Materiały źródłowe

• #1 Interim Estimates of 2024–2025 COVID-19 Vaccine Effectiveness Among Adults Aged ≥18 Years — VISION and IVY Networks, September 2024–January 2025 | MMWR

  https://www.cdc.gov/mmwr/volumes/74/wr/mm7406a1.htm

  Vaccine effectiveness (VE) of 2024-2025 COVID-19 vaccine was 33% against COVID-19-associated emergency department (ED) or urgent care (UC) visits among adults aged 18 years and 45%-46% against hospitalizations among immunocompetent adults aged 65 years, compared with not receiving a 2024-2025 vaccine dose. VE against hospitalizations in immunocompromised adults aged 65 years was 40%. […] These findings indicate that 2024-2025 COVID-19 vaccination provides additional protection against COVID-19-associated ED/UC encounters and hospitalization, versus no 2024-2025 vaccination and support CDC and ACIP recommendations that all persons aged 6 months receive 2024-2025 COVID-19 vaccination. […] These findings demonstrate that vaccination with a 2024-2025 COVID-19 vaccine dose provides additional protection against COVID-19-associated ED/UC encounters and hospitalizations compared with not receiving a 2024-2025 dose and support current CDC and ACIP recommendations that all persons aged 6 months receive a 2024-2025 COVID-19 vaccine dose.

• #2 Efficacy of first dose of covid-19 vaccine versus no vaccination on symptoms of patients with long covid: target trial emulation based on ComPaRe e-cohort

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9978748/

  To evaluate the effect of covid-19 vaccination on the severity of symptoms in patients with long covid. […] By 120 days, vaccination had reduced the number of long covid symptoms (mean 13.0 (standard deviation 9.4) in the vaccinated group v 14.8 (9.8) in the control group; mean difference 1.8, 95%confidence interval 3.0 to 0.5) and doubled the rate of patients in remission (16.6% v 7.5%, hazard ratio 1.93, 95%confidence interval 1.18 to 3.14). […] In this study, covid-19 vaccination reduced the severity of symptoms and the effect of long covid on patients’ social, professional, and family lives at 120 days in those with persistent symptoms of infection. […] The results suggest that vaccination should be encouraged in all patients who have already been infected with the SARS CoV-2 virus.

• #2 Interim Estimates of 2024–2025 COVID-19 Vaccine Effectiveness Among Adults Aged ≥18 Years — VISION and IVY Networks, September 2024–January 2025 | MMWR

  https://www.cdc.gov/mmwr/volumes/74/wr/mm7406a1.htm

  During September 2024-January 2025, 2024-2025 COVID-19 vaccination provided additional protection against COVID-19-associated ED/UC encounters and hospitalizations among adults with and without immunocompromising conditions, compared with not receiving a 2024-2025 COVID-19 vaccine dose. […] In this analysis, receipt of a 2024-2025 COVID-19 vaccine dose provided additional protection against COVID-19-associated ED/UC visits and hospitalization among adults with and without immunocompromise.

• #3 Grading of Recommendations, Assessment, Development, and Evaluation (GRADE): Pfizer-BioNTech COVID-19 Vaccine | ACIP | CDC

  https://www.cdc.gov/acip/grade/covid-19-pfizer-biontech-vaccine.html

  The policy question was, „Should vaccination with Pfizer-BioNTech COVID-19 vaccine (2-doses, IM) be recommended for persons 16 years of age and older?” The potential benefits pre-specified by the ACIP COVID-19 Vaccines Work Group included prevention of symptomatic laboratory-confirmed COVID-19 (critical), hospitalization due to COVID-19 (critical), death due to COVID-19 (important) and asymptomatic SARS-CoV-2 infection, assessed using PCR (important). The two pre-specified harms were serious adverse events (SAEs) (including myocarditis and anaphylaxis) (critical) and reactogenicity (severe, grade 3) (important). […] In terms of benefits, the available data from RCTs demonstrated that, compared with placebo, vaccination was associated with a lower risk of symptomatic laboratory-confirmed COVID-19 (relative risk [RR] 0.09, 95% confidence interval [CI] 0.070.11; evidence type 1), hospitalization due to COVID-19 (RR 0.02; 95% CI 0.000.12; evidence type 2), and death due to COVID-19 (RR 0.17, 95% CI 0.021.39; evidence type 2). The certainty of estimates regarding hospitalization and death due to COVID-19 was reduced due to imprecision.

