Seroprevalence of Human Immunodeficiency Virus and Hepatitis B in Blood Donors at the N’Zérékoré Regional Blood Transfusion Centre in Guinea ()
1. Introduction
Blood transfusion saves lives and reduces morbidity and mortality for many diseases and clinical conditions, but it is not without risk [1]. Every patient who receives a blood transfusion is at risk of contracting a post-transfusion infection such as HIV, hepatitis B virus (HBV), hepatitis C virus (HCV) or syphilitic infection, due to the shortcomings of the various national blood transfusion programmes, which often have inadequate infrastructure and limited financial resources, and sometimes have unqualified staff [2]. In 2023, according to the WHO, the prevalence of blood transfusion-related infection in low-income countries was 2.00 to 6.02% for HIV, 0.5 to 1.67% for HBV and 0.60 to 1.81% for HCV [3].
In 2016, in a study of 599 donors in the Democratic Republic of the Congo (DRC), researchers found a prevalence of 8.01% for HBV and 2.67% for HIV [2]. In the same year, another group of researchers found an overall seroprevalence of 9.7% for HBV and 5.8% for HIV in 4458 donors [4]. Finally, a study carried out in Senegal in 2021 on 2613 donors showed that 10.5% were HBsAg positive, compared with 0.38% carrying HIV markers [5]. In a study of 8055 donors, researchers also found that 14.77% carried HBsAg, compared with 2.16% for HIV [6]. In Guinea, the first study available online, carried out in 2012 on 6401 blood donations to the Centre National de Transfusion Sanguine of Guinea (CNTS), revealed a seroprevalence of 14.94% for HBV and 1.63% for HIV [7]. An annual report from Guinea’s CNTS reported 9.02% for hepatitis B and 3.75% for HIV [8]. In the recent literature, studies of HIV and HBV marker carriage data are incomplete in Guinea. There are no studies in the N’Zérékoré region on HIV and HBV markers in blood donors. The results of this study, the aim of which was to determine the seroprevalence of HIV and hepatitis B, as well as the factors associated with seropositivity for these pathogens in blood donors received at the N’Zérékoré regional blood transfusion centre in Guinea, are thus reported.
2. Material and Methods
2.1. Study Population
This was a retrospective cohort of blood donors who came to the N’Zérékoré Regional Blood Transfusion Centre over 5 years (January 2016 to December 2020). The study population consisted of adults aged 18 to 60 years and weighing 60 kg or more, who were either voluntary donors (the majority) or family donors (compensatory donation) in whom diagnostic tests for HIV, hepatitis, syphilis and blood grouping had been performed during the study period. We proceeded to an exhaustive sampling of all donors meeting our inclusion criteria (above), whose socio-demographic characteristics (gender, age, residence, level of education, profession...) and biological test results (blood group, HIV, HBV and Syphilis status) are well recorded in the registries and/or electronically during the five years covering the study. The sampling procedure consisted of manual counting of cases in the laboratory registers, with the agreement of the regional director of blood transfusion, using an agreed survey form. The Alere HIV-1/2 test was used to diagnose HIV, and the procedures are described below. The “Determine HIV 1 and 2” test is an immunochromatographic test for the qualitative detection of HIV-1 and HIV-2 antibodies. The sample is deposited on the deposition zone, migrates to the conjugate zone where it builds up and mixes with the colloidal selenium-Ag conjugate. This mixture continues to migrate across the solid surface to the immobilised recombinant Ag synthesised at the patient window. The appearance of a horizontal bar on the control side ensures the validity of the test. If anti-HIV Ac is present, it binds to the selenium colloid conjugate antigen and the patient window Ag forming a red line at the patient window. If not present, the selenium colloid conjugate crosses the patient window without forming a red line. The principle behind “Determine HBsAg” is similar to that for HIV [9]. The Determine results were confirmed using the Multisure test, a rapid test that detects most of the virus carriers.
