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Detecting behavioural changes in human movement to inform the spatial scale of interventions against COVID-19.

ABSTRACT: On March 23 2020, the UK enacted an intensive, nationwide lockdown to mitigate transmission of COVID-19. As restrictions began to ease, more localized interventions were used to target resurgences in transmission. Understanding the spatial scale of networks of human interaction, and how these networks change over time, is critical to targeting interventions at the most at-risk areas without unnecessarily restricting areas at low risk of resurgence. We use detailed human mobility data aggregated from Facebook users to determine how the spatially-explicit network of movements changed before and during the lockdown period, in response to the easing of restrictions, and to the introduction of locally-targeted interventions. We also apply community detection techniques to the weighted, directed network of movements to identify geographically-explicit movement communities and measure the evolution of these community structures through time. We found that the mobility network became more sparse and the number of mobility communities decreased under the national lockdown, a change that disproportionately affected long distance connections central to the mobility network. We also found that the community structure of areas in which locally-targeted interventions were implemented following epidemic resurgence did not show reorganization of community structure but did show small decreases in indicators of travel outside of local areas. We propose that communities detected using Facebook or other mobility data be used to assess the impact of spatially-targeted restrictions and may inform policymakers about the spatial extent of human movement patterns in the UK. These data are available in near real-time, allowing quantification of changes in the distribution of the population across the UK, as well as changes in travel patterns to inform our understanding of the impact of geographically-targeted interventions.

SUBMITTER: Gibbs H

PROVIDER: S-EPMC8297940 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Interventions that work must be effectively delivered at scale to achieve population level benefits. Researchers must choose among a vast array of implementation frameworks (>?60) that guide design and evaluation of implementation and scale-up processes. Therefore, we sought to recommend conceptual frameworks that can be used to design, inform, and evaluate implementation of physical activity (PA) and nutrition interventions at different stages of the program life cycle. We also sought to recommend a minimum data set of implementation outcome and determinant variables (indicators) as well as measures and tools deemed most relevant for PA and nutrition researchers. METHODS:We adopted a five-round modified Delphi methodology. For rounds 1, 2, and 3 we administered online surveys to PA and nutrition implementation scientists to generate a rank order list of most commonly used; i) implementation and scale-up frameworks, ii) implementation indicators, and iii) implementation and scale-up measures and tools. Measures and tools were excluded after round 2 as input from participants was very limited. For rounds 4 and 5, we conducted two in-person meetings with an expert group to create a shortlist of implementation and scale-up frameworks, identify a minimum data set of indicators and to discuss application and relevance of frameworks and indicators to the field of PA and nutrition. RESULTS:The two most commonly referenced implementation frameworks were the Framework for Effective Implementation and the Consolidated Framework for Implementation Research. We provide the 25 most highly ranked implementation indicators reported by those who participated in rounds 1-3 of the survey. From these, the expert group created a recommended minimum data set of implementation determinants (n?=?10) and implementation outcomes (n?=?5) and reconciled differences in commonly used terms and definitions. CONCLUSIONS:Researchers are confronted with myriad options when conducting implementation and scale-up evaluations. Thus, we identified and prioritized a list of frameworks and a minimum data set of indicators that have potential to improve the quality and consistency of evaluating implementation and scale-up of PA and nutrition interventions. Advancing our science is predicated upon increased efforts to develop a common 'language' and adaptable measures and tools.

Project description:BackgroundCurrent approaches to support patients living with post-COVID condition, also known as Long COVID, are highly disparate with limited success in managing or resolving a well-documented and long-standing symptom burden. With approximately 2.1 million people living with the condition in the UK alone and millions more worldwide, there is a desperate need to devise support strategies and interventions for patients.MethodsA three-round Delphi consensus methodology was distributed internationally using an online survey and was completed by healthcare professionals (including clinicians, physiotherapists, and general practitioners), people with long COVID, and long COVID academic researchers (round 1 n = 273, round 2 n = 186, round 3 n = 138). Across the three rounds, respondents were located predominantly in the United Kingdom (UK), with 17.3-15.2% (round 1, n = 47; round 2 n = 32, round 2 n = 21) of respondents located elsewhere (United States of America (USA), Austria, Malta, United Arab Emirates (UAE), Finland, Norway, Malta, Netherlands, Iceland, Canada, Tunisie, Brazil, Hungary, Greece, France, Austrailia, South Africa, Serbia, and India). Respondents were given ∼5 weeks to complete the survey following enrolment, with round one taking place from 02/15/2022 to 03/28/22, round two; 05/09/2022 to 06/26/2022, and round 3; 07/14/2022 to 08/09/2022. A 5-point Likert scale of agreement was used and the opportunity to include free text responses was provided in the first round.FindingsFifty-five statements reached consensus (defined as >80% agree and strongly agree), across the domains of i) long COVID as a condition, ii) current support and care available for long COVID, iii) clinical assessments for long COVID, and iv) support mechanisms and rehabilitation interventions for long COVID, further sub-categorised by consideration, inclusion, and focus. Consensus reached proposes that long COVID requires specialised, comprehensive support mechanisms and that interventions should form a personalised care plan guided by the needs of the patients. Supportive approaches should focus on individual symptoms, including but not limited to fatigue, cognitive dysfunction, and dyspnoea, utilising pacing, fatigue management, and support returning to daily activities. The mental impact of living with long COVID, tolerance to physical activity, emotional distress and well-being, and research of pre-existing conditions with similar symptoms, such as myalgic encephalomyelitis, should also be considered when supporting people with long COVID.InterpretationWe provide an outline that achieved consensus with stakeholders that could be used to inform the design and implementation of bespoke long COVID support mechanisms.FundingNone.

Project description:BackgroundPopulation health interventions (PHIs) have the potential to improve the health of large populations by systematically addressing underlying conditions of poor health outcomes (i.e., social determinants of health) and reducing health inequities. Scaling-up may be one means of enhancing the impact of effective PHIs. However, not all scale-up attempts have been successful. In an attempt to help guide the process of successful scale-up of a PHI, we look to the organizational readiness for change theory for a new perspective on how we may better understand the scale-up pathway. Using the change theory, our goal was to develop the foundations of an evidence-based, theory-informed framework for a PHI, through a critical examination of various PHI scale-up experiences documented in the literature.MethodsWe conducted a multi-step, critical interpretive synthesis (CIS) to gather and examine insights from scale-up experiences detailed in peer-reviewed and grey literatures, with a focus on PHIs from a variety of global settings. The CIS included iterative cycles of systematic searching, sampling, data extraction, critiquing, interpreting, coding, reflecting, and synthesizing. Theories relevant to innovations, complexity, and organizational readiness guided our analysis and synthesis.ResultsWe retained and examined twenty different PHI scale-up experiences, which were extracted from 77 documents (47 peer-reviewed, 30 grey literature) published between 1995 and 2013. Overall, we identified three phases (i.e., Groundwork, Implementing Scale-up, and Sustaining Scale-up), 11 actions, and four key components (i.e., PHI, context, capacity, stakeholders) pertinent to the scale-up process. Our guiding theories provided explanatory power to various aspects of the scale-up process and to scale-up success, and an alternative perspective to the assessment of scale-up readiness for a PHI.ConclusionOur synthesis provided the foundations of the Scale-up Readiness Assessment Framework. Our theoretically-informed and rigorous synthesis methodology permitted identification of disparate processes involved in the successful scale-up of a PHI. Our findings complement the guidance and resources currently available, and offer an added perspective to assessing scale-up readiness for a PHI.

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Detecting behavioural changes in human movement to inform the spatial scale of interventions against COVID-19.

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