The co-prevalence of Hepatitis and Malaria in Patients Attending a Major Tertiary Healthcare in North Central, Nigeria.

doi:10.21203/rs.3.rs-4862774/v1

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Research Article

The co-prevalence of Hepatitis and Malaria in Patients Attending a Major Tertiary Healthcare in North Central, Nigeria.

https://doi.org/10.21203/rs.3.rs-4862774/v1

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Background

Many developing countries in Africa have shown high prevalence of malaria, HBsAg and HCV in recent times. The presence of these diseases in a population have caused severe public health problems worldwide. This study investigates the prevalence of malaria, Hepatitis B (HBsAg) and Hepatis C (HCV) in patients attending Bishop Murray Medical Centre (BMMC).

Methods

Blood specimens were collected from two hundred and forty eight, 248 patients from BMMC, Makurdi and were screened for malaria, HBsAg and HCV using rapid serological kits. High prevalence of malaria, HBsAg and HCV was observed among the patients.

Results

Malaria had a prevalence of 29.1%. prevalence of HBsAg. Prevalence of malaria was 29.4% (n = 73/248) in BMMC, Makurdi, prevalence of HBsAg was 5.2% (n = 13/248) and prevalence of HCV was 4.0% (n = 10/248) in BMMC. The prevalence of malaria according to clinical manifestation of patients attending BMMC, Makurdi is shown in table 6, 28.5% of patients who complained of fever tested positive for malaria while 71.5% of fever patients were negative. Prevalence of malaria was 32.0% in patients experiencing headache, while 68.0% were negative. Those with backpain had no malaria (0.0%), persistent crying also had no malaria (0%), hotness of body (100%), blurred vision (100%), stomach pain (100%) and joint pain all had 100% prevalence rates respectively. The difference in the prevalence rate of malaria according to clinical manifestation was not statistically significant (p > 0.05; p = 0.272).

Conclusions

Prevalence of Malaria, HBsAg and HCV was high in Benue State. Findings of this study provide a critical data to assess the impact of current prevention and control strategies in Nigeria, and serve as a reference for designing and implementing effective public health management programmes towards the 2030 elimination goal of the diseases.

Prevalence

Malaria

Hepatitis

patients

BMMC

Makurdi

Hepatitis B infection is a major global health problem. Hepatitis B virus (HBV) causes inflammation or infection of the liver, it causes a chronic infection and puts people at high risk of death from cirrhosis and liver cancer [1]. Globally, WHO estimates that, more than 2 billion people are living with HBV infection and over 350 million people are believed to be at risk of developing complications of chronic hepatitis such as cirrhosis and primary hepatocellular carcinoma [2, 3]. Although global prevalence rates vary, the tropical region of the world has the highest infection rates.

In Africa, mortality risk associated with HBV is about 25%, with a chronic infection prevalence of over 50 million people [4]. Hyper endemic infection rates have been reported in the Western part of Africa, indicating over 8% of the population chronically infected with HBV [5]. In Nigeria, a national survey carried out in 2016, reported HBV prevalence rate to be 12.2%⁶. Transmission routes of HBV include body fluids, contaminated sharps needles and razors, transmission from mother to child during childbirth, sexual contact, and most commonly, blood transfusion. Blood transfusion is one of the major risk factors for HBV transmission, due to occult HBV infection among blood donors [4].

Hepatitis C virus (HCV) infection is a public health concern affecting more than 170 million people worldwide [6–7]. Globally, about 130–150 million people are living with chronic HCV infection [8–10] with about 350,000–500,000 lives lost every year [11]. Infection begins as acute and usually asymptomatic during early stages [12, 13]. In most untreated cases, the infection progresses into chronic infections and gradually develops liver fibrosis which then leads to cirrhosis, liver damage, and hepatocellular carcinoma (HCC) [14]. In Africa, the prevalence of HCV is between 0.1% and 17.5%. There are many risk factors of acquiring HCV infection. In the Sub-Saharan Africa, practices such as dental surgery, therapeutic injection, intravenous drug, and age have been reported as major risk factors associated with HCV infection [15–17].

Malaria is the most prevalent mosquito-borne parasitic disease throughout tropical and subtropical regions of the world. The disease is widespread in the tropical and subtropical regions that exist in a broad band around the equator [18]. This includes much of sub-Saharan Africa, Asia, and Latin America [19]. In 2021, 247 million cases of malaria worldwide resulted in an estimated 619,000 deaths, with 77 percent being 5 years old or less. Around 95% of the cases and deaths occurred in sub-Saharan Africa. Rates of disease decreased from 2010 to 2014, but increased from 2015 to 2021. [20] Malaria is a major public health concern in Nigeria, with an estimated 68 million cases and 194 000 deaths due to the disease in 2021 [20]. This study is aimed at determining the prevalence rate of Hepatitis B, Hepatitis C and Malaria, the associated risk factors of the diseases and the socio-demographic information of the patients attending a major tertiary health institution in Makurdi, Benue State, Nigeria.

