Cumulative Number Of Cases Research Articles

Balancing act: How do local governments use social media in crises?

Governments can benefit from social media usage in crisis management, but the amplified public scrutiny facilitated by social media may also impede crisis management and damage reputations. How governments balance such benefits and risks when using social media for crisis communication remains an open question. With a data set of epidemic statistics and social media posts of local governments across China during the first wave of COVID-19, we quantitatively investigate how the local crisis situations and coping resources influenced government usage of social media. Our analysis reveals that the first confirmed case in a city leads to a significant increase in government social media use. This effect is stronger in cities with more medical resources. In addition, the number of cumulative cases has an inverted U-shaped influence on government social media use. These findings suggest that governments value the importance of social media for crisis handling and reputation protection, adapting their communication strategies based on the crisis severity and their own capacities.

Incidence, healthcare resource utilization and costs of hospitalized patients with tick-borne encephalitis (TBE) in Italy

ObjectiveOur study's objective was to assess the incidence trends and healthcare resource utilization of hospitalizations for Tick-Borne Encephalitis (TBE) and associated costs in Italy in order to improve public awareness and preventive measures. MethodsThis retrospective observational study was based on the Italian Ministry of Health's Hospital Discharge Record (HDR) database. Data were gathered across Italy from 2015 to 2019, selecting hospitalizations with ICD-9 code 063 related to TBE, both in primary and secondary diagnoses. For each year, we collected the following variables: number of hospitalizations, hospitalization rate, mortality rate, mean length of hospital stay, hospital ward, and cost of hospitalization. ResultsThere were a total of 237 hospitalizations from 2015 to 2019; 62 % of those were male. The lowest number of TBE hospitalizations was in 2015 (21 cases, corresponding to 0.35 per million inhabitants), the highest in 2019 (64 cases, 1.04 per million inhabitants). The summer months saw a greater than average number of hospitalizations. For the years analyzed, the cumulative number of cases peaked in June (54 cases), July (46 cases), and August (35 cases). There were only two deaths registered in our study sample. TBE cases were mostly localized in the North-Eastern regions of Italy. TBE incidence during the study period in the most affected areas were: Autonomous Province of Trento, ranging from 11.2 to 42.3 per million inhabitants, Autonomous Province of South Tyrol, from 0 to 21.1 per million inhabitants, and Veneto Region, from 2.6 to 4.5 per million inhabitants. In the study period, the average length of hospital stay was largely stable ranging from 10.6 days to 12.8 days, with related costs ranging from 5,813.7 € to 7,352.5 €. ConclusionsAccording to our data, the majority of TBE hospitalizations occur in North-East Italy with an increasing trend over the analyzed period. Even though Italy has fewer TBE cases than other neighboring European countries, the health and economic impact can be high in the affected areas.

Rate of post Covid-19 symptoms: a systematic review and meta-analysis

Background. Covid-19 pandemic has led to global pandemic and substantial health, economic and social impact. The causative agent is coronavirus-2 (SARS-CoV-2) which belongs to the coronavirus family. The clinical picture of the infection ranges from a flu-like symptoms to severe pneumonia and mortality. Till January 2022, the cumulative number of cases exceeded 600 million worldwide with mortality rate of more than 6 million. Objective: to identify rate of total and individual presentations of post COVID-19 conditions. Methodology: the literature was reviewed till 1st July 2022, in six databases, we identified 5486 articles; after removal of duplicates and screening for eligible studies according to inclusion criteria, 17 studies were included for further qualitative and quantitative analysis. Results: the results showed high rate of post COVID-19 condition among patients. With prevalence rate of 5 to 10%, fatigue was the most reported symptom with prevalence of 34% among patients (RE: 0.33%, 95%CI: 0.32-0.35). The second highest common symptom was breathlessness with prevalence of 31% (RE: 0.31, 95%CI: 0.20-0.43). Mental health symptoms including anxiety and depression were also distinctly frequent. We also reported on different neurocognitive symptoms including attention and memory problems with rate of 16% (RE: 0.16, 95%CI: 0.11-0.22) and 19% (RE: 0.19, 95%CI: 0.14-0.26) respectively. Conclusion: it is apparent that a significant percentage of individuals with COVID-19 (45%) continue to grapple with a variety of persistent symptoms. Among these, fatigue and dyspnea emerge as highly prevalent issues consistently reported across various groups of patients. However, it is evident that a considerable portion of patients also contend with a diverse array of other lingering symptoms, displaying variability both in number and severity.

