This paper reports on development of an optical biosensor for the detection of antibodies against SARS-CoV-2 virus proteins in blood serum. ZnO nanotetrapods with high surface area and stable room ...temperature photoluminescence (PL) were selected as transducers. Structure and optical properties of the ZnO tetrapods have been studied by XRD, SEM and Raman spectroscopy. Crystallinity, dimensions and emission peaks of the ZnO tetrapods were determined. The ZnO tetrapods were fixed on glass chip. Silanization of ZnO tetrapods surface resulted in forming of functional surface groups suitable for the immobilization of bioselective layer. Two types of recombinant proteins (rS and rN) have been used to form bioselective layer on the surface of the ZnO tetrapods. Flow through microfluidic system, integrated with optical system, has been used for the determination of antibodies against SARS-CoV-2 virus proteins present in blood samples. The SARS-CoV-2 probes, prepared in PBS solution, have been injected into the measurement chamber with a constant pumping speed. Steady-state photoluminescence spectra and photoluminescence kinetics have been studied before and after injection of the probes. The biosensor signal has been tested to anti-SARS-CoV-2 antibodies in the range of 0.001 nM–1 nM. Control measurements have been performed with blood serum of healthy person. ZnO-SARS-CoV-2-rS and ZnO-SARS-CoV-2-rN biosensors showed high stability and sensitivity to anti-SARS-CoV-2 antibodies in the range of 0.025–0.5 nM (LOD 0.01 nM) and 0.3–1 nM (LOD 0.3 nM), respectively. Gibbs free energy of interaction between ZnO/SARS-CoV-2-rS and ZnO/SARS-CoV-2-rN bioselective layers with anti-SARS-CoV-2 antibodies showed −35.5 and −21.4 kJ/mol, respectively. Average detection time of biosensor integrated within microfluidic system was 15–20 min. The detection time and pumping speed (50 μL/min) were optimized to make detection faster. The developed system and ZnO-SARS-CoV-2-rS nanostructures have good potential for detection of anti-SARS-CoV-2 antibodies from patient's probes.
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•Glass-chip was modified by ZnO tetrapods as photoluminescence (PL) transducers.•PL-based system for detection of antibodies against SARS-CoV-2 virus was designed.•Two types of recombinant proteins (rS and rN) were immobilized on the ZnO tetrapods.•Sensor was integrated within flow through microfluidic system.•Sensitivity towards antibodies against SARS-CoV-2 virus proteins was determined.
COVID-19 is a severe acute respiratory syndrome caused by the Coronavirus-2 virus (SARS-CoV-2). The virus spreads from one to another through droplets from an infected person, and sometimes these ...droplets can contaminate surfaces that may be another infection pathway. In this study, we developed a COVID-19 model based on data and observations in Thailand. The country has strictly distributed masks, vaccination, and social distancing measures to control the disease. Hence, we have classified the susceptible individuals into two classes: one who follows the measures and another who does not take the control guidelines seriously. We conduct epidemic and endemic analyses and represent the threshold dynamics characterized by the basic reproduction number. We have examined the parameter values used in our model using the mean general interval (GI). From the calculation, the value is 5.5 days which is the optimal value of the COVID-19 model. Besides, we have formulated an optimal control problem to seek guidelines maintaining the spread of COVID-19. Our simulations suggest that high-risk groups with no precaution to prevent the disease (maybe due to lack of budgets or equipment) are crucial to getting vaccinated to reduce the number of infections. The results also indicate that preventive measures are the keys to controlling the disease.
In order to determine the effectiveness of non-pharmaceutical interventions on an epidemic, we develop an agent-based model that simulates the spread of an infectious disease in a small community and ...its emerging phenomena. We vary parameters such as initial population, initial infected, infection rate, recovery rate, death rate, and asymptomatic rates, as inputs. Our simulations show that (i) random mass testing decreases the number of deaths, infections and time duration; (ii) as well as quarantines; (iii) social distancing lengthen outbreak period to an extent and helps flatten the epidemic curve; and (iv) the most effective combination of NPIs to minimize death, infection and duration is no mass testing, no social distancing and a total lockdown. Results of this study can aid decision makers in their policies to be implemented to have an optimal output.
During the COVID-19 epidemic, China became the focus of international public opinions, and its national image was put to the test. This paper collects and organizes China-related reports on the ...COVID-19 epidemic from the German weekly magazine Der Spiegel, and summarizes the image of China portrayed by the German mainstream media in the reports of the COVID-19 epidemic by adopting the method of content analysis and data analysis. It also analyzes the reasons for the negative reports by the German media from several aspects, including reporting tradition, market pressure and value differences, and proposes that China should adjust its foreign publicity strategies timely and appropriately to build a positive image in international community.
