The calculation of the sample size of patients was based on the following formula:

n ≥ ( g ) ∗ ( Z / d ) 2 ∗ p ∗ ( 1 − p )

In which the different symbols represent respectively:

g: Factor that accounts for cluster effect (g = 2), HDs and health structures.

Z: Coefficient of Confidence (for a 95% confidence level, Z = 1.96)

d: Risk of error (for a margin of error of 5.0%, d = 0.05)

p: The prevalence of malaria confirmed by the TD for the city of Kinshasa, reported in the DHS 2013-2014, is 18.1%.

n = g ∗ Z 2 p ∗ ( 1 − p ) d 2 or n = 2 ∗ ( 1.96 ) 2 ( 0.18 ) ∗ ( 1 − 0.18 ) ( 0.05 ) 2 = 454

To account for possible non-responses, 15% of the minimum sample size calculated (68 suspect cases) was added. This brings this size up to 522 patients. 520 patients were selected.

The data were collected from the cards of patients admitted for fever or fever history 48 hours before the consultation during the period of our study or in any patient whose diagnosis of malaria was made by the clinician, the blood sample was done by a laboratory technician, the slides were colored and read in the laboratory of the Kinshasa School of Public Health by an experienced technician, the reason why no quality control was required.

We used probabilistic two-stage sampling: Health Districts and Health Facilities.

Referring to the stratification of Giovanfrancesco et al. (2016) on the mapping of the risk of malaria in Kinshasa [7] , the HDs of Kinshasa were grouped into 3 strata:

1) Low-risk HDs with a prevalence of malaria less than 5%;

2) Intermediate risk HDs with a prevalence of malaria between 5 and 30%;

3) High risk HDs with malaria prevalence greater than 30%.

Taking into account the weight of each stratum, the following distribution was selected: 2 out of 6 HDs of stratum 1.4 out of 36 HDs of stratum 2.

The Biyela HD being the only one constituting the stratum 3, was automatically selected.

For the first 2 strata, the HD were selected in a simple random manner. The different selected HDs are presented in Table 1.

This table gives us the selected HDs for our study according to the geographical distribution of malaria in the city-province of Kinshasa concerning the prevalence of the disease.

Although carried out at different proportions, it was important during this study to compare the results of these 2 diagnostic biological tests submitted to the suspect patient. Table 3 shows that in all of the 520 patients examined, 26.7% with a confidence interval of [22.9 - 31.0] was diagnosed positive for TD compared with positive RDT results is 18.9% with a confidence interval: CI [5.3 - 23.0].

The results of this study inform us that out of a total of 520 patients, we counted 189 men and 331 women. To show trends by sex, Figure 2 shows that there is not a significant difference between the results of the thick positive blood test found in male patients (28.6%) than found in female patients (25.7%).

The prevalence and severity of malaria are not the same in children and adults, which led us to release the results by age group. The figure above shows that it is in the 0 to 5 age group that the positivity rate (30.2%) is high compared to other age groups (Figure 3).

To compare this study with those carried out on the prevalence of malaria in the city of Kinshasa and the risk mapping of this disease, it is necessary to group the results by stratum.

As a result, Table 4 shows that it is Stratum 3 that a large number of patients were diagnosed with the thick positive drop (30.1%).

Although performed at different proportions, it is imperative in this study to compare the results of these two diagnostic tests submitted to the patients. Figure 4 gives the results of RDT performed in different structures. It is the age group of 6 to 10 years that the positivity rate is the highest (23.9%).

Since the positivity rate of RDT was much lower than that of TD, we calculated from the data in Table 5 the sensitivity, specificity and positive and negative predictive values to evaluate the validity of this test. The results found showed

that the sensitivity of the RDT is 71.0%, the specificity of 77.8%, the positive predictive value of 42.6% and the negative predictive value of 92.0%.

The positivity rate of TD of 26.7% found in this study is lower than those reported in most studies and some reports in sub-Saharan Africa and the DRC, these include SANRU which reported 71% in 2015 [8] , WHO/Burundi in its 2014 annual report mentioned a TD positivity rate of 53.6% [9] , the NMCP/DRC in its 2013 annual activity report (63.2%) [4] , and in Mozambique by Mabunda et al. who found 37.8% [10] .

This result is higher than that found by SA Haidaro et al. In Mali, this found 12.8% among suspected patients hospitalized in internal medicine at Point G Hospital in Bamako [11] .

In children, the positivity rate of 30.2% found in this study is higher than that reported by DRC/DHS 2013-2014, 23% [1] and those reported by A. Munier et al. In Senegal and F, Tietche et al. in Cameroon respectively 54.4% and 43.25% [12] [13] . With regard to the results of TD by stratum, our study confirms the stratification of Ferrari G et al. with regard to the result of strata 2 and 3 which come first in terms of positivity (26.4% and 30%).

The positivity rate of RDT found in our study was 18.9%. This result is lower than that found in most studies conducted in the world and DRC. DRC/DHS 2013-2014, found in children a rate of 31% [1] and yet WHO in its report on malaria in the world for the years 2014 and 2015 had reported rates of 44% and 52% respectively [6] .

In its annual report on activities in 2013, the NMCP reported that 41,037,745 out of 6,096,993 completed RDTs were positive, a positivity rate of 67.3% [12] . Regarding the validity of this test with respect to TD, we noted low values of sensitivity, specificity and positive predictive value (respectively 71%, 77.8% and 42.6%) with a positivity rate of RDT. of 31% in children, this positive predictive value reflects a low extrinsic validity of this test.