Spatiotemporal transmission of infectious particles in environment: A case study of Covid-19.

This study explores the dynamic transmission of infectious particles due to COVID-19 in the environment using a spatiotemporal epidemiological approach. We proposed a novel multi-agent model to simulate the spread of COVID-19 by considering several influencing factors. The model divides the population into susceptible and infected and analyzes the impact of different prevention and control measures, such as limiting the number of people and wearing masks on the spread of COVID-19. The findings suggest that reducing population density and wearing masks can significantly reduce the likelihood of virus transmission. Specifically, the research shows that if the population moves within a fixed range, almost everyone will eventually be infected within 1 h. When the population density is 50%, the infection rate is as high as 96%. If everyone does not wear a mask, nearly 72.33% of the people will be infected after 1 h. However, when people wear masks, the infection rate is consistently lower than when they do not wear masks. Even if only 25% of people wear masks, the infection rate with masks is 27.67% lower than without masks, which is strong evidence of the importance of wearing a mask. As people's daily activities are mostly carried out indoors, and many super-spreading events of the new crown epidemic also originated from indoor gatherings, the research on indoor epidemic prevention and control is essential. This study provides decision-making support for epidemic preventions and controls and the proposed methodology can be used in other regions and future epidemics.

Trends of SARS-CoV-2 Infection Among Couriers in Risky Business After the Optimization of Prevention and Control Measures - China, December 2022 to January 2023.

Introduction: On December 7, 2022, China implemented "Ten New Measures" to optimize prevention and control measures for coronavirus disease 2019 (COVID-19). The purpose of this study was to evaluate the national and regional trends of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among couriers in China from December 2022 to January 2023. Methods: Data from the National Sentinel Community-based Surveillance in China was utilized, including participants from 31 provincial-level administrative divisions and Xinjiang Production and Construction Corps. Participants were tested for SARS-CoV-2 infection twice a week from December 16, 2022 to January 12, 2023. Infection was defined as a positive result for SARS-CoV-2 nucleic acid or antigen. The daily average newly positive rate of SARS-CoV-2 infection and the estimated daily percentage change (EDPC) were calculated. Results: In this cohort, 8 rounds of data were collected. The daily average newly positive rate of SARS-CoV-2 infection decreased from 4.99% in Round 1 to 0.41% in Round 8, with an EDPC of -33.0%. Similar trends of the positive rate were also observed in the eastern (EDPC: -27.7%), central (EDPC: -38.0%) and western regions (EDPC: -25.5%). Couriers and community population showed a similar temporal trend, with the peak daily average newly positive rate of couriers being higher than that of community population. After Round 2, the daily average newly positive rate of couriers decreased sharply, becoming lower than that of community population in the same period. Conclusions: The peak of SARS-CoV-2 infection among couriers in China has passed. As couriers are a key population for SARS-CoV-2 infection, they should be monitored continuously.

Trends of SARS-CoV-2 Infection in Sentinel Community-Based Surveillance After the Optimization of Prevention and Control Measures - China, December 2022-January 2023.

Introduction: On December 7, 2022, China implemented the "Ten New Measures" to optimize its prevention and control measures for coronavirus disease 2019 (COVID-19). To provide the latest data after the optimization, we evaluated trends of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among the community population in China. Methods: We utilized data from the National Sentinel Community-Based Surveillance (NSCS) system in China to assess trends of SARS-CoV-2 infection. NSCS is a national community-based surveillance cohort with 0.42 million participants from all 31 provincial-level administrative divisions (PLADs) and Xinjiang Production and Construction Corps (XPCC). Participants were tested for infection twice a week (a total of eight rounds) from December 16, 2022 to January 12, 2023. SARS-CoV-2 infection was defined as testing positive for SARS-CoV-2 nucleic acid or antigen. We calculated the daily average of newly positive rates of SARS-CoV-2 infection. Results: In this national cohort, the daily average newly positive rate of SARS-CoV-2 infection decreased from 4.13% in Round 1 (December 16-19, 2022) to 0.69% in Round 8 (January 10-12, 2023). The epidemic peak occurred in Round 2 (December 20-22, 2022). Similar trends were observed in urban areas (decreasing from 4.65% to 0.73%), rural areas (decreasing from 2.83% to 0.57%), the eastern region (decreasing from 4.18% to 0.67%), the central region (decreasing from 5.43% to 0.61%), and the western region (decreasing from 3.01% to 0.77%). Conclusions: NSCS data showed that the peak of SARS-CoV-2 infection in China had passed. SARS-CoV-2 infection in community populations in China is currently at a low epidemic level.

