Malaria is a febrile and haemolytic erythrocytopathy caused by the presence and development, multiplication in the liver, then in the red blood cells of a haematozoa of the genus Plasmodium transmitted by the infecting bite of an infected female Anopheles mosquito of the Culicidae family [1]. Currently, five specifically human Plasmodium species have been identified: Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale, Plasmodium malariae, and Plasmodium knowlesi. Plasmodium knowlesi, genetically close to Plasmodium vivax, and microscopically close to Plasmodium malariae, was recently discovered in humans in Malaysia (but was previously known in monkeys in Southeast Asia) [2].

Plasmodium falciparum and Plasmodium malariae are ubiquitous species, the first largely dominated by its workforce. Plasmodium vivax, also very widespread in the world, does not exist in Central Africa and West Africa, where it is replaced by Plasmodium ovale, a specifically African and Malagasy species [3].

According to the World Health Organization (WHO), malaria affected approximately 229 million people worldwide in 2019 and caused 409,000 deaths [4]. The situation is more worrying for several years since parasites have been developing resistance to antimalarial molecules and mosquitoes are less and less afraid of insecticides [5]. In France, approximately 5500 cases are reported of importation each year, among which 94% of the cases are from Malaria, in the tropical zones of Africa [6].

Malaria particularly affects underprivileged tropical areas of Africa, Asia and Latin America. The African region is by far the most affected with 94% of malaria cases recorded in this region. Epidemics can occur when populations exposed to malaria move to highly endemic areas [4]; children and pregnant women are the most vulnerable groups [7].

Malaria is responsible for 36.5% of the reasons for consultation in health services [6]. It is the leading cause of death for children under 5 after the neonatal period [8].

6 countries (Nigeria, DRC, Burkina Faso, Mozambique, Côte d’Ivoire, and Mali) account for 60% or 390,000 deaths due to malaria. About 40% of mortality attributable to malaria in the world is concentrated in two countries, including Nigeria and the DRC, and mainly affects children under five years of age [9].

In the DRC, Plasmodium falciparum remains the most predominant Plasmodiale species in the country, and it is responsible for serious forms of malaria; Plasmodium malariae and Plasmodium ovale are found either separately or in co-infection with Plasmodium falciparum. Plasmodium vivax was found as much in Tshimbulu in Kasaï Central at a low prevalence as in a faithful Kimbanguist from Tshiopo who came on pilgrimage to Nkamba in Kongo-Central [10]. The three DPS of Kasaï, namely Kasaï, Kasaï―Central and Kasaï Oriental, have experienced the highest prevalence rates in the country, oscillating between 32% and 38% [11].

In Kasaï Oriental, the species that remains dominant is Plasmodium falciparum, which is why the rapid diagnostic tests that are available (Care stare or SD Bioline) are HRP2-based tests [12].

Indeed, all four species of Plasmodium have a first enzyme called Aldolase, this protein has a short persistence after successful treatment. The second is the Parasite Lactate Dehydrogenase (pLDH) produced by the asexual and sexual stages of the parasite with a distinction between isoenzymes of Plasmodium falciparum, Plasmodium vivax and others with short persistence after successful treatment. The third is specific to the Plasmodium falciparum species (Histidine Rich Protein-2 (HRP-2): it is produced by the trophozoites and gametocytes of Plasmodium falciparum with persistence of ±43 days after successful treatment [12].

This creates difficulty in distinguishing species and determining the positivity rate for malaria rapid diagnostic tests in places where there are only HRP 2 tests such as in Eastern Kasaï, from where, conventional microscopic techniques, thin smear and thick smear remain the reference [2].

In Eastern Kasaï, it is accepted that malaria is due to Plasmodium falciparum, Plasmodium ovale, more rarely found and Plasmodium malariae, the populations of this region are not infected by Plasmodium vivax, because this Plasmodium requires the presence of Duffy subgroup on red blood cells, the Duffy antigen being the Plasmodium vivax receptor [2]. However, in this region, Africans are mostly Duffy negative [13].

Analysis of data made by the Provincial Service of the National Program for the Fight against Malaria in Eastern Kasaï reveals in its report a positivity rate for Rapid Diagnostic Tests higher than 79% in the province and the interpreter of a counter-performance with regard to the indicator in 2021 in the second quarter, among the 19 HZs that make it up, there is a low rate of positivity for RDTs in the Health Areas of the Nzaba, 59.2%, qualified as performing by the PNLP, which motivates the choice of this NZABA health entity in this study.

