An Enhanced Computer Vision Platform for Clinical Diagnosis of Malaria

Arnon Houri-Yafin, Yochay Eshel, Natalie Lezmy, Sarah Levy-Schreier,

Caitlin Lee Cohen, Joseph Joel Pollak1 and Seth J. Salpeter

Sight Diagnostics Ltd., Israel

Benedicta Larbi and Emma Wypkema

Department of Clinical Hematology Lancet Laboratories, Lancet Corner, South Africa

Veena Dayan

Department of Parisitology, City Hospital Mangalore, India

All Correspondences to: Seth Salpeter, Sight Diagnostics Ltd., Jerusalem Technology Park, Jerusalem 96951, Israel, E-mail: seth@sightdx.com

ABSTRACT

Accurate malaria diagnosis is necessary to prevent unnecessary deaths and curb malaria drug resistance related to unnecessary treatment. While numerous diagnostic assays exist, the need for a low-cost, rapid and highly accurate malaria test remains. Here we evaluate the diagnostic performance of a computer vision platform, the Sight Diagnostic P2 device for malaria diagnosis, speciation and parasite quantification. The trial was conducted at two centers on Plasmodium falciparum and Plasmodium vivax samples, using different testing protocols: 374 samples were collected at City Hospital Mangalore India and 167 samples were collected at Lancet Laboratories Johannesburg South Africa. At City Hospital, the device diagnoses were compared to RT-PCR results while at Lancet Laboratories the device diagnoses were compared to a panel of tests provided by the clinic. For identification of malaria, the device demonstrated a sensitivity of 97% and a specificity of 99.5% at City Hospital India, and a sensitivity of 97.8% and a specificity of 97.5% at Lancet Laboratories Johannesburg. For speciation, the device correctly identified 87.5% for Plasmodium Vivax and 93.5% for Plasmodium Falciparum at City Hospital India. Lastly, comparing the device parasite count with that of trained microscopes, produced an average pearsons correlation of 0.87.

Keywords: Malaria; Diagnostic; Computer vision; Machine Learninga

Introduction

ccurate diagnosis of malaria is imperative to Areduce morbidity, prevent resistance to anti-malarials, and limit the number of adverse treatment effects from unnecessary use [1]. Furthermore, many studies show that infectious malaria carriers maintain a very low parasitemia, making sensitive detection technologies imperative for treatment targeted at epidemiologic control [2,3]. Many governmental health organizations now require patients to undergo malaria testing before receiving any anti-malarial medicine. As a result, the WHO forecasts an increase in global demand for malaria tests from 500 million in 2012 to nearly 1 billion

tests by 2020 [1,4].

Due to increased demand for malaria tests, reliable, simple and highly accurate malaria diagnostic is needed. Globally, only 77% of suspected cases in the public sector are tested, while in Africa only 47% of cases are assayed [5]. A recent report showed that in some regions 81% of people taking ACT therapy are not infected, while only 31% of the positive cases received the treatment [6]. This glaring disparity not only leaves the needy untreated but encourages the further development of drug resistant malaria strains.

While new diagnostic modalities for malaria have emerged in recent years, none have the ideal set of test characteristics. According to the World Health Organization, an ideal test would be inexpensive,

consistent, highly-sensitive, adequately specific, quantitative, and species-differentiating. Microscopy remains the gold standard malaria test worldwide [7,8], as it supports direct parasite identification and also provides monitoring of systemic inflammation and its response to therapy [9]. However, microscopy can be very inaccurate, needs extensive analysis, and requires highly trained staff [10,11]. Notably, malaria is associated with systemic spiraling of innate inflammation and additional blood abnormalities, further complicating microscopy examination [12]. Numerous reports have also shown inconsistent sensitivity of microscopist due to the high volume of tests and varied level of skill among malaria technicians [13,14]. Rapid diagnostics tests (RDTs) continue to increase in popularity and market share as they have significantly improved the diagnosis of malaria in remote, inaccessible areas [15]. However, RDTs have significant limitations that make many practitioners wary of their use, including decreased sensitivity at low parasitemia, inability to quantitate parasite burden, and inconsistencies between brands in their ability to detect and differentiate different malaria species [16,17]. Recent improvements to malaria diagnostic technologies include Polymerase Chain Reaction (PCR) and loop-mediated isothermal amplification (LAMP), which offer superior sensitivity, speciation and parasitemia but are impractical for the vast majority malaria-endemic areas [18,19].

