Epidemiological Modeling of TB Elimination. David Dowdy, MD PhD Union-NAR Meeting Feb. 25, 2016

Transcription

1 Epidemiological Modeling of TB Elimination David Dowdy, MD PhD Union-NAR Meeting Feb. 25, 2016

2 Objectives Describe the role of modeling in exploring strategies for TB elimination, in both high- and low-burden contexts Describe challenges in modeling TB transmission in the elimination phase Reactivation > transmission Migration and mixing Increasing importance of outbreaks Describe the results of modelling studies that focus on the elimination of TB

3 Background: TB Elimination Definition: <1 case per million per year Action Framework: 8 Priority Actions How close are we?

4 Background: TB Elimination Definition: <1 case per million per year Action Framework: 8 Priority Actions How close are we? 2014: 9,421 cases Elimination: 319 cases/year U.S. Centers for Disease Control and Prevention

5 Background: TB Elimination Definition: <1 case per million per year Action Framework: 8 Priority Actions How close are we? To achieve elimination, we must prevent 29 out of 30 TB cases that currently occur in the United States. 2014: 9,421 cases Elimination: 319 cases/year U.S. Centers for Disease Control and Prevention

6 29 Out of 30: Consider TB incidence in the USA in 2014 fell by 2.2%. About the same rate of decline as seen globally At a 2.2%/year decline, we will achieve elimination in the year Two-thirds of all cases occur in the foreign-born. Zero decline in foreign-born cases since 2012 Preventing all cases except those among people arriving in the past year would still leave us at twice the elimination threshold. Best estimates of the percent of TB cases reflecting recent transmission within U.S. borders: 5-15% Interrupting all TB transmission within the USA would prevent 2-4 out of 30 cases.

7 Transmission Models of TB Dowdy, Dye, Cohen; IJTLD 2013 Commonly used to evaluate impact of TB interventions on future transmission. As the prevalence of TB declines, the rate of infection (1) falls. Capture dynamics that may not be seen in statistical analyses alone.

8 TB Transmission Modeling Example Choose a population you wish to model. Southeast Asia: high TB incidence, low HIV Describe the likely effects of new interventions. Example: new diagnostics shorten time to treatment by 3-4 months Project TB incidence and mortality over time. Including the impact of each intervention

9 Challenges in Modeling TB Elimination Transmission is not the key to elimination. Migration can drive dynamics. Outbreaks and local effects become more important.

10 Interrupting Transmission Elimination At least three existing models of TB elimination exist: Hill A et al (Epidemiol Infect 2012): Modeling TB trends in the USA Dye et al (Annu Rev Public Health 2013): Prospects for global TB elimination Hill P et al (IJTLD 2014): Mass TB treatment to eliminate TB in Kiribati All agree on one thing: Elimination in any reasonable time frame will require preventive therapy on a massive scale. Do we need transmission models? Arguably, can just calculate the number of people infected (by risk group) and estimate the coverage required. Bad news: Likely have to treat people (e.g., elderly foreign-born) for whom the risks of treatment outweigh the benefits.

11 Interrupt transmission Treat 17% of LTBI every year Model of eliminating TB in the USA Interrupting transmission has relatively small impact on the epidemic Can eliminate TB in the US-born (continuing current trends) by 2056 Cannot eliminate TB in the USA by 2060, even with massive treatment of LTBI and 75% reduction of LTBI among FB arrivals

12 Model of eliminating TB globally Interrupting transmission leaves us 100x above elimination threshold To achieve elimination, would need to: Treat 14% of the world s population with LTBI per year (equivalent to treating the entire US population, every year) And interrupt transmission of active disease

13 Model of mass treatment of active TB in Kiribati Detecting 96% of all cases and treating them effectively gets us to 1000x the elimination threshold. Can achieve elimination in 2035 by treating everyone in the population for active TB, every 5 years, with 95% efficacy.

14 Bottom Line If we are seeking to eliminate TB, we must focus on prevention in addition to transmission. And be prepared to do so on a massive scale Do we need transmission models? Arguably, can calculate the number of people infected (by risk group) and estimate the coverage required. Bad news: Likely have to treat people (e.g., elderly foreign-born) for whom the risks of treatment outweigh the benefits. Is this vaccine case an argument we can make for TB elimination?

15 Role of Migration Elimination in low-incidence settings depends on progress globally. Two-thirds of the TB incidence in the USA reflects infection acquired abroad. Migration and mixing are key drivers of TB transmission. Difficult to model: do individuals who are foreign-born/homeless/etc mix exclusively with other people of the same group? Immigrants to the USA are not representative of the home country population. TB incidence in the first year after arrival is already half the expected reactivation rate in home countries. Reflects pre-immigration screening, higher SES, etc. How much with imported TB fall if global TB declines by 50%?

16 Migration and Mixing Shrestha et al; in revision Mixing between hotspots and general population may be a critical driver of TB incidence. The hotspots in low-incidence settings are Latin America, Asia, & Africa. Better understanding of these dynamics is critical if we are to model TB elimination. Though arguably even more important in high-burden settings, where most active TB still represents recent transmission.

17 Outbreaks As TB epidemics approach elimination, they become less predictable. Two outbreaks of 3 cases each would be sufficient to take the entire state of Colorado above the elimination threshold for a year. Traditional models become more difficult to fit and less useful in making projections. Relevant question becomes how do we prevent outbreaks rather than what is the expected number of cases. Resource use also becomes more difficult to justify. Fojo et al, SGIM abstract under review

18 Models: Helpful or Not? Models: Helpful How is TB likely to be different in the elimination phase? What are likely to be the key drivers of future TB epidemics? What is the comparative impact of different interventions? How important are factors like immigration and outbreaks? Can we better understand the role of transmission vs. reactivation? If current trends continue, will TB incidence plateau? Models: Less Helpful When will we reach TB elimination in the USA? If TB funding is cut by $XX million, what will the impact on incidence be? If we implement intervention X, exactly how many cases will we avert? Where is the next outbreak going to occur? How many cases of TB have we averted through TLBTI to date? What is our TB incidence going to be in 2030?

19 TB Modeling as an Iterative Process Knight et al, IJID 2016

20 Summary Elimination of TB is a very ambitious goal. Must avert 29 of every 30 current cases in the USA Modeling of TB elimination involves specific challenges. Smaller contribution of transmission Migration and mixing of populations Larger role of unpredictable outbreaks TB elimination models should be developed collaboratively with public health practitioners. Models are more useful for understanding than for prediction. When put to good use, important insight can be gained.

21 Acknowledgments JHSPH TB Modeling and Translational Epi Group Sourya Shrestha, Todd Fojo, Alice Zwerling, Andrew Azman NYC DOHMH Natalie Stennis, Shama Ahuja CDC TB NEEMA Team Suzanne Marks, Andrew Hill, Nick Menzies, Josh Salomon, Travis Porco, Alex Goodall Other Collaborators Gwen Knight, Nila Dharan, Ted Cohen, Susmita Chatterjee