MP Multisure HIV 1/2 Confirmatory Test is a qualitative immunochromatographic assay for the rapid in vitro detection and differentiation of antibodies to Human Immunodeficiency Virus Types 1 and 2 (HIV-1 and HIV-2) in human serum or plasma. It is intended for professional use as a supplemental test on human serum or plasma samples found to be repeatedly reactive by screening procedures. The Multisure HIV 1/2 Confirmatory Test is your Solution to Confirmatory Test in < 30 minutes.
For HBV, an in vitro immunochromatographic test detecting hepatitis B surface antigen (HBsAg) was used. The Centre Regional de Transfusion de N’Zérékoré is a public reference centre covering the transfusion units of seven health districts in the forest region of Guinea and located in the prefecture of N’Zérékoré (Figure 1). Data collection lasted 5 months and consisted of a physical and electronic document review, during which information on sociodemographic characteristics and the results of immunoserological tests included in the documents were consulted. All subjects for whom information was incomplete or could not be found were excluded from the study.
2.2. Ethical Aspects
The retrospective aspect of the study made it impossible to obtain the participants’ consent. However, the data were collected anonymously and the protocol was approved by the Scientific Committee of the Faculty of Health Sciences and Techniques of the Gamal Abdel Nasser University of Conakry (Guinea). The study was conducted in accordance with the Declaration of Helsinki.
2.3. Statistical Analysis of Data
The data was entered using a kobo collect Ver-sion1.25.1 form and stored on the kobo Toolbox server. The raw data downloaded in Excel format were analysed using R Version 4.0 software. All analyses were performed with a 5% bilateral alpha risk. A descriptive analysis was carried out, followed by Chi-2 and Student’s t tests, and a multivariate logistic regression.
3. Results
3.1. Demographic Characteristics of the Study Population
Our study included 9029 blood donors, 79% (7129) of whom were male, with a sex ratio of 3.7 (Figure 1). The average age of the population was 30, with extremes ranging from 18 to 60. The 25 to 34 age group was in the majority, at 44.2%. The majority of our population lived in urban areas (74%), and the most common occupational category was farmer (19.9%), followed by manual worker (19.5%) (Table 1).
3.2. Clinical and Biological Description of the Study Population
In this study, blood typing was one of the priority activities, and the results showed that more than half the donors had blood type O (55.6%). The majority of donors (89.5%) had no previous blood donation experience (first-time donors). We observed a seroprevalence of 3.6% for HIV, 13.4% for hepatitis B (HBsAg) and 0.2% for HIV/HBV co-infection. Seropositive donors for both pathogens were predominantly in the 25 - 34 age group (49.5%) for HIV and 47.2% for HBV (P-value < 0.001) (Table 1). During the study, the prevalence of HIV/hepatitis B co-infection detected was 0.
Figure 1. Geographical map of the prefecture of N’Zérékoré, location of the Regional Blood Transfusion Centre.
Figure 2. Donor inclusion flow chart at the N’Zérékoré Regional Blood Transfusion Centre.
Table 1. Comparative analysis of the characteristics of blood donors at the N’Zérékoré Regional Blood Transfusion Centre according to HIV serology results.
