- Open Access
Characteristics of users of HIV self-testing in Kenya, outcomes, and factors associated with use: results from a population-based HIV impact assessment, 2018
BMC Public Health volume 22, Article number: 643 (2022)
Background and setting
About 20% of persons living with HIV aged 15–64 years did not know their HIV status in Kenya, by 2018. Kenya adopted HIV self-testing (HIVST) to help close this gap. We examined the sociodemographic characteristics and outcomes of self-reported users of HIVST as our primary outcome.
We used data from a 2018 population-based cross-sectional household survey in which we included self-reported sociodemographic and behavioral characteristics and HIV test results. To compare weighted proportions, we used the Rao-Scott χ-square test and Jackknife variance estimation. In addition, we used logistic regression to identify associations of sociodemographic, behavioral, and HIVST utilization.
Of the 23,673 adults who reported having ever tested for HIV, 937 (4.1%) had ever self-tested for HIV. There were regional differences in HIVST, with Nyanza region having the highest prevalence (6.4%), p < 0.001. Factors independently associated with having ever self-tested for HIV were secondary education (adjusted odds ratio [aOR], 3.5 [95% (CI): 2.1–5.9]) compared to no primary education, being in the third (aOR, 1.7 [95% CI: 1.2–2.3]), fourth (aOR, 1.6 [95% CI: 1.1–2.2]), or fifth (aOR, 1.8 [95% CI: 1.2–2.7]) wealth quintiles compared to the poorest quintile and having one lifetime sexual partner (aOR, 1.8 [95% CI: 1.0–3.2]) or having ≥ 2 partners (aOR, 2.1 [95% CI: 1.2–3.7]) compared to none. Participants aged ≥ 50 years had lower odds of self-testing (aOR, 0.6 [95% CI: 0.4–1.0]) than those aged 15–19 years.
Kenya has made progress in rolling out HIVST. However, geographic differences and social demographic factors could influence HIVST use. Therefore, more still needs to be done to scale up the use of HIVST among various subpopulations. Using multiple access models could help ensure equity in access to HIVST. In addition, there is need to determine how HIVST use may influence behavior change towardsaccess to prevention and HIV treatment services.
HIV diagnosis through testing is the doorway to HIV prevention and antiretroviral therapy (ART) services , whose benefits are well documented [2, 3] and are critical for reducing transmissions and achieving epidemic control . To attain HIV epidemic control, the Joint United Nations Programme on HIV/AIDS (UNAIDS) set 90–90-90 targets: 90% of all people living with HIV (PLHIV) knowing their HIV status; of these, 90% receiving sustained ART; and of these, 90% having viral suppression by 2020 . In 2015, UNAIDS revised these targets to 95–95-95 by 2030 . In addition, the UNAIDS recommended broadening testing options to attain the first target, including community-based testing, home-based self-testing, events, location-based testing, community mobilization for testing, public–private partnerships, and voluntary and provider-initiated counseling. The Kenya Ministry of Health adopted these targets in the 2014/2015–2018/2019 Kenya AIDS Strategic Framework .
Even with comprehensive HIV testing strategies and a global increase in the percentage of people living with HIV (PLHIV) who know their HIV-positive status (from 71% in 2015 to 84% in 2020), testing gaps still exist, especially among men and young people. About 16% of PLHIV globally and 10% of adults aged 15 years and older in eastern and southern Africa were unaware of their HIV status in 2020  and about 20% of PLHIV aged 15–64 years were unaware of their HIV status in Kenya in 2018 . Several studies have demonstrated high acceptability and effectiveness of HIVST as a strategy for reaching men and young people [10,11,12,13]. In its 2015 guidelines, the World Health Organization (WHO) recommended HIV self-testing as an effective strategy to narrow the gap and increase HIV status knowledge among PLHIV . In 2016, WHO’s HIVST and assisted partner notification services guidelines emphasized HIVST as a strategy to help identify PLHIV . Kenya adopted these WHO guidelines and rolled out HIVST guidelines that included both oral and blood-based HIVST . In Kenya, studies continue to show feasibility and acceptability of HIVST among diverse users in the population [16,17,18,19].
