Spread Of Coronavirus Disease Research Articles

MODELING THE SPREAD OF COVID-19 DISEASE WITH TIME DELAY IN PONTIANAK CITY

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by a coronavirus originating from the city of Wuhan in 2019. This disease affects the respiratory system. The city of Pontianak has the highest population density in West Kalimantan. This density results in a higher spread of Covid-19. In this article, the spread of COVID-19 is formulated into a mathematical model, equilibrium points are sought, stability is analyzed, and a delay time is introduced to reduce the spread of COVID-19. The magnitude of the delay time given during quarantine complies with health protocols, which is between 2 – 14 days. This article aims to analyze the influence of the delay time in modeling the spread of Covid-19. The problem of COVID-19 spread is constructed into an SIQR model, with a sub-population of recovered individuals returning to the susceptible sub-population. The population is divided into four sub-populations: susceptible (S), Infected (I), Quarantined (Q), and Recovered (R). The parameters used include the natural birth rate ( ), the rate of susceptibility to infection ( ), the rate of infection under quarantine ( ), the recovery rate from infection ( ), the recovery rate from infection under quarantine ( ), the death rate from infection ( ), the death rate under quarantine ( ), the delay time from infection to quarantine process ( ), the natural death rate ( ), and the rate of recovered immunity returning to susceptibility ( ). The simulation results show that when the basic reproduction number is less than , the disease-free equilibrium is stable, and when the basic reproduction number is greater than , the endemic equilibrium point is stable. The addition of a time delay ( ) in the SIQR model affects the stability of the endemic equilibrium point but does not affect the stability of the disease-free equilibrium point.

Post-COVID-19: Time to Change Our Way of Life for a Better Future.

Background and Objectives: From the year 1 anno Domini until 1855, with the third plague, major pandemics occurred on average every 348 years. Since then, they have occurred on average every 33 years, with coronavirus disease 2019 (COVID-19) now underway. Even though current technologies have greatly improved the way of life of human beings, COVID-19, with more than 700,000,000 cases and 6,950,000 deaths worldwide by the end of 2023, reminds us that much remains to be done. This report looks back at 18 months of COVID-19, from March 2020 to August 2021, with the aim of highlighting potential solutions that could help mitigate the impact of future pandemics. Materials and Methods: COVID-19 data, including case and death reports, were extracted daily from the Worldometer platform to build a database for the macroscopic analysis of the spread of the virus around the world. Demographic data were integrated into the COVID-19 database for a better understanding of the spatial spread of the SARS-CoV-2 virus in cities/municipalities. Without loss of generality, only data from the top 30 (out of 200 and above) countries ranked by total number of COVID-19 cases were analyzed. Statistics (regression, t-test (p < 0.05), correlation, mean ± std, etc.) were carried out with Excel software (Microsoft® Excel® 2013 (15.0.5579.1001)). Spectral analysis, using Matlab software (license number: 227725), was also used to try to better understand the temporal spread of COVID-19. Results: This study showed that COVID-19 mainly affects G20 countries and that cities/municipalities with high population density are a powerful activator of the spread of the virus. In addition, spectral analysis highlighted that the very first months of the spread of COVID-19 were the most notable, with a strong expansion of the SARS-CoV-2 virus. On the other hand, the following six months showed a certain level of stability, mainly due to multiple preventive measures such as confinement, the closure of non-essential services, the wearing of masks, distancing of 2 m, etc. Conclusion: Given that densely populated cities and municipal areas have largely favored the spread of the SARS-CoV-2 virus, it is believed that such a demographic context is becoming a societal problem that developed countries must address in a manner that is adequate and urgent. COVID-19 has made us understand that it is time to act both preventatively and curatively. With phenomenological evidence suggesting that the next pandemic could occur in less than 50 years, it may be time to launch new societal projects aimed at relieving congestion in densely populated regions.