Characteristics |
Positive N = 321 |
Negative N = 8708 |
P-value |
Age in year |
|
|
<0.001 |
[18, 24] |
41 (12.8%) |
1932 (22.2%) |
|
[25, 34] |
159 (49.5%) |
3826 (44.0%) |
|
[35, 44] |
99 (30.8%) |
2212 (25.4%) |
|
[45, 60] |
22 (6.9%) |
727 (8.4%) |
|
Missing |
0 |
11 |
|
Average age |
30 (26 - 36) |
30 (25 - 36) |
0.2 |
Gender |
|
|
0.044 |
Women |
82 (25.5%) |
1818 (20.9%) |
|
Male |
239 (74.5%) |
6890 (79.1%) |
|
Residene |
|
|
0.076 |
Rural |
97 (30.2%) |
2247 (25.8%) |
|
Urban |
224 (69.8%) |
6461 (74.2%) |
|
Professional categories |
|
|
0.001 |
Health agent |
6 (1.9%) |
188 (2.2%) |
|
No |
10 (3.1%) |
175 (2.0%) |
|
Farmers |
73 (22.7%) |
1725 (19.8%) |
|
Students |
20 (6.2%) |
905 (10.4%) |
|
Student |
10 (3.1%) |
287 (3.3%) |
|
Continued
Civil servant |
19 (5.9%) |
640 (7.3%) |
|
Merchands/Traders) |
46 (14.3%) |
1527 (17.5%) |
|
Mechanic |
7 (2.2%) |
229 (2.6%) |
|
Housekeeper |
58 (18.1%) |
1184 (13.6%) |
|
Military |
14 (4.4%) |
144 (1.7%) |
|
Worker |
58 (18.1%) |
1704 (19.6%) |
|
Blood Group |
|
|
0.9 |
A |
54 (16.9%) |
1594 (18.3%) |
|
AB |
11 (3.4%) |
293 (3.4%) |
|
B |
78 (24.4%) |
1973 (22.7%) |
|
O |
177 (55.3%) |
4844 (55.7%) |
|
Missing |
1 |
4 |
|
History of blood donation |
|
|
<0.001 |
First-time donor |
320 (99.7%) |
7759 (89.1%) |
|
Former donor |
1 (0.0%) |
949 (10.9%) |
|
HBsAg results |
|
|
<0.001 |
Positive |
18 (5.6%) |
1191 (13.7%) |
|
Negative |
303 (94.4%) |
7 517 (86.3%) |
|
n (%); Median (EI) |
Chi-square test for independence; Student’s t test |
Note: Average age 30, extremes [18 and 60]. Ratio (M/F) = 3.7.
Comparative analysis of the characteristics of blood donors at the Nzérékoré Regional Blood Transfusion Centre according to HBsAg results revealed a seroprevalence of 3.56% for HIV infection among blood donors (Table 2). The 25 to 34 age group was more represented, i.e. 49.5% with a value (P < 0.001). Males were in the majority (74.5%) and lived mainly in urban areas (69.8%). The occupational category most affected was farmers (22.7%, P = 0.001). Almost all donors were first-time donors (99.7%, P < 0.001). In this series, age, serological status and history of blood donation were factors associated with HIV positivity (P < 0.05) (Table 3).
Multivariate analysis of HBsAg seropositivity and socio-demographic characteristics showed a prevalence of 13.4%, predominantly in the 25 - 34 age group [0.98 (0.82; 1.16, P < 0.001]. Male donors were the most represented with [1.16 (0.93; 1.45), P < 0.2]. Donor origin was dominated by urban areas [0.96 (0.83; 1.11), P < 0.2] and the most common socio-professional category was mechanics (Table 4). Group B had the highest proportion [1.02 (0.85; 1.23), P < 0.006]. HBsAg-positive donors were first-time donors. During the study, HIV serostatus and blood donation history were factors associated with HBsAg seropositivity. The prevalence of HIV/HBV co-infection was 0.2%.
Table 2. Multivariate analysis of HIV seropositivity and blood donor characteristics.
