First report of pfhrp2 and pfhrp3 gene deletions compromising HRP2-based malaria rapid diagnostic tests in Malawi

First report of pfhrp2 and pfhrp3 gene deletions compromising HRP2-based malaria rapid diagnostic tests in Malawi | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article First report of pfhrp2 and pfhrp3 gene deletions compromising HRP2-based malaria rapid diagnostic tests in Malawi Johnsy Mary Louis, Ernest Mazigo, Hojong Jun, Wang-Jong Lee, Jadidan Hada Syahada, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6618930/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Oct, 2025 Read the published version in Infectious Diseases of Poverty → Version 1 posted 5 You are reading this latest preprint version Abstract Background HRP2-based rapid diagnostic tests (RDTs) are widely used for malaria diagnosis in Malawi, but their accuracy may be compromised by Plasmodium falciparum parasites lacking the pfhrp2 and pfhrp3 genes. While such deletions have been reported in other malaria-endemic countries, their presence and diagnostic impact in Malawi remain unknown. Methods A cross-sectional study was conducted between December 2020 and June 2021, enrolling 1,582 participants from referral hospitals in Mzuzu ( n = 1,186) and Lilongwe ( n = 396). Malaria diagnosis was performed using RDTs, microscopy, and qPCR. A total of 391 P. falciparum positive samples were analyzed for pfhrp2/pfhr3 gene deletions using multiplex qPCR. Results Malaria prevalence was higher in Lilongwe (45.2%) than in Mzuzu (22.9%). Infections in Lilongwe were predominantly asymptomatic (94.2%), whereas Mzuzu had mostly symptomatic cases (97.1%). RDTs demonstrated higher sensitivity (78.5%) than microscopy (64.8%), but slightly lower specificity, with 93.6% for RDT compared to 95.4% for microscopy. Dual pfhrp2/3 gene deletions were found in 24 (15.0%) isolates from Lilongwe and 24 (10.4%) from Mzuzu. All dual-deleted samples were false negative by RDT but were positive by microscopy and qPCR. Conclusions This study is the first to report pfhrp2/3 gene deletions in Malawi. The presence of these deletions may compromise the performance of HRP2-based RDTs, indicating the need to reassess diagnostic strategies in affected regions. Plasmodium falciparum pfhrp2 pfhrp3 gene deletion diagnostic accuracy rapid diagnostic test Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Malaria is still considered a significant public health concern ( 1 ). In 2022, there were an estimated 249 million cases globally, 94% (233 million) of them occurring in sub-Saharan African countries including Malawi. More than 95% of Malawi population live in malaria endemic areas ( 2 ). In 2021, Malawi contributed to 1.7% of the global malaria cases, 1.2% of global deaths, and 8% of all malaria cases in Eastern and Southern African countries. Plasmodium falciparum was responsible for more than 95% of malaria infections and deaths in 2021 in Malawi ( 3 ). Since 2000, a dramatic decrease in global malaria cases and deaths has been reported in sub-Saharan African countries ( 4 ). The decrease resulted from the scaling-up of interventions including the use of malaria rapid diagnostic tests (RDTs) for detection of malaria infections, which was recommended by the WHO in the early 1990s. Since its deployment, RDTs have considerably facilitated early malaria diagnosis procedures, especially in rural malaria endemic regions and other areas where good microscopy is not feasible. For instance, of 3.1 billion RDTs that were sold between 2010 and 2020, 81% were used in sub-Saharan countries, making it the primary malaria diagnostic technique. However, although the use of RDTs is increasing, the global rise in isolates with P. falciparum histidine-rich proteins ( pfhrp2 and pfhrp3 ) gene deletions is challenging their efficacy ( 5 ). Accurate diagnosis of malaria is a fundamental strategy for its control ( 6 ). RDTs detect Plasmodium specific antigens, primarily histidine-rich protein 2 (HRP2) or parasite-specific