Despite studies showing high acceptability for HIVST, few studies have looked at prevalence of HIVST use at the population level . In Zimbabwe and Malawi a population based survey found 1.2% prevalence of use of HIVST . In Kenya, after rolling out HIVST guidelines , information on the prevalence of HIVST use and the characteristics of HIVST users is limited. To address this, we used data from a population-based HIV impact assessment survey to characterize HIVST users in Kenya, HIV status outcomes, and factors associated with HIVST use.
Study design and population
The methods used in the 2018 Kenya Population-based HIV Impact Assessment (KENPHIA) 2018 have been previously described . Briefly, KENPHIA (October 2018–February 2019) was a cross-sectional household survey targeting adults aged 15–64 years and children ≤ 14 years old. The survey was a two-stage, stratified cluster sample design with the sampling frame that comprised of all households in the country, based upon the National Sample Survey and Evaluation Program version 5, (NASSEP-V) sampling frame. In the first stage, 800 clusters within the 47 counties of Kenya were selected using a probability proportional to size method. During the second stage, a sample of households was randomly selected within each cluster, using an equal probability method. We restricted our analysis to respondents aged 15–64 years who had ever been tested for HIV.
Data collection methods
Respondents were interviewed using a standardized PHIA questionnaire regarding household and demographic characteristics, bio-behavioral factors, and use of HIV-related services such as HIV testing services (HTS) and having ever used an HIVST kit. These data were collected on tablet computers and transmitted electronically to a central database. Since receipt of test results was a requirement for participation in the biomarker component, if an individual did not want to receive his or her HIV test result, this was considered a refusal, and the survey was concluded. For respondents consenting to receive test results, HIV home-based counseling and testing were conducted in each household per national guidelines via a sequential rapid-testing algorithm. The first screening test was with Determine HIV 1/2 RT; individuals with a non-reactive test result were reported as HIV negative. No further HIV testing was performed at home. Persons with a reactive result underwent confirmatory testing at home using a second rapid test (First Response HIV 1–2.0 Card Test [Premier Medical Corporation, Mumbai, India]). Those with a reactive result on both screening and confirmatory tests were classified as HIV positive. For quality assurance, whole-blood specimens collected in the household were transported to satellite laboratories. The first 50 tests from each tester and a fraction of negative specimens were tested using the national HIV rapid testing algorithm and confirmatory testing to determine field results’ accuracy. In addition, all HIV-positive specimens were confirmed with the Geenius HIV-1/2 supplemental assay (Bio-Rad Laboratories, Redmond, WA United States).
We included the following sociodemographic characteristics for this secondary analysis: sex, residence (urban/rural), age, education, marital status, and wealth quintile. We also included sexual behavioral factors such as sexual encounters in the last 12 months, lifetime sexual partners, and age at sexual debut. We selected the variables due to their relevance in HIVST uptake. Some variables, such as residence and geographic locations, were predetermined from the sampling frame at the survey cluster level. Wealth quintiles were calculated using an established process considering household possessions and income. We categorized the age in years into age bands. Our primary outcome was the prevalence of HIVST use and characteristics associated with HIVST users. The respondents reported their sex, age, education, marital status, and household possessions, and HIVST use during face-to-face interviews. We included the HIV test results by merging the laboratory results with the individual questionnaire response datasets for respondents who consented to a blood draw and testing.
We used PROC SURVEYFREQ in SAS to compare the independence of weighted proportions using the Rao-Scott chi-square statistical test, accounting for the sample design. We used jackknife weights for variance estimation. We tested for associations of sociodemographic, behavioral, and HIV testing services utilization with HIVST and presented both unadjusted and adjusted odds ratios. For the unadjusted logistic regression model, the factors were selected a priori for comparability because they were relevant for the HIV program. In the bivariate analyses, significant covariates at p < 0.05 level were then fitted into a multivariable logistic regression model. We additionally assessed for collinearity of factors in the multivariate model and determined that they were not collinear. In all analyses, p-values < 0.05 were considered statistically significant.