Trends of SARS-CoV-2 Infection in Rural Area in Sentinel Community-Based Surveillance - China, December 2022 to January 2023.

Introduction: In late 2022, a rapid transmission of Omicron variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurred throughout China. The purpose of this study was to provide the latest data and evaluate trends of SARS-CoV-2 infection in rural China among the community population. Methods: Data on SARS-CoV-2 infection among approximately 90,000 participants in rural China were collected by the National Sentinel Community-Based Surveillance (NSCS) system. Participants were tested for SARS-CoV-2 infection (defined as positive for SARS-CoV-2 nucleic acid or antigen) twice weekly from December 16, 2022 to January 12, 2023. The daily average of newly positive rate and its estimated daily percentage change were calculated to describe the national and regional trends of SARS-CoV-2 infection in rural China. Results: In rural China, the daily average new positive rate of SARS-CoV-2 infection peaked at 4.79% between December 20-22, 2022 and then decreased to 0.57% between January 10-12, 2023, with an average decrease of 29.95% per round. The peak of new SARS-CoV-2 infection was slightly earlier and lower in North China (5.28% between December 20-22, 2022) than in South China (5.63% between December 23-26, 2022), and then converged from December 30, 2022 to January 2, 2023. The peak of 6.09% occurred between December 20-22, 2022 in eastern China, while the peak of 5.99% occurred later, between December 27-29, 2022, in central China. Conclusions: Overall, the epidemic wave in rural China peaked between December 20-22, 2022, and passed quickly following the optimization of prevention and control measures. Currently, SARS-CoV-2 infection in community populations in rural China is sporadic.

Portable nanopore-sequencing technology: Trends in development and applications.

Sequencing technology is the most commonly used technology in molecular biology research and an essential pillar for the development and applications of molecular biology. Since 1977, when the first generation of sequencing technology opened the door to interpreting the genetic code, sequencing technology has been developing for three generations. It has applications in all aspects of life and scientific research, such as disease diagnosis, drug target discovery, pathological research, species protection, and SARS-CoV-2 detection. However, the first- and second-generation sequencing technology relied on fluorescence detection systems and DNA polymerization enzyme systems, which increased the cost of sequencing technology and limited its scope of applications. The third-generation sequencing technology performs PCR-free and single-molecule sequencing, but it still depends on the fluorescence detection device. To break through these limitations, researchers have made arduous efforts to develop a new advanced portable sequencing technology represented by nanopore sequencing. Nanopore technology has the advantages of small size and convenient portability, independent of biochemical reagents, and direct reading using physical methods. This paper reviews the research and development process of nanopore sequencing technology (NST) from the laboratory to commercially viable tools; discusses the main types of nanopore sequencing technologies and their various applications in solving a wide range of real-world problems. In addition, the paper collates the analysis tools necessary for performing different processing tasks in nanopore sequencing. Finally, we highlight the challenges of NST and its future research and application directions.

Decline of onset-to-diagnosis interval and its impacts on clinical outcome of COVID-19 in China: a nation-wide observational study.

BACKGROUND: To quantitatively assess the impact of the onset-to-diagnosis interval (ODI) on severity and death for coronavirus disease 2019 (COVID-19) patients. METHODS: This retrospective study was conducted based on the data on COVID-19 cases of China over the age of 40 years reported through China's National Notifiable Infectious Disease Surveillance System from February 5, 2020 to October 8, 2020. The impacts of ODI on severe rate (SR) and case fatality rate (CFR) were evaluated at individual and population levels, which was further disaggregated by sex, age and geographic origin. RESULTS: As the rapid decline of ODI from around 40 days in early January to < 3 days in early March, both CFR and SR of COVID-19 largely dropped below 5% in China. After adjusting for age, sex, and region, an effect of ODI on SR was observed with the highest OR of 2.95 (95% CI 2.37‒3.66) at Day 10-11 and attributable fraction (AF) of 29.1% (95% CI 22.2‒36.1%) at Day 8-9. However, little effect of ODI on CFR was observed. Moreover, discrepancy of effect magnitude was found, showing a greater effect from ODI on SR among patients of male sex, younger age, and those cases in Wuhan. CONCLUSION: The ODI was significantly associated with the severity of COVID-19, highlighting the importance of timely diagnosis, especially for patients who were confirmed to gain increased benefit from early diagnosis to some extent.