The specific objectives of the study were to determine the prevalence rates of Hepatitis B, Hepatitis C and Malaria in Benue State; determine the risk factors associated with the prevalence of Hepatitis B, Hepatitis C and Malaria in Benue State; correlate the association between Plasmodium, Hepatitis B surface antigen and Hepatitis C virus; and determine the socioeconomic and demographic characteristics of the patients attending a major tertiary health institution in Makurdi, Benue State, Nigeria.

Research Design

This study is a six (6) months hospital based prospective longitudinal and cross-sectional survey which was carried out at Bishop Murray Medical Centre (BMMC), Makurdi. Benue State, Nigeria.

Ethical clearance

Ethical clearance was sought and ethical approvals gotten from BMMC, Makurdi respectively. Consenting individuals were recruited for the study during the daily clinic. Semi-structured questionnaires were administered after explaining the details of the study and procedure.

Inclusion criteria

Consented individuals with febrile illness were used for the study and they included patients who were sent to the laboratory for test.

Exclusion criteria

These included patients who do not have any symptoms of febrile illness.

Sample Size

Determination of sample size

Sample size was determined using this formula; n = Z² P q/d²

Where n = desired sample size

Z = standard and normal deviation usually set at 1.96 or approximately 2.0 which correspond to 95% (0.05) confidence level.

P = proportion in the target population estimated to have the particular characteristics.

q = 1.0-p

d = degree of accuracy usually set at 0.05

The sample size was determined in view of the prevalence rate of 25.5% for malaria and hepatitis from previous studies carried out in Kano, Nigeria [21]. Number of subjects who were studied in each group was calculated to be 200. An attrition rate of 10% was added to the number to arrive at the sample size.

The calculation was based on fisher’s sample size formula [22].

N = minimum sample size,

Z = (1.96) constant mean deviate,

1 = constant

P = local prevalence of similar previous study = 25.5% ²¹.

d = Degree of precision adopted for the study = 0.05

N = (1.96)² X 0.25 X 0.83/(005)² = 0.535

N = 0.535/0.0025

N = 224

Using attrition rate of 10%, we have 224/0.9 = 248

Sample collection

Blood specimens were collected from individuals who came to the laboratory for tests and experiencing symptoms of the diseases. The study population was made up two hundred and forty-eight (248) patients from Bishop Murray Medical Centre. These included patients who were at the laboratory for test, (male, female, adult and children). Two hundred and forty-eight (248) questionnaires were administered to adults who came to the laboratory for tests.

Data Collection and Serological Examination

Blood specimens (about 5 ml) were collected using sterile disposable syringes from the veno-punctured vein under aseptic conditions. All the specimens were tested for malaria, hepatitis B surface antigen and hepatitis C virus using rapid serological kits for malaria, HbsAg and HCV (Global, Germany). The study was conducted between July, 2016 and December, 2016. All tests were carried out according to standard procedures and practices following manufacturer’s instructions [23, 24].

Laboratory procedures for malaria test

Samples of blood (about 5ml) were obtained intravenously with the assistance of hospital phlebotomist. The blood samples were transferred into an ethylenedi aminetetraacetic acid (EDTA) bottle to prevent blood coagulation. Two blood films, one thin and one thick were made from the blood samples. The thick and thin smears were prepared on clean, dry microscope glass slides and were allowed to dry. The thin smear was fixed in methanol and both smears were stained with 2% Giemsa BDH Laboratory supplies; Poole BH 15 ITD England [25].

The slides were viewed under a microscope using oil immersion at 100x magnification. Staining of the slides and parasite counting were made independently by two microscopists with discrepancies resolved by a senior microscopist who ensured quality control. The films were viewed for the presence of parasite. A negative result would mean absence of parasites at 200 high power fields. Parasite density was quantified against 200 leucocytes on an assumed leucocyte count of 8000 per ul of blood [26]. The degree of parasite density was graded as mild, moderate, and severe when the counts were < 1000 parasites/ul of blood, 1000–9999/ul of blood, and 10,000/ul of blood, respectively, following the method

described by Dawaski et al., (2016) [27].

Parasites/ul of blood = No. of asexual stages × 8000 leukocytes/200 leukocytes.

Test procedure for malaria was carried out using care start. The strip from the sealed foil punch was gently removed and the sample number written on the strip. After which the sample number was also written on the cassette, then 5µl of whole blood was added into ‘’S’’ well and 60ul assay buffer was added. The result was read after 20 minutes and written down.

Interpretation of test result

The presence of two colour band (One band in the control and another band in the test indicates a positive result).

The presence of only one band in the control area indicates a negative result.

The test is invalid if the Control band does not appear.