lactose dehydrogenase (pLDH) antigen, from a drop of blood in malaria positive patients ( 7 ). The kits specific for P. falciparum are designed to capture histidine-rich protein 2 (PfHRP2), which is encoded by the pfhrp2 gene located in the sub-telomeric region of chromosome 8 ( 8 ). The pfhrp2 gene is 85–90% homology in nucleotide sequence-flanking repeats similar to pfhrp3 , which causes them to cross-react in RDTs ( 8 ). As RDTs detect an inert protein component of P. falciparum parasites, detection methods using PfHRP2/PfHRP3 are thus limited as proxy measures of parasite density. The sensitivity of RDTs falls sharply when parasite density drops below 100 to 500 parasites/µL ( 9 , 10 ). Moreover, the persistence of PfHRP2/PfHRP3 in the bloodstream for several weeks after parasite clearance has been a matter of concern regarding the accuracy of RDT ( 11 ). Based on the WHO guidelines, each country should establish the status and surveillance of gene deletion trends over time ( 11 ). Re-assessment of the national diagnostic strategy has to be done when more than 5% of P. falciparum clinical infections are missed by HRP2-based RDTs ( 12 ). This study aimed to investigate the prevalence of P. falciparum and pfhrp2/3 gene deletions in isolates from Mzuzu and Lilongwe, Malawi. Additionally, it assessed how pfhrp2/3 gene deletions and parasite density impact the accuracy, sensitivity, and specificity of RDTs and microscopy. Importantly, this is the first study to report the presence of pfhrp2 and pfhrp3 gene deletions in Malawi. The identification of P. falciparum parasites lacking these genes, along with their detection patterns using field diagnostic tools, provides valuable evidence of the effectiveness of the current malaria surveillance and diagnostic strategies in the country. Methods Study site, population, and sampling Samples were collected from Lilongwe and Mzuzu referral hospitals in Malawi from December 2020 to June 2021. The study targeted individuals of all age groups who were visiting the hospitals for treatments. The two referral hospitals were purposively selected because they serve a large proportion of the population and are in high malaria transmission settings. Approximately 15% of Malawi’s population resides in Lilongwe, while Mzuzu is reported to be the fastest-growing city in terms of population. Both regions are reported to have among the highest population at risk of malaria ( 13 ). In this study, a total of 1,582 patients blood samples were collected, 396 (25.0%) blood samples from Lilongwe and 1,186 (75.0%) blood samples from Mzuzu hospitals (Fig. 1 A and 1 B). The sample size was not statistically predetermined; instead, it was based on the number of eligible participants available during the study period. This convenience sampling approach aimed to collect as many samples as possible to support meaningful molecular and diagnostic analyses. Clinical sample collection and handling All procedures were performed by skilled and trained technicians working at the local hospitals. At each selected hospital, participants were consulted and screened for eligibility to participate in the study. After obtaining voluntary informed consent, blood was drawn using the finger-prick method with a sterile lancet and capillary tube. Malaria was diagnosed using a histidine rich protein 2 (HRP2)-based rapid diagnostic test (RDT) as part of the routine procedure in local health facilities (Paracheck-Pf®, Orchid Biomedical Systems, Goa, India). Simultaneously, approximately 250 µL of venous whole blood was collected into K2 EDTA tubes (BD Vacutainer krackeler scientific) and homogeneously mixed by inverting 10 times. If venous blood had already been collected for other clinically necessary tests, any leftover blood was used for the study instead. Immediately after whole blood collection, two thin Giemsa-stained blood smears were prepared for malaria diagnoses by microscopy. Each slide was examined independently by two skilled microscopists. In