Knowing that the Rapid Diagnostic Test kits available on the market are specific to a single species of Plasmodium falciparum parasite and in cases where a malaria infection can be caused by other Plasmodium species and does not react to test positive of Rapid Diagnosis at HRP 2, a question arises on this particularity between the Health Zones of the same province as follows: are there no other species of plasmodia which would reveal negative the test at HRP 2 while the patient suffers from malaria? What is the true frequency of malaria in this health zone?

To carry out this work, we used the following materials:

To carry out our work and achieve the objectives assigned above, we used the prospective method supported by the techniques of analysis of Medical Biology (malaria microscopy which consists in taking blood samples to make thick drops and thin smears), then observation under the microscope and the data were collected using Kobo-collect V2021.2.4 software, analyzed using SPSS.20 software.

This study is carried out in the 18 Health Areas of the NZABA. It is limited to determining the frequency and identifying plasmodial species for the patient samples that we have taken. It covered a period from May to July for theory and from August to September 2021 for laboratory analyses.

The laboratory of the General Reference Hospital of DIPUMBA served as a framework for the realization of our work; we chose this laboratory because of the good working conditions it offers us in terms of size, workspace and materials available for our research.

We carried out our study among individuals in the Health Areas of the Nzabawho attended curative services during our study; they amount to 201 people thanks to the non-probability sampling technique by convenience.

Indeed, the Health Areas of the Nzaba is located in the Provincial Division of Kasaï Oriental in the Democratic Republic of the Congo (DRC). Administratively, Nzaba is in the commune of Bipemba. It is bordered to the east by the Bonzola zone, to the west by the Mukumbi health zone, to the north by the Health Areas of the Mpokolo, to the south by the Tshishimbi health zone and to the northeast by Bipemba health zone.

It has a relief that is made up of plains and valleys with a sandy-clayey soil; the vegetation is dominated by grassy savannah as well as small gallery forests. It has a humid tropical type climate with alternating two seasons: a long rainy season from mid-August to mid-May (9 months) period during which there is intense multiplication of Anopheles mosquitoes. It is connected by road 14 kilometers from the city center of Mbujimayi, the capital of the province [14].

This analytical study is of a transversal and descriptive type on the frequency and identification of plasmodial species in the NZABA health zone.

To succeed in collecting the data of this treaty, we went through the following steps:

・ Implementation of data collection software;

・ Obtaining the visa of the MCZ of NZABA;

・ Briefing of nurses in charge of health areas in this area;

・ Blood sampling from patients who have attended the care services;

・ Confections of thick drops coupled with thin smears and their colorations;

・ Readings of the slides under the microscope with the 100× objective;

・ Actual data collection by encoding in the Kobo collection software.

Kobo Collection Box central server was encoded in software deployed via an Android brand phone and the statistical calculations were performed using SPSS software, the data is presented in tables and expressed as a percentage.

We have retained the following parameters or variables for our work:

This study obtained the authorization of the ethics committee of the Higher Institute of Medical Techniques of Mbujimayi and the approval of the Provincial Health Division of Kasaï Oriental. The oral consent of the patients was obtained after having clearly provided explanations of the objectives and the interest of the study. The patient’s medical confidentiality was not disclosed. In addition, patient anonymity was guaranteed by the use of codes.

A thick drop is read using an optical microscope with a 100 objective (immersion objective). It consists in putting the blade on the plate and putting a drop of oil on the spot. First place the 10× objective, then the 100× objective and bring it into contact with the oil; Lamp dimmer fully open, Capacitor lifted; fully open iris diaphragm. Make sure that the chosen area has the required quality and examine the slide on at least 100 microscopic fields using the Rampart method. (Figure 1)

The “plus” system is already outdated; there is currently an emphasis on the use of parasite density if the thick film is positive for Malaria [10].

It consists of counting the parasites per µl of blood on a thick drop, compared to a predetermined number of white blood cells. In each field, the parasites are counted at the same time as the leukocytes. The number of leukocytes counted varies between 200 and 500 according to the following diagram: If after having counted 200 leukocytes, the number of parasites counted is greater than or equal to 100, in this case the reading stops and the density is calculated according to the formula downstairs [16]. However, if on the other hand, at 200 leukocytes, the number of parasites counted is less than 100, it is then necessary to continue up to 500 leukocytes, and calculate the density according to the formula below [16].

Parasite   density = Numberoftrophozoitescounted Numberofwhitebloodcellscounted × 8000

NB: 8000 is the average leukocyte count per µl in humans.