Spread Of Novel Coronavirus Research Articles

Thai COVID-19 patient clustering for monitoring and prevention: data mining techniques

<span lang="EN-US">This research aims to optimize emerging infectious disease monitoring techniques in Thailand, which will be extremely valuable to the government, doctors, police, and others involved in understanding the seriousness of the spread of novel coronavirus to improve government policies, decisions, medical facilities, treatment. The data mining techniques included cluster analysis using K-means clustering. The infection data were obtained from the open data of the digital government development agency, Thailand. The dataset consisted of 1,893,941 cumulative cases from January 2020 to October 2021 of the outbreak. The results from clustering consisted of 8 groups. Clustering results determined the three largest, three medium-sized, and the two most minor numbers of infected people, respectively. These clusters represent their activities, namely touching an infected person and checking themselves. The components of emerging diseases in Thailand are closely related to waves, gender, age, nationality, career, behavioral risk, and region. The province of onset was mainly in Bangkok and its vicinity or central Thailand, as well as industrial areas. Adult workers aged 19 to 27 years and 43 to 54 years or over were seeds of new infection sources.</span>

Multivariate risks assessment for complex bio-systems by Gaidai reliability method

Spread of novel coronavirus and other flu-like illnesses, periodically causing increased death and morbidity rates, places pressures on national health systems. In order to provide a reliable long-term forecast of the new coronavirus infection rate, this research employs novel Gaidai bio-system reliability technique, especially suitable for multi-regional biological, environmental and public health systems. The goal of this study was to directly apply state of art statistical techniques to unprocessed raw clinical data, utilizing a multicenter, population-based biostatistical methodology. Epidemiological risks have been accurately forecasted, specifically for European Union member states. Based on their clinical survey data, suggested spatiotemporal methodology may be applied in a variety of public biological and health applications.

A Multi-dimensional Review on Severe Acute Respiratory Syndrome Coronavirus-2.

The advent and spread of novel coronavirus (nCoV) has posed a new public health crisis since December 2019. Several cases of unexplained pneumonia occurred in Wuhan, Hubei Province, China, only a month before the Chinese Spring festival. After the diagnosis of bronchoalveolar fluid samples of people infected, the new coronavirus was identified using nextgeneration sequence technology. This work aims to provide information regarding COVID-19 that will help the researchers to identify the vital therapeutic targets for SARS-CoV-2 and also will provide insights into some significant findings of recent times highlighted by scientific communities around the globe. In this review, we have tried to explore multiple aspects related to COVID-19, including epidemiology, etiology, COVID-19 variants, vaccine candidates, potential therapeutic targets, the role of natural products, and computational studies in drug design and development, repurposing, and analysis of crystal structures available for COVID-19 related protein structures. Druggable targets include all viral enzymes and proteins involved in viral replication and regulation of host cellular machines. The medical community tracks several therapies to combat the infection by investigating various antiviral and immunomodulatory mechanisms. While some vaccines are approved in this worldwide health crisis, a more precise therapy or drug is formally recommended to be used against SARS-CoV-2 infection. Natural products other than synthetic drugs have been tested by in silico analysis against COVID-19. However, important issues still need to be addressed regarding in vivo bioavailability and better efficacy.

Analysis of SARS transmission based on SIR model and SEIRP model

People's lives are still greatly impacted by the novel coronavirus outbreak, which has no effective treatment; however, the SARS virus two decades ago quickly disappeared. The study aims to find out how the SARS virus spreads, and also compares the SARS virus to the novel coronavirus. In the whole study, the author used the SIR model and the SEIRP model. It also combines specific cases of specific cities. Finally, through analysis, it is found that the epidemic of COVID-19 can be defeated by mass immunization and improving medical treatment. And how to prevent the spread of novel coronavirus.

COVID -19 and Lessons from ‘Triple Lock’: COVID Containment Strategy of Kerala Police

This Article reviews Kerala’s efforts to check the spread of novel coronavirus (COVID-19) without additional expenditure or infrastructure and employing the state police forces. This was remarkable in the face of the fact that healthcare systems were stretched the world over and were struggling beyond capacity to treat the number of people affected by the virus. To add to the overstretched healthcare systems, there were reports of attacks on healthcare workers and facilities. The state of Kerala was among the first to report a coronavirus case in January 2020. Against this backdrop, Kerala’s approach to mobilize the state’s resources, particularly the police, ran counter to that of many other states and their demands for assistance and financial support from the central government. This article details how one state addressed the problem during a national and international crisis. It includes a review of Kerala’s lateral thinking and successful case studies from the field. This research provides strategic thinking and solutions that other states could potentially follow when dealing with pandemics within their borders, both today and in the future.

