Missing and accounted for: gaps and areas of wealth in the public health review literature

<p>Abstract</p> <p>Background</p> <p>High-quality review evidence is useful for informing and influencing public health policy and practice decisions. However, certain topic areas lack representation in terms of the quantity and quality of review literature available. The objectives of this paper are to identify the quantity, as well as quality, of review-level evidence available on the effectiveness of public health interventions for public health decision makers.</p> <p>Methods</p> <p>Searches conducted on <url>http://www.health-evidence.ca</url> produced an inventory of public health review literature in 21 topic areas. Gaps and areas of wealth in the review literature, as well as the proportion of reviews rated methodologically strong, moderate, or weak were identified. The top 10 topic areas of interest for registered users and visitors of <url>http://www.health-evidence.ca</url> were extracted from user profile data and Google Analytics.</p> <p>Results</p> <p>Registered users' top three interests included: 1) healthy communities, 2) chronic diseases, and 3) nutrition. The top three preferences for visitors included: 1) chronic diseases, 2) physical activity, and 3) addiction/substance use. All of the topic areas with many (301+) available reviews were of interest to registered users and/or visitors (mental health, physical activity, addiction/substance use, adolescent health, child health, nutrition, adult health, and chronic diseases). Conversely, the majority of registered users and/or visitors did not have preference for topic areas with few (≤ 150) available reviews (food safety and inspection, dental health, environmental health) with the exception of social determinants of health and healthy communities. Across registered users' and visitors' topic areas of preference, 80.2% of the reviews were of well-done methodological quality, with 43.5% of reviews having a strong quality rating and 36.7% a moderate review quality rating.</p> <p>Conclusions</p> <p>In topic areas in which many reviews are available, higher level syntheses are needed to guide policy and practice. For other topic areas with few reviews, it is necessary to determine whether primary study evidence exists, or is needed, so that reviews can be conducted in the future. Considering that less than half of the reviews available on <url>http://www.health-evidence.ca</url> are of strong methodological quality, the quality of the review-level evidence needs to improve across the range of public health topic areas.</p

A knowledge management tool for public health: health-evidence.ca

<p>Abstract</p> <p>Background</p> <p>The ultimate goal of knowledge translation and exchange (KTE) activities is to facilitate incorporation of research knowledge into program and policy development decision making. Evidence-informed decision making involves translation of the best available evidence from a systematically collected, appraised, and analyzed body of knowledge. Knowledge management (KM) is emerging as a key factor contributing to the realization of evidence-informed public health decision making. The goal of health-evidence.ca is to promote evidence-informed public health decision making through facilitation of decision maker access to, retrieval, and use of the best available synthesized research evidence evaluating the effectiveness of public health interventions.</p> <p>Methods</p> <p>The systematic reviews that populate health evidence.ca are identified through an extensive search (1985-present) of 7 electronic databases: MEDLINE, EMBASE, CINAHL, PsycINFO, Sociological Abstracts, BIOSIS, and SportDiscus; handsearching of over 20 journals; and reference list searches of all relevant reviews. Reviews are assessed for relevance and quality by two independent reviewers. Commonly-used public health terms are used to assign key words to each review, and project staff members compose short summaries highlighting results and implications for policy and practice.</p> <p>Results</p> <p>As of June 2010, there are 1913 reviews in the health-evidence.ca registry in 21 public health and health promotion topic areas. Of these, 78% have been assessed as being of strong or moderate methodological quality. Health-evidence.ca receives approximately 35,000 visits per year, 20,596 of which are unique visitors, representing approximately 100 visits per day. Just under half of all visitors return to the site, with the average user spending six minutes and visiting seven pages per visit. Public health nurses, program managers, health promotion workers, researchers, and program coordinators are among the largest groups of registered users, followed by librarians, dieticians, medical officers of health, and nutritionists. The majority of users (67%) access the website from direct traffic (e.g., have the health-evidence.ca webpage bookmarked, or type it directly into their browser).</p> <p>Conclusions</p> <p>Consistent use of health-evidence.ca and particularly the searching for reviews that correspond with current public health priorities illustrates that health-evidence.ca may be playing an important role in achieving evidence-informed public health decision making.</p

Rapid Review: What is known about stigmatization related to COVID-19 in Canada?

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Combining Spectral Data and a DSM from UAS-Images for Improved Classification of Non-Submerged Aquatic Vegetation

Monitoring of aquatic vegetation is an important component in the assessment of freshwater ecosystems. Remote sensing with unmanned aircraft systems (UASs) can provide sub-decimetre-resolution aerial images and is a useful tool for detailed vegetation mapping. In a previous study, non-submerged aquatic vegetation was successfully mapped using automated classification of spectral and textural features from a true-colour UAS-orthoimage with 5-cm pixels. In the present study, height data from a digital surface model (DSM) created from overlapping UAS-images has been incorporated together with the spectral and textural features from the UAS-orthoimage to test if classification accuracy can be improved further. We studied two levels of thematic detail: (a) Growth forms including the classes of water, nymphaeid, and helophyte; and (b) dominant taxa including seven vegetation classes. We hypothesized that the incorporation of height data together with spectral and textural features would increase classification accuracy as compared to using spectral and textural features alone, at both levels of thematic detail. We tested our hypothesis at five test sites (100 m × 100 m each) with varying vegetation complexity and image quality using automated object-based image analysis in combination with Random Forest classification. Overall accuracy at each of the five test sites ranged from 78% to 87% at the growth-form level and from 66% to 85% at the dominant-taxon level. In comparison to using spectral and textural features alone, the inclusion of height data increased the overall accuracy significantly by 4%–21% for growth-forms and 3%–30% for dominant taxa. The biggest improvement gained by adding height data was observed at the test site with the most complex vegetation. Height data derived from UAS-images has a large potential to efficiently increase the accuracy of automated classification of non-submerged aquatic vegetation, indicating good possibilities for operative mapping

