Title |
End TB strategy: the need to reduce risk inequalities
|
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Published in |
BMC Infectious Diseases, March 2016
|
DOI | 10.1186/s12879-016-1464-8 |
Pubmed ID | |
Authors |
M. Gabriela M. Gomes, Maurício L. Barreto, Philippe Glaziou, Graham F. Medley, Laura C. Rodrigues, Jacco Wallinga, S. Bertel Squire |
Abstract |
Diseases occur in populations whose individuals differ in essential characteristics, such as exposure to the causative agent, susceptibility given exposure, and infectiousness upon infection in the case of infectious diseases. Concepts developed in demography more than 30 years ago assert that variability between individuals affects substantially the estimation of overall population risk from disease incidence data. Methods that ignore individual heterogeneity tend to underestimate overall risk and lead to overoptimistic expectations for control. Concerned that this phenomenon is frequently overlooked in epidemiology, here we feature its significance for interpreting global data on human tuberculosis and predicting the impact of control measures. We show that population-wide interventions have the greatest impact in populations where all individuals face an equal risk. Lowering variability in risk has great potential to increase the impact of interventions. Reducing inequality, therefore, empowers health interventions, which in turn improves health, further reducing inequality, in a virtuous circle. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | 33% |
France | 1 | 33% |
United States | 1 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 67% |
Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 2% |
United States | 1 | 1% |
Switzerland | 1 | 1% |
Brazil | 1 | 1% |
Unknown | 87 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 19 | 21% |
Researcher | 13 | 14% |
Student > Ph. D. Student | 9 | 10% |
Student > Doctoral Student | 6 | 7% |
Professor | 5 | 5% |
Other | 19 | 21% |
Unknown | 21 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 23 | 25% |
Nursing and Health Professions | 10 | 11% |
Social Sciences | 8 | 9% |
Biochemistry, Genetics and Molecular Biology | 4 | 4% |
Mathematics | 4 | 4% |
Other | 17 | 18% |
Unknown | 26 | 28% |