A Bayesian network analysis quantifying risks versus benefits of the Pfizer COVID-19 vaccine in Australia

Using health literacy principles to improve understanding of evolving evidence in health emergencies: Optimisation and evaluation of a COVID-19 vaccination risk-benefit calculator

BACKGROUND

Risk communication tools based on epidemiological models can help inform decision-making, but must be responsive to health literacy needs to be effective. To facilitate informed choice about risks and benefits of COVID-19 vaccination, an epidemiological model called the COVID-19 Risk Calculator (CoRiCal) tool was developed by a multi-disciplinary team.

AIM

This paper demonstrates how to use health literacy principles to improve consumer understanding of COVID-19 and vaccine effects, using a range of methods that could be applied to any health emergency.

METHODS

Stage 1: Health literacy optimisation and user testing to reduce improve understandability (n = 19). Stage 2: Experiments to explore the effect of risk communication formats on perceived understanding including probability, graphs, evaluative labels and comparison risks (n = 207). Stage 3: Randomised controlled trial (n = 2005) with 4 arms: 1) standard government information; 2) standard CoRiCal output based on bar graphs; 3) animation explaining bar graphs in "x per million" format; 4) animation explaining bar graphs in "1 in x chance" format. The primary outcome was knowledge about COVID-19 risk.

RESULTS

Stage 1 reduced the complexity of the text and graphs. Stage 2 showed that different risk communication formats change perceived understanding, with a preference for evaluative labels across 2 experiments and some indication people with lower health literacy had a greater preference for bar graphs. Stage 3 showed both animations increased knowledge compared to standard government information. There was no difference between the probability formats, or by health literacy level.

DISCUSSION

The results showed that simple explanations of complex epidemiological models improve knowledge about COVID-19 and vaccination. This demonstrates how health literacy design principles and short animations can be used to support informed decision making about health emergencies.

Effectiveness of the BNT162b2 vaccine in preventing morbidity and mortality associated with COVID-19 in children aged 5 to 11 years: A systematic review and meta-analysis

A rapid systematic review, based on Cochrane rapid review methodology was conducted to assess the effectiveness of two 10μg doses of BNT162b2 vaccine in preventing morbidity and mortality associated with COVID-19 in children aged 5 to 11 years. We searched the Cochrane Library COVID-19 study register, the COVID-NMA living review database and the McMaster University Living Evidence Synthesis for pre-appraised trials and observational studies up to 7 December 2022. Records were screened independently in duplicate. Where appraisal was not available, these were done in duplicate. Meta-analysis was conducted using RevMan 5.3 presenting risk ratios/odds ratios/inverse vaccine efficacy with 95% confidence intervals (CI). GRADE for assessing the overall certainty of the evidence was done in Gradepro. We screened 403 records and assessed 52 full-text articles for eligibility. One randomised controlled trial (RCT) and 24 observational studies were included. The RCT reported that BNT162b2 was likely safe and 91% efficacious, RR 0.09 (95% CI 0.03 to 0.32) against incident COVID-19 infection (moderate certainty evidence). In absolute terms, this is 19 fewer cases per 1,000 vaccines delivered (ranging from 15 to 21 fewer cases). Observational studies reported vaccine effectiveness (VE) against incident COVID-19 infection of 65% (OR 0.35, 95% CI 0.26 to 0.47) and 76% against hospitalisation (OR 0.24, 95% CI 0.13 to 0.42) (moderate certainty evidence). The absolute effect is 167 fewer cases per 1,000 vaccines given (ranging from 130 fewer to 196 fewer cases) and 4 fewer hospitalisations per 10,000 children (from 3 fewer to 5 fewer hospitalisations). Adverse events following vaccination with BNT162b2 were mild or moderate and transient. The evidence demonstrated a reduction in incident COVID-19 cases and small absolute reduction in hospitalisation if a two-dose BNT162b2 vaccine regimen is offered to children aged 5 to 11 years, compared to placebo. PROSPERO registration: CRD42021286710.

Predictive factors of ergonomic behaviors based on social cognitive theory among women workers on assembly lines: application of Bayesian networks

BACKGROUND

This study focuses on identifying the key factors associated with ergonomic behaviors (ERBE) among women workers on assembly lines (WwAL) to prevent musculoskeletal disorders (MSDs) caused by repetitive motions and unfavorable body postures. To achieve this objective, this study employed Bayesian networks (BN) analysis based on social cognitive theory (SCT).

METHODS

A cross-sectional study was conducted to examine the predictive factors of ERBE among 250 WwAL from six different industries located in Neyshabur, a city in northeastern Iran. The study used a two-stage cluster sampling method for participant selection and self-report questionnaires to collect data on demographic characteristics, variables associated with SCT, ERBE, and the standard Nordic questionnaire. The collected data were analyzed using Netica and SPSS version 21, which involved statistical analyses such as independent t-tests, Pearson correlation, and ANOVA tests at a significance level of p < 0.05. BN analysis was conducted to identify the important factors that impact ERBE.

