Memoire Online - Prevalence of hiv infection and factors associated with discordant couples receiving hiv test in Gasabo district

All participants have been selected from Kibagabaga Hospital. systematic random sampling was used to sample the discordant couples who tested for HIV, and all of them had an equal chance to participate in the study.

- Couples affected by HIV discordance: The study included couples where one partner is HIV-positive (index case) and the other is HIV-negative.

- Residence in Gasabo District: Participants must reside within the Gasabo District to ensure the study's focus on this specific urban setting.

- Willingness to participate: Couples who expressed willingness to participate in the study through informed consent processes.

- Age criteria: Depending on study objectives, specific age ranges (e.g., 18-49 years) may be included to capture relevant age-related dynamics.

- Non-consenting couples: Couples who do not provide informed consent to participate in the study.

- Couples not meeting discordance criteria: Couples where both partners are HIV-positive or both partners are HIV-negative would be excluded.

- Residence outside Gasabo District: Couples residing outside Gasabo District would not be included to maintain geographical focus.

These criteria are essential for ensuring the study's relevance and integrity, focusing on the specific population of interest and enabling researchers to draw meaningful conclusions about HIV discordance within the targeted urban context of Gasabo district.

3.8 Data Analysis

This analysis plan was structured to meticulously investigate the impacts of socio-demographic, behavioral, clinical, psychosocial, and relationship factors on HIV outcomes. The process started with rigorous data cleaning to address missing data, outliers, and inconsistencies. Descriptive analysis followed, providing a detailed understanding of the dataset through frequency distributions, summary statistics, and visualizations of social demographics variables. In addition, Bivariate analysis identified significant associations between each variable and HIV status using chi-squared tests where statistical significance was measured at p-value <0.05. The study culminated in multivariate logistic regression models that assessed the combined effects of significant predictors while adjusting for confounders. The study reported adjusted odds Ratio, 95% CI, and p-value.

3.9 Ethical-considerations

A clearance letter turned into-received from the ethical research Committee of the college of Rwanda faculty of Public fitness. Permission become sought from the Gasabo district by way of providing the clearance letter from the faculty to get records from Kibagabaga clinic. informed consent become requested from all the research participants using an informed consent form signed with the aid of each participant. individuals who felt uncomfortable have been allowed to withdraw at any moment throughout the records series system without any penalty. information

changed into treated with utmost confidentiality the use of numbers as opposed to names and confined get entry to to data by non-researchers.

Table 1 illustrates the socio-demographic characteristics of a population of 254 individuals, highlighting distinct trends across various demographic markers. In gender distribution, males are predominantly represented with 165 (65%) compared to females who account for 89 (35%). The age group 26-35 years comprises the largest segment at 71 (28%), emphasizing a younger adult population. Educationally, the highest completion is at the university level with 71 (28%), showing a significant presence of higher education within the group. Occupation-wise, salaried positions lead at 58 (22.8%), reflecting a substantial portion of the population in formal employment. Religious affiliations are diverse, with Catholics being the most prevalent at 69 (27.2%). (see table 1)

Variable(s)	Number(n)	Percentage (%)
Gender
Female	89	35
Male	165	65
Age in years
18-25	68	26.8
26-35	71	28
36-45	52	20.5
>45	63	24.8
Education
A'level	56	22
O'level	57	22.4
Primary school	70	27.6
University level	71	28
Occupation
Business	41	16.1
Casual labor	44	17.3
Driver	36	14.2
Motorist	38	15

Figure 2 shows the HIV Prevalence among discordant couples, in 2020 it was 18.1%, while in 2021 was 13.4%, in 2022 was 31.5%, in 2023 was 23.6% and in 2024 was 13.4%.

4.2. Bivariate analysis of socio-demographic characteristics and HIV infection among discordant couples

The bivariate analysis of socio-demographic characteristics and HIV infection among discordant couples highlights two significant associations. First, age appears to play a critical role in infection rates, particularly among those over 45 years, where 41 individuals (65.1%, p-value = 0.0052) tested positive, suggesting a higher vulnerability to HIV infection. Secondly, occupation, specifically for

drivers, is associated with a markedly higher rate of HIV positivity, with 25 drivers (69.4%, p-value = 0.0167) being infected. (See table 2)

Table 2: shows the socio-demographic characteristics and HIV infection among discordant

*couples*
		HIV Status
	Negative	Positive
Variable(s)	No(row%)	No(row%)	P-Value
Gender			0.895
Female	44(49.4)	45(50.6)
Male	83(50.3)	82(49.7)
Age in years			0.0052
18-25	37(54.4)	31(45.6)
26-35	40(56.3)	31(43.7)
36-45	28(53.8)	24(46.2)
>45	22(34.9)	41(65.1)
Education			0.547
A'level	25(44.6)	31(55.4)
O'level	26(45.6)	31(54.4)
Primary school	39(55.7)	31(44.3)
University level	37(52.1)	34(47.9)
Occupation			0.0167
Business	25(61)	16(39)
Casual labor	24(54.5)	20(45.5)
Driver	11(30.6)	25(69.4)
Motorist	19(50)	19(50)
No occupation	19(51.4)	18(48.6)
Salaried	29(50)	29(50)
Religion			0.254