cases of discordant results, a third microscopist was involved. All microscopists had received formal training in malaria microscopy, underwent and competency assessments, and participated in routine internal quality control and external quality assurance (EQA) programs to ensure accuracy and reliability. Microscopists were blinded to each other’s results reported by the other. Dried blood spots (DBS) were prepared from the remaining whole blood of each participant. DBS papers were packed separately into plastic bags with silica gels and then shipped to Kangwon National University (KNU) in Republic of Korea, where qPCR was conducted for malaria diagnosis and detection of pfhrp2/3 deletions. P. falciparum in vitro culture and gDNA extraction for pfhrp2/3 control preparation To determine the limit of detection (LoD) of qPCR diagnosis targeting the 18S rRNA gene and pfhrp2/3 detection based on parasite count, P. falciparum strains 3D7 (ATCC) (wildtype, west Africa origin), Dd2 ( pfhrp2 deletion, Indochina origin), and HB3 ( pfhrp3 deletion, Honduras origin) were cultured using human erythrocytes at 2% hematocrit in RPMI-1640 medium (Invitrogen, CA). The culture medium was supplemented with 2.3 g/L sodium bicarbonate, 0.05 g/L hypoxanthine, 10% Albumax I solution, and 10 mg/mL gentamicin. Cultures were maintained in a gas mixture of 90% N 2 , 5% O 2 , and 5% CO 2 and incubated at 37°C. Thin blood films were prepared following standard protocols, and parasitemia was measured by Giemsa staining under a microscope at 100X magnification. Once ring-stage of parasites reached 5% after synchronization, genomic DNA (gDNA) was extracted from the cultured samples ( 14 ). For the clinical isolates gDNA extraction, one spot (10 mm in diameter) was punched from each dried blood spot (DBS) paper, cut into several pieces, and transferred into individual sterile 1.5 mL microcentrifuge tubes. DNA was extracted using the QIAamp DNA Mini Kits (Qiagen, Hilden, Germany), according to manufacturer’s instructions with 50 µL of final elution. Molecular diagnosis of P. falciparum infections by quantitative PCR (qPCR) Molecular diagnosis targeting the 18S rRNA gene of P. falciparum was performed using qPCR with previously published primers (Forward primer: ATTGCTTTTGAGAGGTTTTGTTACTTT, Reverse primer: GCTGTAGTATTCAAACACAATGAACTCAA) and a probe (FAM-CATAACAGACGGGTAGTCAT) ( 15 ). The qPCR assay components and cyclic conditions were slightly modified to optimize performance. Briefly, each qPCR reactions were conducted in a total volume of 20 µL, including 10 µL of 2X Prime Time Gene expression Master Mix with ROX reference dye (Integrated DNA technologies, IA), 1 µL of template DNA (gDNA), 0.5 µM of each of the primers, and 0.25 µM of each TaqMan Probes. Reactions were run on an AriaMx Real-Time PCR system (Agilent Technologies, CA) under the following cycling conditions: an initial hot-start polymerase activation at 95℃ for 10 minutes, followed by 45 cycles of denaturation at 95℃ for 15 seconds and annealing at 65℃ for 65 seconds. A standard curve for the qPCR diagnosis was prepared using P. falciparum 3D7 strain parasites cultured in vitro at 5% ring-stage. All qPCR reactions were performed in duplicate, and for each test, a tenfold serial dilution of the standard curve was included. Characterization of pfhrp2 and pfhrp3 deletions in P. falciparum positive samples A multiplex qPCR was performed to identify pfhrp2 and pfhrp3 deletions. The multiplex reactions were run together with the cultured P. falciparum 3D7 as standard controls. Published primer sequences for pfhrp2 (Forward: GTATTATCCGCTGCCGTTTTTGCC; Reverse: CATCTACATGTGCTTGATTTTCGT) and pfhrp3 (Forward: ATATTATCCGCTGCCGTTTTTGCT; Reverse: CCTGCATGTGCTTGACTTTCGT) and probes (PfHRP2: FAM-TTCCGCATTTAATAATAACTTGTGTAGC, and PfHRP3: HEX-CTCCGAATTTAACAATAACTTGTTTAGC) were adapted for the multiplex qPCR platform ( 16 ). These primers were tested with varying gDNA concentrations extracted from Pf3D7 , PfDd2 and PfHB3 strains, corresponding