Cost–benefit analysis of the COVID-19 vaccination model incorporating different infectivity reductions

The spread and control of coronavirus disease 2019 (COVID-19) present a worldwide economic and medical burden to public health. It is imperative to probe the effect of vaccination and infectivity reductions in minimizing the impact of COVID-19. Therefore, we analyze a mathematical model incorporating different infectivity reductions. This work provides the most economical and effective control methods for reducing the impact of COVID-19. Using data from Ghana as a sample size, we study the sensitivity of the parameters to estimate the contributions of the transmission routes to the effective reproduction number Re. We also devise optimal interventions with cost–benefit analysis that aim to maximize outcomes while minimizing COVID-19 incidences by deploying cost-effectiveness and optimization techniques. The outcomes of this work contribute to a better understanding of COVID-19 epidemiology and provide insights into implementing interventions needed to minimize the COVID-19 burden in similar settings worldwide.

Evaluating the efficacy of univariate LSTM approach for COVID-19 data prediction in Indonesia

The coronavirus disease 2019 (COVID-19) pandemic, originating in 2020, has emerged as a critical global issue due to its rapid and widespread transmission. Indonesia, among the affected nations, has taken measures to address the situation, including the development of a deep learning model for predicting future COVID-19 infection and spread. This predictive tool serves as a valuable reference for the government and stakeholders, aiding them in making informed decisions and implementing appropriate measures to contain the virus. The deep learning model employs the long short-term memory (LSTM) algorithm, chosen for its ability to recognize temporal patterns in the country’s COVID-19 data. The model creation process involves data collection, preprocessing, model architecture planning, modeling, training, and evaluation. Two LSTM models were developed: a univariate and a multivariate model. Following thorough training and evaluation, the univariate model emerged as the superior choice, boasting evaluation metrics of 16.72 for mean absolute percentage error (MAPE) and 66.36 for root mean squared error (RMSE). This model was then deployed on a publicly accessible website, presenting visualizations of past COVID-19 data and predictions of future cases through line graphs. This user-friendly platform enables the public to access and analyze the data easily.

In-silico Identification of Dexamethasone-similar Compounds Against SARS-Cov-2 Spike Protein: A Drug Repurposing Approach

Abstract: To identify potential drug candidates for the treatment of COVID-19 using a computational method. The recent pandemic of COVID-19 is observed as not less than a natural calamity of humankind and raised serious concerns for its immediate management. The continued spread of coronavirus disease across the globe poses a significant threat to human health. Out of this, the application of Dexamethasone has been correlated with reduced mortality in COVID-19 cases. This study sheds new light on the pharmacological potential of Dexamethasone and similar compounds in mitigating SARSCoV2 infection. : In this study, we explored Dexamethasone-similar compounds, which can modulate the binding of SARS-CoV-2 spike protein to the host and TH17 programming in the host using a computer-aided drug repurposing method. The docking studies indicate that Desoximetasone can bind to the spike proteins of SARS-CoV-2, which are crucial for viral attachment and entry into host cells. By competing with these spike proteins, Desoximetasone may interfere with the virus's ability to attach to and enter host cells, potentially inhibiting viral replication and spread. The results from molecular dynamic simulation analysis further support this notion by demonstrating that Desoximetasone has a strong interaction with the binding sites of the spike protein. Experimental validation through in vitro studies and clinical trials is needed to evaluate its potential as a treatment option for COVID-19. Together, these findings revealed the underlying mechanism of how Desoximetasone can influence the fate of the virus in the host and advocated its anti-viral potential.

Prediction of COVID-19 spread with models in different patterns: A case study of Russia

Abstract This study deals with a mathematical model that examines the spread of Coronavirus disease (COVID-19). This model has been handled with different processes such as deterministic, stochastic, and deterministic–stochastic. First of all, a detailed analysis is presented for the deterministic model, which includes the positivity of the solution, the basic reproduction number, the disease, and endemic equilibrium points. Then, for the stochastic model, we investigate under which conditions, the solution exists and is unique. Later, model is reconsidered with the help of the piecewise derivative, which can combine deterministic and stochastic processes. Numerical simulations are presented for all these processes. Finally, the model has been modified with the rate indicator function. The model presenting these four different situations is compared with the real data in Russia. According to the results obtained from these situations, the model that is obtained by adding the rate indicator function predicts the COVID-19 outbreak in Russia more accurately. Thus, it is concluded that the model with the rate indicator function presents more realistic approach than the previous ones.

