scholarly journals Inner city residents and health decision-makers: perceptions of health problems and solutions.

1974 ◽  
Vol 64 (6) ◽  
pp. 612-613 ◽  
Author(s):  
R A Kurtz ◽  
H P Chalfant ◽  
K Kaplan
Keyword(s):  
Inner City ◽  
Health Problems ◽  
Decision Makers ◽  
Problems And Solutions ◽  
Health Decision

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.

Revitalizing Human Communities and Reclaiming Biological Communities

2017 ◽  
Author(s):  
William R. Burch ◽  
Gary E. Machlis ◽  
Jo Ellen Force
Keyword(s):  
United States ◽  
Natural Resources ◽  
Ecosystem Model ◽  
The United States ◽  
Decision Makers ◽  
Public And Private ◽  
Integrated Network ◽  
Biological Communities ◽  
Human Ecosystem ◽  
Problems And Solutions

This chapter demonstrates how the Human Ecosystem Model (HEM) offers a unity of understanding with shared concepts, a framework, and a model for resolving complex human ecosystem problems. With it, decision-makers from different organizations—public and private—may coordinate their work with that of local citizens. The emphasis is on the whole system, which combines issues such as trends in crime, housing, education, health, natural resources, and community stability into an integrated network. The chapter illustrates how the framework and model was applied in a major city in the United States: Baltimore, Maryland. The Baltimore story emphasizes that certain universal problems and solutions confront all human societies. The universality of problems and the search for integrated solutions required a framework like the HEM to identify, apply, and store learning.

scholarly journals Development of the ACTIVE framework to describe stakeholder involvement in systematic reviews

2019 ◽  
Vol 24 (4) ◽  
pp. 245-255 ◽  
Author(s):  
Alex Pollock ◽  
Pauline Campbell ◽  
Caroline Struthers ◽  
Anneliese Synnot ◽  
Jack Nunn ◽  
...  
Keyword(s):  
Systematic Review ◽  
Systematic Reviews ◽  
Health Professionals ◽  
Public Involvement ◽  
Review Process ◽  
Data Extraction ◽  
Stakeholder Involvement ◽  
Decision Makers ◽  
Literature Searching ◽  
Health Decision

Objectives Involvement of patients, health professionals, and the wider public (‘stakeholders’) is seen to be beneficial to the quality, relevance and impact of research and may enhance the usefulness and uptake of systematic reviews. However, there is a lack of evidence and resources to guide researchers in how to actively involve stakeholders in systematic reviews. In this paper, we report the development of the ACTIVE framework to describe how stakeholders are involved in systematic reviews. Methods We developed a framework using methods previously described in the development of conceptual frameworks relating to other areas of public involvement, including: literature searching, data extraction, analysis, and categorization. A draft ACTIVE framework was developed and then refined after presentation at a conference workshop, before being applied to a subset of 32 systematic reviews. Data extracted from these systematic reviews, identified in a systematic scoping review, were categorized against pre-defined constructs, including: who was involved, how stakeholders were recruited, the mode of involvement, at what stage there was involvement and the level of control or influence. Results The final ACTIVE framework described whether patients, carers and/or families, and/or other stakeholders (including health professionals, health decision makers and funders) were involved. We defined: recruitment as either open or closed; the approach to involvement as either one-time, continuous or combined; and the method of involvement as either direct or indirect. The stage of involvement in reviews was defined using the Cochrane Ecosystem stages of a review. The level of control or influence was defined according to the roles and activities of stakeholders in the review process, and described as the ACTIVE continuum of involvement. Conclusions The ACTIVE framework provides a structure with which to describe key components of stakeholder involvement within a systematic review, and we have used this to summarize how stakeholders have been involved in a subset of varied systematic reviews. The ACTIVE continuum of involvement provides a new model that uses tasks and roles to detail the level of stakeholder involvement. This work has contributed to the development of learning resources aimed at supporting systematic review authors and editors to involve stakeholders in their systematic reviews. The ACTIVE framework may support the decision-making of systematic review authors in planning how to involve stakeholders in future reviews.

scholarly journals Effectiveness of COVID-19 Vaccines against Delta (B.1.617.2) Variant: A Systematic Review and Meta-Analysis of Clinical Studies

Vaccines ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 23
Author(s):  
Ali Pormohammad ◽  
Mohammad Zarei ◽  
Saied Ghorbani ◽  
Mehdi Mohammadi ◽  
Saeideh Aghayari Sheikh Neshin ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Severe Infection ◽  
Vaccination Rate ◽  
Decision Makers ◽  
Morbidity Rate ◽  
Short Term ◽  
Mortality And Morbidity ◽  
Public Health Decision ◽  
Health Decision

