralization. Results showed that the serum antibody induced by RBMFP neutralized Omicron variants. The screened affibody molecules specifically bound the RBMFP of SARS-CoV-2 with high affinity and neutralized the Delta and Omicron pseudovirus in vitro. So, the RBMFP induced serum provides neutralizing effects against pseudovirus in vitro, and the affibodies have the potential to be developed into specific prophylactic agents for SARS-CoV-2 and its variants.

Impact of Public Health and Social Measures on the COVID-19 Pandemic in the United States and Other Countries: Descriptive Analysis.

BACKGROUND: The United States of America has the highest global number of COVID-19 cases and deaths, which may be due in part to delays and inconsistencies in implementing public health and social measures (PHSMs). OBJECTIVE: In this descriptive analysis, we analyzed the epidemiological evidence for the impact of PHSMs on COVID-19 transmission in the United States and compared these data to those for 10 other countries of varying income levels, population sizes, and geographies. METHODS: We compared PHSM implementation timing and stringency against COVID-19 daily case counts in the United States and against those in Canada, China, Ethiopia, Japan, Kazakhstan, New Zealand, Singapore, South Korea, Vietnam, and Zimbabwe from January 1 to November 25, 2020. We descriptively analyzed the impact of border closures, contact tracing, household confinement, mandated face masks, quarantine and isolation, school closures, limited gatherings, and states of emergency on COVID-19 case counts. We also compared the relationship between global socioeconomic indicators and national pandemic trajectories across the 11 countries. PHSMs and case count data were derived from various surveillance systems, including the Health Intervention Tracking for COVID-19 database, the World Health Organization PHSM database, and the European Centre for Disease Prevention and Control. RESULTS: Implementing a specific package of 4 PHSMs (quarantine and isolation, school closures, household confinement, and the limiting of social gatherings) early and stringently was observed to coincide with lower case counts and transmission durations in Vietnam, Zimbabwe, New Zealand, South Korea, Ethiopia, and Kazakhstan. In contrast, the United States implemented few PHSMs stringently or early and did not use this successful package. Across the 11 countries, national income positively correlated (r=0.624) with cumulative COVID-19 incidence. CONCLUSIONS: Our findings suggest that early implementation, consistent execution, adequate duration, and high adherence to PHSMs represent key factors of reducing the spread of COVID-19. Although national income may be related to COVID-19 progression, a country's wealth appears to be less important in controlling the pandemic and more important in taking rapid, centralized, and consistent public health action.

Optimizing global COVID-19 vaccine allocation: An agent-based computational model of 148 countries.

BACKGROUND: Based on the principles of equity and effectiveness, the World Health Organization and COVAX formulate vaccine allocation as a mathematical optimization problem. This study aims to solve the optimization problem using agent-based simulations. METHODS: We built open-sourced agent-based models to simulate virus transition among a demographically representative sample of 198 million people in 148 countries using advanced computational services. All countries continuing their current vaccine progress is defined as the baseline scenario. Comparison scenarios include achieving minimum vaccination rates and allocating vaccines based on pandemic levels. FINDINGS: The simulations are fitted using the pandemic data from 148 countries from January 2020 to June 2021. Under the baseline scenario, the world will add 24.36 million cases and 468,945 deaths during the projection period of three months. Inoculating at least 10%, 20%, and 26% of populations in all countries requires 1.12, 3.31, and 5.00 million additional vaccine doses every day, respectively. Achieving these benchmarks reduces new cases by 0.56, 2.74, and 3.32 million, respectively. If allocated by the current global distribution, 5.00 million additional vaccine doses will only avert 1.45 million new cases. If those 5.00 million vaccines are allocated based on projected cases in each country, the averted cases will increase more than six-fold to 9.20 million. Similar differences between allocation methods are observed in averted deaths. CONCLUSION: The global distribution of COVID-19 vaccines can be optimized to achieve better outcomes in terms of both equity and effectiveness. Alternative vaccine allocation methods may avert several times more cases and deaths than the current global distribution. With reasonable requirements on additional vaccines, COVAX could adopt alternative allocation strategies that reduce cross-country inequity and save more lives.

An outbreak of acute respiratory disease caused by HAdV-55 in Beijing, China, 2020.