Impact assessment of self-medication on COVID-19 prevalence in Gauteng, South Africa, using an age-structured disease transmission modelling framework

ObjectiveTo assess the impact of self-medication on the transmission dynamics of COVID-19 across different age groups, examine the interplay of vaccination and self-medication in disease spread, and identify the age group most prone to self-medication.MethodsWe developed an age-structured compartmentalized epidemiological model to track the early dynamics of COVID-19. Age-structured data from the Government of Gauteng, encompassing the reported cumulative number of cases and daily confirmed cases, were used to calibrate the model through a Markov Chain Monte Carlo (MCMC) framework. Subsequently, uncertainty and sensitivity analyses were conducted on the model parameters.ResultsWe found that self-medication is predominant among the age group 15-64 (74.52%), followed by the age group 0-14 (34.02%), and then the age group 65+ (11.41%). The mean values of the basic reproduction number, the size of the first epidemic peak (the highest magnitude of the disease), and the time of the first epidemic peak (when the first highest magnitude occurs) are 4.16499, 241,715 cases, and 190.376 days, respectively. Moreover, we observed that self-medication among individuals aged 15-64 results in the highest spreading rate of COVID-19 at the onset of the outbreak and has the greatest impact on the first epidemic peak and its timing.ConclusionStudies aiming to understand the dynamics of diseases in areas prone to self-medication should account for this practice. There is a need for a campaign against COVID-19-related self-medication, specifically targeting the active population (ages 15-64).

Intraoperative neuromonitoring during thyroidectomy does not decrease vocal cord palsy risk, but the cumulative experience of the surgeon may

PurposeTo evaluate the influence of intraoperative neuromonitoring (IONM) on vocal cord palsy (VCP) rates and assess the temporal trends in VCP rates.MethodsThe subjects of this retrospective study were patients who underwent thyroidectomy for thyroid cancer between March, 2014 and June, 2022, at a university hospital in Korea. We compared VCP rates between the non-IONM and IONM groups and analyzed the risk factors for VCP and VCP rates over time.ResultsA total of 712 patients were included in the analysis. The rates of transient and permanent VCP did not differ significantly between the non-IONM and IONM groups. Transient VCP occurred in 4.6% and 4.3% patients (p = 0.878) and VCP was permanent in 0.7% and 0.4% patients (p = 0.607) in the non-IONM and IONM groups, respectively. Among the nerves at risk, transient damage occurred in 2.8% and 3.0% patients (p = 0.901), and permanent damage occurred in 0.4% and 0.3% (p = 0.688), respectively. Multivariate analysis revealed no significant risk factors for VCP. There was a significant decreasing trend in VCP rates over time as the cumulative number of cases increased (p = 0.017).ConclusionsIONM did not reduce the risk of VCP significantly. However, the declining trend of VCP rates suggests that the surgeon’s experience may mitigate VCP risk.

