Jason Andrews, MD, SM, DTM&H Division of Infectious Diseases Massachusetts General Hospital

1. Intensified case finding in the era of new diagnostics: what is the impact? Jason Andrews, MD, SM, DTM&H Division of Infectious Diseases Massachusetts General Hospital Harvard Medical School International AIDS Society July 2, 2013

2. Introduction: Active Case Finding (ACF) • There are good data on yieldof ACF for TB via community-based case finding or household contact investigations • Meta-analysis of 27 studies: 4.5% HH contacts had active TB • Shapiro et al. found at least one TB case in 19% of HHs where an index case had been found and 1% of random households visited in South Africa • Fewer data on the individual level clinical benefits of early case detection. • Even more limited evidence base (DETECTB, ZAMSTAR) on population level epidemiologic impact of ACF interventions Morrison et al., Lancet Infect Dis 2008 Shapiro et al., AJRCCM 2012

3. What can mathematical models tell us about the benefits of active case finding for TB? Not much… in quantitative terms. Limitations in understanding of: • Infectiousness over time • Duration of subclinical tuberculosis • Role of social contact structure

4. Overview • Explain critical assumptions and limitations of TB diagnostic models • How these assumptions impact projections for community-based ACF and household contact investigations • What we need to make better projections

9. Examining these assumptions:impact on ACF

10. Active CF Passive CF Dowdy DW, Basu S, Andrews JR. Am J Resp Crit Care Med, 2012

11. Model and Results • If individuals are asymptomatic (“subclinical”, and only 0.25x as infectious) for half of their duration of TB: - 20% increase in passive diagnosis would reduce TB incidence by 11% over 10 years - ACF targeted at 5% of population would reduce TB incidence by 16% over 10 years • As duration/infectiousness subclinical period increases, efficacy of passive case detection decreases • ACF needed if much of transmission occurs during a subclinical period

12. ? ? Dowdy DW, Basu S, Andrews JR. Am J Resp Crit Care Med, 2012

13. Examining these assumptions:household contact investigations

14. Household Susceptible Exposed Infectious

15. Household Susceptible Exposed Infectious

16. Household Susceptible Exposed Infectious

17. Household Susceptible Exposed Infectious

18. Household Susceptible Exposed Infectious

19. Household Contacts • Created a simple model, governed by ordinary differential equations, with two levels of transmission: within and between households • Calibrated it to TB prevalence of 170/100,000 • Varied proportion of TB transmitted within the household versus within the community** • Projected the impact of: 1) HH contact investigations for active TB; 2) HH contact investigations + LTBI treatment Assumed 100% coverage of intervention and “perfect” sensitivity of diagnostic testing

20. Cape Town

21. Conclusions • We have poor data on role of subclinical TB in transmission, which is critical to projecting the impact of passive and active case finding approaches • Epidemiologic impact of household contact investigations is somewhat attenuated due to mutual contacts between the index and secondary case • Data on within-household versus between- household transmission could improve quantitative projections on contact investigation interventions

22. Acknowledgements Robin Wood, FCP(SA), DSc – University of Cape Town Rochelle Walensky, MD, MPH – MGH/Harvard David Dowdy, MD, PhD – Johns Hopkins Sanjay Basu, MD, PhD – Stanford Megan Murray, MD, ScD - Harvard