(2021) 10:77
Munyeku et al. Infect Dis Poverty
https://doi.org/10.1186/s40249-021-00860-1

RESEARCH ARTICLE

Open Access

Prevalence of Plasmodium falciparum
isolates lacking the histidine rich protein 2 geneamong symptomatic malaria patients in Kwilu
Province of the Democratic Republic of Congo
Yannick Bazitama Munyeku1,2,3,4*, Alain Abera Musaka5,9, Medard Ernest4,7, Chris Smith3,8,Paul Mankadi Mansiangi6 and Richard Culleton3,4,10,11*

Abstract
Background: Malaria rapid diagnostic tests have become a primary and critical tool for malaria diagnosis in malariaendemic countries where Plasmodium falciparum Histidine Rich Protein 2-based rapid diagnostic tests (PfHRP2-basedRDTs) are widely used. However, in the last decade, the accuracy of PfHRP2-based RDTs has been challenged by the
emergence of P. falciparum strains harbouring deletions of the P. falciparum histidine rich protein 2 (pfhrp2) gene, resulting in false-negative results. In the Democratic Republic of Congo (D.R. Congo), little is known about the prevalenceof the pfhrp2 gene deletion among P. falciparum isolates infecting symptomatic patients, especially in low to moderate transmission areas where pfhrp2 deletion parasites are assumed to emerge and spread. Here we determine thelocal prevalence and factors associated with pfhrp2 gene deletions among symptomatic malaria patients in the Kwilu
Province of the D.R. Congo.
Methods: We used secondary data from a prospective health facility-based cross-sectional study conducted in 2018.
Blood was collected for microscopy, PfHRP2-RDT, and spotted onto Whatman filter paper for downstream genetic
analysis. Genomic DNA was extracted and used to perform PCR assays for the detection and confirmation of pfhrp2
gene deletions. Fischer’s exact and the Kruskal–Wallis tests were applied to look for associations between potential
explanatory variables and the pfhrp2 gene deletion with a level of statistical significance set at P < 0.05.
Results: Of the 684 enrolled symptomatic patients, 391 (57.7%) were female. The majority (87.7%) reported thepresence of mosquito breeding sites within the household’s compound, and fever was the most reported symptom(81.6%). The overall prevalence of the pfhrp2 gene deletion was 9.2% (95% CI: 6.7%–12.1%). The deletion of the pfhrp2
gene was associated with health zone of origin (P = 0.012) and age (P = 0.019). Among false-negative PfHRP2-RDT
results, only 9.9% were due to pfhrp2 gene deletion.
Conclusions: P. falciparum isolates with pfhrp2 gene deletions are relatively common among symptomatic patientsin Kwilu province. Further investigations are needed to provide enough evidence for policy change. Meanwhile, the*Correspondence: ymunyeku@gmail.com; culleton.richard.oe@ehime-u.ac.jp
1
Direction Des Laboratoires de Santé, Ministère de La Santé, Kinshasa,
Democratic Republic of the Congo
3
Graduate School of Tropical Medicine and Global Health (TMGH),
Nagasaki University, Nagasaki, Japan
Full list of author information is available at the end of the article© The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
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Munyeku et al. Infect Dis Poverty(2021) 10:77

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use of RDTs targeting PfHRP2 and parasite lactate dehydrogenase (pLDH) antigens could limit the spread of deleted
isolates.
Keywords: Plasmodium falciparum histidine rich protein 2, Gene deletion, False negative, Rapid diagnostic test,
Symptomatic patient

BackgroundMalaria remains a global health issue despite progressover the last decade. In 2018, there were an estimated 228
million new malaria cases, including 405 000 deaths [1].
Ninety-two percent of malaria cases and 93% of malaria
deaths occurred in Africa. Fifteen countries in sub-Saharan Africa and India carried nearly 80% of the global
malaria burden of which Nigeria and the Democratic
Republic of the Congo (D.R. Congo) accounted for about
35% [1].
D.R. Congo accounts for 12% of all malaria cases in
sub-Saharan Africa [1]. In D.R. Congo, malaria is theleading cause of morbidity and mortality, accounting
for more than 40% of all outpatient visits, and for 19%
of deaths among under five years children [2]. The highburden of malaria in D.R. Congo can be explained by
the fact that nearly the entire population (97%) lives inhigh-transmission zones where the most common vector
encountered is Anopheles gambiae, and Plasmodium falciparum is the most common species responsible for the
majority of severe cases [2, 3].
An important component of malaria control and elimination is appropriate case management, which is basedon early and accurate diagnosis. Accurate diagnosis facilitates appropriate and prompt treatment and minimizes
the risk of developing drug resistance [1].
The WHO recommends microscopic examination as
the gold standard for malaria diagnosis. However, in ruraland semi-urban settings where lack of equipment, reagents, trained and skilled personnel, and electricity can
prevent this diagnosis method, the use of rapid diagnostic tests (RDTs) offers an alternative for quick and accurate diagnosis [4, 5].
RDTs have become a primary and critical tool for
malaria diagnosis in the D.R. Congo as well as in Malaria
endemic countries. They accounted for nearly 75% of
diagnostic testing among suspected cases in Africa in2017 [1]. Current RDT kits are designed to detect either
P. falciparum alone or in combination with other species of human malaria parasites. Three main antigens aredetected by malaria RDTs, namely P. falciparum histidine
rich protein 2 (PfHRP2), parasite lactate dehydrogenase(pLDH), and parasite aldolase (pAldo) [6, 7].
PfHRP2, a P. falciparum specific antigen, has the advantage of being highly abundant and heat-stable. PfHRP2based RDTs can lead to false-positive results in the caseof persistent circulating HRP2 antigen as a result of antimalarial treatment, and false-negative results in individuals whose levels of parasitaemia is under the detection
threshold of 200 parasites/µl [6, 7].
In the last decade, however, some studies have reported
false-negative results among individuals infected with
P. falciparum parasites presenting a deletion of the P.
falciparum histidine-rich protein 2 (pfhrp2) gene. The
majority of these studies have also identified co-existing
deletions of the P. falciparum histidine-rich protein 3(pfhrp3) gene, which produces an antigen that showssome cross-reactivity with HRP2 [4, 5, 8–30].
While the WHO recommends not initiating antimalarial treatment without biological evidence, selectionof P. falciparum isolates with pfhrp2 gene deletions may
occur when only RDT positive patients are treated. The
non-treated patients infected by parasites harbouring
pfhrp2 gene deletions will facilitate the spread of phrp2
deleted strains, jeopardizing progress towards disease
control and elimination in low setting countries.
To date, only one study has investigated pfhrp2-deleted
mutant parasites in D.R. Congo, reporting a countrywide prevalence of 6.4% among children under-fiveyears and providing spatial distribution and population
genetics of these deletions [14]. However, this nationwide study could not explore clinical differences between
pfhrp2-deleted and wild type P. falciparum malaria due
to limited clinical data and study population (the majority being asymptomatic and under-five), nor was it able
to conclude about the relative virulence of pfhrp2-deletedparasites.
In order to address the above limitations, we selected
Kwilu Province which is classified by the D.R. Congo
National Malaria Control Program (NMCP) as a province at high risk of malaria [3]. Kwilu Province is classified in the tropical facies where malaria transmission
occurs predominantly during the long rainy season lasting 5 to 8 months, and where the number of infected
bites per people per year ranges from 60 to 400 [3]. Using
data from a prospective health facility-based cross-sectional study, we aimed to determine the local prevalenceof the pfhrp2 gene deletion among malaria symptomaticpatients, and associated clinical, biological, and sociodemographic factors in the Kwilu Province (D.R. Congo).
The aim of this study is to contribute to a better characterization of the prevalence and consequences of pfhrp2

