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1.
Risk Manag Healthc Policy ; 15: 1741-1749, 2022.
Article | MEDLINE | ID: covidwho-2166181

Résumé

Purpose: This study aimed to investigate the impact of characteristic ischemic stroke and outcomes during the first COVID-19 pandemic lockdown. Patients and Methods: A retrospective, observational cohort study of a comprehensive tertiary stroke center was conducted. Patients with ischemic stroke were divided into pre-COVID-19 lockdown (11/1/2019 to 1/30/2020) and COVID-19 lockdown (1/31/2020 to 4/30/2020) period groups. Patient data on stroke admission, thrombolysis, endovascular treatment, and 3-month routine follow-up were recorded. Data analysis was performed using SPSS according to values following a Gaussian distribution. Results: The pre-COVID-19 lockdown period group comprised 230 patients compared to 215 patients in the COVID-19 lockdown period group. Atrial fibrillation was more predominant in the COVID-19 lockdown period group (11.68% vs 5.65%, p=0.02) alongside patients who were currently smoking (38.8% vs 28.7%, p=0.02) and drinking alcohol (30.37% vs 20.00%, p=0.012) compared with that of the pre-COVID-19 lockdown period group. For patients receiving thrombolysis, the median door-to-CT time was longer in the COVID-19 lockdown period group (17.0 min (13.0, 24.0) vs 12.0 min (8.0, 17.3), p=0.012), median door to needle time was 48.0 minutes (35.5, 73.0) vs 43.5 minutes (38.0, 53.3), p=0.50, compared with that of the pre-COVID-19 lockdown period group. There were no differences for patients receiving mechanical thrombectomy. The median length of hospitalization (IQR) was no different. Discharge mRS scores (IQR) were higher in the COVID-19 lockdown period group (1.0 (1.0, 3.0) vs 1.0 (1.0, 2.0), p=0.022). Compared with the pre-COVID-19 lockdown period, hospitalization cost (Chinese Yuan) in the COVID-19 period group was higher (13,445.7 (11,009.7, 20,030.5) vs 10,799.2 (8692.4, 16,381.7), p=0.000). There was no difference observed in 3-month mRS scores. Conclusion: Patients presenting with ischemic stroke during the COVID-19 pandemic lockdown period had longer median door-to-CT time and higher hospitalization costs. There were no significant differences in 3-month outcomes. Multidisciplinary collaboration and continuous workflow optimization may maintain stroke care during the COVID-19 pandemic lockdown.

2.
Risk Manag Healthc Policy ; 15: 1859-1868, 2022.
Article Dans Anglais | MEDLINE | ID: covidwho-2166176

Résumé

Background: To prevent the spread of COVID-19 and carry out a successful vaccination program especially in low-income countries, people must have faith on scientists and health experts. The most significant challenge to vaccination programs' efficacy is now regarded to be a lack of information and trust in immunization due to myths and misinformation spread in the community. Therefore, this study aimed to identify the myth and misconceptions that are propagated about the COVID-19 vaccine, the refusal rate of the vaccine and determine the factors associated with COVID-19 vaccine refusal. Methods: A community-based cross-sectional study was conducted from December 7 to January 25, 2022. Face-to-face interviews with a standardized questionnaire were used to collect data on the variables. Data were entered into the statistical tool Epi data version 3.1 and then exported to SPSS version 25 for analysis. Binary logistic regression, both bivariable and multivariable, was conducted. In the multivariable binary logistic regression model, the adjusted odds ratio with 95% confidence interval was used to declare statistically significant factors based on a p value less than 0.05. Results: Out of the total 574 respondents, 60.3% [95% CI (55.5, 64.2)] of them refused to take COVID-19 vaccine. In this study, respondent's age [AOR = 2.1 at 95% CI: (1.8, 4.9)], perception on COVID-19 vaccine [AOR = 3.0 at 95 CI: (1.9, 4.6)], eHealth literacy [AOR = 2.7 at 95% CI: (1.7, 4.1)], source of information about the vaccine [AOR = 2.9 at 95% CI: (1.9, 4.4)], computer literacy [AOR = 2.8 at 95 CI: (1.8, 4.2)] and frequency of internet use [AOR = 2.2 at 95 CI: (1.8, 5.3)] were identified as determinant factors for COVID-19 vaccine acceptance. Conclusion: Factors like eHealth literacy, source of information about the vaccine, frequency of internet use, respondent's perception about the vaccine and computer literacy were found to be determinant factors for COVID-19 vaccine acceptance.

