Poverty-related and neglected diseases – an economic and epidemiological analysis of poverty relatedness and neglect in research and development
Identifieur interne : 001478 ( Main/Exploration ); précédent : 001477; suivant : 001479Poverty-related and neglected diseases – an economic and epidemiological analysis of poverty relatedness and neglect in research and development
Auteurs : Peter Von Philipsborn [Allemagne] ; Fridolin Steinbeis [Allemagne] ; Max E. Bender [Allemagne] ; Sadie Regmi [Allemagne, Royaume-Uni] ; Peter Tinnemann [Allemagne]Source :
- Global Health Action [ 1654-9716 ] ; 2015.
Abstract
Economic growth in low- and middle-income countries (LMIC) has raised interest in how disease burden patterns are related to economic development. Meanwhile, poverty-related diseases are considered to be neglected in terms of research and development (R&D).
Developing intuitive and meaningful metrics to measure how different diseases are related to poverty and neglected in the current R&D system.
We measured how diseases are related to economic development with the income relation factor (IRF), defined by the ratio of disability-adjusted life-years (DALYs) per 100,000 inhabitants in LMIC versus that in high-income countries. We calculated the IRF for 291 diseases and injuries and 67 risk factors included in the Global Burden of Disease Study 2010. We measured neglect in R&D with the neglect factor (NF), defined by the ratio of disease burden in DALYs (as percentage of the total global disease burden) and R&D expenditure (as percentage of total global health-related R&D expenditure) for 26 diseases.
The disease burden varies considerably with the level of economic development, shown by the IRF (median: 1.38; interquartile range (IQR): 0.79–6.3). Comparison of IRFs from 1990 to 2010 highlights general patterns of the global epidemiological transition. The 26 poverty-related diseases included in our analysis of neglect in R&D are responsible for 13.8% of the global disease burden, but receive only 1.34% of global health-related R&D expenditure. Within this group, the NF varies considerably (median: 19; IQR: 6–52).
The IRF is an intuitive and meaningful metric to highlight shifts in global disease burden patterns. A large shortfall exists in global R&D spending for poverty-related and neglected diseases, with strong variations between diseases.
Url:
DOI: 10.3402/gha.v8.25818
PubMed: 25623607
PubMed Central: 4306754
Affiliations:
- Allemagne, Royaume-Uni
- Angleterre, Bavière, Berlin, District de Haute-Bavière, Grand Manchester
- Berlin, Manchester, Munich
- Université de Manchester, Université technique de Munich
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(UAEM), Berlin, Germany</nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea>Universities Allied for Essential Medicines Europe e.V. (UAEM), Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation><affiliation wicri:level="4"><nlm:aff id="AF0005">Institute for Science, Ethics and Innovation, University of Manchester, Manchester, United Kingdom</nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Institute for Science, Ethics and Innovation, University of Manchester, Manchester</wicri:regionArea><placeName><settlement type="city">Manchester</settlement><region type="country">Angleterre</region><region type="région" nuts="1">Grand Manchester</region><settlement type="city">Manchester</settlement></placeName><orgName type="university">Université de Manchester</orgName></affiliation></author><author><name sortKey="Tinnemann, Peter" sort="Tinnemann, Peter" uniqKey="Tinnemann P" first="Peter" last="Tinnemann">Peter Tinnemann</name><affiliation wicri:level="3"><nlm:aff id="AF0004">Institute for Social Medicine, Epidemiology and Health Economics, Charité Universitätsmedizin Berlin, Berlin, Germany</nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea>Institute for Social Medicine, Epidemiology and Health Economics, Charité Universitätsmedizin Berlin, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author></analytic><series><title level="j">Global Health Action</title><idno type="ISSN">1654-9716</idno><idno type="eISSN">1654-9880</idno><imprint><date when="2015">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec id="st1"><title>Background</title><p>Economic growth in low- and middle-income countries (LMIC) has raised interest in how disease burden patterns are related to economic development. Meanwhile, poverty-related diseases are considered to be neglected in terms of research and development (R&D).</p></sec><sec id="st2"><title>Objectives</title><p>Developing intuitive and meaningful metrics to measure how different diseases are related to poverty and neglected in the current R&D system.