Vulnerability to Mental Health Problems in Indian Population during Lockdown amidst COVID-19 Pandemic: An Alarm not to Snooze

Background: Lockdown measures are being implemented in several parts of the world to control the spread of novel coronavirus. This unprecedented crisis has significantly affected the lives of people in different ways. Aim: To understand the experiences and vulnerability to mental health problems during lockdown among the Indian population during COVID-19 pandemic. Materials and Methods: A cross-sectional study was conducted using an online survey form circulated through various social media platforms from April 12 to May 3, 2020 containing self-reported questionnaires to collect lockdown related experiences and scales to assess anxiety (GAD-7) and depression (PHQ-9). A convenience sampling method was used. Results: 442 valid responses were received from different states of India. Statistical analysis revealed that one-third of the respondents suffered from some form of anxiety and depression during a lockdown. Less than 10% of them had severe levels of symptoms. The majority were males aged 18-45 years and private sector employees. Delivering essential services was involved with significant anxiety and depression. Availability of food and daily essentials was the most common problem. Difficulty in availing medicines and financial crisis were significant predictors of anxiety and depression. Worsening of interpersonal relationships was associated with higher levels of anxiety and depression. Conclusions: The study concluded that experiences during the lockdown and associated psychological outcomes are important factors to consider and appropriate preventive measures to be taken in case of any future lockdowns.

Assessing the effectiveness of the intervention measures of COVID-19 in China based on dynamical method.

Normalized interventions were implemented in different cities in China to contain the outbreak of COVID-19 before December 2022. However, the differences in the intensity and timeliness of the implementations lead to differences in final size of the infections. Taking the outbreak of COVID-19 in three representative cities Xi'an, Zhengzhou and Yuzhou in January 2022, as examples, we develop a compartmental model to describe the spread of novel coronavirus and implementation of interventions to assess concretely the effectiveness of Chinese interventions and explore their impact on epidemic patterns. After applying reported human confirmed cases to verify the rationality of the model, we apply the model to speculate transmission trend and length of concealed period at the initial spread phase of the epidemic (they are estimated as 10.5, 7.8, 8.2 days, respectively), to estimate the range of basic reproduction number (2.9, 0.7, 1.6), and to define two indexes (transmission rate v t and controlled rate v c ) to evaluate the overall effect of the interventions. It is shown that for Zhengzhou, v c is always more than v t with regular interventions, and Xi'an take 8 days to achieve v c > v t twice as long as Yuzhou, which can interpret the fact that the epidemic situation in Xi'an was more severe. By carrying out parameter values, it is concluded that in the early stage, strengthening the precision of close contact tracking and frequency of large-scale nucleic acid testing of non-quarantined population are the most effective on controlling the outbreaks and reducing final size. And, if the close contact tracking strategy is sufficiently implemented, at the late stage large-scale nucleic acid testing of non-quarantined population is not essential.

Predicting the efficacy of variant-modified COVID-19 vaccine boosters.

Booster vaccination for the prevention of Coronavirus Disease 2019 (COVID-19) is required to overcome loss of protection due to waning immunity and the spread of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Studies have assessed the ability of existing ancestral-based vaccines as well as novel variant-modified vaccine regimens to boost immunity to different variants, and a crucial question is to assess the relative benefits of these different approaches. Here we aggregate data on neutralization titers from 14 reports (three published papers, eight preprints, two press releases and notes of one advisory committee meeting) comparing booster vaccination with the current ancestral-based vaccines or variant-modified vaccines. Using these data, we compare the immunogenicity of different vaccination regimens and predict the relative protection of booster vaccines under different scenarios. We predict that boosting with ancestral vaccines can markedly enhance protection against both symptomatic and severe disease from SARS-CoV-2 variant viruses, although variant-modified vaccines may provide additional protection, even if not matched to the circulating variants. This work provides an evidence-based framework to inform choices on future SARS-CoV-2 vaccine regimens.