Hepatitis B and hepatitis C virus testing

The skin over the tip of the middle or ring finger of the respondent was punctured with a sterile lancet to obtain hanging drops of finger stick whole blood after it was cleaned with alcohol swab. The hanging drops of finger stick whole blood were allowed to fall onto the “specimen pad” of the hepatitis B surface antigen and HCV rapid test strips (Abon Biopharm [Hangzhou] Co. Ltd., P. R., China). Then, a drop of buffer solution was added. The result was read at 15 min according to the manufacturer's instructions. A strip with two distinct coloured lines was read as positive while with a single-coloured line appearing at the control region was read as negative. The rapid test strips have sensitivity of 99.0% (98.1–99.6%) and specificity of 99.1% (98.5–99.5%).

Laboratory procedure for hepatitis B surface antigen

The strip from the sealed foil punch was removed and sample number was written on the strip. Two (2) drops of whole blood was added into the “sample pad’’ of the test strip and 1 drop of buffer was added thereafter. The result was read after 15 minutes when the red line has appeared.

The presence of two colour band (One band in the control and another band in the test indicates a positive result) for hepatitis B surface antigen. The presence of only one band in the control area indicates a negative result. The test is invalid if the Control band does not appear.

Test procedure for hepatitis C

The presence of two colour band (One band in the control and another band in the test indicates a positive result).

The presence of only one band in the control area indicates a negative result.

The test is invalid if the Control band does not appear.

Data Collection via Questionnaires

Semi structured questionnaire which contained demographic information like age, sex, address, family size, marital status, ethnic group, source of water, educational status and occupation were administered to all the subjects. Other medical information contained in the questionnaire includes prophylaxis, use of insecticides, tribal mark/tattoo, drug abuse, alcohol consumption blood transfusion, previous hospitalization, previous surgery, clinical details and if any any prophylaxis is given.

Data Analysis

Data collected were tabulated and carefully double entered and analyzed using computer statistical package SPSS version 25.0. Chi square test was used to determine associations between variables; correlation coefficients were used to determine relationships between variables. Descriptive statistics (frequency and percentages) were used in data analyses. In all the analyses the confidence level was held at 95% and significance was held at 0.05 level.

Two hundred and forty eight patients (248) attending a tertiary institution in Makurdi, Benue State, Nigeria_ Bishop Murray Medical Centre, Makurdi were screened for Malaria, HBsAg and HCV infections.

The result showed the prevalence of malaria, HBsAg and HCV in relation to gender in Bishop Murray Medical Centre, Makurdi. Results showed that prevalence of malaria in BMMC, Makurdi was 29.1%; prevalence in male was 32.0% while 68.0% of the male were negative. Prevalence of malaria in female was 27.7% while 72.3% were negative (Fig. 1). The difference in the prevalence of malaria by sex in BMMC, Makurdi was not statistically significant (p > 0.05; p = 0.466). Prevalence of HBsAg was 5.2% in BMMC, Makurdi, it was 5.0% in male while 95% of male were negative. Exactly 5.4% of the female tested positive for HBsAg while 94.6% of the female were negative. The difference in the prevalence rates was not statistically significant (p > 0.05; p = 0.888). Prevalence of HCV was 4.0% in BMMC, Makurdi. In male 3.0% were positive while 97.0% were negative. In female 4.7% were positive while 95.3% were negative. The difference was not statistically significant (p > 0.05 (p = 0.497).

The prevalence of malaria, HBsAg and HCV according to marital status in BMMC, Makurdi is shown in Fig. 2. Malaria had a prevalence rate of 34.8% in the singles (65.2% negative) and 26.3% prevalent in the married (73.7% negative). The difference was not statistically significant (p > 0.05 (p = 0.156). Result of HBsAg showed that singles was 6.5% positive (93.5% negative) while the married had prevalence rate of 4.5% (95.5% negative) in BMMC, Makurdi. The difference was not statistically significant (p > 0.05 p = 0.487). For HCV, prevalence was 4.3% in the singles (95.7% negative) and 3.8% in the married (96.2% negative). The difference was not statistically significant (p > 0.05, p = 0. 846).

Prevalence of Malaria, HBsAg and HCV by Income Level in Bishop Murray Medical Centre, Makurdi is presented in Fig. 3. Results showed that 29.7% of the low-income earners tested positive for malaria while 70.3% were negative. Exactly 25.0% of the middle-income earners tested positive for malaria while 75.0% were negative. The difference in prevalence rate of malaria according to income level was not statistically significant (p > 0.05; p = 0.687) according to chi square test. Results for HBsAg showed that 4.7% of the low-income earners were positive for HBsAg while 95.3% were negative. Middle-income had a prevalence of 12.2% for HBsAg while 87.5% were negative. The difference in prevalence rate was not statistically significant (p > 0.05; p = 0.178).

Prevalence of HCV by income level showed that low-income level had a prevalence of 3.9% while middle-income level had a prevalence of 6.3%. The difference in prevalence rate was not statistically significant (p > 0.05; p = 0.641).

