A Publication from
ICAP’s Strategic
Information Unit
December 2014
ICAP Achievements as of September 30, 2014
Total facilities supported: 3,477
Care and treatment:
2,276 facilities reporting
 Enrolled in care: 1,267,924; 95,054 children
 Initiated ART: 898,167; 70,995 children
TB screening for HIV patients:
2,433 Facilities reporting
 554,347 HIV-positive patients screened for TB
HIV testing for TB patients:
1,036 facilities reporting
 299,861 new TB patients tested for HIV
 18,946 new TB patients tested positive for HIV
 1,796 co-infected and enrolled in HIV care and
treatment
PMTCT:
2,813 facilities reporting
 4,241,164 pregnant women counseled and tested at
ANC
HIV testing and counseling:
1,861 facilities reporting
 11,370,907 HIV counseled, tested, and received
results
Laboratory supports:
224 facilities reporting
 1,537,293 HIV rapid tests, 853,089 CD4 count,
110,427 CD4%, and 375,661 AFB conducted
About Databytes:
DataBytes is a publication series from ICAP’s Strategic
Information Unit. DataBytes highlights important trends
and outcomes in ICAP-supported programs with the
goal of encouraging closer examination and discussion
of routinely collected aggregate- and patient-level data
and facilitating evidence-based programming. For
suggestions on future issues, please contact Padmaja
(Piku) Patnaik at [email protected].
CASE FINDING IN HIV TESTING AND
COUNSELING SERVICES
With rapidly expanding access to effective antiretroviral therapy (ART) for lifelong treatment and as prophylaxis to prevent mother-to-child transmission of
HIV in sub-Saharan Africa over the past decade, timely diagnosis of HIV status
has become an increasingly urgent priority. HIV testing and counseling (HTC)
mechanisms can be classified into two general approaches, depending on
whether a client is seeking an HIV test (voluntary counseling and testing, or
VCT) or whether HIV tests are offered to clients seeking clinical care other
than an HIV test (provider-initiated testing and counseling, or PITC). In 2007,
the World Health Organization and the Joint United Nations Programme on
HIV/AIDS recommended that countries with generalized HIV epidemics
maximize case finding by offering PITC to all persons attending health
facilities.1
Prior studies have found varying HIV prevalence across different points of
testing. For example, studies have shown that VCT clients have a higher HIV
prevalence than estimated background seroprevalence, likely due to people
who consider themselves at high risk for HIV infection being more likely to
seek VCT services.2 Similarly, patients receiving PITC at PMTCT—assuming
testing coverage is high—as well as TB clinics have also been observed to
have higher HIV prevalence compared to background seroprevalence.3-8
There is limited data on HIV prevalence among PITC in other points of
services, such as inpatient and outpatient settings. Our assumption is that
HIV prevalence in these settings will be strongly dependent on testing
coverage among patients. Specifically, since the overall population receiving
medical care in these settings would approximate a general population, our
assumption is that universal PITC in these settings as recommended by the
WHO would result in seroprevalence similar to, or below (due to optingout by known HIV-positive patients), background prevalence. A targeted,
diagnostic approach of providing PITC selectively to the sickest or at-risk patients in outpatient and inpatient settings
would presumably result in a seroprevalence substantially higher than background prevalence.
To describe implementation of national HTC policies, and specially examine implementation of universal PITC, we used
routinely collected HTC program data from January 2010 to June 2012 from 1,492 ICAP-supported facilities in 5 countries
with generalized HIV epidemic, including Ethiopia, Cote d’Ivoire, Mozambique, Rwanda, and Tanzania. We describe the
volume of HTC from four different HIV-testing settings - VCT, PITC (including outpatient and inpatient settings), routine
testing of TB patients (with the exception of Tanzania), and pregnant women in ANC for PMTCT - for each country. We also
compare regional/provincial HIV prevalence across these settings, and with background HIV prevalence.
HIV seroprevalence was calculated by dividing the number testing HIV positive by the total number testing for HIV within a
particular HTC setting. HIV seroprevalence in VCT and PITC settings within each country were compared using chi-square
tests. While we did not conduct similar comparisons for TB and PMTCT testing, data from these settings are presented to
demonstrate the scale and distribution of HTC services and HIV seroprevalence in all ICAP-supported settings. Estimates of
region- or province-specific background HIV prevalence from Demographic and Health Surveys (DHS) conducted in each of
the five countries between 2005 and 2009 were compared to seroprevalence observed in VCT and PITC settings.9-13
HTC volume and HIV prevalence vary substantially by country and HTC setting.
HTC volume and seroprevalence by country: HTC volume and seroprevalence by setting varied substantially between
countries. Facilities in Ethiopia had the largest volume of HTC but the lowest overall seroprevalence (2.2%). Facilities in
Mozambique had the second highest volume and the highest overall seroprevalence (20.2%). (Table 1)
HTC volume and seroprevalence by setting: Testing in TB clinics accounted for 1% or less of all testing in each country,
while PMTCT was the predominant setting for HTC in Tanzania, Mozambique, and Cote d’Ivoire (10-58% of tests across all
