Low coverage of HIV testing among adolescents and young adults in Nigeria: Implication for achieving the UNAIDS first 95

Anthony Idowu Ajayi; Oluwafemi Emmanuel Awopegba; Oluwafemi Atanda Adeagbo; Boniface Ayanbekongshie Ushie

doi:10.1371/journal.pone.0233368

. 2020 May 19;15(5):e0233368. doi: 10.1371/journal.pone.0233368

Low coverage of HIV testing among adolescents and young adults in Nigeria: Implication for achieving the UNAIDS first 95

Anthony Idowu Ajayi ^1,^*, Oluwafemi Emmanuel Awopegba ², Oluwafemi Atanda Adeagbo ^3,⁴, Boniface Ayanbekongshie Ushie ¹

Editor: Olanrewaju Oladimeji⁵

PMCID: PMC7237011 PMID: 32428005

Abstract

Background

Most studies on HIV testing among young people in Nigeria are not nationally representative. As such, recent nationally representative data, such as the Multiple Indicator Cluster Survey (MICS), could help assess the current level of HIV testing among young people, a key target population for HIV prevention in the country. In this study, we examined the coverage and factors associated with HIV testing among adolescents and young adults (AYA).

Methods

We used the data for 14,312 AYA that examined recent and lifetime HIV testing from the 2017 MCIS. Our outcomes of interest were ever tested for HIV and recently tested for HIV. We examined the association between socio-demographic factors (e.g., age, marital status, education attainment, wealth status), stigma belief, exposure to media and HIV knowledge, and uptake of HIV testing using adjusted and unadjusted logistic regression models.

Results

Less than a quarter of the AYA (23.7%) had ever tested for HIV, and an even lower proportion (12.4%) tested in the year preceding the survey. More females (25.4%) compared to males (20.8%) had ever tested for HIV. Young people who were aged 20–24 years (AOR 1.52, 95% CI 1.34–1.72), married (AOR 2.42, 95% CI 1.98–2.97), had higher educational attainment (AOR 5.85, 95% CI 4.39–7.81), and belonged to the wealthiest quintile (AOR 1.99, 95% CI 1.53–2.60), had higher odds of having ever tested for HIV compared to those aged 15–19 years, never married, had no formal education and belonged to the poorest wealth quintile. Also, those who had positive stigma belief towards people living with HIV (AOR 2.93, 95% CI 2.47–3.49), had higher HIV knowledge (AOR 1.62, 95% CI 1.24–2.11), and higher media exposure (AOR 1.64, 95% CI 1.36–1.97), had higher odds of having ever tested compared to those who had more negative stigma belief, had low knowledge of HIV and low media exposure.

Conclusion

The HIV testing coverage among AYA in Nigeria is well below the national target of 95% indicated in the national HIV/AIDS strategic framework (2017–2021). Also, the low rate of HIV testing found in this study means realising the UNAIDS first 95 will require interventions targeting AYA. These interventions should focus on improving young people's knowledge of HIV, reducing negative stigma belief through media campaigns and increasing access to HIV testing through home-based testing and "opt-out" strategy at the point of care.

Background

Despite the significant impact of antiretroviral therapy (ART) and other preventive strategies in the reduction of new HIV infections and AIDS-related deaths, HIV remains the leading cause of deaths among adolescents and young adults in sub-Saharan Africa (SSA)[1, 2]. Close to 66% of the 5,000 new HIV infection a day in SSA. Late diagnosis and poor adherence to ART and retention in care are among the main reasons for poor treatment outcomes in this age cohort. There is evidence that less than a quarter of young adults in sub-Saharan Africa have ever tested for HIV, and the rate is even much lower among young men, and for those who are HIV+, the testing is usually performed late[3–6]. Early diagnosis of HIV is a critical first step to initiating ART, preventing new HIV infections and AIDS-related deaths, and ensuring good quality of life and wellbeing for young people potentially living with HIV[1].

Adolescents and young adults (AYA) (15–24 years) bear a disproportionate burden of HIV, particularly for new HIV infection[1]. Approximately 510,00000 [300,000–740,000] AYA were newly infected with HIV in 2018[7] and 61% of these new infection occurred in SSA[1]. What is more, adolescent girls in SSA account for four in five new infections[7]. Also, AYA are less likely to have tested for HIV, have the lowest level of adherence to ART and viral load suppression[1]. For example, a study shows that only 20.7% adolescents in South Africa achieved complete adherence compared with 40.5% among adults[8]. The study further reveals that 43.6% of adolescents achieved viral suppression at 24 months of follow up compared with 62.3% among adults[8]. Screening for HIV is an important public health intervention required to reduce the burden of HIV, especially among AYA who are most at risk of contracting the infection[9]. HIV testing is beneficial not only for individuals that test positive but also for those who return a negative result given that uptake of HIV testing promotes preventive behaviours [10, 11]. The World Health Organisation (WHO) recommended "Universal test and treat" as the approach for eliminating new HIV infections [12].

Recognising the centrality of HIV testing to averting new infections, the UNAIDS set the ambitious 95-95-95 target towards ending the HIV epidemic by 2030. The target aims to ensure that by 2030, 95% of all people living with HIV will know their HIV status, 95% of all people with diagnosed HIV infection will receive sustained antiretroviral therapy, and 95% of those on treatment will have suppressed viral load[13]. A newly published study in the New England Journal of Medicine[9] has established the effectiveness of the "universal test and treat" in reducing new HIV infection, further underscoring the need for scaling up of HIV testing. Nigeria needs to scale up the universal test and treat, especially among young people who are most at risk[9], to achieve a significant reduction in the rate of new infections.

Several studies have focused on factors hindering the uptake of HIV testing with lack of access, fear of being diagnosed positive, perceived low risk of contracting HIV, fear of stigmatisation, and the perceived psychological burden of living with HIV being among the most reported barriers [5, 14–19]. In contrast, physical health deterioration, knowing someone who died as a result of HIV, knowing one's partner HIV status, HIV knowledge, couples’ open communication about HIV, expanding access to HIV testing and treatment, as well as having a social support network and the guarantee of anonymity and confidentiality are factors that facilitate HIV testing uptake [5, 20–22].

At 1.5%, Nigeria has a low prevalence of HIV, but the country's large population of >200 million[23] means that the number of people living with HIV in the country is substantial [24, 25]. A significant proportion (up to 34.1%) of new infections occurs among adolescents and young adults in the country[2]. Lack of comprehensive sexual health education, sexual and gender-based violence, poor access to sexual and reproductive health services, and poverty are among the drivers of new HIV infections in the country [26]. The lack of access to HIV testing, especially in rural areas, is also among the factors fueling new HIV infection [27]. However, in the past decade, significant effort has been made towards scaling up of access to HIV testing in the country [28, 29]. A study examining the trend in HIV testing among AYA from 2003 to 2013 shows that testing uptake has increased from 14.6% among males to about 22% and from 5.9% to 19.4% among females [4]. Nevertheless, the level of HIV testing uptake among young people in Nigeria is low compared to countries like Kenya, Zambia, and South Africa [4]. What is more, only 38% of people living with HIV (PLHIV) are aware of their status in Nigeria, which has harmful consequences for new infections, treatment outcomes, and cost of care.

Most studies on HIV testing among young people in Nigeria are not nationally representative or are now outdated [4, 5, 19, 30]. As such, recent nationally representative data, such as the Multiple Indicators Cluster Survey (MICS), could help assess the current level of HIV testing among young people and the level of progress recorded since the scaling up of HIV testing services in Nigeria. Given this context, the present study aims to determine the level of HIV testing among adolescents and young adults in Nigeria. Also, the study examines the influence of demographics (such as age, sex, education, knowledge of HIV), behavioural (sexual activity, and condom use), community/social (knowledge, stigma and media exposure) and contextual factors (household wealth, geopolitical zones and urban/rural residence) on uptake of HIV testing.

Health behavioural theories, like the Health Belief Model, have highlighted the role of knowledge as a critical factor influencing the use of services[31–34]. Thus, we hypothesise that knowledge of HIV is associated with increased odds of uptake of HIV testing. With improved knowledge of HIV, individuals can assess their risk of contracting HIV, access HIV testing, and initiate ART. Furthermore, better knowledge of HIV could help reduce stigma behaviour, which is a significant barrier to uptake of HIV testing in settings in SSA [14, 18, 35]. Advances in HIV treatment now mean HIV is no longer a death sentence and with undetectable viral load (undetectable means untransmittable), implying zero risks of HIV transmission [36]. Spreading this message is critical to reducing HIV stigma and increase uptake of HIV testing. Our primary proposition in this study is that expanding access to HIV testing alone, without improving HIV knowledge, and addressing internalised HIV-related stigma, is not enough to increase uptake of HIV testing. In other words, focusing on improving HIV knowledge of young people is as important as expanding access to HIV testing. This study aligns with the global focus on meeting the UNAIDS' first 95', which aims to ensure 95% of people living with HIV know their status by 2020 and which Nigeria aims to achieve by 2021. Achieving this aim in Nigeria will require evidence-informed policies.

Materials and methods

The data used in this study were from the fifth multiple indicators cluster survey (MICS) for Nigeria, which is freely available upon request at http://mics.unicef.org/surveys. The 5th multiple cluster survey was carried out from September 2016 to January 2017 throughout the country. The MICS was a cross-sectional study conducted across all the geopolitical zones in 37, 440 households in Nigeria. The sample size was representative of the country and also of the six geopolitical zones.

