The Global Alliance for Chronic Diseases
Bibliographic record
Abstract
Approximately 35 million people will die this year from chronic, noncommunicable diseases (CNCDs) worldwide ([ 1 ][1], [ 2 ][2]). CNCDs include cardiovascular disease and stroke, cancer, diabetes, and chronic respiratory diseases. CNCDs account for 60% of all deaths worldwide, of which 80% occur in low- and middle-income countries (LMICs) ([ 3 ][3]). Yet, until now there has been no coordinated effort by major global health research councils to address these specific needs. To this end, we announce a new global health initiative, the Global Alliance for Chronic Diseases (GACD). The first alliance of its kind among government health research councils, the GACD was launched on 15 June 2009 in Seattle, Washington, coincident with the meeting of Heads of International Biomedical Research Organizations. The GACD has a global reach, bringing together an initial formative group of six major national health research councils. These agencies together represent about 80% of all public research funding in the world. Member agencies are Australia's National Health and Medical Research Council; the Canadian Institutes of Health Research; the Chinese Academy of Medical Sciences; the U.K. Medical Research Council; and the U.S. National Institutes of Health, specifically its National Heart, Lung, and Blood Institute and Fogarty International Center. In addition, the Indian Council of Medical Research has been invited to be a Member agency of the Alliance. ![Figure][4] Allies. Global Alliance for Chronic Diseases signatories make the Alliance official [back row, left to right: Depei Liu (China), Warwick Anderson (Australia), Abdallah Daar (University of Toronto), Stig Pramming (Oxford Health Alliance), and Leszek Borysiewicz (United Kingdom); front row, left to right: Elizabeth Nabel (United States) and Alain Beaudet (Canada)]. CREDIT: KEVIN P. CASEY FOR THE GLOBAL ALLIANCE FOR CHRONIC DISEASES The GACD intends to coordinate research activities that address the prevention and treatment of chronic diseases on a global scale ([ 2 ][2]). It will collectively seek to identify common approaches to develop the evidence base needed to guide policy, develop and share best practices for fighting chronic diseases, and foster a sustainable and significant reduction of illness, disability, and death around the world. A significant focus is on the CNCDs in LMICs and among low-income and indigenous populations of the more developed countries to support collaborative, coordinated research on low-cost interventions and to build capacity in research, training, and healthcare delivery. This initial group will expand to involve other research funders, including philanthropic foundations, from around the world with an interest in the Alliance's agenda. Industry has an important role in solving some of these problems, ensuring the public-private aspect of this venture. The World Health Organization (WHO) has joined in an Observer status and, in addition to the Grand Challenges priorities ([ 2 ][2]), GACD will consider the WHO 2008–2013 Action Plan for the Prevention and Control of Noncommunicable Diseases in setting priorities ([ 4 ][5]). The following priorities have been proposed by some GACD founding members, but exact research priorities await further discussion and will develop as the Alliance evolves: prevention of cardiovascular diseases; public health measures for the control of diabetes and obesity; characterization, quantification of risk factors (tobacco and environmental pollution), and development of control measures for chronic obstructive airways disease, cancer, cardiovascular disease and other disorders; and implementation research of interventions to address these and other priorities. A future Alliance research priority is likely to be in the area of mental health. The creation of the GACD brings to fruition a global commitment to urgently increase the resources and attention to CNCDs. With concerted action, many millions of premature deaths can be averted in the decades ahead. 1. [↵][6]”The maladies of affluence,” The Economist (11 August 2007). 2. [↵][7]1. A. S. Daar 2. et al. , Nature 450, 494 (2007). [OpenUrl][8][CrossRef][9][PubMed][10][Web of Science][11] 3. [↵][12]1. A. D. Lopez 2. et al ., Global Burden of Disease and Risk Factors (Oxford Univ. Press and World Bank, Washington, DC, 2006). 4. [↵][13]World Health Organization, 2008–2013 Action Plan for the Global Strategy for the Prevention and Control of Noncommunicable Diseases ([www.who.int/nmh/Actionplan-PC-NCD-2008.pdf][14]). [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: pending:yes [5]: #ref-4 [6]: #xref-ref-1-1 View reference 1 in text [7]: #xref-ref-2-1 View reference 2 in text [8]: {openurl}?query=rft.jtitle%253DNature%26rft.stitle%253DNature%26rft.aulast%253DDaar%26rft.auinit1%253DA.%2BS.%26rft.volume%253D450%26rft.issue%253D7169%26rft.spage%253D494%26rft.epage%253D496%26rft.atitle%253DGrand%2Bchallenges%2Bin%2Bchronic%2Bnon-communicable%2Bdiseases.%26rft_id%253Dinfo%253Adoi%252F10.1038%252F450494a%26rft_id%253Dinfo%253Apmid%252F18033288%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [9]: /lookup/external-ref?access_num=10.1038/450494a&link_type=DOI [10]: /lookup/external-ref?access_num=18033288&link_type=MED&atom=%2Fsci%2F324%2F5935%2F1642.atom [11]: /lookup/external-ref?access_num=000251158500032&link_type=ISI [12]: #xref-ref-3-1 View reference 3 in text [13]: #xref-ref-4-1 View reference 4 in text [14]: http://www.who.int/nmh/Actionplan-PC-NCD-2008.pdf
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.181 | 0.154 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".