PEPFAR Data Review...•Monthly analysis of DHIS data has been on-going ... in interventions are authorized . FY17 DATIM alignment - progress report Reporting Julperiod -16 Aug SeptOct

PEPFAR Data Review How PEPFAR is Looking at the Data?

What are the Tools?

Patrick Nadol

CDC/SA

Areas of (re-newed) focus for PEPFAR

Granularity:

Site, age, sex, population, trends

over time

Composite monitoring:

Linkage to Tx, Tx net new

Timeliness

TX_CURR gap: By District and Cumulative gap

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0%

2%

4%

6%

8%

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14%

Cu

mu

lati

ve T

X_C

UR

R g

ap

% T

X_C

UR

R g

ap (

dis

tric

t ga

p/t

ota

l gap

)

%_TX_CURR_gap sum_TX_CURR_gap

80% of TX_CURR gap is located in 16/27 districts

50% of TX_CURR gap is located in 6/27 districts

Row Labels

CUMM

TARGETS:

FY2017

RESULTS: FY17-

Q1

RESULTS: FY17-

Q3

CUMM

RESULTS:

FY2017

%

ACHIEVEMENT

STATUS

HTS_TST_Pos+Neg 5,767,766 2,503,472 2,887,251 5,390,723 93%

HTS_TST_Pos 823,111 221,932 236,295 458,227 56%

TX_NEW 965,131 183,957 149,570 333,527 35%

TX_CURR 3,935,927 2,950,894 3,131,935 3,131,935 80%

TX_NET NEW 1,220,164 235,131 181,041 416,172 34%

Clin

ical

cascad

e

PMTCT_STAT 719,446 186,570 170,310 356,880 50%

PMTCT

PMTCT_STAT_Pos 391,670 47,729 50,997 98,726 25%

PMTCT_ART 155,489 45,894 46,120 92,014 59%

PMTCT_EID 154,992 66,172 74,226 140,398 91%

PMTCT_EID_POS_12MO 232 385 580 965 416%

PMTCT_EID_POS_2MO 1,488 317 336 653 44%

PrEP_NEW 1,279 304 698 1,002 78%

VMMC_CIRC 393,465 44,626 145,240 189,866 48%PREVENTION

PMTCT

Q3 Progress: PEPFAR Focus Districts (n=27)

4

Good case-detection with overall high yield

Sub-optimal TX_NEW & TX net new with improving ‘linkage’

post-UTT

Moderate acceleration of

VMMC

Timeliness

Timeliness

• Quarterly analysis of data is insufficient

• Beginning in Q3 (May-June data), PEPFAR is reporting its quarterly data more ‘real-time’ • Moved aware from reporting 1 quarter in arrears

• VMMC is reporting results weekly

• Efforts underway to have TX results reported weekly

• Monthly analysis of DHIS data has been on-going

• Rationale: • Updated NDoH policy supports more timely flow of data from facility to national

level (<30 days) • Allows for more immediate identification of progress & corrective action as

required • Changes in interventions are authorized

FY17 DATIM alignment - progress report

Reporting period Jul-16 Aug-16 Sept-16 Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sept-17

Status on

May 15, 2017

Arrears

FY17-Q1

Arrears

FY17-Q2


Status on

Aug 15, 2017

Aligned

FY17-Q1

Aligned

FY17-Q3


Planned:

Sept 22, 2017

Aligned

FY17-Q1

Aligned

FY17-Q2

Aligned

FY17-Q3


Planned:

Nov 15, 2017

Aligned

FY17-Q1

Aligned

FY17-Q2

Aligned

FY17-Q3

Aligned

FY17-Q4

We are

here

Monthly review: TX CURR by district, facility

-

50 000

100 000

150 000

200 000

250 000

300 000

350 000

400 000

gp City of Johannesburg Metropolitan Municipality kz eThekwini Metropolitan Municipality

kz uMgungundlovu District Municipality gp City of Ekurhuleni Metropolitan Municipality

Monthly reporting/review of data

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2000

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Ap

r_1

6

May

_16

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_16

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_1

6

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_16

No

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6

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_1

7

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_1

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_1

7

Ap

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_17

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_17

kz Cato Manor CHC

TX_CURR

TX_CURR

Granularity

Granularity of reporting and analysis • While district-level results remain critical…reporting and analysis (and

remediation) is down to the level of service delivery (e.g. facility) is essential to reaching goals

• Epi and program data strongly indicate variation in HIV burden, service update, and response by age, sex, population (key-, priority-)….