Analysis of Factors Influencing the Corporate Performance of Listed Companies in China's Agriculture and Forestry Sector Based on a Panel Threshold Model

The global food crisis caused by COVID-19 and the Russia-Ukraine conflict have made many countries around the world realize the significance of agroforestry to a country's food security. However, China's agroforestry R&D innovation is currently lagging behind in development, and some agricultural seeds are heavily dependent on foreign countries, which seriously affects China's national food security. It is especially important to explore the reasons why China's agroforestry R&D and innovation is lagging behind. As listed agroforestry companies face the market demand directly, there is an urgent need to study the R&D innovations of listed agroforestry companies at present. This paper analyzes the impacts of R&D innovation, corporate management and supply chain management on the corporate performance of listed agroforestry companies using the entropy weighting method, GMM estimation and panel threshold model, mainly by selecting annual panel data from CSMAR for the period 2010 to 2021. The following conclusions were drawn: (1) There is a nonlinear relationship between R&D innovation and firm performance, and a 'U';-shaped relationship. This indicates that there is an entrance threshold for R&D innovation in the agroforestry industry, below which corporate performance does not improve. (2) There is a nonlinear relationship between corporate management and corporate performance, and a U-shaped relationship. (3) There is a nonlinear relationship between supply chain management and firm performance, with an inverted-U-shaped relationship. This paper explains the reasons for the slow development of R&D innovation in China's agriculture and forestry industry and fills the gap in the theoretical study of the nonlinear relationship between R&D innovation and corporate performance of listed companies in China's agriculture and forestry industry. Finally, this paper provides a theoretical basis for the decision making of government departments related to agriculture and forestry, and offers some suggestions for listed companies in agriculture and forestry to improve their corporate performance.

Children with type 1 diabetes in COVID-19 pandemic: Difficulties and solutions.

Children/adolescents with type 1 diabetes (T1D) require holistic approach and continuous care. However, the coronavirus disease 2019 (COVID-19) pandemic has made challenges for the T1D children and their caregivers, professionals, and the healthcare system. This minireview aims to consolidate and discuss the difficulties and solutions of children with type 1 diabetes in the COVID-19 pandemic. T1D has been the most common type of diabetes in children and adolescents and the last decades has seen a rapid increase in the prevalence of T1D in youths worldwide, which deserves a public concern particularly in the COVID-19 pandemic. As reported in previous studies, T1D is a risk factor related to severe cases, while the virus may induce new-onset diabetes and serious complications. Moreover, restriction strategies influence medical availability and lifestyle, impact glycemic control and compilation management, and thus pose stress on families and health providers of youths with T1D, especially on those with certain fragile conditions. Therefore, special treatment plans are required for children provided by caregivers and the local health system. Latest health tools such as improved medical devices and telemedicine service, as well as a combined support may benefit in this period. This minireview emphasises that continued medical access and support are required to prevent deteriorated condition of children and adolescents with diabetes throughout this pandemic. Therefore, strategies are supposed to be formulated to mitigate the difficulties and stress among this group, particularly in the most at-risk population. Proposed solutions in this minireview may help individuals and the health system to overcome these problems and help youths with T1D in better diabetes management during such emergency situations.

Hepatitis B virus (HBV) codon adapts well to the gene expression profile of liver cancer: an evolutionary explanation for HBV's oncogenic role.

Due to the evolutionary arms race between hosts and viruses, viruses must adapt to host translation systems to rapidly synthesize viral proteins. Highly expressed genes in hosts have a codon bias related to tRNA abundance, the primary RNA translation rate determinant. We calculated the relative synonymous codon usage (RSCU) of three hepatitis viruses (HAV, HBV, and HCV), SARS-CoV-2, 30 human tissues, and hepatocellular carcinoma (HCC). After comparing RSCU between viruses and human tissues, we calculated the codon adaptation index (CAI) of viral and human genes. HBV and HCV showed the highest correlations with HCC and the normal liver, while SARS-CoV-2 had the strongest association with lungs. In addition, based on HCC RSCU, the CAI of HBV and HCV genes was the highest. HBV and HCV preferentially adapt to the tRNA pool in HCC, facilitating viral RNA translation. After an initial trigger, rapid HBV/HCV translation and replication may change normal liver cells into HCC cells. Our findings reveal a novel perspective on virus-mediated oncogenesis.

