Telehealth Use Across Time and Regional Medical Resources During the COVID-19 Pandemic: Evidence from China.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has created lots of difficulties for individuals to seek medical help offline. Telehealth is considered as a potential approach to solve this issue. During the COVID-19 pandemic, although the use of telehealth has increased in the short term, it still remains unknown whether the use of telehealth can maintain a high level of development in the long term. The purpose of this article is to investigate the impact of COVID-19 pandemic on telehealth use across time and regional medical resources. Materials and Methods: Our research used the Internet search index from Baidu Index Platform in 31 provinces of China as the proxy of telehealth use. A total of 2,119,486 times of searching behaviors from January 2018 to December 2021 are included in our dataset. Changing plots, the method of analysis of variance and empirical models are applied to reveal the relationship between COVID-19 pandemic and telehealth use. Results: Baidu Index counts increased (p < 0.01) at the beginning of COVID-19 pandemic (2020) but started to decline (p < 0.01) during the period of regular epidemic prevention and control (2021). Moreover, the counts of Baidu Index in regions with rich medical resources are higher than those in other regions in 2020. Comparing Baidu Index counts in 2020, the COVID-19 pandemic has higher positive effects on telehealth use during the period of 2021 in regions with average and poor medical resources. Conclusions: COVID-19 pandemic has a positive effect on telehealth use in 2020 but has a negative effect in 2021. During the epidemic, telehealth use differs in regions with rich, average, and poor medical resources. Our findings indicate that the use of telehealth should be promoted with different measures in regions with different medical resources, thereby contributing its healthy development in the long term.

Kinetics of SARS-CoV-2 Specific and Neutralizing Antibodies over Seven Months after Symptom Onset in COVID-19 Patients.

To assess the persistence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies produced by natural infection and describe the serological characteristics over 7 months after symptom onset among coronavirus disease 2019 (COVID-19) patients by age and severity group, we followed up COVID-19 convalescent patients confirmed from 1 January to 20 March 2020 in Jiangsu, China and collected serum samples for testing IgM/IgG and neutralizing antibodies against SARS-CoV-2 between 26 August and 28 October 2020. In total, 284 recovered participants with COVID-19 were enrolled in our study. Patients had a mean age of 46.72 years (standard deviation [SD], 17.09), and 138 (48.59%) were male. The median follow-up time after symptom onset was 225.5 (interquartile range [IQR], 219 to 232) days. During the follow-up period (162 to 282 days after symptom onset), the seropositive rate of IgM fluctuated around 25.70% (95% confidence interval [CI], 20.72% to 31.20%) and that of IgG fluctuated around 79.93% (95% CI, 74.79% to 84.43%). Of the 284 patients, 64 participants were tested when discharged from hospital. Compared with that at the acute phase, the IgM/IgG antibody levels and IgM seropositivity have decreased; however, the seropositivity of IgG was not significantly lower at this follow-up (78.13% versus 82.81%). Fifty percent inhibitory dilution (ID50) titers of neutralizing antibody for samples when discharged from hospital (geometric mean titer [GMT], 82; 95% CI, 56 to 121) were significantly higher than those at 6 to 7 months after discharge (GMT, 47; 95% CI, 35 to 63) (P < 0.001). After 7 months from symptom onset, the convalescent COVID-19 patients continued to have high IgG seropositive; however, many plasma samples decreased neutralizing activity. IMPORTANCE The long-term characteristics of anti-SARS-CoV-2 antibodies among COVID-19 patients remain largely unclear. Tracking the longevity of these antibodies can provide a forward-looking reference for monitoring COVID-19. We conducted a comprehensive assessment combining the kinetics of specific and neutralizing antibodies over 7 months with age and disease severity and revealed influencing factors of the protection period of convalescent patients. By observing the long-term antibody levels against SARS-CoV-2 and comparing antibody levels at two time points after symptom onset, we found that the convalescent COVID-19 patients continued to have a high IgG seropositive rate; however, their plasma samples decreased neutralizing activity. These findings provide evidence supporting that the neutralizing activity of SARS-CoV-2-infected persons should be monitored and the administration of vaccine may be needed.