• …Necessitates the need to understand program coverage by age, sex and to design and implement population appropriate programs to fill these gaps

• International community has recommended reporting by ‘finer’ disaggregations (Ref: WHO. Consolidated Strategic Information Guidelines. 2015)…

• …Beginning in Q1 ‘18 (October 2017), PEPFAR will require reporting on more precise age, sex bands

*Site-Level monitoring: On-line GIS Server (PEPFAR)*

HTC Yield: https://devgeocenter.org/flexviewers/PEPFARSAHTCPositivity/

Linkage to Tx: https://devgeocenter.org/flexviewers/PEPFARSALinkedToTreatment/

Treatment : https://devgeocenter.org/flexviewers/PEPFARSAARTTReatmentGap/

https://devgeocenter.org/flexviewers/PEPFARSAHTCPositivity/

https://devgeocenter.org/flexviewers/PEPFARSAHTCPositivity/

https://devgeocenter.org/flexviewers/PEPFARSALinkedToTreatment/



https://devgeocenter.org/flexviewers/PEPFARSAARTTReatmentGap/

https://devgeocenter.org/flexviewers/PEPFARSAARTTReatmentGap/

VMMC % of Target Achieved (Q3) – Site Level Analysis

12

13

51% 49% 47% 49% 54%

49% 43%

19% 22% 17% 15%

17% 18%

15%

11% 11%

11% 11%

9% 10%

12%

19% 18%

23% 24%

19% 22%

28%

1% 1% 1% 1% 1% 1% 2%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Jul to Sep 2015 Oct to Dec 2015 Jan to Mar 2016 Apr to Jun 2016 Jul to Sep 2016 Oct to Dec 2016 Jan to Mar 2017

Total

>=50

25:49

20:24

15:19

10:14

Circumcisions by Age Band: 27 Districts Q1 - Q3

Trends in HIV Positivity Rate Dashboard

0%10%20%30%40%50%60%70%80%90%

100%

gp City ofJohannesburgMetropolitanMunicipality

gp EkurhuleniMetropolitanMunicipality

kz eThekwiniMetropolitanMunicipality

kz uMgungundlovuDistrict

Municipality

Male 15-24: TX_CURR (Q2 '17) vs. TX_CURR gap (%)

M_15_24_Q2TXCURR M_15_24_Q2TXCURR_gap

0%

20%

40%

60%

80%

100%




kzuMgungundlovu

DistrictMunicipality

Female <15: TX_CURR (Q2 '17) vs. TX_CURR gap (%)

F_0015_Q2TXCURR F_0015_Q2TXCURR_gap

0%

20%

40%

60%

80%

100%




kz uMgungundlovuDistrict

Municipality

Female 15-24: TX_CURR (Q2 '17) vs. TX_CURR gap (%)

F_15_24_Q2TXCURR F_15_24_Q2TXCURR_gap

0%20%40%60%80%

100%




kzuMgungundlovu


Female 25+: TX_CURR (Q2 '17) vs. TX_CURR gap (%)

F_25PL_Q2TXCURR F_25PL_Q2TXCURR_gap

Males, Females TX_CURR coverage (Q2 ‘17) and remaining gap to COP17 target by age, sex band

0%

20%

40%

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80%

100%




kzuMgungundlovu


Male <15: TX_CURR (Q2 '17) vs. TX_CURR gap (%)

M_0015_Q2TXCURR M_0015_Q2TXCURR_gap

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20%

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100%




kzuMgungundlovu


Male 25+: TX_CURR (Q2 '17) vs. TX_CURR gap (%)

M_25PL_Q2TXCURR M_25PL_Q2TXCURR_gap

Viral Suppression (%) by age group: 2015-16

2589 32321 31031 36533

105678 1657327

20434

1883 16853 17992 20693

30698 332623

7326

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

<1 1-9 10-14 15-19 20-24 25+ notstated

% V

LS

AGE CATEGORY

2017

yes No

Current performance line Target line

1109

13059 10197 10412

27625

428394 9198

1660

11278 9808 11467

19071

192959 6116

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

<1 1-9 10-14 15-19 20-24 25+ notstated

% V

LS

AGE CATEGORY

2016

yesNoCurrent performance line

4057

50693 42706 46739

130522 2110487

32143

3668

29978 29415 33090

50777 542708

13830

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

<1 1-9 10-14 15-19 20-24 25+ notstated

% V

LS

AGE CATEGORY

2015

yes No

Current performance line Target line

REF: NHLS/CCMT report July 2017

Composite Measures

Composite indicators e.g. linkages, ‘net_new’

• Individuals move across programs and services which requires monitoring & analysis of ‘composite’ rather than ‘siloed’ indicators • Linkage: HIV testing->HIV Treatment ( ‘direct’ linkage indicator under

consideration)

