The Effect of the COVID-19 Vaccine on Daily Cases and Deaths Based on Global Vaccine Data

Impact of vaccination status on clinical outcomes of hospitalized COVID-19 patients

INTRODUCTION

It is important to identify the relationship between the COVID-19 vaccination status and the prognosis of this disease in hospitalized patients to gain a more accurate picture of their status and the effect of vaccination, as well as take necessary measures to improve their medical care. Thus, the present study was conducted to investigate the relationship between the vaccination status of hospitalized COVID-19 patients and the disease severity index in terms of clinical, imaging, and laboratory criteria.

METHODS

This research is a descriptive-analytical cross-sectional study. the study population consisted of patients with a positive RT-PCR test for coronavirus, admitted to COVID-19 departments of teaching hospitals in Yazd, Iran, during two months in the sixth peak of COVID-19. The patients' data comprised demographic information (age, sex, and underlying disease), clinical information (length of hospital stay, length of ICU stay, and vaccination status), disease outcome (mortality and intubation), laboratory information (ESR, CRP, and NLR), and imaging information (lung involvement percentage), and finally, the relationship between patients' vaccination status and disease severity indices were analyzed with the chi-square test, independent t-test, and logistic regression analysis at a 95% confidence interval (CI).

FINDINGS

According to research findings, the duration of hospitalization was 5.25 ± 2.34 and 6.11 ± 3.88 days in groups of patients with complete and incomplete vaccination, respectively (P = 0.003). The lengths of ICU stay were 6 ± 4.63 and 5.23 ± 3.73 days in both groups of patients admitted to the ICU (P = 0.395). Furthermore, there were significant relationships between the ICU admission rates, endotracheal intubation, mortality rate, the lung involvement score in the chest CT scan, and the NLR with the vaccination status.Multivariate regression analysis indicated that DM, IHD, NLR, CT scan score and vaccination status were related to patients' in-hospital mortality.

CONCLUSION

Complete vaccination of COVID-19 led to a milder disease in terms of clinical, imaging, and laboratory criteria of patients and decreased the possibility of hospitalization in ICUs, intubation, and mortality in patients.

Significance of weather condition, human mobility, and vaccination on global COVID-19 transmission

The transmission growth rate of infectious diseases, particularly COVID-19, has forced governments to take immediate control decisions. Previous studies have shown that human mobility, weather condition, and vaccination are potential factors influencing virus transmission. This study investigates the contribution of weather conditions, namely temperature and precipitation, human mobility, and vaccination to coronavirus transmission. Three machine learning models: random forest (RF), XGBoost, and neural networks, are applied to predict the confirmed cases based on three aforementioned variables. All models' prediction are evaluated via spatial and temporal analysis. The spatial analysis observes the model performance over countries on certain times. The temporal analysis looks at the model prediction of each country during the specified period. The models' prediction results effectively indicate the transmission trend. The RF model performs best with a coefficient of determination of up to 89%. Meanwhile, all models confirm that vaccination is most significantly associated with COVID-19 cases.

COVID-19 transmission dynamics and the impact of vaccination: modelling, analysis and simulations

Despite the lifting of COVID-19 restrictions, the COVID-19 pandemic and its effects remain a global challenge including the sub-Saharan Africa (SSA) region. Knowledge of the COVID-19 dynamics and its potential trends amidst variations in COVID-19 vaccine coverage is therefore crucial for policy makers in the SSA region where vaccine uptake is generally lower than in high-income countries. Using a compartmental epidemiological model, this study aims to forecast the potential COVID-19 trends and determine how long a wave could be, taking into consideration the current vaccination rates. The model is calibrated using South African reported data for the first four waves of COVID-19, and the data for the fifth wave are used to test the validity of the model forecast. The model is qualitatively analysed by determining equilibria and their stability, calculating the basic reproduction number R0 and investigating the local and global sensitivity analysis with respect to R0. The impact of vaccination and control interventions are investigated via a series of numerical simulations. Based on the fitted data and simulations, we observed that massive vaccination would only be beneficial (deaths averting) if a highly effective vaccine is used, particularly in combination with non-pharmaceutical interventions. Furthermore, our forecasts demonstrate that increased vaccination coverage in SSA increases population immunity leading to low daily infection numbers in potential future waves. Our findings could be helpful in guiding policy makers and governments in designing vaccination strategies and the implementation of other COVID-19 mitigation strategies.