Application of Skimmed-Milk Flocculation Method for Wastewater Surveillance of COVID-19 in Kathmandu, Nepal.

Wastewater surveillance (WS) has been used globally as a complementary tool to monitor the spread of coronavirus disease 2019 (COVID-19) throughout the pandemic. However, a concern about the appropriateness of WS in low- and middle-income countries (LMICs) exists due to low sewer coverage and expensive viral concentration methods. In this study, influent wastewater samples (n = 63) collected from two wastewater treatment plants (WWTPs) of the Kathmandu Valley between March 2021 and February 2022 were concentrated using the economical skimmed-milk flocculation method (SMFM). The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was tested by qPCR using assays that target the nucleocapsid (N) and envelope (E) genes. Overall, 84% (53/63) of the total samples were positive for SARS-CoV-2 according to at least one of the tested assays, with concentrations ranging from 3.5 to 8.3 log10 gene copies/L, indicating the effectiveness of the SMFM. No correlation was observed between the total number of COVID-19 cases and SARS-CoV-2 RNA concentrations in wastewater collected from the two WWTPs (p > 0.05). This finding cautions the prediction of future COVID-19 waves and the estimation of the number of COVID-19 cases based on wastewater concentration in settings with low sewer coverage by WWTPs. Future studies on WS in LMICs are recommended to be conducted by downscaling to sewer drainage, targeting a limited number of houses. Overall, this study supports the notion that SMFM can be an excellent economical virus-concentrating method for WS of COVID-19 in LMICs.

New-onset or relapse of uveitis after rapid spreading of COVID-19 infection in China and risk factor analysis for relapse

BackgroundThe aim of this study was to report the clinical profile of new-onset and relapse of uveitis following rapid spreading of coronavirus disease 2019 (COVID-19) infection due to change of anti-COVID-19 policies in China and investigate potential risk factors for inflammation relapse.MethodsIn this retrospective case-control study, patients with new-onset or a history of uveitis between December 23, 2022, and February 28, 2023, were included to assess the influence of COVID-19 infection on uveitis. Detailed information on demographic data, clinical characteristics, treatment measures, treatment response, and ocular inflammatory status before and after COVID-19 infection was collected.ResultsThis study included 349 patients with a history of uveitis. The uveitis relapse rate was higher (28.8%, n = 288) in those with COVID-19 infection than in patients without COVID-19 infection (14.8%, n = 61) (P = 0.024). Among the relapse cases, 50.8% experienced a relapse of anterior uveitis, while 49.2% had a relapse of uveitis involving the posterior segment. Multivariable regression analysis indicated a positive correlation between disease duration and uveitis relapse, while the last relapse exceeding one year before COVID-19 infection and the use of methotrexate during COVID-19 infection were negatively correlated with relapse of uveitis. Thirteen patients who developed new-onset uveitis following COVID-19 infection were included; among them, three (23.1%) had anterior uveitis and 10 (76.9%) had uveitis affecting the posterior segment. Regarding cases involving the posterior segment, four patients (30.8%) were diagnosed with Vogt-Koyanagi-Harada disease.ConclusionsCOVID-19 infection increases the rate of uveitis relapse. Long disease duration is a risk factor, while time since the last relapse more than 1 year and methotrexate use are protective factors against uveitis relapse.

Knowledge and preventive practices regarding COVID-19 disease among Ukrainian refugees in Poland.