• Net New on Treatment: change in TROA over time

• TX_NEW-TX net new

• Treatment cascade

• Allows for a holistic picture of program across interventions and for deeper analysis for corrective actions

Time Trend: Linkage to care (Positive test / New ART start), stratified by priority (SOURCE: South Africa DHIS)

19

Impact of UTT implementation:

- Pre-ART Mop Up

- Same Day Initiation

- Linkage Officers

Source: DHIS

0%

20%

40%

60%

80%

100%

120%

140%

160%

Scale-up: Aggressive Scale-up: Saturation

Linkage to TX (TX_New/HTC_Pos): Johannesburg

Oct-Dec 2016 Linkage

Apr-June 2017 Linkage

Linkage (TX_NEW/HTC_POS) by Age/Sex, Q1-Q2: kz eThekwini Metropolitan Municipality

0%

50%

100%

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250%

10:14 15:19 20:24 25:49 >=50

Female Male

TX_NEW - TX_NET_NEW, Q1’17

22

-1000

0

1000

2000

3000Ekhuruleni Patient Volume

-3000

-2000

-1000

0

1000

2000

3000eThekwini

Patient Volume

-15000

-10000

-5000

0

5000

City of Johannesburg Patient Volume

-2500

-2000

-1500

-1000

-500

0

500Umgungundlovu Patient Volume

TX_NEW > TX_NET_NEW; potential retention issues

TX_NEW<TX_NET_NEW; potential transfer-in issues

Current/Future Directions

• Accelerated progress towards 90 90 90 is needed

• More timely (e.g. weekly, monthly) review and response to data is essential

• Aggressive monitoring of program, partner performance: • Monthly updating of DHIS Dashboard; quarterly review of cohort

(TX_RET) and viral load data

• Close monitoring of HTC_pos, linkage, TX_NEW, TX_CURR, TX_Retain, TX_net_new, VMMC • Age, sex bands (more precise age bands are forthcoming)

• Site level

• Direct measure of linkage may be forthcoming

• AssessFeedback with remediation plansRepeat

Final thought

• MER represents the minimum and should not be rate-limiting for additional analytics and interpretation to improve the quality of the program.

Acknowledgements

• PEPFAR Strategic Information TWG (CDC, USAID)

• SA NDoH

District TX Net_New Total (secondary x axis)

Site TX Net_New (primary x axis)

Site Q2 ‘17 TX_CURR (circle size)

Partner (circle color)

TX_NET_NEW, Q4’16-Q2’17, by District

-50000

0

50000

100000

150000

200000

Achievement Target

Q3 Progress: PEPFAR ‘Saturation’ Districts (n=4)

Row Labels

CUMM

TARGETS:

FY2017

RESULTS: FY17-

Q1

RESULTS: FY17-

Q3

CUMM

RESULTS:

FY2017

%

ACHIEVEMENT

STATUS

HTS_TST_Pos+Neg 2,065,597 828,458 1,059,260 1,887,718 91%

HTS_TST_Pos 292,716 90,898 93,232 184,130 63%

TX_NEW 336,242 66,716 54,433 121,149 36%

TX_CURR 1,486,960 1,043,202 1,118,564 1,118,564 75%

TX_NET NEW 533,314 89,556 75,362 164,918 31%

Cli

nic

al

cascad

e

PMTCT_STAT 240,901 60,293 57,223 117,516 49%

PMTCT

PMTCT_STAT_Pos 113,316 17,091 17,651 34,742 31%

PMTCT_ART 63,377 16,300 16,994 33,294 53%

PMTCT_EID 63,154 25,517 26,273 51,790 82%

PMTCT_EID_POS_12MO 71 158 203 361 508%

PMTCT_EID_POS_2MO 631 148 153 301 48%

PrEP_NEW 1,279 213 295 508 40%

VMMC_CIRC 173,227 20,890 52,194 73,084 42%PREVENTION

PMTCT

28

-

50 000

100 000

150 000

200 000

250 000

Females Males Females Males Females Males Females Males

Positive

Negative

29

COP 2017 Community Modality Targets

Home Based Index Mobile Other & KP

Entry Streams for ART Enrollment Tested for HIV Identified Positive Newly initiated (90% Linkage)

Community 1,915,892 166,819 150,137

Home Based 440,927 30,674 27,607

Index 482,093 36,770 33,093

Mobile 801,092 76,194 68,575

Other & Key Pop 193,100 23,379 21,041

SAPR 2017 Community Modality Results

8.34%

6.56%

7.92%

7.94%

9.36% 7.06%

9.96% 7.08%

Documents

PEPFAR Data Review...•Monthly analysis of DHIS data has been on-going ... in interventions are authorized . FY17 DATIM alignment - progress report Reporting Julperiod -16 Aug SeptOct