Munyeku et al. Infect Dis Poverty(2021) 10:77

deletions in D.R. Congo by providing relevant regional
data to improve malaria management and control.

Methods
Study design and setting

We used secondary data from a prospective health facility-based cross-sectional study conducted on individualsof all ages, seeking healthcare from October to December 2018 in 34 randomly selected health facilities of threehealth zones in the Kwilu Province (D.R. Congo), Fig. 1.
The Kwilu Province is one of 26 provinces of D.R.
Congo with an area of 79 906 ­km2. It is divided into fiveadministrative territories: Bagata (including the cityof Bandundu), Bulungu (including the city of Kikwit),
Gungu, Idiofa, and Masimanimba [31].
The two selected cities (Bandundu and Kikwit) include
three of the 24 health zones of the Kwilu Province [31].
They are the two main cities in the province and bear thehighest burden of malaria. pfhrp2 gene deletions werepreviously reported in this region [14, 32].
Bandundu, the capital city of the Kwilu Province, islocated 400 km from Kinshasa, the capital of D.R. Congo[33]. Bandundu covers an area of 222 k­ m2 with a population estimated at 950 683 as of 2015 [33]. It has a tropical wet and dry climate with two seasons. Heavy rainfalls
and constant heat characterize the rainy season while

Fig. 1 Collection sites

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fewer rainfalls are recorded during the dry season. The
average annual temperature is 26.9 °C [33]. Bandundu
City has one semi-urban health zone of the same nameand 17 health areas, including 11 urban and six rural.
Kikwit is the second-largest city in Kwilu Province,
located in the south-west of D.R. Congo, at 525 km from
Kinshasa and 400 km from Bandundu. It is the main economic city of the province and a commercial hub thatprovides access to diamond-rich regions of Kasaï Province and Angola. Kikwit covers an area of 92 k­ m2 withan estimated population of 1 326 068 as of 2016 [34].
The city has a tropical wet and dry climate with a long
rainy season from early September through to the end of
May and a short dry season from early June to the end of
August. Kikwit City has two urban health zones: KikwitNord and Kikwit-Sud.
Ethics, consent, and permissions

The study was approved by the Kwilu Province Division of Health (N° ADM/707/01/DPS-KLU/CD/
JPBK/632/2018), the Kinshasa School of Public Health
Ethical Committee (ESP/CE/015/2019) and the Schoolof Tropical Medicine and Global Health Ethical Review
Committee.
The study was first explained to all participants, thenwritten and verbal voluntary informed consent wasMunyeku et al. Infect Dis Poverty(2021) 10:77

obtained from all study participants including guardian/parents of non-adult participants.
Study population

The study population included individuals of all ages
seeking health care in health facilities located in the three
Health Zones of Bandundu (one) and Kikwit (two) cities. Health facilities included General Reference Hospitals, Reference Health Centres, and Health Centres. The
smallest selection units were individuals attending these
health facilities with symptoms suggestive of malaria. The
study included all individuals seeking care in the selected
health facilities with symptoms suggestive of malaria
such as fever, headaches, malaise; during the study period
for whom a laboratory test (PfHRP2-RDT and/or microscopic examination) was performed. Individuals who
failed to meet the inclusion criteria or did not consent toparticipate in the study were excluded.
Sample size calculation

The minimum number of subjects required to enrol inthis study was calculated based on a previously reported
proportion of pfhrp2 gene deletion in the Kwilu Province(3%) and recommendations from WHO for studies on
pfhrp2/3 deletion among symptomatic patients [14, 35].
According to the WHO protocol for estimating pfhrp2/3
deletion prevalence, for an expected prevalence of 3.2%,
at least 370 individuals with P. falciparum infection are
required per sampling domain [35]. In this study, thesampling domain was the Kwilu province, which included
34 health facilities. The study enrolled a total of 684
patients meeting the inclusion criteria of which 491 werepositive for P. falciparum using PCR.
Recruitment method

The primary study applied a two-stage random sampling
to select health centres. At stage one, 27 health centres
were randomly selected among the 62 health centresin the targeted areas. For neighbouring health centres,
one health centre was randomly selected out of two. Inorder to increase the chance of catching individuals notrespecting the referral system by directly seeking carein high-level health facilities, four reference health centres and three general reference hospitals from the threehealth zones were included, bringing the total number of
selected health facilities to 34 (27 in Kikwit and seven in
Bandundu).
At stage two, individuals attending the selected healthfacilities with symptoms indicative of malaria wererecruited. The lead investigator weighed the number ofindividuals to recruit per health centre to the average rateof service utilization provided by the National Health
Information System.