to parasite count in tenfold serial dilution from 210,000 parasites/µL to 0.21 parasites/µL. Reactions were conducted in a total volume of 10 µL, including 5 µL of 2X Prime Time Gene expression Master Mix with ROX reference dye (Integrated DNA technologies), 1 µL of template DNA (gDNA), 0.5 µM of each of the primers, and 0.25 µM of each TaqMan Probes. Reactions were conducted on an AriaMx Real-Time PCR system (Agilent Technologies) with the following cycling conditions: hot-start polymerase activation at 95℃ for 5 minutes, followed by 45 cycles of denaturation at 95℃ for 15 seconds and annealing at 60℃ for 35 seconds. To establish molecular surveillance criteria for the pfhrp2 and pfhrp3 genes, a cutoff of relative parasitemia based on the 18S rRNA gene of under 5 parasites/µL, as described elsewhere, was implemented ( 17 ). Hence, in this analysis, samples with less than 5 parasites/µL in 18S rRNA gene detection were considered analytically negative for P. falciparum infection and were excluded from pfhrp2 and pfhrp3 gene detection. Case definitions Symptomatic malaria is defined by the presence of malaria-related symptoms (vomiting, headache, and body temperature > 37°C) within the past 2 days and at the time of examination, along with detectable malaria parasites in blood. Clinical manifestations data were collected using a structured questionnaire administered to all participants, which included questions about the presence of these symptoms within the specified timeframe. Asymptomatic malaria is defined as the presence of detectable parasites in the blood without any malaria-related symptoms during the past week or at the time of the survey, and with no history of antimalaria drug use within the past week. Statistical analysis The qPCR data were visualized by Agilent AriaMx 1.8 software (Agilent Technologies) and statistically analyzed with GraphPad Prism 8 software. A log transformation of parasitemia was performed to compare detection by microscopy and qPCR. Correlation analysis of parasitemia was conducted using spearman correlation ( ρ ) and linear regression via Sigma Plot software v12. Actual parasitemia measured by microscopy and relative parasitemia from 18S rRNA qPCR were summarized as means and correlated to assess the agreement between log-transformed parasite values. An unpaired t -test was used to compare the two diagnostic methods, while differences in asymptomatic and symptomatic cases between the two regions were analyzed using the Mann–Whitney test. The Wilcoxon signed-rank test was used to compare paired numeric values. Statistical analysis of clinical specimen diagnosis was conducted with MEDCALC statistical, available at https://www.medcalc.org/calc/diagnostic_test.php . Data were organized into double-entry tables to calculate sensitivity, specificity, and positive and negative predictive values for each test at 95% confidence intervals. Ethics statement The study procedures were approved by the National Health Science Committee (NHSRC), a division of Malawi’s Ministry of Health (MoH) (IRB00003905 – Evaluation of Diagnostic Accuracy of the Next Generation Mobile Malaria Diagnostic Kit (miLab™)), as well as by the Ethical Review Board at Kangwon National University (KWNUIRB-2023-05-008). Before participating in the study, all participants provided informed consent. All experiments were conducted in accordance with relevant guidelines and regulations. Results Prevalence of P. falciparum in Lilongwe and Mzuzu, Malawi A total of 1,582 participants were enrolled in the study, including 396 (25.0%) from Lilongwe and 1,186 (75.0%) from Mzuzu (Fig. 1 A and 1 B). Malaria-related symptoms were recorded for all participants at the time of sample collection. Of the collected samples, 1,528 (96.6%) and 1,563 (98.8%) were successfully tested using light microscopy (LM) and malaria rapid diagnostic tests (RDT), respectively (Fig. 1 A and 1 B). A total of 1,514 (95.7%) samples were tested by both diagnostic methods. Molecular diagnosis