Oral Ursodeoxycholic Acid Therapy Failed to Mitigate SARS-CoV-2 Omicron Variants BA.5.2 Infection (preprint)

Background Ursodeoxycholic acid (UDCA) was reported to reduce susceptibility to SARS-CoV-2 infection by downregulating farnesoid X receptor (FXR) -ACE2 signaling. However, we found a different story in real-world clinical studies.Objectives We attempted to verify whether UDCA can effectively prevent SARS-CoV-2 transmission or have positive therapeutic effects in a real-world clinical study.Methods We performed a retrospective study, collected and assessed clinical presentation and laboratory data on patients with liver diseases infected with SARS-CoV-2 Omicron sub-variant BA.5.2 who had been treated with or without UDCA.Results Treatment with UDCA did not prevent infection with the Omicron sub-variant BA.5.2, failed in reducing the duration of infection and hardly mitigated the severity of COVID-19. Meanwhile, the severity of liver diseases, especially TBil, ALP, γ-GT, liver cirrhosis and Child-Pugh classification, should be considered as risk factors for severe COVID-19 in chronic hepatic patients.Conclusion UDCA failed to show inhibitory effects against SARS-CoV-2 infection in complex clinical settings. The regulatory mechanism of the novel UDCA-FXR-ACE2 pathway needs to be further investigated in real-world clinical studies.

The early stage of COVID-19 pandemic: Gastrointestinal manifestations and liver injury in COVID-19 patients in Wuhan, China

There are few and inconsistent data focusing on gastrointestinal (GI) manifestations and liver injury in China's early stage of COVID-19 pandemic. In this study, we research the prevalence and role of GI symptoms and liver injury in COVID-19 patients in Wuhan during the disease's first outbreak. We conducted a cross-sectional observational study in a non-ICU unit in Wuhan, China. COVID-19 patients were consecutively admitted from 23 February 2020 to 5 April 2020. Demographic and clinical data were retrieved and analyzed throughout the disease course. A total of 93 patients were enrolled, including 45.2% moderate, 54.8% severe, and 2.2% critical type patients. 69.9% of patients had at least one GI symptom;if excluding hyporexia/anorexia, 49.5% of patients showed at least one GI symptom. The incidence rate of hyporexia/anorexia, diarrhea, nausea/vomiting, abdominal discomfort/pain, and elevated liver enzymes were 67.7, 29.0, 28.0, 21.5, and 23.7%, respectively. Patients with GI symptoms or elevated liver enzymes have a higher risk of severe type disease than patients without GI symptoms or elevated liver enzymes (67.7 vs. 25.0%, p < 0.001;77.3 vs. 47.9%, p = 0.016, respectively), and experienced longer disease duration. In multivariate analysis, hyporexia/anorexia was confirmed as an independent predictive factor of severe type disease (odds ratio: 5.912;95% confidence interval: 2.247–15.559;p < 0.001). In conclusion, in the early stage of the COVID-19 pandemic, GI symptoms and elevated liver enzymes are common throughout the disease course, and associated with severer disease and longer disease duration.

Metabolomics-based investigation of SARS-CoV-2 vaccination (Sinovac) reveals an immune-dependent metabolite biomarker

SARS-CoV-2 and its mutant strains continue to rapidly spread with high infection and fatality. Large-scale SARS-CoV-2 vaccination provides an important guarantee for effective resistance to existing or mutated SARS-CoV-2 virus infection. However, whether the host metabolite levels respond to SARS-CoV-2 vaccine-influenced host immunity remains unclear. To help delineate the serum metabolome profile of SARS-CoV-2 vaccinated volunteers and determine that the metabolites tightly respond to host immune antibodies and cytokines, in this study, a total of 59 sera samples were collected from 30 individuals before SARS-CoV-2 vaccination and from 29 COVID-19 vaccines 2 weeks after the two-dose vaccination. Next, untargeted metabolomics was performed and a distinct metabolic composition was revealed between the pre-vaccination (VB) group and two-dose vaccination (SV) group by partial least squares-discriminant and principal component analyses. Based on the criteria: FDR < 0.05, absolute log2 fold change greater than 0.25, and VIP >1, we found that L-glutamic acid, gamma-aminobutyric acid (GABA), succinic acid, and taurine showed increasing trends from SV to VB. Furthermore, SV-associated metabolites were mainly annotated to butanoate metabolism and glutamate metabolism pathways. Moreover, two metabolite biomarkers classified SV from VB individuals with an area under the curve (AUC) of 0.96. Correlation analysis identified a positive association between four metabolites enriched in glutamate metabolism and serum antibodies in relation to IgG, IgM, and IgA. These results suggest that the contents of gamma-aminobutyric acid and indole in serum could be applied as biomarkers in distinguishing vaccinated volunteers from the unvaccinated. What’s more, metabolites such as GABA and taurine may serve as a metabolic target for adjuvant vaccines to boost the ability of the individuals to improve immunity.

