Application of ARIMA and SVM combination model in prediction of COVID-19

OBJECTIVE: To establish a combination model based on differential autoregressive moving average model (ARIMA) and introduction of support vector machine (SVM) method so as to predict the incidence trend of COVID-19. METHODS: ARIMA model was employed to predict the linear part of data of daily increased confirmed cases and capture the linear change trend of time series data. SVM was employed to predict the non-linear change trends. The mean absolute error (MAE), mean square error (MSE) and mean absolute percentage error (MAPE) were compared between the two combination models so as to assess the prediction results. RESULTS: During fitting stage of the models, as compared with the single ARIMA model and SVM model, the MSE of the ARIMA-SVM combination model was 0.004 (the least) in prediction of COVID-19, the MAE 0.055, the MAPE 0.004. During the prediction stage of the models, the MSE, MAE and MAPE of the combination model were respectively 7.811, 2.730 and 0.764, which were also the least among the 3 models. CONCLUSION: The ARIMA-SVM combination model is more precise than the single ARIM or SVM in prediction of trend of COVID-19.

The Mpro structure-based modifications of ebselen derivatives for improved antiviral activity against SARS-CoV-2 virus.

The main protease (Mpro or 3CLpro) of SARS-CoV-2 virus is a cysteine enzyme critical for viral replication and transcription, thus indicating a potential target for antiviral therapy. A recent repurposing effort has identified ebselen, a multifunctional drug candidate as an inhibitor of Mpro. Our docking of ebselen to the binding pocket of Mpro crystal structure suggests a noncovalent interaction for improvement of potency, antiviral activity and selectivity. To test this hypothesis, we designed and synthesized ebselen derivatives aimed at enhancing their non-covalent bonds within Mpro. The inhibition of Mpro by ebselen derivatives (0.3 µM) was screened in both HPLC and FRET assays. Nine ebselen derivatives (EBs) exhibited stronger inhibitory effect on Mpro with IC50 of 0.07-0.38 µM. Further evaluation of three derivatives showed that EB2-7 exhibited the most potent inhibition of SARS-CoV-2 viral replication with an IC50 value of 4.08 µM in HPAepiC cells, as compared to the prototype ebselen at 24.61 µM. Mechanistically, EB2-7 functions as a noncovalent Mpro inhibitor in LC-MS/MS assay. Taken together, our identification of ebselen derivatives with improved antiviral activity may lead to developmental potential for treatment of COVID-19 and SARS-CoV-2 infection.

Influence of COVID-19 prevention and control measures on the temporal and spatial evolution of epidemic situation

Objective: To understand the spatiotemporal distribution and spatial clustering of coronavirus disease 2019 (COVID-19), and to evaluate the impact of comprehensive prevention and control measures on the COVID-19 epidemic.

Characteristics and evaluation of the effectiveness of monitoring and control measures for the first 69 Patients with COVID-19 from 18 January 2020 to 2 March in Wuxi, China.

BACKGROUND: The Coronavirus disease (COVID-19) has caused 91,305 confirmed cases and 4746 deaths in China by 13:50 on October 11, 2020. We analyzed data on 69 infections in Wuxi to describe the disease's characteristics, to analyze factors of cases clinical outcome and to evaluate the prevention and control measures. METHODS: The demographic characteristics, exposure history, time indicators and propagation dynamics in Wuxi were collected. RESULTS: The clinical severity of cases was mostly mild and normal (75.36 %). Aging (relative risk [RR] = 1.04, 95 % confidence interval [CI]: 1.001-1.08) and fever (RR = 10.33, 95 %CI: 2.75-38.78) were risk factors for disease severity. The mean incubation period was estimated to be 4.77 days (95 % CI: 3.61-5.94), with a mean serial interval of 6.31 days (95 % CI: 5.12-7.50). The controlled reproduction number was estimated to be 1.12 (95 %CI: 0.71-1.69). CONCLUSIONS: The incidence of COVID-19 in Wuxi has turned into a lower level, suggesting the early prevention and control measures have achieved effectiveness. Aging and fever of initial symptom were risk factors for severe clinical outcome. The family clusters provided further clues of the risk factors for COVID-19 transmission.

Fangcang shelter hospitals are a One Health approach for responding to the COVID-19 outbreak in Wuhan, China.

