Estimating the Case Detection Rate in Kenya

Cancun: December 2009

Brian Williams and John Mansoer

www.sacema.ac.za

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WajWes

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CNR 1990

TB Case notification rates per 100k population in Kenya in 1990. (NLTP database; Nairobi)

0

100

200

300

1980 1990 2000

Ca

se

s/1

00

k/y

ea

r

TB case notification rates from 1980 to 2006.

TB trends in Kenya

1996: SS+ notification rate 61/100k population, HIV-prevalence 0.30 ± 0.02 SS+ HIV− TB notification rate in 1996 of 42.5/100k population.

2006: SS+ notification rate 124/100k population, HIV-prevalence 0.52 ± 0.02SS+ HIV− notification rate of 59.5/100k.

The case detection rate has increased by a factor of 1.40. CD 1996 of 57%:

Case detection rate in 2006 of 79% ±±±± 15%.

van Gorkom J, Kibuga, D, Abdallah, S, et al. HIV-seroprevalence among tuberculosis patients in Kenya. East Afr Med J, 1999; 76: 452-456.

van Gorkom J, Kibuga, DK. HIV infection among patients with tuberculosis in Kenya. Int J Tuberc Lung Dis, 1999; 3: 741-742.

Estimating the increase in SS+ HIV- TB

n

pπσ=CDR

Prevalence of HIV in adults = p

Annual risk of developing TB if HIV positive = π

Incidence of TB in people who are HIV-positive is pπ .

The proportion of HIV-positive TB patients that are SS+ = σ

pπσ=Incidence

Notification rate = n

Estimating the SS+ HIV+ CDR

Case detection rate in 2006 of 57% ±±±± 31%

0

50

100

150

1995 2000 2005

Year

SS

+ c

ase

s/1

00

k p

opu

lation

Smooth line: logistic curve fitted up to 2000

Estimating the total SS+ CDR

Case detection rate in 2006 of 72% ±±±± 19%

30

40

50

60

1995 2000 2005

HU

N/T

PN

/M

5

10

15

20

1995 2000 2005

He

alth u

nits/M

peop

le

Dia

gn

ostic u

nits/M

peo

ple

The number of diagnostic units (left) and health units (right) per million people in the population.

30

40

50

60

70

1995 2000 2005

N

40

60

80

100

1995 2000 2005

5

10

15

1995 2000 2005

Smoothed

0

1

2

1995 2000 2005

SS

+/d

iag

. u

nit

TB

ca

se

s/h

ealth

un

it

SS

+/s

usp

ect

Su

sp

ects

/k p

op

n.

a b c d

The number of a) smear-positive TB cases per diagnostic unit; b) TB cases (all forms) per health unit; c) the number of smear-positive cases found for each ten suspects examined; and d) the number of suspects examined per 1,000 population.

The staff complement of the NTLP. CU: central unit; PTLCsand DTLCs: provincial and district TB and leprosy coordinators

0

20

40

60

80

100

120

140

160

180

200

1996 1998 2000 2002 2004 2006

Pers

onnel

CU

Drivers

PTLCs

DTLCs

New Retreatment Smear-negative Extra-pulmonary

0.6

0.7

0.8

0.9

1.0

1996 1998 2000 2002 20040.6

0.7

0.8

0.9

1.0

1996 1998 2000 2002 2004

Trans. out

Absconded

Died

Failure

Completed

Cured

0.6

0.7

0.8

0.9

1.0

1996 1998 2000 2002 2004

0.6

0.7

0.8

0.9

1.0

1996 1998 2000 2002 2004

Treatment outcomes for new cases, retreatment cases, smear-negative cases and extra-pulmonary cases.

0

5

10

15

1996 1998 2000 2002 2004 2006

US

$ (

M)

CDC/PEPFAR (Partners)Global FundCDC/PEPFAR (CoAg)GDFUSAID/JSIKNCV/CIDA/JSIWHOKNCV/Gov NetherlandsGOK (salaries NLTP staff)GOK (drugs)

Funding to support the NLTP in Kenya.

0.231-0.264

0.199-0.231

0.167-0.199

0.134-0.167

0.102-0.134

0.069-0.102

0.037-0.069

0.005-0.037

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P(HIV/ANC)

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P(HIV:FSP) [SS>50]

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Vih

ANC women

TB patients

Distribution of HIV in Kenya

0

50

100

150

200

1995 2000 2005

SS

+/1

00k p

op

ula

tio

n

Smear-positive TB per 100k population in the high (blue) and low (red) prevalence districts bordering Lake Victoria.

0.64 0.70

0.170.12

0.08 0.060.07 0.080.04 0.04

0.0

0.2

0.4

0.6

0.8

1.0

High HIV Low HIV

Pro

port

ion o

f cases

TO

Absc

Died

ND

Neg

The proportion of smear-positive cases that, at the end of treatment, were smear-negative, did not have smears done, died, absconded or transferred out for districts with high and low prevalence of HIV.

1990 1995 2000 2005

10

5

0

Pre

vale

nce H

IV (

%)

Urban

Rural

National

TB

Trends in HIV in Kenya

Tanzania

n

pπσ=CDR

Prevalence of HIV in adults = p

Annual risk of developing TB if HIV positive = π

Incidence of TB in people who are HIV-positive is pπ .

The proportion of HIV-positive TB patients that are SS+ = σ

pπσ=Incidence

Notification rate = n

Estimating the SS+ HIV+ CDR

Case detection rate in 2006 of 68% ±±±± 20%

Annual rate of decline in:

SS+ 1.6% ± 0.5%ARI 2.7%HIV 1.3% ± 0.3%

-0.080

-0.060

-0.040

-0.020

0.000

0.020

0-14 15–24 25–34 35–64 65+

Male

Female

Trend in SS+ 1999 to 2008A

nn

ua

l ra

te o

f ch

an

ge

Thank you

0.00

0.02

0.04

0.06

0.08

1980 1990 2000 2010 2020 2030 2040 2050

0.000

0.005

0.010

Pre

va

len

ce

Incid

en

ce

an

d m

ort

alit

y/y

r

0

50

100

150

200

1980 1990 2000 2010 2020 2030 2040 2050

Notifications/1

00k/y

r

HIV

TB

Prevalence

Incidence

Mortality

All

HIV-negative

Trends in HIV and TB in Tanzania

CD4 Counts Are Low at Start of HAART

Egger M, 14th CROI; 2007. Abstract 62. ART Cohort Collaboration. http://www.art-cohort-collaboration.org.

2003–2005

• 42 countries

• 176 sites

• 33,008 patients

25

11

8

24

11

16

5

10

Kyela

0.5

Bukoba

7

KisesaMwanza

Kigoma

Arusha

Kilimanjaro

Lindi

DodomaLake Tanganyika

Tabora TangaPemba

Zanzibar

DAR ES SALAAM

Iringa

Mbeya

Lake Nyasa

Mtwara

Estimated prevalence (%) of infection at ante-natal clinics in Tanzania in 1994. Rates are high in Kyela (on the border with Malawi) and in Bokoba (close to the border with Uganda) and very low on the islands of Zanzibar and Pemba.

0.00

0.02

0.04

0.06

0.08

1980 1990 2000 2010 2020 2030 2040 2050

0.000

0.005

0.010

Pre

va

len

ce

Incid

en

ce

an

d m

ort

alit

y/y

r

0

50

100

150

200

1980 1990 2000 2010 2020 2030 2040 2050

Notifications/1

00k/y

r

HIV

TB

Prevalence

Incidence

Mortality

All

HIV-negative

Trends in HIV and TB in Tanzania