Mathematical Models Supporting Control of COVID-19.

Mathematical models have played an important role in the management of the coronavirus disease 2019 (COVID-19) pandemic. The aim of this review is to describe the use of COVID-19 mathematical models, their classification, and the advantages and disadvantages of different types of models. We conducted subject heading searches of PubMed and China National Knowledge Infrastructure with the terms "COVID-19," "Mathematical Statistical Model," "Model," "Modeling," "Agent-based Model," and "Ordinary Differential Equation Model" and classified and analyzed the scientific literature retrieved in the search. We categorized the models as data-driven or mechanism-driven. Data-driven models are mainly used for predicting epidemics, and have the advantage of rapid assessment of disease instances. However, their ability to determine transmission mechanisms is limited. Mechanism-driven models include ordinary differential equation (ODE) and agent-based models. ODE models are used to estimate transmissibility and evaluate impact of interventions. Although ODE models are good at determining pathogen transmission characteristics, they are less suitable for simulation of early epidemic stages and rely heavily on availability of first-hand field data. Agent-based models consider influences of individual differences, but they require large amounts of data and can take a long time to develop fully. Many COVID-19 mathematical modeling studies have been conducted, and these have been used for predicting trends, evaluating interventions, and calculating pathogen transmissibility. Successful infectious disease modeling requires comprehensive considerations of data, applications, and purposes.

Ecology of Middle East respiratory syndrome coronavirus, 2012-2020: A machine learning modelling analysis.

The ongoing enzootic circulation of the Middle East respiratory syndrome coronavirus (MERS-CoV) in the Middle East and North Africa is increasingly raising the concern about the possibility of its recombination with other human-adapted coronaviruses, particularly the pandemic SARS-CoV-2. We aim to provide an updated picture about ecological niches of MERS-CoV and associated socio-environmental drivers. Based on 356 confirmed MERS cases with animal contact reported to the WHO and 63 records of animal infections collected from the literature as of 30 May 2020, we assessed ecological niches of MERS-CoV using an ensemble model integrating three machine learning algorithms. With a high predictive accuracy (area under receiver operating characteristic curve = 91.66% in test data), the ensemble model estimated that ecologically suitable areas span over the Middle East, South Asia and the whole North Africa, much wider than the range of reported locally infected MERS cases and test-positive animal samples. Ecological suitability for MERS-CoV was significantly associated with high levels of bareland coverage (relative contribution = 30.06%), population density (7.28%), average temperature (6.48%) and camel density (6.20%). Future surveillance and intervention programs should target the high-risk populations and regions informed by updated quantitative analyses.

Comparison of epidemiological characteristics and transmissibility of different strains of COVID-19 based on the incidence data of all local outbreaks in China as of March 1, 2022

Background The epidemiological characteristics and transmissibility of Coronavirus Disease 2019 (COVID-19) may undergo changes due to the mutation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) strains. The purpose of this study is to compare the differences in the outbreaks of the different strains with regards to aspects such as epidemiological characteristics, transmissibility, and difficulties in prevention and control. Methods COVID-19 data from outbreaks of pre-Delta strains, the Delta variant and Omicron variant, were obtained from the Chinese Center for Disease Control and Prevention (CDC). Case data were collected from China's direct-reporting system, and the data concerning outbreaks were collected by on-site epidemiological investigators and collated by the authors of this paper. Indicators such as the effective reproduction number (Reff), time-dependent reproduction number (Rt), rate of decrease in transmissibility (RDT), and duration from the illness onset date to the diagnosed date (DID)/reported date (DIR) were used to compare differences in transmissibility between pre-Delta strains, Delta variants and Omicron variants. Non-parametric tests (namely the Kruskal-Wallis H and Mean-Whitney U tests) were used to compare differences in epidemiological characteristics and transmissibility between outbreaks of different strains. P < 0.05 indicated that the difference was statistically significant. Results Mainland China has maintained a “dynamic zero-out strategy” since the first case was reported, and clusters of outbreaks have occurred intermittently. The strains causing outbreaks in mainland China have gone through three stages: the outbreak of pre-Delta strains, the outbreak of the Delta variant, and outbreaks involving the superposition of Delta and Omicron variant strains. Each outbreak of pre-Delta strains went through two stages: a rising stage and a falling stage, Each outbreak of the Delta variant and Omicron variant went through three stages: a rising stage, a platform stage and a falling stage. The maximum Reff value of Omicron variant outbreaks was highest (median: 6.7;ranged from 5.3 to 8.0) and the differences were statistically significant. The RDT value of outbreaks involving pre-Delta strains was smallest (median: 91.4%;[IQR]: 87.30–94.27%), and the differences were statistically significant. The DID and DIR for all strains was mostly in a range of 0–2 days, with more than 75%. The range of duration for outbreaks of pre-Delta strains was the largest (median: 20 days, ranging from 1 to 61 days), and the differences were statistically significant. Conclusion With the evolution of the virus, the transmissibility of the variants has increased. The transmissibility of the Omicron variant is higher than that of both the pre-Delta strains and the Delta variant, and is more difficult to suppress. These findings provide us with get a more clear and precise picture of the transmissibility of the different variants in the real world, in accordance with the findings of previous studies. Reff is more suitable than Rt for assessing the transmissibility of the disease during an epidemic outbreak.