five countries). PITC accounted for 16-29% of testing across all countries except for Ethiopia where it accounted for the
majority of testing (76%). Similarly, VCT accounted for 12-36% of testing in all countries except for Rwanda where it
accounted for the majority of testing (74%). Average seroprevalance across all countries was highest at TB clinics (10.9%),
followed by VCT (9.4%), PMTCT (5.4%), and PITC (2.9%).
Compared to HIV prevalence in VCT, HIV prevalence in PITC was higher in Rwanda and Cote d’Ivoire, similar
in Tanzania, and lower in Ethiopia and Mozambique.
Seroprevalence in PITC vs. VCT: Seroprevalence in PITC was substantially lower than seroprevalence in VCT in both
Ethiopia and Mozambique (both p<0.001), was not significantly different in Tanzania (p=0.9), and was slightly but
significantly higher in Rwanda and Cote d’Ivoire (both p<0.01). This suggests that PITC is more universal in Ethiopia
and Mozambique but more targeted in Tanzania, Rwanda and Cote d’Ivoire.
Table 1. HTC volume (number receiving HIV testing and counseling) and seroprevalence (% HIV-positive) by country and type of HTC
setting, January 2010 to June 2012
VCT
Rwanda
Tanzania
Mozambique
Ethiopia
Cote d'Ivoire
Total
(% HIV+)
243,317
318,531
232,464
482,432
41,586
1,318,330
(2.9)
(6.5)
(33.9)
(2.8)
(9.5)
(9.4)
PITC (% HIV+)
TB
53,918
(3.6)
211,688
(6.3)
147,371 (22.9)
3,060,112 (1.5)
80,639
(10.6)
3,553,728 (2.9)
885
(30.1)
n/a
8,326 (36.2)
40,281
(5.1)
2,374 (13.3)
51,866 (10.9)
(% HIV+)
PMTCT (% HIV+)
Total
32,348
(1.5)
332,846
(3.1)
542,652 (11.2)
425,902
(1.1)
150,325
(2.4)
1,484,073 (5.4)
330,468
(6.4)
863,065
(5.1)
930,813 (20.2)
4,008,727 (2.2)
275,105
(6.0)
6,408,178 (5.6)
(% HIV+)
DATABYTES December 2014
2
HIV seroprevalence in VCT settings is higher than background HIV prevalence in Tanzania, Mozambique,
Ethiopia, and Cote d’Ivoire; they are similar in Rwanda.
Figure 1. Seroprevalence in VCT settings and background seroprevalence, by country,
January 2010 to June 2012
40%
VCT
35%
Background
30%
Seroprevalence
Seroprevalence in VCT versus
background HIV prevalence:
Averaged within each country,
mean seroprevalence in VCT
settings was higher than
background prevalence (estimated
regional or provincial HIV
prevalence based on DHS) in all
countries except for Rwanda
(Figure 1). This suggests that
VCT patients in these 4
countries self-select getting
tested because they have an
elevated risk of HIV infection.
25%
20%
15%
10%
5%
0%
Rwanda
Tanzania
Mozambique
Ethiopia
Cote d'Ivoire
HIV seroprevalence in PITC settings is higher than background HIV prevalence in Tanzania, Mozambique and
Cote d’Ivoire; they are similar in Rwanda and Ethiopia.
Figure 2. Seroprevalence in PITC settings and background seroprevalence, by
country, January 2010 to June 2012
25%
PITC
20%
Seroprevalence
Seroprevalence in PITC versus
background HIV prevalence:
Averaged within each country,
mean seroprevalence in PITC
settings were similar to background
prevalence in Ethiopia and
Rwanda. Mean seroprevalence in
PITC settings was higher than
background prevalence in Cote
d’Ivoire, Mozambique, and
Tanzania (Figure 2). This suggests
that targeted PITC is being
employed in those countries.
Background
15%
10%
5%
0%
Rwanda
Tanzania
Mozambique
Ethiopia
Cote d'Ivoire
DATABYTES December 2014
3
The relationships between HIV prevalence in VCT, PITC and background HIV prevalence varied substantially
within regions of all countries
Regional/provincial seroprevalence in VCT and PITC versus background prevalence: While differences in the
relationship between background HIV prevalence and seroprevalence in VCT and PITC were seen across countries (as
illustrated in Figures 1 and 2), general patterns appeared within countries when examined by region (Figures 3-7, Regional HIV
seroprevalence within ICAP-supported VCT and PITC settings and background seroprevalence, as estimated by the most
recent DHS, by country. Circles representing VCT and PITC are proportional to the number of patients tested in that setting
within each country).
In Rwanda, VCT seroprevalence was similar Figure 3:
to background HIV prevalence in one region,
but lower than background HIV prevalence in
another region. PITC seroprevalence was lower
than background prevalence in one region, and
similar to background prevalence in another
region. VCT seroprevalence was higher than
PITC seroprevalence in one region, but lower
than PITC seroprevalence in another region.
In Tanzania, seroprevalence in both VCT and
PITC was higher than background HIV
prevalence in all five regions. In contrast to
Ethiopia and Mozambique, PITC seroprevalence
was higher than VCT seroprevalence in four of
five regions.
Figure 4:
In Mozambique, seroprevalence in VCT was
Figure 5:
substantially higher than background HIV
prevalence in all five regions, and seroprevalence
in PITC was substantially higher than background
HIV prevalence in four regions, but slightly lower
in one region. VCT seroprevalence was higher
than PITC seroprevalence in all five regions.
DATABYTES December 2014
4
In Ethiopia, seroprevalence in VCT was higher
than background HIV prevalence in three of
four regions, while seroprevalence in PITC was
similar to background HIV prevalence in two
regions, and lower in two regions. VCT
seroprevalence was higher than PITC
seroprevalence in all four regions.
Figure 6:
In Cote d’Ivoire, seroprevalence in both VCT
and PITC was higher than background HIV
prevalence in all three regions. PITC
seroprevalence was similar to VCT
seroprevalence in two regions, and greater than
VCT seroprevalence in one region.
Figure 7:
Discussion