Malaria diagnosis using computer vision offers a potential solution to the shortcomings of other technologies. An

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An Enhanced Computer Vision Platform…

automated microscopist maintains the advantages of a microscopist with significant improvements in speed, cost, and consistency. Previous attempts at a creating a computer microscopist have not surpassed the development stage [20,21]. A recent report from our group, described a clinically available automated microscopist which was tested with the National Institute of Malaria Research India

  1. The device, the SightDx P1 malaria platform, was tested on 431 patients and demonstrated a sensitivity of 97.05%, and a specificity of 96.33% when compared with PCR. Furthermore, the device was able to accurately speciate 73.3% of the PCR Plasmodium falciparum and 91.4% of the PCR Plasmodium vivax samples, and showed a parasitemia correlation with microscopists of 0.89.

Here, we present an enhanced version of the Sight Diagnostic malaria device, the SightDx P2 platform for malaria detection. The device is intended for laboratories performing high volumes of malaria tests as it is capable of scanning a sample in 4 minutes and can hold up to 30 tests. The system has dimensions of 45 x 50 x 58 cm (DxWxH) and can easily fit onto a standard laboratory bench top with minimal installation requirements.

In the following report, we describe the results of clinical studies performed in Mangalore India, and Johannesburg South Africa to evaluate the sensitivity, specificity, speciation and parasite count calculation as compared to standard diagnostic procedures.

Methods

Study design

The study was a double center, prospective, non-randomized, non blinded study conducted at City Hospital, Mangalore India with 374 blood samples from clinically-suspected malaria patients, and at Lancet Laboratories Johannesburg South Africa on 167 clinically suspected malaria patients.

Study Procedures

City Hospital, Mangalore India: Determination of eligibility for malaria treatment was solely based on the clinic’s standard diagnosis protocol and the patients course of treatment and was not altered due to the study or the SightDx diagnostic device. In most cases blood was scanned by the device within 24 hours of sampling. Samples more than 48 hours old were not included in the study. In addition, 100 μL of blood was collected on GE Healthcare FTA Whatman filter paper spots for RT-PCR evaluation. RT-PCR results were considered the standard of comparison for determining the sensitivity, specificity and speciation of the various methods. Lancet Laboratories, Johannesburg South Africa: Samples were provided from malaria tests performed at Lancet Laboratories Johannesburg and at surrounding Lancet Laboratory clinics in South Africa. Samples were tested on the Sight Diagnostic device within 1 week of drawing. RDT and microscopy were performed on all samples. Discrepancies between these tests were evaluated by PCR. Positive samples which were not Plasmodium falciparum or had a parasitemia under 1000 parasites/μL also underwent PCR. All negative samples were reviewed with QBC.

Laboratory Methods

Sight Diagnostic Device Analysis

In all locations digital imaging scanning was carried out onsite. To begin sample diagnosis, 5 μL of patient blood was mixed with a fluorescent dye solution that stained intracellular DNA and RNA. The sample was then loaded into a plastic cartridge and incubated for 5 minutes, during which time the cells formed a monolayer. The stained cells were then excited using 3 different LED light sources (370 nm, 475 nm and 530 nm) after which the imaging system recorded 600 images analyzing ~1.8 million cells. The total scan time per sample was 4 minutes and the device held up to 30 samples which can be loaded in batch. Samples which registered an error on the device due to incorrect user preparation were repeated. Computer vision and statistical models were used to detect the malaria parasites. Using statistical models, the device determined infection status, parasitemia levels, and species.

Parasitemia

Parasitemia counts were performed on 24 positive samples at Lancet laboratories Johannesburg. An expert microscopist analyzed 10 fields at 100X with approximately 100 RBCs counted per field. Parasitemia was calculated as a ratio of infected RBCs to total RBCs.

Real Time PCR Analysis

For PCR experiments performed on samples from City Hospital India, a whole punch was removed from the blood spot on the GE FTA Whatman paper and eluted as previously reported [23]. Real time PCR was performed with Fast Syber Green Master Mix at a volume of 10 μL (Applied Biosystems) using previously published primer sequences [24] for identifying falciparum, vivax and for general Plasmodium (Plu). All reactions were performed in 384 well qPCR plates (Bio-Rad) on a CFX384 real time PCR machine from Bio-rad.

