Study on the virulence evolution of SARS-CoV-2 and the trend of the epidemics of COVID-19

Will the Relaxation of COVID-19 Control Measures Have an Impact on the Chinese Internet-Using Public? Social Media-Based Topic and Sentiment Analysis

Objective: In December 2022, the Chinese government announced the further optimization of the implementation of the prevention and control measures of COVID-19. We aimed to assess internet-using public expression and sentiment toward COVID-19 in the relaxation of control measures in China. Methods: We used a user-simulation-like web crawler to collect raw data from Sina-Weibo and then processed the raw data, including the removal of punctuation, stop words, and text segmentation. After performing the above processes, we analyzed the data in two aspects. Firstly, we used the Latent Dirichlet Allocation (LDA) model to analyze the text data and extract the theme. After that, we used sentiment analysis to reveal the sentiment trend and the geographical spatial sentiment distribution. Results: A total of five topics were extracted according to the LDA model, namely, Complete liberalization, Resource supply, Symptom, Knowledge, and Emotional Outlet. Furthermore, sentiment analysis indicates that while the percentages of positive and negative microblogs fluctuate over time, the overall quantity of positive microblogs exceeds that of negative ones. Meanwhile, the geographical dispersion of public sentiment on internet usage exhibits significant regional variations and is subject to multifarious factors such as economic conditions and demographic characteristics. Conclusion: In the face of the relaxation of COVID-19 control measures, although concerns arise among people, they continue to encourage and support each other.

Two years of SARS-CoV-2 pandemic and COVID-19 in Lombardy, Italy

Lombardy, the largest and most densely populated Italian region, was severely hit in February 2020 by the first pandemic wave of SARS-CoV-2 and associated COVID-19. Since then, additional infection waves spread in the region. The aim of this study was to compare the first with the subsequent waves using the administrative database of the Lombardy Welfare directorate. In the time frames of the four 2020-2022 waves, the absolute number of infected cases, sites of management and crude mortality rate associated with SARS-CoV-2 positivity were extracted from the database. Infected cases progressively increased in the region by approximately 5-fold in the second versus the first wave, 4-fold in the third and 20-fold during the most recent wave mainly associated with the omicron variant. The crude death decreased from 18.7% in the first to 2% in the second and third wave to reach a 0.3% nadir at the time of the fourth wave. This study confirms that in Lombardy outcomes of public health and health-care relevance such as deaths and number of hospitalizations declined dramatically across the four virus waves and reached very low values in 2022 when, at variance with the first three SARS-CoV-2 waves, the majority of infected cases had been previously vaccinated.

Evaluation of COVID-19 pandemic spreading using computational analysis on nonlinear SITR model

The main purpose of present paper is to investigate the nonlinear model of COVID-19 (novel coronavirus) computationally. The SITR model is designed according to four classifications of Susceptible (S), Infectious (I), Treatment (T) and Recovered (R). Two convenient and effective numerical techniques namely the Adams-Bashforth Method (ABM) and Milne-Simpson Method (MSM) are employed to analyze the epidemic model. The influences of the contact rate parameter (β), recovery parameter (μ) and death parameter (α) on the variables including S, I and R are studied comprehensively. The obtained findings indicate that by increasing the contact rate parameter the infectious and recovered categories enhance but the susceptible mechanism decreases.

Why Controlling the Asymptomatic Infection Is Important: A Modelling Study with Stability and Sensitivity Analysis

The large proportion of asymptomatic patients is the major cause leading to the COVID-19 pandemic which is still a significant threat to the whole world. A six-dimensional ODE system (SEIAQR epidemical model) is established to study the dynamics of COVID-19 spreading considering infection by exposed, infected, and asymptomatic cases. The basic reproduction number derived from the model is more comprehensive including the contribution from the exposed, infected, and asymptomatic patients. For this more complex six-dimensional ODE system, we investigate the global and local stability of disease-free equilibrium, as well as the endemic equilibrium, whereas most studies overlooked asymptomatic infection or some other virus transmission features. In the sensitivity analysis, the parameters related to the asymptomatic play a significant role not only in the basic reproduction number R0. It is also found that the asymptomatic infection greatly affected the endemic equilibrium. Either in completely eradicating the disease or achieving a more realistic goal to reduce the COVID-19 cases in an endemic equilibrium, the importance of controlling the asymptomatic infection should be emphasized. The three-dimensional phase diagrams demonstrate the convergence point of the COVID-19 spreading under different initial conditions. In particular, massive infections will occur as shown in the phase diagram quantitatively in the case R0>1. Moreover, two four-dimensional contour maps of Rt are given varying with different parameters, which can offer better intuitive instructions on the control of the pandemic by adjusting policy-related parameters.