Sampling methods

The survey adopted a multi-stage cluster sampling approach, designed to give reliable estimates for numerous indicators on men, women and children's wellbeing, at national, urban/rural, geopolitical zone and state levels in the country. The states were identified as the sampling strata, while the Enumeration Areas (EAs) were the Primary Sampling Units (PSUs). At the first stage, 60 EAs were selected systematically within each (34) states and Abuja (FCT), while 120 EAs each were selected from Kano and Lagos states. In the second stage, a systematic sample of 16 households was taken from each of the selected EAs. Out of 37,440 households sampled, 36,176 women of reproductive age (15–49 years) and 17,868 men were interviewed.

Ethical statement

We did not need to seek ethical approval for the study given that this is a secondary analysis of publicly available de-identified data.

Study population

There were 52,690 MICS respondents (16,514 men and 36,176 women). However, the focus of this study was AYA 15–24 yrs, who comprised 18,494 (35.1% out of all respondents), who met the selection criteria. The analysis was further limited to 14, 312 AYA who responded to the questions on HIV testing. the overview of the study sample is presented in Fig 1.

Variables and measurements

Our dependent variables of interest in this study are two-category nominal measure of uptake of HIV testing. We used two different measures of HIV testing, focusing on having ever tested for HIV and recency of HIV testing (defined as the uptake of HIV test in the past year). The responses were dichotomised into Yes or No with yes coded as "1" and no coded as "0". Participants who tested for HIV in the previous year before the survey were categorised as recently tested for HIV and assigned "1" and those who did not were assigned "0".

We have three sets of explanatory variables, individual-level factors (demographics, behavioural (sexual activity, and condom use, knowledge, stigma, and media exposure), household-level factor (household wealth) and contextual factors (geopolitical zones and urban/rural residence). The demographic variables are age (15–19 and 20–24), sex (male and female), marital status (currently married, formerly married and never married), and level of education (no formal education, primary, secondary and tertiary). The behavioural variables are “ever had sex” and “condom use”, which have dichotomous responses coded as "1" if reported Yes, and "0" if No.

The knowledge of HIV was constructed to measure the respondents' awareness about the virus, transmission routes, and how to prevent HIV transmission. Seven relevant questions were contained in the MCIS and were used to assess participants' knowledge of HIV. Each respondent was given a score between 0 to 7, depending on the number of questions answered correctly. The first question probed whether they had ever heard of AIDS. The second question asks the respondents whether they could avoid the HIV/AIDS virus by having one uninfected partner. The third asks whether the respondents could get the HIV/AIDS virus through supernatural means. The fourth question asks the respondents whether they could avoid the HIV/AIDS virus by using a condom correctly every time. The fifth asks the respondents whether they could get the HIV/AIDS virus from mosquito bites. The sixth question asked whether the respondents could get the HIV virus by sharing food with a person who has HIV. The seventh asked the respondent whether a healthy-looking person may have AIDS virus. The range of scores was categorised as Low," "Moderate" and "High", with a score of 0–3 categorised as low knowledge, a score of 4–5 categorised as moderate knowledge and a score of 6–7 considered high knowledge.

Stigma belief is a misplaced fear of infection via everyday contact with those infected with HIV[35]. The dimension of internalised HIV stigma examined in this study is what is permitted by the five questions asked in the 5th MICS, all of which have dichotomous responses (Yes/No). The first question asks the respondents whether a female teacher with the HIV virus should be allowed to teach in school. The second asks whether the respondents would buy fresh vegetables from a shopkeeper living with HIV/AIDS. The third question poses whether the respondent would want it to remain a secret if a household member became infected with the HIV virus. The fourth asks the respondents whether they would be willing to care for a person with HIV/AIDS in the household. The fifth asks the respondents whether children with HIV should attend school. Exploratory factor analytic techniques suggest that these questions follow one underlying construct, with a Cronbach’s Alpha test scale of 0.72. Stigma belief was constructed and recoded as 1 "Extremely negative" 2 "Negative" 3 "Moderate" 4 "Positive" and 5 "Extremely positive".

The last critical independent variable, media exposure, is constructed from three variables on the frequency of exposure to media: reading print media, listening to the radio and watching television. The frequency of exposure was categorised as 1 "less than once a week" 2 "at least once a week" and 3 "almost every day". These were added up across all respondents to yield a total score of 0–9 per participant. The scores were recategorised as 1 "Low media exposure"(score of 0–3), 2 "Moderate media exposure" (score of 4–6) 3 "High media exposure" (score of 7–9) as used in other studies[4].

Household wealth was measured using the principal component analysis to surmise questions on types of roofing and general infrastructure in participants' home. The variable was already computed before making the data public. The contextual factors include geopolitical zones and residential area–classified as rural and urban.

Statistical analysis

Sample weights were used in all analyses to adjust for disproportionate sampling and to obtain unbiased population parameter estimates. Descriptive statistics such as percentages and frequencies were presented to describe the characteristics of the study respondents. A list-wise logistic regression model was fitted to investigate the influence of demographic, behavioural, community/social and contextual factors on ever and recent testing of HIV. Two models were fitted to investigate the relationship succinctly. Model 1 is the baseline model that examines the association between each of the individual-level factors, household wealth and contextual factors and uptake of HIV testing. Model 2 is a multivariable logistic regression that includes demographic, behavioural, community/social and contextual factors. The regression results were interpreted using odds ratios (OR), with OR > 1 indicating a higher likelihood, OR = 1 showing no likelihood difference and OR < 1 indicating a lower probability. The level of significance was set at 0.05, while a confidence interval (CI) of 95% was used. Stata software (version 14) was used for all data analyses.

Results

Descriptive findings

The weighted social, demographic, contextual, and behavioural characteristics of the study respondents are presented in Table 1. More than half (57.7%) of the participants were between 15 to 19 years old, 64.6% lived in rural areas, 63.2% were female; more than two-thirds (79%) were single (never married), and 64.5% had secondary or technical education. Knowledge of HIV and transmission routes was mostly high or moderate among the participants, while some participants exhibited stigma beliefs related to people with HIV. Access to media was low among most of the participants (57.3%) and over half of the respondents have ever had sex (56.2%), but only 5.8% reported condom use.

Table 1. Weighted sociodemographic, contextual and behavioural characteristics of study participants.

Characteristics	Frequency	Percent
Age group (in Years)
15–19	8255	57.68
20–24	6057	42.32
Gender
Female	9049	63.23
Male	5263	36.77
Marital Status
Never married	11310	79.02
Currently married	2833	19.79
Formerly married	169	1.18
Education
None	2529	17.67
Primary	1237	8.64
Secondary (& Tech)	9226	64.46
Higher	1320	9.22
Wealth Status
Poorest	1807	12.63
Second	2580	18.03
Middle	3196	22.33
Forth	3272	22.86
Richest	3457	24.15
Zone
North central	3616	25.27
North east	3055	21.35
North west	3055	21.35
South east	1692	11.82
South south	2157	15.07
South west	1784	12.47
Residence
Rural	9251	64.64
Urban	5061	35.36
Knowledge of HIV
Low	956	6.68
Moderate	5197	36.31
High	8159	57.01
Attitude towards HIV
Extremely Negative	3234	22.60
Negative	2283	15.95
Moderate	2320	16.21
Positive	3025	21.14
Extremely Positive	3450	24.11
Media Exposure
Low	8199	57.29
Moderate	4612	32.22
High	1501	10.49
Ever has sex
No	8036	56.15
Yes	6276	43.85
Condom Use
No	13488	94.24
Yes	824	5.76
Recently Tested HIV
No	12370	86.43
Yes	1942	13.57

Open in a new tab

Bivariate findings

Tables 2 and 3 present the proportion of respondents who have tested for HIV at any time or recently across demographic, behavioural, community/social and contextual factors. As Table 2 shows, only a quarter of AYA had ever tested for HIV; however, the proportion varies by demographic, behavioural, social and contextual factors. More females than males (25.4% vs 20.8%), young adults than adolescents (33.1% vs 16.7%), tertiary-educated than no formal education (52.9% vs 10.4%), and urban than rural residents (27.2% vs 21.3%) had ever undergone HIV. Likewise, the rate of lifetime uptake of HIV testing was higher among participants who had ever engaged in sex (33.6%), exposed to media (39.9%), held positive attitude to people living with HIV (34.0%) and who had higher HIV knowledge (29.4%) compared to those who never had sex (16.5%%), never used condoms (22.0%), had low media exposure (18.3%), held extremely negative stigma belief (13.0%), and who had low knowledge of HIV (12.4%), respectively.

Table 2. Weighted proportions of adolescents who have ever tested for HIV by demographic, behavioural, social and contextual factors.

