Comparative Performance of Methods for Measuring Malaria Parasite Density in Blood Samples

Abstract

Keywords: Malaria, Parasite, Density, Mosquitoes, Parasitic disease

1. Introduction

Malaria is a life-threatening parasitic disease transmitted by mosquitoes. It remains the most clinically important of the tropical diseases, widespread through the tropics. The disease exacts a heavy toll of illness and death among children especially in endemic areas¹. Malaria caused parasitic disease is seen in more than 300 million people and at least one million deaths annually². Ninety percent of deaths due to malaria occur in Africa South of the Sahara mostly among young children. It kills an African child every 30 seconds². Malaria is the most common cause of outpatient clinic attendance among all age groups in Nigeria and it is responsible for an estimated 300, 000 deaths yearly in children less than five years old (FMOH, 1980-1983).

The detection of malaria parasite in peripheral veins or capillary blood has always been considered an indispensable basis for the definition and diagnosis of malaria^3,4. In the simple determination of parasite density, data collection has usually been limited to a single time point. Little is known about the natural variations in parasite density in the peripheral blood during the course of a day or a week^3,4. In a single individual, parasite density varies spontaneously during the course of several days follow-up. Such variations can lead to an erroneous estimation of the community load of malaria infection^3-6.

High parasite densities may be observed in symptom free individuals, while scores of malaria attacks may occur among those with no detectable parasites and there is no obligate temporal correlation between the occurrence of fever and parasite density³. The calculation of the total number of parasites/microlitre (or mm³) of blood requires the knowledge of the normal range of white blood cells (WBC) in various age groups. Different WBC values have been used in calculation of malaria parasite density based on assumption. The value of 8,000 WBC/mm³ has been generally assumed^2,4,5,7-10. Another assumed average leucocytes concentration value of 7,500 leucocytes/mm³ has equally been used³. While 6,000 leucocytes/ mm³ has equally been employed^5,11,12. These values may not be same in all age groups.

It is not known whether these methods give a good approximation of the parasite density. It has been observed that a common weak point in the estimation of parasite levels by counting parasites against a particular number of WBC is the (incorrect) assumption that all blood samples contain 8,000 WBC/mm³ of blood¹³. Moreover, different age groups have varying WBC counts. Their normal ranges are infants from day one ---3 yrs: 7,500/mm³ + 3,500/mm³ (Dacie and Lewis, 1985); children from 1yr -- 4yrs: 6,000 ­­–18,000/mm³; children between 4 -- 7years: 5,000 – 15,000/mm³; adults: 4,000 - 11,000/mm³¹⁴.

2. Materials and Method

2.1. Study area and subjects

The study was conducted in the University of Nigeria Teaching Hospital, Enugu, Nigeria. Most of the inhabitants of Enugu are of the Igbo tribe and the area has a wet and rainy season. The subjects were clinically selected malaria patients from the Pediatric clinic of the UNTH.

The target populations were children less than 5 years of age, teenagers with the age bracket 5-15years and adults greater than 15 years of age.

Fifty-four (54) blood samples were collected via finger-pricking using sterile blood lancet into sterile EDTA (anticoagulant) containers.

3. Methods of Analysis

3.1. Thick blood film preparation and staining

The thick blood film preparation and staining using Giemsa method (Silverton et al., 1998).

3.2. Procedure

Thick blood films were prepared by making a blood smear with a drop of blood on a clean grease-free slide. The films were allowed to air-dry. The dried thick film was covered with 1in 10 dilution of stock Giemsa stain (filtered) with buffered distilled water pH 7.0. After 30 minutes, the stain was washed off using buffered distilled water. The back of the slide was wiped off and the slide was laced in a slide rack to dry vertically.

3.3. Examination

The leucocytes were counted in batches of 100, 200, 400, and 800, using oil immersion (x 100) objective. The malaria parasites were counted alongside each batch of leucocyte (WBC). A total of four counts for each batch were done, and the average count of malaria parasite for each batch was obtained and used in the calculation of malaria density.

3.4. Counting of total white blood cells

Total white blood cell count using Turks solution⁷.

