Assessing the Impacts of Meteorological Factors on COVID-19 Pandemic Using Generalized Estimating Equations

Background Meteorological factors have been proven to affect pathogens;both the transmission routes and other intermediate. Many studies have worked on assessing how those meteorological factors would influence the transmissibility of COVID-19. In this study, we used generalized estimating equations to evaluate the impact of meteorological factors on Coronavirus disease 2019 (COVID-19) by using three outcome variables, which are transmissibility, incidence rate, and the number of reported cases. Methods In this study, the data on the daily number of new cases and deaths of COVID-19 in 30 provinces and cities nationwide were obtained from the provincial and municipal health committees, while the data from 682 conventional weather stations in the selected provinces and cities were obtained from the website of the China Meteorological Administration. We built a Susceptible-Exposed-Symptomatic-Asymptomatic-Recovered/Removed (SEIAR) model to fit the data, then we calculated the transmissibility of COVID-19 using an indicator of the effective reproduction number (Reff). To quantify the different impacts of meteorological factors on several outcome variables including transmissibility, incidence rate, and the number of reported cases of COVID-19, we collected panel data and used generalized estimating equations. We also explored whether there is a lag effect and the different times of meteorological factors on the three outcome variables. Results Precipitation and wind speed had a negative effect on transmissibility, incidence rate, and the number of reported cases, while humidity had a positive effect on them. The higher the temperature, the lower the transmissibility. The temperature had a lag effect on the incidence rate, while the remaining five meteorological factors had immediate and lag effects on the incidence rate and the number of reported cases. Conclusion Meteorological factors had similar effects on incidence rate and number of reported cases, but different effects on transmissibility. Temperature, relative humidity, precipitation, sunshine hours, and wind speed had immediate and lag effects on transmissibility, but with different lag times. An increase in temperature may first cause a decrease in virus transmissibility and then lead to a decrease in incidence rate. Also, the mechanism of the role of meteorological factors in the process of transmissibility to incidence rate needs to be further explored.

Ruxolitinib attenuates secondary injury after traumatic spinal cord injury.

Excessive inflammation post-traumatic spinal cord injury (SCI) induces microglial activation, which leads to prolonged neurological dysfunction. However, the mechanism underlying microglial activation-induced neuroinflammation remains poorly understood. Ruxolitinib (RUX), a selective inhibitor of JAK1/2, was recently reported to inhibit inflammatory storms caused by SARS-CoV-2 in the lung. However, its role in disrupting inflammation post-SCI has not been confirmed. In this study, microglia were treated with RUX for 24 hours and then activated with interferon-γ for 6 hours. The results showed that interferon-γ-induced phosphorylation of JAK and STAT in microglia was inhibited, and the mRNA expression levels of pro-inflammatory cytokines tumor necrosis factor-α, interleukin-1ß, interleukin-6, and cell proliferation marker Ki67 were reduced. In further in vivo experiments, a mouse model of spinal cord injury was treated intragastrically with RUX for 3 successive days, and the findings suggest that RUX can inhibit microglial proliferation by inhibiting the interferon-γ/JAK/STAT pathway. Moreover, microglia treated with RUX centripetally migrated toward injured foci, remaining limited and compacted within the glial scar, which resulted in axon preservation and less demyelination. Moreover, the protein expression levels of tumor necrosis factor-α, interleukin-1ß, and interleukin-6 were reduced. The neuromotor function of SCI mice also recovered. These findings suggest that RUX can inhibit neuroinflammation through inhibiting the interferon-γ/JAK/STAT pathway, thereby reducing secondary injury after SCI and producing neuroprotective effects.

Total Infectomes Characterization of Respiratory Infections in pre-COVID-19 Wuhan, China (preprint)

At the end of 2019 Wuhan witnessed an outbreak of “atypical pneumonia” that later developed into a global pandemic. Metagenomic sequencing rapidly revealed the causative agent of this outbreak to be a novel coronavirus - SARS-CoV-2. Herein, to provide a snapshot of the pathogens in pneumonia-associated respiratory samples from Wuhan prior to the emergence of SARS-CoV-2, we collected bronchoalveolar lavage fluid samples from 408 patients presenting with pneumonia and acute respiratory infections at the Central Hospital of Wuhan between 2016 and 2017. Unbiased total RNA sequencing was performed to reveal their “total infectome”, including viruses, bacteria and fungi. Consequently, we identified 37 pathogen species, comprising 15 RNA viruses, 3 DNA viruses, 16 bacteria and 3 fungi, often at high abundance and including multiple co-infections (12.8%). However, SARS-CoV-2 was not present. These data depict a stable core infectome comprising common respiratory pathogens such as rhinoviruses and influenza viruses, an atypical respiratory virus (EV-D68), and a single case of a sporadic zoonotic pathogen – Chlamydia psittaci . Samples from patients experiencing respiratory disease on average had higher pathogen abundance than healthy controls. Phylogenetic analyses of individual pathogens revealed multiple origins and global transmission histories, highlighting the connectedness of the Wuhan population. This study provides a comprehensive overview of the pathogens associated with acute respiratory infections and pneumonia, which were more diverse and complex than obtained using targeted PCR or qPCR approaches. These data also suggest that SARS-CoV-2 or closely related viruses were absent from Wuhan in 2016-2017.

