BACKGROUND AND OBJECTIVES:Healthcare utilisation was disrupted by the COVID-19 pandemic, adversely affecting population health. This study investigated healthcare access and utilisation during the COVID-19 pandemic. METHOD:The Optimise Study recruited Victorian adults during September 2020-December 2021. This cross-sectional study examined difficulty accessing healthcare, changes experienced in healthcare utilisation and concerns related to healthcare. RESULTS:Among 779 participants, one-fifth had difficulty accessing healthcare. Participants with chronic illness/es (adjusted odds ratio [aOR]: 2.15, 95% confidence interval [CI]: 1.40-3.30) or earning $1-49,999 per year (aOR: 2.31, 95%CI: 1.14-4.93) or speaking a language other than English at home (aOR: 2.70, 95%CI: 1.38-5.30) had an increased odds of reporting difficulty accessing healthcare. Among 779 participants, the two biggest concerns were delaying or avoiding seeking care (24.4%) and anxiety associated with attending services because of the COVID-19 pandemic (24.0%). DISCUSSION:Future pandemic planning should consider strategies to ensure clear and timely communication with people about how to continue accessing healthcare in emergency situations.

IntroductionSevere COVID-19 disease is characterised by a state of hyperinflammation. As key producers of inflammatory mediators in blood, altered inflammatory activity of monocytes within some individuals may contribute to adverse disease outcomes.MethodsAnalysis of monocyte activity under settings of infection and inflammation can be challenged by activation-induced shedding of monocyte receptors traditionally used to identify monocyte subsets. Here, we utilised alternative, more robust immunophenotyping approaches to investigate the impact of COVID-19 infection on monocyte phenotype and inflammatory status.ResultsImmunophenotype analysis of cryopreserved peripheral blood mononuclear cells from unvaccinated, previously COVID-19 naive individuals (median age 43 years, range 21-95, n=42) with a PCR-confirmed acute COVID-19 infection indicated expansion of a novel population of CD14lowCD16- monocytes as compared to control individuals (adjusted p value <0.001) which was more pronounced in individuals with severe disease presentation (p=0.004 for mild vs severe disease). Expansion of this population during acute COVID-19 was confirmed using an alternative, CD14 and CD16-independent strategy for identifying monocyte subsets and was termed infection associated monocytes (IAM). IAM were refractory to ex vivo stimulation with lipopolysaccharide (LPS) and their proportion correlated with plasma levels of TNF and CXCL10 (p<0.05 for both). Monocyte subsets from individuals with acute COVID-19 exhibited reduced basal and LPS-stimulated production of inflammatory cytokines including IL-1β, TNF and IL-6, indicative of an inert monocyte state. Expansion of IAM and impaired inflammatory activity persisted for up to 3 months after acute COVID-19 infection.DiscussionCOVID-19 is associated with expansion of a novel subset of monocytes with impaired inflammatory activity that persist for at least 3 months after acute infection. Whether this population is uniquely expanded by COVID-19, and the long term implications of its persistence post-acute disease, remain to be defined.

To examine adherence to COVID-19 public health measures among culturally and linguistically diverse (CALD) and low socio-economic status (SES) populations in Victoria using a unique longitudinal cohort. The Optimise Study was a mixed-methods longitudinal cohort and social networks study (September 2020 – December 2023) assessing the impact of COVID-19 and related public health measures in Victoria, Australia. We used a serial cross-sectional design to analyse adherence to public health recommendations, restrictions, and requirements. The study examines two 28-day periods during the COVID-19 pandemic in Victoria: April 23– May 20, 2021 (‘non-lockdown’), and September 13–October 10, 2021 (‘lockdown’). We explored adherence to three categories of COVID-19 public health measures — Recommendations (non-enforced, longer-term), Restrictions (mandated during lockdown periods), and Requirements (mandated, longer-term) — among participants who completed questionnaires during these periods. Participants were grouped as: 1) non-CALD high SES (did not meet CALD or low-SES criteria), 2) CALD, or 3) non-CALD low-SES. Primary outcomes were adherence to Recommendations, Restrictions, and Requirements during the two study periods. Of 782 participants recruited, 579 (75%) completed a survey or diary during at least one study period and were included in the analysis. Of these, 275 (47%) were in the ‘non-CALD high-SES’ group, 114 (20%) in the CALD group, and 190 (33%) in the ‘non-CALD low-SES’ group. Across all groups, risk-reduction behaviours increased during the lockdown. CALD participants showed higher adherence to some Recommendations and Restrictions compared to the other groups. Overall, 28% left home while awaiting a COVID-19 test result, commonly due to work. High adherence among CALD and ‘non-CALD low-SES’ groups suggest structural barriers, rather than behavioural non-compliance, contributed to higher COVID-19 impacts, highlighting the need for tailored support. During future public health emergencies, better supports are needed for individuals working outside of home to remain in isolation while awaiting a test result. What is already known about this subject? In Australia, priority populations such as culturally and linguistically diverse (CALD) and low socio-economic status (SES) groups experienced higher COVID-19 infection, mortality and a disproportionate impact from public health restrictions. What does this study add? CALD populations had an overall higher level of adherence to public health behavioural measures during both lockdown and non-lockdown periods compared to non-CALD populations. Over 25% of participants did not comply with stay-at-home requirements while awaiting a COVID-19 test result, largely due to work responsibilities. How might this impact on clinical practice? Pandemic preparedness efforts should focus on understanding the reasons for non-adherence with isolation requirements and considering tailored support during future pandemics to address the diverse