Randomized, placebo-controlled, single-blind phase 1 studies of the safety, tolerability, and pharmacokinetics of BRII-196 and BRII-198, SARS-CoV-2 spike-targeting monoclonal antibodies with an extended half-life in healthy adults

Background: BRII-196 and BRII-198 are two anti-SARS-CoV-2 monoclonal neutralizing antibodies as a cocktail therapy for treating COVID-19 with a modified Fc region that extends half-life. Methods: Safety, tolerability, pharmacokinetics, and immunogenicity of BRII-196 and BRII-198 were investigated in first-in-human, placebo-controlled, single ascending dose phase 1 studies in healthy adults. 44 participants received a single intravenous infusion of single BRII-196 or BRII-198 up to 3,000 mg, or BRII-196 and BRII-198 combination up to 1500/1500 mg, or placebo and were followed up for 180 days. Primary endpoints were incidence of adverse events (AEs) and changes from pre-dose baseline in clinical assessments. Secondary endpoints included pharmacokinetics profiles of BRII-196/BRII-198 and detection of anti-drug antibodies (ADAs). Plasma neutralization activities against SARS-CoV-2 Delta live virus in comparison to post-vaccination plasma were evaluated as exploratory endpoints. Results: All infusions were well-tolerated without systemic or local infusion reactions, dose-limiting AEs, serious AEs, or deaths. Most treatment-emergent AEs were isolated asymptomatic laboratory abnormalities of grade 1-2 in severity. BRII-196 and BRII-198 displayed pharmacokinetics characteristic of Fc-engineered human IgG1 with mean terminal half-lives of 44.6–48.6 days and 72.2–83.0 days, respectively, with no evidence of interaction or significant anti-drug antibody development. Neutralizing activities against the live virus of the SARS-CoV-2 Delta variant were maintained in plasma samples taken on day 180 post-infusion. Conclusion: BRII-196 and BRII-198 are safe, well-tolerated, and suitable therapeutic or prophylactic options for SARS-CoV-2 infection. Clinical Trial Registration:ClinicalTrials.gov under identifiers NCT04479631, NCT04479644, and NCT04691180.

Epidemiological investigation of an imported COVID-19 case infected with Delta variant from Nepal in Chongqing of China

Objective: To analyze the epidemiological characteristics of a COVID-19 case imported from Nepal in Chongqing of China, and provide evidence for the prevention and control of imported COVID-19.

Development and characterization of neutralizing antibodies against SRAS-CoV-2 (preprint)

Background The novel coronavirus disease 2019(COVID-19) caused by SARS-CoV-2 that belongs to betacoronaviruseis, and is an enveloped, single and positive-stranded RNA virus. In this study, we describe the production and characterization of four monoclonal antibodies (mAb) with neutralization activities.Methods Thirteen mAbs that identified positive were characterized by neutralization assays, binding affinities identification, and ELISA to evaluate the immunocompetence. The genes of neutralizing antibodies were sequenced and analyzed.Results All mAbs recognized two different epitopes respectively, including RBD and hFc, and the binding affinities are also different. Four of nine mAbs that can recognize the epitopes of RBD are conformation neutralizing antibodies that have high binding affinity and neutralization ability. Based on the sequencing, the mAbs are unique antibodies with specificity.Conclusions We characterized thirteen monoclonal antibodies, four of which are neutralizing antibodies and identified unique antibodies with specificity. The results highlight the promise of antibody-based therapeutics and provide the structural basis of rational vaccine design.