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Variables

This study used four groups of variables: sociodemographic, malaria prevention, clinical and biologicalvariables. Plasmodium falciparum HRP2 gene deletion(pfhrp2) was the main outcome variable. Explanatory
variables were age, sex, health zones, household size,
existence of mosquito breeding sites, LLIN (Long Lasting
Insecticidal Net) ownership, use of LLIN, malaria drug
intake, malaria clinical features, parasite density, andmicroscopy result.
Data collection method

Potential participants were introduced to the study by aresearch assistant. After securing consent/assent fromthe subjects or their guardians, socio-demographic,
malaria prevention and treatment practices, and clinical variables were collected using a pre-tested structured
questionnaire. Patients’ medical records were used tocollect data from the physician’s or health officer’s clinicalexamination.
Heel or finger-prick blood was collected from eachindividual. Samples for microscopy were prepared using
two drops of blood. Then 50 µl of blood were applied on
PfHRP2-RDT, and a few drops were spotted onto Whatman filter paper to prepare dried blood spots (DBS).
The membranes of spent PfHRP2-RDT cassettes andthe DBSs were individually stored in plastic bags, sealedwith a desiccant at room temperature before being
shipped to the Institute of Tropical Medicine in Nagasaki(NEKKEN) where they were refrigerated at 4 °C.
The CareStart™ Malaria Pf (HRP2) Ag RDT (Access Bio,Inc., Somerset, New Jersey, USA) was used for the qualitative detection of malaria histidine-rich protein 2 in thewhole blood according to the manufacturer’s instructions[ACCESSBIO, 2018, Somerset, New Jersey, USA]).
The test membrane strip is pre-coated with a P. falciparum HRP2 specific monoclonal antibody as a single line
across the test strip. The reported panel detection score is
91.0% at 200 parasites/µl with a false positive rate of 0.9%
[36, 37]
Malaria RDT screening

Microscopic diagnosis of malaria

A team of four medical technologists read the slides in
the laboratories of health facilities where samples werecollected. When a health facility did not have the necessary equipment to perform the examination, slides wereread at the nearest laboratory possessing adequate equipment. For quality assurance, one expert microscopist
randomly selected positive and negative slides to crosscheck results. In the case results were not concordant,
another reading was performed. About five percent ofMunyeku et al. Infect Dis Poverty(2021) 10:77

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slides went through another quality control in the vector control laboratory of the Kinshasa School of Public
Health.
Thick and thin smears were made on the same slide.
The part of the slide containing the thin smear was
fixed with methanol and dried. Then the whole slide
was stained with 10% Giemsa’s solution for ten minutes
and finally washed off with distilled water and air-dried.
Stained smears were examined under a microscopefor malaria parasite identification. For positive slides,
malaria parasites were counted against 200 white blood
cells (WBC), and parasite density was calculated basedon a total of 8000 WBC/µl using the following formula: (Number of Parasites counted × 8000)/Number ofcounted WBC.
Parasite density calculation was immediately performed when 100 parasites were counted against 200
WBC. However, in the case that fewer than 100 parasites
were counted against 200 WBC, the count continued
until 500 WBC.
Extraction of parasite DNA

Genomic DNA was extracted from membranes of spent
PfHRP2-RDT cassettes and DBS using the QIAGEN
QIAmp®DNA extraction kit (company, city, country)
according to the manufacturer’s instructions. We also
adapted a previously described method to recover DNA

from 197 spent RDTs membranes from Bandundu Health
Zone [38].
Detection of P. falciparum infection & pfhrp2 gene deletion

To confirm P. falciparum infection, we designed specificprimers targeting a 226 base pair region of the P. falciparum lactate dehydrogenase (pfldh) gene and performed areal-time PCR assay (Table 1). This assay was also used
to ensure there was sufficient parasite DNA quantity inthe samples to discriminate P. falciparum negative samples from samples with pfhrp2 gene deletion, as shown in
Fig. 2.
Samples were duplicated and loaded in 96-wells plates
along with serially diluted positive controls (gDNA fromin vitro cultured P. falciparum strain 3D7) (1 ng/µl,
0.1 ng/µl, 0.01 ng/µl, 0.001 ng/µl), as well as negative controls containing DNA from blood spots prepared fromknown malaria negative individuals. We repeated theassay for all discordant duplicates and counted three consistent results as the final result.
For detection of the pfhrp2 gene, we performed anested PCR assay using primers targeting a 228 base pairfragment spanning exon 1, the intron, and a portion ofexon 2 of pfhrp2 as previously described (Table 1) [9]. We
used a lower elongation temperature (68 °C) to improve
PCR sensitivity, pfhrp2 being AT-rich, and increased thenumber of cycles to 40. We used genomic DNA from

Table 1 Primer sequences and PCR conditions for pfhrp2 and pfldh genes amplification
Targeted gene

Primer sequence (5′ → 3′)