Russia's invasion of Ukraine contributed one of the largest migration movements in the 21st century. Refugees may become a source of severe acute respiratory syndrome coronavirus 2 infections for the residents of host countries. The study aim was to assess knowledge and preventive practices regarding coronavirus disease 2019 (COVID-19) among Ukrainian refugees in Poland. The cross-sectional study was conducted between March and April 2022 among Ukrainian refugees registering consecutively in Zielona Góra, Poland. Knowledge and preventive practices were assessed by giving 1 point for each correct answer by anonymous, self-administered questionnaire. The response rate was 96%, 190 participated (mean age 37.8 ± 15.5 years; 57.9% females); 61.6% self-reported their socio-economic status (SES) as high, 38.9% reported high level of education. The mean COVID-19 knowledge score was 3.06 ± 1.95; 19.5% scored >50%. The knowledge level was higher among migrants with high SES (P = .003). The mean preventive practices score was 2.56 ± 1.38; 54.0% scored ≥ 60%. 40.5% declared social distancing, 62.6% followed coughing etiquette, 69.0% home isolate themselves during COVID-19. 57.9% always used masks in public space, however 74.2% wore masks with uncovered nose. Refugees with higher education, high SES and knowledge level had significantly greater preventive practices scores (P = .002; P = .02; P = .03, respectively). The knowledge and preventive practices level was insufficient. Educational campaigns oriented to raising knowledge and prevention behavior skills should be implemented, especially targeting high-risk groups to avoid spread of COVID-19.

A Long-term Interpretation of the Effect of COVID-19 on Food Security: A Lesson for the Future Pandemic Diseases

Background: The global spread of coronavirus disease (COVID-19) could trigger a food security crisis affecting not only impoverished individuals but also urban residents in low- and middle-income countries. Objectives: Given that various strains of COVID-19 impact food security differently, we assessed the food security status of households in Semnan province, Iran, during and after the containment of the omicron variant. Methods: Data from 231 households were gathered using a standard questionnaire that evaluated socioeconomic characteristics, food security based on the U.S. Household Food Security Survey Module, and vulnerability to food insecurity. A quantitative model was utilized to identify factors associated with food insecurity during and post-pandemic. Results: The findings indicated an improvement in household food security following the management of COVID-19, with significant differences observed in food security levels, especially concerning severe food insecurity, during versus after the COVID-19 period. The quantitative model analysis revealed that, with the exception of the head of household's occupation status, personal savings, and the number of educated and employed members within a household, all variables significantly correlated with food security (P &lt; 0.05). Conclusions: These outcomes highlight how the relationship between socioeconomic factors and food security levels may vary depending on the pandemic's timing, environmental conditions, and household resilience, underlining the importance of adaptive policymaking that responds to current circumstances and the evolving links between socioeconomic determinants and food security.

Estimating the Effects of Regulating In-Person University Lectures on the Spread of COVID-19: Evidence from Japan

Universities were the only educational institutions that restricted in-person lectures during the prolonged coronavirus disease 2019 (COVID-19) pandemic. This study is the first attempt to estimate the effects of restricting in-person lectures on containing the spread of COVID-19. Our investigation was conducted on Japanese universities since their various lecture styles are suitable for our analysis. A multiple-event study negative binomial regression model was employed, and the results showed that restricting the ratio of in-person lectures had limited effects on decreasing COVID-19 infections among university students. For example, if universities restrict almost all in-person lecture from a rate of over half of in-person lectures, the number of student infections would decline by 5.5 per 10,000 students between seven weeks before and after the change. Other lecture style changes had even smaller differences. In addition, we estimated the effect of the start of long breaks on the number of infections and found that they lead to a relatively higher level of infections regardless of lecture styles at the end of semesters. This implies that students are more likely to be infected outside than in class.

Evaluating the performance of selected military hospitals in Tehran in response to Covid-19 pandemic: A cross-sectional study.

The rapid spread of coronavirus disease 2019 (Covid-19) led the need to admit a large number of infected people to hospitals in a short period of time, turning them into one of the most important responsive organizations. This study aims to evaluate the performance of selected military hospitals because they carried out a military operation in Tehran in response to the recent pandemic. This is a descriptive-analytical study. The statistical population of this study consisted of military hospitals responding to Covid-19 pandemic in Tehran. A checklist to evaluate the performance of hospitals in response to Covid-19 pandemic (six areas, 23 sub-areas and 152 items) was used as a data collection tool in this study. This tool had six domains, including risk management and planning, coordination and communication, infection prevention and control, diagnosis and treatment, education and training, and resource management. The overall performance of selected hospitals was 63%, which indicated a good performance. The domain of coordination and communication obtained the lowest score. The investigated hospitals had good performance because they had a desirable access to resources. Periodic self-assessment and accreditation is recommended to improve the performance of these hospitals.