Results

The Sight Diagnostic P2 malaria scanning device is a desktop system for computerized malaria diagnostics (Figures 1A and 1B). The stained blood is loaded into a cartridge which holds five patients samples. To evaluate device performance in a clinical setting, 374 samples were collected and scanned at City Hospital Mangalore and 167 samples were collected and scanned at Lancet Laboratories Johannesburg.

Figure 1: The SightDx Malaria Platform. (A) The P2 malaria scanning device. (B) The loading cartridge holds 5 patient samples.

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Sensitivity and specificity

Sensitivity and specificity were analyzed for all trials (Table 1). For samples scanned at City Hospital India device results were compared to qPCR while for samples scanned at Lancet Johannesburg device results were compared to a final diagnosis based on a combination of several malaria diagnostic assays (Table 1). At City Hospital Mangalore sensitivity was calculated as 97%

Seth J. Salpeter

(167/172) and specificity was calculated as 99.5%

(201/202). For samples scanned at Lancet Laboratories Johannesburg sensitivity was 97.8% (46/47) while specificity was 97.5% (117/120). Positive predictive values (PPV) were 99.4% at City Hospital and 93.8% at Lancet Laboratories, and negative predictive values (NPV) were 97.5% at City Hospital and 99.1% at Lancet Laboratories.

Sensitivity Specificity
Percent Ratio 95% CI Percent Ratio 95% CI
City Hospital India 97% 167/172 0.934-0.988 99.50% 201/202 0.972-0.999
Lancet Labs South Africa 97.80% 46/47 0.843-0.994 97.50% 117/120 0.929-0.991

Speciation

Speciation studies were conducted on samples provided at City Hospital Mangalore (Table 2). At City Hospital, the device distinguished between P.v (Plasmodium vivax ) and P.f (Plasmodium falciparum ) and results were compared to qPCR analysis. A total of 167 samples were identified as positive by the device and were analyzed for species type. The device correctly identified samples with Plasmodium vivax at 87.5% sensitivity (119/136) and Plasmodium falciparum at 93.5% sensitivity (29/31).

City Hospital (India)
Percent Ratio 95% CI
Plasmodium Vivax 87.50% 119/136 0.809-0.92
Plasmodium Falciparum 93.50% 29/31 0.793-0.982

Table 2: Speciation accuracy divided according to treatment groups. Speciation percentages of the trials from City Hospital India are presented in the table, as well as the specific number of patients and confidence Index.

Parasitemia

For cases diagnosed at Lancet Laboratories with thin smear microscopy, parasitemia was provided and compared to values from the device (Figure 2).

Figure 2: Micrscopist compared to the device. At Lancet Laboratories a trained microscopist analyzed 24 slides and the results were compared to the parasitemia reported by the device. The correlation between the two produced a Pearsons correlation coefficient of 0.87.

A comparison of the percentage of infected RBC determined by the microscopist and the device yields a Pearsons correlation coefficient of 0.87. The microscopist calculated parasitemia by analyzing the number of infected red blood cells out of the total number of blood cells.

Discussion

This study evaluated the SightDx P2 malaria detection platform, an enhanced computer vision platform for rapid and automated malaria diagnostics. Previous attempts to develop vision based malaria detection devices have had varying levels of success [21,25-28]. While a specific report showed high sensitivity and specificity [29], others demonstrated relatively low performance numbers. Notably, these papers describe development stage technologies showing initial device construction or preliminary algorithm designs for malaria detection. Previous studies showed problems in cartridge design and focus mechanisms, yielding slow scanning times and poor results. While these reports used complicated microfluidics systems, our study presents an easy to use plastic cartridge which fills quickly upon loading using capillary forces activated by mixing the blood with our stain solution. Moreover, we have solved image focus difficulties, by implementing unique algorithms which allow the scanning system to quickly autofocus on each new field allowing for high quality images of all cells scanned. In a previous study [22] we presented the first clinically available computer vision based reader for malaria diagnostics. The P1 device showed a sensitivity of 97.05%, specificity of 96.33% and speciation of 73.3% Plasmodium falciparum and 91.4% for Plasmodium vivax

  • The P2 device features many functional and performance based improvements over the earlier system. While the P1 device holds only 5 patient samples, the P2 machine holds 30 samples and is capable of asynchronous batch loading. Moreover, the P1 device requires 8 minutes to scan a sample while the P2 device requires only 4 minutes, allowing for the rapid scanning of large volumes of specimens. On a performance level, the device showed a similar sensitivity at an average of 97.4% but a significantly improved specificity at an average of 98.5%. Speciation of Plasmodium vivax was comparable to the previous study at 87.5% while speciation of Plasmodium falciparum was significantly improved at 93.5%.