Our findings suggest that HTC strategies differ across countries and across regions within countries with regards to the
volume of people being tested in each HTC setting and in the efficiency of identifying HIV-positive individuals (i.e.,
prevalence).

The relative seroprevalence of HIV in VCT versus PITC differed by country, suggesting that different country programs
practice two types of HIV counseling and testing under the term “PITC”: (1) universal PITC and (2) targeted or
diagnostic testing, where providers are not universally testing all patients but rather those perceived to be at greater HIV
risk.
o
VCT seroprevalence was higher than PITC seroprevalence in Mozambique and Ethiopia, suggesting that these
countries are reporting on something approaching universally-administered PITC and that clients who voluntarily
seek an HIV test are at higher risk for HIV compared to clients receiving a test through a clinical
recommendation.
o
VCT and PITC seroprevalence were similar in Tanzania, suggesting that HIV testing through PITC programs
may be related to clinical factors or perception of HIV risk.
o
PITC seroprevalence was higher than VCT seroprevalence in Rwanda and Cote d’Ivoire, suggesting that the
population receiving HIV tests through provider-initiated approaches are actually at higher risk of HIV than those
voluntarily seeking an HIV test.
DATABYTES December 2014
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
The relationship between case-finding in VCT and what might be expected given background HIV prevalence differed by
country.
o


As expected, HIV seroprevalence in VCT settings is higher than background HIV prevalence in 4 out of 5
countries

In Ethiopia, Cote d’Ivoire, Mozambique, and Tanzania, VCT patients seem to self-select getting
tested because they have an elevated risk of HIV infection.