Characteristics (N = 14,312)	Yes (N)	(%)	95% CI	P-Value
All participants	3599	23.69	[22.39,25.04]
Age group (in Years)				<0.001
15–19	1478	16.66	[15.45,17.96]
20–24	2121	33.1	[31.12,35.14]
Gender				<0.001
Female	2401	25.38	[23.75,27.08]
Male	1198	20.76	[19.13,22.5]
Marital Status				<0.001
Never married	2726	22.37	[21.03,23.78]
Currently married	802	27.93	[25.04,31.02]
Formerly married	71	33.23	[24.96,42.67]
Education				<0.001
None	265	10.43	[8.474,12.78]
Primary	233	19.02	[15.87,22.63]
Secondary (& Tech)	2381	24.74	[23.3,26.23]
Higher	720	52.89	[49.18,56.57]
Wealth Status				<0.001
Poorest	194	9.738	[7.761,12.15]
Second	501	17.88	[15.47,20.57]
Middle	743	20.93	[18.54,23.53]
Forth	970	28.48	[26.01,31.09]
Richest	1191	33.7	[31.49,35.99]
Zone				<0.001
North west	429	13.41	[11.43,15.67]
North central	1118	34.77	[31.57,38.1]
North east	374	16.52	[12.9,20.92]
South east	481	30.03	[27.24,32.99]
South south	764	36.92	[33.76,40.19]
South west	433	26.6	[23.75,29.66]
Residence				<0.001
Rural	2145	21.34	[19.76,23]
Urban	1454	27.16	[24.85,29.6]
Ever has sex				<0.001
No	1429	16.47	[15.15,17.88]
Yes	2170	33.59	[31.62,35.63]
Condom Use				<0.001
No	3132	22.02	[20.73,23.37]
Yes	467	55.27	[50.62,59.83]
Knowledge of HIV				<0.001
Low	137	12.39	[10.13,15.08]
Moderate	985	16.43	[15.07,17.89]
High	2477	29.44	[27.62,31.32]
Attitude towards HIV				<0.001
Extremely Negative	460	13.04	[11.52,14.74]
Negative	450	18.75	[16.8,20.86]
Moderate	552	22.14	[20.07,24.36]
Positive	872	27.41	[25.17,29.77]
Extremely Positive	1265	33.97	[30.97,37.1]
Media Exposure				<0.001
Low	1616	18.28	[16.8,19.87]
Moderate	1380	28.13	[26.08,30.28]
High	603	39.85	[36.41,43.4]

Open in a new tab

Pearson Chi-squared test was used to obtain P-values. This applies for all P-values

Table 3. Weighted proportions of adolescents recently tested for HIV by demographic, behavioural, social and contextual factors.

Characteristics N = 14,312	Yes (N)	(%)	95% CI	P-value
All participants	1942	12.42	[11.49,13.41]
Age group (in Years)				<0.001
15–19	865	9.47	[8.57,10.46]
20–24	1077	16.36	[15.01,17.79]
Gender				0.37
Female	1240	12.69	[11.61,13.85]
Male	702	11.95	[10.61,13.42]
Marital Status				0.675
Never married	1534	12.47	[11.43,13.6]
Formerly married	373	12.09	[10.44,13.96]
Currently married	35	14.78	[10.01,21.3]
Education				<0.001
None	109	4.08	[3.02,5.48]
Primary	121	8.86	[7.09,11.02]
Secondary (& Tech)	1312	13.52	[12.39,14.74]
Higher	400	28.46	[25.44,31.69]
Wealth Status				<0.001
Poorest	107	5.63	[4.23,7.45]
Second	270	8.71	[7.16,10.55]
Middle	398	10.94	[9.35,12.76]
Forth	502	14.56	[12.87,16.42]
Richest	665	18.21	[16.41,20.17]
Zone				<0.001
North west	209	5.89	[4.869,7.112]
North central	670	20.90	[18.07,24.04]
North east	204	7.20	[5.63,9.16]
South east	199	12.73	[10.6,15.21]
South south	441	22.88	[19.98,26.07]
South west	219	13.63	[11.47,16.12]
Residence				0.01
Rural	1150	11.30	[10.23,12.47]
Urban	792	14.05	[12.34,15.97]
Ever has sex				<0.001
No	813	8.98	[8.043,10]
Yes	1129	17.13	[15.74,18.62]
Condom Use				<0.001
No	1673	11.35	[10.48,12.3]
Yes	269	32.50	[28.26,37.05]
Knowledge of HIV				<0.001
Low	74	6.72	[5.16,8.72]
Moderate	537	8.70	[7.75,9.765]
High	1331	15.35	[14.04,16.75]
Attitude towards HIV				<0.001
Extremely Negative	210	6.22	[5.21,7.41]
Negative	202	8.27	[7.06,9.66]
Moderate	262	10.57	[9.10,12.24]
Positive	500	15.10	[13.39,16.97]
Extremely Positive	768	19.34	[16.96,21.97]
Media Exposure				<0.001
Low	829	9.02	[8.02,10.12]
Moderate	767	15.30	[13.82,16.91]
High	346	22.31	[19.53,25.36]

Open in a new tab

Pearson Chi-squared test was used to obtain p -values. This applies for all p values

Only 13.6% of the respondents tested in the year preceding the survey and the proportion of those who recently tested varies by demographic, behavioural, social and contextual. The rate of recent HIV testing was highest among young adults aged 20–24 years, those who had higher education, resided in North Central Nigeria, had higher knowledge of HIV and exposure to media and those who held positive stigma belief about PLHIV (Table 3).

Multivariable findings

Tables 4 and 5 summarise results of the multivariable models examining the association between the uptake of HIV testing and demographic, behavioural, social, and contextual factors. All demographic factors included in the study (age, gender, marital status, education and wealth) were significantly associated with having ever tested for HIV in the unadjusted regression model. The direction of the association persists for all demographic variables but the magnitude of the effect slightly reduced in the adjusted model. Young adults aged 20–24 (AOR 1.52, 95% CI 1.34–1.72) had higher odds of having been tested for HIV, compared to adolescents aged 15–19 years. Also, currently married young people were almost twice as likely to have ever tested for HIV compared to those who have never been married. Compared to respondents with no formal education, those with higher education (AOR 5.85, 95% CI 4.39–7.81) had a higher likelihood of having ever been tested for HIV. Moreover`, young people in the richest wealth quintile were twice more likely to have ever been tested for HIV compared to those in the poorest wealth quintile.

Table 4. Multivariable logistic regression analysis showing predictors of uptake of HIV testing in the respondent's lifetime.

Characteristics (N = 14,312)	Unadjusted Odds ratio [95% CI]		Adjusted Odds ratio [95% CI]
Age group
15–19	Ref
20–24	2.47	[2.24,2.73] ^***	1.52	[1.34,1.72] ^***
Gender
Female	Ref
Male	0.77	[0.70,0.85] ^***	0.95	[0.84,1.08]
Marital Status
Never married	Ref
Currently married	1.34	[1.20,1.51] ^***	2.42	[1.98,2.97] ^***
Formerly married	1.73	[1.17,2.56] ^***	1.54	[0.89,2.67]
Education
None	Ref
Primary	2.02	[1.58,2.57] ^***	1.83	[1.39,2.39] ^***
Secondary (& Tech)	2.82	[2.38,3.35] ^***	2.68	[2.12,3.38] ^***
Higher	9.64	[7.82,11.87] ^***	5.85	[4.39,7.81] ^***
Wealth Status
Poorest	Ref
Second	2.02	[1.62,2.52] ^***	1.57	[1.24.1.99] ^***
Middle	2.45	[2.00,3.012] ^***	1.48	[1.16,1.87] ^***
Forth	3.69	[3.01,4.53] ^***	1.85	[1.43,2.39] ^***
Richest	4.71	[3.87,5.73] ^***	1.99	[1.53,2.60] ^***
Zone
Northwest	Ref
North central	3.44	[2.97,3.99]^***	3.38	[2.87,3.97] ^***
North east	1.28	[1.04,1.58] **	1.29	[1.03,1.61] **
South east	2.77	[2.35,3.28] ^***	2.13	[1.75,2.58] ^***
South south	3.78	[3.24,4.41] ^***	2.55	[2.11,3.07] ^***
South west	2.34	[1.97,2.78] ^***	1.50	[1.22,1.85] ^***
Residence
Rural	Ref
Urban	1.37	[1.25,1.52] ^***	1.00	[0.86,1.16]
Knowledge of HIV
Low	Ref
Moderate	1.39	[1.10,1.75] ^***	1.11	[0.85,1.44]
High	2.95	[2.36,3.69] ^***	1.62	[1.24,2.11]^***
Attitude towards HIV
Extremely Negative	Ref
Negative	1.54	[1.29,1.83] ^***	1.34	[1.11,1.62] ^***
Moderate	1.9	[1.60,2.24] ^***	1.55	[1.28,1.87] ^***
Positive	2.52	[2.16,2.94] ^***	2.03	[1.70,2.43] ^***
Extremely Positive	3.43	[2.94,4.00] ^***	2.93	[2.47,3.49]^***
Media Exposure
Low	Ref
Moderate	1.75	[1.57,1.95] ^***	1.17	[1.02,1.34] ^***
High	2.96	[2.56,3.42] ^***	1.64	[1.36,1.97] ^***
Ever has sex
No	Ref
Yes	2.57	[2.32,2.83] ^***	1.72	[1.49,1.98] ^***
Condom Use
No	Ref
Yes	4.37	[3.68,5.20] ^***	1.84	[1.49,2.28] ^***

Open in a new tab

***P values <0.001

*P values <0.01

Ref indicates the baseline category (reference) for each variable.

Table 5. Multivariable logistic regression analysis showing predictors of recent uptake of HIV testing.