A meta-analysis of risk factors for acute kidney injury in pneumonia: Effectiveness of nursing interventions.

The spread of coronavirus disease 2019 (COVID-19) worldwide since November 2019 is of interest to understand its impact on various organs. COVID-19 patients experience a higher incidence of acute kidney injury (AKI) compared with non-COVID-19 patients. A systematic literature search was conducted that covered the period from November 1, 2019 to February 28, 2021. The analysis incorporated a comprehensive review of 19 studies of 21 362 patients. The older age (mean difference [MDs] = 5.11), cardiovascular disease (CVD) (odds ratio [OR] = 1.94), male sex (OR = 1.55), chronic kidney disease (CKD) (OR = 3.82), hypertension (OR = 2.15), diabetes (OR = 1.71), cancer (OR = 1.16), and chronic obstructive pulmonary disease (COPD) (OR = 1.40), mechanical ventilation (OR = 8.66), and vasopressor (OR = 6.30), were significantly associated with risk factor for AKI (P < 0.05). The analysis revealed independent risk factors for AKI.

Enablers and barriers to vaccine uptake and handwashing practices to prevent and control COVID-19 in Kenya, Uganda, and Tanzania: a systematic review.

The global emergence of coronavirus disease 2019 (COVID-19) posed unprecedented challenges, jeopardizing decades of progress in healthcare systems, education, and poverty eradication. While proven interventions such as handwashing and mass vaccination offer effective means of curbing COVID-19 spread, their uptake remains low, potentially undermining future pandemic control efforts. This systematic review synthesized available evidence of the factors influencing vaccine uptake and handwashing practices in Kenya, Uganda, and Tanzania in the context of COVID-19 prevention and control. We conducted an extensive literature search across PubMed, Science Direct, and Google Scholar databases following Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. Out of 391 reviewed articles, 18 were eligible for inclusion. Some of the common barriers to handwashing in Kenya, Uganda, and Tanzania included lack of trust in the government's recommendations or messaging on the benefits of hand hygiene and lack of access to water, while some of the barriers to vaccine uptake included vaccine safety and efficacy concerns and inadequate awareness of vaccination sites and vaccine types. Enablers of handwashing practices encompassed hand hygiene programs and access to soap and water while those of COVID-19 vaccine uptake included improved access to vaccine knowledge and, socio-economic factors like a higher level of education. This review underscores the pivotal role of addressing these barriers while capitalizing on enablers to promote vaccination and handwashing practices. Stakeholders should employ awareness campaigns and community engagement, ensure vaccine and hygiene resources' accessibility, and leverage socio-economic incentives for effective COVID-19 prevention and control. Clinical trial registration: [https://clinicaltrials.gov/], identifier [CRD42023396303].

Potential health risks to disinfection workers from exposure to active substances in COVID-19 biocidal products