Of the 30,384 2018 KENPHIA participants aged 15–64 years, 23,673 (77.9%) had ever tested for HIV; of these, 23,581 (99.6%) responded to the HIVST question (Fig. 1).
Those who reported to have ever self-tested were 937, 4.0% (95% confidence interval (CI): 3.7–4.6). Most of the respondents who never had self-tested came from urban areas 50.8%, and residents of rural areas had the highest proportion of non-self-testers, 60%, (p < 0.001). The older respondents aged ≥ 50 years and younger respondents, 15–19 years had the lowest percentage of self-testers, 7.0%, and 7.3%, respectively, (p < 0.001). The highest proportion of self-testers was persons who had secondary education or higher 38.9% (95% CI: 34.3—43.5), p < 0.001, or had never been married 50.0% (95% CI: 44.9—55.1), p = 0.033, or were wealthiest 31.5% (95% CI: 25.2—37.9), p < 0.001, or had sex within the past 12 months 78.9% (95% CI: 74.9–82.4), p < 0.001, or respondents who had ≥ two lifetime sexual partners 66.5% (95% CI: 62.2—70.8), p < 0.001, and respondents who had their sexual debut at the age 15–19 years 55.4% (95% CI: 50.8—60.0), p = 0.022, (Table 1).
Prevalence of HIVST use varied by region, with Nyanza region having the highest prevalence, 6.4%, p = < 0.001 compared to other regions (Fig. 2).
Factors individually associated (unadjusted) with having ever self-tested for HIV were: living in an urban compared to rural setting; being 20–34 years compared to 15–19 years old; completion of primary or secondary education compared to no primary education; having never married compared to being widowed; wealth status in the second to the fifth quintile compared to the lowest quintile; having had sex in the past 12 months compared to none and having one or more partners compared to none. Factors independently (adjusted) associated with having ever self-tested for HIV were secondary education adjusted odds ratio (aOR), 3.5 [95% CI: 2.1–5.9]) compared to no primary education, being in the third (aOR, 1.7 [95% CI: 1.2–2.3]), fourth (aOR, 1.6 [95% CI: 1.1–2.2]), or fifth wealth quintiles (aOR, 1.8 [95% CI: 1.2–2.7]) compared to the first wealth quintile and one-lifetime sexual partner (aOR, 1.8 [95% CI: 1.0–3.2]) or ≥ 2 sexual partners (aOR, 2.1 [95% CI: 1.2–3.7]) compared to those with none (Table 2).
HIV prevalence rates were 4.9% (95% CI: 3.1%–6.7%) among respondents who had ever self-tested for HIV and 6.0% (95% CI: 5.5%–6.4%) among those who never had self-tested for HIV. HIV prevalence varied significantly comparing those who had ever self-tested vs. those who had never self-tested among; persons with incomplete primary education 12.9% vs 8.0% (p = 0.015), with secondary education 0.5% vs 2.5% (p < 0.001), were never married 0.9% vs 2.6% (p = 0.016), were in the lowest wealth quintile 13.4% vs 6.6% (p = 0.012), or who had ≥ 2 sexual partners 4% vs 7.7% (p = 0.030) (Table 3).
Among the survey respondents who reported having had an HIV test, we found that 4.0% reported having ever taken an HIV self-test. Comparatively, among those who had had an HIV test in Malawi and Zimbabwe, 1.0% and 1.2%, respectively, reported having ever taken an HIV self-test in a population based survey . The results also showed geographic variation in the prevalence of HIVST use. This geographic variation largely mirrors HIV prevalence in the country and the corresponding efforts to increase access to HIV prevention and treatment services in Kenya. The relatively low prevalence of HIVST provides an opportunity to scale up the use of HIVST kits to meet the demand for HIVST among various populations, as has been demonstrated in previous studies. For example, in a prior survey in Kenya, 70% of the respondents reported willingness to use HIVST privately or at home (men, 74%; women, 67%) . Similarly, other studies have reported high acceptability rates of HIVST among the general population [23, 24] and key populations . To increase access to HIVST, the Ministry of health in Kenya developed the HIVST guidelines , informed by multiple studies on HIVST acceptability and impact to reach populations [26, 27].