The Difference in Open Innovation between Open Access and Closed Access, According to the Change of Collective Intelligence and Knowledge Amount

This study explored the differences in the effects of collective intelligence and references on open innovation between open and closed access journals. This study analyzed the moderating effect of references on the motivation of collective intelligence on open innovation from 2003 to 2006 and 2013 to 2016, considered to be the digital transformation era. The Scopus database on open and closed access journals was used for ordinary regression analysis. During the 2003–2006 period, only papers in closed access journals demonstrated sufficient effect of collective intelligence and reference on open innovation and the effective moderating role of reference. However, between 2013 and 2016, papers in open and closed access journals demonstrated the incentive effects of collective intelligence and references on citation and the moderating role of references on the correlation between collective intelligence and citation. The increase in digital transformation strengthens the collective intelligence and references of open access journals, and citations of open access journals nearly surpass those of closed access journals.

Incidence, Risk Factors, and Outcomes of Patients with COVID‑19‑Associated Pulmonary Aspergillosis (CAPA) in Intensive Care Units: A Systematic Review and Meta-Analysis Of 29 Cohort Studies (preprint)

Background Patients with Coronavirus disease 2019 (COVID-19) admitted to an intensive care unit (ICU) might develop COVID-19-related pulmonary Aspergillosis (CAPA). We aimed to identify studies systematically that describe the incidence and risks factors of CAPA, and to assess its outcome. Methods Two authors independently searched ScienceDirect, PubMed, CNKI, MEDLINE (OVID), and MedRXIV from December 31, 2019 to Feb 27, 2021. We included observational cohort studies that investigated patients with CAPA admitted to an ICU. We assessed the quality of all included studies using the Newcastle–Ottawa Scale). The meta-analysis was registered with PROSPERO (CRD42021242179).ResultsTwenty-nine cohort studies with 2095 patients with COVID-19 admitted to an ICU and 264 patients who developed to CAPA were included (Pooled incidence: 0.14, 95% confidence interval [CI] = 0.11–0.17). The overall mortality and case fatality rate of CAPA were 0.07 (0.05–0.09) and 0.51 (0.44–0.58), respectively. Patients with COVID‑19 would develop CAPA at 7.28 days after mechanical ventilation (range, 5.48–9.08). Compared with patients without CAPA, those with CAPA had a significantly lower median body mass index (27.32 vs. 28.97 kg/m2, P = 0.034), higher median creatinine level (127.94 vs. 88.23 µmol/L, P = 014), and were more likely to receive corticosteroids therapy (41.0% vs. 38.0%, risk ratio [RR] = 1.98, 95% CI=1.08–3.63) and renal replacement therapy (42.0% vs. 28.2%, RR = 1.61, 95% CI=1.04–2.50) during admission. Remarkably, patients with CAPA were associated significantly with a 1.66‑fold higher mortality (RR = 1.66, 95% CI=1.31–2.12) without significant heterogeneity and publication bias. ConclusionsPatients with COVID-19 admitted to an ICU might develop CAPA and have higher all‑cause mortality. We recommend conducting prospective screening for CAPA among patients with severe COVID-19, especially for those who receive mechanical ventilation over 7 days. 

AI based satisfaction survey of patients in fever clinics during the outbreak of COVID-19 (preprint)

Background: We assessed patient by automated survey method in understanding and satisfaction with the use of fever clinic, and observed the effectiveness of this method. Methods: Total 873 patients in fever clinc at Jiangsu Province Hospital (JSPH) from 20 January 2019 to 18 June 2020 were investigated by an antomated survey method conbined by Wechat, Short Message Service (SMS) and AI voice call. Responses were assessed for overall positivity or negativity and further compared according to patients types (isolated patients and non-isolated patients). Responses were also described and compared for each type of survey. Results: A total of 379 patient surveys were returned, for a total response rate of 43.4%. Isolated and non-isolated patients responses were similar and all with more than 90% satisfaction. Most isolated patient represent that the medical staff had explained to them the reason for the isolation and know that can helps prevent COVID-19. AI voice calls had the highest percentage of all response types, followed by WeChat and SMS. Conclusion: The patient has a positive response to the use of fever clinic. The automated survey method combine by different survey types can bring great convenience to the investigation while ensuring good investigation efficiency.