The importance of disinfection has recently been emphasized due to the increasing risk of the spread of infections such as coronavirus disease-2019 (COVID-19). In addition, disinfection for preventing the spread of COVID-19 is highly recommended. The increased use of biocidal products raises concerns regarding the potential health risks from exposure among disinfection workers. This study aimed to assess these exposure and health risks using questionnaires targeting disinfection workers who were exposed to the active substances in biocidal products used for disinfection during the COVID-19 pandemic. A follow-up survey was conducted among 271 disinfection workers for 10 working days within two weeks, and exposure factors with reference to disinfection were evaluated through interview-administered questionnaires. An exposure algorithm was used to evaluate the exposure of disinfection workers during disinfection. The hazard index (HI) was calculated by dividing the inhalation concentration obtained using the exposure algorithm and the dermal dose according to occupational exposure limits (OEL). A sensitivity analysis was conducted to identify the exposure factors with the greatest impact on the inhalation and dermal exposure algorithms. A logistic regression analysis was performed to verify the relationship with health effects and sociodemographic and exposure characteristics. The average number of disinfections performed during 10 working days was 17.5 ± 12.3 times. The type of disinfection work was divided into 2806 cases of COVID-19 prevention and disinfection and 1956 cases of regular pesticide application to prevent and remove any pests. The HI was ≥1, indicating a potential health risk, with the use of ethanol (6.50E+00), quaternary ammonium compounds (QACs; 1.49E+01), and benzalkonium chloride (BKC; 1.73E+00). Dermal exposure was more hazardous than inhalation exposure for 6 of the 11 active substances in biocidal products. The weight fraction and exposure time were the factors that most significantly influenced the inhalation and dermal exposure algorithms in the sensitivity analysis. Higher exposure concentrations were more likely to affect health (AOR: 3.239, 95% CI: 1.155–9.082). This study provides valuable information regarding the exposure and risk of disinfection workers to 11 biocidal active substances included in common disinfectants. Our results suggest that the use of ethanol, BKC, and QACs has potential health risks to disinfection workers, with a higher possibility of negative health impacts with increasing exposure concentration.

Surveillance of the recurrence time of the effectiveness of national and region-level quarantines of COVID-19 pandemic in Chile.

The World Health Organization has recommended a range of social and health measures to mitigate the spread of coronavirus disease 2019 (COVID-19), including strategies such as quarantines, border closures, social distancing, and mask usage, among others. Specifically, the Chilean authorities implemented the "step-by-step" plan, built on the concept of dynamic quarantine. Numerous studies have examined the effectiveness of these quarantines in Chile during the pandemic, utilizing data published by the Chilean Ministry of Health. This study's primary aim was to enhance our understanding of quarantine effectiveness in Chile during the pandemic. We accomplished this by analyzing the distributional behavior of the time until the COVID-19 pandemic was deemed under control or not. In our study, we defined an event with two potential outcomes related to the instantaneous reproductive number (Rt), which signifies the time until a change in the event outcome occurs. Importantly, we did not predefine a specific temporal observation unit. These findings allowed us to complement the concept of effective quarantine by considering the dynamics generated by the protocols, such as phase 1 of the quarantine, in achieving natural herd immunity in response to the number of COVID-19 cases and Rt. We assessed the behavior of the mean and median residual lifetime until the initiation of controlled/uncontrolled episodes of the COVID-19 pandemic based on Rt in all regions of Chile. Despite variations in the distribution of residual times for controlled/uncontrolled episodes in different regions, there was a similar observation during the period considered (between March 2020 and March 2021): the mitigation measures did not produce a clear positive effect for controlling the epidemic. The residual times of episodes with Rr,t > 1 were not different from those episodes with Rr,t ≤ 1.

COVID-19 and Alzheimer's disease: Impact of lockdown and other restrictive measures during the COVID-19 pandemic.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection initially results in respiratory distress symptoms but can also lead to central nervous system (CNS) and neurological manifestations, significantly impacting coronavirus disease 2019 (COVID-19) patients with neurodegenerative diseases. Additionally, strict lockdown measures introduced to curtail the spread of COVID-19 have raised concerns over the wellbeing of patients with dementia and/or Alzheimer's disease. The aim of this review was to discuss the overlapping molecular pathologies and the potential bidirectional relationship between COVID-19 and Alzheimer's dementia, as well as the impact of lockdown/restriction measures on the neuropsychiatric symptoms (NPS) of patients with Alzheimer's dementia. Furthermore, we aimed to assess the impact of lockdown measures on the NPS of caregivers, exploring its potential effects on the quality and extent of care they provide to dementia patients.We utilized the PubMed and Google Scholar databases to search for articles on COVID-19, dementia, Alzheimer's disease, lockdown, and caregivers. Our review highlights that patients with Alzheimer's disease face an increased risk of COVID-19 infection and complications. Additionally, these patients are likely to experience greater cognitive decline. It appears that these issues are primarily caused by the SARS-CoV-2 infection and appear to be further exacerbated by restrictive/lockdown measures. Moreover, lockdown measures introduced during the pandemic have negatively impacted both the NPSs of caregivers and their perception of the wellbeing of their Alzheimer's patients. Thus, additional safeguard measures, along with pharmacological and non-pharmacological approaches, are needed to protect the wellbeing of dementia patients and their caregivers in light of this and possible future pandemics.