• #4 Grading of Recommendations, Assessment, Development, and Evaluation (GRADE): Pfizer-BioNTech COVID-19 Vaccine | ACIP | CDC

  https://www.cdc.gov/acip/grade/covid-19-pfizer-biontech-vaccine.html

  The pooled vaccine effectiveness estimates from observational studies were consistent with these findings. Compared with no vaccination, vaccination with Pfizer-BioNTech COVID-19 vaccine was associated with a decreased risk of symptomatic laboratory-confirmed COVID-19 (RR 0.07, 95% CI 0.050.13; evidence type 2), hospitalization (RR 0.06, 95% CI 0.030.12; evidence type 2), and death due to COVID-19 (RR 0.04, 95% CI 0.020.09; evidence type 2). The certainty of each of these estimates was increased for a strong association. Vaccination was also associated with a decreased risk of asymptomatic SARS-CoV-2 infection (RR 0.11, 95% CI 0.100.12; evidence type 4); the evidence certainty type was downgraded for inconsistency. […] In terms of harms, the available data from RCTs indicated that serious adverse events were balanced between the vaccine and placebo arms (RR 1.00; 95% CI 0.85 to 1.18, evidence type 2), and two serious adverse events were judged to be related to vaccination among more than 22,000 persons vaccinated. The certainty of this estimate was reduced due to imprecision. Reactogenicity grade 3 was associated with vaccination (RR 4.69; 95% CI 3.835.73, evidence type 1). About 11% of vaccine recipients versus 2% of placebo recipients reported grade 3 reactions. Two rare but serious adverse events, anaphylaxis and myocarditis, have been associated with vaccination in post-authorization safety surveillance.

• #5 Efficacy of first dose of covid-19 vaccine versus no vaccination on symptoms of patients with long covid: target trial emulation based on ComPaRe e-cohort

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9978748/

  Further research is needed to understand the mechanisms behind the effect of covid-19 vaccination on symptoms of patients who already have long covid. […] In patients with long covid, we found that the first covid-19 vaccine injection was associated with a reduction in the severity of the disease and on the effect on patients’ social, professional, and family lives at 120 days after baseline. […] Receiving a vaccine was also associated with a significant increase in the proportion of patients reporting an acceptable symptom state; for every 13 patients with long covid who are vaccinated, one will have a notable decrease in the diseases effect on their life. […] Showing the effectiveness of vaccination on symptoms of long covid might also help our understanding of the causes of the persistence of symptoms after SARS-CoV-2 infection. […] The finding that vaccines might reduce symptoms for patients who already have long covid implies that, for at least some patients, the disease could be related to the presence of a persistent viral reservoir, or of virus fragments capable of stimulating the immune system.

• #6 Post-COVID conditions following COVID-19 vaccination: a retrospective matched cohort study of patients with SARS-CoV-2 infection | Nature Communications

  https://www.nature.com/articles/s41467-024-48022-9

  COVID-19 vaccinations protect against severe illness and death, but associations with post-COVID conditions (PCC) are less clear. […] Compared to unvaccinated cases, vaccinated cases had a similar or lower risk of all PCC categories except mental health disorders (RR: 1.06, 95% CI: 1.021.10). […] Vaccination was associated with 10% lower risk of sensory (RR: 0.90, 0.860.95), circulatory (RR: 0.88, 0.830.94), blood and hematologic (RR: 0.79, 0.710.89), skin and subcutaneous (RR: 0.69, 0.660.72), and non-specific COVID-19 related disorders (RR: 0.53, 0.510.56). […] Pre-infection vaccination was associated with reduced risk of several PCC outcomes and hence may decrease the long-term consequences of COVID-19. […] During a median follow-up period of 151 days, a total of 158,404 new-onset PCC outcomes were identified.

• #7 Post-COVID conditions following COVID-19 vaccination: a retrospective matched cohort study of patients with SARS-CoV-2 infection | Nature Communications

  https://www.nature.com/articles/s41467-024-48022-9

  In adjusted analyses, the risk of PCC was significantly lower for vaccinated vs. unvaccinated patients for 9 of the 13 PCC outcomes studied. […] The largest reduction in relative risk (RR) associated with vaccination was observed for non-specific COVID-19 related outcomes (RR: 0.53, 95% CI: 0.510.56), followed by skin and subcutaneous tissue disorders (0.69, 0.66-0.72), blood and hematologic disorders (0.79, 0.710.89), circulatory disorders (0.88, 0.83-0.94), and sensory disorders (comprised of ear, nose, and throat disorders or visual disturbances: 0.90, 0.860.95). […] The current study demonstrated a reduction in the incidence of most PCC outcomes associated with COVID-19 vaccination among more than 300,000 patients with SARS-CoV-2 infection. […] Most associations between vaccination and PCC persisted across SARS-CoV-2 variant periods studied (i.e., pre-Omicron vs. Omicron) and appeared to be unaffected by receipt of a third vaccine dose or time between last vaccination and SARS-CoV-2 infection.