Characteristics (N = 14,312)	Unadjusted Odds ratio [95% CI]		Adjusted Odds ratio [95% CI]
Age group
15–19	Ref
20–24	1.87	[1.66,2.10]^***	1.20	[1.03,1.40]^***
Gender
Female	Ref
Male	0.93	[0.83,1.05]	1.09	[0.94,1.25]
Marital Status
Never married	Ref
Currently married	0.97	[0.83,1.12]	1.67	[1.33,2.091]^***
Formerly married	1.22	[0.79,1.88]	1.09	[0.66,1.81]
Education
None	Ref
Primary	2.29	[1.66,3.16]^***	1.81	[1.29,2.55]^***
Secondary (& Tech)	3.68	[2.89,4.67]^***	2.78	[2.08,3.72]^***
Higher	9.36	[7.14,12.26]^***	4.77	[3.39,6.71]^***
Wealth Status
Poorest	Ref
Second	1.60	[1.22,2.10]^***	1.11	[0.84,1.47]
Middle	2.06	[1.58,2.68]^***	1.05	[0.78,1.42]
Forth	2.86	[2.21,3.70]^***	1.15	[0.85,1.57]
Richest	3.73	[2.91,4.80]^***	1.26	[0.91,1.75]
Zone
Northwest	Ref
North central	4.22	[3.48,5.12]^***	3.61	[2.95,4.43]^***
North east	1.24	[0.96,1.59]	1.20	[0.92,1.56]
South east	2.33	[1.85,2.94]^***	1.60	[1.25,2.06]^***
South south	4.74	[3.87,5.81]^***	3.04	[2.42,3.82]^***
South west	2.52	[2.00,3.17]^***	1.70	[1.31,2.21]^***
Residence
Rural	Ref
Urban	1.28	[1.14,1.45]^***	0.96	[0.82,1.13]
Knowledge of HIV
Low	Ref
Moderate	1.32	[0.99,1.77]	1.01	[0.74,1.37]
High	2.51	[1.90,3.33]^***	1.24	[0.91,1.69]
Attitude towards HIV
Extremely Negative	Ref
Negative	1.36	[1.07,1.72]**	1.16	[0.91,1.48]
Moderate	1.78	[1.42,2.23]^***	1.43	[1.13,1.81]^***
Positive	2.68	[2.18,3.29]^***	2.15	[1.73,2.68]^***
Extremely Positive	3.62	[2.97,4.40]^***	3.04	[2.47,3.75]^***
Media Exposure
Low	Ref
Moderate	1.82	[1.60,2.07]^***	1.24	[1.07,1.45]^***
High	2.90	[2.45,3.43]^***	1.63	[1.33,2.00]^***
Ever has sex
No	Ref
Yes	2.10	[1.86,2.36]^***	1.62	[1.37,1.92]^***
Condom Use
No	Ref
Yes	3.76	[3.13,4.52]^***	1.78	[1.41,2.24]^***

Open in a new tab

***P values <0.001

*P values <0.01

Ref indicates the baseline category (reference) for each variable.

Both place and geopolitical zone of residence were strongly associated with ever having been tested for HIV in the unadjusted regression model. The direction and magnitude of effect persist in the adjusted model. Adolescents and young adults residing in the north-central and south-south geopolitical zones had a higher likelihood of ever having been tested for HIV compared to those in the north-west.

Regarding the association between social factors and uptake of HIV testing, the unadjusted model shows that media exposure, knowledge of HIV, and stigma attitude were significantly related to lifetime uptake of HIV testing. The direction and magnitude of the effect remain consistent even in the adjusted model. Adolescents and young adults who had high HIV knowledge had higher odds of ever having been tested for HIV testing compared to those who had low HIV knowledge. Similarly, those who espoused a positive attitude towards PLHIV were three times more likely to have ever tested for HIV compared to those with an extremely negative attitude towards PLHIV. Additionally, individuals frequently exposed to the media had a higher likelihood of having ever tested for HIV.

Adolescents' and young adults' behavioural characteristics, such as having engaged in sex and condom use, were significantly associated with ever having tested for HIV in the unadjusted model. The strength of the association reduced in the adjusted model, but the direction of the effect persists. Young people who have ever had sex or used condoms had higher odds of having ever tested for HIV.

The relationship between recent uptake of HIV testing and demographic, social, contextual, and behavioural factors was examined using adjusted, and unadjusted logistic regression models and the results are presented in Table 5. Of all demographic factors, only age, educational level and wealth status were significantly positively related to recent uptake of HIV testing in the unadjusted model. However, the magnitude of the effect of these variables reduced substantially in the adjusted model, except for currently married where the effect size increased. Currently married adolescents and young adults had a higher likelihood of recent uptake of HIV testing compared to their never-married counterparts. Similarly, young adults aged 20 to 24 were 20% more likely to have recently tested for HIV compared to adolescents aged 15 to 19. Also, AYA who had higher education were five times likely to have recently tested for HIV compared to those who had no formal education.

Place and geopolitical zones were positively associated with recent uptake of HIV testing in the unadjusted model. The magnitude of effect reduced in the adjusted model for both place of residence and geopolitical zones, but the direction of effect persists only for geopolitical zones. Favourable attitude towards PLHIV, high HIV knowledge, and media exposure were associated with higher odds of recent uptake of HIV testing. The direction of effect persists in the adjusted model, but the magnitude of the effect reduced. Ever had sex and condom use were associated with a higher likelihood of recent uptake of HIV testing and the magnitude and direction of effects persist in the adjusted regression model.

Discussion

This study examined the coverage and factors associated with HIV testing uptake among AYA in Nigeria. Our findings show that HIV testing uptake is low among young people aged 15–24 years. The rate of HIV testing found in this study shows only a minimal increase in the uptake of HIV testing in this age group when compared to the NDHS 2013[4]. While there is evidence that HIV testing uptake has increased significantly among pregnant women [37], it appears that such improvement is yet to be achieved with young people. Interventions to increase HIV testing uptake seem to focus on pregnant women [37], neglecting young people who are among the most at-risk of contracting HIV [9]. Given the importance of early diagnosis to the treatment outcomes of PLHIV [10, 11], there is a need to develop a policy framework targeted at expanding access and uptake of HIV testing among young people.

Consistent with previous studies [15, 17, 19], our study shows that demographic factors, such as age, sex, marital status, and education level, are significantly associated with uptake of HIV testing. Uptake of HIV testing tends to increase with increasing age. Also, females in general and married young girls/women in particular, have higher odds of HIV testing compared to males in Nigeria. Adolescents and young women who had attended antenatal care or given birth have more opportunities of getting tested compared to young men who may have limited reasons to visit the clinic. Although the 'opt-out' strategy is the main policy thrust to increase HIV testing uptake in Nigeria [38], its implementation appears to have targeted mainly pregnant women and neglected other categories of patients attending clinics for other reasons besides pregnancy.

Adolescents and young adults educated up to post-secondary school level had a higher odds of uptake of HIV testing compared to those not educated or with only primary level of education. The importance of education for improved health outcomes has been demonstrated in previous studies [39, 40]. Educated young adults are more likely to have good knowledge of HIV and better able to assess their risk. Knowledge of HIV and risk perceptions have been established to be associated with uptake of HIV testing [5]. Investment in the education of young people will not only increase the uptake of HIV testing but also improve other health outcomes.f

Another important finding of this study is that place and region of residence are positively associated with uptake of HIV testing. The distribution of HIV testing appears to mirror HIV prevalence by state and indicates areas where interventions are concentrated (See S1 Table). While it is important to prioritise areas needing urgent intervention, it is also critical that regions of low prevalence are not neglected.

Consistent with previous studies and behavioural theories, HIV knowledge, stigma belief, and media exposure were associated with uptake of HIV testing[4, 5, 20]. Individuals with higher HIV knowledge were more likely to have ever been tested for HIV compared to those with low knowledge of HIV, indicating the need for sustaining efforts directed at educating people about HIV and the benefits of HIV testing. Likewise, media exposure was associated with higher odds of HIV testing uptake, which further reinforces the role of media towards raising awareness about HIV, the benefits of HIV testing and treatment, and communicating recent advances like availability of pre-exposure prophylaxis and more importantly the “Undetectable Equals Untransmittable” message. Nevertheless, stigma belief about HIV remains associated with lower odds of HIV testing uptake, suggesting that stigma remains a significant barrier in the Nigerian context. While it is unsurprising that stigma belief about HIV is associated with low uptake of HIV testing, the extent of stigma belief expressed by young people in Nigeria, no doubt, indicate misguided knowledge or gaps in knowledge of HIV. Thus efforts should be placed on improving knowledge of young people about HIV in Nigeria to improve health outcomes at the population level.

Besides the individual level barriers, structural barrier also limits AYA’ access to HIV testing. For example, the legal age of consent for independent HIV testing is 18 years in Nigeria [41]. This law presents a structural barrier to accessing HIV testing services [42], as young people will mostly likely not bring their parents to provide consent and also providers would want to follow the law. The experts in the field of sexual and reproductive health (SRH) in Nigeria, during a strategic engagement held with the federal ministry of health, recommended age 14 yrs for the age of consent to HIV testing. We consider removing this legal barrier, as recommended by experts in the field of SRH in Nigeria, to be critical for expanding access to HIV testing in Nigeria. The low level of HIV testing among AYA in Nigeria has severe implication for the spread of HIV, cost of treatment and HIV related-deaths. Nigerian’s AYA are disproportionately affected by HIV and should be a priority group of HIV interventions. Expanding access to HIV testing for AYA remains a priority intervention to achieve the country’s 2020 target of 95% testing rate. Improving young people's knowledge of HIV perhaps through the media as well as other interventions such as home-based testing and the "opt-out" strategy will be critical to substantially increase HIV testing uptake among young people in Nigeria.

