1. Understanding the impact of disease control: TB epidemiology and the GFATM

2. Questions Routine OR SurveysResearch Size of NotificationsPrivate sect.PrevalenceActive CF the Cure rateVital Reg.Incidence problemDeaths Global Report S. AfricaReview S. Korea Direction NotificationsSent. sitesPrevalenceModelling of changeTr. outcomesIncidence MoroccoChennai S. KoreaWorld Reasons HIV; MDR;Risk factorsHIVDuration dis. for changeDiagnosticsSocial issuesMDR AccessPPM NairobiIndia S. Africa S. Africa Impact ofNotificationsDiagnosisPrevalenceDOTS Control Cure rateDrug supplyIncidenceIPT DeathsQual. control PeruCzech.IndiaCzech.

3. Size/Routine Highest TB rates per capita are in Africa 25 to 49 50 to 99 100 to 299 < 10 10 to 24 300 or more No Estimate per 100 000 population The boundaries and names shown and the designations used on this map do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted lines on maps represent approximate border lines for which there may not yet be full agreement. © WHO 2002

4. Size/OR Table 1. Estimating case detection rates from vital registration data. Red: Statistics South Africa. Blue: TB programme. Errors are fractional errors. 2001Error (%) TB deaths (k)50.920 All deaths (k)451.9 Unknown causes (k)56.2 Deaths due to HIV9.220 Completeness of reporting (%)90.05 Proportion of HIV deaths due to TB15.050 TB deaths (k)66.1 Proportion of cases HIV positive (%)59.010 CFR negative (%)16.050 CFR positive (%)35.050 CFR (%)37.0 Incidence (k)242.9 Notifications (k)192.9 CDR (%)80.011.0 TB deaths = Incidence  Case fatality rate

5. Prevalence surveys: National blue; sub-national red. Kolin Size/Surveys

6. ARTI  50 Civil servants South Korea Size/Research 1

7. Calculating sample sizes Size/Research 2

8. Direction/Routine

9. Direction/OR

10. Decline in TB, Alaska 1950-73 -2 0 1 2 3 4 5 6 195019551960196519701975 Incidence or death rate/10K/year source: Grzybowski Tubercle 1976 deaths 30%/yr t 1/2 = 2.3 yr cases 13%/yr t 1/2 = 5 yr Direction/Surveys

11. Direction/Research TB: elimination by 2050? 0 200 400 600 800 1000 1200 1400 1600 1990200020102020203020402050 Incidence/million/yr Projected incidence 100x bigger than elimination threshold in 2050 GP2: incidence falls 5-6%/yr 2010-2015 Vaccines, drugs and risk factors?

12. Nairobi Reasons/Routine

13. Smoking and TB in Chennai 27k deaths and 16k controls, 1994-1997. 2k TB deaths Gajalakshmi, V., Peto, R., et al. Smoking and mortality from tuberculosis and other diseases in India: retrospective study of 43000 adult male deaths and 35000 controls Lancet (2003) 362 507–515. Smoker Non-smokerOdds TB deaths1454386 3.76 Controls643010058 0.64 OR = 5.9 (4.5) F = 0.79 60% of all TB deaths among men in Chennai are attributable to smoking Reasons/OR

14. Reasons/Surveys Drug Resistance in Retreatment Patients (n = 1 508) SA rates weighted by Province

15. TB incidence among gold miners in SA DDR Reasons/Research 1

16. Smear positive disease in South African gold miners Incidence (%/yr) Prevalence (%) Dis.Duration (yr) HIV-0.48 0.55 1.15 HIV+ 2.870.440.15 Ratio6.01 0.800.13 Corbett et al. 2003 Reasons/Research 2

17. Dynamics of pulmonary TB in Peru 1980-2000 100 120 140 160 180 200 220 19801985199019952000 Pulmonary TB cases/100,000 DOTS 1990 PTB falling at 6%/yr case finding Impact/Routine

18. Impact/OR

19. South Korea Impact/Surveys

20. Decline in prevalence Kolin, Czechoslovakia Men: 20%  10%/yr Women: 26%  21% China Impact/Research

21. The last word… We must eradicate tuberculosis, and we must do it now, … All available resources must be used. Chemotherapy, computers, prophylaxis and prevention, case finding and kindness can be blended in a properly constructed epidemiological model which will tell us exactly where we are going and how fast. Davies, J.C.A. The Eradication of Tuberculosis in Rhodesia DPH, London School of Hygiene and Tropical Medicine, 1966

22. Estimating CDR 1.Assume that the 1997 estimate of CDR is correct so that we know the incidence in 1997. 2.Assume that the trend in total notifications (all forms; DOTS non-DOTS) gives the trend in incidence. 3.Use this trend to work out the incidence of all forms in the year 2004. 4.Assume that the SS+ incidence is 45% of the all-forms incidence for HIV- people; 35% for HIV+ people. 5.Calculate the SS+ incidence 6.Divide the notification rate in DOTS areas by the SS+ incidence to get the SS+ DOTS case detection rate.

23. The Design Effect Suppose we have k clusters with m people in each cluster so that the total sample size is n = km. D = 1 + (m  1)ρ where ρ, the intra-class (or intra-cluster) correlation coefficient, is the ratio of the between-cluster variance s b to the total variance so that where s w is the within-cluster variance. 1.All members of a cluster are identical, sw = 0, r = 1 and D = m. Effective sample size = n/m = k = the number of clusters. 2.Members of each cluster have no particular similarity sb = 0, r = 0, and D = 1. Effective sample size = n = number of people. For example, if each cluster contains m = 10 people and ρ =0.1 then 1 + (m-1)ρ = 1.9. m = 20 people and ρ = 0.2 then 1 + (m – 1)ρ = 4.8 Even a small value of the intra-cluster correlation coefficient, multiplied by the size of the cluster, could lead to a substantial increase in variance and reduction in effective sample size.