Characteristics |
Positive |
Negative |
P-value |
Age in year |
|
|
|
[18, 24] |
— |
— |
|
[25, 34] |
1.89 |
1.31 - 2.77 |
0.001 |
[35, 44] |
2.01 |
1.35 - 3.05 |
0.001 |
[45, 60] |
1.42 |
0.81 - 2.45 |
0.2 |
Sexe |
|
|
|
Woman |
— |
— |
|
Male |
0.77 |
0.53 – 1.15 |
0.2 |
Residence |
|
|
|
Rural |
— |
— |
|
Urban |
0.92 |
0.71 – 1.21 |
0.6 |
Professional categories |
|
|
0.001 |
Heath Agent |
— |
— |
|
No |
1.90 |
0.68 - 5.77 |
0.2 |
Farmers |
1.31 |
0.60 - 3.48 |
0.5 |
Students |
1.11 |
0.45 - 3.15 |
0.8 |
University Student |
1.26 |
0.45 - 3.82 |
0.7 |
Civil servant |
0.94 |
0.38 - 2.64 |
0.9 |
Merchands/Traders |
0.91 |
0.41 - 2.41 |
0.8 |
Mechanic |
1.15 |
0.37 - 3.70 |
0.8 |
Housekeeper |
1.25 |
0.55 - 3.35 |
0.6 |
Military |
3.38 |
0.29 - 9.89 |
0.017 |
Morker |
1.20 |
0.55 - 3.19 |
0.7 |
Blood group |
|
|
|
A |
— |
— |
|
AB |
1.07 |
0.52 - 1.99 |
0.9 |
B |
1.18 |
0.83 - 1.70 |
0.4 |
O |
1.09 |
0.80 - 1.50 |
0.6 |
AgHBs Results |
|
|
|
Positive |
— |
— |
|
Negative |
3.04 |
1.94 - 5.10 |
<0.001 |
History of blood donation |
|
|
|
First-time donor |
— |
— |
|
Former donor |
0.01 |
0.00 - 0.04 |
<0.001 |
OR = odds ratio, CI = confidence interval |
Table 3. Comparative analysis of blood donor characteristics at the Nzérékoré Regional Blood Transfusion Centre according to HBsAg result.
characteristics |
Positive N = 1209 |
Negative N = 7820 |
P-value |
Age in year |
|
|
0.001 |
[18, 24] |
286 (23.7%) |
1687 (21.6%) |
|
[25, 34] |
570 (47.2%) |
3415 (43.7%) |
|
[35, 44] |
276 (22.8%) |
2035 (26.1%) |
|
[45, 60] |
76 (6.3%) |
673 (8.6%) |
|
Missing |
1 |
10 |
|
Average age |
30 (25 - 35) |
30 (25 - 37) |
<0.001 |
Gender |
|
|
>0.9 |
Continued
Women |
254 (21.0%) |
1646 (21.0%) |
|
Male |
955 (79.0%) |
6174 (79.0%) |
|
Residence |
|
|
0.011 |
Rural |
350 (28.9%) |
1994 (25.5%) |
|
Urban |
859 (71.1%) |
5826 (74.5%) |
|
Professional categories |
|
|
0.003 |
Heath Agent |
20 (1.7%) |
174 (2.2%) |
|
No |
24 (2.0%) |
161 (2.1%) |
|
Farmers |
284 (23.5%) |
1514 (19.4%) |
|
Student |
137 (11.3%) |
788 (10.1%) |
|
University Student |
41 (3.4%) |
256 (3.3%) |
|
Civil Servant |
75 (6.2%) |
584 (7.5%) |
|
Merchands/Traders) |
186 (15.4%) |
1387 (17.7%) |
|
Mechanic |
39 (3.2%) |
197 (2.5%) |
|
Housekeepers |
179 (14.8%) |
1063 (13.6%) |
|
Military |
22 (1.8%) |
136 (1.7%) |
|
Worker |
202 (16.7%) |
1560 (19.9%) |
|
Blood Group |
|
|
0.006 |
A |
244 (20.2%) |
1404 (18.0%) |
|
AB |
34 (2.8%) |
270 (3.5%) |
|
B |
306 (25.4%) |
1745 (22.3%) |
|
O |
623 (51.6%) |
4398 (56.3%) |
|
Missing |
2 |
3 |
|
History of blood donation |
|
|
<0.001 |
First-time donor |
1207(99.8%) |
2 (0.2%) |
|
Former donor |
948 (12.1%) |
6872 (87.9%) |
|
AgHBs result |
|
|
<0.001 |
Positive |
18 (1.5%) |
303 (3.9%) |
|
Negative |
1191 (98.5%) |
7517 (96.1%) |
|
n (%); Median (EI) |
<0,001 |
Chi-square test for independence; Student’s t test |
|
Note: Average age 30, extremes [18 and 60]. Ratio (M/F) = 3.7.