Study strengths and limitations

The findings reported in this study have some limitations. First, HIV testing is based on self-reporting and while this is a major event that participants should recall, social desirability bias cannot be ruled out even though its impact on the findings should be minimal. Second, the reported association should not be interpreted as causation since the data is cross-sectional, and it is difficult to establish which event is a precondition for another. Nevertheless, the findings of the study are reassuring given that there are based on nationally representative data. The study provides much-needed data for strategic planning and programming to improve health outcomes among young people in the country.

Conclusion

We examined the coverage and associated factors of HIV testing uptake among young people in Nigeria using nationally representative data. Our study found a low rate of HIV testing that varies by demographic, behavioural, social, and contextual characteristics. The findings indicate a slight increase in the rate of HIV testing among young people in the country. However, the rate of increase is too slow and fell far short of the standard required to achieve the UNAIDS first 95 and the national goal of testing 95% of people in the country by 2020. Improving young people's knowledge of HIV perhaps through the media as well as other interventions such as home-based testing and the "opt-out" strategy will be critical to substantially increase HIV testing uptake among young people in Nigeria.

Supporting information

S1 Table. HIV testing by states.

(DOCX)

Click here for additional data file.^{(15KB, docx)}

Data Availability

The MICS 5 data for Nigeria underlying the results presented in the study are freely available from UNICEF at http://mics.unicef.org/surveys.

Funding Statement

The author(s) received no specific funding for this work.

References

1.UNAIDS. Miles to Go—Closing Gaps, Breaking Barriers, Righting Injustices. Geneva, Switzerland: Joint United Nations Programme on HIV/AIDS, 2018. [Google Scholar]
2.UNAIDS. Global HIV & AIDS statistics—2018 fact sheet 2018. Available from: http://www.unaids.org/sites/default/files/media_asset/UNAIDS_FactSheet_en.pdf.
3.Sam-Agudu NA, Folayan MO, Ezeanolue EE. Seeking wider access to HIV testing for adolescents in sub-Saharan Africa. Pediatric Research. 2016;79(6):838 10.1038/pr.2016.28 [DOI] [PubMed] [Google Scholar]
4.Somefun OD, Wandera SO, Odimegwu C. Media Exposure and HIV Testing Among Youth in Sub-Saharan Africa: Evidence From Demographic and Health Surveys (DHS). SAGE Open. 2019;9(2):2158244019851551. [Google Scholar]
5.Ajayi AI, Abioye AO, Adeniyi OV, Akpan WJJobs. Concerns about contracting HIV, knowing partners’ HIV sero-status and discussion of HIV/STI with sexual partners as determinants of uptake of HIV testing. 2018:1–13. [DOI] [PubMed] [Google Scholar]
6.Sogbanmu OO, Goon DT, Obi LC, Iweriebor BC, Nwodo UN, Ajayi AI, et al. Socio-demographic and clinical determinants of late presentation among patients newly diagnosed with HIV in the Eastern Cape, South Africa. Medicine. 2019;98(8). [DOI] [PMC free article] [PubMed] [Google Scholar]
7.UNICEF. Turning the tide against AIDS will require more concentrated focus on adolescents and young people 2019 [24/04/2020]. Available from: https://data.unicef.org/topic/hivaids/adolescents-young-people/.
8.Nachega JB, Hislop M, Nguyen H, Dowdy DW, Chaisson RE, Regensberg L, et al. Antiretroviral therapy adherence, virologic and immunologic outcomes in adolescents compared with adults in southern Africa. Journal of acquired immune deficiency syndromes (1999). 2009;51(1):65. [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Makhema J, Wirth KE, Pretorius Holme M, Gaolathe T, Mmalane M, Kadima E, et al. Universal testing, expanded treatment, and incidence of HIV infection in Botswana. New England Journal of Medicine. 2019;381(3):230–42. 10.1056/NEJMoa1812281 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Delavande A, Kohler H-P. The impact of HIV testing on subjective expectations and risky behavior in Malawi. Demography. 2012;49(3):1011–36. 10.1007/s13524-012-0119-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Cawley C, Wringe A, Slaymaker E, Todd J, Michael D, Kumugola Y, et al. The impact of voluntary counselling and testing services on sexual behaviour change and HIV incidence: observations from a cohort study in rural Tanzania. BMC infectious diseases. 2014;14(1):159. [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Organization WH. Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection: recommendations for a public health approach: World Health Organization; 2016. [PubMed] [Google Scholar]
13.The Joint United Nations Programme on HIV/AIDS. Fast-Track: ending the AIDS epidemic by 2030 Geneva, Switzerland: UNAIDS, 2014. [Google Scholar]
14.Meiberg AE, Bos AE, Onya HE, Schaalma HP. Fear of stigmatization as barrier to voluntary HIV counselling and testing in South Africa. East Afr J Public Health. 2008;5(2):49–54. [PubMed] [Google Scholar]
15.Creel AH, Rimal RN. Factors related to HIV-testing behavior and interest in testing in Namibia. AIDS care. 2011;23(7):901–7. 10.1080/09540121.2010.540227 [DOI] [PubMed] [Google Scholar]
16.MacKellar DA, Hou S-I, Whalen CC, Samuelsen K, Sanchez T, Smith A, et al. Reasons for not HIV testing, testing intentions, and potential use of an over-the-counter rapid HIV test in an internet sample of men who have sex with men who have never tested for HIV. Sexually transmitted diseases. 2011;38(5):419–28. 10.1097/OLQ.0b013e31820369dd [DOI] [PubMed] [Google Scholar]
17.Agha S. Factors associated with HIV testing and condom use in Mozambique: implications for programs. Reproductive Health. 2012;9(1):20. [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Pitpitan EV, Kalichman SC, Eaton LA, Cain D, Sikkema KJ, Skinner D, et al. AIDS-related stigma, HIV testing, and transmission risk among patrons of informal drinking places in Cape Town, South Africa. Annals of Behavioral Medicine. 2012;43(3):362–71. 10.1007/s12160-012-9346-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Amu EO, Olatona FA, Onayade AA. Factors influencing HIV counselling and testing uptake among corps members in Osun State, Nigeria. IOSR Journal of Dental and Medical Sciences. 2014;13(1):14–9. [Google Scholar]
20.Ajayi A, Mudefi E, Adeniyi O, Goon D. Achieving the first of the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 targets: understanding the influence of HIV risk perceptions, knowing one’s partner’s status and discussion of HIV/sexually transmitted infections with a sexual partner on uptake of HIV testing. International health. 2019. [DOI] [PubMed] [Google Scholar]
21.Deblonde J, De Koker P, Hamers FF, Fontaine J, Luchters S, Temmerman M. Barriers to HIV testing in Europe: a systematic review. European Journal of Public Health. 2010;20(4):422–32. 10.1093/eurpub/ckp231 [DOI] [PubMed] [Google Scholar]
22.Musheke M, Ntalasha H, Gari S, Mckenzie O, Bond V, Martin-Hilber A, et al. A systematic review of qualitative findings on factors enabling and deterring uptake of HIV testing in Sub-Saharan Africa. BMC public health. 2013;13(1):220. [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Population Reference Bureau. 2018 World Population Data Sheet. 1875 Connecticut Ave., NW, Suite 520, Washington, DC: Population Reference Bureau, 2018 August, 2018. Report No.
24.National Agency for the Control of AIDS. Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS) Preliminary Findings. Ralph Shodeinde Street, Central Business District, Abuja, FCT: NACA, 2019. [Google Scholar]
25.UNAIDS. Nigeria Geneva 27, Switzerland: UNAIDS; 2019 [cited 2019 9th May]. Available from: http://www.unaids.org/en/regionscountries/countries/nigeria.
26.Awofala AA, Ogundele OE. HIV epidemiology in Nigeria. Saudi journal of biological sciences. 2018;25(4):697–703. 10.1016/j.sjbs.2016.03.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.National Agency for the Control of AIDS. End of term evaluation of national strategic plan 2010. Abuja, Nigeria: 2016.
28.National Agency for the Control of AIDS. National HIV and AIDS Strategic Plan 2017–2021. Abuja, Nigeria: 4th May 2019, 2017.
29.Olakunde BO, Adeyinka DA, Olawepo JO, Pharr JR, Ozigbu CE, Wakdok S, et al. Towards the elimination of mother-to-child transmission of HIV in Nigeria: a health system perspective of the achievements and challenges. International health. 2019. [DOI] [PubMed] [Google Scholar]
30.Ogaji D, Oyeyemi A, Ibrahim I. Awareness, willingness and use of Voluntary HIV testing and counseling services by students of a university in south-south Nigeria. Journal of Community Medicine and Primary Health Care. 2013;25(2):36–44. [Google Scholar]
31.Janz N, Champion V, Strecher V. The health belief model, Health behavior and health education (pp. 45–66). San Francisco: John Wiley & Sons; 2002. [Google Scholar]
32.Rosenstock IM, Strecher VJ, Becker MH. The health belief model and HIV risk behavior change Preventing AIDS: Springer; 1994. p. 5–24. [Google Scholar]
33.Becker MH. The health belief model and personal health behavior: Slack; 1974. [Google Scholar]
34.Janz NK, Becker MH. The health belief model: A decade later. Health Education & Behavior. 1984;11(1):1–47. [DOI] [PubMed] [Google Scholar]
35.Dlamini PS, Wantland D, Makoae LN, Chirwa M, Kohi TW, Greeff M, et al. HIV stigma and missed medications in HIV-positive people in five African countries. AIDS patient care and STDs. 2009;23(5):377–87. 10.1089/apc.2008.0164 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Eisinger RW, Dieffenbach CW, Fauci AS. HIV viral load and transmissibility of HIV infection: undetectable equals untransmittable. Jama. 2019;321(5):451–2. 10.1001/jama.2018.21167 [DOI] [PubMed] [Google Scholar]
37.Ajayi A, Awopegba O, Owolabi E, Ajala A. Coverage of HIV testing among pregnant women in Nigeria: progress, challenges and opportunities. Journal of Public Health. 2019. 10.1093/pubmed/fdz152 [DOI] [PubMed] [Google Scholar]
38.Udoh EE, Ushie BA. Determinants of antenatal HIV testing in the opt-out approach in Nigeria: findings from the Nigerian Demographic and Health Survey. Journal of biosocial science. 2019:1–18. [DOI] [PubMed] [Google Scholar]
39.Schillinger D, Barton LR, Karter AJ, Wang F, Adler N. Does literacy mediate the relationship between education and health outcomes? A study of a low-income population with diabetes. Public health reports. 2006;121(3):245–54. 10.1177/003335490612100305 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Paasche-Orlow MK, Wolf MS. The causal pathways linking health literacy to health outcomes. American journal of health behavior. 2007;31(1):S19–S26. [DOI] [PubMed] [Google Scholar]
41.McKinnon B, Vandermorris A. National age-of-consent laws and adolescent HIV testing in sub-Saharan Africa: a propensity-score matched study. Bulletin of the World Health Organization. 2019;97(1):42 10.2471/BLT.18.212993 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Sam-Agudu NA, Folayan MO, Haire BG. Program implementation gaps and ethical issues in the prevention of HIV infection among infants, children, and adolescents in sub-Saharan Africa. Pediatric research. 2019:1–9. 10.1038/s41390-019-0521-6 [DOI] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0233368.r001