3.4.1. Procedure: About 0.02ml of anticoagulated blood from finger prick was added to 0.38ml of diluting fluid in a tube and mixed. The solution was allowed to stand for 4 minutes to lyse the red cells and tinge the white cells, a cover glass was placed on to an Improved Neubauer counting chamber. The solution containing the white cells was mixed and used to charge the counting chamber using a Pasteur pipette. The chamber was left undisturbed for 2 minutes, to allow the cells to settle, and the cells were counted using (x10) and (x40) objectives.

A total white blood cells were calculated using the counted value.

             WBC = N X 20 X 10⁶

                            5 X 0.1

Where N = Number of cells counted

            20 = The dilution factor (DF)

            5mm³ = Area counted (A)

            0.1mm = The depth of the counting chamber (D)

Results expressed in /mm³ (Silverton et al, 1998).

Normal Ranges: Infants from day one – 3yrs: 7,500/mm³ + 3,500/mm³ (Dacie and Lewis, 1985).

Children from 1yr – 4years: 6,000 – 18,000/mm³.

Children between 4 – 7years: 5,000 – 15,000/mm³.

Adults 4,000 – 11,000/mm³.

Determination of Parasite Densities

        X No of parasites   x    s/mm³

         (n) WBC                         1       

Where: X = no of malaria parasite counted

             N = no of white blood cell counted per field (100, 200, 400, 0r 800).

             s/mm³ = the total WBC count (using 6,000/mm³, 7,500/mm³ or 8,000/mm³).

4. Results

A total of 54 blood samples of three age groups (<5yrs, 5-15yrs and > 15years) were analysed for the malaria parasite density using different total white blood cell counts. There was a significant correlation (Pearson(r) = 0.6664, P<0.0001); see fig. 41 graph.

(Table 1) shows the mean (+SD) of total white blood cell count of the different age groups. The results show a decrease (F = 9.988, P = 0.0002) in the total white blood cell count from patients < 5 years to > 15 years.

(Table 2) represents the mean values and standard deviation of the malaria parasite density of the different age groups using the actual WBC count. The malaria parasite density was calculated after using 100, 200, 400 and 800 WBC respectively. Analysis of variance showed that there were no significant changes (F = 0.1502, P = 0.929) for age group < 5 years; F = 0.1035, P = 0.9577 for age groups 5 – 15 years and F = 0.1423, P = 0.9344 for age group > 15 years) in the parasite densities in each age group when 100, 200, 400 and 800 WNCs were counted.

(Table 3) shows the different malaria parasite density of different age groups using 6,000/ as the total WBC count. Analysis of variance showed no significant changes (F = 0.1748, P = 0.9130 for age group <5 yrs, F = 0.1429, P = 0.9330 for age groups 5 - 15 yrs and F = 0.2093, P = 0.8898 for age group >15 yrs) in the parasite densities in each age group when 100, 200, 400, and 800 WBCs, were counted.

Table 1: Showing the total white blood cell count of the different age groups.

Table 2: Malaria parasite density of different age groups using their actual total WBC counts.

Table 3: Shows the different malaria parasite density of different age groups using 6,000/ as the total WBC count.  

(Table 4) represents the malaria parasite density of different age groups using 7,500/mm³ as the total WBC count. Its analysis of variance showed no significant changes (F = 0.174, P = 0.9135, for age group <5yrs, F = 0.1429, P = 0.9339 for age group 5 - 15 yrs and F = 0.1963, P = 0.8987 for age group >15yrs) in the parasite densities in each age group when 100, 200, 400 and 800 WBC, were counted.

(Table 5) Show the malaria parasite density of different age groups using 8,000/mm3 as the total WBC count. Analysis of variance showed no significant changes (F = 0.1757, P = 0.9124 for age group <5yrs, F = 0.1429, P = 0.9339 for age group 5 - 15 yrs and F = 0.2090, P = 8899 for age group >15yrs) in the parasite densities in each age group when 100, 200, 400 and 800 WBC, were counted.

(Table 6) indicates the malaria parasite density for patients in the age range <5yrs using 6,000/mm³, 7,500/mm³, 8,000/mm³ and the actual total WBC count respectively in the calculation. The analysis of variance showed a significant difference (F = 47.69, P <0.0001) in the malaria parasite density using different total WBC counts.