Digital twin-driven robust bi-level optimisation model for COVID-19 medical waste location-transport under circular economy

COVID-19 medical waste collection-transport system, including the location of the related facilities, transport, and disposal, is a critical component in the circular economy. To promote the circularity of the waste management system and mitigate the spread of novel coronavirus, how to optimise COVID-19 medical waste location-transport strategies remains an open but urgent issue. In this paper, a novel digital twin-driven conceptual framework is proposed to improve the strategic decision on the location of temporary disposal centres and, subsequently, the operational decision on the transport of COVID-19 medical waste in the presence of hierarchical relationships amongst stakeholders, circular economy, environmental regulations, service level, and uncertainty in infection probability. The polyhedral uncertainty set is introduced to characterise stochastic infection probability. Digital twin technology is further used to estimate the upper and lower bound of the uncertainty set. Such a problem is formulated as a digital twin-driven robust bi-level mixed-integer programming model to minimise total infection risks on the upper level and total costs on the lower level. A hybrid solution strategy is designed to combine dual theory, Karush-Kuhn-Tucker (KKT) conditions, and a branch-and-bound approach. Finally, a real case study from Maharashtra in India is presented to evaluate the proposed model. Results demonstrate that the solution strategy performs well for such a complex problem because the CPU time required to conduct all experiments is less than one hour. Under a given uncertainty level of 36 and perturbation ratio of 20%, a regional transport strategy is preferred from generation points to transfer points, while a cross-regional one is usually implemented from transfer points to disposal centres. It is of significance to determine the bound of available temporary disposal centres. Using digital technology (e.g., digital twin) to accurately estimate the amount of COVID-19 medical waste is beneficial for controlling the pandemic. Reducing infection risks relative to cost is the prioritised goal in cleaning up COVID-19 medical waste within a relatively long period.

Two-phase COVID-19 medical waste transport optimisation considering sustainability and infection probability

A safe and effective medical waste transport network is beneficial to control the COVID-19 pandemic and at least decelerate the spread of novel coronavirus. Seldom studies concentrated on a two-phase COVID-19 medical waste transport in the presence of multi-type vehicle selection, sustainability, and infection probability, which is the focus of this paper. This paper aims to identify the priority of sustainable objectives and observe the impacts of multi-phase and infection probability on the results. Thus, such a problem is formulated as a mixed-integer programming model to minimise total potential infection risks, minimise total environmental risks, and maximise total economic benefits. Then, a hybrid solution strategy is designed, incorporating a lexicographic optimisation approach and a linear weighted sum method. A real-world case study from Chongqing is used to illustrate this methodology. Results indicate that the solution strategy guides a good COVID-19 medical waste transport scheme within 1 min. The priority of sustainable objectives is society, economy, and environment in the first and second phases because the total Gap of case No.35 is 3.20%. A decentralised decision mode is preferred to design a COVID-19 medical waste transport network at the province level. Whatever the infection probability is, infection risk is the most critical concern in the COVID-19 medical waste clean-up activities. Environmental and economic sustainability performance also should be considered when infection probability is more than a certain threshold.

Broad Spectrum Antiviral Prophylactic Medicine (Unani) to induce Immunity and Heard Immunity to Prevent the Spread of Novel Corona Virus

Broad Spectrum Antiviral Prophylactic Medicine (Unani) to induce Immunity and Heard Immunity to Prevent the Spread of Novel Corona Virus

SARS-CoV-2 Positive Patients and the Associated Risk Factors During the Third Wave: A Study in a Tertiary Care Hospital of Punjab

Background: SARS-CoV-2 has a high mutation rate, resulting in the emergence of multiple variants in a shortertime frame, starting with Wuhan strain during first wave, then Delta during second wave and Omicron duringthird wave. World faced distressing spread of novel corona virus. The reason for this study was to look at the thirdflood of SARS-CoV-2, clinical highlights and risk factors in northern India.Methods: This study involved 1,43,983 individuals for testing the presence of SARS-CoV-2 infection during January2022 by RT-PCR. The epidemiological record was collected as per the guidelines of ICMR from the patient forms.Results: A total of 12.24% individuals were found positive with mean age of 29±10 years. Large portion of positivepopulation (63.87%) was asymptomatic. Among the positive population, higher positivity rate was observed inmales (57.51%) with age band of 21-40 years (51.17%). Significant association (p value = <0.00001) was foundbetween positivity rate with age, gender and status (symptomatic/ asymptomatic). SARS-CoV-2 was shown tobe more prevalent in Patiala, (49.66%) district followed by Ludhiana (24.24%), Sangrur (10.06%), Mansa (7.06%),Shaheed Bhagat Singh Nagar (6.90%) and Malerkotla (2.08%) during second and third week of January 2022.Hypertension and bronchial asthma were the most well-known comorbidities found in the current study.Conclusion: In totality, current study showed positivity rate of 12.24% from large population size for SARS CoV-2from period of 1st January 2022 to 31 January 2022. Current findings include younger age group (21-40 years), highpercent of asymptomatic individuals, less disease severity and a little need of hospitalization.

Dynamical Analysis of COVID-19 Model Incorporating Environmental Factors.

