scholarly journals Workshop: Quantifying burden of disease to support public health policy: exchange of views and experiences

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
Keyword(s):  
Public Health ◽  
Health Insurance ◽  
Burden Of Disease ◽  
Disease Burden ◽  
Healthcare Research ◽  
Decision Makers ◽  
Epidemiological Surveillance ◽  
Public Health Decision ◽  
Disease Information ◽  
Health Decision

Abstract Information on disease burden, risk factors, related healthcare costs and their variations over time represents a major concern for public health decision makers. These data could contribute to define priorities and strategies, to allocate resources and to evaluate health policies and interventions at regional and national levels. In this context, the use and synthesis of all available data is essential, whether these data were collected for the purpose of epidemiological surveillance, healthcare, research, and/or reimbursement. This process raises conceptual and methodological issues. The question of the use of these data by decision-makers is also essential and depends not only on their validity, but also on their credibility, their usability, and their capacity to respond to needs in the context of decision. There are now national experiences of production and use of these data. There are also international collaborations. In particular, the Global Burden of Disease (GBD) Study is an extremely structured process with extensive global collaboration. The aim of this workshop is to exchange and share experiences on the different approaches, indicators, methods used in order to quantify the burden of disease; the use of health insurance databases as a source of data for quantifying burden of disease; the use of burden of disease information by public health decision-makers at national and local levels. Key messages Disease burden statistics are a resource for data-informed policy-making. Health insurance databases are a complementary source for quantifying disease burden.

scholarly journals The NCCMT’s dynamic model for evidence-informed public health

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
E Clark ◽  
S Neil-Sztramko ◽  
M Dobbins
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Research Evidence ◽  
Decision Makers ◽  
Local Data ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Political Preferences ◽  
Health Decision ◽  
Structured Approach

Abstract Issue It is well accepted that public health decision makers should use the best available research evidence in their decision-making process. However, research evidence alone is insufficient to inform public health decision making. Description of the problem As new challenges to public health emerge, there can be a paucity of high quality research evidence to inform decisions on new topics. Public health decision makers must combine various sources of evidence with their public health expertise to make evidence-informed decisions. The National Collaborating Centre for Methods and Tools (NCCMT) has developed a model which combines research evidence with other critical sources of evidence that can help guide decision makers in evidence-informed decision making. Results The NCCMT's model for evidence-informed public health combines findings from research evidence with local data and context, community and political preferences and actions and evidence on available resources. The model has been widely used across Canada and worldwide, and has been integrated into many public health organizations' decision-making processes. The model is also used for teaching an evidence-informed public health approach in Masters of Public Health programs around the globe. The model provides a structured approach to integrating evidence from several critical sources into public health decision making. Use of the model helps ensure that important research, contextual and preference information is sought and incorporated. Lessons Next steps for the model include development of a tool to facilitate synthesis of evidence across all four domains. Although Indigenous knowledges are relevant for public health decision making and should be considered as part of a complete assessment the current model does not capture Indigenous knowledges. Key messages Decision making in public health requires integrating the best available evidence, including research findings, local data and context, community and political preferences and available resources. The NCCMT’s model for evidence-informed public health provides a structured approach to integrating evidence from several critical sources into public health decision making.

scholarly journals Health economics methods for public health resource allocation: a qualitative interview study of decision makers from an English local authority

2019 ◽  
Vol 15 (1) ◽  
pp. 128-140 ◽  
Author(s):  
Emma Frew ◽  
Katie Breheny
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Health Economics ◽  
Local Authority ◽  
Decision Makers ◽  
Natural Experiments ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Qualitative Interview Study ◽  
Health Decision

AbstractLocal authorities in England have responsibility for public health, however, in recent years, budgets have been drastically reduced placing decision makers under unprecedented financial pressure. Although health economics can offer support for decision making, there is limited evidence of it being used in practice. The aim of this study was to undertake in-depth qualitative research within one local authority to better understand the context for public health decision making; what, and how economics evidence is being used; and invite suggestions for how methods could be improved to better support local public health decision making. The study included both observational methods and in-depth interviews. Key meetings were observed and semi-structured interviews conducted with participants who had a decision-making role to explore views on economics, to understand the barriers to using evidence and to invite suggestions for improvements to methods. Despite all informants valuing the use of health economics, many barriers were cited: including a perception of a narrow focus on the health sector; lack of consideration of population impact; and problems with translating long timescales to short term impact. Methodological suggestions included the broadening of frameworks; increased use of natural experiments; and capturing wider non-health outcomes that resonate with the priorities of multiple stakeholders.