The role of selenium in severe fever with thrombocytopenia syndrome: an integrative analysis of surveillance data and clinical data.

OBJECTIVES: Selenium deficiency can be associated with increased susceptibility to some viral infections and even more severe diseases. In this study, we aimed to examine whether this association applies to severe fever with thrombocytopenia syndrome (SFTS). METHOD: An observational study was conducted based on the data of 13,305 human SFTS cases reported in mainland China from 2010 to 2020. The associations among incidence, case fatality rate of SFTS, and crop selenium concentration at the county level were explored. The selenium level in a cohort of patients with SFTS was tested, and its relationship with clinical outcomes was evaluated. RESULTS: The association between selenium-deficient crops and the incidence rate of SFTS was confirmed by multivariate Poisson analysis, with an estimated incidence rate ratio (IRR, 95% confidence interval [CI]) of 4.549 (4.215-4.916) for moderate selenium-deficient counties and 16.002 (14.706-17.431) for severe selenium-deficient counties. In addition, a higher mortality rate was also observed in severe selenium-deficient counties with an IRR of 1.409 (95% CI: 1.061-1.909). A clinical study on 120 patients with SFTS showed an association between serum selenium deficiency and severe SFTS (odds ratio, OR: 2.94; 95% CI: 1.00-8.67) or fatal SFTS (OR: 7.55; 95% CI: 1.14-50.16). CONCLUSION: Selenium deficiency is associated with increased susceptibility to SFTS and poor clinical outcomes.

[Analysis of the Characteristics of the Outcomes of Job-Transfer Subspecialty Training Program in Pediatrics in Sichuan].

Objective: To discuss the characteristics of physician trainee outcomes after completion of the job-transfer subspecialty training in pediatrics, a program designed to increase the number of pediatricians, in Sichuan Province and to provide countermeasures for alleviating the shortage of pediatricians. Methods: We collected with questionnaire surveys information on changes in the workload and salaries experienced by physicians who completed the job-transfer subspecialty training program in pediatrics between February 2017 and May 2020 in Sichuan Province. Then, we compared the characteristics of physicians who successful became pediatricians and those who did no. Results: A total of 208 physicians completed the job-transfer subspecialty training program in pediatrics. Among them, 178, accounting for 85.6%, completed the questionnaire survey, and 120, accounting for 67.4%, had a background in other subspecialties than pediatrics. The majority (>90%) of physicians who participated in the training program came from secondary or lower levels of hospitals from the cities and prefectures all over Sichuan Province. In this study, we found that the rate of successful job transfer from being a physician to being a pediatrician in Sichuan Province in the past four years was 85.0% (102/120), with the year-by-year results being 88.2% (15/17) in 2017, 72.7% (16/22) in 2018, 86.7% (39/45) in 2019, and 94.% (32/34) in 2020. There was no significant difference between physicians who had successful job transfer and became pediatricians and those who failed to do so in terms of gender, age, hospital level, specialization prior to the job transfer, whether or not the hospital had a pediatrics department, amount of support for the pediatrics department, whether or not the physician was working at a new hospital after the job transfer, salaries, and changes of responsibilities during COVID-19 (all P>0.05). There was significant difference in the change of workload after completion of the training program between physicians who had successful job transfer and became pediatricians and those who failed to do so ( χ 2=9.037, P=0.003), and 78.4% of the trainees stated that their workload had increased after the job transfer. There was a moderate correlation between successful job transfer and changes in workload after the transfer (|Phi[ψ] |=0.729). Conclusions: The policy of government-supported job-transfer subspecialty training in pediatrics has played an active and important role in the swift resolution of the shortage of pediatricians. However, finding the root cause of and addressing the problem of the overwhelming workload of pediatricians remain challenging issues to be resolved.