Comparison of Manual Mapping and Automated Object-Based Image Analysis of Non-Submerged Aquatic Vegetation from Very-High-Resolution UAS Images

Aquatic vegetation has important ecological and regulatory functions and should be monitored in order to detect ecosystem changes. Field data collection is often costly and time-consuming; remote sensing with unmanned aircraft systems (UASs) provides aerial images with sub-decimetre resolution and offers a potential data source for vegetation mapping. In a manual mapping approach, UAS true-colour images with 5-cm-resolution pixels allowed for the identification of non-submerged aquatic vegetation at the species level. However, manual mapping is labour-intensive, and while automated classification methods are available, they have rarely been evaluated for aquatic vegetation, particularly at the scale of individual vegetation stands. We evaluated classification accuracy and time-efficiency for mapping non-submerged aquatic vegetation at three levels of detail at five test sites (100 m × 100 m) differing in vegetation complexity. We used object-based image analysis and tested two classification methods (threshold classification and Random Forest) using eCognition®. The automated classification results were compared to results from manual mapping. Using threshold classification, overall accuracy at the five test sites ranged from 93% to 99% for the water-versus-vegetation level and from 62% to 90% for the growth-form level. Using Random Forest classification, overall accuracy ranged from 56% to 94% for the growth-form level and from 52% to 75% for the dominant-taxon level. Overall classification accuracy decreased with increasing vegetation complexity. In test sites with more complex vegetation, automated classification was more time-efficient than manual mapping. This study demonstrated that automated classification of non-submerged aquatic vegetation from true-colour UAS images was feasible, indicating good potential for operative mapping of aquatic vegetation. When choosing the preferred mapping method (manual versus automated) the desired level of thematic detail and the required accuracy for the mapping task needs to be considered

The National Collaborating Centre for Methods and Tools (NCCMT): Supporting evidence-informed decision-making in public health in Canada

The National Collaborating Centre for Methods and Tools (NCCMT) is part of a network of six National Collaborating Centres for Public Health (NCC) created in 2005 by the federal government following the severe acute respiratory syndrome (SARS) epidemic to strengthen public health infrastructure in Canada. The work of the NCCMT, to support evidence-informed decision-making (EIDM) in public health in Canada, is accomplished by curating trustworthy evidence, building competence to use evidence and accelerating change in EIDM. Ongoing engagement with its target audiences ensures NCCMT’s relevance and ability to respond to evolving public health needs. This has been particularly critical during the coronavirus disease 2019 (COVID-19) pandemic, which saw NCCMT pivot its activities to support the public health response by conducting rapid reviews on priority questions identified by decision-makers from federal to local levels as well as create and maintain a national repository of in-progress or completed syntheses. These efforts, along with partnering with the COVID-19 Evidence Network to support Decision-Making (COVID-END), sought to reduce duplication, increase coordination of synthesis efforts and support decision-makers to use the best available evidence in decision-making. Data from website statistics illustrate the successful uptake of these initiatives across Canada and internationally

Le Centre de collaboration nationale des méthodes et outils (CCNMO) : soutenir la prise de décisions fondée sur des données probantes en santé publique au Canada

Le Centre de collaboration nationale des méthodes et outils (CCNMO) fait partie d’un réseau de six centres de collaboration nationale en santé publique (CCN) créé en 2005 par le gouvernement fédéral à la suite de l’épidémie de syndrome respiratoire aigu sévère (SRAS) afin de renforcer l’infrastructure de la santé publique au Canada. Le travail du CCNMO, qui vise à soutenir la prise de décisions fondée sur des données probantes dans le domaine de la santé publique au Canada, est accompli par l’organisation des données probantes dignes de confiance, le renforcement des compétences dans l’utilisation des données probantes, et l’accélération du changement dans la prise de décisions fondée sur des données probantes est décrit. La consultation permanente auprès de ses publics cibles garantit la pertinence du CCNMO et sa capacité à répondre à l’évolution des besoins en matière de santé publique. Cela s’est avéré particulièrement crucial lors de la pandémie de maladie à coronavirus 2019 (COVID-19). Le CCNMO a alors modifié la direction de ses activités pour soutenir l’intervention de la santé publique en effectuant des revues rapides sur les questions prioritaires identifiées par les décideurs, à l’échelle fédérale ou à l’échelle locale, ainsi qu’en créant et en maintenant un répertoire national de synthèses en cours ou terminées. Ces efforts, ainsi que le partenariat avec le COVID-19 Evidence Network to support Decision-Making (COVID-END), visaient à réduire les doublons, à accroître la coordination des efforts de synthèse et à aider les décideurs à utiliser les meilleures données probantes dont on dispose dans la prise de décisions. Les données tirées des statistiques du site Web illustrent le succès de ces initiatives au Canada et à l’étranger