Among those reporting to have ever used an HIV self-test, we found that participants aged 20–29 years were more likely to use HIVST kits, and those older than 50 years were less likely to self-test. A study in Malawi found a similar pattern of decreasing the use of HIVST across older age groups. This was attributed to possibly frequent access to health facilities by the younger population, where HIVST are distributed . These findings could help inform Kenya’s HIV testing program strategies, whose current HIVST objective is to target partners of pregnant and breastfeeding women, men and young persons to close the gaps in the knowledge of HIV status among these groups . However, even though these target populations have a relatively higher prevalence of HIVST use, further scale-up is still needed to expand the prevalence of HIVST use across all age groups. A large-scale rollout of HIVST with different approaches has been practiced in Malawi, Zambia, and Zimbabwe . Similarly, Kenya’s HIVST guidelines provide multiple distribution channels that include facility-based, community-based, and private-sector channels that utilize pharmacies where individuals can buy self-testing kits  at approximately five US Dollars . At health facilities, and private pharmacies, there is an option of utilizing the HIVST under the guidance of a healthcare worker (assisted HIVST).
Higher wealth quintiles were associated with higher HIVST prevalence, possibly because of the higher purchasing power among those respondents . This finding suggests possible inequity in access to HIVST. Furthermore, in this survey, those in the lowest quintile reported a higher prevalence of HIV but reported the most insufficient use of HIVST. This finding underlines the need to ensure all populations are reached, irrespective of socioeconomic status. Demand for HIVST is price-sensitive [31, 32], and price may create inequalities to access where the pricing is considered out of reach to segments of the population. A mix of methods [33, 34], including free distribution of HIV self-tests , secondary distribution , use of vouchers , text message reminders , and internet-based approaches , may help promote access and use in targeted populations.
We also found higher use of HIVST by those with two or more lifetime sexual partners. This could be associated with participants’ perception of their susceptibility to infection . Individuals with multiple sexual partners are at higher risk of HIV infection [39, 40] and perceived susceptibility has been described as a predictor of HIVST use . Moreover, in this survey, among individuals with ≥ two lifetime sexual partners, those who reported having self-tested for HIV had a lower prevalence of HIV compared to those who had never been tested. This finding warrants further investigation to determine how use of HIVST may influence behavior change towards access of HIV prevention and treatment services.
Although HIVST offers a convenient approach to knowing one’s HIV status, linkage to treatment and other prevention services remains a challenge to be addressed , considering privacy and confidentiality is a key advantage of HIVST. Financial incentives  and interactive voice response systems  have demonstrated potential in increasing the linkage to HIV treatment services. Monitoring ART enrollment and population-based surveys have been proposed for programs to monitor linkage to treatment from HIVST . More research is warranted to explore ways of increasing access to HIVST and linkage to prevention and treatment services among all populations.
Study strengths and limitations
The study had a large sample size from a survey distributed across the country, thus providing a nationally representative sample.
Our findings are subject to several limitations. First, the HIVST question posed during the survey may have been subject to social-desirability bias in responses like all questions asked in face-to-face interviews. However, the HIVST prevalence is comparable to others reported elsewhere in similar PHIA surveys. Second, the KENPHIA survey was not powered to characterize HIVST use in smaller geographical regions but provided national estimates.
From the survey, among those who reported having ever tested for HIV, 4.0% reported having ever self-tested for HIV. Those living in urban areas had a higher prevalence of HIVST use compared to those living in rural areas. Younger age, higher education levels, being of higher wealth quintile, and having multiple lifetime sexual partners were associated with the use of HIVST. While progress has been made by the program in Kenya to roll out HIVST, more may still need to be done to scale up the use of HIVST among various subpopulations and these results could serve as a baseline. The Kenya program could explore using multiple access models to help ensure equity in access to HIVST. In addition, there is a need to determine the impact of HIVST on behavior change towards access to prevention and HIV treatment services.