Reaction component Cycling condition

pfhrp2 Exon 1–2,
Outer
PF3D7_0831800 For: GGT​T TC​C TT​C TC​AAA​AAA​TAAAG​
Rev: TCT​ACA​TGT​GCT​TGA​GTT​TCG​

pfldh (qPCR)

One Taq 2 × MasterMix with standard
buffer: 12.5 µl
10 µmol/L forward
primer: 1 µl
Inner
10 µmol/L reverse
For: GTA​T TA​TCC​GCT​GCC​GTT​T TT​GCC​
primer: 1 µl
Rev: CTA​CAC​AAG​T TA​T TA​T TA​AAT​GCG​GAA​
Nuclease free water:
7.5 µlDNA template: 3 µl
(gDNA or 5 × diluted
outer PCR product25 µl reaction volume

95 °C/5 min;40 cycles of 95 °C/30 s, 55 °C/30 s, 68 °C/30 s
68 °C/5 min
4 °C–∞

For: ACG​ATT​TGG​C TG​GAG​CAG​
Rev: GGA​ACA​CCT​GAA​TGT​TGA​TG

50 °C/2 min;
95 °C/2 min
45 cycles of 95 °C/15 s, 62 °C/1 min, 95 °C/30 s,
60 °C/15 s

LOD Lower limit of detection, qPCR Quantitative or real-time PCRPowerUp™ SYBR ™
Green Master Mix(2 ×): 12.5 µl
10 µmol/L forward
primer: 0.5 µl
10 µmol/L reverse
primer: 0.5 µl
Nuclease free water:
6.5 µlDNA template: 2–4 µl
22–24 µl reaction
volumeLOD(ng/µl)10–5

95 °C/5 min;40 cycles of 95 °C/30 s, 62 °C/30 s, 68 °C/30 s
68 °C/5 min
4 °C–∞

10–4

Munyeku et al. Infect Dis Poverty(2021) 10:77

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Fig. 2 pfhrp2 gene deletion testing pipeline

Dd2 (pfhrp2 negative) and 3D7 (pfhrp2 positive) as controls for all assays.
We repeated the nested PCR for all negative results. In
the case of discordant results, we performed the amplification a third time and counted two consistent results as
the final result.
Reaction components for both real-time and nested
PCR are summarized in Table 1.
PCR product resolution by agarose gel electrophoresis

PCR amplicons were separated by electrophoresis on a
2% agarose gel stained with Gel Red® Nucleic Acid Stain
10 000 × in water. A total of 12 µl of PCR amplicons(6 µl) and loading dye (6 µl) were loaded onto the gel,which was run for 35 min at 100 V and observed under
UV light. A 500 µg/ml Gene Ruler 100 bp DNA Ladder(BioLabs®inc, Ipswich, USA) was loaded onto the samegel to determine the sizes of the resolved fragments.
Statistical analyses

Data were entered and analyzed using STATA15 (StataCorp LLC, Lakeway, Texas, USA). Tables have been used
to describe categorical variables. Continuous variables
have been summarized using median and interquartile
ranges. Proportions have been used to summarize categorical variables.
Fischer’s exact test (for categorical variables) and the
Kruskal–Wallis test (for non-normally distributed continuous variables) were applied to look for associations

between potential explanatory variables and the main
outcome (pfhrp2 gene deletion). We computed the 95%
Confidence Interval (95% CI) for the prevalence of pfhrp2
gene deletion. We considered a P-value less than 0.05 statistically significant.

Results
Socio‑demographic characteristics

Of the 684 symptomatic patients who participated in the
study; 391 (57.7%) were female, and 287 (42.3%) weremale. Kikwit-Nord Health Zone accounted for the majority of patients 362 (52.9%) while Bandundu and KikwitSud Health Zones accounted for 197 (28.8%) and 125(18.3%) patients, respectively.
The median age was nine years, with an interquartile
range from 3 to 26 years old. Children under five years
old represented 36% of enrolled patients. The mediansize of household was six, with an interquartile range
from five to six. Table 2 summarizes socio-demographic
characteristics.
Household environment, malaria prevention,and treatment practices

The majority (87.7%) of patients/patients’ guardian
reported the presence of mosquito breeding sites within
the compound where the household was located. Twothirds of household (64.2%) owned a mosquito bednet, while 49.7% of patients spent the night before theinterview under a mosquito bed net. One-third (220)Munyeku et al. Infect Dis Poverty(2021) 10:77

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Table 2 Socio-demographic
characteristics,
householdenvironment and malaria prevention and treatment practices
Characteristic
Sex (n = 678)n%Median IQRTable 3 Clinical and biological features of symptomatic patients
Characteristic
Clinical features (n = 684)

n%

History of fever

558

81.6

Female391 57.7

Headache

286

41.8

Male

287 42.3

Vomiting

215

31.4

Rigor

156

22.8

Health Zone (n = 684)
Bandundu

197 28.8

Fatigue151

22.1

Kikwit-Nord362 52.9

Abdominal pain

138

20.2

Kikwit-Sud

125 18.3

Joint Pain

58

8.5

Anorexia

42

6.1

Age in years (n = 680)

9

3–26

<5

245 36.0

Neckache

34

5.0

>5

435 64.0

Diarrhoea

32

4.7

Pallor13

1.9

Convulsions

12

1.8

Household Size (n = 684)

Household environment (n = 684)

6

5–8

Mosquito breeding sites

600 87.7

Splenomegaly

5

0.7

LLIN ownership

439 64.2

Impaired consciousness

3

0.4

LLIN utilisation

340 49.7

Temperature at admission (°C)

Malaria prevention and treatment practices
Prior drug intake (n = 684)

220 32.2

Quinine89

13.0

Sulfadoxine–pyrimethamine

42

6.1

Malaria drug taken (n = 220)

Biological features (n = 235)

Parasite density (parasites /µl)

Median

IQR

37.5

37–38

880

64–7200

P arasite density accounts for only microscopy positive samples

Artemether–lumefantrine

33

4.8

Artesunate

14

2.0

Arteether13

1.9

Artemether

12

1.8

Arteether-artemotil

10

1.5

IQR Inter quartile rRange, LLIN Long lasting insecticidal net

ranged from 64 parasites /µl to 7200 parasites /µl witha median parasite density of 880 parasites/µl. Table 3
summarizes the distribution of clinical and biologicalfeatures.