Decision Letter 0

Olanrewaju Oladimeji

17 Apr 2020

PONE-D-20-04813

Low coverage of HIV testing among adolescents and young adults in Nigeria: implication for achieving the UNAIDS first 90

PLOS ONE

Dear Dr Ajayi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We would appreciate receiving your revised manuscript by Jun 01 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Olanrewaju Oladimeji

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

In addition to the reviewers comments, the authors should keep the flowchart vertically downward and easure that the references are in vancouver square bracket.

Journal requirements:

When submitting your revision, we need you to address these additional requirements:

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at http://www.plosone.org/attachments/PLOSOne_formatting_sample_main_body.pdf and http://www.plosone.org/attachments/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please ensure that you refer to Figure 1 in your text as, if accepted, production will need this reference to link the reader to the figure.

3. We note you have included a table to which you do not refer in the text of your manuscript. Please ensure that you refer to Table 4 in your text; if accepted, production will need this reference to link the reader to the Table.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This article is a secondary analysis is publicly available data and establishes low HIV testing coverage among adolescent and young adults (AYA). The article is well written with logical presentation of its findings.

However, the bivarate analysis on table 2 seems not to add up. For instance, there were a total of 14312 eligible AYA. Of these, 3599 responded to ever tested for HIV which gives 25.1% (i.e. 3599/14312) but the tables shows "23.69%". The same is true for all the variables on table 2. Though minor, it would be helpful to either explain why there is a variation or correct the error if that is the case.

Secondly, table 5 show the multivariate logistics regression, is there any reason for adding variables that do not show any bivariate association (e.g. "knowledge of HIV; marital status") in the final model?

Reviewer #2: This paper presents an analysis of MICS data with respect to HIV testing coverage and associated factors among 15 to 24 yr olds in Nigeria. It is a timely analysis for Nigeria in the transition from 90-90-90 UNAIDS targets to 95-95-95 targets.

GENERAL:

1. Please check the tense in the Methods and Results. Best to use past tense for what was done and the results obtained.

2. Add "years" whenever age is mentioned eg 15-24 years, and not simply 15-24.

ABSTRACT:

1. Note and correct the transposition of MICS: Multiple Indicator Cluster Survey (not MCIS)

2. Would be important to add gender info to Abstract results ie stats on higher testing rates among girls than boys

3. "The HIV testing coverage among AYA in Nigeria is well below the national target of 95% testing indicated in the national HIV/AIDS strategic framework (2017-2021)." Suggest delete the word "testing" after "95%"

4. "reducing negative stigma belief through the media campaign". Suggest delete the word "the" and add "s" to campaign.

INTRO:The info is fairly well-written but noticeably devoid of actual epi numbers and the source refs.

1. The first, and especially second para narrate epi info but do not actually state the numbers. Please state and reference the actual epi numbers so that the reader is well-informed. At least, state and reference the actual data for sub-Saharan Africa.

2. Suggest: "AYA aged 15-24 years bear a disproportionate burden of HIV, particularly for new infections and AIDS-related deaths. In sub-Saharan Africa," ...State the proportions for SSA.

3. "Also, they are more unlikely (*suggest less likely*) to have tested for HIV, have the lowest level of adherence to ART and viral load suppression." As I stated above, please provide the actual numbers on likelihood of HIV testing, adherence, and VL suppression. Please do that for the rest of the Intro section.

4. Define WHO acronym at first use; no need to use the acronym since it is used only once in the paper. Similar for SSA...no need for the acronym; used only twice.

5. I strongly suggest replacing 90-90-90 definition with 95-95-95 and providing a reference for the definition. We are in 2020 and 90-90-90 is no longer relevant.

6. ...couples' (apostrophe added) open communication about HIV, expanding access to HIV testing and treatment, *as* well as having a social support network...

7. Suggest: *At 1.5%*, Nigeria has a low prevalence of HIV, but the country’s large population *of >200 million* (ref) means that the number of people living with HIV in the country is *substantial*.

8. *A significant proportion; up to xx%* of new infections occurs among adolescents and young adults in the country." Provide actual epi data and reference.

9. "Most studies on HIV testing among young people in Nigeria are not nationally representative or

are now *outdated* 4,5,16,26"

10. "As such, recent nationally representative data, such as the Multiple Indicator (no "s")

Cluster Survey (MICS) *(suggest capitalize first letters)*, could help assess current HIV testing rates among young people and progress recorded since the scaling *up* of such services in Nigeria."

11. Health Belief Model (capitalize first letters please)

12. Suggest deleting this sentence. Other adjacent statements send the same message in more formal language. "People can test for HIV knowing they could lead a normal and healthy life."

MATERIALS AND METHODS

1. Use the term fifth or 5th (superscript th)

2. Use past tense in Methods, including in Ethical Statement: We *did* not need...

3. Study Population:suggest "There were 52,690 MICS respondents (xx male and xx female). However, the focus of this study was AYA 15-24 yrs, who comprised 18, xxx (xx% out of all respondents), who met selection criteria. The analysis was further limited to 14, xxx AYA who responded to the questions on HIV testing".

4. "Our dependent variables of interest in this study are two two-category nominal measure of uptake

of HIV testing." Is the repeat of the word "two" a typo?

5. The demographic variable should be "formerly married" (not formally). Also correct that in the Tables.

6. Use quotation marks if variables are not in brackets: "The behavioural variables are "ever had sex" and "condom use".

7. The first question probed whether they *had* ever heard of AIDS.

8. with a score of 0-3 Categorised as low knowledge (use small c)

9. I believe term is household wealth, not house wealth? "The variable was already computed (delete "as")

before making the data public." "Model 2", not "Models 2"

10. "...who had low knowledge of HIV (12.4%%)"-delete second %

RESULTS

1. Again, please check your tenses and use past tense

2. it is also critical that regions of low *prevalence* are not neglected

3. (UDOH & USHIE, 2019)-please format this ref

4. "Undetectable Equals Untransmittable" best to write in quotes and capitalize first letters. It's a brand strategic message.

DISCUSSION

1. Study strengths and limitations: "the data is a cross-sectional" -delete "a"

2. Conclusions: The findings indicate a slight increase in the rate of HIV testing among young people in the country but the rate of increase however too slow and fell far short of the standard required to achieve the UNAIDS first 90 and the national goal of testing 95% of people in the country by 2020.-this sentence is too long. Please break it up for easier reading and comprehension.

3. A significant concern for this section is the lack of mention of age of consent and legal barriers to access to testing. Nigeria still has an applied age of consent to HIV testing of 18 years. There is however a 2014 National Consensus document that recommends age 14 yrs for the lower age of consent (Ref: Guidelines for Young Persons' Participation in Research and Access to Sexual and Reproductive Health Services in Nigeria). I strongly recommend a short narrative on this issue, making reference to the Child Rights Act, the 2014 consensus as above, some of the articles by Prof Morenike Folayan and colleagues on adolescent rights and access to SRH services, and the recent Bulletin of the WHO publication by McKinnon and Vandermorris: National age-of-consent laws and adolescent HIV testing in sub-Saharan Africa: a propensity-score matched study.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Okpokoro Evaezi

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 May 19;15(5):e0233368. doi: 10.1371/journal.pone.0233368.r002

Author response to Decision Letter 0

30 Apr 2020

Response : we are thankful for the positive feedback.