The role of colchicine in the management of COVID-19: a Meta-analysis

BackgroundThe Coronavirus disease 2019 (COVID-19) pandemic has robustly affected the global healthcare and economic systems and it was caused by coronavirus-2 (SARS-CoV-2). The clinical presentation of the disease ranges from a flu-like illness to severe pneumonia and death. Till September 2022, the cumulative number of cases exceeded 600 million worldwide and deaths were more than 6 million. Colchicine is an alkaloid drug that is used in many autoinflammatory conditions e.g., gout, familial Mediterranean fever, and Behçet’s syndrome. Colchicine inhibits the production of superoxide and the release of interleukins that stimulate the inflammatory cascade. Colchicine decreases the differentiation of myofibroblast and the release of fibrotic mediators including transforming growth factor (TGF-β1) that are related to the fibrosis. Moreover, colchicine has been used to traet viral myocarditis caused by CMV or EBV, interstitial pneumonia, and pericarditis resulting from influenza B infection. Additionally, colchicine is considered safe and affordable with wide availability.ObjectiveThe aim of the current study was to assess the evidence of colchicine effectiveness in COVID-19 treatment.MethodsA comprehensive review of the literature was done till May 2022 and yielded 814 articles after ranking the articles according to authors and year of publication. Only 8 clinical trials and cohort studies fulfilling the inclusion criteria were included for further steps of data collection, analysis, and reporting.ResultsThis meta-analysis involved 16,488 patients; 8146 patients in the treatment group and 8342 patients in the control group. The results showed that colchicine resulted in a significant reduction in the mortality rate among patients received colchicine in comparison with placebo or standard care (RR 0.35, 95%CI: 0.15–0.79). Colchicine resulted in a significant decrease in the need for O2 therapy in patients with COVID-19 (RR 0.07, 95%CI 0.02–0.27, P = 0.000024). However, colchicine had no significant effect on the following outcomes among COVID-19 patients: the need for hospitalization, ICU admission, artificial ventilation, and hospital discharge rate. Among the PCR confirmed COVID-19 patients, colchicine decreased the hospitalization rate (RR 0.75, 95%CI 0.57–0.99, P = 0.042). However, colchicine had no effect on mortality and the need for mechanical ventilation among this subgroup.ConclusionColchicine caused a significant clinical improvement among COVID-19 patients as compared with the standard care or placebo, in terms of the need for O2, and mortality. This beneficial effect could play a role in the management of COVID-19 especially severe cases to decrease need for oxygen and to decrease mortality among these patients.

How individuals’ opinions influence society’s resistance to epidemics: an agent-based model approach

BackgroundProtecting public health from infectious diseases often relies on the cooperation of citizens, especially when self-care interventions are the only viable tools for disease mitigation. Accordingly, social aspects related to public opinion have been studied in the context of the recent COVID-19 pandemic. However, a comprehensive understanding of the effects of opinion-related factors on disease spread still requires further exploration.MethodsWe propose an agent-based simulation framework incorporating opinion dynamics within an epidemic model based on the assumption that mass media channels play a leading role in opinion dynamics. The model simulates how opinions about preventive interventions change over time and how these changes affect the cumulative number of cases. We calibrated our simulation model using YouGov survey data and WHO COVID-19 new cases data from 15 different countries. Based on the calibrated models, we examine how different opinion-related factors change the consequences of the epidemic. We track the number of total new infections for analysis.ResultsOur results reveal that the initial level of public opinion on preventive interventions has the greatest impact on the cumulative number of cases. Its normalized permutation importance varies between 69.67% and 96.65% in 15 models. The patterns shown in the partial dependence plots indicate that other factors, such as the usage of the pro-intervention channel and the response time of media channels, can also bring about substantial changes in disease dynamics, but only within specific ranges of the dominant factor.ConclusionsOur results reveal the importance of public opinion on intervention during the early stage of the pandemic in protecting public health. The findings suggest that persuading the public to take actions they may be hesitant about in the early stages of epidemics is very costly because taking early action is critical for mitigating infectious diseases. Other opinion-related factors can also lead to significant changes in epidemics, depending on the average level of public opinion in the initial stage. These findings underscore the importance of media channels and authorities in delivering accurate information and persuading community members to cooperate with public health policies.

Mutations make pandemics worse or better: modeling SARS-CoV-2 variants and imperfect vaccination.

COVID-19 is a respiratory disease triggered by an RNA virus inclined to mutations. Since December 2020, variants of COVID-19 (especially Delta and Omicron) continuously appeared with different characteristics that influenced death and transmissibility emerged around the world. To address the novel dynamics of the disease, we propose and analyze a dynamical model of two strains, namely native and mutant, transmission dynamics with mutation and imperfect vaccination. It is also assumed that the recuperated individuals from the native strain can be infected with mutant strain through the direct contact with individual or contaminated surfaces or aerosols. We compute the basic reproduction number, , which is the maximum of the basic reproduction numbers of native and mutant strains. We prove the nonexistence of backward bifurcation using the center manifold theory, and global stability of disease-free equilibrium when , that is, vaccine is effective enough to eliminate the native and mutant strains even if it cannot provide full protection. Hopf bifurcation appears when the endemic equilibrium loses its stability. An intermediate mutation rate leads to oscillations. When increases over a threshold, the system regains its stability and exhibits an interesting dynamics called endemic bubble. An analytical expression for vaccine-induced herd immunity is derived. The epidemiological implication of the herd immunity threshold is that the disease may effectively be eradicated if the minimum herd immunity threshold is attained in the community. Furthermore, the model is parameterized using the Indian data of the cumulative number of confirmed cases and deaths of COVID-19 from March 1 to September 27 in 2021, using MCMC method. The cumulative cases and deaths can be reduced by increasing the vaccine efficacies to both native and mutant strains. We observe that by considering the vaccine efficacy against native strain as 90%, both cumulative cases and deaths would be reduced by 0.40%. It is concluded that increasing immunity against mutant strain is more influential than the vaccine efficacy against it in controlling the total cases. Our study demonstrates that the COVID-19 pandemic may be worse due to the occurrence of oscillations for certain mutation rates (i.e., outbreaks will occur repeatedly) but better due to stability at a lower infection level with a larger mutation rate. We perform sensitivity analysis using the Latin Hypercube Sampling methodology and partial rank correlation coefficients to illustrate the impact of parameters on the basic reproduction number, the number of cumulative cases and deaths, which ultimately sheds light on disease mitigation.