Amodiaquine4

0.6

Artesunate-sulfadoxine-pyrimethamine

20.3

Comparison of RDT, PCR and microscopy

Plant extract

1

0.1

Among patients with a negative PfHRP2-RDT result,
63.9% were ‘false negatives’ compared to PCR. The sensitivity and specificity of RDTs with reference to PCR were
71.3% (325/456) and 42.4% (74/173), respectively. Using
microscopy as the gold standard, the proportion of falsenegative RDT result dropped to 26.3%. The microscopydetermined sensitivity and specificity of RDTs were 74.3%(156/210) and 36.0% (151/419), respectively (Table 4).

For the variable sex, less than 1% information is missing (six entries). For thevariable age, less than 1% information is missing (four entries)
Malaria drug taken includes only individuals who reported malaria drug intake
at least one week before the survey
IQR Inter quartile range, LLIN Long lasting insecticidal netof patients reported prior malaria drug intake. Quinine(13%), sulfadoxine-pyrimethamine (6.1%), artemetherlumefantrine (4.8%), artesunate (2.0%), arteether (1.9%),
artemether (1.8%) were the common drugs taken as illustrated in Table 2.
Clinical and biological features of symptomatic patients

At admission, the body temperature of patients ranged
from 37 °C to 38 °C (median temperature of 37.5 °C). The
common findings of the clinical examination were: A
history of fever the last 72 h (81.6%), headaches (41.8%),
vomiting (31.4%), rigor (22.8%), fatigue (22.1%) andabdominal pain (20.2%). Among the 235 patients witha microscopy positive result, malaria parasite density

Proportion of pfhrp2 gene deletion in false‑negative
PfHRP2‑RDT

Using PCR as the gold standard, there were 131 falsenegative PfHRP2-RDT results of which only 9.9% were
due to pfhrp2 gene deletion, with a 95% CI ranging from
5.4% to 16.4%. The mean parasitaemia of the 131 RDT
false-negative infections was 2447 parasites per µl. The
theoretical limit of detection of PfHRP2-RDT is 200
parasites per ul of blood. Of 155 samples with parasite
densities of over 200 parasites per ul as determined by
microscopy, 30 were negative by RDT (19%). Of these,
only one harboured a deletion at the PfHRP2 locus.

Munyeku et al. Infect Dis Poverty(2021) 10:77

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Table 4 Comparison of HRP2-RDT, PCR, and microscopy
HRP2-RDT (n = 629)

PCR

Microscopy

Negative

Positive

Negative

Positive

n

%

n

%

n

%

n

%

Negative

74

36.1

131

63.9

151

73.7

54

26.3

Positive

99

23.3

325

76.7

268

63.2

156

36.8

HRP2-RDT Histidin Rich Protein 2 based rapid diagnostic test, PCR Polymerase chain reaction

Prevalence of pfhrp2 gene deletion among all
symptomatic PfPCR confirmed cases

The overall prevalence of pfhrp2 gene deletion among
PfPCR confirmed symptomatic cases was 9.2%. The
highest prevalence was found in Bandundu Health Zone
(15.7%), followed by Kikwit-Sud Heath Zone (9.6%) andKikwit-Nord Health (6.2%). Table 5 shows the distribution of pfhrp2 gene deletion among PCR confirmed cases
across Heath Zones.
Socio‑demographic, malaria prevention, biologicalfeatures, and pfhrp2 gene deletion

As shown in Table 6, there was no statistically significant
difference in pfhrp2 gene deletion status between males
and females (8.5% vs 9.8%). Conversely, there was a statistically significant difference in pfhrp2 gene deletions
status in Bandundu health zone compared to KikwitNord and Kikwit-Sud health zones (P = 0.012). There
was a trend towards pfhrp2 gene deletion in older compared to younger patients, but this was not statisticallysignificant (P = 0.079). However, when analyzing age as acontinuous variable, the median age among pfhrp2 genedeleted patients was higher than the median age among
pfhrp2 gene non-deleted patients (18 years vs 7 years).
The Kruskal Wallis test showed strong evidence suggesting that the distributions of age differed by pfhrp2 genedeletion status (P = 0.019). Similarly, there was a trend
towards pfhrp2 gene deletion among negative microscopy results, but weak evidence supported this finding(P = 0.079).

Clinical features and pfhrp2 gene deletion

We found more malaria signs and symptoms among
patients infected with parasites not harbouring pfhrp2
gene deletion. However, the difference was not statistically significant (Table 6).

Discussion
More females participated in this study than males (57%
vs 42.3%). This finding is in keeping with results fromthe D.R. Congo 2013–2014 Demographic and Health
Survey(DHS) which reported a sex ratio slightly in favourof females [39].
Surprisingly, children under-five represented 36%
of participants. This is in contrast with what might be
expected since under-five children are known to be at
higher risk of contracting malaria. Despite the burdenof malaria in Kwilu Province, there is a seasonal trend
in transmission, and immunity is acquired later in life,around 10 years [3]. Late acquisition of immunity can
explain the higher proportion of participants aged morethan five years, seeking treatment for symptoms suggestive of malaria and thus enrolled in this study. The
median household size of six is similar to findings fromthe 2013–2014 DHS which reported of median size of 5.7[39].
There were mosquito breeding sites near households ofthe majority of participants (87.7%). The survey was conducted during the rainy season, which is characterized
by the formation of breeding sites, especially in rural andsemi-urban areas with limited public facilities.