Prevalence of malaria by use of insecticide treated net in BMMC, Makurdi was depicted in Fig. 4.0. Patients who use insecticide treated net had a prevalence rate of 26.7% for malaria while 73.3% were negative. Prevalence of malaria was 34.9% in patients who do not use insecticide treated net while 65.1% tested negative for malaria. The difference in prevalence rate of malaria among insecticide net use and non-insecticide net use was not statistically significant (p > 0.05; p = 0.177).

The prevalence of HBsAg and HCV according to source of water was shown in Fig. 5. It showed that prevalence of HBsAg was 3.5% in patients who use borehole water, 1.9% in patients who use water from hawkers and 11.5% in patients who use well water. The difference in prevalence rate was not statistically significant (p > 0.05; p = 0.106). Result for HCV, showed that 7.1% of borehole users tested positive for HCV, water hawkers had 1.9% and well water had none (0.0%). The difference in prevalence rate was not statistically significant (p > 0.05; p = 0.156).

Prevalence of malaria was 29.4% (n = 73/248) in BMMC, Makurdi, prevalence of HBsAg was 5.2% (n = 13/248) and prevalence of HCV was 4.0% (n = 10/248) in BMMC.

The prevalence of malaria according to clinical manifestation of patients attending BMMC, Makurdi is shown in Table 1, 28.5% of patients who complained of fever tested positive for malaria while 71.5% of fever patients were negative. Prevalence of malaria was 32.0% in patients experiencing headache, while 68.0% were negative. Those with backpain had no malaria (0.0%), persistent crying also had no malaria (0%), hotness of body (100%), blurred vision (100%), stomach pain (100%) and joint pain all had 100% prevalence rates respectively. The difference in the prevalence rate of malaria according to clinical manifestation was not statistically significant (p > 0.05; p = 0.272).

Table 1

Prevalence of Malaria by Clinical Manifestation in Bishop Murray Medical Centre, Makurdi
Clinical manifestation	Number examined (%)	Number positive (%)	Number negative (%)
Fever	151 (100)	43 (28.5)	108 (71.5)
Headache	50 (100)	16 (32.0)	34 (68.0)
General body pain	41 (100)	10 (24.4)	31 (75.6)
Back pain	1 (100)	0 (0.0)	1 (100)
Hotness of the body	1 (100)	1 (100)	0 (0.0)
Persistent crying	1 (100)	0 (0.0)	1 (100)
Blurred vision	1 (100)	1 (100)	0 (0.0)
Stomach pain	1 (100)	1 (100)	0 (0.0)
Joint pain	1 (100)	1 (100)	0 (0.0)
Total	248 (100)	73 (29.4)	175 (70.6)
X² = 8.744, df = 8; p > 0.05 (p = 0.272)

According to Table 2, prevalence of malaria was 29.3% in those on prophylaxis while patients not on prophylaxis had 29.6% prevalence rate. The differences in prevalence were not statistically significant (X² = 0.003, df = 1; p > 0.05, p = 0.953). Those with tattoo or tribal marks had 31.4% prevalence rate while those without tattoo or tribal marks had 28.9%. The differences in prevalence were not statistically significant (X² = 0.116, df = 1; p > 0.05, p = 0.733). It was also observed that 22.2% of the patients who had been transfused tested positive for malaria while 30% of those who had not been transfused tested positive for malaria. The differences in prevalence were not statistically significant (X² = 0.486, df = 1; p > 0.05, p = 0.486).

Patients who had been hospitalized had 28.6% prevalence of malaria while those who had never been hospitalized had 29.7% prevalence. The differences in prevalence were not statistically significant (X² = 0.30, df = 1; p > 0.05, p = 0.862). Those who had undergone surgery had 26.7% while 29.6% of those who had never had surgery tested positive for malaria. The differences in prevalence were not statistically significant (X² = 0.059, df = 1; p > 0.05, p = 0.808).

For those who indulge in drug abuse, none (0.0%) tested positive for malaria while as high as 29.8% of those who don’t indulge in drug abuse were positive.

The differences in prevalence were not statistically significant (X² = 1.267, df = 1; p > 0.05, p = 0.260). Those who consume alcohol had 18.5% while those who do not drink alcohol had 30.8% prevalence of malaria. The difference in prevalence was statistically significant (X² = 1.738, df = 1; p < 0.05, p = 0.1).

