1. Four indirect measures of TB incidence
Incidence, prevalence, deaths derived by rearranging 4 equations

2. From infection prevalence
From disease prevalence
ESTIMATING TB
INCIDENCE
300
300
250
incidence
250
falling
200
200
b > 50
incidence
incidence
ss+/100,000
150
incidence
ss+/100,000
steady
150
100
b = 50
100
weighted duration
illness = 2y 50 50
ss+/- HIV+/- DOTS+/- 1 2 3 4 5 6
200
400
600
ARI (%/year)
prevalence ss+/100,000
From case notifications
From HIV prevalence
300
300
250
250
200
200
incidence
ss+/100,000
ss+/100,000
150
incidence
150
100
100
no HIV 50
proportion detected = 0.8 50 50
100
150
200
250
0.1
0.2
0.3
0.4
notification ss+/100,000
prevalence HIV/100,000

3. “Proportion detected”: guess from quality of surveillance system e. g
“Proportion detected”: guess from quality of surveillance system e.g. USA probably detects about 95% of cases
More objective e.g. % health units reporting in any year
Beware circular arguments
Method 1 weak with poor surveillance, but strong M&S is the ultimate goal

4. Disease prevalence from population surveys e. g
Disease prevalence from population surveys e.g. Philippines, China, Cambodia
Duration: time span of the condition measured in prevalence survey e.g. ss+ disease
Duration from e.g. patients and physicians asked about reporting and treatment delays (often underestimated)

5. Estimating mean duration: Egypt
Proportion ss+ cases treated
DOTS
non-DOTS 0.5
untreated 0.1
Estimated ss+ durations (years):
DOTS 1.0
non-DOTS 1.5
untreated 2.0

6. Prevalence vs incidence: Korean civil servants Tubercle and Lung Disease 76, 534 (1995)
Prevalence PTB /100K
Incidence PTB /100K/yr
Estimated duration = 241/84 = 2.9 years (bigger ratio for older age groups)

8. Estimating incidence from prevalence: Cambodia
prevalence ss /100K in 2002
incidence DOTS (case notification rate) 141/100K in 2002
duration DOTS (questionnaire survey) 1 year
duration nonDOTS (no treatment) 2 years
Therefore:
incidence ss+ nonDOTS 64/100K
total incidence (DOTS + nonDOTS) 205/100K in 2002
NB: usually wide range on estimates

9. Styblo ratio: 1% ARI to 50 ss+/100,000 population (range 40-60)
Accuracy of ARI from tuberculin surveys?
1:50 breaks down when TB incidence not stable (gets bigger in decline), and in presence of HIV

10. Origin of Styblo’s rule Bull IUAT vol 60, 1985

12. Accuracy of deaths from vital registration?
Case fatality more accurately measured from observed cohorts (but fate of defaulters, transfers?)
CFR less accurately from unseen patients, whether treated or untreated

13. Estimating case fatality rate: Egypt
Proportion ss+ cases treated
DOTS
non-DOTS 0.5
untreated 0.1
Estimated case fatality ss+ (years):
DOTS 0.1
non-DOTS 0.3
untreated 0.7

14. Estimating proportion of TB patients infected with HIV
T = AR/[1+A(R-1)]
T = proportion TB patients infected with HIV
A = proportion adults infected with HIV
R = incidence rate ratio (TB incidence in HIV+/TB incidence in HIV-)

16. TB incidence closely correlated with HIV
prevalence in Africa
1000
800
600
Estimated TB incidence
(per 100,000 population)
400
200 10 20 30 40
HIV prevalence, adults 15-49y

17. TB incidence weakly related to social and
economic variables: infant mortality
6.5
6.0
5.5 AF AS
5.0 CA
Ln (estimated TB incidence)
4.5 EE SA
4.0 US WP
3.5 ME
3.0 WE
Series10
2.5
2.0
1.5
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
Ln (Infant mortality rate 1991)

18. Association between the rate of TB among country-of-birth-specific groups in Australia and the rate of TB in the country of birth. From Watkins & Plant 2003.

19. What’s wrong with the estimation process?
Cannot survey the whole world (infection or disease)
Many estimates are based on guesses about case detection
Estimates often too inaccurate or too biased to judge progress to case detection targets
National estimates do not apply sub-nationally
 value of exploiting surveillance data