Table 5 Frequency of pfhrp2 gene deletion among all symptomatic PfPCR confirmed cases
Health Zones

Subjects

Plasmodium falciparum infection

pfhrp2 gene deletionnnPrevalence (95% CI)

Prevalence (95% CI)

Overall

684

491

71.8 (68.2–75.1)

45

9.2 (6.7–12.1)

Bandundu

197

121

61.4 (54.2–68.2)

19

15.7 (9.7–23.4)

Kikwit-Nord

362

276

76.2 (71.5–80.5)17

6.2 (3.6–9.7)

Kikwit-Sud

125

94

75.2 (66.7–82.5)9

9.6 (4.5–17.4)

PCR Polymerase chain reaction, CI Confidential intervalMunyeku et al. Infect Dis Poverty(2021) 10:77

Page 9 of 13

Table 6 Socio-demographic, malaria prevention, biological features and pfhrp2 gene deletion
Characteristic

pfhrp2 gene deletedn

Sex (n = 487)%

Medianpfhrp2 gene non-deleted
IQR

n

%

Female

27

9.8

248

90.2

Male

18

8.5

194

91.5

Health Zone (n = 491)
Bandundu

19

15.7

102

84.3

Kikwit-Nord

17

6.2

259

93.8

Kikwit-Sud

9

9.6

85

90.4

179

93.7

264

88.9

Age in years (n = 488)

18

<5

12

6.3

>5

33

11.1

Household size (n = 491)

Mosquito breeding sites (n = 491)

7

4.9–30

6–8

8

14.0

49

86.0

37

8.5

397

91.5

No

16

9.0

161

91.0

Yes

29

9.2

285

90.8

LLIN utilization (n = 491)
No

0.012

24

9.5

228

90.5

21

8.8

218

91.2

2.9–190.019*
0.079

6Absent

IQR

0.640

7

Present
LLIN ownership (n = 491)

MedianP-value

5–8

0.388*
0.217> 0.999
0.876

Yes
Prior drug intake (n = 491)
No

29

9.0

295

91.0

Yes

16

9.6

151

90.4

Negative

33

11.1

265

88.9

Positive

12

6.2

181

93.8

Microscopy (n = 491)

Parasite density (n = 491)

Clinical features (n = 491)

Temperature at admission (°C)
History of fever

34

4680

264–14 800

37.5

36.4–38.6

8.4

371

91.6

0.869

0.079
1200

112–8080

37.8

37–38

0.3771*0.345*
0.217

Headache

19

9.4

183

90.6

0.875

Vomiting

11

6.6

156

93.4

0.187

Rigor

5

4.4

108

95.6

0.061

Fatigue

9

8.3

99

91.7

0.851

Abdominal pain

5

4.8

100

95.2

0.087

Joint pain

3

7.7

36

92.3

1.000

Anorexia

3

9.4

29

90.6

1.000

Kruskal Wallis test (*) has been used to compare distributions for continuous variables (parasite density, age, and household size), Fischer exact test has been used for
categorical variables
Pfhrp2: Plasmodium falciparum Histidin Rich Protein 2 gene, IQR Inter quartile range, LLIN Long lasting insecticidal net

The use of mosquito bednets was the primary meansof bite-prevention. Two-thirds of households (64.2%)
owned a bednet, and only 49.7% of participants spent
the night before the interview under a mosquito bednet.
These results are lower than the previous report fromthe DHS in Kwilu Province. In 2014, 87% of households
surveyed in the Kwilu province possessed a bednet, and69.4% of participants slept under a bednet the night
before the interview [39]. Back then, an extensive mosquito bednet distribution campaign was implemented
with a higher rate of implementation, especially in Kwilu.
However, Mwandagalirwa et al. recently reported consistent data (72% ownership vs 45% use) in health zones
of Kinshasa province, neighbouring Kwilu province [40].

Munyeku et al. Infect Dis Poverty(2021) 10:77

A low coverage during bednet distribution campaigns
can explain the lower proportion of household possessing
bed net. Also, bednet usage is known to be higher among
under-five children and falls progressively to as low as
34% by the early twenties [40]. Subsequently, the majorityof participants (64%) being over five years may accountfor the majority of participants not using bednets.
Among participants who reported prior malaria drug
intake, 13% took quinine at least one week before thesurvey. This finding highlights the poor compliance with
the WHO guidelines for the treatment of malaria in the
study areas as well as challenges associated with the useof injectable artesunate in areas where quinine is cheaper,easy to use and available.
As might be expected, 81.6% of participants reported
a history of fever. In many cases, fever is suggestive of
malaria but is also reported in several febrile illnesses
prevailing in tropical areas. Without a reliable diagnostic tool, a syndromic approach often leads to overtreatment, especially among people living in low tomoderate malaria transmission areas [41]. A recent analysis of household survey data from 24 Sub-Saharan Africa
countries between 2006 and 2014 showed that 35.7% of
all fevers reported by participants were accompanied bymalaria infection evidence, but only 10% of these fevers
were attributable to malaria [42]. Non-malarial febrile illnesses (NFMI) can coincide with malaria infection, andmay lead to over-diagnosis of malaria and underestimation of the burden of associated NFMI [42].
Only 9.9% of false-negative PfHRP2-RDT results
involved parasites with pfhrp2 gene deletions. A similar
result (10.6%) has been reported in Nigeria, [24]. Conversely, Wurtz et al. (2013), in Senegal reported a lower
proportion (2.4%) while Amoah et al. (2016), in Ghana
reported a higher proportions of 23% [4, 5, 17].
This weak proportion shows that pfhrp2 gene deletion is not a major cause of false-negative PfHRP2-RDT
results. Several reasons may explain a false-negative
PfHRP2-RDT result such as poor quality of the test, inappropriate manipulation and interpretation, low parasite
density, excess of circulating parasite antigens creatinga prozone-like effect, and genetic polymorphisms in thetarget antigen [6, 23, 43, 44].
Even though the proportion of PfHRP2-RDT false-negative results due to pfhrp2 gene deletion has surpassed
the 5% threshold set by the WHO, requiring a subnational change in malaria RDTs, the required number ofP. falciparum isolates (37) to include per health facility inthe sampling domain was not reached. Therefore, further
investigations are needed to provide enough evidence forpolicy change.
The overall prevalence of P. falciparum isolates with
pfhrp2 gene deletion was 9.2%. This prevalence is higher