In Rwanda, it is not clear why HIV seroprevalence in VCT settings is lower than background HIV
prevalence.
The relationship between case-finding in PITC and what might be expected given background HIV prevalence differed by
country.
o
In Cote d’Ivoire, Mozambique, and Tanzania HIV seroprevalence in PITC settings is higher than background
HIV prevalence, possibly reflecting a certain amount of targeted, diagnostic HIV testing in PITC settings rather
than a practice of testing all patients.
o
In Ethiopia, Rwanda and Tanzania HIV seroprevalence in PITC settings is similar to background HIV
prevalence, suggesting that these countries are reporting on more universally-administered PITC.
We observed a high variation of HIV testing volume and seroprevalence by HTC settings within regions, suggesting that
these particular testing strategies are not implemented systematically across a country. These differences may also be
reflective of regional differences in the HIV epidemic.
Conclusions
Routinely-collected HIV testing and counseling indicator data and publicly available data can be used to draw inferences about
HTC implementation in ICAP-supported countries. When this data was stratified by HIV testing setting (i.e., PITC, HTC, TB,
PMTCT), it allows us to identify the scale of HTC in each setting, compare HIV seroprevalence between these settings, and to
compare seroprevalence from each setting with background population-level measures of HIV prevalence estimated by the
DHS. If PITC strategies were adopted to test all patients regardless of clinical diagnosis or perception of risk, we would expect
HIV seroprevalence to consistently be lower in PITC settings compared to VCT settings, and comparable or lower than
background seroprevalence estimates. Our findings show that this is the case in some regions and countries. In other regions
and countries, HIV seroprevalence in PITC exceeded both background HIV estimates and seroprevalence measured in VCT.
This suggests that PITC testing, as reported to ICAP, was not conducted universally, independent of clinical diagnosis or risk
assessment, per World Health Organization and the Joint United Nations Programme on HIV/AIDS recommendations.
We recommend that strategies for HTC be examined more closely. The roles of PITC and VCT in HIV case detection in subSaharan Africa should be better elucidated, including assessing the similarities and differences in HIV-infected populations
reached by VCT and PITC.
DATABYTES December 2014
6
Data Source and Methods
Sample
ICAP began collecting HTC data from 8 country teams centrally in January 2010. Only 5 countries – Ethiopia, Cote d’Ivoire,
Mozambique, Rwanda, and Tanzania –supported VCT, PITC, PMTCT, and (with the exception of Tanzania) HIV testing in
TB clinics and submitted aggregate indicator data separately for each type of testing to ICAP centrally. Since this range of
HTC and type of information was required for this analysis, our analyses were limited to these five countries. (Countries not
included are Nigeria, South Africa, and Kenya.)
Definitions and calculations

Provider-Initiated testing and counseling (PITC) – HTC provided as part of clinical care. PITC was reported for
clinical points of service including Outpatient, Inpatient, Laboratory, Family planning, Eye unit, Well baby clinic,
Casualty/trauma, Cervical cancer screening, and STI clinics.

Seroprevalence: The percentage of patients tested positive for HIV among those tested in a population.

Seroprevalence ratio: The mean seroprevalence in HTC for a geographic area divided by the population-level
seroprevalence for the same geographic area as measured in DHS.