</p></sec><sec id="st3"><title>Design</title><p>We measured how diseases are related to economic development with the income relation factor (IRF), defined by the ratio of disability-adjusted life-years (DALYs) per 100,000 inhabitants in LMIC versus that in high-income countries. We calculated the IRF for 291 diseases and injuries and 67 risk factors included in the Global Burden of Disease Study 2010. We measured neglect in R&D with the neglect factor (NF), defined by the ratio of disease burden in DALYs (as percentage of the total global disease burden) and R&D expenditure (as percentage of total global health-related R&D expenditure) for 26 diseases.</p></sec><sec id="st4"><title>Results</title><p>The disease burden varies considerably with the level of economic development, shown by the IRF (median: 1.38; interquartile range (IQR): 0.79–6.3). Comparison of IRFs from 1990 to 2010 highlights general patterns of the global epidemiological transition. The 26 poverty-related diseases included in our analysis of neglect in R&D are responsible for 13.8% of the global disease burden, but receive only 1.34% of global health-related R&D expenditure. Within this group, the NF varies considerably (median: 19; IQR: 6–52).</p></sec><sec id="st5"><title>Conclusions</title><p>The IRF is an intuitive and meaningful metric to highlight shifts in global disease burden patterns. A large shortfall exists in global R&D spending for poverty-related and neglected diseases, with strong variations between diseases.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Jamison, Dt" uniqKey="Jamison D">DT Jamison</name></author><author><name sortKey="Summers, Lh" uniqKey="Summers L">LH Summers</name></author><author><name sortKey="Alleyne, G" uniqKey="Alleyne G">G Alleyne</name></author><author><name sortKey="Arrow, Kj" uniqKey="Arrow K">KJ Arrow</name></author><author><name sortKey="Berkley, S" uniqKey="Berkley S">S Berkley</name></author><author><name sortKey="Binagwaho, A" uniqKey="Binagwaho A">A Binagwaho</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Remais, Jv" uniqKey="Remais J">JV Remais</name></author><author><name sortKey="Zeng, G" uniqKey="Zeng G">G Zeng</name></author><author><name sortKey="Li, G" uniqKey="Li G">G Li</name></author><author><name sortKey="Tian, L" 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uniqKey="Blum J">J Blum</name></author><author><name sortKey="Neumayr, Al" uniqKey="Neumayr A">AL Neumayr</name></author><author><name sortKey="Keiser, J" uniqKey="Keiser J">J Keiser</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hotez, Pj" uniqKey="Hotez P">PJ Hotez</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Cohen, J" uniqKey="Cohen J">J Cohen</name></author><author><name sortKey="Dibner, Ms" uniqKey="Dibner M">MS Dibner</name></author><author><name sortKey="Wilson, A" uniqKey="Wilson A">A Wilson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Viergever, Rf" uniqKey="Viergever R">RF Viergever</name></author><author><name sortKey="Terry, Rf" uniqKey="Terry R">RF Terry</name></author><author><name sortKey="Karam, G" uniqKey="Karam G">G Karam</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>Allemagne</li><li>Royaume-Uni</li></country><region><li>Angleterre</li><li>Bavière</li><li>Berlin</li><li>District de Haute-Bavière</li><li>Grand Manchester</li></region><settlement><li>Berlin</li><li>Manchester</li><li>Munich</li></settlement><orgName><li>Université de Manchester</li><li>Université technique de Munich</li></orgName></list><tree><country name="Allemagne"><region name="Bavière"><name sortKey="Von Philipsborn, Peter" sort="Von Philipsborn, Peter" uniqKey="Von Philipsborn P" first="Peter" last="Von Philipsborn">Peter Von Philipsborn</name></region><name sortKey="Bender, Max E" sort="Bender, Max E" uniqKey="Bender M" first="Max E." last="Bender">Max E. Bender</name><name sortKey="Bender, Max E" sort="Bender, Max E" uniqKey="Bender M" first="Max E." last="Bender">Max E. Bender</name><name sortKey="Regmi, Sadie" sort="Regmi, Sadie" uniqKey="Regmi S" first="Sadie" last="Regmi">Sadie Regmi</name><name sortKey="Steinbeis, Fridolin" sort="Steinbeis, Fridolin" uniqKey="Steinbeis F" first="Fridolin" last="Steinbeis">Fridolin Steinbeis</name><name sortKey="Steinbeis, Fridolin" sort="Steinbeis, Fridolin" uniqKey="Steinbeis F" first="Fridolin" last="Steinbeis">Fridolin Steinbeis</name><name sortKey="Tinnemann, Peter" sort="Tinnemann, Peter" uniqKey="Tinnemann P" first="Peter" last="Tinnemann">Peter Tinnemann</name><name sortKey="Von Philipsborn, Peter" sort="Von Philipsborn, Peter" uniqKey="Von Philipsborn P" first="Peter" last="Von Philipsborn">Peter Von Philipsborn</name></country><country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Regmi, Sadie" sort="Regmi, Sadie" uniqKey="Regmi S" first="Sadie" last="Regmi">Sadie Regmi</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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