In February 2020, the exponential growth of COVID-19 cases in Wuhan city posed a huge economic burden to local medical systems. Consequently, Wuhan established Fangcang Shelter hospitals as a One Health approach for responding to and containing the COVID-19 outbreak by isolating and caring for mild-to-moderate cases. However, it is unclear to what degree the hospitals contained COVID-19. This study performed an interrupted time series analysis to compare the number of new confirmed cases of COVID-19 before and after the operation of Fangcang Shelter hospitals. The initial number of confirmed cases in Wuhan increased significantly by 68.54 cases per day prior to February 4, 2020. Compared with the number of cases noted 20 days before the use of Fangcang Shelter hospitals, a sustained reduction in the number of confirmed cases (trend change, -125.57; P < 0.0001) was noted 41 days after the use of the hospitals. Immediate-level changes were observed for confirmed cases (level change, 725.97; P = 0.025). These changes led to an estimated 5148 fewer confirmed cases (P < 0.0001). According to the mean confirmed cases of 395.71 per day before the intervention, we estimated that Wuhan had advanced the terminal phase of COVID-19 by 13 days. Furthermore, immediately after introduction of Fangcang Shelter Hospitals on February 5, the reproduction number dropped rapidly, from a pre-introduction rate of 4.0 to 2.0. The Fangcang Shelter hospitals most likely to reversed the epidemic trend of COVID-19 while a containment strategy was implemented in Wuhan. In a One Health perspective, Fangcang Shelter hospitals, with their functions of isolation and treatment of confirmed COVID-19 patients, engaging professionals from many disciplines, such as medicine, engineering, architecture, psychology, environmental health, and social sciences. The results of this study provide a valuable reference for health policy makers in other countries.

Comparison of Venous Thromboembolism Risks Between COVID-19 Pneumonia and Community-Acquired Pneumonia Patients.

OBJECTIVE: The objectives were to investigate and compare the risks and incidences of venous thromboembolism (VTE) between the 2 groups of patients with coronavirus disease 2019 (COVID-19) pneumonia and community-acquired pneumonia (CAP). Approach and Results: Medical records of 616 pneumonia patients who were admitted to the Yichang Central People's Hospital in Hubei, China, from January 1 to March 23, 2020, were retrospectively reviewed. The patients with COVID-19 pneumonia were treated in the dedicated COVID-19 units, and the patients with CAP were admitted to regular hospital campus. Risks of VTE were assessed using the Padua prediction score. All the patients received pharmaceutical or mechanical VTE prophylaxis. VTE was diagnosed using Duplex ultrasound or computed tomography pulmonary angiogram. Differences between COVID-19 and CAP groups were compared statistically. All statistical tests were 2 sided, and P<0.05 was considered as statistically significant. All data managements and analyses were performed by IBM SPSS, version 24, software (SPSS, Inc, Chicago, IL). Of the 616 patients, 256 had COVID-19 pneumonia and 360 patients had CAP. The overall rate of VTE was 2% in COVID-19 pneumonia group and 3.6% in CAP group, respectively (P=0.229). In these two groups, 15.6% of the COVID-19 pneumonia patients and 10% of the CAP patients were categorized as high risk for VTE (Padua score, >4), which were significantly different (P=0.036). In those high-risk patients, the incidence of VTE was 12.5% in COVID-19 pneumonia group and 16.7% in CAP group (P=0.606). Subgroup analysis of the critically ill patients showed that VTE rate was 6.7% in COVID-19 group versus 13% in CAP group (P=0.484). In-hospital mortality of COVID-19 and CAP was 6.3% and 3.9%, respectively (P=0.180). CONCLUSIONS: Our study suggested that COVID-19 pneumonia was associated with hypercoagulable state. However, the rate of VTE in COVID-19 pneumonia patients was not significantly higher than that in CAP patients.

Epidemiology of 2019 novel coronavirus in Jiangsu Province, China after wartime control measures: A population-level retrospective study.

BACKGROUND: A novel coronavirus emerged in China in December 2019, and human-to-human transmission was previously identified. This study aimed to compare the epidemiological characteristics in Jiangsu Province and assess whether so-called wartime control measures changed the trend of coronavirus disease 2019 (COVID-19) in the province. METHODS: Epidemiological data were obtained from the websites of China's Bureau of Health and the People's Government of Jiangsu Province and informal online sources from January 22 to February 20, 2020. RESULTS: The cumulative number of patients in Jiangsu Province (over 79 million people) was 613. The number of daily confirmed new cases reached the inflection point on January 31 with the maximum of 39 cases. The temporal number of patients peaked from January 29 to February 9. The proportion of confirmed cases who were residents or travelers to Hubei Province was 100.0%-58.8% before January 31 and then gradually declined. The proportion of close contacts increased gradually from January 27 to February 17. The geographical distribution of COVID-2019 cases showed that all 13 cites reported confirmed new cases after only five days of the first confirmed new case in Suzhou. The cases were concentrated in Nanjing, Suzhou, and Xuzhou with a high population density (over eight million people). The epidemiological features of COVID-2019 cases in Wuxi, Jiangsu showed that seven confirmed cases were tourists from others areas beyond Hubei Province. The longest incubation period of COVID-2019 was 19 days based on the onset of laboratory-confirmed cases. CONCLUSION: The number of daily confirmed new cases in Jiangsu Province peaked around January 31 and then declined. This result emphasized that wartime control measures, such as putting cities on lockdown to limit population mobility in Jiangsu Province, resulted in dramatic reductions in COVID-19 cases.