Table 2

Prevalence of Malaria according to Medical Records\History in BMMC, Makurdi
Medical information	Number examined (%)	Number positive (%)	Number negative (%)	Chi square value
Prophylaxis
Yes	140 (100)	41 (29.3)	99 (70.7)
No	108 (100)	32 (29.6)	76 (70.4)
Total	248 (100)	73 (29.4)	175 (70.6)	X² = 0.003, df = 1; p > 0.05 (p = 0.953)
Tattoo/Tribal Marks
Yes	51 (100)	16 (31.4)	35 (68.6)
No	197 (100)	57 (28.9)	140 (71.1)
Total	248 (100)	73 (29.4)	175 (70.6)	X² = 0.116, df = 1; p > 0.05 (p = 0.733)
Blood Transfusion
Yes	18 (100)	4 (22.2)	14 (77.8)
No	230 (100)	69 (30.0)	161 (70.0)
Total	248 (100)	73 (29.4)	175 (70.6)	X² = 0.486, df = 1; p > 0.05 (p = 0.486)
Previous Hospitalization
Yes	63 (100)	18 (28.6)	45 (71.4)
No	185 (100)	55 (29.7)	130 (70.3)
Total	248 (100)	73 (29.4)	175 (70.6)
				X² = 0.30, df = 1; p > 0.05 (p = 0.862)
Previous surgery
Yes	15 (100)	4 (26.7)	11 (73.3)
No	233 (100)	69 (29.6)	164 (70.4)
Total	248 (100)	73(29.4)	175 (70.6)	X² = 0.059, df = 1; p > 0.05 (p = 0.808)
Drug abuse
Yes	3 (100)	0 (0.0)	3 (100)
No	245 (100)	73 (29.8)	172 (70.2)
Total	248 (100)	73(29.4)	175 (70.6)	X² = 1.267, df = 1; p > 0.05 (p = 0.260)
Alcohol consumption
Yes	27 (100)	5 (18.5)	22 (81.5)
No	221(100)	68 (30.8)	153 (69.2)
Total	248 (100)	73(29.4)	175 (70.6)	X² = 1.738, df = 1; p > 0.05 (p = 0.01)

Table 3 showed the prevalence of HBsAg according to Medical Records in BMMC, Makurdi. Prevalence of HBsAg was 5.0% among patients on prophylaxis. The difference in prevalence among patients on prophylaxis was not statistically significant (X² = 2.350, df = 1; p > 0.05, p = 0.125). Prevalence of HBsAg was 5.9% among patients with tattoo or tribal marks. The difference in prevalence among patients with tattoo was not statistically significant. (X² = 0.053, df = 1; p > 0.05, p = 0.818). Prevalence of HBsAg was 5.6% among patients who were transfused. The difference in prevalence among patients who were transfused was not statistically significant (X² = 0.004, df = 1; p > 0.05, p = 0.95). Prevalence of HBsAg was 4.8% among those who were previously hospitalized. The difference in prevalence among patients who were previously hospitalized were not statistically significant (X² = 0.039, df = 1; p > 0.05, p = 0.843). As high as 13.3% prevalence of HBsAg was found in patients who had surgery. The difference in prevalence among patients who had surgery was not statistically significant (X² = 2.104, df = 1; p > 0.05, p = 0.147). Prevalence was 0.0% in patients who consume alcohol and 0.0% in patients who abuse drugs. The difference in prevalence among them was not statistically significant (X² = 1.676, df = 1; p > 0.05, p = 0.195) and (X² = 0.168, df = 1; p > 0.05, p = 0.682).

Table 4

Prevalence of HBsAg according to Medical Records in BMMC, Makurdi
Medical information	Number examined (%)	Number positive (%)	Number negative (%)	Chi square value
Prophylaxis
Yes	140 (100)	7 (5.0)	133 (95.0)
No	108 (100)	6 (5.6)	102 (94.1)
Total	248 (100)	13 (5.2)	232 (94.8)	X² = 0.038, df = 1; p > 0.05 (p = 0.846)
Tattoo/Tribal Marks
Yes	51 (100)	3 (5.9)	48 (94.1)
No	197 (100)	10 (5.1)	187 (94.9)
Total	248 (100)	13 (5.2)	232 (94.8)	X² = 0.053, df = 1; p > 0.05 (p = 0.818)
Blood Transfusion
Yes	18 (100)	1 (5.6)	17 (94.4)
No	230 (100)	12 (5.2)	218 (94.8)
Total	248 (100)	13 (5.2)	235 (94.8)	X² = 0.004, df = 1; p > 0.05 (p = 0.95)
Previous Hospitalization
Yes	63 (100)	3 (4.8)	60 (95.2)
No	185 (100)	10 (5.4)	175 (94.6)
Total	248 (100)	13 (5.2)	235 (94.8)
				X² = 0.039, df = 1; p > 0.05 (p = 0.843)
Previous surgery
Yes	15 (100)	2 (13.3)	13 (86.7)
No	233 (100)	11 (4.7)	222 (95.3)
Total	248 (100)	13 (5.3)	235 (94.8)	X² = 2.104, df = 1; p > 0.05 (p = 0.147)
Drug abuse
Yes	3 (100)	0 (0.0)	3 (100)
No	245 (100)	13 (5.3)	232 (98.7)
Total	248 (100)	13 (5.2)	235 (94.8)	X² = 0.168, df = 1; p > 0.05 (p = 0.682)
Alcohol consumption
Yes	27 (100)	0 (0.0)	27 (100)
No	221 (100)	13 (5.9)	208 (94.1)
Total	248 (100)	13 (5.2)	235 (94.1)	X² = 1.676, df = 1; p > 0.05 (p = 0.195)