Research on Financing of Small and Micro Enterprises in Postepidemic Period: Based on Evolutionary Game and Numerical Simulation

Small and microenterprises are most affected during the COVID-19 epidemic period. Despite the government introducing many preferential policies, financing for small and microenterprises is still difficult. Based on evolutionary game theory and Matlab r2017b software, this paper discusses the causes of financing problems from two aspects. By taking loan amount, loan interest rate, guarantee value, and intermediary business income as variables, the research shows that banks not only pay attention to the comprehensive return of small and microenterprises but also pay more attention to the coverage of loan principal and interest by the value of collateral. Relying on collateral for credit is still the main way, and the lack of collateral causes financing difficulties of small and microenterprises. Accordingly, this paper puts forward the countermeasures and suggestions to improve the guarantee compensation mechanism and innovate the financing mode.

Risk Factors Associated with Disease Severity and Clinical Outcomes for COVID-19 in Wuhan, China (preprint)

Background: A new type of pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) appeared in Wuhan, China. However, the risk factors and characteristics related to the severity of the disease and its outcomes need to be further explored.Methods: In this retrospective study, we evaluated COVID-19 patients with severe disease and those who were critically ill, as diagnosed at Jinyintan Hospital (Wuhan, China). The demographic information, clinical characteristics, complications, and laboratory results for the patients were evaluated. Multivariate logistic regression methods were used to analyze risk factors related to hospital deaths.Results: The 235 COVID-19 patients included were divided into a severe group of 183 (78%) and a critical group of 52 (22%). Of these patients, 185 (79%) were discharged, and 50 (21%) died during hospitalization. In multivariate logistic analyses, age (OR=1.07, 95% CI 1.02-1.14, P=0.009), critical disease (OR=48.23, 95% CI 10.91-323.13, P<0.001), low lymphocyte counts (OR=15.48, 95% CI 1.98-176.49, P=0.015), elevated interleukin 6 (IL-6) (OR=9.11, 95% CI 1.69-67.75, P=0.017), and elevated aspartate aminotransferase (AST) (OR=8.46, 95% CI 2.16-42.60, P=0.004) were independent risk factors for adverse outcomes.Conclusions: The results show that advanced age (> 64 years), critical illness, low lymphocyte levels, and elevated IL-6 and AST were factors for the risk of death for COVID-19 patients who had severe disease and those who were critically ill.

Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases (preprint)

Chest radiography (CXR) is the most widely-used thoracic clinical imaging modality and is crucial for guiding the management of cardiothoracic conditions. The detection of specific CXR findings has been the main focus of several artificial intelligence (AI) systems. However, the wide range of possible CXR abnormalities makes it impractical to build specific systems to detect every possible condition. In this work, we developed and evaluated an AI system to classify CXRs as normal or abnormal. For development, we used a de-identified dataset of 248,445 patients from a multi-city hospital network in India. To assess generalizability, we evaluated our system using 6 international datasets from India, China, and the United States. Of these datasets, 4 focused on diseases that the AI was not trained to detect: 2 datasets with tuberculosis and 2 datasets with coronavirus disease 2019. Our results suggest that the AI system generalizes to new patient populations and abnormalities. In a simulated workflow where the AI system prioritized abnormal cases, the turnaround time for abnormal cases reduced by 7-28%. These results represent an important step towards evaluating whether AI can be safely used to flag cases in a general setting where previously unseen abnormalities exist.

Analysis of clinical features and related factors of coronavirus disease 2019 in Shanghai

