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. 2021 Mar 9;36(6):939–954. doi: 10.1093/heapol/czab030

Table 3.

Studies of the cost of scaling up HIV and syphilis testing

Study Intervention(s) Country Study population Setting Time horizon Study design Type of economic analysis (and ratio if applicable) Data source (s) Analytical approach to measure scale
#1 (Shelley et al., 2015) Syphilis testing/RST/POC Zambia Pregnant women (age not specified) ANC clinic 5 months Cross-sectional study Cost analysis Primary data collection Empirical
#2 (Schackman et al., 2007)

Syphilis testing, comparing:

#1 Syndromic surveillance/not POC

#2 RPR for syphilis/not POC

#3 RST/POC

Haiti Pregnant women (age not specified) ANC clinic Not specified Modelling Cost-effectiveness analysis Published literature/data Modelling
#3 (Bautista-Arredondo et al., 2018a,b) HIV voluntary and provider-initiated counselling and testing/HIV rapid test/not POC Nigeria General population (age not specified) Health facility 6 months Cross-sectional study Cost analysis Primary data collection Econometric
#4 (Dandona et al., 2008a,b) HIV voluntary counselling and testing/HIV rapid test/not POC India General population (age not specified) Health facility 1 year Cross-sectional study Cost analysis Primary data collection Empirical
#5 (Galárraga et al., 2017) HIV testing and counselling/HIV rapid test/not POC Kenya General population (age not specified) Health facility 22 months Cross-sectional study Cost analysis Primary data collection Econometric
#6 (Hontelez et al., 2013)

HIV testing/type of test not specified/not POC, comparing:

#1 ART at CD4 count ≤350 cells/µl

#2 Universal testing and treatment

South Africa General population (aged 15–65 years) Not specified Lifetime Modelling Cost-effectiveness analysis Published literature/data Modelling
#7 (Ishikawa et al., 2016)

HIV testing/HIV rapid test/not POC, comparing:

#1 The current coverage

#2 A focused approach

#3 A universal approach

Namibia, Kenya, Haiti and Vietnam Pregnant women (aged 15–49 years old) ANC clinic 20 years Modelling Cost-effectiveness analysis Published literature/data Modelling
#8 (McConnel et al., 2005) HIV rapid voluntary counselling and testing/HIV rapid test/POC South Africa General population (age not specified) VCT clinic 1 year Cross-sectional study Cost analysis Primary data collection Empirical
#9 (Ahaibwe and Kasirye, 2013)

HIV testing/HIV rapid test/not POC, comparing:

#1 The current coverage

#2 100% coverage of adult population

Uganda General population (adult 15–49 years) Stand alone, integrated w/health facility, non- health facility and mobile VCT services Lifetime Modelling Cost-effectiveness analysis Published literature/data Modelling
#10 (Alsallaq et al., 2017)

HIV testing/HIV rapid test/not POC, comparing:

#1 HIV strategies focusing on youth (15–24 years old)

#2 HIV strategies focusing on adults (15+ years)

Kenya Youth population (aged 15–24 years) Health facility 20 years Modelling Cost-effectiveness analysis Published literature/data Modelling
#11 (Cambiano et al., 2015)

HIV testing/HIV rapid test/not POC, comparing:

#1 Provider-delivered HIV testing and counselling

#2 HIV self-testing

Zimbabwe General population (aged 15–65 years old) Not specified 20 years Modelling Cost-effectiveness analysis Published literature/data Modelling
#12 (Cherutich et al., 2018)

aPS HIV testing/rapid HIV test/not POC, comparing:

#1 Current coverage at 5%

#2 Scale up to reach coverage of 50%

Kenya General population (age not specified) Health facility and community-based health services 5 years Modelling Cost-effectiveness analysis and budget impact analysis Published literature/data Modelling
#13 (Mwenge et al., 2017) HIV voluntary and provider-initiated counselling and testing/rapid HIV test/not POC Malawi, Zambia and Zimbabwe General population (aged 15–49 years) Health facility 1 year Cross-sectional study Cost analysis Primary data collection Econometric
#14 (Stuart et al., 2018) HIV testing/type of test not specified/not POC South Africa General population (age not specified) Not specified 30 years Modelling Cost analysis Published literature/data Modelling
#15 (Tromp et al., 2013)

HIV voluntary counselling and testing/HIV rapid test/not POC, comparing:

#1 Current practice

#2 Scaling up to reach coverage 80%

Indonesia Key populations (FSWs, IDUs, higher-risk MSM, transgender, prisoner, clients of FSWs and partner IDUs) (age not specified) Community-based VCT clinic 20 years Modelling Cost-effectiveness analysis Published literature/data Modelling
#16 (Zhuang et al., 2018)

HIV testing and treatment/type of test not specified/not POC, comparing:

#1 Current strategy

#2 Reached 90–90–90 target by 2020

# Reached 90–90–90 target by 2025

China MSM (age not specified) Health facility 20 years Modelling Cost-effectiveness analysis Published literature/data Modelling
#17 (Dandona et al., 2008a,b) HIV counselling and testing/HIV rapid test/not POC India Pregnant women (age not specified) Hospital and community health centre 1 year Cross-sectional study Cost analysis Primary data collection Econometric
#18 (Dandona et al., 2005) HIV counselling and testing/HIV rapid test/not POC India General population (age not specified) VCT clinics 1 year Cross-sectional study Cost analysis Primary data collection Econometric
#19 (Forsythe, 2002) HIV voluntary counselling and testing/serial of HIV rapid testing/POC Kenya General population (age not specified) Health facility A year Cross-sectional study Cost analysis Primary data collection Empirical
#20 (Granich et al., 2009)