SARS-CoV-2 encoded microRNAs are involved in the process of virus infection and host immune response.

The outbreak of COVID-19 caused by SARS-CoV-2 is spreading worldwide, with the pathogenesis mostly unclear. Both virus and host-derived microRNA (miRNA) play essential roles in the pathology of virus infection. This study aims to uncover the mechanism for SARS-CoV-2 pathogenicity from the perspective of miRNA. We scanned the SARS-CoV-2 genome for putative miRNA genes and miRNA targets and conducted in vivo experiments to validate the virus-encoded miRNAs and their regulatory role on the putative targets. One of such virus-encoded miRNAs, MR147-3p, was overexpressed that resulted in significantly decreased transcript levels of all of the predicted targets in human, i.e., EXOC7, RAD9A, and TFE3 in the virus-infected cells. The analysis showed that the immune response and cytoskeleton organization are two of the most notable biological processes regulated by the infection-modulated miRNAs. Additionally, the genomic mutation of SARS-CoV-2 contributed to the changed miRNA repository and targets, suggesting a possible role of miRNAs in the attenuated phenotype of SARS-CoV-2 during its evolution. This study provided a comprehensive view of the miRNA-involved regulatory system during SARS-CoV-2 infection, indicating possible antiviral therapeutics against SARS-CoV-2 through intervening miRNA regulation.

Pre-diagnostic circulating concentrations of insulin-like growth factor-1 and risk of COVID-19 mortality: results from UK Biobank.

Coronavirus disease 2019 (COVID-19) deteriorates suddenly primarily due to excessive inflammatory injury, and insulin-like growth factor-1 (IGF-1) is implicated in endocrine control of the immune system. However, the effect of IGF-1 levels on COVID-19 prognosis remains unknown. Using UK Biobank resource, we investigated the association between circulating IGF-1 concentrations and mortality risk (available death data updated on 07 Sep 2020) among COVID-19 patients who had pre-diagnostic serum IGF-1 measurements at baseline (2006-2010). Unconditional logistic regression was performed to estimate the odds ratio (OR) and 95% confidence intervals (CIs) of mortality. Among 1670 COVID-19 patients, 415 deaths occurred due to COVID-19. Compared to the lowest quartile of IGF-1 concentrations, the highest quartile was associated with a 41% lower risk of mortality (OR = 0.59, 95% CI 0.41-0.86, P-trend = 0.01). In the continuous model, per 1-standard deviation increment in log-transformed IGF-1 was associated with a 15% reduction in the risk (intraclass correlation coefficients corrected OR = 0.85, 95% CI 0.73-0.99). The association was largely consistent in the various stratified and sensitivity analyses. In conclusion, our data suggest that higher IGF-1 concentrations are associated with a lower risk of COVID-19 mortality. Further studies are required to determine whether and how targeting IGF-1 pathway might improve COVID-19 prognosis.

Novel insight from the first lung transplant of a COVID-19 patient.

BACKGROUND: To reveal detailed histopathological changes, virus distributions, immunologic properties and multi-omic features caused by SARS-CoV-2 in the explanted lungs from the world's first successful lung transplantation of a COVID-19 patient. MATERIALS AND METHODS: A total of 36 samples were collected from the lungs. Histopathological features and virus distribution were observed by optical microscope and transmission electron microscope (TEM). Immune cells were detected by flow cytometry and immunohistochemistry. Transcriptome and proteome approaches were used to investigate main biological processes involved in COVID-19-associated pulmonary fibrosis. RESULTS: The histopathological changes of the lung tissues were characterized by extensive pulmonary interstitial fibrosis and haemorrhage. Viral particles were observed in the cytoplasm of macrophages. CD3+ CD4- T cells, neutrophils, NK cells, γ/δ T cells and monocytes, but not B cells, were abundant in the lungs. Higher levels of proinflammatory cytokines iNOS, IL-1ß and IL-6 were in the area of mild fibrosis. Multi-omics analyses revealed a total of 126 out of 20,356 significant different transcription and 114 out of 8,493 protein expression in lung samples with mild and severe fibrosis, most of which were related to fibrosis and inflammation. CONCLUSIONS: Our results provide novel insight that the significant neutrophil/ CD3+ CD4- T cell/ macrophage activation leads to cytokine storm and severe fibrosis in the lungs of COVID-19 patient and may contribute to a better understanding of COVID-19 pathogenesis.