Limitations:
o
Country-specific reporting mechanisms make it difficult to distinguish between “truly PITC” testing numbers
and those conducted outside of VCT for diagnostic confirmatory purposes which get reported as PITC. This
may additionally explain high reported PITC seroprevalence estimates in several countries.
o
Data used in the analyses are aggregate-level data; patient-level factors that may influence outcomes were not
assessed and conclusions cannot be drawn to individuals.
o
Analyses are limited by the quality of reported data.
Credits
• Contributors: William Reidy, Beatriz Thome, Suzue Saito, Stephen Arpadi, Ruby Fayorsey, Rosalind Carter, Batya Elul,
Matt Lamb, Piku Patnaik, Mansi Agarwal, and Justin Knox.
For more information, please contact William Reidy at [email protected].
References
1. World Health Organization. Guidance on provider-initiated HIV testing and counselling in health facilities. 2007.
2. Horyniak D, Guy R, Prybylski D, Hellard M, Kaldor J. The utility of voluntary counselling and testing data as a source
of information on HIV prevalence: a systematic review. Int J STD AIDS. 2010 May;21(5):305-11.
3. Mpairwe H, Muhangi L, Namujju PB, Kisitu A, Tumusiime A, Muwanga M, Whitworth JA, Onyango S, Biryahwaho
B, Elliott AM. HIV risk perception and prevalence in a program for prevention of mother-to-child HIV transmission:
comparison of women who accept voluntary counseling and testing and those tested anonymously. J Acquir Immune
Defic Syndr. 2005 Jul 1;39(3):354-8.
DATABYTES December 2014
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4. Fabiani M, Nattabi B, Ayella EO, et al. Using prevalence data from the programme for the prevention of mother-tochild-transmission for HIV-1 surveillance in North Uganda. AIDS 2005;19:823–7.
5. Kapata N, Chanda-Kapata P, Grobusch MP, O'Grady J, Schwank S, Bates M, Jansenn S, Mwinga A, Cobelens F,
Mwaba P, Zumla A. Scale-up of TB and HIV programme collaborative activities in Zambia - a 10-year review. Trop
Med Int Health. 2012 Jun;17(6):760-6.
6. Pevzner ES, Vandebriel G, Lowrance DW, Gasana M, Finlay A. Evaluation of the rapid scale-up of collaborative
TB/HIV activities in TB facilities in Rwanda, 2005-2009. BMC Public Health. 2011 Jul 11;11:550.
7. Centers for Disease Control and Prevention (CDC). HIV testing and treatment among tuberculosis patients --- Kenya,
2006-2009. MMWR Morb Mortal Wkly Rep. 2010 Nov 26;59(46):1514-7.
8. Deribew A, Negussu N, Kassahun W, Apers L, Colebunders R. Uptake of provider-initiated counselling and testing
among tuberculosis suspects, Ethiopia. Int J Tuberc Lung Dis. 2010 Nov;14(11):1442-6.
9. Instituto Nacional de Saúde (INS), Instituto Nacional de Estatística (INE), e ICF Macro. 2010. Inquérito Nacional de
Prevalência, Riscos Comportamentais e Informação sobre o HIV e SIDA em Moçambique 2009. Calverton, Maryland,
EUA: INS, INE e ICF Macro.
10. Central Statistical Agency [Ethiopia] and ORC Macro. 2006. Ethiopia Demographic and Health Survey 2005.
11. Addis Ababa, Ethiopia and Calverton, Maryland, USA: Central Statistical Agency and ORC Macro.
12. Institut National de la Statistique du Rwanda (INSR) and ORC Macro. 2006. Rwanda Demographic and Health
Survey 2005. Calverton, Maryland, U.S.A.: INSR and ORC Macro.
13. Tanzania Commission for AIDS (TACAIDS), Zanzibar AIDS Commission (ZAC), National Bureau of Statistics
(NBS), Office of the Chief Government Statistician (OCGS), and Macro International Inc. 2008. Tanzania
HIV/AIDS and Malaria Indicator Survey 2007-08. Dar es Salaam, Tanzania: TACAIDS, ZAC, NBS, OCGS, and
Macro International Inc. Institut National de la Statistique (INS) et ICF International. 2012.
14. Institut National de la Statistique (INS) et Ministère de la Lutte contre le Sida [Côte d’Ivoire] et ORC Macro. 2006.
Enquête sur les Indicateurs du Sida, Côte d’Ivoire 2005. Calverton, Maryland, U.S.A. : INS et ORC Macro.
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