Response: This is not an error. The percentages presented are from the weighted samples. The 23.69% is inaccurate given the complex sampling adopted. The weighted results are the accurate results. We have retitled the tables to reflect that the percentages are weighted.

Response: The best practice is to include variables in a model based on extant literature and theories (1).Zellner D, Keller F, Zellner GE. Variable selection in logistic regression models. Communications in Statistics-Simulation and Computation. 2004 Jan 2;33(3):787-805. 2) Peter Flom. 2018. Stopping stepwise: Why stepwise selection is bad and what you should use instead 3) https://personal.utdallas.edu/~pkc022000/6390/SP06/NOTES/Logistic_Regression_4.pdf).

The Health Belief Model and previous studies informed our selection of variables to include in our model.

Response: many thanks for the positive feedback

GENERAL:

1. Please check the tense in the Methods and Results. Best to use past tense for what was done and the results obtained.

Response: We have checked the tenses and reported in past tenses.

2. Add "years" whenever age is mentioned eg 15-24 years, and not simply 15-24.

Response: Done

ABSTRACT:

1. Note and correct the transposition of MICS: Multiple Indicator Cluster Survey (not MCIS)

Response: Many thanks for correction. We have implemented it.

2. Would be important to add gender info to Abstract results ie stats on higher testing rates among girls than boys

Response: we have added a sentence on gender difference in HIV testing.

Response: deleted

4. "reducing negative stigma belief through the media campaign". Suggest delete the word "the" and add "s" to campaign.

Response. Done

INTRO:The info is fairly well-written but noticeably devoid of actual epi numbers and the source refs.

2. Suggest: "AYA aged 15-24 years bear a disproportionate burden of HIV, particularly for new infections and AIDS-related deaths. In sub-Saharan Africa," ...State the proportions for SSA.

Response: we have included the actual data by following this suggestion

Response: We have included the actual data by following this suggestion

4. Define WHO acronym at first use; no need to use the acronym since it is used only once in the paper. Similar for SSA...no need for the acronym; used only twice.

Response: Done

5. I strongly suggest replacing 90-90-90 definition with 95-95-95 and providing a reference for the definition. We are in 2020 and 90-90-90 is no longer relevant.

Response: Done

6. ...couples' (apostrophe added) open communication about HIV, expanding access to HIV testing and treatment, *as* well as having a social support network...

Response: corrected

Response: Many thanks for this suggestion. We have implemented the change.

8. *A significant proportion; up to xx%* of new infections occurs among adolescents and young adults in the country." Provide actual epi data and reference.

Response: We have added the data (up to 34%), 41000 out of 120,000 new infections.

9. "Most studies on HIV testing among young people in Nigeria are not nationally representative or

are now *outdated* 4,5,16,26"

Response: Many thanks for the suggestion. We have implemented the suggestion.

10. "As such, recent nationally representative data, such as the Multiple Indicator (no "s")

Cluster Survey (MICS) *(suggest capitalize first letters)*, could help assess current HIV testing rates among young people and progress recorded since the scaling *up* of such services in Nigeria."

Response: this has been corrected

11. Health Belief Model (capitalize first letters please)

Response: done

12. Suggest deleting this sentence. Other adjacent statements send the same message in more formal language. "People can test for HIV knowing they could lead a normal and healthy life."

Response: done

MATERIALS AND METHODS

1. Use the term fifth or 5th (superscript th)

Response: we have changed 5th to fifth

2. Use past tense in Methods, including in Ethical Statement: We *did* not need...

Response: done

Response: many thanks for this suggestion. We have revised accordingly.

4. "Our dependent variables of interest in this study are two two-category nominal measure of uptake

of HIV testing." Is the repeat of the word "two" a typo?

Response: typo has been corrected

5. The demographic variable should be "formerly married" (not formally). Also correct that in the Tables.

Response: we have made the correction throughout the manuscript.

6. Use quotation marks if variables are not in brackets: "The behavioural variables are "ever had sex" and "condom use".

Response: done

7. The first question probed whether they *had* ever heard of AIDS.

Response: corrected

8. with a score of 0-3 Categorised as low knowledge (use small c)

Response: corrected

9. I believe term is household wealth, not house wealth? "The variable was already computed (delete "as")before making the data public." "Model 2", not "Models 2"

Response: done

10. "...who had low knowledge of HIV (12.4%%)"-delete second %

Response: done

RESULTS

1. Again, please check your tenses and use past tense

Response: done

2. it is also critical that regions of low *prevalence* are not neglected

Response: corrected

3. (UDOH & USHIE, 2019)-please format this ref

Response: done

4. "Undetectable Equals Untransmittable" best to write in quotes and capitalize first letters. It's a brand strategic message.

Response: done

DISCUSSION

1. Study strengths and limitations: "the data is a cross-sectional" -delete "a"

Response: corrected

Response: revised.

Response: we have added this paragraph.

PLoS One. doi: 10.1371/journal.pone.0233368.r003

Decision Letter 1

Olanrewaju Oladimeji

5 May 2020

Low coverage of HIV testing among adolescents and young adults in Nigeria: implication for achieving the UNAIDS first 95

PONE-D-20-04813R1

Dear Dr. Ajayi,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

With kind regards,

Olanrewaju Oladimeji, MB;BS, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Authors have addressed almost all the critical issues raised and the manuscript reads well

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0233368.r004

Acceptance letter

Olanrewaju Oladimeji

8 May 2020

PONE-D-20-04813R1

Low coverage of HIV testing among adolescents and young adults in Nigeria: implication for achieving the UNAIDS first 95

Dear Dr. Ajayi:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Olanrewaju Oladimeji

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. HIV testing by states.

(DOCX)

Click here for additional data file.^{(15KB, docx)}

Data Availability Statement

The MICS 5 data for Nigeria underlying the results presented in the study are freely available from UNICEF at http://mics.unicef.org/surveys.

[pone.0233368.ref001] 1.UNAIDS. Miles to Go—Closing Gaps, Breaking Barriers, Righting Injustices. Geneva, Switzerland: Joint United Nations Programme on HIV/AIDS, 2018. [Google Scholar]

[pone.0233368.ref002] 2.UNAIDS. Global HIV & AIDS statistics—2018 fact sheet 2018. Available from: http://www.unaids.org/sites/default/files/media_asset/UNAIDS_FactSheet_en.pdf.

[pone.0233368.ref003] 3.Sam-Agudu NA, Folayan MO, Ezeanolue EE. Seeking wider access to HIV testing for adolescents in sub-Saharan Africa. Pediatric Research. 2016;79(6):838 10.1038/pr.2016.28 [DOI] [PubMed] [Google Scholar]

[pone.0233368.ref004] 4.Somefun OD, Wandera SO, Odimegwu C. Media Exposure and HIV Testing Among Youth in Sub-Saharan Africa: Evidence From Demographic and Health Surveys (DHS). SAGE Open. 2019;9(2):2158244019851551. [Google Scholar]

[pone.0233368.ref005] 5.Ajayi AI, Abioye AO, Adeniyi OV, Akpan WJJobs. Concerns about contracting HIV, knowing partners’ HIV sero-status and discussion of HIV/STI with sexual partners as determinants of uptake of HIV testing. 2018:1–13. [DOI] [PubMed] [Google Scholar]

[pone.0233368.ref006] 6.Sogbanmu OO, Goon DT, Obi LC, Iweriebor BC, Nwodo UN, Ajayi AI, et al. Socio-demographic and clinical determinants of late presentation among patients newly diagnosed with HIV in the Eastern Cape, South Africa. Medicine. 2019;98(8). [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0233368.ref007] 7.UNICEF. Turning the tide against AIDS will require more concentrated focus on adolescents and young people 2019 [24/04/2020]. Available from: https://data.unicef.org/topic/hivaids/adolescents-young-people/.