Propensity scores are an important tool for using observational data to answer causal questions. Machine learning methods for estimating propensity scores have out-performed more commonly used logistic regression methods in studies considering large, synthetic datasets. To inform propensity estimation methods for smaller datasets from real-world observational studies, we describe the implementation of machine learning algorithms using data from a prison-recruited cohort. This study describes a procedure to use logistic regression, gradient-boosting, random forest and single-hidden-layer neural networks to balance confounders between a treatment and control group. We assess balance using the average standardised absolute mean difference (ASAM), where a lower ASAM indicates better balance. We provide an application to an observational cohort of Australian incarcerated men for a causal question for the effect of emotional support in prison on emergency department presentations within 100 days post prison release. There were 328 participants, of whom 231 (70

Background The COVID-19 pandemic exacerbated health disparities globally, with certain populations experiencing disproportionate disease burdens. In Australia, COVID-19 deaths occurred disproportionately among first-generation migrants. This study examined risk factors for COVID-19 infection in a Victorian cohort recruited from priority populations, including healthcare workers, people with chronic health conditions, and culturally and linguistically diverse (CALD) communities. Methods We conducted a cross-sectional analysis of participants from the Optimise longitudinal cohort study (September 2020–December 2023). The primary outcome was the self-reported count of confirmed COVID-19 infections (PCR or rapid antigen test positive) from December 2019 to December 2023. We used Poisson regression to examine associations between baseline sociodemographic characteristics and infection count, calculating unadjusted and adjusted incidence rate ratios (IRRs) with 95% confidence intervals (CIs). Results Of 433 participants (median age 51 years, 75% female), 25% reported no infections, 48% reported one infection, and 27% reported two or more infections. In univariate analysis, CALD status (IRR=1.24,95%CI:1.02–1.50) and larger household size (2-5 people, IRR=1.71,95%CI:1.14-2.50) were associated with higher infection rates, while chronic health conditions (IRR=0.73, 95%CI:0.61–0.88) and older age (IRR=0.54, 95%CI:0.43–0.67) were associated with lower infection rates. In adjusted analysis, younger age (18-34 years vs ≥55 years: aIRR=0.63,95%CI:0.48–0.82) and medium household size (living alone vs 2-5 person household: aIRR=1.42, 95%CI:1.11–1.83) remained significant predictors. CALD status and socioeconomic status showed no independent association with infection risk after adjustment for household size and age. Conclusion COVID-19 infection risk in this Victorian cohort was driven by younger age and larger household size rather than CALD status or socioeconomic status, suggesting that housing density and age, rather than cultural or socioeconomic characteristics, determined infection patterns. Future pandemic preparedness should prioritise policies enabling safe quarantine and isolation for individuals in larger households and workplace protections and economic security for younger essential workers. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Protocols ### Funding Statement The author(s) received no specific funding for this work. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics approval for Optimise was provided by the Alfred Human Research Ethics Committee, Approval Number 333/20. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All relevant data are within the manuscript and its Supporting Information files.