Table 3 provides a detailed exploration of primary characteristics and their correlation with HIV infection among discordant couples, highlighting several significant associations. Notably, engaging in transactional sex shows a marginally significant correlation with HIV positivity, with 39 individuals (51.3%, p-value = 0.0471) being positive, suggesting the potential risk associated with such behavior. A more pronounced risk is observed among those with multiple sex partners, where those without multiple partners exhibit a higher infection rate of 75 (57.3%, p-value = 0.017), underscoring the importance of limiting sexual partners in reducing HIV transmission. Additionally, a diagnosis with STIs also correlates with a higher HIV infection rate, with 77 positive cases (53.5%, p-value = 0.0205), highlighting the critical link between STI management and HIV risk reduction. Furthermore, relationship type emerges as a significant factor; individuals in monogamous relationships have an unexpectedly higher rate of HIV infection, at 67 (55.4%, p-value = 0.0102), indicating that even monogamous setups among discordant couples carry substantial transmission risks. (See Table 3)

Table 3:shows the primary characteristics and HIV infection among discordant couples

		HIV Status
	Negative	Positive
Variable(s)	No(row%)	No(row%)	P-Value
Transactional Sex			0.0471
Always	37(48.7)	39(51.3)
Condom use	30(50.8)	29(49.2)
Never	29(44.6)	36(55.4)
Sometimes	31(57.4)	23(42.6)
Multiple Sex			0.017


No	56(42.7)	75(57.3)
Yes	71(57.7)	52(42.3)
Sex Under
Influence			0.706
No	68(51.1)	65(48.9)
Yes	59(48.8)	62(51.2)
Diagnosis with
STIs			0.0205
No	60(54.5)	50(45.5)
Yes	67(46.5)	77(53.5)
Attended PrEP and PEP			0.38
No	68(52.7)	61(47.3)
Yes	59(47.2)	66(52.8)
Access to HIV
Services			0.166
No	74(54)	63(46)
Yes	53(45.3)	64(54.7)
HIV-related
Stigma			0.802
No	64(49.2)	66(50.8)
Yes	63(50.8)	61(49.2)
HIV Status Communication			0.954
Not discussed at all	25(50)	25(50)
Open and frequent	30(54.5)	25(45.5)
Rarely discussed	27(49.1)	28(50.9)
Somewhat open	23(46.9)	26(53.1)
partner	22(48.9)	23(51.1)
Depression Due to HIV Status			0.98
Always	28(50.9)	27(49.1)
Never	33(50.8)	32(49.2)
Rarely	32(47.8)	35(52.2)

	34(50.7)	33(49.3)
Length			0.765
1 to 2 years	32(51.6)	30(48.4)
6 months to 1 year	36(50.7)	35(49.3)
Less than 6 months	27(44.3)	34(55.7)
More than 2 years	32(53.3)	28(46.7)
Relationship Type			0.0102
Casual	73(54.9)	60(45.1)
Monogamous	54(44.6)	67(55.4)
Relationship Satisfaction			0.0523
Neutral	65(47.1)	73(52.9)
Very satisfied	62(53.4)	54(46.6)

4.4. Logistic regression of the associated risk factors of HIV infection among the discordant couples

Table four presents a logistic regression analysis of hazard factors for HIV infection among discordant couples, that specialize in adjusted odds ratios (AOR) and their significance. significantly, people over forty five years antique exhibit significantly higher odds of infection, with an AOR of 2.37 (95% CI: 1.10-five.12, p-price = 0.027), highlighting age as a essential issue in HIV susceptibility. similarly, drivers face a markedly multiplied danger, with an AOR of 4.seventy seven (ninety five% CI: 1.seventy one-thirteen.31, p-price = zero.003), pointing to occupational risks that contribute to HIV risks. moreover, having multiple sex partners drastically elevates HIV contamination odds, with an AOR of 1.67 (95% CI: 1.31-2.88, p-price = 0.016). (see table four)

Table 4: Logistic regression of the associated risk factors of HIV infection among the discordant couples

