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with improvements in clinical knowledge of Covid-19.

Disasters such as the COVID-19 pandemic pose an overwhelming demand on resources that cannot always be met by official organisations. Limited resources and human response to crises can lead members of local communities to turn to one another to fulfil immediate needs. This spontaneous citizen-led response can be crucial to a community's ability to cope in a crisis. It is thus essential to understand the scope of such initiatives so that support can be provided where it is most needed. Nevertheless, quickly developing situations and varying definitions can make the community response challenging to measure.

To create an accessible interactive map of the citizen-led community response to need during the COVID-19 pandemic in Wales, UK that combines information gathered from multiple data providers to reflect different interpretations of need and support.

We gathered data from a combination of official data providers and community-generated sources to create 14 variables representative of need and support. unity response to explore and analyse the distribution of need and support across Wales. While there can be limitations to the accuracy of community-generated data, we demonstrate that they can be effectively used alongside traditional data sources to maximise the understanding of community action. This adds to our overall aim to measure community response and resilience, as well as to make complex population health data accessible to a range of audiences. Future developments include the integration of other factors such as well-being.Hospital data for covid-19 surveillance, planning and modelling are challenging to find worldwide in public aggregation portals. Detailed covid-19 hospital data provides insights into covid-19's health burden including identifying which sociodemographic groups are at greatest risk of covid-19 morbidity and mortality. Timely hospital data is the best source of information for actionable forecasts and projection models of hospital capacity, including critical resources such as intensive care unit beds and ventilators that take time to plan or procure. A challenge to generate timely and detailed hospital data is the reliance on separation or discharge abstracts and census counts. What are needed are well-maintained lists of patients hospitalized with covid-19. From the standpoint of public health and health services researchers and practitioners, we describe the role of hospital data for studying covid-19, why admission data are hard to find, and how improved data infrastructure can meet surveillance and planning needs in the near future. Modern hospital electronic health records can create covid-19 patient lists and these decision support tools are increasingly used for research. These tools can generate patient lists that are transmitted and combined with public health data systems.

The unprecedented COVID-19 pandemic unveiled a strong need for advanced and informative surveillance tools. The Centre for Health Informatics (CHI) at the University of Calgary took action to develop a surveillance dashboard, which would facilitate the education of the public, and answer critical questions posed by local and national government.

The objective of this study was to create an interactive method of surveillance, or a "COVID-19 Tracker" for Canadian use. The Tracker offers user-friendly graphics characterizing various aspects of the current pandemic (e.g. case count, testing, hospitalizations, and policy interventions).

Six publicly available data sources were used, and were selected based on the frequency of updates, accuracy and types of data, and data presentation. The datasets have different levels of granularity for different provinces, which limits the information that we are able to show. Additionally, some datasets have missing entries, for which the "last observation carried forwardd Canadians of the current pandemic.

Hospitalizations for ambulatory care sensitive conditions, of which chronic obstructive pulmonary disease (COPD) is among the most common, represent an indirect measure of the healthcare system to manage chronic disease. Research has pointed to disparities in various COPD-related outcomes between persons of lower versus higher income; however, few studies have examined the influence of patients' social context on potentially avoidable COPD admissions.

The research explores the use of linked population census and administrative health data to assess the influence of income inequalities on the risk of hospitalization and rehospitalization for COPD among Canadian adults.

This analysis utilizes data from the 2006 Census linked longitudinally to the 2006/07-2008/09 Discharge Abstract Database. Multiple logistic regressions were conducted to assess the independent influence of income inequality on the risks of hospitalization and of six-month readmission due to COPD among the population aged 30-69, controllinhysician and hospital care, a clear income gradient in the risk of being hospitalized and, to some extent, rehospitalized for COPD, is found. TASIN30 Income inequalities may be contributing to excess hospitalizations, reinforcing the importance of integrating social and economic issues in primary care to meet the ambulatory needs of this population.

The long-term health and wellbeing of adoptees is under-researched. One reason for this has been limited data accessibility regarding the adoption process, and another is a practice common in some UK jurisdictions of changing the National Health Service (NHS) number (or equivalent) at adoption, as part of creating the new identity. The SAIL Databank holds data on child and family court cases from Cafcass Cymru, together with children's social care data, and can link these with routine health and administrative data in anonymised form. However, because the linkage key at SAIL is based on an encryption of the NHS number, working with pre- and post-adoption records for longitudinal research remains a major challenge. We set out to explore the legal implications of, and social support for, linking these records for use in anonymised form for longitudinal research.

We reviewed the main legislation and regulations governing the use of data about adoptees in England and Wales. We gauged support for a social licence in Wales by carrying out interviews with individuals who had been involved in the adoptions process, and by engaging with general public groups for their views.