Background:It is critical to disseminate all evidence on long COVID's impact on people's lives to inform policy and practice. We aimed to assess five measures of well-being, before and after SARS-CoV-2 infection between people with long COVID (defined as symptoms lasting more than 1 month) and people with short COVID (defined as symptoms resolving within 1 month). Methods:Participants from the Optimise Study, a longitudinal cohort study in Victoria, Australia (September 2020-August 2022), had self-reported history of SARS-CoV-2 infection and self-reported long COVID status. Serial cross-sectional analysis compared participants with long and short COVID on Personal Well-being Index, number of COVID-19-like symptoms experienced, number of days exercised and frequency of experiencing positive and negative emotions. Results:217 participants were included, aged 20-86 years (median age 43, IQR: 31-57), 75% women. Compared with those with short COVID, participants with long COVID had lower well-being before (mean difference (MD)=-8.3, 95% CI (-14.7, -2.0), p-adjusted=0.07), during (MD=-10.3, 95% CI (-16.5, -4.0), p-adjusted=0.03) and after (MD=-9.91, 95% CI (-16.71, -3.11), p-adjusted=0.05) infection and experienced more COVID-19-like symptoms during infection (MD=1.72 (0.72, 2.72), p-adjusted=0.03). In December 2022, 71% (40/56) reported difficulty performing tasks in the past 4 weeks. Conclusion:On average, we observed lower well-being among participants with long COVID, including before SARS-CoV-2 infection, suggesting an underlying difference in well-being between groups. Long COVID continued to impact physical functioning, but ongoing changes were not detected by personal well-being scales.

Background/Objectives: Understanding the psychological determinants of vaccine uptake is critical for effective public health strategies, particularly during prolonged pandemics. The Health Belief Model is widely used to examine vaccine behavior, yet its applicability in longitudinal and policy-intensive contexts remains underexplored. This study assessed how two core Health Belief Model constructs—perceived severity of and susceptibility to COVID-19—related to vaccine intentions and uptake over time, and how these perceptions varied by demographic characteristics. Methods: Data came from Optimise, a longitudinal cohort study of adults in Victoria, Australia, conducted between September 2020 and August 2022. Perceived severity of and susceptibility to COVID-19 were measured monthly, alongside COVID-19 vaccine intentions and uptake. Generalized Estimating Equations evaluated associations between these two Health Belief Model constructs and vaccine outcomes over time. Separate models identified demographic predictors of perceived severity and susceptibility. Results: Perceived severity of COVID-19 was positively associated with intention to receive further COVID-19 vaccine doses (OR = 2.53, 95% CI: 1.26–5.07) and the total vaccine doses received (OR = 2.74, 95% CI: 1.58–4.76), with these associations changing over time as vaccine mandates were lifted and the pandemic context evolved. Perceived susceptibility to COVID-19 showed no significant associations with vaccine outcomes. Older age, presence of a chronic health condition, and lower employment status was associated with higher perceived severity. In contrast, perceived susceptibility was higher among high-income earners but lower among older adults and the unemployed. Conclusions: The predictive value of two Health Belief Model constructs was context- and time-dependent. Perceived severity consistently predicted vaccine uptake once mandates were lifted, while susceptibility did not. Our findings highlight the importance of context-sensitive behavioral frameworks when designing vaccine promotion strategies during extended public health crises.

Introduction:Long COVID is a significant public health concern. This study aimed to identify the prevalence, impact, and factors associated with long COVID among young people in Victoria, Australia. Methods:From April to June 2023, we conducted a cross-sectional online survey of people aged 15-29 years. Participants reported if they had ever experienced long COVID (defined as COVID-19 symptoms for more than 4 weeks) and the impact on their daily functioning. We used multivariable logistic regression to compare participants who reported long COVID with participants who reported acute COVID-19. Results:Among 765 participants, 11.2% reported they had ever had long COVID; however, only 1 in 10 had been diagnosed by a medical practitioner. Compared to those without prolonged symptoms, participants reporting long COVID were younger (adjusted odds ratio [aOR]: 0.92; 95% confidence interval [CI]: 0.85-0.99), reported worsened general health (aOR: 8.22; 95% CI: 4.34-15.56), expressed greater concern about getting long COVID again (aOR: 1.20; 95% CI: 1.09-1.33), and had more family or friends who also experienced long COVID (aOR: 4.43; 95% CI: 1.92-10.19). In the past 4 weeks, 79.1% of participants with current long COVID reported difficulties with performing work, and 79.1% accomplished less than desired. Conclusions:One in 10 participants aged 15-29 years experienced long COVID, and most reported negative impacts on their daily life. General practitioners should be aware of the high burden of suspected long COVID in young people and consider supports to mitigate its effects on the health and well-being of this population.