Asymmetric Effects of Economic Development, Agroforestry Development, Energy Consumption, and Population Size on CO2 Emissions in China

The COVID-19 epidemic and the Russian–Ukrainian conflict have led to a global food and energy crisis, making the world aware of the importance of agroforestry development for a country. Modern agriculture mechanization leads to massive energy consumption and increased CO2 emissions. At the same time, China is facing serious demographic problems and a lack of consumption in the domestic market. The Chinese government is faced with the dilemma of balancing environmental protection with economic development in the context of the “double carbon” strategy. This article uses annual World Bank statistics from 1990 to 2020 to study the asymmetric relationships between agroforestry development, energy consumption, population size, and economic development on CO2 emissions in China using the partial least squares path model (PLS-PM), the autoregressive VAR vector time series model, and the Granger causality test. The results are as follows: (1) The relationship between economic development and carbon dioxide emissions, agroforestry development and carbon dioxide emissions, energy consumption and carbon dioxide emissions, and population size and carbon dioxide emissions are both direct and indirect, with an overall significant positive effect. There is a direct negative relationship between population size and carbon dioxide emissions. (2) The results of the Granger causality test show that economic development, energy consumption, and CO2 emissions are the causes of the development of agroforestry;economic development, agroforestry development, population size, and CO2 emissions are the causes of energy consumption;energy consumption is the cause of economic development and CO2 emissions;and agroforestry development is the cause of population size and energy consumption. (3) In the next three years, China’s agroforestry development will be influenced by the impulse response of economic development, energy consumption, and CO2 emission factors, showing a decreasing development trend. China’s energy consumption will be influenced by the impulse response of economic development, agroforestry development, population size, and CO2 emission factors, showing a decreasing development trend, followed by an increasing development trend. China’s CO2 emission will be influenced by the impulse response of energy consumption and agroforestry development. China’s CO2 emissions will be influenced by the impulse response of energy consumption and agroforestry development factors, showing a downward and then an upward development trend.

Thrombocytopenia and increased risk of adverse outcome in COVID-19 patients.

Background: Thrombocytopenia was common in the coronavirus disease 2019 (COVID-19) patients during the infection, while the role of thrombocytopenia in COVID-19 pathogenesis and its relationship with systemic host response remained obscure. The study aimed to systematically evaluate the relationship between thrombocytopenia in COVID-19 patients and clinical, haematological and biochemical markers of the disease as well as adverse outcomes. Methods: To assess the relationship between abnormal platelet levels and disease progression, a multi-center retrospective cohort study was conducted. COVID-19 patients with thrombocytopenia and a sub-cohort of matched patients without thrombocytopenia were compared for their clinical manifestations, haematological disorders, biochemical parameters, inflammatory markers and clinical outcome. Results: Thrombocytopenia was present in 127 of 2,209 analyzed patients on admission. Compared with the control group, thrombocytopenia patients developed significantly higher frequency of respiratory failure (41.9% vs. 22.6%, P = 0.020), intensive care unit entrance (25.6% vs. 11.5%, P = 0.012), disseminated intravascular coagulation (45.2% vs. 10.6%, P < 0.001), more altered platelet morphology indexes and coagulation perturbation, higher levels of inflammatory markers. In addition, a significantly increased all-cause mortality (hazard ratio 3.08, 95% confidence interval 2.26-4.18, P < 0.001) was also observed in the patients with thrombocytopenia. Late development of thrombocytopenia beyond 14 days post-symptom was observed in 61 patients, from whom a comparable mortality rate yet longer duration to death was observed compared to those with early thrombocytopenia. Conclusions: Our finding from this study adds to previous evidence that thrombocytopenia is associated with adverse outcome of the disease and recommend that platelet count and indices be included alongside other haematological, biochemical and inflammatory markers in COVID-19 patients' assessment during the hospital stay.