Influence of media campaigns efforts to control spread of COVID-19 pandemic with vaccination: A modeling study

Abstract The outbreak of coronavirus disease 2019 (COVID-19) has been declared a pandemic by the world health organization on March 11, 2020,. Here, a nonlinear mathematical model is proposed and analyzed to study the spread of coronavirus disease in a human habitat. In modeling the dynamics, the total population is divided into five subclasses: susceptible population, asymptomatic infective population, symptomatic infective population, recovered population, and vaccinated population. It is assumed that the disease is transmitted directly from infectives. It is further assumed that due to the effect of media, susceptible individuals become aware about the disease and avoid contact with the infectives. The analysis of the model is performed using the stability theory of differential equations. Furthermore, conditions that influence the persistence of the system are obtained. We have also conducted numerical simulations to validate the analytical results. The model analysis shows that with an increase in media awareness, the spread of coronavirus disease decreases with a decrease in the number of infective populations.

Estimation of the Impact of Vaccination Intervention on Recovered Coronavirus Patients

This work estimated the impact of vaccination intervention on coronavirus patients who have recovered from the disease and the vulnerability index of the recovered population due to the impact of vaccine was also investigated. This work adopted a numerical solution to study the continuous dynamical system of linear first order differential equations describing a SEIR (Susceptible, Exposed, Infected, Recovered) model on the spread of Coronavirus Disease – 2019 (COVID-19). To tackle this problem, MATLAB ordinary differential equation of order 45 (ODE45) numerical method was adopted for the analysis. The vulnerability index of the recovered population was low due to the impact of vaccine meaning that the recovered population will gain immunity and they will not be re-infected. The study recommended that coronavirus patients who have recovered from the disease should ensure that they have vaccination administered to them to avoid re-occurrence of the virus attack as an intervention strategy.

Preparedness, response, and preventive behaviors for a pandemic disaster caused by COVID-19 among primary school students in Krabi province, Thailand.

The global impact of the Coronavirus Disease 2019 (COVID-19) pandemic has been enormous. The primary school's role and responsibilities include providing students with education and training, cooperating and supporting educational management, and monitoring, following up, and evaluating the school's operations. The goals of this study were to evaluate the conditions of preparation for the COVID-19 epidemic's prevention and response, as well as to investigate the relationship between predisposing, enabling, and reinforcing factors in preventing the spread of COVID-19 among primary school students in the educational area. A cross-sectional analytical study was used as the research design. The informants are kids in grades 4-6 at Anuban Krabi School in Krabi province. Data is gathered in a computational quantitative manner. Purposive sampling was used to choose the informants. The researchers employed a questionnaire with a content validity index (CVI) of 0.89 and a reliability coefficient (Cronbach's Alpha Coefficient) of 0.89. For quantitative data analysis, the Pearson Correlation Coefficient was used. In preparation for the COVID-19 outbreak, there is a high degree of knowledge, behaviors, and self-conduct (x=2.78, 2.55, 2.66, and 2.78). The perception and awareness of the COVID-19 epidemic were statistically significant at P < 0.01 in terms of the relationship between perception, awareness, behavior, and self-conducting in stopping the spread of COVID-19. Conclusion: At P < 0.01, regarding the relationship between COVID-19 epidemic perceptions, behaviors, and self-conducting. The correlation between awareness, behaviors, and self-conducting in relation to the COVID-19 outbreak was statistically significant at P<0.01. To prepare and response for COVID-19 enhance and concern perceived policy and COVID-19 information, participation with stakeholders or communities emphasize COVID-19 prevention and all of organization and family.