Table 4: Malaria parasite density using 7,500/mm³ as WBC count.

Table 5: Showing the malaria parasite density of different age groups using 8,000/mm3 as the total WBC count.

Table 6: Malaria parasite density for age range (<5yrs) using different values as the total WBC counts.

(Table 7) Shows the malaria parasite density for patients in the age range 5 –15yrs using different total WBC counts (6,000/mm³, 7,500/mm³, 8,000/mm³ and actual total WBC count respectively). Its analysis of variance showed a significant difference (F = 30.85, P<0.0001) in the different estimations of parasite density.

(Table 8) Represents the malaria parasite density for patients in the age range >15yrs using different total WBC counts (6,000/mm³, 7,500/mm³, 8,000/mm³ and the actual total WBC count respectively). The analysis of variance showed no significant difference (F = 15.25, P = 0.0002) in the estimation of parasite density.

Table 7: Malaria parasite density for the age range (5 – 15 yrs) using different values as the total WBC counts.

Table 8: Malaria parasite density for the age range (>15yrs) using different value as the total WBC count.

5. Discussion

Malaria is a life-threatening parasitic disease transmitted by mosquitoes and caused by the specie of the genius plasmodium. Four species infect man; P. falciparum, P. vivax, P. ovale and P. malariae¹.

From my findings, there was a significant correlation (Pearson(r) =0.6664, P<0.0001) between malaria parasite count and the total white blood cell count of all the age groups (<5yrs, 5-15yrs and >15yrs). There was a significant decrease (F = 9.988, P = 0.0002) in the total white blood cell count from patients <5yrs to >15yrs (Table 1). There was no significant change when the mean values and standard deviation of the malaria parasite density of the different age groups using the actual WBC counts (after reading 100, 200, 400 and 800 WBC respectively). Also, there was no significant variations was noticed in malaria parasite densities among different age groups using 6,000/mm³, 7,500/mm³ and 8,000/mm³ and the actual WBC count respectively, there was a significant difference (F = 47.69, P<0.001). The analysis of variance of patients in the age range 5-15yrs showed a significant difference (F = 30.85, P<0.0001) when different total WBC counts of 6,000/mm³, 7,500/mm³ and 8,000/mm³ and the actual were used respectively.

Those of age range >15yrs showed no significant difference. The most widely used method of parasite density determination based on the assumed average total WBC count, gave incorrect counts in malaria patients^4,15. Assuming that counting of parasite against the WBC in the blood smear and consequent number of PRBC/WBC was correct, the probable cause of this error is the deviation of WBC counts in patients^5,15. Therefore, this agree with Dubey, et al., 1999 that when the parasite densities were calculated based on the actual WBC counts of each patient, the error will be eliminated and more accurate parasite densities obtained^16-20.

6. Conclusion

It can be concluded from the results of this study that based on the average WBC count of 8,000/mm3 was most unsatisfactory for determining parasite density in most clinical situations. The number of parasites per total WBC and the actual WBC count was found to be the most accurate.

7. Acknowledgements
The authors would like to acknowledge the management of University of Nigeria Teaching Hospital, Enugu, Nigeria for creating the enabling environment for this study. Thanks to all the Laboratory and technical staff of St Kenny Research Consult, Ekpoma, Edo State, Nigeria for their excellent assistance and for providing medical writing support/editorial support in accordance with Good Publication Practice (GPP3) guidelines. 

7.1. Disclosure of conflict of interest
The authors declare no conflicts of interest. The authors alone are responsible for the content and the writing of the paper.

7.2. Statement of ethical approval
Ethical approval was obtained from the ethics and research committee of Asokoro District Hospital, Abuja, Nigeria, and informed consent of the patients was obtained before sample collection.

7.3. Funding
This research did not receive any grant from funding agencies in the public, commercial, or not-for-profit sectors.

7.4. Availability of data and materials

The authors declare consent for all available data present in this study.

7.5. Authors’ Contribution
The entire study procedure was conducted with the involvement of all writers. 

7.6. Statement of informed consent
Informed consent was obtained from all individual participants included in the study. 

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