According to Table 5, exactly 5.7% of patients on prophylaxis tested positive for HCV while patients who are not on prophylaxis had 1.9% positive. The difference in prevalence was not statistically significant (X² = 2.350, df = 1; p > 0.05 (p = 0.125). Only 2.0% of those with tattoo or tribal marks tested positive for HCV while those without tattoo or tribal marks were 4.6%. This difference in prevalence was not statistically significant (X² = 0.712, df = 1; p > 0.05, p = 0.399). Only 5.6% of the patients who had been transfused tested positive for HCV while 3.9% of those who had not been transfused tested positive. The differences in prevalence were not statistically significant (X² = 1.16, df = 1; p > 0.05, p = 0.733).

Patients who had been hospitalized had only 3.2% prevalence of HCV while those who had never been hospitalized had 4.3% prevalence. The differences in prevalence were not statistically significant (X² = 0.161, df = 1; p > 0.05, p = 0.689). Those who had undergone surgery had 6.7% while 3.9% of those who had never had surgery tested positive for HCV. The differences in prevalence were not statistically significant (X² = 0.128, df = 1; p > 0.05, p = 0.593). For those who indulge in drug abuse, none (0.0%) tested positive for HCV while as high as 29.8% of those who don’t indulge in drug abuse were positive. (X² = 0.128, df = 1; p > 0.05, p = 0.721). The differences in prevalence were not statistically significant. Those who consume alcohol had 18.5% while those who do not drink alcohol had 30.8% prevalence of HCV. The difference in prevalence was statistically significant (X² = 0.008 df = 1; p > 0.05, p = 0.927).

Table 5

Prevalence of HCV according to Medical Records/History in BMMC, Makurdi
Medical information	Number examined (%)	Number positive (%)	Number negative (%)	Chi square value
Prophylaxis
Yes	140 (100)	8 (5.7)	132 (94.3)
No	108 (100)	2 (1.9)	106 (98.1)
Total	248 (100)	10 (4.0)	238 (96.0)	X² = 2.350, df = 1; p > 0.05 (p = 0.125)
Tattoo/Tribal Marks
Yes	51 (100)	1 (2.0)	50 (98.0)
No	197 (100)	9 (4.6)	188 (95.4)
Total	248 (100)	10 (4.0)	238 (96.0)	X² = 0.712, df = 1; p > 0.05 (p = 0.399)
Blood Transfusion
Yes	18 (100)	1 (5.6)	17 (94.4)
No	230 (100)	9 (3.9)	221 (96.1)
Total	248 (100)	10 (4.0)	238 (96.0)	X² = 1.16, df = 1; p > 0.05 (p = 0.733)
Previous Hospitalization
Yes	63 (100)	2 (3.2)	61 (96.8)
No	185 (100)	8 (4.3)	177 (95.7)
Total	248 (100)	10 (4.0)	238 (96.0)
				X² = 0.161, df = 1; p > 0.05 (p = 0.689)
Previous surgery
Yes	15 (100)	1 (6.7)	14 (93.3)
No	233 (100)	9 (3.9)	224 (96.1)
Total	248 (100)	10 (4.0)	238 (96.0)	X² = 0.128, df = 1; p > 0.05 (p = 0.593)
Drug abuse
Yes	3 (100)	0 (0.0)	3 (100)
No	245 (100)	10 (4.1)	235 (95.9)
Total	248 (100)	10 (4.0)	238 (96.0)	X² = 0.128, df = 1; p > 0.05 (p = 0.721)
Alcohol consumption
Yes	27 (100)	1 (3.7)	26 (96.3)
No	221 (100)	9 (4.1)	212 (95.9)
Total	248 (100)	10 (4.0)	238 (96.0)	X² = 0.008 df = 1; p > 0.05 (p = 0.927)

This study has demonstrated high prevalence of malaria, HBsAg and HCV among patients in BMMC, Makurdi, Benue State. Malaria had a prevalence of 29.1% in BMMC, Makurdi. In Nigeria, higher prevalence had been reported by previous studies. As high as 66.7% was reported by Dawaki et al. (2016) [27]. Prevalence of malaria was higher in males (32.0%) than females (27.7%). %. In Nigeria, higher prevalence had been reported by previous studies. As high as 66.7% was reported by Dawaki et al. (2016) [27], Nmadu et al. (2015) [28] reported 64.0% and Prevalence of malaria was higher in males than females. Furthermore, the prevalence of malaria in this study was lower than the results of a cross-sectional study conducted among students of a southwest Nigerian Federal University (80.6%) [29], and in Southern Tanzania (78.0%) [30]. The low prevalence in this study compared to the other previous malaria study in Nigeria might be attributed to the usage of insecticide treated nets as well as the setting. Insecticide treated nets (ITNs) and indoor residual spraying have both been demonstrated to reduce malaria [31].