Table 4. Multivariate analysis of HBsAg positivity and blood donor characteristics.
Characteristics |
OR |
95% IC |
P-value |
Age in year |
|
|
|
[18, 24] |
— |
— |
|
[25, 34] |
0.98 |
0.82 - 1.16 |
0.8 |
[35, 44] |
0.78 |
0.63 - 0.95 |
0.013 |
[45, 60] |
0.67 |
0.50 - 0.89 |
0.006 |
Gender |
|
|
|
Women |
— |
— |
|
Male |
1,16 |
0,93 - 1,45 |
0.2 |
Residence |
|
|
|
Rural |
— |
— |
|
Urban |
0.96 |
0.83 - 1.11 |
0.6 |
Continued
Professionnal Categories |
|
|
|
Health Agent |
— |
— |
|
No |
1.18 |
0.62 - 2.26 |
0.6 |
Farmers |
1.43 |
0.89 - 2.41 |
0.2 |
Student |
1.35 |
0.82 - 2.33 |
0.3 |
Unisersty Student |
1.25 |
0.71 - 2.28 |
0.4 |
Civi Servant |
1.13 |
0.67 - 1.97 |
0.7 |
Merchands/Traders) |
1.07 |
0.67 - 1.81 |
0.8 |
Mechanic |
1.49 |
0.83 - 2.73 |
0.2 |
Housekeeper |
1.38 |
0.84 - 2.37 |
0.2 |
Military |
1.38 |
0.71 - 2.70 |
0.3 |
Worker |
1.06 |
0.66 - 1.79 |
>0.9 |
Blood Group |
|
|
|
A |
— |
— |
|
AB |
0.71 |
0.47 - 1.03 |
0.081 |
B |
1.02 |
0.85 - 1.23 |
0.8 |
O |
0.84 |
0.71 - 0.99 |
0.033 |
HIV status |
|
|
|
Positive |
— |
— |
|
Negative |
3.04 |
1.94 - 5.09 |
<0.001 |
History of blood donation |
|
|
|
First-time donor |
— |
— |
|
Former donors |
0.01 |
0.00 - 0.04 |
<0.001 |
OR = odds ratio, CI = confidence interval |
<0.001 |
4. Discussion
We conducted this study to determine the seroprevalence of HIV and hepatitis B among blood donors at the N’Zérékoré Regional Blood Transfusion Centre (Figure 2). The study was faced with a number of limitations, including the lack of information due to the deterioration or unavailability of certain donor registers, the illegibility of the handwriting in places (erasures, overwriting), the use of rapid diagnostic tests for the detection of serological markers, and the lack of molecular biology tests or nucleic acid detection tests which are capable of identifying infections in blood earlier and with greater sensitivity. The latter remain inaccessible and unaffordable for countries with limited resources [10]. Although they are sometimes rejected, their use is increasingly desirable, with good sensitivity, as older methods such as ELISA and Western blots have become more widely used [11]. It should be remembered that certain clinical situations, such as HIV seropositivity, can reduce the sensitivity of the rapid test [12] and also the quality of some rapid diagnostic tests, which remains to be desired and raises the issue of the use of accurate tests and safe transfusions. As for the availability of health information, this is a real problem in developing countries in general, and in Guinea in particular, because of the lack of computerisation of the system and the humidity of our landscape.
