Modelling the social and structural determinants of tuberculosis: opportunities and challenges

被引:30
|
作者
Pedrazzoli, D. [1 ,2 ,3 ]
Boccia, D. [3 ]
Dodd, P. J. [4 ]
Lonnroth, K. [5 ,6 ]
Dowdy, D. W. [7 ]
Siroka, A. [5 ]
Kimerling, M. E. [8 ]
White, R. G. [1 ,2 ,3 ]
Houben, R. M. G. J. [1 ,2 ,3 ]
机构
[1] London Sch Hyg & Trop Med, TB Ctr, TB Modelling Grp, London, England
[2] London Sch Hyg & Trop Med, Ctr Math Modelling Infect Dis, London, England
[3] London Sch Hyg & Trop Med, Dept Infect Dis Epidemiol, Keppel St, London WC1E 7HT, England
[4] Univ Sheffield, Sch Hlth & Related Res, Hlth Econ & Decis Sci, Sheffield, S Yorkshire, England
[5] WHO, Global TB Programme, Geneva, Switzerland
[6] Karolinska Inst, Dept Publ Hlth Sci, Stockholm, Sweden
[7] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD USA
[8] TB Fdn, KNCV, The Hague, Netherlands
关键词
mathematical modelling; tuberculosis; social determinants; RISK; METAANALYSIS; EPIDEMICS; TRENDS; HIV;
D O I
10.5588/ijtld.16.0906
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
INTRODUCTION: Despite the close link between tuberculosis (TB) and poverty, most mathematical models of TB have not addressed underlying social and structural determinants. OBJECTIVE: To review studies employing mathematical modelling to evaluate the epidemiological impact of the structural determinants of TB. METHODS: We systematically searched PubMed and personal libraries to identify eligible articles. We extracted data on the modelling techniques employed, research question, types of structural determinants modelled and setting. RESULTS: From 232 records identified, we included eight articles published between 2008 and 2015; six employed population-based dynamic TB transmission models and two non-dynamic analytic models. Seven studies focused on proximal TB determinants (four on nutritional status, one on wealth, one on indoor air pollution, and one examined overcrowding, socioeconomic and nutritional status), and one focused on macro-economic influences. CONCLUSIONS: Few modelling studies have attempted to evaluate structural determinants of TB, resulting in key knowledge gaps. Despite the challenges of modelling such a complex system, models must broaden their scope to remain useful for policy making. Given the intersectoral nature of the interrelations between structural determinants and TB outcomes, this work will require multidisciplinary collaborations. A useful starting point would be to focus on developing relatively simple models that can strengthen our knowledge regarding the potential effect of the structural determinants on TB outcomes.
引用
收藏
页码:957 / 964
页数:8
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