Nudging towards COVID-19 and influenza vaccination uptake in medically at-risk children: EPIC study protocol of randomised controlled trials in Australian paediatric outpatient clinics

Introduction
Children with chronic medical diseases are at an unacceptable risk of hospitalisation and death from influenza and SARS-CoV-2 infections. Over the past two decades, behavioural scientists have learnt how to design non-coercive ‘nudge’ interventions to encourage positive health behaviours. Our study aims to evaluate the impact of multicomponent nudge interventions on the uptake of COVID-19 and influenza vaccines in medically at-risk children.

Methods and analyses
Two separate randomised controlled trials (RCTs), each with 1038 children, will enrol a total of approximately 2076 children with chronic medical conditions who are attending tertiary hospitals in South Australia, Western Australia and Victoria. Participants will be randomly assigned (1:1) to the standard care or intervention group. The nudge intervention in each RCT will consist of three text message reminders with four behavioural nudges including (1) social norm messages, (2) different messengers through links to short educational videos from a paediatrician, medically at-risk child and parent and nurse, (3) a pledge to have their child or themselves vaccinated and (4) information salience through links to the current guidelines and vaccine safety information. The primary outcome is the proportion of medically at-risk children who receive at least one dose of vaccine within 3 months of randomisation. Logistic regression analysis will be performed to determine the effect of the intervention on the probability of vaccination uptake.

Ethics and dissemination
The protocol and study documents have been reviewed and approved by the Women’s and Children’s Health Network Human Research Ethics Committee (HREC/22/WCHN/2022/00082). The results will be published via peer-reviewed journals and presented at scientific meetings and public forums.

Trial registration number
NCT05613751.

Leggi
Febbraio 2024

Descriptive analysis to assess seasonal patterns of COVID-19 and influenza in low-income and middle-income countries in Asia, the Middle East and Latin America

Objectives
Understanding disease seasonality can help predict the occurrence of outbreaks and inform public health planning. Respiratory diseases typically follow seasonal patterns; however, knowledge regarding the seasonality of COVID-19 and its impact on the seasonality of influenza remains limited. The objective of this study was to provide more evidence to understand the circulation of SARS-CoV-2, the virus responsible for COVID-19, in an endemic scenario to guide potential preventive strategies.

Design
In this study, a descriptive analysis was undertaken to describe seasonality trends and/or overlap between COVID-19 and influenza in 12 low-income and middle-income countries using Our World in Data and FluMart data sources. Plots of COVID-19 and influenza cases were analysed.

Setting
Singapore, Thailand, Malaysia, the Philippines, Argentina, Brazil, Mexico, South Africa, Morocco, Bahrain, Qatar and Saudi Arabia.

Outcome measures
COVID-19 cases and influenza cases.

Results
No seasonal patterns of SARS-CoV-2 or SARS-CoV-2/influenza cocirculation were observed in most countries, even when considering the avian influenza pandemic period.

Conclusions
These results can inform public health strategies. The lack of observed seasonal behaviour highlights the importance of maintaining year-round vaccination rather than implementing seasonal campaigns. Further research investigating the influence of climate conditions, social behaviour and year-round preventive measures could be fundamental for shaping appropriate policies related to COVID-19 and respiratory viral disease control in low-income and middle-income countries as COVID-19 variant data and epidemiologic patterns accrue over time.

Leggi
Gennaio 2024

Risk factor associations for severe COVID-19, influenza and pneumonia in people with diabetes to inform future pandemic preparations: UK population-based cohort study

Objective
This study aimed to compare clinical and sociodemographic risk factors for severe COVID-19, influenza and pneumonia, in people with diabetes.

Design
Population-based cohort study.

Setting
UK primary care records (Clinical Practice Research Datalink) linked to mortality and hospital records.

Participants
Individuals with type 1 and type 2 diabetes (COVID-19 cohort: n=43 033 type 1 diabetes and n=584 854 type 2 diabetes, influenza and pneumonia cohort: n=42 488 type 1 diabetes and n=585 289 type 2 diabetes).

Primary and secondary outcome measures
COVID-19 hospitalisation from 1 February 2020 to 31 October 2020 (pre-COVID-19 vaccination roll-out), and influenza and pneumonia hospitalisation from 1 September 2016 to 31 May 2019 (pre-COVID-19 pandemic). Secondary outcomes were COVID-19 and pneumonia mortality. Associations between clinical and sociodemographic risk factors and each outcome were assessed using multivariable Cox proportional hazards models. In people with type 2 diabetes, we explored modifying effects of glycated haemoglobin (HbA1c) and body mass index (BMI) by age, sex and ethnicity.

Results
In type 2 diabetes, poor glycaemic control and severe obesity were consistently associated with increased risk of hospitalisation for COVID-19, influenza and pneumonia. The highest HbA1c and BMI-associated relative risks were observed in people aged under 70 years. Sociodemographic-associated risk differed markedly by respiratory infection, particularly for ethnicity. Compared with people of white ethnicity, black and south Asian groups had a greater risk of COVID-19 hospitalisation, but a lesser risk of pneumonia hospitalisation. Risk factor associations for type 1 diabetes and for type 2 diabetes mortality were broadly consistent with the primary analysis.

Conclusions
Clinical risk factors of high HbA1c and severe obesity are consistently associated with severe outcomes from COVID-19, influenza and pneumonia, especially in younger people. In contrast, associations with sociodemographic risk factors differed by type of respiratory infection. This emphasises that risk stratification should be specific to individual respiratory infections.

Leggi
Gennaio 2024