It was also discovered in this study that prevalence of malaria was higher in the singles than the married (singles 34.8%, married 26.3%) in BMMC, Makurdi. According to Ngum et al. (2023) [32], the prevalence of malaria varies from place to place, even within the same country, and may be due to differences in socio-demographic, environmental and climatic factors.

The high prevalence rates observed in this study agrees with reports of Baiden et al. (2022) [33]. Malaria is prevalent in tropical and subtropical regions of the world. Nigeria is considered a tropical country in Africa and this high prevalence was attributed to the high temperature and relative humidity of the environment. Oladeinde et al. (2012) [34] had stressed that malaria transmission is higher among the rural settings than the urban areas, and may be due to the higher vector density, poor housing status, and poor drainage systems in rural settings.

High prevalence of HBsAg was also observed in this study (BMMC- 5.2%), other studies had reported higher prevalence of HBsAg [35]. Recent studies by Eleje et al., (2020) [36] had also reported higher prevalence of 12.2% in Nigeria. Similarly Nuobiap et al. (2015a) [37] and Nuobiap et al. (2015b) [38] had also reported higher prevalence rates of 10.1% and 12% among blood donors in Cameroon. In constrast, Jatau et al. (2009) [39] reported a low prevalence of 4.3% from Zaria while Agbede et al. (2007) [40] reported a prevalence of 5.7% from Ilorin.

Prevalence of HBsAg was observed to be higher in females than in males. Prevalence of HBsAg in Bishop Murray Medical Centre, Makurdi was 5.2% in males and 5.4% in females. This finding supports reports from other studies in Nigeria, where 11.6% HBsAg prevalence was reported from Maiduguri among pregnant women [41]. Frambo et al. (2014) [42] had previously reported higher prevalence rate of 9.7% among pregnant women in Beau. Work done by Forbi et al. (2008) [43] had also reported very high prevalence rate of 17.1% from female sex workers in Nassarawa State. In contrast, other studies had reported prevalence of HBsAg to be higher in males than females, studies from Uganda and other sub-Saharan African countries, reported chronic HBV infections to be more common in males [44].

Results of this study demonstrated a high prevalence of HCV in Benue State. Prevalence of HCV in Bishop Murray Medical Centre, Makurdi was 4.0%, prevalence in males was 3.0% and females 4.7%. Similarly high prevalence of between 3.4–8.4% had been reported by Lanini et al. (2016) [45] in Nigeria. Countries with high prevalence of HCV are Mongolia 9.6–10.8%, Georgia 6.7%, Gabon 4.9–11.2%, Cameroon 4.9–13.8% and Nigeria had a prevalence of 3.1–8.4% (Lanini et al., 2016) [45]. This agrees with the findings of this study. In Africa, the prevalence of HCV is between 0.1% and 17.5%. In Rwanda, prevalence of HCV infection has been reported in specific groups of the populations such as in pregnant women and in patients infected with tuberculosis and HIV [46–48]. A prevalence of 4.9% was estimated in a 2011 study [49], but a recent review by Karoney and Siiki indicates that this figure could be an underestimation [50]. Prevalence of HCV seems to be increasing over the years, this is because of challenges such as barriers to screening, cost-related factors, and inadequate knowledge and awareness of hepatitis C [51].

Prevalence of HBsAg and HCV was also observed to be higher among the singles than the married (HBsAg -singles 6.5%, married 4.5% and HCV-singles 4.3%, married 3.8%) in BMMC, Makurdi. There are many risk factors of acquiring HCV infection [15].

Prevalence of malaria was 46.8% in patients who use insecticide treated net and 70.7% in patients who do not use insecticide treated net. The difference in the prevalence rate between them was statistically significant (p < 0.05; p = 0.01). Insecticide treated nets are a form of personal protection from mosquito bite and it has been shown to reduce malaria [52]. In several African settings, insecticide treated nets were shown to reduce the death of children under 5 years from malaria by about 20% [53].

Results of this study (BMMC, Makurdi) showed prevalence of malaria was 28.5% in patients who complained of fever, 32.0% in patients experiencing headache, those with backpain had no malaria (0.0%), persistent crying also had no malaria (0%), hotness of body (100%), blurred vision (100%), stomach pain (100%) and joint pain all had 100% prevalence rates respectively. The difference in the prevalence rate of malaria according to clinical manifestation was not statistically significant (p > 0.05; p = 0.272). Adults with malaria tend to experience chills and fever as well as headache, fatigue, abdominal discomfort, and muscle pain[54]. Children tend to have more general symptoms: fever, cough, vomiting, and diarrhea [54]. Initial manifestations of the disease common to all malaria species are similar to flu-like symptoms[55]. The presentation may include headache, fever, shivering, joint pain, vomiting, hemolytic anemia, jaundice, hemoglobin in the urine, retinal damage, and convulsions [56].