for P. falciparum was performed on all 1,582 (100%) isolates using quantitative PCR (qPCR) (Fig. 1 A and 1 B). Overall, malaria positive rate based on field-based diagnostic tools was significantly higher in Lilongwe (30.6% by LM and 53.4% by RDT) compared to Mzuzu (21.0% by LM and 21.2% by RDT). Across both regions, the overall prevalence was 23.5% by LM and 29.2% by RDT (Table 1 ). In contrast, the laboratory-based qPCR method detected a higher overall prevalence of 31.5% (499/1,582 samples) compared to the field diagnostic tools (Table 1 ). Table 1 P. falciparum prevalence based on each diagnostic tools in Lilongwe and Mzuzu, Malawi Diagnostic tool Lilongwe Mzuzu Total No. of Positive (%) No. of Negative (%) Total (%)* No. of Positive (%) No. of Negative (%) Total (%)* No. of Positive (%) No. of Negative (%) Total (%)* Microscopy 121 (30.6) 274 (69.4) 395 (99.7) 238 (21.0) 895 (79.0) 1,133 (95.5) 359 (23.5) 1,169 (76.5) 1,528 (96.6) RDT 206 (53.4) 180 (46.6) 386 (97.5) 250 (21.2) 927 (78.8) 1,177 (99.2) 456 (29.2) 1,107 (70.8) 1,563 (98.8) qPCR 214 (54.0) 182 (46.0) 396 (100.0) 283 (23.9) 903 (76.1) 1,186 (100.0) 497 (31.4) 1,085 (68.6) 1,582 (100.0) * Number of isolates (%) accessible by each diagnostic tool among the total participants. Comparison of field diagnostic performance and the effect of parasite density In reference to qPCR, RDT showed higher sensitivity of 78.5% (95% CI: 74.6%-82.1%) but lower specificity at 93.6% (92.0%-95.0%) when compared to light microscopy (LM), which had a sensitivity of 64.8% (95% CI: 60.3%-69.1%) and specificity of 95.4% (95% CI: 94.0%-96.6%) (Fig. 2 A). The positive predictive value (PPV), which is the probability that the disease is present when the test is positive, was higher for microscopy (LM) at 86.63% (95% CI: 82.98–89.59%), while the negative predictive value (NPV), which is the probability that the disease is not present when the test is negative, was higher for RDT at 90.4% (95% CI: 88.9–91.8%). Diagnostic accuracy in this study was defined as the proportional of true positive and true negative among all individuals tested and was higher for RDT (88.8%, 95% CI: 87.1%-90.3%) than for LM (85.8%, 95% CI: 84.0%-87.5%) (Fig. 2 A). Under LM detection, parasitemia was significantly lower in Mzuzu (Mean ± SD: 46,805 ± 113,152 parasites/µL) than in Lilongwe (Mean ± SD: 57,931 ± 85,397 parasites/µL) ( p < 0.001). A strong positive correlation was observed between parasitemia quantified by LM in the field and relative parasite density estimated by 18S rRNA based qPCR in the laboratory ( ρ = 0.722, p < 0.001), indicating a consistent association between the two methods (Fig. 2 B). However, regression analysis suggested that qPCR may systematically yield lower parasite density estimates compared to LM. The parasitemia levels detected by field diagnostic methods differed significantly, with LM showing a median of 1,488 parasites/µL (IQR: 5,877.9) and RDT showing a median of 882.4 parasites/µL (IQR: 4,108.2; p = 0.0344) (Fig. 2 C). Based on parasite density, the performance of both LM and RDT was evaluated for infections above 2.4 parasites/µL, which corresponds to the detection limit of the qPCR method used as the reference standard in the study regions (Fig. 2 C). When Comparing LM to RDT and qPCR, the differences in parasitemia between false negative (FN) and true positive (TP) results showed varying average parasitemia levels (Fig. 2 D). In this study, false negative results refer to samples that tested negative by both RDT and qPCR but were positive by LM, while true positive results are those that tested positive by both RDT and qPCR. False negative cases had averages of 9,964.5 parasites/µL in RDT, and 8961.4 parasites/µL in qPCR, while true positive cases exhibited averages of 55,431.0 parasites/µL in RDT, and 56,918.6 parasites/µL in qPCR (Fig. 2 D). These differences in parasitemia levels between FN and TP detected by RDT and qPCR, when compared with LM, were statistically significant (Fig. 2 D). These