Seven Principles for Rapid-Response Data Science: Lessons Learned from Covid-19 Forecasting (preprint)

In this article, we take a step back to distill seven principles out of our experience in the spring of 2020, when our 12-person rapid-response team used skills of data science and beyond to help distribute Covid PPE. This process included tapping into domain knowledge of epidemiology and medical logistics chains, curating a relevant data repository, developing models for short-term county-level death forecasting in the US, and building a website for sharing visualization (an automated AI machine). The principles are described in the context of working with Response4Life, a then-new nonprofit organization, to illustrate their necessity. Many of these principles overlap with those in standard data-science teams, but an emphasis is put on dealing with problems that require rapid response, often resembling agile software development.

The change of atmospheric ozone formation sensitivity in Fujian Province based on OMI satellite data during the period of COVID-19

Based on the OMI satellite data, the characteristics of atmospheric ozone sensitivity in Fujian province and its nice municipalities during the period of COVID-19 epidemic were assessed with HCHO and NO2 vertical column densities as proxies for ozone sensitivity. The results showed that Fujian Province was dominated by VOCs-limited regime before the pandemic with the controlled area proportion of 46.5%. The other two regimes: NOx-VOCs-limited regime and NOx-limited regime, controlled 25.0% and 28.5% of the area, respectively. The area proportion controlled by VOXs-limited regime was highest in Xiamen and lowest in Nanping. During the period with strict pandemic control policies, VOXs-limited regime, NOx-VOCs-limited regime and NOx-limited regime controlled 29.5%, 21.1%, and 49.4% of the area, respectively. The area proportion controlled by NOx-limited regime was highest in Ningde and lowest in Putian. During the stable period, VOXs-limited regime, NOx-VOCs-limited regime and NOx-limited regime controlled 23.1%, 29.1%, and 47.8% of the area, respectively. NOx-limited regime was the dominant regime with highest area proportion controlled in Nanping and lowest area proportion in Xiamen. Compared with the before pandemic period, the area proportion of Xiamen controlled by VOCs-limited regime was obviously reduced（38.1% less） during the period with strict control policies, and the lowest reduction was in Sanming with a moderate decrease of 7.9%. According to the conversion results, Putian, Quanzhou, and Xiamen were categorized into the first city group where changes in ozone sensitivity were jointly influenced by its precursors including formaldehyde（HCHO） and nitrogen dioxide（NO2）, while other cities could be categorized into the second group where ozone sensitivities were mainly affected by NO2 column concentrations. Therefore, effective strategies for ozone reduction would be more complex in the first group of cities.

Curating a COVID-19 data repository and forecasting county-level death counts in the United States (preprint)

As the COVID-19 outbreak evolves, accurate forecasting continues to play an extremely important role in informing policy decisions. In this paper, we present our continuous curation of a large data repository containing COVID-19 information from a range of sources. We use this data to develop predictions and corresponding prediction intervals for the short-term trajectory of COVID-19 cumulative death counts at the county-level in the United States up to two weeks ahead. Using data from January 22 to June 20, 2020, we develop and combine multiple forecasts using ensembling techniques, resulting in an ensemble we refer to as Combined Linear and Exponential Predictors (CLEP). Our individual predictors include county-specific exponential and linear predictors, a shared exponential predictor that pools data together across counties, an expanded shared exponential predictor that uses data from neighboring counties, and a demographics-based shared exponential predictor. We use prediction errors from the past five days to assess the uncertainty of our death predictions, resulting in generally-applicable prediction intervals, Maximum (absolute) Error Prediction Intervals (MEPI). MEPI achieves a coverage rate of more than 94% when averaged across counties for predicting cumulative recorded death counts two weeks in the future. Our forecasts are currently being used by the non-profit organization, Response4Life, to determine the medical supply need for individual hospitals and have directly contributed to the distribution of medical supplies across the country. We hope that our forecasts and data repository at https://covidseverity.com can help guide necessary county-specific decision-making and help counties prepare for their continued fight against COVID-19.