Availability of data and materials
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
Acquired Immunodeficiency syndrome
Adjusted odds ratio
HIV: Human immunodeficiency virus
HIV Testing services
Kenya Population-based HIV Impact Assessment
National Sample Survey and Evaluation Program version 5
Population-based HIV Impact Assessment
People Living with HIV
The Joint United Nations Programme on HIV/AIDS
United States of America
World health organization
World Health Organization. Consolidated guidelines on HIV testing services 2015. WHO; 2015. https://doi.org/10.1111/j.1749-6632.1990.tb15103.x. https://www.who.int/publications-detailredirect/9789241508926.
Tanser F, Baernighausen T, Graspa E, Zaidi J. Newell M.-L. High Coverage of ART Associated with Decline in Risk of HIV Acquisition in Rural KwaZulu-Natal, South Africa. Science. 2013;339:966–72.
Grinsztejn B, et al. Effects of early versus delayed initiation of antiretroviral treatment on clinical outcomes of HIV-1 infection: Results from the phase 3 HPTN 052 randomised controlled trial. Lancet Infect Dis. 2014;14:281–90.
PEPFAR. Controlling the epidemiC: delivering on the promise of an aids-free generation. 2015.
UNAIDS. 90-90-90 An ambitious treatment target to help end the AIDS epidemic. United Nations; 2014. https://doi.org/10.1177/002194360103800306.
UNAIDS. Fast-Track. Ending the AIDS Epidemic by 2030. 2014. https://www.unaids.org/sites/default/files/media_asset/90-90-90_en.pdf.
NASCOP. The Kenya HIV Testing Services Guidelines. Nascop; 2015.
UNAIDS. Confronting inequalities- Lessons for pandemic responses from 40 years of AIDS. Global AIDS Update. 2021.
NASCOP. Kenphia 2018 Preliminary Report. Nascop; 2020. p. 1–26. https://doi.org/10.1017/CBO9781107415324.004. https://www.health.go.ke/wp-content/uploads/2020/02/KENPHIA-2018-PREL-REP-2020-HR3-final.pdf.
Izizag BB, et al. Factors associated with acceptability of HIV self-testing (HIVST) among university students in a Peri-Urban area of the Democratic Republic of Congo (DRC). Pan African Med J. 2018;31:1–9.
Brown III W, Carballo-Diéguez A, Marie John R, Schnall R. Information, Motivation, and Behavioral Skills of High-Risk Young Adults to Use the HIV Self-Test. 2016. https://doi.org/10.1007/s10461-016-1309-x.
Hatzold K, et al. HIV self-testing: breaking the barriers to uptake of testing among men and adolescents in sub-Saharan Africa, experiences from STAR demonstration projects in Malawi, Zambia and Zimbabwe. J Int AIDS Soc. 2019;22:43–52.
Chikwari CD, Dringus S, Ferrand RA. Barriers to, and emerging strategies for, HIV testing among adolescents in sub-Saharan Africa. Curr Opin HIV AIDS. 2018;13:257–64.
World Health Oraganization. GUIDELINES ON HIV SELF-TESTING NOTIFICATION. 2016.
NASCOP. An operational manual for the delivery of HIV Self-Testing and assisted partner notification services in Kenya. Nairobi: NASCOP; 2019.
Kalibala S. et al. Factors associated with acceptability of HIV self-testing among health care workers in Kenya. AIDS Behav. 2014;18.
Thirumurthy H. et al. Acceptability and feasibility of a novel approach to promote HIV testing in sexual and social networks using HIV self-tests. J Int AIDS Soc. 2015;18.
Ngure K, et al. Feasibility and acceptability of HIV self-testing among pre-exposure prophylaxis users in Kenya. J Int AIDS Soc. 2017;20.
Pintye J, et al. Acceptability and outcomes of distributing HIV self-Tests for male partner testing in Kenyan maternal and child health and family planning clinics. AIDS. 2019;33.