Page 10 of 13

than the previously reported national prevalence of 6.4%
and the local prevalence of 3% [14]. The present study
exclusively enrolled subjects with symptoms suggestive of malaria and thus more likely to be infected while
the previous one included more asymptomatic subjects.
Secondly, Kwilu Province is located in a low to moderate transmission area where immunity is acquired later inlife. This condition of reduced host immunity is favourable to infection by parasites harbouring pfhrp2 genedeletion, which can survive and spread [18]. Thirdly, theprevalence of parasites harbouring pfhrp2 gene deletionhas been shown to be higher in low to moderate transmission area in the beginning of the rainy season, whichis the case for the present study [45].
A similar prevalence has been reported in Eritrea(9.7%) and Kenya (9%) [13, 46]. However, lower prevalence has been reported in Senegal (2.4%), Mozambique(1,4%) and higher prevalence in Nigeria (17%), Ghana(36%) and Zambia (37.5%) [4, 15–17, 24, 25]. The difference in study design and methodology used for deletion
confirmation (nested PCR vs qPCR of a single-copy gene)
could explain the discrepancy. Publications using nested
PCR for confirmation of deletion tend to overestimate
the prevalence while amplification of a single-copy geneby real-time PCR is recommended for appropriate deletion call [47, 48].
The first protocol concerning phrp2/3 deletions was
released in 2014 [49]. Subsequently, the WHO released
a second protocol in 2018 for estimating phrp2/3 deletions among symptomatic patients [35]. Finally, Parr et al.
revised the existing protocols and released a streamlined
protocol taking into account challenges faced by previous
authors [48].
There was a statistically significant difference in
pfhrp2 gene deletion prevalence in Bandundu healthzone compared to Kikwit-Nord and Kikwit-Sud healthzones (P = 0.012). Variations in pfhrp2 gene deletion status within regions and countries have been previously
reported and depend on several factors including levelof transmission and magnitude of PfHRP2-RDT use [10,12, 20, 50]. Further analysis of population genetics may
clarify this finding.
There was a trend towards pfhrp2 gene deletion inolder compared to younger (under-five) patients, but
this was not statistically significant (P = 0.079). However, when analyzing age as a continuous variable, theKruskal Wallis test showed strong evidence suggestingthat the distributions of age differed by pfhrp2 gene deletion status (P = 0.019). This may suggest that the risk ofbeing infected with parasites harboring pfhrp2 deletion
increases with age while traditionally under-5 years old
are at high risk of contracting malaria compared to theolder group.

Munyeku et al. Infect Dis Poverty(2021) 10:77

Similarly, there was a trend towards pfhrp2 gene deletion among negative microscopy results, but weak evidence supported this finding (P = 0.079). Microscopic
examination is based on morphological aspects of theparasite and might not be influenced by genetic traits
such as gene deletions. Even considering that PfHRP2 isknown to be involved in the formation of hemozoin, thisis not the only morphological feature allowing parasite
detection by microscopic examination.
We found more malaria signs and symptoms among
patients infected with parasites not harbouring pfhrp2
gene deletions. However, the difference was not statistically significant. This study could only identify 45 P. falciparum isolates with pfhrp2 gene deletions, and a larger
sample size may be required to detect differences andprovide evidence of association.
This study is the first to provide the local prevalence ofP. falciparum isolates with pfhrp2/3 gene deletion among
symptomatic patients in this region. The availability ofclinical, biological, and sociodemographic data allowed
exploration of differences between infection by pfhrp2deleted and wild-type P. falciparum parasites. However,the limited sample size precluded identification of predictors of pfhrp2 gene deletion and did not allow us tomake solid conclusions regarding differences in pathology between pfhrp2 deleted and wild-type parasites.
The selection of study sites based on known burden ofmalaria and sociodemographic characteristics may haveintroduced a selection bias making the sample not representative of the whole province within which the levelof transmission varies. A health facility-based designis undoubtedly the best choice to recruit symptomaticpatients, but the low service utilization rate and insufficient public subsidies allocated to malaria management
may have prevented some subjects with the characteristic of interest to attend health facilities and thus to beenrolled in the study.
The D.R. Congo National Malaria Control Program
has adopted a five year (2016–2020) strategic plan withgoals including the diagnosis of at least 80% of fever cases
and the treatment of all positive diagnosed cases with
ACT. Increased service utilization, the significant use of
PfHRP2 based RDTs as primary diagnostic tools and coinfections with non-malaria febrile illnesses could leadto the initiation of a selective treatment favoring pfhrp2
deleted parasites. There is a need, therefore, to establish
a surveillance system for pfhrp2 deleted mutants as a partof malaria control programs. Such a surveillance systemshould be strengthened with reliable diagnostic tools
such as molecular point of care testing to ensure efficientand evidence-based allocation of resources to disease
control programs.

Page 11 of 13

In routine practice, clinicians should investigate otherfebrile illnesses despite a positive RDT result to minimize
failure in disease management.

