1 Introducing risk inequality metrics in tuberculosis policy 2 development 3 M. Gabriela M. Gomes1,2*, Juliane F. Oliveira2, Adelmo Bertolde3, Diepreye 4 Ayabina1, Tuan Anh Nguyen4, Ethel L. Maciel5, Raquel Duarte6, Binh Hoa Nguyen4, 5 Priya B. Shete7, Christian Lienhardt8,9 6 1Liverpool School of Tropical Medicine, Liverpool L3 5QA, United Kingdom. 7 2CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, 8 Universidade do Porto, 4485-661 Vairão, Portugal. 9 3Departamento de Estatística, Universidade Federal do Espírito Santo, Vitória, 10 Espírito Santo 29075-910, Brazil. 11 4National Lung Hospital, Hanoi 10000, Vietnam. 12 5Laboratório de Epidemiologia, Universidade Federal do Espírito Santo, Vitória, 13 Espírito Santo 29047-105, Brazil. 14 6Faculdade de Medicina, and EPIUnit, Instituto de Saúde Pública, Universidade do 15 Porto, 4050-091 Porto, Portugal. 16 7Division of Pulmonary and Critical Care Medicine, University of California San 17 Francisco, 94110 San Francisco, USA. 18 8Global TB Programme, World Health Organization, 1211 Geneva 27, Switzerland. 19 9Unité Mixte Internationale TransVIHMI (UMI 233 IRD – U1175 INSERM – 20 Université de Montpellier), Institut de Recherche pour le Développement (IRD), 21 34394 Montpellier, France. 22 23 * Correspondence and requests for materials should be addresses to M.G.M.G. (email: 24
[email protected]). 25 1 26 ABSTRACT 27 Global stakeholders including the World Health Organization rely on predictive 28 models for developing strategies and setting targets for tuberculosis care and control 29 programs. Failure to account for variation in individual risk leads to substantial biases 30 that impair data interpretation and policy decisions. Anticipated impediments to 31 estimating heterogeneity for each parameter are discouraging despite considerable 32 technical progress in recent years.