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

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

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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. Introduction: Active Case Finding (ACF). - PowerPoint PPT Presentation

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

Page 1: Jason Andrews, MD, SM, DTM&H Division of Infectious Diseases   Massachusetts General Hospital

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

Harvard Medical School

International AIDS SocietyJuly 2, 2013

Intensified case finding in the era of new diagnostics: what is the impact?

Page 2: Jason Andrews, MD, SM, DTM&H Division of Infectious Diseases   Massachusetts General Hospital

Introduction: Active Case Finding (ACF)

• There are good data on yield of 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

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What can mathematical models tell us about the benefits of active case finding for TB?

Not much… in quantitative terms.

Limitations in understanding of:1.Infectiousness over time2.Duration of subclinical tuberculosis3.Role of social contact structure

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Overview

1. Explain critical assumptions and limitations of TB diagnostic models

2. How these assumptions impact projections for community-based ACF and household contact investigations

3. What we need to make better projections

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Examining these assumptions:impact on ACF

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

Passive CFActive CF

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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

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

?

?

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Examining these assumptions:household contact investigations

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Household

InfectiousExposedSusceptible

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Household

InfectiousExposedSusceptible

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Household

InfectiousExposedSusceptible

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Household

InfectiousExposedSusceptible

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Household

InfectiousExposedSusceptible

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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

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0%

10%

20%

30%

40%

50%Reduction in TB Prevalence over 10 years

Screening Contacts Screening + LTBI Treatment

Percentage of all TB transmitted within Household

Redu

ction

in T

B Pr

eval

ence

20% 40%0%

Cape Town

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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

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Acknowledgements

Robin Wood, FCP(SA), DSc – University of Cape Town

Rochelle Walensky, MD, MPH – MGH/HarvardDavid Dowdy, MD, PhD – Johns HopkinsSanjay Basu, MD, PhD – StanfordMegan Murray, MD, ScD - Harvard