results indicate that the sensitivity of RDT and qPCR is strongly influenced by parasite density. Distribution of parasitemia levels and associated symptoms in malaria positive participants Participants were recruited based on their availability at local hospitals, rather than clinical suspicion of malaria. To assess differences in clinical manifestation patterns across the study regions, symptoms related to malaria, such as vomiting, headache, and body temperature (> 37°C) were recorded. In Lilongwe, 114 out of 121 (94.2%) P. falciparum -positive participants identified by LM did not have any specific symptoms related to malaria, while the remaining 7 (5.8%) were symptomatic (Fig. 3 ). In contrast, in Mzuzu, 231 out of 238 (97.1%) LM positive participants were symptomatic, with either single or mixed clinical manifestation, while 8 participants (3.4%) were asymptomatic (Fig. 3 ). Among the asymptomatic individuals from both Lilongwe and Mzuzu, LM positive isolates did not show a statistically significant difference ( p = 0.43). The overall average parasitemia under LM was significantly different between clinically recorded isolates in Lilongwe ( n = 121, 57,931 ± 85,397 parasites/µL) and Mzuzu ( n = 239, 45,262 ± 111,561 parasites/µL) ( p = 0.002). These results clearly indicate that the degree of symptom onset differed significantly between the two regions, while parasitemia levels did not differ. Molecular validation of pfhrp2 and pfhrp3 gene deletions using qPCR in field isolates To detect and confirm molecular surveillance of pfhrp2 and pfhrp3 gene deletions, a multiplex qPCR-based assay was performed ( 16 ). Genomic DNA from three different P. falciparum in vitro cultured strains (3D7, Dd2, and HB3) were used to optimize and validate the assay for pfhrp2 and pfhrp3 gene deletions status. The P. falciparum 3D7 strain exhibits both the pfhrp2 and pfhrp3 genes, while the Dd2 strain has a single gene deletion of the pfhrp2 , and the HB3 strain has a deletion of the pfhrp3 gene (Fig. 4 A and 4 B). To establish molecular surveillance criteria for detecting deletion of pfhrp2 and pfhrp3 genes in clinical isolates, a cutoff of relative parasitemia below 5 parasites/µL based on the 18S rRNA gene was employed as described elsewhere ( 17 ). Relative parasitemia in pfhrp2 and pfhrp3 deleted isolates was estimated by comparing the Cq values of these target genes to those of a reference gene ( P.falciparum 3D7 strain). This relative quantification approach was used to determine the presence or absence of pfhrp2 and pfhrp3 gene targets based on their amplification profiles. The analytical limit of detection (LoD) for the multiplex qPCR targeting both pfhrp2 and pfhrp3 genes using the P. falciparum 3D7 strain was estimated to be 2.1 parasites/µL, with qPCR efficiencies of 93.1% and 92.3%, respectively (Fig. 4 C). The LoD for the pfhrp2 and pfhrp3 genes was approximately 10 times higher than that of the 18S rRNA gene (0.21 parasites/µL) when detected by qPCR. A significant positive correlation was observed between the 18S rRNA gene and pfhrp2 ( ρ = 0.898), and between and 18S rRNA with pfhrp3 ( ρ = 0.900) (Fig. 4 D). In this analysis, samples with less than 5 parasites/µL based on 18S rRNA gene detection were considered analytically negative and excluded from the further gene deletion analysis (Fig. 4 D). Deletions of pfhrp2 and pfhrp3 genes in isolates from Mzuzu and Lilongwe, Malawi Multiplex qPCR assays were performed on 488 clinical isolates confirmed as P. falciparum positive by qPCR to assess pfhrp2 and pfhrp3 gene deletion. Based on the inclusion criteria for gene deletions analysis, 160 isolates from Lilongwe and 231 isolates from Mzuzu were included in the final dataset. In Lilongwe, pfhrp2 single gene deletions were detected in 7 isolates (4.4%) with a relative parasite density of 1,460 ± 3,705 parasites/µL, calculated from the 18S rRNA gene (Table 2 ). In Mzuzu, 2 isolates (0.9%) showed pfhrp2 single gene deletions, with a relative parasite density