Rivera AS, et al. Implementation outcomes of HIV self-testing in low- And middle-income countries: A scoping review. PLoS ONE. 2021;16.
Johnson C, et al. Use and awareness of and willingness to self-test for HIV: An analysis of cross-sectional population-based surveys in Malawi and Zimbabwe. BMC Public Health. 2020;20:779.
Waruiru W, et al. The Kenya AIDS indicator survey 2012: Rationale, methods, description of participants, and response rates. J Acquir Immune Defic Syndr. 2014;66:1–19.
Kurth AE, et al. Accuracy and Acceptability of Oral Fluid HIV Self-Testing in a General Adult Population in Kenya. AIDS Behav. 2016. https://doi.org/10.1007/s10461-015-1213-9.
Mugo PM, et al. Uptake and acceptability of oral HIV self-testing among community pharmacy clients in Kenya: A feasibility study. PLoS ONE. 2017;12:1–15.
Burke VM, et al. HIV self-testing values and preferences among sex workers, fishermen, and mainland community members in Rakai, Uganda: A qualitative study. PLOS ONE. 2017;12:e0183280.
Masters SH, et al. Promoting Partner Testing and Couples Testing through Secondary Distribution of HIV Self-Tests: A Randomized Clinical Trial. PLOS Med. 2016;13:e1002166.
ichangi A, et al. Impact of HIV self-test distribution to male partners of ANC clients: Results of a randomized controlled trial in Kenya. J Acquir Immune Defic Syndr. 2018;79:467–73.
Indravudh PP, et al. Who is Reached by HIV Self-Testing? Individual Factors Associated With Self-Testing Within a Community-Based Program in Rural Malawi. J Acquir Immune Defic Syndr (1999). 2020. https://doi.org/10.1097/QAI.0000000000002412.
KL, et al. Private sector HIV self-testing in Kenya: Insights from a Mystery shopper study. in Abstract IAS 2019. 2019.
Kenya national bureau of statistics. Quarterly Labour Force Report, Quarter 1 2019. 2019. https://www.knbs.or.ke/download/quarterly-labour-force-report-first-quarter-2019/.
Chang W, et al. Effect of Prices, Distribution Strategies, and Marketing on Demand for HIV Self-testing in Zimbabwe: A Randomized Clinical Trial. JAMA Network Open. 2019;2.
Sibanda EL, et al. Applying user preferences to optimize the contribution of HIV self-testing to reaching the “first 90” target of UNAIDS Fast-track strategy: results from discrete choice experiments in Zimbabwe. J Int AIDS Soc. 2019;22:33–42.
Nwaozuru U, et al. Preferences for HIV testing services among young people in Nigeria. BMC Health Serv Res. 2019;19:1003.
Okal J, Obare F, Matheka J, Tun W. Potential outlets for distribution of HIV oral self-test kits in Kenya: an exploratory study. 20th International AIDS Conference, July 20-25, 2014, Melbourne, Australia. 2014.
Marlin RW, et al. Piloting an HIV self-test kit voucher program to raise serostatus awareness of high-risk African Americans, Los Angeles. BMC Public Health. 2014;14.
Kelvin EA, et al. A Randomized Controlled Trial to Increase HIV Testing Demand Among Female Sex Workers in Kenya Through Announcing the Availability of HIV Self-testing Via Text Message. AIDS Behav. 2019;23:116–25.
De Boni RB, et al. An internet-based HIV self-testing program to increase HIV testing uptake among men who have sex with men in Brazil: Descriptive cross-sectional analysis. J Med Internet Res. 2019;21:1–15.
Janz NK, Becker MH. The Health Belief Model: A Decade Later. Health Educ Behav. 1984;11:1–47.
Diero LO, et al. Characteristics of HIV infected patients cared for at “Academic Model for the Prevention and Treatment of HIV/AIDS” clinics in Western Kenya. East Afr Med J. 2006;83:424–33.