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Importantly, in contrast to the study on P1 which was performed only in India, the current trial was conducted on samples from both continental Africa and India. Numerous studies have shown the ability of strains of malaria to develop mutations causing significant difficulties in diagnosis [1,30,31]. In particular, it has been shown that RDTs which identify HRP-2 from Plasmodium falciparum can yield false negatives due to specific antigen mutations

  1. Specific regions are known to develop unique genetic variants of even the most standard species of Plasmodium. Our results confirm the devices ability to detect strains of malaria in variety of geographical regions. In the current study, the device maintains a limit of detection of 50 parasites/ μL. While the system is capable of identifying as few as 5 parasites/ μL the current algorithm only identifies a positive sample if it detects more than 50 objects identified as malaria parasites. This limitation was evident from the six cases of false negatives where the parasitemia was found to be under 50 parasites/ μL, explaining the misdiagnoses. Decreasing the current limit of detection causes an increase of false positives reported by the system. False positives have been found to be caused by particles that have flourescence morphology similar to the stained malaria within the RBC. The four false positives found in our study were determined to result from Howell Jolly bodies which are malaria-like DNA/RNA fragments found in RBCs. By collecting larger libraries of samples, as well as samples with Howell Jolly bodies, we will be able to apply machine learning to improve the accuracy of the algorithm classification and overall diagnosis. Additional data collection and algorithm design work will be necessary to further improve the differentiation between malaria and these objects to lower the limit of detection. Several device improvements are currently under development to strengthen diagnostic performance and provide additional clinical information to assist in patient treatment. Speciation for P.v was calculated at 87.5% and P.f at 93.5%, leaving room for increased accuracy. As the device speciation is based on a machine learning algorithm which improves with an increased database, the collection of additional scanned samples of both P.v and P.f should significantly improve speciation results. Moreover, to expand speciation capabilities to Plasmodium ovale , Plasmodium malarie and mixed infection a large library of P.o and P.m and mixed infection samples will need to be collected and analyzed. Additional studies will also be necessary which feature completely blinded data collection as well as PCR ground truth for all samples.

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Prevalence of Haemoparasites (Plasmodium and Microfilaria) in Blood Donors Attending University Of Maiduguri Teaching Hospital (UMTH)

Bukar Alhaji, Mary Ann Amarachi Umeh, Obi Simon Osita, Waziri Gimba, Medugu Jessy Thomus
Department of Haematology, University of Maiduguri Teaching Hospital, Maiduguri,
Anthony Nwobi, Osakue Eguagie Osareniro
Department of Chemical Pathology, Igbinedion University Teaching Hospital, Okada
Olaniyan Matthew Folaranmi
Department of Medical Laboratory Science, Achievers University, Owo
Jeremiah Zaccheaus Awortu.
Department of Medical Laboratory Science, Niger Delta University
All correspondence to: alhajibukar@gmail.com.

ABSTRACT
Haemoparasite,such as Plasmodium and Microfilaria are animal parasite living in the blood of a vertebrate host. The study was aimed to determine the prevalence of Haemoparasite (Plasmodium and Microfilaria) in blood donors attending University of Maiduguri Teaching Hospital. A total of 230 blood donors were recruited for this study using simple random sampling. A semi-structured questionnaire was used to collect data regarding demographic and social profile of the subjects. Giemsa stained thick blood film was used for the detection of malaria parasite while wet preparation was used for the detection of microfilaria. A total of 78 blood donors had malaria parasites while no filarial parasite was recorded showing a prevalence of 33.9% and 0% respectively. The prevalence of malaria parasites in the blood donors was not significantly associated with usage of insecticide and/or insecticide treated net. The prevalence of malaria parasite was however significantly associated with treatment with antimalarial drugs. It is therefore necessary for the government to improve the sanitary condition of Maiduguri which will in turn reduce the availability of breeding sites for mosquitos.

Keywords: Malaria, microfilaria, blood donors.