HIV Outcome	COR (95%CI)	P-value	AOR (95%CI)	P-Value
Age in years
18-25	1.00		1.00
26-35	1.83(1.35,1.90)	0.018*	0.93(0.45,1.90)	0.85
36-45	1.12(0.47,2.31)	0.909	1.02(0.47,2.21)	0.949
>45	2.37(1.12,6.12)	0.033*	2.37(1.10,5.12)	0.027*
Occupation
Business	1.00		1.00
Casual labor	1.37(0.59,3.65)	0.299	1.47(0.59,3.65)	0.399
Driver	4.03(1.71,13.01)	0.013*	4.77(1.71,13.31)	0.003*
Motorist	2.22(0.82,5.42)	0.123	2.12(0.82,5.52)	0.12
No occupation	1.37(0.61,4.17)	0.357	1.57(0.61,4.07)	0.347
Salaried	2.63(0.85,5.76)	0.179	2.03(0.85,4.86)	0.109
Transactional sex
Never	1.35(0.61,2.55)	0.635	1.25(0.61,2.56)	0.535
Sometimes	1.68(1.32,1.83)	0.0314*	0.68(0.32,1.43)	0.314
Condom use	1.02(0.49,2.11)	0.945	1.02(0.49,2.11)	0.945
Always	1.00		1.00
Having multiple sex partners
Yes	1.52(1.31,1.88)	0.006	1.67(1.31,2.88)	0.016
No	1.00		1.00
Diagnosis with STIs
Yes	0.49(0.06,0.59)	0.0148	1.49(0.86,2.59)	0.148
No	1.00		1.00
Relationship type
Monogamous	1.57(1.11,2.69)	0.009	1.57(0.91,2.69)	0.098
Casual	1.00		1.00

This take a look at aimed to evaluate the superiority of HIV contamination amongst discordant couples who examined HIV repute at Kibagabaga health facility over a length from 2020 to 2024. The statistics discovered a noteworthy increase in the share of HIV-positive individuals many of the couples, highlighting a critical shift within the HIV contamination dynamics inside this population. further analysis confirmed that the following factors are key predictors of HIV infection amongst discordant couples: multiple sexual partners, age of greater than forty five years, and driver profession.

have a look at findings showed that having multiple sexual partners become a ability hazard aspect for HIV infection among discordant couples. these findings are similar with different research like the examine conducted. studies which include Dunkle et al. (2008) and the partners in Prevention HSV/HIV Transmission have a look at team (2010) display that more than one partnerships make bigger the risk of HIV transmission thru multiplied publicity possibilities, which includes to drug-resistant virus traces. those findings are regular across specific regions, including sub-Saharan Africa, where a meta-evaluation by means of Mah and Halperin (2010) underscores the correlation among more than one concurrent partnerships and better HIV infection costs. moreover, psychological and social dynamics additionally play a critical function, as visible in research with the aid of Chai et al. (2014) in China, which factors to the want for culturally tailored interventions to deal with those elements effectively. Prevention techniques highlighted by Allen and Meinzen-Derr (2000) emphasize the importance of lowering the range of sexual partners and continually the usage of condoms to mitigate transmission risks among discordant couples.

Our findings found out that couples with ages extra than forty five years had been are threat of HIV infection. but, these consequences and constant with different findings. The findings that couples over the age of 45 are at risk of HIV contamination might first of all seem unexpected however are well-supported by using the literature, reflecting a broader fashion in public fitness knowledge that HIV chance is not restrained to younger individuals by myself. research inclusive of that conducted by Brooks et al. (2016) highlights that older adults have interaction in hazard behaviors similar to younger populations however are regularly neglected in preventive interventions. organic and behavioral adjustments with age, which include decreased condom use and changes in sexual characteristic, make a contribution to improved threat. furthermore, socio-

economic elements may also lead older adults to form relationships with more youthful partners, probably altering risk dynamics. research by way of Schick et al. (2014) and Zablotska et al. (2018) additionally emphasize that older adults are much less in all likelihood to be tested for HIV because of healthcare vendors' assumptions approximately their sexual pastime, that may put off diagnosis and remedy. This convergence of things underscores the want for healthcare techniques that emphasize education, testing, and prevention tailor-made to all age corporations, as echoed in comparative research like the ones with the aid of Skolnik et al. (2019), reinforcing the significance of addressing HIV danger across various populations and age brackets.

have a look at findings showed that couples wherein one of them became a driving force showed a more risk of HIV infection and this is steady with other research. The commentary that couples in which one associate is a driving force are at an expanded hazard of HIV infection is supported by severa research that check out the precise occupational dangers associated with mobile jobs. for example, drivers regularly spend long periods away from domestic, that can lead to engagement in high-danger sexual behaviors, together with interactions with commercial sex workers, as mentioned in research like those through Delany-Moretlwe et al. (2010). This transient lifestyle also can result in social isolation, further increasing the probability of seeking companionship in dangerous contexts. moreover, Lichtenstein (2015) highlights that truck drivers are specially vulnerable due to their common exposure to environments wherein casual sex is greater commonplace. Comparative studies throughout regions, which includes the examine by means of Ramjee and Gouws (2017), confirms higher prices of HIV amongst drivers, emphasizing the want for focused intervention techniques

Prevalence of hiv infection and factors associated with discordant couples receiving hiv test in Gasabo district

3.5 Sampling technique

3.8 Data Analysis

3.9 Ethical-considerations