RESULTS

The majority of individuals reported experiencing chronic pain in their back, neck, and shoulder areas. Engaging in physical activity, consuming dairy products, and attaining a higher level of education were found to be significantly associated with the adoption of ERBE p < 0.05. Among the various SCT constructs, observational learning, intention, and social support demonstrated the highest levels of sensitivity towards ERBE, with scores of 4.08, 3.82, and 3.57, respectively. However, it is worth noting that all SCT constructs exhibited a certain degree of sensitivity towards ERBE.

CONCLUSIONS

The research findings demonstrate that all constructs within SCT are effective in identifying factors associated with ERBE among WwAL. The study also highlights the importance of considering education levels and variables related to healthy lifestyles when promoting ERBE in this specific population.

A decision support tool for risk-benefit analysis of Japanese encephalitis vaccine in travellers

BACKGROUND

During pre-travel consultations, clinicians and travellers face the challenge of weighing the risks verus benefits of Japanese encephalitis (JE) vaccination due to the high cost of the vaccine, low incidence in travellers (~1 in 1 million), but potentially severe consequences (~30% case-fatality rate). Personalised JE risk assessment based on the travellers' demographics and travel itinerary is challenging using standard risk matrices. We developed an interactive digital tool to estimate risks of JE infection and severe health outcomes under different scenarios to facilitate shared decision-making between clinicians and travellers.

METHODS

A Bayesian network (conditional probability) model risk-benefit analysis of JE vaccine in travellers was developed. The model considers travellers' characteristics (age, sex, co-morbidities), itinerary (destination, departure date, duration, setting of planned activities) and vaccination status to estimate the risks of JE infection, the development of symptomatic disease (meningitis, encephalitis), clinical outcomes (hospital admission, chronic neurological complications, death) and adverse events following immunization.

RESULTS

In low-risk travellers (e.g. to urban areas for <1 month), the risk of developing JE and dying is low (<1 per million) irrespective of the destination; thus, the potential impact of JE vaccination in reducing the risk of clinical outcomes is limited. In high-risk travellers (e.g. to rural areas in high JE incidence destinations for >2 months), the risk of developing symptomatic disease and mortality is estimated at 9.5 and 1.4 per million, respectively. JE vaccination in this group would significantly reduce the risk of symptomatic disease and mortality (by ~80%) to 1.9 and 0.3 per million, respectively.

CONCLUSION

The JE tool may assist decision-making by travellers and clinicians and could increase JE vaccine uptake. The tool will be updated as additional evidence becomes available. Future work needs to evaluate the usability of the tool. The interactive, scenario-based, personalised JE vaccine risk-benefit tool is freely available on www.VaxiCal.com.

Being Bayesian in the 2020s: opportunities and challenges in the practice of modern applied Bayesian statistics

Building on a strong foundation of philosophy, theory, methods and computation over the past three decades, Bayesian approaches are now an integral part of the toolkit for most statisticians and data scientists. Whether they are dedicated Bayesians or opportunistic users, applied professionals can now reap many of the benefits afforded by the Bayesian paradigm. In this paper, we touch on six modern opportunities and challenges in applied Bayesian statistics: intelligent data collection, new data sources, federated analysis, inference for implicit models, model transfer and purposeful software products. This article is part of the theme issue 'Bayesian inference: challenges, perspectives, and prospects'.

Primary and booster vaccination in reducing severe clinical outcomes associated with Omicron Naïve infection

BACKGROUND

Little is known about long-term effectiveness of COVID-19 vaccine in reducing severity and deaths associated with Omicron VOC not perturbed by prior infection and independent of oral anti-viral therapy and non-pharmaceutical (NPI).

METHODS

A retrospective observational cohort study was applied to Taiwan community during the unprecedent large-scale outbreaks of Omicron BA.2 between April and August, 2022. Primary vaccination since March, 2021 and booster vaccination since January, 2022 were offered on population level. Oral Anti-viral therapy was also offered as of mid-May 2022. The population-based effectiveness of vaccination in reducing the risk of moderate and severe cases of and death from Omicron BA.2 with the consideration of NPI and oral anti-viral therapy were assessed by using Bayesian hierarchical models.

RESULTS

The risks of three clinical outcomes associated with Omicron VOC infection were lowest for booster vaccination, followed by primary vaccination, and highest for incomplete vaccination with the consistent trends of being at increased risk for three outcomes from the young people aged 12 years or below until the elderly people aged 75 years or older with 7 age groups. Before the period using oral anti-viral therapy, complete primary vaccination with the duration more than 9 months before outbreaks conferred the statistically significant 47 % (23-64 %) reduction of death, 48 % (30-61 %) of severe disease, and 46 % (95 % CI: 37-54 %) of moderate disease after adjusting for 10-20 % independent effect of NPI. The benefits of booster vaccination within three months were further enhanced to 76 % (95 % CI: 67-86 %), 74 % (95 % CI: 67-80 %), and 61 % (95 % CI: 56-65 %) for three corresponding outcomes. The additional effectiveness of oral anti-viral therapy in reducing moderate disease was 13 % for the booster group and 5.8 % for primary vaccination.

CONCLUSIONS

We corroborated population effectiveness of primary vaccination and its booster vaccination, independent of oral anti-viral therapy and NPI, in reducing severe clinical outcomes associated with Omicron BA.2 naïve infection population.