COVID-2019 is a global threat, for this reason around the world, researches have been focused on topics such as to detect it, prevent it, cure it, and predict it. Different analyses propose models to ...predict the evolution of this epidemic. These analyses propose models for specific geographical areas, specific countries, or create a global model. The models give us the possibility to predict the virus behavior, it could be used to make future response plans. This work presents an analysis of COVID-19 spread that shows a different angle for the whole world, through 6 geographic regions (continents). We propose to create a relationship between the countries, which are in the same geographical area to predict the advance of the virus. The countries in the same geographic region have variables with similar values (quantifiable and non-quantifiable), which affect the spread of the virus. We propose an algorithm to performed and evaluated the ARIMA model for 145 countries, which are distributed into 6 regions. Then, we construct a model for these regions using the ARIMA parameters, the population per 1M people, the number of cases, and polynomial functions. The proposal is able to predict the COVID-19 cases with a RMSE average of 144.81. The main outcome of this paper is showing a relation between COVID-19 behavior and population in a region, these results show us the opportunity to create more models to predict the COVID-19 behavior using variables as humidity, climate, culture, among others.
The strict control measures and social lockdowns initiated to combat COVID-19 epidemic have had a notable impact on air pollutant concentrations. According to observation data obtained from the China ...National Environmental Monitoring Center, compared to levels in 2019, the average concentration of NO2 in early 2020 during COVID-19 epidemic has decreased by 53%, 50%, and 30% in Wuhan city, Hubei Province (Wuhan excluded), and China (Hubei excluded), respectively. Simultaneously, PM2.5 concentration has decreased by 35%, 29%, and 19% in Wuhan, Hubei (Wuhan excluded), and China (Hubei excluded), respectively. Less significant declines have also been found for SO2 and CO concentrations. We also analyzed the temporal variation and spatial distribution of air pollutant concentrations in China during COVID-19 epidemic. The decreases in PM2.5 and NO2 concentrations showed relatively consistent temporal variation and spatial distribution. These results support control of NOx to further reduce PM2.5 pollution in China. The concurrent decrease in NOx and PM2.5 concentrations resulted in an increase of O3 concentrations across China during COVID-19 epidemic, indicating that coordinated control of other pollutants is needed.
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Abstract— A pandemic Covid-19 is an epidemic that spreads over a big region, Crosse international borders, and often affects a lot of people. Only a few pandemics result in severe illness in a subset ...of people or in an entire community. The virus has mainly affects the elderly population. The virus, that causes Covid-19, has mainly been transmitted through droplet generate once an infected persons exhales, sneezes and coughs. These symptoms are too heavy; to hang in air, and quickly, fall on surface or floor. The COVID-19 pandemic model including the Vaccination Campaign is of natural phenomenon which can be represented as a system of differential equations for the first order; the mathematical models include a system of several second order nonlinear equations. We applied the Adomian decomposition methods to the mathematical models of Covid-19. The main advantage of this method is that it can be directly applied to all kinds of linear and nonlinear differential equations, homogeneous or nonhomogeneous, with constant or variable coefficients. The derivatives of all compartments of the coronavirus model are continuous at t ≥ 0. The solutions of the model are non-negativity. It indicates that the, infection, will be gradually the epidemic and disappear will, stop. If, R_0>1, the average of each affected individually. More than one person has infected, and the incidence of infection is in wrinkles. That means the epidemic, will not be end, while maintain the existence of the disease, the R_0=1 means that each infected patient results in an average infections.
The COVID-19 pandemic led to the adoption of severe measures to counteract the spread of the infection. Social distancing and lockdown measures modified people’s habits, while the Internet gained a ...major role in supporting remote working, e-teaching, online collaboration, gaming, video streaming, etc. All these sudden changes put unprecedented stress on the network.
In this paper, we analyze the impact of the lockdown enforcement on the Politecnico di Torino campus network. Right after the school shutdown on the 25th of February, PoliTO deployed its own in-house solution for virtual teaching. Ever since, the university provides about 600 virtual classes daily, serving more than 16 000 students per day. Here, we report a picture of how the pandemic changed PoliTO’s network traffic. We first focus on the usage of remote working and collaboration platforms. Given the peculiarity of PoliTO online teaching solution that is hosted in-house, we drill down on the traffic, characterizing both the audience and the network footprint. Overall, we present a snapshot of the abrupt changes seen on campus traffic due to COVID-19, and testify how the Internet has proved robust to successfully cope with challenges while maintaining the university operations.
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