Thinking of treatment strategies for colorectal cancer patients in tumor hospitals under the background of coronavirus pneumonia / 中华胃肠外科杂志

In December 2019, a new outbreak of coronavirus pneumonia began to occur. Its pathogen is 2019-nCoV, which has the characteristics of strong infectivity and general susceptibility. The current situation of prevention and control of new coronavirus pneumonia is severe. In this context, as front-line medical workers bearing important responsibilities and pressure, while through strict management strategy, we can minimize the risk of infection exposure. By summarizing the research progress and guidelines in recent years in the fields of colorectal cancer disease screening, treatment strategies(including early colorectal cancer, locally advanced colorectal cancer, obstructive colorectal cancer, metastatic colorectal cancer and the treatment of patients after neoadjuvant therapy), the choice of medication and time limit for adjuvant therapy, the protective measures for patients undergoing emergency surgery, the re-examination of postoperative patients and the protection of medical staff, etc., authors improve treatment strategies in order to provide more choices for patients to obtain the best treatment under the severe epidemic situation of new coronavirus pneumonia. Meanwhile we hope that it can also provide more timely treatment modeling schemes for colleagues.

Methylene blue photochemical treatment as a reliable SARS-CoV-2 plasma virus inactivation method for blood safety and convalescent plasma therapy for the COVID-19 outbreak (preprint)

Background  With the outbreak of unknown pneumonia in Wuhan, China in December 2019, a new coronavirus (SARS-CoV-2) attracted worldwide attention. Although coronaviruses typically infect the upper or lower respiratory tract, discovery of the virus in plasma is common. Therefore, the risk of transmitting coronavirus through transfusion of blood products remains. As more asymptomatic infections are found in COVID-19 cases, blood safety is shown to be particularly important, especially in endemic areas. Study Design and MethodsBX-1, an ‘AIDS treatment instrument’ based on methylene blue (MB) photochemical technology, developed by Boxin (Beijing) Biotechnology Development LTD, has proven that inactivation of lipid-enveloped viruses such as HIV-1 in plasma has high efficiency, without damage to other components in the plasma, and proved safe and reliable in clinical trials of HIV treatment. In order to confirm the inactivation effect of BX-1 in SARS-CoV-2, we used the SARS-CoV-2 virus strain isolated from Zhejiang University for plasma virus inactivation studies. Results and ConclusionBX-1 can effectively eliminate SARS-CoV-2 within 2 mins, and the virus titer decline can reach 4.5 log10 TCID50/mL. Faced with the expanding epidemic, BX-1 is safe for blood transfusion and plasma transfusion therapy in recovery patients, and the inactivated vaccine preparation has great potential for treatment in the current outbreak.

Expert consensus on emergency surgery management for traumatic orthopedics under prevention and control of novel coronavirus pneumonia / 中华创伤杂志

Since December 2019, novel coronavirus pneumonia (NCP) has been reported in Wuhan, Hubei Province, and spreads rapidly to all through Hubei Province and even to the whole country. The virus is 2019 novel coronavirus (2019-nCoV), never been seen previously in human, but all the population is generally susceptible. The virus spreads through many ways and is highly infectious, which brings great difficulties to the prevention and control of NCP. Based on the needs of orthopedic trauma patients for emergency surgery and review of the latest NCP diagnosis and treatment strategy and the latest principles and principles of evidence-based medicine in traumatic orthopedics, the authors put forward this expert consensus to systematically standardize the clinical pathway and protective measures of emergency surgery for orthopedic trauma patients during prevention and control of NCP and provide reference for the emergency surgical treatment of orthopedic trauma patients in hospitals at all levels.

Complete genome characterisation of a novel coronavirus associated with severe human respiratory disease in Wuhan, China (preprint)

Emerging and re-emerging infectious diseases, such as SARS, MERS, Zika and highly pathogenic influenza present a major threat to public health1-3. Despite intense research effort, how, when and where novel diseases appear are still the source of considerable uncertainly. A severe respiratory disease was recently reported in the city of Wuhan, Hubei province, China. At the time of writing, at least 62 suspected cases have been reported since the first patient was hospitalized on December 12nd 2019. Epidemiological investigation by the local Center for Disease Control and Prevention (CDC) suggested that the outbreak was associated with a sea food market in Wuhan. We studied seven patients who were workers at the market, and collected bronchoalveolar lavage fluid (BALF) from one patient who exhibited a severe respiratory syndrome including fever, dizziness and cough, and who was admitted to Wuhan Central Hospital on December 26th 2019. Next generation metagenomic RNA sequencing4 identified a novel RNA virus from the family Coronaviridae designed WH-Human-1 coronavirus (WHCV). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that WHCV was most closely related (89.1% nucleotide similarity similarity) to a group of Severe Acute Respiratory Syndrome (SARS)-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) previously sampled from bats in China and that have a history of genomic recombination. This outbreak highlights the ongoing capacity of viral spill-over from animals to cause severe disease in humans.