INTRODUCTION
Blood transfusion is potentially a lifesaving therapeutic procedure and a common form of tissue transplantation which is aimed to provide patients with blood components which they are deficient.1. Although,blood transfusion is generally believed to save human lives, blood can nonetheless be a route for the transmission of infections generally referred to as transfusion transmissible infections (TTIs). TTI occurs when a patient is infected by the same parasite that was present in the donor’s blood. TTIs are broadly classified into viral, bacterial, amoebal or parasitic.Haemoparasite is an animal parasite such as a haemoflagellate or filarial worm living in the blood of a vertebrate host2. These parasites reside eitherin the blood cells or in the plasma. Malaria parasite and Babesiaare haemoparasites that resides in the red blood cells, while leishmania and filarial wormsresides in the white blood cells and the plasma respectively3.
In Nigeria, malaria and filariasis are more prevalent and over the years varying prevalence has been recorded among Nigerian blood donors4. Haemoparasites constitute a serious threat to human race as they can result in increased morbidity and mortality5. Malaria is sporozoan parasite of the genus Plasmodium, its infection is transmitted naturally through the bite of infected female Anopheles mosquitoes6. In endemic areas, malaria transmission is so intense that a large proportion of the population is infected but not made ill by these parasites7. These carriers harbour low levels of the parasitesand shows no clinical signs of infection as they are immune to parasitic illness but not to the infection and for this reason, blood from such donors contains malaria parasite which can easily be transmitted to recipients by blood transfusion.
A bite from an infected mosquito may cause malaria by introducing as few as 15 parasites while a single parasite identified on a thick film (4ul) is equivalent to approximately 10,000 parasites in 450ml unit thereby causing malaria in transfused patients8. Transfusion-transmitted malaria can however have serious consequences, as infection with P. falciparum may prove rapidly fatal when such blood is transfused especially into children under 5 years, pregnant women, trauma victims with acute blood loss and immuno-suppressed patients9. Malaria destroys red blood cells and converts it to methaemoglobin leading to methemoglobinemia causing illness especially in immune compromised individuals 7, 10.

Filariasis on the other hand is a parasitic disease that is caused by thread-like nematodes (roundworms) belonging to the superfamily Filarioidea. These parasites are transmitted from host to host by blood feeding arthropods, mainly black flies and mosquitoes.
As adults, the worms can survive and reproduce for up to 7 years within which the worms gradually build-up in the vessels of their host. This interfereswith the lymphatic system’s ability to fight infection and causes lymph fluid to accumulate in the arms, legs, breasts and male genitals leading to welling and disfigurement3, 11.
In all species, sexually mature female worms release microfilariae, which are their pre-larval stages into the bloodstream of their infected host.If, the blood from microfilaraemic individuals is transfused into a patient, the transfused microfilariae may persist in the recipient’s circulation for up to 3 years12. Recipient of these blood component usually develop post transfusion allergic reactions due to dying microfilariae13.
In Nigeria, screening forparasitic infections is not routinely done in blood banks, nor stipulated in the current National Blood Guidelines. This is because transmission of parasitic infections such as malaria through blood transfusion is generally not regarded as a serious problem in adult and adolescent whose level of immunity is thought to be sufficiently effective in combating post transfusion malaria in an endemic area like Nigeria6. These parasites are prevalent in Nigeria but the extent to which it currently affects blood donors attending UMTH is unknown, we therefore, considered it necessary to contribute some information on this subject.

MATERIALS AND METHOD
This study was conducted at the University of Maiduguri Teaching hospital (UMTH) from February 2017 to May 2017. A total of 230blood donors which are negative to HIV 1/2, HBsAg, Syphilis and HCVwere recruited for the study. These donors were recruited using simple random sampling. Two millitres of the donor’s venous blood was collected into an EDTA container.ABO and RhD blood groups of the donors were determined using tile method. Malaria parasite was qualitatively determined by making thick blood films in duplicates for each blood samples on a clean grease free glass slide. these was allowed to air-dry after which it was stained with Giemsa stain. Stained films were examined under x100 objective lens of microscope with Immersion oil for any stage of malaria parasite. A slide is defined as negative if no asexual stage of the parasite is found after counting 100 microscopic fields.For, microfilaria parasite, a drop of anticoagulated blood was dispensed on a cleaned grease-free slide and covered with cover slip. It was examined microscopically using x10 and x 40 magnification for motile microfilaria. Result were analysed using, percentage and SPSS 20.0 statistical package. Chi-square was used to determine if prevalence was dependent on certain factors. A P-value of less than or equal to 0.05 (p=0.05) was considered as statistically significant.