Epidemiology of Reportable Bacterial Infectious Diseases in Saudi Arabia.

Bacterial infections have a significant impact on human health; they can cause severe morbidity and mortality, particularly in susceptible populations. Epidemiological surveillance is a critical tool for monitoring the population's health and facilitate the prevention and control of infectious disease outbreaks. Knowing the burden of bacterial communicable diseases is an initial core step toward public health goals. Saudi epidemiology surveillance data were utilized to depict the changing epidemiology of bacterial infectious diseases in Saudi Arabia from 2018 to 2021. The cumulative numbers of cases, demographics, and incidence rates were analyzed and visualized. Parametric tests were used to compare the difference in the mean values between categorical variables. Regression analysis was employed to estimate trends in disease rates over time. Statistical significance was set at pvalue ≤ 0.05. The results revealed that brucellosis, tuberculosis, and salmonellosis were the most frequently reported bacterial infectious diseases in Saudi Arabia. Males were more significantly affected by brucellosis and tuberculosis infections than females. Salmonellosis infections were more significant among Saudi citizens, while pulmonary tuberculosis was more significant in non-Saudis. Interestingly, there was a decline in the incidence rates of numerous bacterial infectious diseases during the Coronavirus Disease 2019 (COVID-19) pandemic and COVID-19 restrictions. Some bacterial infectious diseases were rarely reported in Saudi Arabia, including syphilis and diphtheria. The future perspective of this research is to enhance disease surveillance reporting by including different variables, such as the source of infection, travel history, hospitalization, and mortality rates. The aim is to improve the sensitivity and specificity of surveillance data and focus on the mortality associated with bacterial pathogens to identify the most significant threats and set a public health priority.

Learning curve of ultrasound-guided percutaneous nephrolithotripsy in the treatment of complex renal calculi.

This study was performed to investigate the learning curve of ultrasound-guided percutaneous nephrolithotripsy (PCNL) for the treatment of complex renal calculi. Seventy-two patients with complex renal stones who underwent ultrasound-guided PCNL by the same operator from November 2016 to September 2020 were retrospectively analyzed. The learning curve of PCNL for complex renal stones was analyzed using multifactorial cumulative sum (CUSUM) analysis and best-fit curves. The CUSUM best-fit curve peaked at Case 36, which represented the minimum number of cumulative cases required to cross the learning curve for this surgical procedure. Accordingly, the learning curve was divided into a learning improvement period (36 cases) and a proficiency phase (36 cases). Compared with the learning improvement period, the proficiency phase was characterized by a shorter puncture time and operation time, a smaller drop in the hemoglobin level, and a lower postoperative complication rate. The learning curve of PCNL for the treatment of complex renal calculi can be divided into a learning improvement period and a proficiency phase, and the minimum cumulative number of cases is 36.

A New Bimodal Growth Speed Model With Application in Multiwave Epidemic Simulations

An epidemic can cause enormous damage through financial and economic losses in addition to impaired health and loss of life. Good epidemic models can provide insights into ongoing waves that may facilitate public health responses and other readiness. Epidemic systems can undergo or consist of more than two driving forces; actually, they involve several. This paper deals with the modeling epidemics with two wave dynamics. We present a mathematical model with three driving forces, which is more compatible with the biology of the epidemic than conventional bilogistic and bi‐Richards ones, which have two driving forces. Simulation results show that our proposed model can predict turning points (waves) and cumulative case numbers during the two waves of epidemics satisfactorily. As a sample examination of our proposed model against real data, we show that the second phase of a typical epidemic can be detected by using less case data past the beginning of the epidemic than the bi‐Richards model.