A Meta-Analysis on the Association between Peptic Ulcer Disease and COVID-19 Severity

The association between peptic ulcer disease and the severity of coronavirus disease 2019 (COVID-19) is inconclusive across individual studies. Thus, this study aimed to investigate whether there was a significant association between peptic ulcer disease and COVID-19 severity through a meta-analysis. The electronic databases (Web of Science, Wiley, Springer, EMBASE, Elsevier, Cochrane Library, Scopus and PubMed) were retrieved for all eligible studies. The Stata 11.2 software was used for all statistical analyses. The pooled odds ratio (OR) with a 95% confidence interval (CI) was calculated by a random-effects meta-analysis model. The heterogeneity was evaluated by the inconsistency index (I²) and Cochran's Q test. Egger's analysis and Begg's analysis were conducted to evaluate the publication bias. Meta-regression analysis and subgroup analysis were done to explore the potential source of heterogeneity. Totally, our findings based on confounding variables-adjusted data indicated that there was no significant association between peptic ulcer disease and the higher risk for COVID-19 severity (pooled OR = 1.17, 95% CI: 0.97-1.41) based on 15 eligible studies with 4,533,426 participants. When the subgroup analysis was performed by age (mean or median), there was a significant association between peptic ulcer disease and a higher risk for COVID-19 severity among studies with age ≥ 60 years old (pooled OR = 1.15, 95% CI: 1.01-1.32), but not among studies with age < 60 years old (pooled OR = 1.16, 95% CI: 0.89-1.50). Our meta-analysis showed that there was a significant association between peptic ulcer disease and a higher risk for COVID-19 severity among older patients but not among younger patients.

Barriers and Facilitators Affecting the Uptake of COVID-19 Vaccines: A Qualitative Perspective of Frontline Nurses in Namibia

Aim

Vaccinations remain one of the most effective measures to prevent and control the spread of COVID-19, while also reducing hospitalizations and deaths, yet many are unwilling to be vaccinated. This study explores the barriers and facilitators affecting the uptake of COVID-19 vaccines among frontline nurses.

Design

A qualitative, explorative, descriptive, and contextual research strategy was employed.

Methods

A sample of 15 nurses were selected via purposeful sampling to the point of data saturation. The participants were nurses at the COVID-19 vaccinations Centre in Rundu, Namibia. Data were collected using semistructured interviews and analyzed thematically.

Results

Three themes and 11 subthemes were identified, namely: (a) barriers, (b) facilitators, and (c) measures to increase the COVID-19 vaccine uptake. Barriers included living in deep rural areas, unavailability of vaccines, and misinformation, whereas scared of death, availability of COVID-19 vaccines, and family influence and peer pressure emerged as facilitators to the uptake of COVID-19 vaccines. Adoption of vaccination passport as a requirement to work premises and as an international travel requirement were the measures proposed to increase the COVID-19 vaccine uptake.

Conclusion

The study found several facilitators and barriers to COVID-19 vaccine uptake among frontline nurses. The identified barriers cover the individual, health system, and social factors hindering the COVID-19 vaccine uptake among frontline nurses. Whereas fear of COVID-19 deaths, family influence, and availability of vaccines were found to promote COVID-19 uptake. This study recommends targeted interventions to improve the uptake of COVID-19 vaccines.

Spatial and Temporal Analysis of COVID-19 Cases in West Java, Indonesia and Its Influencing Factors

Coronavirus Disease 2019 (COVID-19) spread quickly and reached epidemic levels worldwide. West Java is Indonesia's most populous province and has a high susceptibility to the transmission of the disease, resulting in a significant number of COVID-19 cases. Therefore, this research aimed to determine the influencing factors as well as the spatial and temporal distribution of COVID-19 in West Java. Data on COVID-19 cases in West Java obtained from PIKOBAR were used. Spatial distribution was described using a choropleth, while the influencing factors were evaluated with regression analysis. To determine whether COVID-19s policies and events affected its temporal distribution, the cases detected were graphed daily or biweekly with information on those two variables. Furthermore, the cumulative incidence was described in the linear regression analysis model as being significantly influenced by vaccinations and greatly elevated by population density. The biweekly chart had a random pattern with sharp decreases or spikes in cumulative incidence changes. Spatial and temporal analysis helps greatly in understanding distribution patterns and their influencing factors, specifically at the beginning of the pandemic. Plans and strategies for control and assessment programs may be supported by this study material.

Estimated global public health and economic impact of COVID-19 vaccines in the pre-omicron era using real-world empirical data

BACKGROUND

Limited data are available describing the global impact of COVID-19 vaccines. This study estimated the global public health and economic impact of COVID-19 vaccines before the emergence of the Omicron variant.

METHODS

A static model covering 215 countries/territories compared the direct effects of COVID-19 vaccination to no vaccination during 13 December 2020-30 September 2021. After adjusting for underreporting of cases and deaths, base case analyses estimated total cases and deaths averted, and direct outpatient and productivity costs saved through averted health outcomes. Sensitivity analyses applied alternative model assumptions.

RESULTS

COVID-19 vaccines prevented an estimated median (IQR) of 151.7 (133.7-226.1) million cases and 620.5 (411.1-698.1) thousand deaths globally through September 2021. In sensitivity analysis applying an alternative underreporting assumption, median deaths averted were 2.1 million. Estimated direct outpatient cost savings were $21.2 ($18.9-30.9) billion and indirect savings of avoided productivity loss were $135.1 ($121.1-206.4) billion, yielding a total cost savings of $155 billion globally through averted infections.