The high transmissibility, mortality, and morbidity rate of the SARS-CoV-2 Delta (B.1.617.2) variant have raised concerns regarding vaccine effectiveness (VE). To address this issue, all publications relevant to the effectiveness of vaccines against the Delta variant were searched in the Web of Science, Scopus, EMBASE, and Medline (via PubMed) databases up to 15 October 2021. A total of 15 studies (36 datasets) were included in the meta-analysis. After the first dose, the VE against the Delta variant for each vaccine was 0.567 (95% CI 0.520–0.613) for Pfizer-BioNTech, 0.72 (95% CI 0.589–0.822) for Moderna, 0.44 (95% CI 0.301–0.588) for AstraZeneca, and 0.138 (95% CI 0.076–0.237) for CoronaVac. Meta-analysis of 2,375,957 vaccinated cases showed that the Pfizer-BioNTech vaccine had the highest VE against the infection after the second dose, at 0.837 (95% CI 0.672–0.928), and third dose, at 0.972 (95% CI 0.96–0.978), as well as the highest VE for the prevention of severe infection or death, at 0.985 (95% CI 0.95–0.99), amongst all COVID-19 vaccines. The short-term effectiveness of vaccines, especially mRNA-based vaccines, for the prevention of the Delta variant infection, hospitalization, severe infection, and death is supported by this study. Limitations include a lack of long-term efficacy data, and under-reporting of COVID-19 infection cases in observational studies, which has the potential to falsely skew VE rates. Overall, this study supports the decisions by public health decision makers to promote the population vaccination rate to control the Delta variant infection and the emergence of further variants.

scholarly journals Prediction of prevalence of type 2 diabetes in Rwanda using the metropolis-hasting sampling

2021 ◽  
Vol 21 (2) ◽  
pp. 702-709
Author(s):  
Angelique Dukunde ◽  
Jean Marie Ntaganda ◽  
Juma Kasozi ◽  
Joseph Nzabanita
Keyword(s):  
Physical Activity ◽  
Mathematical Model ◽  
Type 2 Diabetes ◽  
Monte Carlo ◽  
Transition Matrix ◽  
Decision Makers ◽  
World Health ◽  
Health Decision ◽  
The Masses

In this work, we predict the prevalence of type 2 diabetes among adult Rwandan people. We used the Metropolis-Hasting method that involved calculating the metropolis ratio. The data are those reported by World Health Organiation in 2015. Considering Suffering from diabetes, Overweight, Obesity, Dead and other subject as states of mathematical model, the transition matrix whose elements are probabilities is generated using Metropolis-Hasting sampling. The numerical results show that the prevalence of type 2 diabetes increases from 2.8% in 2015 to reach 12.65% in 2020 and to 22.59% in 2025. Therefore, this indicates the urgent need of prevention by Rwandan health decision makers who have to play their crucial role in encouraging for example physical activity, regular checkups and sensitization of the masses. Keywords: Non communicable diseases; type 2 diabetes; Markov Chain Monte Carlo method; Metropolis-Hasting method; Transition probabilities.rds: 

Health Decision Makers' Perceptions of Program Evaluation Questionnaire

1992 ◽  
Author(s):  
Sharon E. Carpinello ◽  
Dianna L. Newman ◽  
Linnea L. Jatulis
Keyword(s):  
Program Evaluation ◽  
Decision Makers ◽  
Evaluation Questionnaire ◽  
Health Decision

scholarly journals Rigorous surveillance is necessary for high confidence in end-of-outbreak declarations for Ebola and other infectious diseases

2019 ◽  
Vol 374 (1776) ◽  
pp. 20180431 ◽  
Author(s):  
Robin N. Thompson ◽  
Oliver W. Morgan ◽  
Katri Jalava
Keyword(s):  
Infectious Disease ◽  
Disease Outbreaks ◽  
Decision Makers ◽  
World Health ◽  
Theme Issue ◽  
Public Health Decision ◽  
Infectious Disease Outbreaks ◽  
Travel Restrictions ◽  
Health Decision ◽  
Health Organization

The World Health Organization considers an Ebola outbreak to have ended once 42 days have passed since the last possible exposure to a confirmed case. Benefits of a quick end-of-outbreak declaration, such as reductions in trade/travel restrictions, must be balanced against the chance of flare-ups from undetected residual cases. We show how epidemiological modelling can be used to estimate the surveillance level required for decision-makers to be confident that an outbreak is over. Results from a simple model characterizing an Ebola outbreak suggest that a surveillance sensitivity (i.e. case reporting percentage) of 79% is necessary for 95% confidence that an outbreak is over after 42 days without symptomatic cases. With weaker surveillance, unrecognized transmission may still occur: if the surveillance sensitivity is only 40%, then 62 days must be waited for 95% certainty. By quantifying the certainty in end-of-outbreak declarations, public health decision-makers can plan and communicate more effectively.This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This issue is linked with the earlier theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.

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