The balance between traffic control and economic development in tourist cities under the context of COVID-19: A case study of Xi'an, China.

Selecting an appropriate intensity of epidemic prevention and control measures is of vital significance to promoting the two-way dynamic coordination of epidemic prevention and control and economic development. In order to balance epidemic control and economic development and suggest scientific and reasonable traffic control measures, this paper proposes a SEIQR model considering population migration and the propagation characteristics of the exposed and the asymptomatic, based on the data of COVID-19 cases, Baidu Migration, and the tourist economy. Further, the factor traffic control intensity is included in the model. After determining the functional relationship between the control intensity and the number of tourists and the cumulative number of confirmed cases, the NSGA-II algorithm is employed to perform multi-objective optimization with consideration of the requirements for epidemic prevention and control and for economic development to get an appropriate traffic control intensity and suggest scientific traffic control measures. With Xi'an City as an example. The results show that the Pearson correlation coefficient between the predicted data of this improved model and the actual data is 0.996, the R-square in the regression analysis is 0.993, with a significance level of below 0.001, suggesting that the predicted data of the model are more accurate. With the continuous rise of traffic control intensity in different simulation scenarios, the cumulative number of cases decreases by a significant amplitude. While balancing the requirements for epidemic prevention and control and for tourist economy development, the model works out the control intensity to be 0.68, under which some traffic control measures are suggested. The model presented in this paper can be used to analyze the impacts of different traffic control intensities on epidemic transmission. The research results in this paper reveal the traffic control measures balancing the requirements for epidemic prevention and control and for economic development.

10098-MPC-10 HOW SHOULD WE RESPOND TO REPEATED WHO REVISIONS? IN-HOUSE MOLECULAR DIAGNOSIS SYSTEM BY ADVANCED MEDICAL SYSTEM

Abstract BACKGROUND Since the WHO2016 revision, required molecular markers has been increasing, placing a burden on clinical practice of diffuse gliomas. We established an in-house molecular diagnostic platform by Senshin-Iryo (meaning advanced medical care system) and have since been partially modifying the analysis method in accordance with the WHO2021 revision. We review our achievements in total 5 years. METHODS Analyses of IDH, BRAF, and H3 point mutations, loss of heterozygosity on 1p19q and chromosomes 10 and 17, and MGMT methylation were combined into a set and submitted as a Senshin-Iryo "Drug resistance gene testing for anticancer chemotherapy" and approved in August 2018. Subsequently, in October 2021, Sanger sequencing for TERT promotor mutation was added to the set and the LOH analysis was replaced to MLPA, in order to analyze 1p19q codeletion and newly required genetic markers; EGFR, PTEN, CDKN2A, etc. in WHO2021. RESULTS The cumulative number of cases has reached over 200. Among them, 54 cases were analyzed after WHO2021 revision. The laboratory has maintained the diagnostic platform in which molecular diagnoses are steadily confirmed generally within two weeks. The initial expenditure was exceeded the income obtained from the patient co-payment, however, it has gradually been reduced to running costs alone, then is approaching profitability. After WHO2021 revision, diagnoses could be confirmed by molecular markers obtained from Senshin-Iryo in 38 of 54 cases (70.1%). Among the remaining 16, only 4 (7.4%) cases remained diagnosed as diffuse glioma, NEC, exclusionary after 12 cases in which glioblastoma was confirmed by histopathological diagnosis. CONCLUSIONS Our Senshin-Iryo trial has functioned as a salvage system to overcome the current transition period in which the continuing revision of WHO classification causing a clinical dilemma of healthcare system.