Introduction Longitudinal studies can provide timely and accurate information to evaluate and inform COVID-19 control and mitigation strategies and future pandemic preparedness. The Optimise Study is a multidisciplinary research platform established in the Australian state of Victoria in September 2020 to collect epidemiological, social, psychological and behavioural data from priority populations. It aims to understand changing public attitudes, behaviours and experiences of COVID-19 and inform epidemic modelling and support responsive government policy.Methods and analysis This protocol paper describes the data collection procedures for the Optimise Study, an ongoing longitudinal cohort of ~1000 Victorian adults and their social networks. Participants are recruited using snowball sampling with a set of seeds and two waves of snowball recruitment. Seeds are purposively selected from priority groups, including recent COVID-19 cases and close contacts and people at heightened risk of infection and/or adverse outcomes of COVID-19 infection and/or public health measures. Participants complete a schedule of monthly quantitative surveys and daily diaries for up to 24 months, plus additional surveys annually for up to 48 months. Cohort participants are recruited for qualitative interviews at key time points to enable in-depth exploration of people’s lived experiences. Separately, community representatives are invited to participate in community engagement groups, which review and interpret research findings to inform policy and practice recommendations.Ethics and dissemination The Optimise longitudinal cohort and qualitative interviews are approved by the Alfred Hospital Human Research Ethics Committee (# 333/20). The Optimise Study CEG is approved by the La Trobe University Human Ethics Committee (# HEC20532). All participants provide informed verbal consent to enter the cohort, with additional consent provided prior to any of the sub studies. Study findings will be disseminated through public website (https://optimisecovid.com.au/study-findings/) and through peer-reviewed publications.Trial registration number NCT05323799.

ObjectivesWhilst public health measures were effective in reducing COVID-19 transmission, unintended negative consequences may have occurred. This study aims to assess changes alcohol consumption and the heavy episodic drinking (HED) during the pandemic.MethodsData were from the Optimise Study, a longitudinal cohort of Australian adults September 2020-August 2022 that over-sampled priority populations at higher risk of contracting COVID-19, developing severe COVID-19 or experiencing adverse consequences of lockdowns. Frequency of alcohol consumption (mean number of days per week) and past-week HED were self-reported. Generalised linear models estimated the association between time and (1) the frequency of alcohol consumption and (2) heavy episodic drinking.ResultsData from 688 participants (mean age: 44.7 years, SD:17.0; 72.7% female) and 10,957 surveys were included. Mean days of alcohol consumption per week decreased from 1.92 (SD: 1.92) in 2020 to 1.54 (SD:1.94) in 2022. The proportion of participants reporting HED decreased from 25.4% in 2020 to 13.1% in 2022. During two lockdown periods, known as "lockdown five", (OR:0.65, 95%CI [0.47,0.90]) and "lockdown six" (OR:0.76, 95%CI [0.67,0.87]), participants were less likely to report HED.ConclusionsParticipants alcohol drinking frequency and HED decreased during the pandemic. This study provides a strong description of alcohol consumption during the pandemic and suggests that lockdowns did not have the unintended consequences of increased alcohol consumption.

OBJECTIVE:To estimate the proportion of Victorians infected with COVID-19 in January 2022.METHODS:Between 11-19 February 2022 we conducted a nested cross-sectional survey on experiences of COVID-19 testing, symptoms, test outcome and barriers to testing during January 2022 in Victoria, Australia. Respondents were participants of the Optimise Study, a prospective cohort of adults considered at increased risk of COVID-19 or the unintended consequences of COVID-19-related interventions.RESULTS:Of the 577 participants, 78 (14%) reported testing positive to COVID-19, 240 (42%) did not test in January 2022 and 91 of those who did not test (38%) reported COVID-19-like symptoms. Using two different definitions of symptoms, we calculated symptomatic (27% and 39%) and asymptomatic (4% and 11%) test positivity. We extrapolated these positivity rates to participants who did not test and estimated 19-22% of respondents may have had COVID-19 infection in January 2022.CONCLUSION:The proportion of Victorians infected with COVID-19 in January 2022 was likely considerably higher than officially reported numbers.IMPLICATIONS FOR PUBLIC HEALTH:Our estimate is approximately double the COVID-19 case numbers obtained from official case reporting. This highlights a major limitation of diagnosis data that must be considered when preparing for future waves of infection.