3.
International Journal of Clinical and Health Psychology ; : 100364, 2022.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165365

Résumé

The present study examined the impact of the COVID-19 pandemic on the emotional quality of dreams, the incorporation of pandemic-related themes, and the occurrence of lucid dreaming. Dream reports and lucidity ratings of psychiatric outpatients (n = 30) and healthy controls (n = 81) during two lockdowns in Germany were compared to those of healthy controls (n = 33) before the pandemic. Results confirmed previous reports that pandemic-specific themes were incorporated into dreams. Overall, however, incorporation into dreams was rare. Contrary to expectations, psychiatric outpatients did not differ from controls in the frequency of dream incorporation of pandemic-related content. Moreover, incorporation was independent of psychiatric symptoms and loneliness. Loneliness was, however, associated with threat-related content, suggesting that it represents a risk for bad dreams but not for crisis-specific dream incorporation. Regarding lucid dreaming, both groups had similar scores for its underlying core dimensions, i.e., insight, control, and dissociation, during the two lockdowns. Scores for control and dissociation but not insight were lower compared to the pre-pandemic sample. Our working hypothesis is that REM sleep during lockdowns intensified as a means of increased emotional consolidation, rendering the associated mental state less hybrid and thereby less lucid.

4.
International Journal of Cardiology Congenital Heart Disease ; : 100434, 2022.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165364

Résumé

Background The COVID-19 pandemic has significantly increased stress and strain on health professionals. With a focus on paediatric cardiac care, this study explored health professionals' concerns about COVID-19, perceptions of the impact of pandemic on healthcare, and experiences of psychological stress. Methods Paediatric health professionals working at a large quaternary hospital in Australia were invited to complete a survey between June 2020 and February 2021. Demographic factors, clinical role characteristics, and anxiety and depressive symptoms were assessed. Qualitative data on experiences and perceived effects of the pandemic on paediatric cardiac care were also collected. Results 228 health professionals (152 nurses, 37 medical doctors, 22 allied and mental health professionals, 17 medical research and administrative staff) participated in the survey (54.4% response rate, 85% women). Half the sample (52.2%) endorsed ‘moderate' to ‘extreme' worry about COVID-19 and 38% of participants perceived healthcare services as adversely impacted by the pandemic to a ‘great' or ‘very great' extent. Almost one in five health professionals reported anxiety (18%) and 11% reported depressive symptoms indicative of a need for clinical intervention. Six themes were identified in the qualitative data: (1) Concern about the consequences of visitor restrictions and disrupted patient services, (2) Intensified strain on healthcare workers, (3) Feelings of fear and loss, (4) Social isolation and disconnection, (5) Adapting to change, and (6) Gratitude. Conclusion Timely, tailored policies, supports, and interventions are needed to address health professionals' mental health needs during and beyond the pandemic, to minimize the far-reaching impact of situational stressors.

5.
International Journal of Antimicrobial Agents ; : 106708, 2023.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165360

Résumé

Nirmatrelvir/ritonavir (N/R) is among the most effective antiviral drugs against SARS-CoV-2. We review here the preclinical development, pharmacodynamics and pharmacokinetics of N/R. Randomized clinical trials have been exclusively run with pre-Omicron variants of concern, but in vitro studies show that efficacy against all Omicron sublineages is preserved, as confirmed by post-marketing observational studies. Nevertheless, investigations of large viral genome repositories have shown that mutation in the main protease causing resistance to N/R are increasingly frequent. In addition, virological and clinical rebounds after N/R discontinuation have been reported in immunocompetent patients. This finding is of concern when translated to immunocompromised patients, for which N/R efficacy has never been formally investigated in clinical trials. We finally discuss economical sustainability and perspectives for this therapeutic arena

6.
Infectious Disease Modelling ; 2023.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165359

Résumé

Recently some of us used a random-walk Monte Carlo simulation approach to study the spread of COVID-19. The calculations were reasonably successful in describing secondary and tertiary waves of infection, in countries such as the USA, India, South Africa and Serbia. However, they failed to predict the observed third wave for India. In this work we present a more complete set of simulations for India, that take into consideration two aspects that were not incorporated previously. These include the stochastic movement of an erstwhile protected fraction of the population, and the reinfection of some recovered individuals because of their exposure to a new variant of the SARS-CoV-2 virus. The extended simulations now show the third COVID-19 wave for India that was missing in the earlier calculations. They also suggest an additional fourth wave, which was indeed observed during approximately the same time period as the model prediction.

7.
Infectious Disease Modelling ; 2023.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165358

Résumé

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 vt and controlled rate vc) to evaluate the overall effect of the interventions. It is shown that for Zhengzhou, vc is always more than vt with regular interventions, and Xi'an take 8 days to achieve vc > vt 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.

8.
Infectious Disease Modelling ; 2022.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165357

Résumé

Virus evolution is a common process of pathogen adaption to host populations and environments. Frequently, a small but important fraction of virus mutations are reported to contribute to higher risks of host infection, which is one of the major determinants of infectious diseases outbreaks at population scale. The key mutations contributing to transmission advantage of a genetic variant often grows and reaches fixation rapidly. Based on classical epidemiology theories of disease transmission, we proposed a mechanistic explanation of the process that between-host transmission advantage may shape the observed logistic curve of the mutation proportion in population. The logistic growth of mutation is further generalized by incorporating time-varying selective pressure to account for impacts of external factors on pathogen adaptiveness. The proposed model is implemented in real-world data of COVID-19 to capture the emerging trends and changing dynamics of the B.1.1.7 strains of SARS-CoV-2 in England. The model characterizes and establishes the underlying theoretical mechanism that shapes the logistic growth of mutation in population.

9.
Infectious Disease Modelling ; 2022.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165356

Résumé

Analytic compartmental models are currently used in mathematical epidemiology to forecast the COVID-19 pandemic evolution and explore the impact of mitigation strategies. In general, such models treat the population as a single entity, losing the social, cultural and economical specificities. We present a network model that uses socio-demographic datasets with the highest available granularity to predict the spread of COVID-19 in the province of Barcelona. The model is flexible enough to incorporate the effect of containment policies, such as lockdowns or the use of protective masks, and can be easily adapted to future epidemics. We follow a stochastic approach that combines a compartmental model with detailed individual microdata from the population census, including social determinants and age-dependent strata, and time-dependent mobility information. We show that our model reproduces the dynamical features of the disease across two waves and demonstrates its capability to become a powerful tool for simulating epidemic events.

10.
IDCases ; : e01664, 2023.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165354

Résumé

During the COVID-19 pandemic, cases of acute sinusitis due to COVID-19 and even co-infections have been reported [1]. We want to discuss a case in Colombia where a patient with detected type 2 diabetes presented sinusitis and COVID-19.A 51-year-old man from Sincelejo, Sucre, consulted on May 23, 2020, with one day presenting general malaise and fever (38°C), lumbar pain, frequent urination, polydipsia and hyperglycemia (366 mg/dl). He denies cough, travel during the last two weeksan Physical examination revealed a blood pressure of 170/110 mmHg, heart rate of 115 beats/minute, respiratory rate of 16 breaths/minute, and temperature of 36.6°C. Neither lymphadenopathies nor cardiopulmonary disturbances were noted. A working diagnosis of febrile syndrome, ketoacidosis, and recent-onset type 2 diabetes, with uncontrolled hypertension, was contemplated at admission RT-PCR for SARS-CoV-2 was positive. A head CT Scan revealed left maxillary sinusitis with mucosal thickening of the maxillary Despite the sizeable SARS-CoV-2 pandemic, the number of reports of sinusitis in association with COVID-19 has been limited [2], [3]. Sinusitis is more often diagnosed among immunocompromised patients, including diabetes of our patient. COVID-19, as a multisystemic condition., It may affect different anatomical areas, including the paranasal sinuses and the upper and lower respiratory mucosa. Although it is uncertain whether SARS-CoV-2 was the sole cause of the sinusitis in our patient or just a contributing factor, other reports suggest a significant involvement of the virus in the development of this condition, in addition to its role in worsening the clinical course of patients with chronic rhinosinusitis

11.
IATSS Research ; 2022.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165353

Résumé

In this study, we develop a system to provide information on the sterilization of baggage carts and arriving passenger baggage to airport (Hereafter referred as arrival baggage) by using ultraviolet (UV) sterilization and information communication technology as border quarantine measures at airports. This system sterilizes arrival baggage and baggage carts by UV irradiation, and allows passengers to easily view the sterilization information recognized by radio frequency indentation technology. This is to provide safety and security not only to passengers, but also to staff, who may come into direct contact with the arrival baggage, of airport, airline, customs, and so on. In addition, the passengers can be provided with baggage tracking information, such as the current location and estimated delivering time of the baggage. This makes it possible to keep social distancing at baggage claims as an infection prevention. Furthermore, we verify the feasibility of the developed system and identify the issues to be addressed for its practical application through a demonstration of proof of concept at Central Japan International Airport.

12.
Heart & Lung ; 58:204-209, 2023.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165350

Résumé

Background Extracorporeal membrane oxygenator (ECMO) is one of the life-saving modalities for the treatment of multiple organs dysfunction, particularly the heart and the lungs. Objective To evaluate the benefit of ECMO for the treatment of SAR-COV-2 infection and its outcomes, complications, and mortality rate. Methods A comprehensive search for articles was performed using MEDLINE and SCOPUS from December 2019 to December 2020. Two independent reviewers selected eligible studies, extracted the data, assessed the quality of the studies, reviewed the full study protocols, and reported the findings according to the PRISMA protocol. The meta-analyses were performed using the Comprehensive Meta-Analysis software version 2.0. Results Pooled data from 57 studies was analyzed. There were 7,035 patients with SAR-COV-2 infection with event rate of ECMO treatment was 58.10% (95%CI: 43.70–71.20). The mortality rate was 16.66% (95%CI: 11.49–23.53). The mean mortality rate of ECMO supported patients was 35.60% (95%CI: 30.60 to 41.00). Thirty-one percent (95%CI: 24.50–38.40) of the patients had venous thromboembolic events, 30.90% (95%CI: 17.90–47.80) of the patients had ECMO circuit thrombosis, and 24.50% (95%CI: 12.50–42.40) of the patients had bleeding. In the subgroup analysis, the mortality rate was higher among patients who were treated with ECMO, the pooled odds ratio was 4.47 (95%CI: 2.39–8.35, p < 0.001), and was significantly higher in Asia with an odds ratio of 7.88 (95%CI: 2.40–25.85, p = 0.001). Conclusion Mortality rate among patients who received ECMO therapy was high. A system of care, including patient selection, resource management and referral system, can impact the outcomes of ECMO therapy.

14.
Health Policy and Technology ; : 100724, 2023.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165346

Résumé

Objectives Telehealth use has increased steadily since the mid-2000's when technology shifted from voice-only systems to live video-conferencing and other technologies supported by broadband Internet. More recently, the COVID-19 pandemic has resulted in exponential growth in telehealth use. As telehealth systems become increasingly complex and gain widespread adoption, this study explores how users' digital competences affect telehealth use. Methods We apply a series of multivariate logit models to a representative sample of California adults with Internet access surveyed in early 2021. We estimate the impact of self-reported digital competence–using items from the digital skills assessment scale–on a participant's likelihood of telehealth use during the COVID-19 pandemic as well as the likelihood to continue using telehealth beyond the pandemic. Results The findings show that a one-unit increase in digital competence is associated with 72.8% greater odds of telehealth use (p <.001) and 71.6% greater odds of willingness to continue using telehealth services beyond the pandemic (p<.01). We also found that greater social and economic capital generally were associated with increased odds of telehealth use. Conclusions Improving access to telehealth will require solutions addressing both the first level (i.e., access to broadband and devices) and the second level (i.e., skills and attitudes towards the internet) of digital inequality. Policies and programs seeking to expand internet access must be coupled with investments in digital upskilling and training. Those with limited digital competence will face continued barriers in navigating telehealth systems, further exacerbating disparities in healthcare access and outcomes. Public Interest Summary Digital competence is the ability and confidence to apply one's knowledge and skills to perform tasks through information technology, including computing devices and the internet. This study explores the relationship between digital competence and telehealth use among those with broadband internet access at home. Telehealth has become increasingly common due to its cost-effectiveness and accessibility for patients unable to visit healthcare facilities. Though the COVID-19 pandemic has contributed to a significant increase in telehealth use, it is expected that telehealth services will continue to expand after the pandemic subsides. In our analysis of California adults, a year into the pandemic, we find those with greater digital competence are more likely to have used telehealth during the pandemic. Further, among telehealth users, those with greater digital competence are more likely to continue using telehealth beyond the pandemic. Addressing disparities in healthcare access and outcomes will require improving potential users' digital competence.

15.
Health Policy and Technology ; : 100717, 2022.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165344

Résumé

Objectives This study aimed to determine the opportunities of and barriers to communicable diseases surveillance system (CDSS) during the COVID-19 pandemic and the extent to which the disease integrated into the CDSS in the Kurdistan region of Iraq. Study design A descriptive qualitative approach was applied. Methods We conducted seven semi-structured interviews and seven interviewee in a focus group discussion (FGD) with purposefully identified Key Informants (KI) from June to December 2020. All interviews were digitally recorded and transcribed verbatim. We adopted a mixed deductive-inductive approach for thematic data analysis, facilitated by using MAXQDA20 software for data management. Results Although the CDSS was considered appropriate and flexible, the COVID-19 was interpreted not to be integrated into the system due to political influence. The main concerns regarding core and support activities were the lack of epidemic preparedness, timeliness, and partial cessation of training and supervision during the pandemic. The existence of reasonable surveillance infrastructure, i.e., trained staff, was identified as an opportunity for improvement. The main challenges include staff deficiency, absence of motivation and financial support for present staff, scarce logistics, managerial and administrative issues, and lack of cooperation, particularly among stakeholders and surveillance staff. Conclusion Our findings revealed that the CDSS in the Kurdistan region requires substantial enhancement in epidemic preparedness, strengthening human resources, and logistics. the system can be developed by fostering meaningful intersectoral collaboration. We advocate that the health authorities and policy-makers prioritise the surveillance and effective management of communicable diseases.

16.
Heart, Lung and Circulation ; 2023.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165343

Résumé

Objectives COVID-19 and the lockdowns have affected health care provision internationally, including medical procedures and methods of consultation. We aimed to assess the impact of COVID-19 at two Australian hospitals, focussing on cardiovascular hospital admissions, the use of community resources and cardiovascular risk factor control through a mixed methods approach. Methods Admissions data from the quaternary referral hospital were analysed, and 299 patients were interviewed from July 2020 to December 2021. With the admissions data, the number, complexity and mortality of cardiology hospital admissions, prior to the first COVID-19 lockdown (T0=February 2018–July 2019) were compared to after the introduction of COVID-19 lockdowns (T1=February 2020–July 2021). During interviews, we asked patients about hospital and community health resource use, and their control of cardiovascular risk factors from the first lockdown. Results Admission data showed a reduction in hospital presentations (T0=138,099 vs T1=128,030) and cardiology admissions after the lockdown period began (T0=4,951 vs T1=4,390). After the COVID-19-related lockdowns began, there was an increased complexity of cardiology admissions (T0=18.7%, 95% CI 17.7%–19.9% vs T1=20.3%, 95% CI 19.1%–21.5%, chi-square test: 4,158.658, p<0.001) and in-hospital mortality (T0=2.3% of total cardiology admissions 95% CI 1.9%–2.8% vs T1=2.8%, 95% CI 2.3%–3.3%, chi-square test: 4,060.217, p<0.001). In addition, 27% of patients delayed presentation due to fears of COVID-19 while several patients reported reducing their general practitioner or pathology/imaging appointments (27% and 11% respectively). Overall, 19% reported more difficulty accessing medical care during the lockdown periods. Patients described changes in their cardiovascular risk factors, including 25% reporting reductions in physical activity. Conclusion We found a decrease in hospital presentations but with increased complexity after the introduction of COVID-19 lockdowns. Patients reported being fearful about presenting to hospital and experiencing difficulty in accessing community health services.

17.
Heliyon ; : e12809, 2023.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165342

Résumé

During the COVID-19 pandemic, the news of clinical trials for vaccines and mass vaccinations have brought renewed optimism for stabilizing the economy and financial markets. However, the mental stress of investors or doubt about the effectiveness of government policies to cope with economic disruptions has caused stock market volatility. We investigate the significance of the vaccination rate in alleviating the global stock market volatility which is measured by the GJR–GARCH model. We discover that a higher vaccine initiation rate has a positive effect on global stock markets, especially in developed countries and areas with higher rates than their average. Our findings remain reliable even when using different projected volatility models and other estimates of the main independent variables. Mass immunization also implies that governments will not have to take extreme measures to handle the pandemic, which alleviates investor worries about compliance and the prolonged effects of COVID-19. Our research indicates that global stock markets are providing insight into the economic value of the development of COVID-19 vaccines, even before public vaccinations start.

