Spatiotemporal impacts of human activities and socio-demographics during the COVID-19 outbreak in the US.

BACKGROUND: Understanding non-epidemiological factors is essential for the surveillance and prevention of infectious diseases, and the factors are likely to vary spatially and temporally as the disease progresses. However, the impacts of these influencing factors were primarily assumed to be stationary over time and space in the existing literature. The spatiotemporal impacts of mobility-related and social-demographic factors on disease dynamics remain to be explored. METHODS: Taking daily cases data during the coronavirus disease 2019 (COVID-19) outbreak in the US as a case study, we develop a mobility-augmented geographically and temporally weighted regression (M-GTWR) model to quantify the spatiotemporal impacts of social-demographic factors and human activities on the COVID-19 dynamics. Different from the base GTWR model, the proposed M-GTWR model incorporates a mobility-adjusted distance weight matrix where travel mobility is used in addition to the spatial adjacency to capture the correlations among local observations. RESULTS: The results reveal that the impacts of social-demographic and human activity variables present significant spatiotemporal heterogeneity. In particular, a 1% increase in population density may lead to 0.63% more daily cases, and a 1% increase in the mean commuting time may result in 0.22% increases in daily cases. Although increased human activities will, in general, intensify the disease outbreak, we report that the effects of grocery and pharmacy-related activities are insignificant in areas with high population density. And activities at the workplace and public transit are found to either increase or decrease the number of cases, depending on particular locations. CONCLUSIONS: Through a mobility-augmented spatiotemporal modeling approach, we could quantify the time and space varying impacts of non-epidemiological factors on COVID-19 cases. The results suggest that the effects of population density, socio-demographic attributes, and travel-related attributes will differ significantly depending on the time of the pandemic and the underlying location. Moreover, policy restrictions on human contact are not universally effective in preventing the spread of diseases.

COVIDFast™: A high-throughput and RNA extraction-free method for SARS-CoV-2 detection in swab (SwabFAST™) or saliva (SalivaFAST™) (preprint)

ABSTRACT There is an urgent need of having a rapid, high throughput, yet accurate SARS-COV-2 PCR testing to control the COVID19 pandemic. However, the RNA extraction step in conventional PCR creates a major bottle neck in the diagnostic process. In this paper we modified the CDC COVID-19 assay and developed an RNA-extraction free RT-qPCR assay for SARS-CoV-2, i.e. COVIDFast ™ . Depending on sample types, the assay is further divided into SwabFAST ™ , which uses anterior nares nasal swab, and SalivaFAST ™ , which uses saliva. By utilizing the proprietary buffer for either swab or saliva samples, the performance of SwabFAST or SalivaFAST is equivalent to RNA-extraction SARS-CoV-2 RT-qPCR in both contrived and clinical samples. The limit of detection of either assay is 4 copies/μL. We further developed a semi-automatic system, which is easy to adapt by clinical lab for implementation of a high-throughput SARS-CoV-2 test. Working together with the COVIDCheck Colorado, we have tested over 400,000 samples using COVIDFast (83.62% SwabFAST and 16.38% SalivaFAST) in less than a year, resulting in significant clinical contribution in the battle against COVID-19 during the pandemic.

The Effectiveness of Far-Ultraviolet (UVC) Light Prototype Devices with Different Wavelengths on Disinfecting SARS-CoV-2

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as a serious threat to human health worldwide. The inactivation of SARS-CoV-2 on object surfaces and in the indoor air might help to halt the COVID-19 pandemic. Far-ultraviolet light (UVC) disinfection has been proven to be highly effective against viruses and bacteria. To understand the wavelength and duration of UVC radiation required for SARS-CoV-2 inactivation, we examined the efficacy of UVC light prototype devices with the wavelengths of 275, 254, and 222 nm. The disinfection effectiveness was determined by cell-based assays including the median tissue culture infectious dose (TCID50) and an immunofluorescent assay on African green monkey kidney epithelial Vero E6 cells. Among the three prototypes, the UVC LED (275 nm) had the best virucidal activity with a log-reduction value (LRV) >6 after 10 s of exposure. The mercury lamp (254 nm) reached similar virucidal activity after 20 s of exposure. However, the excimer lamp (222 nm) showed limited anti-SARS-CoV-2 activity with a LRV < 2 after 40 s of exposure. Overall, in comparison, the UVC LED (275 nm) exhibited superior SARS-CoV-2 disinfection activity than the mercury lamp (254 nm) and the excimer lamp (222 nm).

SARS-CoV-2 viral load monitoring by extraction-free testing of saliva (preprint)

Real-time quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) remains the foundation of SARS-CoV-2 testing due to its accessibility, scalability, and superior assay performance. Variability in specimens and methods prevent standardization of RT-qPCR assays and reliable quantitative reporting to assess viral load. We developed an extraction-free RT-qPCR assay for detection of SARS-CoV-2 in saliva and monitored viral load until convalescence in COVID-19 patients. Comparison of 231 matched anterior nares swab and saliva specimens demonstrated that extraction-free testing of saliva has equivalent analytical and clinical assay performance compared to testing of RNA extracts from either anterior nares or saliva specimens. Analysis of specimen pairs revealed higher viral loads in the nasal cavity compared to the oral cavity, although this difference did not impact clinical sensitivity for COVID-19. Extraction-free testing of a combination specimen consisting of both nasal swab and saliva is also demonstrated. Assessment of viral load by RT-qPCR and parallel digital droplet PCR (ddPCR) revealed that cycle threshold (Ct) values less than approximately 30 correlated well with viral load, whereas Ct values greater than 30 correspond to low viral loads <10 copies/{micro}L. Therefore, extraction-free saliva testing maximizes testing efficiency without compromising assay performance and approximates viral loads >10 copies/{micro}L. This technology can facilitate high-throughput laboratory testing for SARS-CoV-2, monitor viral load in individual patients, and assess efficacy of therapies for COVID-19.

Implications of Liver Injury in Risk-Stratification and Management of Patients with COVID-19 (preprint)

BackgroundInfection with SARS-CoV-2 has been associated with liver dysfunction, aggravation of liver burden, and liver injury. This study aimed to assess the effects of liver injuries on the clinical outcomes of patients with COVID-19.MethodsA total of 1,564 patients with severe or critical COVID-19 from Huoshenshan Hospital, Wuhan, were enrolled. Chronic liver disease (CLD) was confirmed by consensus diagnostic criteria. Laboratory test results were compared between different groups. scRNA-seq data and bulk gene expression profiles were used to identify cell types associated with liver injury.ResultsA total of 10.98% of patients with severe or critical COVID-19 developed liver injury after admission that was associated with significantly higher rates of mortality (21.74%, p<0.001) and intensive care unit admission (26.71%, p<0.001). A pre-existing CLD was not associated with a higher risk. However, fatty liver disease and cirrhosis were associated with higher risks, supported by evidences from single cell and bulk transcriptome analysis that showed more TMPRSS2+ cells in these tissues. By generating a model, we were able to predict the risk and severity of liver injury during hospitalization.ConclusionWe demonstrate that liver injury occurring during therapy in patients with COVID-19 is significantly associated with the severity of disease and mortality, but the presence of CLD is not associated. We provide a risk-score model that can predict whether patients with COVID-19 will develop liver injury or proceed to higher risk stages during subsequent hospitalizations. These findings may prove beneficial for the clinical management of patients infected with SARS-CoV-2.