The objective of this study is to systematically review the effect of community-based approaches of HIV testing and counselling on CD4 at diagnosis, testing uptake, community HIV incidence, linkage to care rates, proportion of people receiving their first HIV test, and cost-effectiveness.
The PubMed, EMBASE, African Index Medicus, Index Medicus for the Eastern Mediterranean Region, Index Medicus for the Southeast Asia Region, Western Pacific Region Index Medicus, and Latin American and Caribbean Health Science Literature databases will be systematically searched without language, publication, date, or any other limits. The WHO International Clinical Trials Registry Platform, the Cochrane Central Register of Controlled Trials (CENTRAL), the International Standard Randomised Controlled Trial Number Register, and ClinicalTrials.gov will be searched for future and on-going studies. Experts in the field will be contacted to identify unpublished research and on-going studies.
Randomised trials and observational cohort studies.
Condition or domain being studied
HIV testing and counselling outside of health facilities.
People in generalised or concentrated HIV epidemics.
Community and facility-based HTC.
Facility-based HTC alone.
CD4 value at diagnosis, testing uptake (i.e. the proportion of the study population accepting HTC), community HIV incidence, linkage to care rates, proportion of people receiving their first HIV test, and cost effectiveness.
Data extraction, (selection and coding)
Data extraction will be completed using a standardised extraction form comprising five tables. The first table will summarise the characteristics of study participants. The second table will include information on the community-based testing approaches, including: pre-test demand creation, multi-disease components, study design, linkage to care, provision of incentives, and required number of visits. The third table will summarise the reported outcomes.
Subsequent tables will include studies with a comparator arm. The fourth table will summarise study methods (analytical model used and variables included in the model, information on the comparator arm, and information on outcome ascertainment). The final table will focus on quality assessment.
Risk of bias (quality) assessment
For the quality assessment, studies will be stratified based on study design (i.e. randomised controlled trial or observational study). Per recommendations from the Cochrane Collaboration, the Collaboration’s ‘Risk of bias’ tool will be used to assess bias in randomised trials with a comparator arm. This tool rates studies based on six criteria in four sources of bias. The presence of random sequence generation for allocation into intervention and comparator arms, and attempts to conceal this allocation, will be used to gauge selection bias. Blinding of study participants, personnel, and outcome assessment during the conduct and analysis of the studies will be used to gauge performance and detection bias. Incomplete outcome data, through review of participants excluded from outcome analyses or lost to follow-up, will be used to gauge attrition bias. Selective reporting of outcomes, time-points, subgroups, or analyses, will be used to gauge reporting bias. A criterion for other forms of bias will also be used. Based on these criteria, studies will be scored out of 100%.
Per recommendations from the Cochrane Collaboration, the Newcastle-Ottawa Quality Assessment Scale will be used to assess bias in observational studies with a comparator arm. This scale rates studies based on eight criteria in three sources of bias. Each criterion is worth one point except confounding, which is worth two points. Selection bias will be assessed using four criteria:
(1) representativeness of the cohort in the intervention arm the average person in the community from which study participants were drawn,
(2) representativeness of the cohort in the comparator arm to the intervention arm,
(3) ascertainment of HTC, and
(4) demonstration that the outcome was not present at the start of follow up.
Adjustment for a patient-level barrier (distance to testing site, income level, or education level) will be used to judge whether appropriate methods were used to address confounding. Measurement bias will be assessed using three criteria:
(1) assessment of outcome,
(2) adequate follow-up to detect the outcome, and
(3) <= 30% of participants lost to follow up during the study. Based on these criteria, studies will be scored out of 100%.
For randomised trials and observational cohort studies, studies scoring >= 67% will be considered to have a low risk of bias, those scoring 34-66% will be considered to have an unclear risk of bias, and those <= 33% will be considered to have a high risk of bias.
The quality of evidence will be assessed using the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) system to guide programme managers and other policy makers on national community-based HTC strategies.
Strategy for data synthesis
For statistical analyses, studies will be stratified based on the community-based testing approach. A funnel plot with the effect measures on the x-axis and standard error of the log for the effect measures on the y-axis will be created to assess publication bias and the Egger and Begg tests will be used to test the funnel plot’s symmetry. If studies are similar enough to combine, meta-analyses will be performed and statistical heterogeneity will be assessed. Effect measures will be entered as the natural log of the effect measure and standard error as the natural log of (95% upper limit ÷ 95% lower limit) ÷ 3.92. Fixed-effect models assume that the magnitude and direction of an intervention's effects are identical across studies and that observed differences among study results are due solely to chance. Random-effects models assume that the magnitude and direction of an intervention's effects are not identical but follow a distribution. Since it is possible that the magnitude and direction of community HTC’s impact could differ for reasons other than chance, random-effects models will be used for all analyses. An I-squared statistic will be used to measure heterogeneity. I-squared statistics near 25% indicate low heterogeneity, values near 50% indicate moderate heterogeneity, and those above 75% indicate high heterogeneity.
Analysis of subgroups or subsets
If there is moderate to significant heterogeneity in estimates, potential causes, including pre-test community sensitisation; study design; linkage to care; provision of incentives; and required number of visits, will be explored using sensitivity analyses. STATA version 10.0 will be used for all analyses.
Contact details for further information
Antiretroviral Treatment and HIV Care
Department of HIV/AIDS
Building D, 1st Floor, room 1005
World Health Organization
Avenue Appia 20
CH-1211, Geneva 27
Organisational affiliation of the review
World Health Organization
Dr Amitabh Suthar,
Anticipated or actual start date
22 May 2012
Anticipated completion date
28 September 2012
Conflicts of interest
Subject index terms status
Subject indexing assigned by CRD
Subject index terms
Community Health Services; Counseling; HIV Infections; Humans; Mass Screening; Patient Acceptance of Health Care; Preventive Health Services
Formal screening of search results against eligibility criteria
Risk of bias (quality) assessment
PROSPERO This information has been provided by the named contact for this review. CRD has accepted this information in good faith and registered the review in PROSPERO. CRD bears no responsibility or liability for the content of this registration record, any associated files or external websites.