Conclusions
We found a local prevalence of 9.2% of P. falciparum isolates with a pfhrp2 gene deletion among symptomaticpatients. These isolates explained only 9.9% of PfHRP2RDT false-negative results, suggesting that factors otherthan pfhrp2 gene deletion are of significant importancein the false-negativity rates of PfHRP2-based RDTs. Even
though the proportion of false-negative PfHRP2-RDT
results due to the pfhrp2 deletion has surpassed the 5%
threshold set by the WHO for a subnational change inmalaria RDTs, further regional investigations with appropriate sampling are needed to provide enough evidence
for policy change. Meanwhile, the use of RDTs targeting PfHRP2 and pLDH antigens could limit the spread ofdeleted isolates.
Abbreviations°C: Degree centigrade; ACT​: Artemisinin-based Combination Therapy; Ag:
Antigen; CAID: Cellules d’Analyses des Indicateurs de Developpement/Unitfor development indicators analysis; D.R. Congo: Democratic Republic ofCongo; DBS: Dried Blood Spot; DNA: Deoxyribonucleic Acid; ELISA: Enzymelinked Immunosorbent Assay; g/dL: Gram per deciliter; HIV/AIDS: Human
Immunodeficiency Virus/Acquired Immunodeficiency Syndrome; IQR: Inter
Quartile Range; kDa: KiloDalton; LLIN: Long Lasting Insecticidal Net; LOD: Limitof Detection; mmHg: Millimeter mercury; mmol/L: Millimole per liter; ng:
Nanogram; NMFI: Non-Malaria Febrile Illness; pAldo: Parasite Aldolase; PCR:
Polymerase Chain Reaction; PfHRP1: Plasmodium falciparum Histidine Rich
Protein 1; pfhrp2: Plasmodium falciparum Histidine Rich Protein 2 gene; PfHRP2:
Plasmodium falciparum Histidine Rich Protein 2; pfHRP2-RDT: Plasmodium
falciparum Histidine Rich Protein 2 based Rapid Diagnostic Test; PfHRP3:
Plasmodium falciparum Histidine Rich Protein 3; pfldh: Plasmodium falciparum
lactate dehydrogenase gene; PfPCR: Plasmodium falciparum Polymerase Chain
Reaction; pLDH: Parasite Lactate Dehydrogenase; PNLP: Programme Nationalde Lutte contre le Paludisme / National Malaria Control Programme; QBC:
Quantitative Buffy Coat; qPCR: Quantitative Polymerase Chain Reaction; RBC:
Red Blood Cell; RDT: Rapid Diagnostic Test; SP: Sulfadoxine-Pyrimethamine;
USAID: United States Agency for International Development; WBC: White
Blood Cell; WHO: World Health Organization; µl: Microliter.
Acknowledgements
The authors would like to thank all patients and are grateful to the Division
Provinciale de Santé du Kwilu (DPS-Kwilu) for assistance with samples collection. The authors are also grateful to Carole Ihomi Nkoy, Joel Imponge, andAgathe Bikupe Nkoy for their valuable contribution in data entry and field
logistics.
Authors’ contributions
YBM, AAM and PMM conceived and designed the study; YBM, AAM & ME performed experiments and data analysis; YBM, RLC and CS interpreted the results
and wrote the manuscript. All authors read and approved the final manuscript.
Funding
This study was supported by the Nagasaki University School of Tropical
Medicine and Global Health and the Malaria Unit of the Nagasaki Institute ofTropical Medicine. R.C. is supported by Japanese Society for the Promotion of
Science (JSPS), Japan Grant-in-Aid for Scientific Research Nos. 16K21233 and19K07526.

Munyeku et al. Infect Dis Poverty(2021) 10:77

Availability of data and materials
The datasets used and/or analysed during this study are available from thecorresponding author on reasonable request.

Page 12 of 138.
9.

Declarations
Ethics approval and consent to participate.
The study was approved by the Kwilu Province Division of Health (N°ADM/707/01/DPS-KLU/CD/JPBK/632/2018), the Kinshasa School of Public
Health Ethical Committee (ESP/CE/015/2019) and the School of Tropical
Medicine and Global Health Ethical Review Committee.Written and verbal
voluntary informed consent was obtained from all study participants including guardian/parents of non-adult participants.

10.

11.

Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Direction Des Laboratoires de Santé, Ministère de La Santé, Kinshasa, Democratic Republic of the Congo. 2 Institut National de Recherche Biomédicale(INRB), Laboratoire de Virologie Clinique, Kinshasa, Democratic Republicof the Congo. 3 Graduate School of Tropical Medicine and Global Health(TMGH), Nagasaki University, Nagasaki, Japan. 4 Malaria Unit, Departmentof Pathology, Institute of Tropical Medicine, Nagasaki University, Nagasaki,
Japan. 5 Division Provinciale de La Santé du Kwilu, Kwilu, Democratic Republicof the Congo. 6 Kinshasa School of Public Health, Faculty of Medicine, University of Kinshasa, Kinshasa, Democratic Republic of the Congo. 7 Laboratoryof Malaria and Vector Research, National Institute of Allergy and Infectious
Diseases, National Institutes of Health, Rockville, MD 20852, USA. 8 Departmentof Clinical Research, London School of Hygiene & Tropical Medicine, London,
UK. 9 Institut Supérieur Des Techniques Médicales (ISTM), Kikwit, DR, Congo.
10
Department of Protozoology, Institute of Tropical Medicine (NEKKEN), Nagasaki, Japan. 11 Division of Molecular Parasitology, Proteo‑Science Centre, Ehime
University, Toon, Japan.

12.

13.

14.

15.

16.

Received: 22 January 2021 Accepted: 13 May 2021
17.

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