The continuing coronavirus pandemic has come up with considerable questions in front of the world. Presently, India is among concerned countries in Asia. Even though the recovery rate is more than the death rate, it is affecting human lives and experiencing losses to the market. Several methods were employed to study the spread of novel coronavirus. Mathematical modeling is one of the prominent techniques to evaluate the dynamics of novel coronavirus. In this work, we extend the mathematical model SEIAQRDT by incorporating environmental transmission to analyze the transmission of coronavirus in India. The notable aspect of the model incorporates asymptomatic population, quarantine individuals, and environmental transmission factors. These factors have enormous significance in the ongoing COVID-19 outbreak. The basic reproduction number is calculated theoretically. Bifurcation analysis of is also done analytically. The existence and stability analysis of disease-free equilibrium (DFE) and endemic equilibrium (EE) points are established. The impact of environmental factors in spreading COVID-19 pandemic is deliberated. The case study for India and Italy is presented and compared with real data, and the results are in accordance with the real situation.

Educational Institutions of Islamabad during COVID-19 Pandemics: A Reflective Study

Purpose: The spread of Novel Corona virus (COVID-19) affected all fields of life along with education across the globe. After increase in positive cases of COVID-19, Federal Government of Pakistan announced the closure of educational institutions all over the country in the mid of March, 2020, as a protective measure for students and staff members. Due to complete lockdown in the country, internal and board exams of secondary school certificate (SSC) and higher secondary school certificate (HSSC) cancelled. Students got promotion without annual examination into next classes based on previous performance. This study investigated the blow of COVID- 19 on the students of government educational institutions of Islamabad along with the response of Government on the issue.
 Methodology: This was a qualitative study with case study approach. Target population was all the students and teachers/head teachers from public High and Higher secondary schools in Islamabad Pakistan. Random convenient sampling technique used for collection of data. Semi structured interviews were conducted telephonically for data. After completion, interviews/ responses transcribed and analyzed.
 Findings: Results of this research have revealed that this pandemic has badly affected the Federal educational institutions of Islamabad because of confinement of students in homes. Generally, students in government schools are from middle and lower middle class. They have no/limited access to internet and technology at home. It has widened the gap between privileged and none privileged/less privileged students due to inequality in access to internet and unavailability of gadgets in unbiased access to quality education. These factors compelled the Government to launch Tele-School on PTV (Pakistan Television) channel that started its regular transmission on 14 April 2020. Basic aim was to give assistance to all students confined at home. Schools opened after expected peak time I.e. 15 September. Students were allowed to join the regular school in small groups on alternate day. Strict precautionary measures, like social distancing, use of disinfectants in and around the premises/humans and provision of regular medical assistance carried out. Data revealed that the whole system was overburdened but the steps taken caused the far less damage than expected to the students.
 Recommendation: The study recommend that Tele-school channel should continue even after pandemic. It is beneficial for students to learn during closure of schools. It is also helpful to the students of remote areas, with no or least of internet facilities. Time has proven that the low-income government institutions have tackled the situation very well under the visionary umbrella of Federal Directorate of Education Islamabad Pakistan.

Performance of exponential similarity measures in supply of commodities in containment zones during COVID-19 pandemic under Pythagorean fuzzy sets.

Following the breakout of the novel coronavirus disease 2019 (COVID‐19), the government of India was forced to prohibit all forms of human movement. It became important to establish and maintain a supply of commodities in hotspots and containment zones in different parts of the country. This study critically proposes new exponential similarity measures to understand the requirement and distribution of commodities to these zones during the rapid spread of novel coronavirus (COVID‐19) across the globe. The primary goal is to utilize the important aspect of similarity measures based on exponential function under Pythagorean fuzzy sets, proposed by Yager. The article aims at finding the most required commodity in the affected areas and ensures its distribution in hotspots and containment zones. The projected path of grocery delivery to different residences in containment zones is determined by estimating the similarity measure between each residence and the various necessary goods. Numerical computations have been carried out to validate our proposed measures. Moreover, a comparison of the result for the proposed measures has been carried out to prove the efficacy.