RESULTS
A total of two hundred and thirty subjects (230) were recruited for the study. The subjects were within the age group of 18-55 years with the age group 20-29 having the
highest mode (47.6%, 110/230) and age group 50-59 years with the least (3%, 7/230).
Table I shows the prevalence of malaria parasite and filarial worms in the blood donors attending UMTH.Out of the 230 blood donors studied, 78 donors had malaria parasite giving a prevalence rate of 33.9% while none had filarial worm giving a prevalence rate of 0%.Table II shows the prevalence of malaria parasite in blood donors attending UMTH in relation to blood group and donation history. Malaria parasite in respect to ABO blood group, group B donors had the highest prevalence rate of 38.1% (16/42) while blood group AB donors had no malaria parasite in their blood. This difference was not statistical significant (x2 = 1.513, df= 3, p-value = 0.679). Malaria parasite with relation to Rh D blood group, Rh D- donors had a higher prevalence rate of 37.5% (6/16) while Rh D+ donors had a lower prevalence of 33.6% (72/214). This difference was also not statistically significant (x2 =0.99, df =1, p-value = 0.753). Family replacement donors had a higher prevalence of malaria infection 34.2% (77/225) when compared to voluntary donors who had a prevalence rate of 20% (1/4), this difference was also not statistically significant (x2 =0.441, df= 1, p=0.506). There was no commercial blood donor in this study. Repeat donors had a higher prevalence rate of malarial infection 36.1% (49/119) while first-time donors had a lower prevalence rate 35.1% (35/111). This prevalence is not statistically significant (x2 =0.543, df= 1, p=0.461).
Table III shows the prevalence of malaria parasite in relation to some social factors.Female donors had higher prevalence rate of malaria parasite (36.4%, 4/11) compared to male donors who had a prevalence rate of 33.8% (74/219). This difference is not statistically significant (x2=0.31, df= 1, p=0.860). Donors below 20 years had the highest prevalence of malarial infection 40% (4/10) while those within the age range of 40-49 had the least prevalence.It is not statistically significant (x2=3.994, df= 4, p=0.479).The prevalence is higher among the singles, 40.7% (50/123) while no infection was detected among the divorced donor. It is not statistically significant (x2=5.66, df= 2, p=0.059).
Table IV shows the prevalence of malaria parasite in relation to usage of insecticides and/ or insecticide treated net. Blood donors who neither used insecticides nor insecticide treated net had the highest prevalence rate of 50% (18/18) while those who used both insecticides and insecticide treated net had the least prevalence rate of 23.5% (4/17). This difference is not statistically significant.
Table V shows the prevalence of malaria parasite in relation to treatment with antimalarial drugs. Donors who 

said to have never been treated with antimalarial drugs had the highest prevalence of 56.7% (17/30) while donors who self-administered antimalarial drug within the last six months had the least prevalence 14.5% (11/76). This difference is statistically significant. No Filarial parasite is found in any of the donors.
DISCUSSION
Results obtained from this study showed that 78 blood donors had malaria while none had filarial worm showing a prevalence of 33.9% and 0% respectively. The prevalence of malaria parasitaemia in this study was lower than that reported by Abioye et al.15 who recorded a prevalence rate of 56% (140/250) in Abuja and was higher than the report of Garba et al.16 who reported a prevalence of 7.5% (27/360) in Kaduna. These differences in regional prevalence could be attributed to variation in predisposing factors such as present of Anopheles species, environmental conditions, climatic conditions, period of study, the study population and diagnostic test method used. The high prevalence rate may be attributed to current security challenges in Borno which forced people from other villages within other towns of the state to relocate to Maiduguri which in turn increases the population and decreases sanitary condition of the city. The decreased sanitary condition has resulted in increased chocked drainage channels which provide a suitable breeding ground for Anopheles mosquito.However, in relation to filarial worms the result from this study was inconsistent with the report of Bolaji et al.3 who reported a prevalence of 2% with Loa loa, Brugria Malayi and Wuchereria Bancrofti in the following proportion; 4(1.33%), 1(0.33%) and 1(0.33%) respectively.This difference may be attributed to difference in the number of subjects and geographical locations. Although Ochocerca Volvulus is prevalent in some areas in Bornu such as Hawul18,it is not prevalent in Maiduguri possibly due to lacks fast flowing water which is a suitable breeding site for its biological vector (Backfly).