Human adenoviruses (HAdVs) can cause acute respiratory diseases (ARDs) worldwide, and HAdV-55 is a reemergent pathogen in recent years. In the study, we investigated an outbreak of ARD at a school due to HAdV-55 in Beijing, China, during the early outbreak of coronavirus disease 2019 (COVID-19). The epidemic prevention team was dispatched to the school to collect epidemiologic data and nasopharyngeal samples. Then, real-time reverse transcription polymerase chain reaction (PCR) and multiplex PCR assays were used to detect severe acute respiratory syndrome coronavirus 2 and other respiratory pathogens, respectively. One representative HAdV-55 isolate was selected and submitted for whole-genome sequencing using a MiSeq system and the whole-genome phylogenetic tree was conducted based on the maximum likelihood method. The outbreak lasted from January 27 to February 6, 2020, and 108 students developed fever, among whom 60 (55.56%) cases were diagnosed with HAdV-55 infection in the laboratory using real-time PCR and 56 cases were hospitalized. All the confirmed cases had a fever and 11 cases (18.33%) presented with a fever above 39°C. Other main clinical symptoms included sore throat (43.33%) and headache (43.33%). We obtained and assembled the full genome of one isolate, BJ-446, with 34 761 nucleotides in length. HAdV-55 isolate BJ-446 was 99.85% identical to strain QS-DLL, which was the first HAdV-55 strain in China isolated from an ARD outbreak in Shanxi in 2006. One and four amino acid mutations were observed in the hexon gene and the coding region of L2 pV 40.1 kDa protein, respectively. We identified the first HAdV-55 infection associated with the ARD outbreak in Beijing since the emergence of COVID-19. The study suggests that improved surveillance of HAdV is needed, although COVID-19 is still prevalent in the world.

Nucleocapsid protein of SARS-CoV-2 is a potential target for developing new generation of vaccine.

BACKGROUND: SARS-CoV-2 has spread worldwide causing more than 400 million people with virus infections since early 2020. Currently, the existing vaccines targeting the spike glycoprotein (S protein) of SARS-CoV-2 are facing great challenge from the infection of SARS-CoV-2 virus and its multiple S protein variants. Thus, we need to develop a new generation of vaccines to prevent infection of the SARS-CoV-2 variants. Compared with the S protein, the nucleocapsid protein (N protein) of SARS-CoV-2 is more conservative and less mutations, which also plays a vital role in viral infection. Therefore, the N protein may have the great potential for developing new vaccines. METHODS: The N protein of SARS-CoV-2 was recombinantly expressed and purified in Escherichia coli. Western Blot and ELISA assays were used to demonstrate the immunoreactivity of the recombinant N protein with the serum of 22 COVID-19 patients. We investigated further the response of the specific serum antibodies and cytokine production in BALB/c mice immunized with recombinant N protein by Western Blot and ELISA. RESULTS: The N protein had good immunoreactivity and the production of IgG antibody against N protein in COVID-19 patients was tightly correlated with disease severity. Furthermore, the N protein was used to immunize BALB/c mice to have elicited strong immune responses. Not only high levels of IgG antibody, but also cytokine-IFN-γ were produced in the N protein-immunized mice. Importantly, the N protein immunization induced a high level of IgM antibody produced in the mice. CONCLUSION: SARS-CoV-2 N protein shows a great big bundle of potentiality for developing a new generation of vaccines in fighting infection of SARS-CoV-2 and its variants.

Our Experiences with Plastic and Reconstructive Surgery Procedures during Coronavirus Disease 2019 Pandemic.

The novel Coronavirus Disease 2019 (COVID-19) has rapidly become a health threat worldwide and has been declared global pandemic by the World Health Organization. Possible transmission routes, including respiratory droplets, close contact, and aerosol propagation, have put plastic and reconstructive healthcare professionals at high risk, especially during surgical procedures. The aim of this study was to summarize and share our experience of infection control measures and corresponding outcomes during the COVID-19 pandemic. METHODS: Infection control measures, including workflow optimization, useful epidemiologic survey methods, and personal full protective clothing, were discussed. Characteristics and outcomes of emergency cases and elective cases under local and general anesthesia during the COVID-19 pandemic were summarized. RESULTS: A hierarchy of interventions were applied mainly from 4 aspects. First, administration control and online consultation significantly decreased patient attendance. Second, a triage workflow was established to identify high-/low-risk patients, with clinical manifestations (fever, fatigue, cough, nasal discharge, etc), epidemiologic survey, blood test, chest computed tomographic scan, and coronavirus test if necessary. Third, strict environmental control was adopted using increasing ventilation, isolated room for inpatients, etc. Fourth, proper rotation of healthcare staff was ensured to reduce workload and minimize possible contact. A total of 904 emergency interventions, 2561 local anesthesia, and 570 general anesthesia were performed during this period, and none of the cases/healthcare professionals were found to be infected. CONCLUSIONS: Our experience could help global plastic and reconstructive healthcare professionals to get better preparation and continue to give qualified medical services during the COVID-19 pandemic. Proper adjustments should be taken according to their own clinical settings.

Monitoring peripheral neutrophil and T-lymphocyte subsets could assist in differentiating the severity and disease progression of coronavirus disease 2019.