Objective • To explore the common clinical features of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)-infected local patients in Shanghai and their related influencing factors. Methods • A total of 320 patients admitted to Shanghai Public Health Clinical Center from January to March 2020 and diagnosed as having coronavirus disease 2019(COVID-19) were selected. Clinical data of the patients were collected to analyze their characteristics. Using the statistical operation formula of R language, the correlation analysis of hospitalization days, days of increased hypersensitive C-reactive protein concentration (allergic days), days of lung CT improvement (CT days), and days required for nucleic acid turning negative with the main clinical manifestations and laboratory data was carried out. The correlation factors affecting the above four variables were analyzed. Results • Among the 320 patients, the proportions of mild type, moderate type, serious type and critical type were 6.25%, 83.44%, 6.88% and 3.44%, respectively;91.25% of them had a history of exposure to Hubei. The proportions of fever, cough, sputum and fatigue were 79.06%, 46.56%, 21.56% and 15.31%, respectively. Spearman correlation analysis showed that the concentrations of lactate dehydrogenase, interleukin-2(IL-2) and IL-6 were positively correlated with the above four variables, respectively (all P<0.05), albumin concentration was negatively correlated with allergic days (P=0.018), and CD4+ cell count was negatively correlated with CT days and days required for nucleic acid turning negative (both P<0.05). Stepwise multiple linear regression analysis showed that procalcitonin (PCT) concentration was negatively correlated with hospitalization days, CT days and allergic days (both P<0.05), and disease type was positively correlated with hospitalization days, allergic days, CT days and days required for nucleic acid turning negative (all P<0.05). Conclusion • Moderate type is common in the local patients in Shanghai;fever, cough and fatigue are common symptoms, and most of the patients are accompanied by lung CT abnormalities. The therapeutic effect and prognosis of these patients are closely related to disease type, concentrations of PCT and IL-6, as well as CD4+ cell count.

Treatment with Arbidol and Moxifloxacin in Ordinary and Severe Adult Patients Infected with COVID-19 (preprint)

Background An outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widely spread. We aim to investigate the therapeutic effect of arbidol and moxifloxacin in patients infected with SARS-CoV-2. Methods We collected and analyzed data on 94 patients with COVID-19 including 27 severe patients at the Intensive Care Unit (ICU) and 74 ordinary patients at general isolation ward in Wuhan Xiehe Hospital, from February 15, 2020 to March 15, 2020. All patients were treated with arbidol (100mg each time, three times a day for 14 days) and moxifloxacin (0.4g each time, once a day for 7-14 days). Other data was also collected including demographic data, symptoms, laboratory findings, treatments and clinical outcomes. Results In basic characteristics, compared with the ordinary patients, the severe patients were older (median age was 63.0 years V.S 57.0 years, p=0.03), had higher proportion of hypertension (30% V.S 9%, p=0.03), higher possibility of getting fatigue and/or myalgia (26% V.S 6%, p=0.03), and had more obvious dyspnea symptom (26% V.S 3%, p=0.006). In regarding to laboratory results, we found the severe patients have higher white blood cell counts (p=0.003), neutrophil counts (p=0.007), higher levels of D-dimer (p<0.001), ALT (p<0.001) and AST (p=0.013) than the ordinary patients. After treatment of arbidol and moxifloxacin for one week, the rates of SARS-CoV-2 nucleic acid turning negative were 69.2% in the severe group and 77.8% in the ordinary group. A peculiar phenomenon was that IL-6 stands out among the cytokines in both groups, and higher in severe group than the ordinary one (p=0.011). After treating with arbidol and moxifloxacin for one week, IL-6 decreased significantly in severe group (p=0.023). Conclusion In summary, we proved the treatment of arbidol and moxifloxacin could be helpful in reducing viral load and inflammation during SARS-CoV2 infection, especially for negatively regulating fatal inflammation in severe COVID-19 patients. However, more evidence awaits further clinical verification.

Detection of SARS-CoV-2 in Exhaled Breath from COVID-19 Patients Ready for Hospital Discharge (preprint)

The COVID-19 pandemic has brought an unprecedented crisis to the global health sector1. When recovering COVID-19 patients are discharged in accordance with throat or nasal swab protocols using reverse transcription polymerase chain reaction (RT-PCR), the potential risk of re-introducing the infection source to humans and the environment must be resolved 2,3,4. Here we show that 20% of COVID-19 patients, who were ready for a hospital discharge based on current guidelines, had SARS-CoV-2 in their exhaled breath (~105 RNA copies/m3). They were estimated to emit about 1400 RNA copies into the air per minute. Although fewer surface swabs (1.3%, N=318) tested positive, medical equipment frequently contacted by healthcare workers and the work shift floor were contaminated by SARS-CoV-2 in four hospitals in Wuhan. All air samples (N=44) appeared negative likely due to the dilution or inactivation through natural ventilation (1.6-3.3 m/s) and applied disinfection. Despite the low risk of cross environmental contamination in the studied hospitals, there is a critical need for strengthening the hospital discharge standards in preventing re-emergence of COVID-19 spread.

MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation (preprint)

The rapid spread of the new pandemic, i.e., COVID-19, has severely threatened global health. Deep-learning-based computer-aided screening, e.g., COVID-19 infected CT area segmentation, has attracted much attention. However, the publicly available COVID-19 training data are limited, easily causing overfitting for traditional deep learning methods that are usually data-hungry with millions of parameters. On the other hand, fast training/testing and low computational cost are also necessary for quick deployment and development of COVID-19 screening systems, but traditional deep learning methods are usually computationally intensive. To address the above problems, we propose MiniSeg, a lightweight deep learning model for efficient COVID-19 segmentation. Compared with traditional segmentation methods, MiniSeg has several significant strengths: i) it only has 83K parameters and is thus not easy to overfit; ii) it has high computational efficiency and is thus convenient for practical deployment; iii) it can be fast retrained by other users using their private COVID-19 data for further improving performance. In addition, we build a comprehensive COVID-19 segmentation benchmark for comparing MiniSeg to traditional methods.

Detection of 2019 novel coronavirus in semen and testicular biopsy specimen of COVID-19 patients (preprint)

Background: As of March 11, 2020, the COVID-19 outbreak was declared as a pandemic. Expending our understanding of the transmission routes of the viral infection is crucial in controlling the outbreak. It is unclear whether the 2019 novel coronavirus (2019-nCoV) can directly infect the testes or male genital tract and be sexually transmitted from males. Methods: From January 31 to March 14, 2020, 12 patients in recovery and one patient died of COVID-19 were included in this descriptive study. The clinical characteristics, laboratory findings, chest CT scans and outcome data were recorded. To examine whether there is sexual transmission from male, we employed realtime polymerase chain reaction testing (RT-PCR) to detect 2019-nCov in semen or testicular biopsy specimen. Findings: The age range of the 12 patients in recovery was 22-38 years. None of the patients developed severe COVID-19 pneumonia. As of March 14, 2020, ten patients discharged from the hospital while the rest 2 had developed into recovery stage. All of the patients in recovery tested negative for 2019-nCoV RNA in semen samples. Another died patient was 67 years old, who died in March 10, 2020 and tissue sample via testicular biopsy was tested negative for viral RNA. Conclusion: No positive RT-PCR result was found in the semen or testicular biopsy specimen. The results from this study show no evidence of sexual transmission of 2019-nCov from males.

A mathematical model for estimating the age-specific transmissibility of a novel coronavirus (preprint)

Background: A novel coronavirus named as "SARS-CoV-2" has spread widely in many countries since December 2019, especially in China. This study aimed to quantify the age-specific transmissibility by using a mathematical model. Methods: An age-specific susceptible - exposed - symptomatic - asymptomatic - recovered - seafood market (SEIARW) model was developed based on two suspected transmission routes (from market to person and person to person). The susceptible people from Wuhan City were divided into different age groups. We used the subscript i and j to represent age group 1 to 4 (1: <= 14 years; 2: 15-44 years; 3: 45-64 years; 4: >= 65 years) and 1 to 5 (1: <= 5 years; 2: 6-14 years; 3: 15-24 years; 4: 25-59 years; 4: >= 60 years), respectively. Data of reported COVID-19 cases were collected from one published literature from 26 November to 22 December, 2019 in Wuhan City, China. The age-specific transmissibility of the virus was estimated accordingly secondary attack rate (SAR). Results: The age-specific SEIARW model fitted with the reported data well by dividing the population into four age groups ({chi}2 = 4.99 x 10-6, P > 0.999), and five age groups ({chi}2 = 4.85 x 10-6, P > 0.999). Based on the four-age-group SEIARW model, the highest transmissibility occurred from age group 2 to 3 (SAR23 = 17.56 per 10 million persons), followed by from age group 3 to 2 (SAR32 = 10.17 per 10 million persons). The lowest transmissibility occurred from age group 1 to 2 (SAR12 = 0.002 per 10 million persons). Based on the five-age-group SEIARW model, the highest transmissibility occurred from age group 4 to 5 (SAR45 = 12.40 per 10 million persons), followed by from age group 5 to 4 (SAR54 = 6.61 per 10 million persons). The lowest transmissibility occurred from age group 3 to 4 (SAR34 = 0.0002 per 10 million persons). Conclusions: SARS-CoV-2 has high transmissibility among adults and elder people but low transmissibility among children and young people.