[pone.0233368.ref008] 8.Nachega JB, Hislop M, Nguyen H, Dowdy DW, Chaisson RE, Regensberg L, et al. Antiretroviral therapy adherence, virologic and immunologic outcomes in adolescents compared with adults in southern Africa. Journal of acquired immune deficiency syndromes (1999). 2009;51(1):65. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0233368.ref009] 9.Makhema J, Wirth KE, Pretorius Holme M, Gaolathe T, Mmalane M, Kadima E, et al. Universal testing, expanded treatment, and incidence of HIV infection in Botswana. New England Journal of Medicine. 2019;381(3):230–42. 10.1056/NEJMoa1812281 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0233368.ref010] 10.Delavande A, Kohler H-P. The impact of HIV testing on subjective expectations and risky behavior in Malawi. Demography. 2012;49(3):1011–36. 10.1007/s13524-012-0119-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0233368.ref011] 11.Cawley C, Wringe A, Slaymaker E, Todd J, Michael D, Kumugola Y, et al. The impact of voluntary counselling and testing services on sexual behaviour change and HIV incidence: observations from a cohort study in rural Tanzania. BMC infectious diseases. 2014;14(1):159. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0233368.ref012] 12.Organization WH. Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection: recommendations for a public health approach: World Health Organization; 2016. [PubMed] [Google Scholar]

[pone.0233368.ref013] 13.The Joint United Nations Programme on HIV/AIDS. Fast-Track: ending the AIDS epidemic by 2030 Geneva, Switzerland: UNAIDS, 2014. [Google Scholar]

[pone.0233368.ref014] 14.Meiberg AE, Bos AE, Onya HE, Schaalma HP. Fear of stigmatization as barrier to voluntary HIV counselling and testing in South Africa. East Afr J Public Health. 2008;5(2):49–54. [PubMed] [Google Scholar]

[pone.0233368.ref015] 15.Creel AH, Rimal RN. Factors related to HIV-testing behavior and interest in testing in Namibia. AIDS care. 2011;23(7):901–7. 10.1080/09540121.2010.540227 [DOI] [PubMed] [Google Scholar]

[pone.0233368.ref016] 16.MacKellar DA, Hou S-I, Whalen CC, Samuelsen K, Sanchez T, Smith A, et al. Reasons for not HIV testing, testing intentions, and potential use of an over-the-counter rapid HIV test in an internet sample of men who have sex with men who have never tested for HIV. Sexually transmitted diseases. 2011;38(5):419–28. 10.1097/OLQ.0b013e31820369dd [DOI] [PubMed] [Google Scholar]

[pone.0233368.ref017] 17.Agha S. Factors associated with HIV testing and condom use in Mozambique: implications for programs. Reproductive Health. 2012;9(1):20. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0233368.ref018] 18.Pitpitan EV, Kalichman SC, Eaton LA, Cain D, Sikkema KJ, Skinner D, et al. AIDS-related stigma, HIV testing, and transmission risk among patrons of informal drinking places in Cape Town, South Africa. Annals of Behavioral Medicine. 2012;43(3):362–71. 10.1007/s12160-012-9346-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0233368.ref019] 19.Amu EO, Olatona FA, Onayade AA. Factors influencing HIV counselling and testing uptake among corps members in Osun State, Nigeria. IOSR Journal of Dental and Medical Sciences. 2014;13(1):14–9. [Google Scholar]

[pone.0233368.ref020] 20.Ajayi A, Mudefi E, Adeniyi O, Goon D. Achieving the first of the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 targets: understanding the influence of HIV risk perceptions, knowing one’s partner’s status and discussion of HIV/sexually transmitted infections with a sexual partner on uptake of HIV testing. International health. 2019. [DOI] [PubMed] [Google Scholar]

[pone.0233368.ref021] 21.Deblonde J, De Koker P, Hamers FF, Fontaine J, Luchters S, Temmerman M. Barriers to HIV testing in Europe: a systematic review. European Journal of Public Health. 2010;20(4):422–32. 10.1093/eurpub/ckp231 [DOI] [PubMed] [Google Scholar]

[pone.0233368.ref022] 22.Musheke M, Ntalasha H, Gari S, Mckenzie O, Bond V, Martin-Hilber A, et al. A systematic review of qualitative findings on factors enabling and deterring uptake of HIV testing in Sub-Saharan Africa. BMC public health. 2013;13(1):220. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0233368.ref023] 23.Population Reference Bureau. 2018 World Population Data Sheet. 1875 Connecticut Ave., NW, Suite 520, Washington, DC: Population Reference Bureau, 2018 August, 2018. Report No.

[pone.0233368.ref024] 24.National Agency for the Control of AIDS. Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS) Preliminary Findings. Ralph Shodeinde Street, Central Business District, Abuja, FCT: NACA, 2019. [Google Scholar]

[pone.0233368.ref025] 25.UNAIDS. Nigeria Geneva 27, Switzerland: UNAIDS; 2019 [cited 2019 9th May]. Available from: http://www.unaids.org/en/regionscountries/countries/nigeria.

[pone.0233368.ref026] 26.Awofala AA, Ogundele OE. HIV epidemiology in Nigeria. Saudi journal of biological sciences. 2018;25(4):697–703. 10.1016/j.sjbs.2016.03.006 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0233368.ref027] 27.National Agency for the Control of AIDS. End of term evaluation of national strategic plan 2010. Abuja, Nigeria: 2016.

[pone.0233368.ref028] 28.National Agency for the Control of AIDS. National HIV and AIDS Strategic Plan 2017–2021. Abuja, Nigeria: 4th May 2019, 2017.

[pone.0233368.ref029] 29.Olakunde BO, Adeyinka DA, Olawepo JO, Pharr JR, Ozigbu CE, Wakdok S, et al. Towards the elimination of mother-to-child transmission of HIV in Nigeria: a health system perspective of the achievements and challenges. International health. 2019. [DOI] [PubMed] [Google Scholar]

[pone.0233368.ref030] 30.Ogaji D, Oyeyemi A, Ibrahim I. Awareness, willingness and use of Voluntary HIV testing and counseling services by students of a university in south-south Nigeria. Journal of Community Medicine and Primary Health Care. 2013;25(2):36–44. [Google Scholar]

[pone.0233368.ref031] 31.Janz N, Champion V, Strecher V. The health belief model, Health behavior and health education (pp. 45–66). San Francisco: John Wiley & Sons; 2002. [Google Scholar]

[pone.0233368.ref032] 32.Rosenstock IM, Strecher VJ, Becker MH. The health belief model and HIV risk behavior change Preventing AIDS: Springer; 1994. p. 5–24. [Google Scholar]

[pone.0233368.ref033] 33.Becker MH. The health belief model and personal health behavior: Slack; 1974. [Google Scholar]

[pone.0233368.ref034] 34.Janz NK, Becker MH. The health belief model: A decade later. Health Education & Behavior. 1984;11(1):1–47. [DOI] [PubMed] [Google Scholar]

[pone.0233368.ref035] 35.Dlamini PS, Wantland D, Makoae LN, Chirwa M, Kohi TW, Greeff M, et al. HIV stigma and missed medications in HIV-positive people in five African countries. AIDS patient care and STDs. 2009;23(5):377–87. 10.1089/apc.2008.0164 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0233368.ref036] 36.Eisinger RW, Dieffenbach CW, Fauci AS. HIV viral load and transmissibility of HIV infection: undetectable equals untransmittable. Jama. 2019;321(5):451–2. 10.1001/jama.2018.21167 [DOI] [PubMed] [Google Scholar]

[pone.0233368.ref037] 37.Ajayi A, Awopegba O, Owolabi E, Ajala A. Coverage of HIV testing among pregnant women in Nigeria: progress, challenges and opportunities. Journal of Public Health. 2019. 10.1093/pubmed/fdz152 [DOI] [PubMed] [Google Scholar]

[pone.0233368.ref038] 38.Udoh EE, Ushie BA. Determinants of antenatal HIV testing in the opt-out approach in Nigeria: findings from the Nigerian Demographic and Health Survey. Journal of biosocial science. 2019:1–18. [DOI] [PubMed] [Google Scholar]

[pone.0233368.ref039] 39.Schillinger D, Barton LR, Karter AJ, Wang F, Adler N. Does literacy mediate the relationship between education and health outcomes? A study of a low-income population with diabetes. Public health reports. 2006;121(3):245–54. 10.1177/003335490612100305 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0233368.ref040] 40.Paasche-Orlow MK, Wolf MS. The causal pathways linking health literacy to health outcomes. American journal of health behavior. 2007;31(1):S19–S26. [DOI] [PubMed] [Google Scholar]

[pone.0233368.ref041] 41.McKinnon B, Vandermorris A. National age-of-consent laws and adolescent HIV testing in sub-Saharan Africa: a propensity-score matched study. Bulletin of the World Health Organization. 2019;97(1):42 10.2471/BLT.18.212993 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0233368.ref042] 42.Sam-Agudu NA, Folayan MO, Haire BG. Program implementation gaps and ethical issues in the prevention of HIV infection among infants, children, and adolescents in sub-Saharan Africa. Pediatric research. 2019:1–9. 10.1038/s41390-019-0521-6 [DOI] [PubMed] [Google Scholar]

PERMALINK

Low coverage of HIV testing among adolescents and young adults in Nigeria: Implication for achieving the UNAIDS first 95

Anthony Idowu Ajayi

Oluwafemi Emmanuel Awopegba

Oluwafemi Atanda Adeagbo

Boniface Ayanbekongshie Ushie

Roles

Abstract

Background

Methods

Results

Conclusion

Background

Materials and methods

Sampling methods

Ethical statement

Study population

Fig 1. Overview of the study sample.

Variables and measurements

Statistical analysis

Results

Descriptive findings

Table 1. Weighted sociodemographic, contextual and behavioural characteristics of study participants.

Bivariate findings

Table 2. Weighted proportions of adolescents who have ever tested for HIV by demographic, behavioural, social and contextual factors.

Table 3. Weighted proportions of adolescents recently tested for HIV by demographic, behavioural, social and contextual factors.

Multivariable findings

Table 4. Multivariable logistic regression analysis showing predictors of uptake of HIV testing in the respondent's lifetime.

Table 5. Multivariable logistic regression analysis showing predictors of recent uptake of HIV testing.

Discussion

Study strengths and limitations

Conclusion

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Olanrewaju Oladimeji

Roles

Author response to Decision Letter 0

Decision Letter 1

Olanrewaju Oladimeji

Roles

Acceptance letter

Olanrewaju Oladimeji

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases