Dataset Information

Vaccination Criteria Based on Factors Influencing COVID-19 Diffusion and Mortality.

ABSTRACT: SARS-CoV-2 is highly contagious, rapidly turned into a pandemic, and is causing a relevant number of critical to severe life-threatening COVID-19 patients. However, robust statistical studies of a large cohort of patients, potentially useful to implement a vaccination campaign, are rare. We analyzed public data of about 19,000 patients for the period 28 February to 15 May 2020 by several mathematical methods. Precisely, we describe the COVID-19 evolution of a number of variables that include age, gender, patient's care location, and comorbidities. It prompts consideration of special preventive and therapeutic measures for subjects more prone to developing life-threatening conditions while affording quantitative parameters for predicting the effects of an outburst of the pandemic on public health structures and facilities adopted in response. We propose a mathematical way to use these results as a powerful tool to face the pandemic and implement a mass vaccination campaign. This is done by means of priority criteria based on the influence of the considered variables on the probability of both death and infection.

SUBMITTER: Spassiani I

PROVIDER: S-EPMC7765372 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Vaccination Criteria Based on Factors Influencing COVID-19 Diffusion and Mortality.

Spassiani Ilaria I Gubian Lorenzo L Palù Giorgio G Sebastiani Giovanni G

Vaccines 20201215 4

SARS-CoV-2 is highly contagious, rapidly turned into a pandemic, and is causing a relevant number of critical to severe life-threatening COVID-19 patients. However, robust statistical studies of a large cohort of patients, potentially useful to implement a vaccination campaign, are rare. We analyzed public data of about 19,000 patients for the period 28 February to 15 May 2020 by several mathematical methods. Precisely, we describe the COVID-19 evolution of a number of variables that include age ...[more]

PMID: 33334007

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Project description:ObjectivesThis study aims to investigate the factors influencing parental willingness in COVID-19 vaccination for children in Japan in light of the introduction of pediatric vaccines.MethodsAn online survey was conducted in February 2022, coinciding with the imminent start of pediatric COVID-19 vaccinations in Japan. It assessed attitudes toward vaccine uptake and included questions about health-related attributes, psychological considerations, and sources of COVID-19 information. Data from 2,419 respondents who had children under the age of 12 were analyzed using multinomial logistic regression to identify factors associated with parental willingness towards COVID-19 vaccination for children. The outcomes were "agree" (in favor of vaccination), "not sure" (undecided), with "disagree" (against vaccination) as the reference category.ResultsAmong participants supportive of vaccination ("agree" compared to the "disagree" reference), salient determinants included: gender (Men in reference to women: odds ratio [OR] 1.54; 95 % confidence interval [CI] 1.11-2.15), highest educational level (Junior College/Vocational in reference to under high school: OR 0.61; 95 % CI 0.40-0.93, Bachelor's /Master's/Doctoral degree in reference to under high school: OR 0.59; 95 % CI 0.42-0.84), perception of benefits of COVID-19 vaccination (Significant in reference to Insignificant: OR 2.04; 95 % CI 1.26-3.28), perception of risks of COVID-19 vaccination (Significant in reference to Insignificant: OR 0.28; 95 % CI 0.19-0.42, Neutral in reference to Insignificant: OR 0.48; 95 % CI 0.33-0.71), the number of referenced information sources utilized for COVID-19 was associated with attitudes towards children's vaccination (OR 1.02; 95 % CI 1.00-1.04).ConclusionThe study highlights the multifaceted factors influencing parents' COVID-19 vaccination attitudes for their children, encompassing socioeconomic, health, psychological, and informational aspects. Factors like cautious information gathering, vaccine concerns and diverse referenced information sources impact willingness. To facilitate informed decision-making, essential measures include government risk communication, widespread vaccine information dissemination, and enhancing parents' health information accessibility and evaluation skills are important.

Project description:BackgroundVaccination is an important preventive measure against the coronavirus disease 19 (COVID-19) pandemic. We aimed to examine the willingness to vaccination and influencing factors among college students in China.MethodsFrom March 18 to April 26, 2021, we conducted a cross-sectional online survey among college students from 30 universities in Wuhan, Hubei Province, China. The survey was composed of the sociodemographic information, psychological status, experience during pandemic, the willingness of vaccination and related information. Students' attitudes towards vaccination were classified as 'vaccine acceptance', 'vaccine hesitancy', and 'vaccine resistance'. Multinomial logistic regression analyses were performed to identify the influencing factors associated with vaccine hesitancy and resistance.ResultsAmong 23,143 students who completed the survey, a total of 22,660 participants were included in the final analysis with an effective rate of 97.9% after excluding invalid questionnaires. A total of 60.6% of participants would be willing to receive COVID-19 vaccine, 33.4% were hesitant to vaccination, and 6.0% were resistant to vaccination. Social media platforms and government agencies were the main sources of information vaccination. Worry about the efficacy and adverse effects of vaccine were the top two common reason of vaccine hesitancy and resistance. Multiple multinomial logistic regression analysis identified that participants who worried about the adverse effects of vaccination were more likely to be vaccine hesitancy (aOR = 2.44, 95% CI = 2.30, 2.58) and resistance (aOR = 2.71, 95% CI = 2.40, 3.05).ConclusionMore than half of college students are willing to receive the COVID-19 vaccine, whereas nearly one-third college students are still hesitant or resistant. It is crucial to provide sufficient and scientific information on the efficacy and safety of vaccine through social media and government agencies platforms to promote vaccine progress against COVID-19 and control the pandemic in China.

Project description:The ongoing COVID-19 contagious disease caused by SARS-CoV-2 has disrupted global public health, businesses, and economies due to widespread infection, with 676.41 million confirmed cases and 6.77 million deaths in 231 countries as of February 07, 2023. To control the rapid spread of SARS-CoV-2, it is crucial to determine the potential determinants such as meteorological factors and their roles. This study examines how COVID-19 cases and deaths changed over time while assessing meteorological characteristics that could impact these disparities from the onset of the pandemic. We used data spanning two years across all eight administrative divisions, this is the first of its kind--showing a connection between meteorological conditions, vaccination, and COVID-19 incidences in Bangladesh. We further employed several techniques including Simple Exponential Smoothing (SES), Auto-Regressive Integrated Moving Average (ARIMA), Auto-Regressive Integrated Moving Average with explanatory variables (ARIMAX), and Automatic forecasting time-series model (Prophet). We further analyzed the effects of COVID-19 vaccination on daily cases and deaths. Data on COVID-19 cases collected include eight administrative divisions of Bangladesh spanning March 8, 2020, to January 31, 2023, from available online servers. The meteorological data include rainfall (mm), relative humidity (%), average temperature (°C), surface pressure (kPa), dew point (°C), and maximum wind speed (m/s). The observed wind speed and surface pressure show a significant negative impact on COVID-19 cases (-0.89, 95% confidence interval (CI): 1.62 to -0.21) and (-1.31, 95%CI: 2.32 to -0.29), respectively. Similarly, the observed wind speed and surface pressure show a significant negative impact on COVID-19 deaths (-0.87, 95% CI: 1.54 to -0.21) and (-3.11, 95%CI: 4.44 to -1.25), respectively. The impact of meteorological factors is almost similar when vaccination information is included in the model. However, the impact of vaccination in both cases and deaths model is significantly negative (for cases: 1.19, 95%CI: 2.35 to -0.38 and for deaths: 1.55, 95%CI: 2.88 to -0.43). Accordingly, vaccination effectively reduces the number of new COVID-19 cases and fatalities in Bangladesh. Thus, these results could assist future researchers and policymakers in the assessment of pandemics, by making thorough efforts that account for COVID-19 vaccinations and meteorological conditions.

Dataset Information

Vaccination Criteria Based on Factors Influencing COVID-19 Diffusion and Mortality.

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Vaccination Criteria Based on Factors Influencing COVID-19 Diffusion and Mortality.

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