It was discovered that prevalence of malaria was higher (29.7%) among the low-income earners than the middle-income earners (25%). The difference in prevalence rate of malaria according to income level was not statistically significant (p > 0.05; p = 0.687). Exactly 4.7% of the low-income earners tested positive for HBsAg, 12.2% of middle-income earners. Prevalence of HCV was 3.9% in low income-level and 6.3% in middle-income level. According to Gollin and Zimmermann, (2007) [57], malaria is commonly associated with poverty and has a significant negative effect on economic development. Research had proven that prevalence of malaria is comparatively higher among the rural settings than the urban areas, and may be due to the higher vector density, poor housing status, and poor drainage systems in rural setting [32].

Of particular interest from our findings is the difference in the prevalence of HBsAg among the low-income earners and the middle-income earners. It was observed that HBsAg is most prevalent among the middle-income earners, and may have been intensified by the lack of awareness about the implications of HBV infection, under-developed shared care pathways for HBV management, and high-risk lifestyles. Inability to receive treatment due to inadequate funds [20]. This profound lack of access to treatment and care and people's inability to afford mosquito bed nets may be responsible for the high prevalence rate [58]. To reduce HBV prevalence in Nigeria, a dedicated focus on socio-economic, cultural and population health factors are required, for example, equity of access of health care across rural and urban regions.

Prevalence of HCV was 5.7% in patients on prophylaxis, 2.0% in those with tattoo or tribal marks, 5.6% in the patients who had been transfused. Patients who had been hospitalized had only 3.2% prevalence of HCV, those who had undergone surgery had 6.7%, those who indulge in drug abuse, had none (0.0%), those who consume alcohol had 18.5% prevalence of HCV. Studies reported that in Sub-Saharan Africa, practices such as dental surgery, therapeutic injection, intravenous drug, and age have been reported as major risk factors associated with HCV infection [16, 17].

The prevalence of Malaria, HBsAg and HCV was high in Benue State. The World Health Organizations’ criteria for HBV endemicity was (≥ 8%; high, 2–7%; moderate and < 2%; low). Prevalence was higher in females than in the males in all the diseases studied. Prevalence was higher in the singles than the married. Prevalence was higher among the age group 26–40 years in all the diseases. It was also observed that malaria was more prevalent in those who do not use ITNs compared to those who ITNs. Clinical manifestation such as fever, headache, general body pains, hotness of body and blurred vision were associated with the prevalence of malaria. Factors such as hospitalization, blood transfusion and drug abuse were strongly associated with HCV. Factors such as source of water, hospitalization and surgery, were implicated in the prevalence of HBsAg. Findings of this study provide a critical data to assess the impact of current prevention and control strategies in Nigeria, and serve as a reference for designing and implementing effective public health management programmes towards the 2030 elimination goal of the diseases.

Acknowledgements

We acknowledge the role of the health directorates in Bishop Murray Medical Center, Makurdi, Benue State. and their support and facilitation of the data collection.

Authors’ contributions

Both authors participated in designing the questionnaire, statistical analysis, interpreting the data, writing major parts of the manuscript, drafting, and preparing the manuscript for submission. Both authors contributed to the data collection, data entry, review of the literature, and statistical analysis. JKA revised all the statistical analyses and conceptualized the study design. All authors read and approved the final manuscript.

Funding

This study did not receive any specific grant from any funding institution.

Availability of data and materials

The datasets generated and analyzed during the current study are not publicly available due to privacy considerations of the participants but are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

Ethics approval was obtained from the research ethics committee of the Bishop Murray Medical Center, Makurdi, Benue State, Nigeria and the College of Biological Sciences, Joseph Sarwuan Tarka University Makurdi, Makurdi, Benue State, Nigeria, and administrative approval was obtained from the Bishop Murray Medical Center Health Directorate. The participants’ confidentiality was maintained by using code numbers rather than personal identifiers on the questionnaires. The aims of the study were explained to each participant before filling out the questionnaire. Written informed consent was obtained from all participants in the study. All measures were performed following the relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

All authors declare that they have no competing interests.

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The co-prevalence of Hepatitis and Malaria in Patients Attending a Major Tertiary Healthcare in North Central, Nigeria.

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Abstract

Background

Methods

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INTRODUCTION

METHOD

Research Design

Ethical clearance

Inclusion criteria

Exclusion criteria

Sample Size

Determination of sample size

Sample collection

Data Collection and Serological Examination

Laboratory procedures for malaria test

Interpretation of test result

Hepatitis B and hepatitis C virus testing

Laboratory procedure for hepatitis B surface antigen

Test procedure for hepatitis C

Data Collection via Questionnaires

Data Analysis

RESULTS

DISCUSSION

CONCLUSION

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References

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