HIV testing/type of test not specified/not POC, comparing:

#1 Reference scenario

#2 Universal voluntary HIV testing and immediate ART

South Africa General population (age not specified) Not specified 42 years Modelling Cost-effectiveness analysis Published literature/data Modelling
#21 (Kasymova, Johns and Sharipova, 2009) HIV testing and counselling/serial of HIV rapid test/not POC Tajikistan

Youth population

(aged 15–25 years)

Youth friendly health services 2 years Cross-sectional study Cost analysis Primary data collection Modelling
#22 (Kato et al., 2013)

HIV testing type of test not specified/not POC, comparing:

#1 Reference scenario

#2 Targeted PTIT scenario

#3 Universal PTIT scenario

Vietnam Key population: PWID, MSM, FSWs, MCF, IDU and low-risk women (age not specified) Health facility 50 years Modelling Cost effectiveness analysis Published literature/data Modelling
#23 (Kumar et al., 2006)

HIV testing and counselling/rapid HIV test/not POC, comparing:

#1 A universal testing

#2 A targeted testing

India Pregnant women (age not specified) ANC clinic Lifetime Modelling Cost–benefit analysis Published literature/data Modelling
#24 (Dandona et al., 2009) HIV voluntary counselling and testing/HIV rapid test/not POC India General population (age not specified) VCT clinic 1 year Cross-sectional study Cost analysis Primary data collection Modelling
#25 (Mangenah et al., 2019) HIVST/HIV rapid testing/not POC Malawi, Zambia, and Zimbabwe General population (aged 15–59 years) Community based distributing agent 1 year Cross-sectional study Cost analysis Primary data collection Econometric
#26 (McCreesh et al., 2017)

HIV self-testing/HIV rapid test/not POC, comparing

#1 Current coverage

#2 Increased HIV testing (doubled)

Uganda General population (aged under 51 years) Door-to-door community-based 15 years Modelling Cost-effectiveness analysis Published literature/data Modelling
#27 (Minh et al., 2012) HIV voluntary counselling and testing/type of test not specified/not POC Vietnam General population (age not specified) Facility based and freestanding VCT clinic 4 months Costing study Cost analysis Primary data collection Modelling
#28 (Sharma et al., 2016)

HIV home-based partner education and testing (HOPE)/HIV rapid test/not POC, comparing:

#1 Standard care (facility-based HIV testing)

#2 Adding HOPE to standard care

Kenya Partner of pregnant women (aged 0–59 years) Home based 10 years Modelling alongside randomized controlled trial Cost-effectiveness analysis Primary data collection Modelling
#29 (Nelwan et al., 2016) HIV testing and counselling/HIV rapid test/not POC Indonesia Prisoner (age not specified) Outpatient clinic in prison 3 years Case–control study Cost analysis Primary data collection Modelling
#30 (Luong Nguyen et al., 2018)

HIV voluntary counselling and testing/HIV rapid test/not POC, comparing:

#1 Current testing coverage of 62%

#2 Scale up testing coverage to 90%

Kenya General population (age not specified) Health facility 20 years Modelling Cost-effectiveness analysis and budget impact analysis Published literature/data Modelling
#31 (Rely, 2003)

HIV counselling and testing/HIV rapid test/not POC, comparing:

#1 Status quo (with 4% testing coverage)

#2 Increase in coverage to 85%

Mexico Pregnant women (age not specified) Health facility Lifetime Modelling Cost-effectiveness analysis Published literature/data Modelling
#32 (Tchuenche et al., 2018) VEID/DNA-PCR/not POC Lesotho HIV-exposed infants (0–2 weeks) Health facility 1 year Retrospective observational study Cost analysis Primary data collection Modelling
#33 (Verstraaten et al., 2017) HIV voluntary counselling and testing/HIV rapid test/not POC Indonesia FSWs (age not specified) Mobile VCT services 1 year Cost analysis Primary data collection Modelling
#34 (Zang et al., 2016)

HIV testing, comparing:

#1 One4All (include testing, counselling, CD4 results, and viral load)/HIV rapid test/POC

#2 Standard care/HIV rapid test+ western blot confirmatory test/POC

China General population (aged 15–64 years old) Hospital 1, 5 and 25 years Modelling Cost-effectiveness analysis alongside clustered randomized trial Published literature/data Modelling
#35 (Zhang et al., 2015)

HIV testing/type of test not specified/not POC, comparing

#1 Status quo

#2 Reach universal coverage by 2015

#3 Reach universal coverage by 2017

#4 Reach universal coverage by 2022

Thailand MSM (age not specified) Health facility 3-,5-and 10-years Modelling Cost-effectiveness analysis Primary data collection Modelling

90–90–90 target: 90% of all people living with HIV will know their HIV status, 90% of all people with diagnosed HIV infection will receive sustained antiretroviral therapy and 90% of all people receiving antiretroviral therapy will have viral suppression. ANC, antenatal care; aPS, assisted partner service; ART, antiretroviral treatment; CD4, cluster of differentiation 4; DNA-PCR, deoxyribonucleic acid-polymerase chain reaction, a molecular diagnostic testing using DNA sequencing; HIVST, HIV self-testing; IDUs: injected drug users; MCF, male clients of female sex workers; POC: point-of-care; PTIT, HIV periodic testing and immediate treatment; PWID, people with injected drug; RPR, rapid plasma regain; VCT, HIV voluntary counselling and testing; VEID, very early infant diagnosis.