In this study, donor age ranged from 18 - 60 years, with a predominance of donors aged 25 - 34 (44.2%). Similar results have been reported by some authors in Mali, with a proportion of 40.36% of the population studied [6]. Other researchers have also reported that the 26 - 35 age group was more represented, with proportions of 57.1%, 38.4% and 36.75% respectively [13] [14] [15]. The high representation of young people in this study could be explained by the fact that they are potentially the most active and supposed to be in good health, and therefore more likely to donate blood.
Male donors were the most represented in this study (79.0%). A similar finding has been reported by other authors, in which the majority of donors were male (90.7%) [16] [17] [18]. The most represented occupational category was farmers (19.9%), followed by manual workers (19.5%). It should be remembered that agriculture is the activity practised by the majority of the Guinean population, with manual workers in second place. In the blood group determination, more than half of the donors were of blood group O (55.6%). Similar results have been reported by researchers in Gabon [19] and several other researchers in Cameroon [20] [21] [22]. In this cohort, first-time donors were more heavily represented (89.5%). This can be explained by the fact that donors are volunteers, and it is difficult to build donor loyalty. In this study, we observed a seroprevalence of 3.6% for HIV, 13.4% for HBsAg and 0.2% for HIV/HBV co-infection. In the case of HIV, this prevalence far exceeds the national figure of 1.5% according to the latest Guinea Demographic and Health Survey [23]. The prevalence of hepatitis B is similar to that reported in the literature, as Guinea is in a high-prevalence area [24]. With regard to co-infection, the proportion of 0.2% seems to be much lower than the reality in Guinea, as shown by Keita et al. [25]. In Sub-Saharan Africa, blood transfusion represents a potential risk of contamination. However, the high HIV seroprevalence in this study could be attributed partly to the performance of the system set up at the regional blood transfusion centre in N’Zérékoré (Guinea), and partly to the diagnostic tests used, which may result in false positives in the absence of confirmatory molecular biology tests. Although the study was unable to determine whether the infections were recent or chronic, it did help to improve transfusion safety, since the presence of just one of these immunoserological markers is sufficient to discard a blood bag and thus avoid contamination [11] [26]. The results of HBV screening in blood transfusion centres vary. They are 9.7% in Sierra Leone [27], 20.4% in Burkina Faso [28], 7.3% in Gabon [17] and 10.5% in Senegal [5]. With regard to coinfection, contrary proportions have been reported by several researchers. It was 8.49% of HBV/HIV-positive patients in Guinea [24]; 6.47% in the Central African Republic [9], in Mali in two studies it was 1.90% and 2.9% respectively [15] [16]. The association between HIV and hepatitis B can be explained by their modes of transmission and the risk factors associated with these infections, which are identical. The occupational category most affected was farmers (22.7%), P = 0.001). Contrary results have been reported by authors in Mali 4.13% [15]. In this study, age, serological status and history of blood donation were factors associated with HIV positivity (P < 0.05).
5. Conclusion
The study assessed the seroprevalence and associated factors of HIV and HBsAg among blood donors at the Centre Regional de la Transfusion Sanguine de N’Zérékoré (Guinea). We reported a high prevalence of HIV and HBsAg, with a predominance of men, a high representation of people from urban areas, generally farmers and with blood group O for both diseases. Almost all of the donors had never given blood. Sex, serological status and history of blood donation were factors associated with HIV positivity. For HBsAg, HIV serostatus and blood donation history were factors associated with seropositivity. Strict pre-donation screening of all donors could be a solution to ensure a good supply of quality blood for transfusion safety.
Acknowledgements
The authors would like to thank the technical staff. We would also like to thank all the participants in this study.
Authors’ Contributions
All the authors have contributed to the design, translation or layout of this paper, albeit to different degrees. Contributed to conception and data collection: AC, ET, INH, YY, ISD, MSD, KK and AT. Contributed to study design: AC, ET, INH, KK and AT. Contributed to data analysis: ET, INH, AT, YY, AC, JC and MC. Wrote the paper: ET, AC, INH, DK, KK, TMT, BM and SB. Correction and formatting: AC, AT, KK, MSD, BM and SB.