TY - JOUR
T1 - Modelling the social and structural determinants of tuberculosis
T2 - Opportunities and challenges
AU - Pedrazzoli, D.
AU - Boccia, D.
AU - Dodd, P. J.
AU - Lönnroth, K.
AU - Dowdy, D. W.
AU - Siroka, A.
AU - Kimerling, M. E.
AU - White, R. G.
AU - Houben, R. M.G.J.
N1 - Funding Information:
This work was supported by the Bill and Melinda Gates Foundation through the TB Modelling and Analysis Consortium (TB MAC) grant (OPP1084276). The authors thank all the participants at the TB MAC 7 Meeting. Conflicts of interest: none declared.
Publisher Copyright:
© 2017 Pedrazzoli et al.
PY - 2017/9/1
Y1 - 2017/9/1
N2 - 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.
AB - 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.
KW - Mathematical modelling
KW - Social determinants
KW - Tuberculosis
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U2 - 10.5588/ijtld.16.0906
DO - 10.5588/ijtld.16.0906
M3 - Review article
C2 - 28826444
AN - SCOPUS:85028088827
SN - 1027-3719
VL - 21
SP - 957
EP - 964
JO - International Journal of Tuberculosis and Lung Disease
JF - International Journal of Tuberculosis and Lung Disease
IS - 9
ER -