Rositch AF, et al. HIV infection and sexual partnerships and behaviour among adolescent girls in Nairobi, Kenya. Int J STD AIDS. 2012;23:468–74.
Grispen JE, Ronda J, Dinant G, De Vries GJ, Van Der Weijden NK. To test or not to test: A cross-sectional survey of the psychosocial determinants of self-testing for cholesterol, glucose, and HIV. BMC Public Health. 2011;11:112.
Johnson CC, et al. Examining the effects of HIV self-Testing compared to standard HIV testing services: A systematic review and meta-Analysis. J Int AIDS Soc. 2017;20.
Choko AT, et al. HIV self-testing alone or with additional interventions, including financial incentives, and linkage to care or prevention among male partners of antenatal care clinic attendees in Malawi: An adaptive multi-arm, multi-stage cluster randomised trial. PLoS Med. 2019;16.
Majam M, Phatsoane M, Rhagnath N, Quaife M. High self-reporting of HIV self-test results through an interactive voice response telephone line in inner city Johannesburg.
Choko AT, et al. Measuring linkage to HIV treatment services following HIV self‐testing in low‐income settings. J Int AIDS Soc. 2020;20.
We acknowledge the Kenya Ministry of Health, NASCOP, the Ministry of Planning and Devolution, and all partners for the scientific, strategic, and technical leadership through KENPHIA Principal Investigators: Dr. Peter Cherutich, Dr. Kigen Bartilol, Dr. Kevin M. De Cock, and Dr. Jessica Justman. We also thank the various planning organs of the KENPHIA through the National Executive Steering Committee, Council of Governors, and the KENPHIA Technical Working Group and Technical Sub-Committees from relevant survey partner institutions.
We thank the 14 community mobilization coordination officers, 1,600 community mobilizers, five regional coordination supervisory teams, 50 field data collection teams, six roving satellite laboratory teams, and the central laboratory team who worked tirelessly to collect high-quality data. Kenyans from all walks of life across the country participated in this survey. We also wish to acknowledge ICAP at Columbia University, who made this survey possible through financial support from PEPFAR and the Global Fund, and the CDC’s technical support.
The household head consented to the household questionnaire on behalf of the household; heads of households were adults aged 18–64 years or emancipated individuals with no parent or guardian or not living with their parent/guardian. Informed consent was documented electronically on the tablet with a signature or other mark by the interviewer on the consent form’s designated field. To participate in the study, adolescents aged 15–17 years provided written assent, and their parents or guardians provided written informed consent.
This KENPHIA survey has been supported by the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) through the United States Centers for Disease Control and Prevention (CDC) under the terms of Cooperative Agreement #U2GGH001226. The United States Agency for International Development (USAID), and the Global Fund to Fight AIDS, TB, and Malaria provided additional support.
Ethics approval and consent to participate
This study was approved by the Kenya Medical Research Institute’s Ethical Review Committee, the US Centers for Disease Control and Prevention’s Institutional Review Board, and the Committee on Human Research of the University of California, San Francisco. In addition, the Kenya Ministry of Health, the National AIDS and STI Control Program, and the President’s Emergency Plan for AIDS Relief funding agencies provided concurrence. All the PHIA protocols were carried out in accordance with relevant guidelines and regulations. The Protocols were also reviewed per the CDC IRB human research protection procedures. Columbia University IRB additionally reviewed and approved the 2018 PHIA protocol.
Consent for publication
Individual data not presented. Not applicable.
The authors declare that they have no competing interests. The findings and conclusions of this article are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention, Ministry of Health Kenya, National AIDS & STI Control Program, National HIV Reference Laboratory, Nairobi, Kenya.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Mwangi, J., Miruka, F., Mugambi, M. et al. Characteristics of users of HIV self-testing in Kenya, outcomes, and factors associated with use: results from a population-based HIV impact assessment, 2018. BMC Public Health 22, 643 (2022). https://doi.org/10.1186/s12889-022-12928-0
- HIV testing
- HIV self-testing
- Population-based HIV Impact Assessment (PHIA)