Predicting Number of Accumulative Cases of Covid-19 Using the Iteration Method

The COVID-19 pandemic, first identified in Wuhan, China in December 2019, has rapidly spread to various countries, including India and Indonesia. This study utilizes data from the cumulative cases in India and Indonesia, espand specific provinces within Indonesia, such as DKI Jakarta and Gorontalo, spanning a period of approximately two years. The proposed method incorporates factors such as expected recovery and mortality rates to determine the maximum daily growth, which deviates from exponential growth and tends towards stability or decline. RStudio software was employed to estimate future trends based on the current available data. The results indicate that Indonesia, Jakarta, and Gorontalo exhibit a sloping average growth rate over the past 30 days, while India demonstrates linear movement compared to the previous period. A 20% increase in growth rate in Jakarta leads to a significant rise in new cases compared to the other regions. Conversely, a 0% growth rate reduction in India and Gorontalo results in a notable deviation of cumulative case numbers from the actual data. This method can be applied to analyze similar problems if in the future there is another spread of pandemic diseases.Keywords: COVID-19, Iteration Method, Exponential Growth, Gorontalo and DKI Jakarta.

Community transmission of SARS-CoV-2 during the Delta wave in New York City

BackgroundUnderstanding community transmission of SARS-CoV-2 variants of concern (VOCs) is critical for disease control in the post pandemic era. The Delta variant (B.1.617.2) emerged in late 2020 and became the dominant VOC globally in the summer of 2021. While the epidemiological features of the Delta variant have been extensively studied, how those characteristics shaped community transmission in urban settings remains poorly understood.MethodsUsing high-resolution contact tracing data and testing records, we analyze the transmission of SARS-CoV-2 during the Delta wave within New York City (NYC) from May 2021 to October 2021. We reconstruct transmission networks at the individual level and across 177 ZIP code areas, examine network structure and spatial spread patterns, and use statistical analysis to estimate the effects of factors associated with COVID-19 spread.ResultsWe find considerable individual variations in reported contacts and secondary infections, consistent with the pre-Delta period. Compared with earlier waves, Delta-period has more frequent long-range transmission events across ZIP codes. Using socioeconomic, mobility and COVID-19 surveillance data at the ZIP code level, we find that a larger number of cumulative cases in a ZIP code area is associated with reduced within- and cross-ZIP code transmission and the number of visitors to each ZIP code is positively associated with the number of non-household infections identified through contact tracing and testing.ConclusionsThe Delta variant produced greater long-range spatial transmission across NYC ZIP code areas, likely caused by its increased transmissibility and elevated human mobility during the study period. Our findings highlight the potential role of population immunity in reducing transmission of VOCs. Quantifying variability of immunity is critical for identifying subpopulations susceptible to future VOCs. In addition, non-pharmaceutical interventions limiting human mobility likely reduced SARS-CoV-2 spread over successive pandemic waves and should be encouraged for reducing transmission of future VOCs.

No increased risk of intussusception after pentavalent rotavirus vaccination in China: a retrospective birth cohort using electronic health records of Ningbo city

ABSTRACT Some post-licensure studies have shown a potential increased risk of intussusception following vaccination with rotavirus vaccines. This is the first study that aimed to assess the incidence and risk of intussusception within 90 days after vaccination with RotaTeq in Chinese infants. A population-based birth cohort from 27th November 2018 to 30th June 2021 included all newborns in Ningbo city. The records of intussusception were identified through the ICD-10 code K56.1 or Chinese keywords “Chang Tao” from all hospital discharge records. Each episode was confirmed in line with the Brighton criteria, and only Brighton level 1 cases were included. The association of RotaTeq vaccination and intussusception was evaluated using the Poisson regression. A total of 108,405 eligible subjects from birth cohort were eligible, with 52.30% males. Among them, 26, 847 (24.77%) infants received at least one dose of RotaTeq, and 95.52% of them were fully vaccinated, with 76, 934 doses in total. After adjudication, none of the cases occurred post first, or second dose, the cumulative number of cases that occurred 1–7, 1–14, 1–21, 1–42, and 1–90 days post third dose was 0, 1, 1, 3, and 7, respectively. Adjusting for age, sex, birth year, birth season and location, the incidence rate ratio of intussusception after RotaTeq vaccination was 0.90 (90% two-sided CI: 0.46, 1.75). Increasing age and male gender were associated with higher risk of intussusception. In summary, no increased risk of IS was observed following 3 months of RotaTeq vaccination in this study.