Essential skills for using research evidence in public health policy: a systematic review

2021 ◽  
Author(s):  
Saliha Ziam ◽  
Pierre Gignac ◽  
Élodie Courant ◽  
Esther Mc Sween-Cadieux
Keyword(s):  
Public Health ◽  
Systematic Review ◽  
Decision Making ◽  
Research Evidence ◽  
Informed Decision ◽  
Decision Makers ◽  
Informed Decision Making ◽  
Evidence Use ◽  
Public Health Decision ◽  
Health Decision

Background: Decisions related to the development and implementation of public health programmes or policies can benefit from more effective use of the best available knowledge. However, decision makers do not always feel sufficiently equipped or may lack the capacity to use evidence. This can lead them to overlook or set aside research results that could be relevant to their practice area.Aims and objectives: The objective of this systematic review was to synthesise the essential skills that facilitate the use of research evidence by public health decision makers.Methods: Thirty-nine articles that met our inclusion criteria were included. An inductive approach was used to extract data on evidence-informed decision-making-related skills and data were synthesised as a narrative review.Findings: The analysis revealed three categories of skills that are essential for evidence-informed decision-making process: interpersonal, cognitive, and leadership and influencing skills. Such cross-sectoral skills are essential for identifying, obtaining, synthesising, and integrating sound research results into the decision-making process.Discussion and conclusions: The results of this systematic review will help direct capacity-building efforts towards enhancing research evidence use by public health decision makers, such as developing different types of training that would be relevant to their needs. Also, when considering the evidence-informed decision-making skills development, there are several useful and complementary approaches to link research most effectively to action. On one hand, it is important not only to support decision makers at the individual level through skills development, but also to provide them with a day-to-day environment that is conducive to evidence use.<br />Key messages<br /><ul><li>Public health programmes or policies can benefit from more effective use of the best available knowledge;</li><br /><li>This review identified 39 studies on skills related to evidence-informed decision making;</li><br /><li>Three categories of skills are proposed: cognitive, interpersonal and leadership and influencing skills;</li><br /><li>It will help direct capacity-building efforts towards enhancing evidence use by decision makers.</li></ul>

scholarly journals Forecasting the geographical spread of smallpox cases by air travel

2003 ◽  
Vol 131 (2) ◽  
pp. 849-857 ◽  
Author(s):  
R. F. GRAIS ◽  
J. H. ELLIS ◽  
G. E. GLASS
Keyword(s):  
Public Health ◽  
Negative Impact ◽  
Analytical Framework ◽  
Air Travel ◽  
Decision Makers ◽  
Public Health Decision ◽  
Geographical Spread ◽  
Travel Restrictions ◽  
Health Decision ◽  
Potential Benefits

Instituting air travel restrictions to slow the geographical spread of smallpox cases would have significant consequences and present serious logistical concerns. Public health decision makers must weigh the potential benefits of such restrictions against their negative impact. The goal of this research is to provide a basic analytical framework to explore some of the issues surrounding the use of air travel restrictions as a part of an overall containment strategy. We report preliminary results of a compartmental model for the inter-city spread of smallpox cases resulting from US domestic air travel. Although air traffic can be halted within hours as was shown following the terrorist attacks of 11 September 2001, these results suggest that the consequences of halting domestic air travel may not be outweighed by public health benefits.

scholarly journals Seroprevalence of anti-SARS-CoV-2 antibodies among school and daycare children and personnel: protocol for a cohort study in Montreal, Canada

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e053245
Author(s):  
Kate Zinszer ◽  
Britt McKinnon ◽  
Noémie Bourque ◽  
Monica Zahreddine ◽  
Katia Charland ◽  
...  
Keyword(s):  
Public Health ◽  
Well Being ◽  
Decision Makers ◽  
School Level ◽  
Public Health Decision ◽  
Health Lifestyle ◽  
Centre Hospitalier Universitaire ◽  
Health Decision ◽  
Study Participants

