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Current human papillomavirus (HPV) vaccines provide substantial protection against the most common HPV types responsible for oral and anogenital cancers, but many circulating cancer-causing types remain for which vaccine coverage is lacking. In addition, all current HPV vaccines rely on aluminum salt-based adjuvant formulations that function through unclear mechanisms with few substitutes available. In an effort to expand the toolbox of available adjuvants suitable for HPV vaccines, we compared the immunogenicity of the RG1-VLP (virus-like particle) vaccine in BALB/c mice when formulated with either the aluminum hydroxide adjuvant Alhydrogel or the novel polyphosphazene macromolecular adjuvant poly[di (carboxylatoethylphenoxy) phosphazene] (PCEP). PCEP-formulated RG1-VLPs routinely outperformed VLP/Alhydrogel in several measurements of VLP-specific humoral immunity, including consistent improvements in the magnitude of antibody (Ab) responses to both HPV16-L1 and the L2 RG1 epitope as well as neutralizing titers to HPV16 and cross-neutralization of pseudovirion (PsV) types HPV18 and HPV39. Dose-sparing studies indicated that RG1-VLPs could be reduced in dose by 75% and the presence of PCEP ensured activity comparable to a full VLP dose adjuvanted by Alhydrogel. In addition, levels of HPV16-L1 and -L2-specific Abs were achieved after two vaccinations with PCEP as adjuvant that were equivalent to or greater than levels achieved with three vaccinations with Alhydrogel alone, indicating that the presence of PCEP resulted in accelerated immune responses that could allow for a decreased dose schedule. Given the extensive clinical track record of polyphosphazenes, these data suggest that substitution of alum-based adjuvants with PCEP for the RG1-VLP vaccine could lead to rapid seropositivity requiring fewer boosts, the dose-sparing of commercial VLP-based vaccines, and the establishment of longer-lasting humoral responses to HPV.

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., Competing Interests: Competing interests: Burnet Institute has received investigator initiated clinical research funding form Gilead Sciences, AbbVie and Merck unrelated to this grant., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

COVID-19 has resulted in dramatic and widespread social network interventions across the globe, with public health measures such as distancing and isolation key epidemiological responses to minimize transmission. Because these measures affect social interactions between people, the networked structure of daily lives is changed. Such largescale changes to social structures, present simultaneously across many different societies and touching many different people, give renewed significance to the conceptualization of social network interventions. As social network researchers, we need a framework for understanding and describing network interventions consistent with the COVID-19 experience, one that builds on past work but able to cast interventions across a broad societal framework. In this theoretical paper, we extend the conceptualization of social network interventions in these directions. We follow Valente (2012) with a tripartite categorization of interventions but add a multilevel dimension to capture hierarchical aspects that are a key feature of any society and implicit in any network. This multilevel dimension distinguishes goals, actions, and outcomes at different levels, from individuals to the whole of the society. We illustrate this extended taxonomy with a range of COVID-19 public health measures of different types and at multiple levels, and then show how past network intervention research in other domains can also be framed in this way. We discuss what counts as an effective network, an effective intervention, plausible causality, and careful selection and evaluation, as central to a full theory of network interventions., (© 2022 Elsevier B.V. All rights reserved.)