OBJECTIVE:We describe COVID-19 risk reduction strategies adopted by Victorian adults during December 2021-January 2022, a period of high COVID-19 infection and limited government mandated public health measures.METHODS:In February 2022, participants of a Victorian-based cohort study (Optimise) completed a cross-sectional survey on risk reduction behaviours during December 2021-January 2022. Regression modelling estimated the association between risk reduction and demographics.RESULTS:A total of 556 participants were included (median age 47 years; 75% women; 82% in metropolitan Melbourne). Two-thirds (61%) adopted at least one risk reduction behaviour, with uptake highest among younger participants (18-34 years; adjusted relative risk (aRR): 1.20, 95% confidence interval [CI]: 1.01, 1.41) and those with a chronic health condition (aRR: 1.17, 95% CI: 1.02, 1.35).CONCLUSIONS:Participants adopted their own COVID-19 risk reduction strategies in a setting of limited government restrictions, with young people more likely to adopt a risk reduction strategy that did not limit social mobility.IMPLICATION FOR PUBLIC HEALTH:A public health response to COVID-19 that focusses on promoting personal risk reduction behaviours, as opposed to mandated restrictions, could be enhanced by disseminating information on and increasing availability of effective risk reduction strategies tailored to segments of the population.

Background Longitudinal studies are critical to informing evolving responses to COVID-19 but can be hampered by attrition bias, which undermines their reliability for guiding policy and practice. We describe recruitment and retention in the Optimise Study, a longitudinal cohort and social networks study that aimed to inform public health and policy responses to COVID-19. Methods Optimise recruited adults residing in Victoria, Australia September 01 2020–September 30 2021. High-frequency follow-up data collection included nominating social networks for study participation and completing a follow-up survey and four follow-up diaries each month, plus additional surveys if they tested positive for COVID-19 or were a close contact. This study compared number recruited to a-priori targets as of September 302,021, retention as of December 31 2021, comparing participants retained and not retained, and follow-up survey and diary completion October 2020–December 2021. Retained participants completed a follow-up survey or diary in each of the final three-months of their follow-up time. Attrition was defined by the number of participants not retained, divided by the number who completed a baseline survey by September 302,021. Survey completion was calculated as the proportion of follow-up surveys or diaries sent to participants that were completed between October 2020–December 2021. Results At September 302,021, 663 participants were recruited and at December 312,021, 563 were retained giving an overall attrition of 15% ( n = 100/663). Among the 563 retained, survey completion was 90% ( n = 19,354/21,524) for follow-up diaries and 89% ( n = 4936/5560) for monthly follow-up surveys. Compared to participants not retained, those retained were older (t-test, p < 0.001), and more likely to be female (χ 2 , p = 0.001), and tertiary educated (χ 2 , p = 0.018). Conclusion High levels of study retention and survey completion demonstrate a willingness to participate in a complex, longitudinal cohort study with high participant burden during a global pandemic. We believe comprehensive follow-up strategies, frequent dissemination of study findings to participants, and unique data collection systems have contributed to high levels of study retention.

Background: High vaccine uptake requires strong public support, acceptance, and willingness. Methods: A longitudinal cohort study gathered survey data every four weeks between 1 October 2020 and 9 November 2021 in Victoria, Australia. Data were analysed for 686 participants aged 18 years and older. Results: Vaccine intention in our cohort increased from 60% in October 2020 to 99% in November 2021. Vaccine intention increased in all demographics, but longitudinal trends in vaccine intention differed by age, employment as a healthcare worker, presence of children in the household, and highest qualification attained. Acceptance of vaccine mandates increased from 50% in October 2020 to 71% in November 2021. Acceptance of vaccine mandates increased in all age groups except 18–25 years; acceptance also varied by gender and highest qualification attained. The main reasons for not intending to be vaccinated included safety concerns, including blood clots, and vaccine efficacy. Conclusion: COVID-19 vaccination campaigns should be informed by understanding of the sociodemographic drivers of vaccine acceptance to enable socially and culturally relevant guidance and ensure equitable vaccine coverage. Vaccination policies should be applied judiciously to avoid polarisation.