Clinical characteristics and risk factors for severe scrub typhus in pediatric and elderly patients.

BACKGROUND: Scrub typhus (ST) is a life-threatening infectious disease if appropriate treatment is unavailable. Large discrepancy of clinical severity of ST patients was reported among age groups, and the underlying risk factors for severe disease are unclear. METHODS: Clinical and epidemiological data of ST patients were collected in 55 surveillance hospitals located in Guangzhou City, China, from 2012 to 2018. Severe prognosis and related factors were determined and compared between pediatric and elderly patients. RESULTS: A total of 2,074 ST patients including 209 pediatric patients and 1,865 elderly patients were included, with a comparable disease severity rate of 11.0% (95% CI 7.1%-16.1%) and 10.3% (95% CI 9.0%-11.8%). Different frequencies of clinical characteristics including lymphadenopathy, skin rash, enlarged tonsils, etc. were observed between pediatric and elderly patients. Presence of peripheral edema and decreased hemoglobin were the most important predictors of severe illness in pediatric patients with adjusted ORs by 38.99 (9.96-152.67, p<0.001) and 13.22 (1.54-113.50, p = 0.019), respectively, while presence of dyspnea and increased total bilirubin were the potential determinants of severe disease in elderly patients with adjusted ORs by 11.69 (7.33-18.64, p<0.001) and 3.17 (1.97-5.11, p<0.001), respectively. Compared with pediatric patients, elderly patients were more likely to receive doxycycline (64.8% v.s 9.9%, p<0.001), while less likely to receive azithromycin therapy (5.0% v.s 41.1%, p<0.001). CONCLUSION: The disease severity rate is comparable between pediatric and elderly ST patients, while different clinical features and laboratory indicators were associated with development of severe complications for pediatric and elderly patients, which is helpful for diagnosis and progress assessment of disease for ST patients.

Super Dominant Pathobiontic Bacteria in the Nasopharyngeal Microbiota Cause Secondary Bacterial Infection in COVID-19 Patients.

Coronavirus disease 2019 (COVID-19) is a respiratory infectious disease responsible for many infections worldwide. Differences in respiratory microbiota may correlate with disease severity. Samples were collected from 20 severe and 51 mild COVID-19 patients. High-throughput sequencing of the 16S rRNA gene was used to analyze the bacterial community composition of the upper and lower respiratory tracts. The indices of diversity were analyzed. When one genus accounted for >50% of reads from a sample, it was defined as a super dominant pathobiontic bacterial genus (SDPG). In the upper respiratory tract, uniformity indices were significantly higher in the mild group than in the severe group (P < 0.001). In the lower respiratory tract, uniformity indices, richness indices, and the abundance-based coverage estimator were significantly higher in the mild group than in the severe group (P < 0.001). In patients with severe COVID-19, SDPGs were detected in 40.7% of upper and 63.2% of lower respiratory tract samples. In patients with mild COVID-19, only 10.8% of upper and 8.5% of lower respiratory tract samples yielded SDPGs. SDPGs were present in both upper and lower tracts in seven patients (35.0%), among which six (30.0%) patients possessed the same SDPG in the upper and lower tracts. However, no patients with mild infections had an SDPG in both tracts. Staphylococcus, Corynebacterium, and Acinetobacter were the main SDPGs. The number of SDPGs identified differed significantly between patients with mild and severe COVID-19 (P < 0.001). SDPGs in nasopharyngeal microbiota cause secondary bacterial infection in COVID-19 patients and aggravate pneumonia. IMPORTANCE The nasopharyngeal microbiota is composed of a variety of not only the true commensal bacterial species but also the two-face pathobionts, which are one a harmless commensal bacterial species and the other a highly invasive and deadly pathogen. In a previous study, we found that the diversity of nasopharyngeal microbiota was lost in severe influenza patients. We named the genus that accounted for over 50% of microbiota abundance as super dominant pathobiontic genus, which could invade to cause severe pneumonia, leading to high fatality. Similar phenomena were found here for SARS-CoV-2 infection. The diversity of nasopharyngeal microbiota was lost in severe COVID-19 infection patients. SDPGs in nasopharyngeal microbiota were frequently detected in severe COVID-19 patients. Therefore, the SDPGs in nasopharynx microbiota might invade into low respiratory and be responsible for secondary bacterial pneumonia in patients with SARS-CoV-2 infection.