IntroductionFurther evidence is needed to understand the contribution of schools and daycares for the spread of COVID-19 in the context of diverse transmission dynamics and continually evolving public health interventions. The Enfants et COVID-19: Étude de séroprévalence (EnCORE) study will estimate the seroprevalence and seroconversion of SARS-CoV-2 among school and daycare children and personnel. In addition, the study will examine associations between seroprevalence and sociodemographic characteristics and reported COVID-19 symptoms and tests, and investigates changes in health, lifestyle and well-being outcomes.Methods and analysisThis study includes children and personnel from 62 schools and daycares in four neighbourhoods in Montreal, Canada. All children aged 2–17 years attending one of the participating schools or daycares and their parents are invited to participate, as well as a sample of personnel members. Participants respond to brief questionnaires and provide blood samples, collected via dried blood spot, at baseline (October 2020–March 2021) and follow-up (May–June 2021). Questionnaires include sociodemographic and household characteristics, reported COVID-19 symptoms and tests, potential COVID-19 risk factors and prevention efforts and health and lifestyle information. Logistic regression using generalised estimating equations will be used to estimate seroprevalence and seroconversion, accounting for school-level clustering.Ethics and disseminationThis study was approved by the research ethics boards of the Université de Montréal (CERSES) and the Centre Hospitalier Universitaire Sainte-Justine. Results will contribute to our knowledge about SARS-CoV-2 transmission in schools and daycares and will be made available to study participants and their families, school and public health decision-makers and the research community.

scholarly journals Model Input and Optimization: Improving the Speed and Accuracy of Our COVID-19 Hospitalization Forecasts

2021 ◽  
Vol 1 (S1) ◽  
pp. s9-s9
Author(s):  
Sarah Rhea ◽  
Emily Hadley ◽  
Kasey Jones ◽  
Alexander Preiss ◽  
Marie Stoner ◽  
...  
Keyword(s):  
Public Health ◽  
North Carolina ◽  
Real Time ◽  
Acute Care ◽  
Acute Care Hospitals ◽  
Decision Makers ◽  
Hospital Level ◽  
Public Health Decision ◽  
Health Decision ◽  
Speed And Accuracy

Background: During the COVID-19 pandemic, public-health decision makers have increasingly relied on hospitalization forecasts that are routinely provided, accurate, and based on timely input data to inform pandemic planning. In North Carolina, we adapted an existing agent-based model (ABM) to produce 30-day hospitalization forecasts of COVID-19 and non–COVID-19 hospitalizations for use by public-health decision makers. We sought to continually improve model speed and accuracy during forecasting. Methods: The geospatially explicit ABM included movement of agents (ie, patients) among 104 short-term acute-care hospitals, 10 long-term acute-care hospitals, 421 licensed nursing homes, and the community in North Carolina. Agents were based on a synthetic population of North Carolina residents (ie, >10.4 million agents). We assigned SARS-CoV-2 infections to agents according to county-level susceptible, exposed, infectious, recovered (SEIR) models informed by reported COVID-19 cases by county. Agents’ COVID-19 severity and probability of hospitalization were determined using agent-specific characteristics (eg, age, comorbidities). During May 2020–December 2020, we produced weekly 30-day forecasts of intensive care unit (ICU) and non-ICU bed occupancy for COVID-19 agents and non–COVID-19 agents statewide and by region under a range of SARS-CoV-2 effective reproduction numbers. During the reporting period, we identified optimizations for faster results turnaround. We evaluated the incorporation of real-time hospital-level occupancy data at model initialization on forecast accuracy using mean absolute percent error (MAPE). Results: During May 2020–December 2020, we provided 31 weekly reports of 30-day hospitalization forecasts with a 1-day turnaround time. Reports included (1) raw and smoothed 7-day average values for 42 model output variables; (2) static visuals of ICU and non-ICU bed demand and capacity; and (3) an interactive Tableau workbook of hospital demand variables. Identifying code efficiencies reduced a single model runtime from ~100 seconds to 28 seconds. The use of cloud computing reduced simulation runtime from ~20 hours to 15 minutes. Across forecasts, the average MAPEs were 21.6% and 7.1% for ICU and non-ICU bed demand, respectively. By incorporating hospital-level occupancy data, we reduced the average MAPE to 6.5% for ICU bed demand and 3.9% for non-ICU bed demand, indicating improved accuracy. Conclusions: We adapted an ABM and continually improved it during COVID-19 forecasting by optimizing code and computing resources and including real-time hospital-level occupancy data. Planned SEIR model updates for enhanced forecasts include the addition of compartments for undocumented infections and recoveries as well as permission of reinfection from recovered compartments.Funding: NoDisclosures: None

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