Effect of Coronavirus on Indian Tourism Sector

Purpose: India is one of the most famous tourist destinations globally, offering a wide cluster of spots to see and activities to do. It is a mosaic of myriad attractions, from historical cities to natural splendors and finest architectural heritage. They draw in worldwide travelers. Indian tourism and hospitality industry are among largest contributors to economic growth and employ a huge workforce. This sector already facing difficulties due to global economic slowdown, and now industry lies in shreds due to spread of novel coronavirus. Government’s decision to undergo a complete lockdown to contain coronavirus added to precedence woes of people employed in sectors putting countless jobs in danger. Study seeks to understand impact of coronavirus on tourism sector associates and look into various suggestions for industry’s revival. Design/Methodology/Approach: Research design includes qualitative analysis to understand COVID-19’s impact on Indian tourism sector. Findings: The pandemic has a devastating impact on the industry. Research work finds inappropriate measures by government and business style with alternates need to be explored and adopted by industry. Practical Implications/Limitations: This study explores impact of COVID-19 on Indian tourism industry and suggests yardsticks to improve adverse state of affairs. It makes further study to strengthen tourism industry to come out from this distressing situation.

The impact of emotion management ability on learning engagement of college students during COVID-19.

During the COVID-19, the wanton spread of novel coronavirus had a huge negative effect on the emotions of college students, resulting in a serious impact on the daily learning behavior of many college students. In this context, college students’ emotion management ability is particularly important. Therefore, based on the results of a questionnaire survey of 580 college students, the present study conducts an in-depth analysis of the relationship between current college students’ emotion management ability and learning engagement, and explores the mediating role of psychological safety and self-efficacy in the relationship between emotion management ability and learning engagement. The results show that college students’ emotion management ability is significantly positive related to learning engagement, psychological safety and self-efficacy; Psychological safety and self-efficacy can play a partial mediating role between emotion management ability and college students’ learning engagement. The results reveal the importance of good emotion management ability of college students during the COVID-19, and enlighten colleges and universities to actively pacify students’ emotions to promote their normal learning.

Use QR Code and IoT Mobile Devices to Prevent the Spread of an Epidemic (COVID-19)

The spread of new pandemic novel Corona-Virus (COVID-19) brought violent changes in livelihood. It was difficult to control and cause Curfew in many countries, disrupted life, Imposing conditions for social distancing, masks because of unavailable of drugs, and treatments. The aim of this paper is using QR code and IoT for prevention transmission of COVID-19 by making electronic medical register for each human stored in cloud database included periodic Corona-Virus test and generate unique QR code for each one on the other side two software applications designed one for monitoring and update information of the medical register in the cloud and the second software read QR code and control the gates of public locations via IoT, as the results only healthy people can travel among public locations (markets, malls, Universities, Subways,…etc) and the infected persons can be monitored.

Psychological Impact and Its Correlates Following COVID-19 Pandemic Among Medical Students

Background: The continuous spread of novel coronavirus (COVID-19) pandemic, home quarantine, strict isolation measures and delays in opening educational institutions across the country is expected to influence the mental health of college students. The aim of our study is to assess the psychological impact and its correlates following the COVID-19 lockdown period, among the MBBS exam going students of a private medical college, Puducherry. Methods: A Descriptive Cross-Sectional Study was conducted among Undergraduate students in a private medical college of Puducherry between January-March 2021. Around 204 exam going students from Pre-final and Final year MBBS were enrolled in the study with their consent. Depression, Anxiety, and Stress among the study participants following the COVID 19 lockdown period was assessed using Depression Anxiety Stress Scale (DASS 21). Data was captured and Spearman`s correlation, Ordinal logistics regression was applied to find the predictors of Depression, Anxiety and Stress. Results: Among 204 study participants, the distribution was almost equal between Pre-Final (52%) and Final year (48%) MBBS students. Prevalence of Stress, Anxiety and Depression among students was found to be 38.2%, 52.8% and 48% respectively. Practicing regular physical activity, history of contact with COVID19 patients, year of MBBS were found to be predictors of Stress, Anxiety and Depression. It was also found that Stress level increases with increase in age. Conclusion: Around half of the study participants have either of the psychological impact following COVID 19 lockdown period that may adversely affect their performance in university exams. Still, there is a scope of further research that could be planned by applying interventions to improve the mental health status of the students.

COVID-19 Vaccination and Case Fatality Rate in India

India has experienced two severe waves of infection with COVID-19. Since there isn’t any effective drug, emerging variants of the virus, an unknown epidemiological life cycle, lockdown, and restrictions at public places slowed the spread of novel Coronavirus in the country. However, a large number of new COVID-19 cases and deaths have been reported from across the country. We carried out a study to evaluate the effectiveness of vaccination in India, randomly selected five states and a union territory to control the severity of COVID-19 (case fatality rate). During the study period, March 21st 2020 to 6th August 2021, with the initiation of vaccination, the case fatality rate was reduced to less than 1.0% in the selected states and union territory. Thus, vaccination for COVID-19 infection is found to be effective in decreasing the severity of the disease. The eligible population should get themselves inoculated at the nearest health facilities.