• #8 Vaccine effectiveness against SARS-CoV-2 infection or COVID-19 hospitalization with the Alpha, Delta, or Omicron SARS-CoV-2 variant: A nationwide Danish cohort study | PLOS Medicine

  https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003992

  The continued occurrence of more contagious Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants and waning immunity over time require ongoing reevaluation of the vaccine effectiveness (VE). This study aimed to estimate the effectiveness in 2 age groups (12 to 59 and 60 years or above) of 2 or 3 vaccine doses (BNT162b2 mRNA or mRNA-1273) by time since vaccination against SARS-CoV-2 infection and Coronavirus Disease 2019 (COVID-19) hospitalization in an Alpha-, Delta-, or Omicron-dominated period. […] In the oldest age group, VE against infection after 2 doses was 90.7% (95% CI: 88.2; 92.7) for the Alpha variant, 82.3% (95% CI: 75.5; 87.2) for the Delta variant, and 39.9% (95% CI: 26.3; 50.9) for the Omicron variant 14 to 30 days since vaccination. […] Two vaccine doses provided high protection against SARS-CoV-2 infection and COVID-19 hospitalization with the Alpha and Delta variants with protection, notably against infection, waning over time. Two vaccine doses provided only limited and short-lived protection against SARS-CoV-2 infection with Omicron. However, the protection against COVID-19 hospitalization following Omicron SARS-CoV-2 infection was higher. The third vaccine dose substantially increased the level and duration of protection against infection with the Omicron variant and provided a high level of sustained protection against COVID-19 hospitalization among the +60-year-olds.

• #9 Vaccine effectiveness against SARS-CoV-2 infection or COVID-19 hospitalization with the Alpha, Delta, or Omicron SARS-CoV-2 variant: A nationwide Danish cohort study | PLOS Medicine

  https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003992

  Our findings indicate that a third dose is necessary to maintain protection against infection for longer time and to ensure a high level of protection against COVID-19 hospitalization with the Omicron variant. Further research with longer follow-up time is needed to evaluate the VE after more than 120 days to inform authorities about whether to administer further vaccine doses.

• #10 Impact of Vaccination on the Course and Outcome of COVID-19 in Patients with Multimorbidity

  https://www.mdpi.com/2076-393X/11/11/1696

  Vaccination is the most cost-effective method of preventing COVID-19; however, data on its effect on patients with multimorbidity is limited. […] The aim was to evaluate the effect of vaccination against new coronavirus infection (NCI) in patients with multimorbid pathology in hospital treatment on the outcome of COVID-19 disease. […] When assessing the outcome of NCI in Model 1, the odds of death decreased by 3.228 times with two doses of Sputnik V in patients with multimorbidity. […] According to Model 2, for patients with multimorbidity, the chances of death decreased by 3.281 times with two doses of Sputnik V. […] The presence of two doses of Sputnik V increased the likelihood of recovery in patients with multimorbidity by more than three times. […] Our study aimed to establish the effect of vaccination against a new coronavirus infection in patients with multimorbidity in hospital treatment on the severity, duration, and outcome of COVID-19.

• #11 Impact of Vaccination on the Course and Outcome of COVID-19 in Patients with Multimorbidity

  https://www.mdpi.com/2076-393X/11/11/1696

  The chances of recovery in the vaccinated group were 1.975 times higher than in the unvaccinated group; the difference in odds was statistically significant. […] Therefore, vaccination against COVID-19 significantly reduces the adverse course of the disease. […] To do this, we developed a predictive model using binary logistic regression to determine the probability of recovery or death from COVID-19, depending on the number of vaccine doses administered previously while taking into account the age and gender of patients. […] When assessing the probability of a favorable outcome of COVID-19 depending on the presence of multimorbidity in patients, the chances of death increased by 4.604 times when there were two of the listed diseases and by 9.402 times when there were three. […] If the patient had a history of vaccination, the chances of death were reduced by 3.281 times with two doses of Sputnik V. […] Thus, we found that vaccine prevention of COVID-19 in the adult population using Russian-made vaccines for patients with multimorbidity has high epidemiological effectiveness.