Helper T cells (CD3+CD4+ T cells) and cytotoxic T cells (CD3+CD8+ T cells) play direct and indirect antiviral roles. This study retrospectively explored the clinical significance of peripheral lymphocytes, especially the dynamic analysis of T-cell subsets, in determining coronavirus disease 2019 (COVID-19) severity and progression. Seventy-nine patients with COVID-19 in the Public Health Clinical Center of Chengdu from January to February 2020 were included, 59 of which were analyzed for dynamic peripheral T-cell subsets expression. The neutrophil to CD4+ T lymphocyte ratio (N4R) and neutrophil to CD3+ T lymphocyte ratio (N3R) showed clinical significance in differentiating severe or critically-severe COVID-19, with area under receiver operating characteristic curves (AUCs) of 0.933 and 0.900, respectively (P < 0.05). COVID-19 patients with more baseline peripheral lymphocytes or NK cells were prone to test negative to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after therapy (P < 0.05), and the AUC of NK cells for predicting negative results of SARS-CoV-2 RNA detection after therapy was 0.800. When the number of peripheral CD3+CD4+ and CD3+CD8+ T cells in COVID-19 patients continuously increased 6-9 days after baseline, the period of disease exacerbation could be delayed for more than 2 weeks after admission. Baseline N4R and N3R could be potential biomarkers for assisting in differentiating COVID-19 severity, and dynamically monitoring peripheral CD3+CD4+ and CD3+CD8+ T cells 6-9 days after baseline could help clinicians to evaluate disease progression in COVID-19 patients.

Overall reduced lymphocyte especially T and B subsets closely related to the poor prognosis and the disease severity in severe patients with COVID-19 and diabetes mellitus.

BACKGROUND: A dysregulated host immune response is common in patients with COVID-19. AIM: In this study, we aimed to define the characteristics of lymphocyte subsets and their relationship with disease progression in COVID-19 patients with or without diabetes mellitus (DM). METHODS: The baseline peripheral lymphocyte subsets were compared between 55 healthy controls and 95 patients with confirmed COVID-19, and between severe and non-severe COVID-19 patients with or without DM. RESULTS: The prevalence of DM in the COVID-19 group was 20%, and patients with severe COVID-19 had a higher prevalence of DM than those with non-severe disease (P = 0.006). Moreover, a significantly poor prognosis and a higher rate of severity were found in those with DM relative to those without DM (P = 0.001, 0.003). Generally, all lymphocytes and subsets of lymphocytes, especially B and T cells, were significant reduced in COVID-19 patients, particularly in those with DM. Patients with severe COVID-19 and DM had the lowest lymphocyte counts compared with those with severe COVID-19 without DM, and those with non-severe COVID-19 with or without DM. Partially decreased lymphocyte subsets, age and DM were closely related to disease progression and prognosis. CONCLUSIONS: These findings provide a reference for clinicians that immunomodulatory treatment may improve disease progression and prognosis of COVID-19 patients, especially those with severe disease with DM. Trial registration Chinese Clinical Trial Register ChiCTR2000034563.

Epidemiological characteristics and clinical features of 32 critical and 67 noncritical cases of COVID-19 in Chengdu.

BACKGROUND: In December 2019, Wuhan, China, experienced an outbreak of coronavirus (COVID-19). The number of cases has increased rapidly, but information on the clinical characteristics remains limited. OBJECTIVES: This paper describes the epidemiological and clinical characteristics of COVID-19. Early detection and identification of critically ill patients is necessary to facilitate scientific classification and treatment. STUDY DESIGN: This study included a retrospective, single-center case series of 99 consecutively hospitalized patients with confirmed COVID-19 at Chengdu Public Health Clinical Medical Center in Chengdu, China, from January 16 to February 20, 2020. The final date of follow-up was February 23, 2020. We collected and analyzed epidemiological, demographic, clinical, laboratory, radiological, and treatment data. We compared outcomes of critically ill patients and noncritically ill patients. RESULTS: Of the 99 hospitalized patients with COVID-19, the median age was 49 years (minimum, 3 months; maximum, 87 years) and 51 (52 %) were men; 42 (42 %) had traveled to or lived in Wuhan and 48 (49 %) had come into close contact with patients with new coronavirus pneumonia; 41 (41 %) patients had underlying disease. Common symptoms included fever (85 [86 %]), dry cough (84 [85 %]), and fatigue (72 [73 %]). We analyzed the clinical characteristics of patients. We expressed the measurement data as mean ±â€¯standard deviation. We collected data for age (49.39 ±â€¯18.45 years), number of hospital days (12.32 ±â€¯6.70 days), and laboratory indicators. We compared critically ill and noncritically ill patients: p-values for age, C-reactive protein, high-sensitivity troponin T, prothrombin time, fibrin degradation products, D-Dimer, and CD4+ count were p < 0.001; and p-values for hospital days, white blood cell, neutrophil, lymphocyte, creatine kinase isoenzyme, myoglobin, N-terminal brain natriuretic peptide, and CD8+ count were p < 0.05. CONCLUSIONS: We collected data from a single-center case series of 32 hospitalized patients who were critically ill with confirmed COVID-19 in Chengdu, China, and compared data with 67 noncritically ill patients. Elderly patients had chronic underlying diseases, notably cardiovascular disease. Higher C-reactive protein levels, higher levels of myocardial damage, and higher brain natriuretic peptide levels; lower white blood cells, neutrophils, and lymphocytes; and lower CD4 and CD8 counts could be used for early detection and identification of critically ill patients, and dynamic Data observation was more important than at a single moment.