Spatial statistical analysis of Coronavirus Disease 2019 (Covid-19) in China.

The cluster of pneumonia cases linked to coronavirus disease 2019 (Covid-19), first reported in China in late December 2019 raised global concern, particularly as the cumulative number of cases reported between 10 January and 5 March 2020 reached 80,711. In order to better understand the spread of this new virus, we characterized the spatial patterns of Covid-19 cumulative cases using ArcGIS v.10.4.1 based on spatial autocorrelation and cluster analysis using Global Moran's I (Moran, 1950), Local Moran's I and Getis-Ord General G (Ord and Getis, 2001). Up to 5 March 2020, Hubei Province, the origin of the Covid-19 epidemic, had reported 67,592 Covid-19 cases, while the confirmed cases in the surrounding provinces Guangdong, Henan, Zhejiang and Hunan were 1351, 1272, 1215 and 1018, respectively. The top five regions with respect to incidence were the following provinces: Hubei (11.423/10,000), Zhejiang (0.212/10,000), Jiangxi (0.201/10,000), Beijing (0.196/10,000) and Chongqing (0.186/10,000). Global Moran's I analysis results showed that the incidence of Covid-19 is not negatively correlated in space (p=0.407413>0.05) and the High-Low cluster analysis demonstrated that there were no high-value incidence clusters (p=0.076098>0.05), while Local Moran's I analysis indicated that Hubei is the only province with High-Low aggregation (p<0.0001).

Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing, China.

Previous studies have showed clinical characteristics of patients with the 2019 novel coronavirus disease (COVID-19) and the evidence of person-to-person transmission. Limited data are available for asymptomatic infections. This study aims to present the clinical characteristics of 24 cases with asymptomatic infection screened from close contacts and to show the transmission potential of asymptomatic COVID-19 virus carriers. Epidemiological investigations were conducted among all close contacts of COVID-19 patients (or suspected patients) in Nanjing, Jiangsu Province, China, from Jan 28 to Feb 9, 2020, both in clinic and in community. Asymptomatic carriers were laboratory-confirmed positive for the COVID-19 virus by testing the nucleic acid of the pharyngeal swab samples. Their clinical records, laboratory assessments, and chest CT scans were reviewed. As a result, none of the 24 asymptomatic cases presented any obvious symptoms while nucleic acid screening. Five cases (20.8%) developed symptoms (fever, cough, fatigue, etc.) during hospitalization. Twelve (50.0%) cases showed typical CT images of ground-glass chest and 5 (20.8%) presented stripe shadowing in the lungs. The remaining 7 (29.2%) cases showed normal CT image and had no symptoms during hospitalization. These 7 cases were younger (median age: 14.0 years; P=0.012) than the rest. None of the 24 cases developed severe COVID-19 pneumonia or died. The median communicable period, defined as the interval from the first day of positive nucleic acid tests to the first day of continuous negative tests, was 9.5 days (up to 21 days among the 24 asymptomatic cases). Through epidemiological investigation, we observed a typical asymptomatic transmission to the cohabiting family members, which even caused severe COVID-19 pneumonia. Overall, the asymptomatic carriers identified from close contacts were prone to be mildly ill during hospitalization. However, the communicable period could be up to three weeks and the communicated patients could develop severe illness. These results highlighted the importance of close contact tracing and longitudinally surveillance via virus nucleic acid tests. Further isolation recommendation and continuous nucleic acid tests may also be recommended to the patients discharged.