• #12 Predictive biomarkers of COVID-19 prognosis identified in Bangladesh patients and validated in Japanese cohorts | Scientific Reports

  https://www.nature.com/articles/s41598-024-63184-8

  Our results indicate that the predictive biomarker panel is particularly useful in determining the risk of severe disease in COVID-19 patients in environments where public vaccination rates are high. […] This study, successfully identified a panel of 15 biomarkers that could predict, with particularly high accuracy, whether vaccinated COVID-19-infected individuals would subsequently have mild symptoms or worsen to medium or severe states that required inpatient treatment. […] Our predictive model could help to alleviate hospital congestion by quickly identifying patients that can recover safely as out-patients, while identifying mild cases that will subsequently worsen so that these patients can be hospitalized and receive preventative treatment.

• #13 Predictive biomarkers of COVID-19 prognosis identified in Bangladesh patients and validated in Japanese cohorts | Scientific Reports

  https://www.nature.com/articles/s41598-024-63184-8

  Despite high vaccination rates globally, countries are still grappling with new COVID infections, and patients diagnosed as mild dying at home during outpatient treatment. […] In an environment of widespread vaccination, these biomarkers could help medical practitioners determine if newly infected COVID-19 patients will improve and can be managed on an out-patient basis, or if they will deteriorate and require hospitalization. […] In this context where COVID patients can still experience severe disease progression despite the widespread use of vaccines, having a predictive model that can easily can distinguish patients at high risk of deterioration with just a blood sample would be highly beneficial. […] We believe that cytokines/chemokines/soluble receptors in the serum reflect a variety of conditions, including the patient’s underlying disease, and therefore can be used to determine the worsening status even in the absence of clinical background information.

• #14 Predicting mortality in SARS-COV-2 (COVID-19) positive patients in the inpatient setting using a Novel Deep Neural Network | medRxiv

  https://www.medrxiv.org/content/10.1101/2020.12.13.20247254.full

  Our aim was to develop a machine learning-based model to predict mortality using the deep learning Neo-V framework. We hypothesized this novel machine learning approach could be applied to COVID-19 patients to predict mortality successfully with high accuracy. […] We observed that several clinical and laboratory-based variables were statistically significant for both univariate and multivariate analyses while others were not. […] Machine learning results showed our DNN (Neo-V) model outperformed all conventional machine learning models with test set accuracy of 99.53%, sensitivity of 89.87%, and specificity of 95.63%; positive predictive value, 50.00%; negative predictive value, 91.05%; and area under the curve of the receiver-operator curve of 88.5. […] Our novel Deep-Neo-V model outperformed all other machine learning models. The model is easy to implement, user friendly and with high accuracy.

• #15 Predicting mortality in SARS-COV-2 (COVID-19) positive patients in the inpatient setting using a Novel Deep Neural Network | medRxiv

  https://www.medrxiv.org/content/10.1101/2020.12.13.20247254.full

  We hypothesize that machine learning, specifically deep-learning could be applied to COVID-19 patients with high accuracy. Using deep-learning to predict mortality in these patients may assist in clinical decision making, risk stratification and planning strategies in future for such pandemics at a larger scale. […] The Deep-Neo-V model has some limitations in terms of the available dataset, retrospective nature of the dataset and data from a single hospital, analyzed at admission and day-one data, other observational study confounders may exist and are unaccounted for. In the immediate future we actively look to validate these findings in an external dataset. In the longer term we will continue to develop an algorithm built on the Neo-V Framework approach that has the potential to be implemented, initially in future pandemics because of its ability to accurately predict outcomes using smaller datasets.

• #16 COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies | Virology Journal | Full Text

  https://virologyj.biomedcentral.com/articles/10.1186/s12985-022-01771-9

  The COVID-19 burden including deaths and new infections would decrease with increasing vaccination coverage rate. Priority vaccination to the elderly and adolescents would minimize both deaths and new infections. […] In this study, we aimed to estimate the impact of age-specific vaccination on reducing the prevalence of COVID-19 and explore the best vaccination strategy. […] Our results showed that if we increased the vaccination rate to 40% in each age group on June 1, 2021, the reduced total number of cumulative deaths in the 75-100, 65-74 and 45-64 age groups were 63, 23 and 10 as of June 1, 2021, respectively. And the reduced number of new infections in the 18-44, 0-17 and 45-64 age groups were 13,463, 12,807 and 11,073, respectively. […] Therefore, we obtained the fourth vaccine allocation scheme (0-17 age group accounted for 80% and 75-100 age group accounted for 20%) was the most optimal, the reduced cumulative numbers of deaths and new infections were 21 and 40,688 per increased 100,000 vaccinated individuals, respectively, which could ensure the greatest reduction in the cumulative number of deaths and new infections simultaneously in NYC.

• #17 COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies | Virology Journal | Full Text

  https://virologyj.biomedcentral.com/articles/10.1186/s12985-022-01771-9

  Since December 14, 2020, New York City (NYC) has started the first batch of COVID-19 vaccines. However, the shortage of vaccines is currently an inevitable problem. Therefore, optimizing the age-specific COVID-19 vaccination is an important issue that needs to be addressed as a priority. […] Combined with the reported COVID-19 data in NYC, this study aimed to construct a mathematical model with five age groups to estimate the impact of age-specific vaccination on reducing the prevalence of COVID-19. […] Compared with the current vaccination strategy in NYC, if we gradually increased the vaccination coverage rate for only one age group from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 75-100 age group would be reduced the most, about 72 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0-17 age group would be reduced the most, about 21,591 fewer new infections per increased 100,000 vaccinated individuals.

• #18 Development and Validation of the Outcome Expectancy Scale for COVID-19 Vaccination in the Adult General Population

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9866430/

  Promotion of COVID-19 vaccination requires understanding its determinants, an important one of which is outcome expectancy. […] Positive and negative outcome expectancies are important determinants of COVID-19 vaccination, as health economists have pointed out that decisions are largely dependent on weighing potential gains and losses of a particular behavior. […] The construct of outcome expectancy is multi-dimensional. Perceived efficacy and side effects represent key positive and negative expected outcomes of COVID-19 vaccination, respectively; such factors are among the most commonly reported cognitive factors of COVID-19 vaccination behavior and hesitancy. […] The development of the OES-COVID-19 may also facilitate theory development, as outcome expectancy is an important construct of a number of commonly used behavioral health theories, including the Health Action Process Approach (HAPA) model and the Social Cognitive Theory (SCT).

• #19 Development and Validation of the Outcome Expectancy Scale for COVID-19 Vaccination in the Adult General Population

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9866430/

  The validated scale shows satisfactory concurrent validity, as demonstrated by the significant associations between its four subscales and COVID-19 vaccination intention/behavior. […] Thus, the OES-COVID-19 developed in the present study has been carefully validated and is ready to use. It can potentially contribute to understanding and predicting COVID-19 vaccination behavior, vaccine hesitancy, and vaccine resistance. […] The first factor of Positive Contribution to Society factor explained the largest percentage of variance among the four identified factors. […] The findings have an important implication that COVID-19 vaccination, like influenza vaccination, can be seen as a prosocial behavior. […] The validated OES-COVID-19 is a reliable, valid, and potentially useful tool for advancing COVID-19 vaccination research.

• #20 Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier

  https://www.mdpi.com/2306-5729/6/11/112

  Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier […] This study focuses on the future prediction of the effectiveness of the COVID-19 vaccine effectiveness which has been presented as a light in the dark. […] This study intends to estimate what perception the masses will establish about the role of the COVID-19 vaccine in the future. […] The results prove that the SVM produces the best forecasting results and that artificial neural networks (ANNs) produce the worst prediction toward the individual aptitude to be vaccinated by the COVID-19 vaccine. […] Thus, the results show that the studied prediction technique is a promising and encouraging procedure for studying the future trends of the COVID-19 vaccine. […] This study aims to predict the perception of people toward the COVID-19 vaccine.

• #21 Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier

  https://www.mdpi.com/2306-5729/6/11/112

  The goal of this study is to predict the trend of the people towards the COVID-19 vaccinations, besides different myths and side effects of vaccination on health. […] The proposed system shows a better result on the random dataset with the voting classifier, as it produced 89.9% accuracy score. […] The results of this study are more promising and encouraging for the random dataset. […] While the overall results with the given dataset shows that there is a positive trend of people towards the vaccination, there are still people who are apprehensive towards the vaccination because of different myths and risks or any other health concerns.

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