Did the emergence of the Omicron variant impact the COVID-19 vaccine acceptance in the Arab world? A Twitter-based sentiment analysis

Background: Low vaccine acceptance constitutes a major obstacle for achieving herd immunity against coronavirus disease 2019 (COVID-19). Data on COVID-19 show a significant rise in the number of cumulative cases in Arab countries where vaccine uptake is lower than the uptake at the global level for the 2021-2022 period. The aim of this study is to analyze sentiments related to vaccine acceptance before and after the emergence of the COVID-19 Omicron variant in the Arab-speaking world. Methods: Tweets were collected before and after the Omicron emergence period in the Arab-speaking world using Python-enabled CAMeL Tools (Arabic Natural Language Processing toolkit) libraries. A sentiment analysis on COVID-19 vaccines using Arabic hashtags and a sentiment analysis by city were conducted. Results: Two data sets pre-Omicron and post-Omicron tweets exhibited a difference in sentiments marking a shift towards less negativity and more neutrality. Sentiments by city showed most tweets in both periods coming from Riyadh and Jeddah in Saudi-Arabia, and from Salt in Jordan. Conclusions: Despite the limitations of the study, the change in sentiments detected by the study may suggest more vaccine acceptance which raises some hope and perhaps a higher vaccine uptake in the future. The sentiments by city findings may help in the design of future research.

A compartmental model for COVID-19 to assess effects of non-pharmaceutical interventions with emphasis on contact-based quarantine

Relative to the number of casualties, COVID-19 ranks among the ten most devastating plagues in history. The pandemic hit the South Asian nation of Bangladesh in early March 2020 and has greatly impacted the socio-economic status of the country. In this article, we propose a compartmental model for COVID-19 dynamics, introducing a separate class for quarantined susceptibles, synonymous to isolation of individuals who have been exposed and are suspected of being infected. The current model assumes a perfect quarantine based on contact with infectious individuals. Numerical simulation is conducted to investigate the efficiency of disease control by segregating suspected individuals and other non-pharmaceutical interventions. In addition, we assort quantitatively the importance of parameters that influence the dynamics of the system. Fitting the system to the early phase of COVID-19 outbreaks in Bangladesh, by taking into account the cumulative number of cases with the data of the first 17-week period, the basic reproduction number is estimated as 1.69.

The relationship between vaccine acceptance and COVID-19 mortality in Europe: A Cross-Country analysis of public opinion and Epidemiological data

IntroductionMore than two years after SARS-CoV-2 emerged in Wuhan, China, COVID-19 has become one of the most severe pandemics in modern human history. Prior to the widespread availability of specific vaccines in 2021, public opinion surveys indicated significant vaccine hesitancy in 26 European countries. Materials and methodsEpidemiological data on COVID-19 morbidity and mortality for 26 European countries were collected in November 2021 and compared with the proportions of people willing to receive the SARS-CoV-2 vaccine according to public opinion surveys analysed in 2020. Correlations between various variables were calculated using the Pearson correlation test and visualized with the R programming language. ResultsPaired Student's t-test revealed no significant differences between survey results and actual vaccination rates (p = 0.9546), suggesting that the polls were good predictors. The percentage of people willing to receive the SARS-CoV-2 vaccine was significantly positively correlated with actual vaccination rates (R = 0.72, p = 0.00003) and significantly negatively correlated with the number of cumulative deaths per million people (R = -0.78, p = 0.0000024). However, there was no significant correlation with the number of cumulative cases per million people (R = -0.27, p = 0.18). These findings indicate that vaccines used in Europe were particularly effective at preventing severe COVID-19 and disease-related deaths, but did not necessarily provide strong protection against SARS-CoV-2 infection itself. ConclusionEncouraging widespread immunization through vaccination was crucial for rapidly improving the epidemiological situation in Europe.

A study on the transmission dynamics of COVID-19 considering the impact of asymptomatic infection

The COVID-19 epidemic has been spreading around the world for nearly three years, and asymptomatic infections have exacerbated the spread of the epidemic. To analyse and evaluate the role of asymptomatic infections in the spread of the epidemic, we establish an improved COVID-19 infectious disease dynamics model. We fit the epidemic data in the four time periods corresponding to the selected 614G, Alpha, Delta and Omicron variants and obtain the proportion of asymptomatic persons among the infected persons gradually increased and with the increase of the detection ratio, the cumulative number of cases has dropped significantly, but the decline in the proportion of asymptomatic infections is not obvious. Therefore, in view of the hidden transmission of asymptomatic infections, the cooperation between various epidemic prevention and control policies is required to effectively curb the spread of the epidemic.