18.
Heliyon ; 9(1):e12768, 2023.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165339

Résumé

Emergency remote teaching in the immediate wake of the COVID-19 pandemic has created a challenging situation for both students and teachers. The purpose of this research is to identify the perceptions and challenges that university students faced during online classes in a women only university in Saudi Arabia. Data was collected by circulating Google forms among students from different colleges, and a total of 542 students submitted their responses. Apart from gathering the personal information of participants, the survey also collected information on aspects such as educational, financial, internet connectivity and volunteering/donations. Chi-squared test was used to determine whether there was a significant difference in opinion between different groups of students on various questions. Stress was identified as the most prevalent issue among students. Students were found to be stressed regardless of their college of study or age. In comparison to others, younger students and students from financially disadvantaged families faced more difficulties. In terms of remote practical class satisfaction, health/medical stream students were the most dissatisfied group. They also faced more difficulties than students from other colleges. The analysis results show that problems such as stress, poor internet connectivity, the need for technical support, a lack of proper interaction with faculty, a lack of proper academic advising, a lack of proper study space at home etc. must be addressed in order to improve the effectiveness of online classes. This paper also includes recommendations for resolving the various issues that students face.

19.
Heliyon ; 9(1):e12767, 2023.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165338

Résumé

Many people die on the streets every year. Year after year this number is decreasing, but there are still a lot of them. Although COVID-19 has reduced the number of traffic accidents, this figure is still very high. For this reason, in order to identify the federal states with the highest number of traffic accidents and to do everything possible to minimize the analytical value and improve road safety, we will develop accident forecasts for the next few years. Need to know. The author's aim is to predict the number of road accidents by state in Poland, but this has not been done for many years. For this purpose, monthly data from police statistics on the number of traffic accidents by state in Poland were analyzed. Based on this data, a forecast of the number of traffic accidents in the next years from 2022 to 2024 was created in Statistica. A selected neural network model was used to predict the number of traffic accidents. The results show that a reduction in the number of traffic accidents on Polish roads can still be expected, but the prevalent COVID-19 confounds the results obtained. The choice of number of samples (training, testing, and validation) affects the results obtained.

20.
Heliyon ; 9(1):e12753, 2023.
Article Dans Anglais | ScienceDirect | ID: covidwho-2165336

Résumé

Background Misconceptions about adverse side effects are thought to influence public acceptance of the Coronavirus disease 2019 (COVID-19) vaccines negatively. To address such perceived disadvantages of vaccines, a novel machine learning (ML) approach was designed to generate personalized predictions of the most common adverse side effects following injection of six different COVID-19 vaccines based on personal and health-related characteristics. Methods Prospective data of adverse side effects following COVID-19 vaccination in 19943 participants from Iran and Switzerland was utilized. Six vaccines were studied: The AZD1222, Sputnik V, BBIBP-CorV, COVAXIN, BNT162b2, and the mRNA-1273 vaccine. The eight side effects were considered as the model output: fever, fatigue, headache, nausea, chills, joint pain, muscle pain, and injection site reactions. The total input parameters for the first and second dose predictions were 46 and 54 features, respectively, including age, gender, lifestyle variables, and medical history. The performances of multiple ML models were compared using Area Under the Receiver Operating Characteristic Curve (ROC-AUC). Results The total number of people receiving the first dose of the AZD1222, Sputnik V, BBIBP-CorV, COVAXIN, BNT162b2, and mRNA-1273 were 6022, 7290, 5279, 802, 277, and 273, respectively. For the second dose, the numbers were 2851, 5587, 3841, 599, 242 and 228. The Logistic Regression model for predicting different side effects of the first dose achieved ROC-AUCs of 0.620–0.686, 0.685–0.716, 0.632–0.727, 0.527–0.598, 0.548–0.655, 0.545–0.712 for the AZD1222, Sputnik V, BBIBP-CorV, COVAXIN, BNT162b2 and mRNA-1273 vaccines, respectively. The second dose models yielded ROC-AUCs of 0.777–0.867, 0.795–0.848, 0.857–0.906, 0.788–0.875, 0.683–0.850, and 0.486–0.680, respectively. Conclusions Using a large cohort of recipients vaccinated with COVID-19 vaccines, a novel and personalized strategy was established to predict the occurrence of the most common adverse side effects with high accuracy. This technique can serve as a tool to inform COVID-19 vaccine selection and generate personalized factsheets to curb concerns about adverse side effects.

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