This study further revealed that malaria parasitsitaemia is higher among blood group B donors while no malaria parasite was recorded in AB blood donors. This result does not tally with the report of Agboola et al.5 who reported a higher prevalence among blood group O donors. This difference may be as a result of chance. The difference in malaria among ABO blood groups in this study was however not statistically significant, indicating that susceptibility to malaria parasite is independent of a person’s ABO blood group. Also, a higher prevalence of parasitaemia among Rh D negative blood donors was reported in this study compared to the Rh D+ blood donors. This finding was not similar to a report by Bankole et al.19 who reported a higher prevalence among Rh D+ blood donors. The difference between Rh D blood groups in this study was not statistically significant, indicating that susceptibility to malaria parasite is independent of a person’s Rh D blood group. The study clearly suggests that family replacement donors were the major source of blood for transfusion in UMTH. This is consistent with findings from other researchers19, 20, indicating that family replacement donors were the major source of blood for transfusion in most states in Nigeria.There is higher prevalence of malaria parasitaemia in family replacement donors when compared to voluntary blood donors, this result is in line with the report of Olawumi et al.20, however not statistically significant. The lower prevalence recorded in this study indicates that there is reduced risk of transmission ofmalaria when blood productsare derived from voluntary donors. Result from this study shows a higher prevalence of parasitaemia in repeat donors when compared to first-time donors. This result is consistent with the report of Garba et al.16. This could be as a result of the fact that first-time donors are apprehensive and those having mild symptoms of malaria such as headache are usually excluded to donate blood.

The prevalence of malaria parasite in this study shows high rate among female donors when compared to male donors. The difference in prevalence between the genders may not be conclusive owing to the relatively small number of female donors who participated in the study. Higher prevalence of parasitaemia was found in donors whose age where below twenty and the least prevalence was seen in donors within the age range of 40-49 years of age. This result does not tally with the report of Ekwunife et al.(2011)6 who reported the highest prevalence among donors within the range of 25-29 and the least prevalence among donors within the age range of 50-54 years of age. The difference may be due to chance.There is higher prevalence rate in single (unmarried) blood donors while malaria parasite was not detected in the blood of the divorced donor. The result does not tally with the report of Alli et al.,4 who reported a higher prevalence among married donors which might be probably by chance.
Overall, there is no significant relationship between the prevalence of malaria infection and the usage of personal protection against mosquitos. This indicatesthat the current prevalence of malaria parasite among the blood donors is not dependent on the use of insecticide and/or insecticide treated nets. The results also indicated that there is statistically significant relationship between the prevalence of malaria infection and treatment with anti-malaria drugs. This indicates that treatment with antimalarial drugs significantly reduces the prevalence of malaria among blood donors. This coincides with the report of UNICEF 21, which states that the two major ways to reduce the spread of malaria are the use of insecticide treated mosquito nets and early diagnosis and prompt treatment with antimalarial medications.

CONCLUSION
In conclusion the result from this study shows a progressive increase in the prevalence of malaria parasite among blood of donors attending UMTH when compared with previous results. This increase is alarming as these donors are apparently healthy subjects indicating an increased risk of transmission of malaria through transfusion in Maiduguri. No filarial worm was recorded in this study. No statistically significant relationship was established betweenmalaria infection and the usage of Insecticide and/ or insecticide treated net. However, statistically significant relationship between the prevalence of malaria parasite and treatment with antimalarial drugs is noted.

Recommendations Haemoparasites can be transmitted through transfusion of infected blood derived from asymptomatic donors. This may negatively affect patient’s health and increase the duration of their illness. State government should improve the sanitary condition of Maiduguri and environs which will in turn reduce mosquito breeding sites. Screening donors for parasitic infections should be included in the current nation’s transfusion guidelines. Enlighten donors on better ways of preventing infections with haemoparasites.Encourage prompt and effective treatment of infected prospective donors.In additions incentives such as insecticide treated mosquito net, insect repellent and refreshments should be given to donors as this may encourage voluntary donation and as well reduce the prevalence of haemoparasites in the blood of donors.

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