CONCLUSIONS

Using a conservative modeling approach that considered direct effects only, we estimated that COVID-19 vaccines have averted millions of infections and deaths, generating billions of cost savings worldwide, which underscore the continued importance of vaccination in public health response to COVID-19.

Contrasting Epidemiology and Population Genetics of COVID-19 Infections Defined by Multilocus Genotypes in SARS-CoV-2 Genomes Sampled Globally

Since its emergence in 2019, SARS-CoV-2 has spread and evolved globally, with newly emerged variants of concern (VOCs) accounting for more than 500 million COVID-19 cases and 6 million deaths. Continuous surveillance utilizing simple genetic tools is needed to measure the viral epidemiological diversity, risk of infection, and distribution among different demographics in different geographical regions. To help address this need, we developed a proof-of-concept multilocus genotyping tool and demonstrated its utility to monitor viral populations sampled in 2020 and 2021 across six continents. We sampled globally 22,164 SARS-CoV-2 genomes from GISAID (inclusion criteria: available clinical and demographic data). They comprised two study populations, “2020 genomes” (N = 5959) sampled from December 2019 to September 2020 and “2021 genomes” (N = 16,205) sampled from 15 January to 15 March 2021. All genomes were aligned to the SARS-CoV-2 reference genome and amino acid polymorphisms were called with quality filtering. Thereafter, 74 codons (loci) in 14 genes including orf1ab polygene (N = 9), orf3a, orf8, nucleocapsid (N), matrix (M), and spike (S) met the 0.01 minimum allele frequency criteria and were selected to construct multilocus genotypes (MLGs) for the genomes. At these loci, 137 mutant/variant amino acids (alleles) were detected with eight VOC-defining variant alleles, including N KR203&204, orf1ab (I265, F3606, and L4715), orf3a H57, orf8 S84, and S G614, being predominant globally with > 35% prevalence. Their persistence and selection were associated with peaks in the viral transmission and COVID-19 incidence between 2020 and 2021. Epidemiologically, older patients (≥20 years) compared to younger patients (<20 years) had a higher risk of being infected with these variants, but this association was dependent on the continent of origin. In the global population, the discriminant analysis of principal components (DAPC) showed contrasting patterns of genetic clustering with three (Africa, Asia, and North America) and two (North and South America) continental clusters being observed for the 2020 and 2021 global populations, respectively. Within each continent, the MLG repertoires (range 40−199) sampled in 2020 and 2021 were genetically differentiated, with ≤4 MLGs per repertoire accounting for the majority of genomes sampled. These data suggested that the majority of SARS-CoV-2 infections in 2020 and 2021 were caused by genetically distinct variants that likely adapted to local populations. Indeed, four GISAID clade-defined VOCs - GRY (Alpha), GH (Beta), GR (Gamma), and G/GK (Delta variant) were differentiated by their MLG signatures, demonstrating the versatility of the MLG tool for variant identification. Results from this proof-of-concept multilocus genotyping demonstrates its utility for SARS-CoV-2 genomic surveillance and for monitoring its spatiotemporal epidemiology and evolution, particularly in response to control interventions including COVID-19 vaccines and chemotherapies.

Parental perceptions and the 5C psychological antecedents of COVID-19 vaccination during the first month of omicron variant surge: A large-scale cross-sectional survey in Saudi Arabia

BACKGROUND

With the rapid surge of SARS-CoV-2 Omicron variant, we aimed to assess parents' perceptions of the COVID-19 vaccines and the psychological antecedents of vaccinations during the first month of the Omicron spread.

METHODS

A cross-sectional online survey in Saudi Arabia was conducted (December 20, 2021-January 7, 2022). Convenience sampling was used to invite participants through several social media platforms, including WhatsApp, Twitter, and email lists. We utilized the validated 5C Scale, which evaluates five psychological factors influencing vaccination intention and behavior: confidence, complacency, constraints, calculation, and collective responsibility.

RESULTS

Of the 1,340 respondents, 61.3% received two doses of the COVID-19 vaccine, while 35% received an additional booster dose. Fify four percentage were unwilling to vaccinate their children aged 5-11, and 57.2% were unwilling to give the additional booster vaccine to children aged 12-18. Respondents had higher scores on the construct of collective responsibility, followed by calculation, confidence, complacency, and finally constraints. Confidence in vaccines was associated with willingness to vaccinate children and positively correlated with collective responsibility (p < 0.010). Complacency about COVID-19 was associated with unwillingness to vaccinate older children (12-18 years) and with increased constraints and calculation scores (p < 0.010). While increasing constraints scores did not correlate with decreased willingness to vaccinate children (p = 0.140), they did correlate negatively with confidence and collective responsibility (p < 0.010).

CONCLUSIONS

The findings demonstrate the relationship between the five antecedents of vaccination, the importance of confidence in vaccines, and a sense of collective responsibility in parents' intention to vaccinate their children. Campaigns addressing constraints and collective responsibility could help influence the public's vaccination behavior.