of 11.05 ± 0.70 parasites/µL, which was marginally lower than in Lilongwe. Single pfhrp3 gene deletions were detected in 11 isolates (6.9%) in Lilongwe and 11 isolates (4.8%) in Mzuzu. The parasite density was 615.1 ± 1,785 parasites/µL in Lilongwe and 168.5 ± 433.4 parasites/µL in Mzuzu (Table 2 ). Dual gene deletions, which lead to false negatives in RDT, were detected in 24 isolates (15.0%) in Lilongwe and 24 isolates (10.4%) in Mzuzu, with parasite densities of 26.36 ± 37.52 parasites/µL and 167.2 ± 570.5 parasites/µL, respectively (Table 2 ). Overall, deletions in either the pfhrp2 , pfhrp3 or both genes were confirmed in 79 isolates (20.2%) in Malawi (Table 2 ). Table 2 pfhrp2 and pfhrp3 gene deletion status in Lilongwe and Mzuzu, Malawi. Δpfhrp2 Δpfhrp3 Δpfhrp2 and 3 No deletion Total n (%) RPD* n (%) RPD* n (%) RPD* n (%) RPD* n Lilongwe 7 (4.4) 1,460 ± 3,705 11 (6.9) 615.1 ± 1,785 24 (15.0) 26.36 ± 37.52 118 (73.8) 17,291 ± 38,647 160 Mzuzu 2 (0.9) 11.05 ± 0.70 11 (4.8) 168.5 ± 433.4 24 (10.4) 167.2 ± 570.5 194 (84.0) 3,408 ± 7,039 231 Total 9 (2.3) 22 (5.6) 48 (12.3) 312 (79.8) 391 *RPD: relative parasite density (parasites/µL, Mean ± S.D.) Discussion This study was conducted to determine the prevalence of P. falciparum in Malawi and the contribution of pfhrp2 and pfhrp3 gene deletion to the effectiveness of malaria diagnostic tools. As the Global Technical Strategy on Malaria 2016–2030 aims for a malaria-free world by 2030, surveillance of pfhrp2/3 deletions is essential for monitoring progress towards this goal ( 18 ). As malaria transmission declines in endemic countries, the proportion of low-density infections among both symptomatic and asymptomatic individuals are likely to increase, which may reduce the utility of light microscopy (LM) and malaria rapid diagnostic tests (RDTs). Both methods have been shown to underestimate malaria prevalence in such cases. In Malawi, as in many malaria-endemic countries, LM and RDTs remain the primary tools for malaria diagnosis. Therefore, it is essential to evaluate the effectiveness of these diagnostic tools ( 16 ). Molecular techniques, particularly PCR-based methods, are known for their higher sensitivity in malaria detection ( 19 – 21 ). Our findings indicate that while both LM and RDTs are highly specific, LM generally has a lower detection rate compared to RDTs ( 22 , 23 ). This is due to several factors that limit LM efficiency, including reliance on reader expertise, slide preparation quality, and its detection threshold. Although HRP2/3-based RDTs offer higher sensitivity, they can produce false-positive results due to the prolonged persistence of HRP2/3 antigens following parasite clearance ( 24 , 25 ). In this study, when qPCR used as a reference standard, RDT showed a higher sensitivity (78.50%) making them more effective than LM in detecting malaria in the studied regions. Conversely, LM showed higher specificity (95.42%) compared to RDTs. This aligns with a study from Nigeria ( 26 ), suggesting that RDTs may detect low-density infections or lingering HRP2/3 antigens post-infection, which LM could miss ( 27 ). So far, comparative analysis of LM and RDT provided the rate of false positives and true positives both of which have implications for malaria control and intervention in Malawi. In this study, we found that the prevalence rate of asymptomatic malaria was higher in Lilongwe (28.9%) than Mzuzu district (0.8%). This finding was comparable to a study conducted from December 2019 to April 2020 on asymptomatic malaria in blood donors from the central zone of Malawi, which reported 18.5% asymptomatic malaria cases in Lilongwe and 8.6% in Mzuzu from northern zone ( 28 ). Other studies in Malawi have reported asymptomatic malaria prevalence rates of 42% among school age children, and 14.1% in younger children ( 29 , 30 ). Similar trends have been observed in countries such as Ethiopia (Pawe, 14.5%) ( 31 ), Nigeria (77.6%) ( 32 ), Cameroon (Douala, 28.9%) ( 33 ), and Tanzania (Bagamoyo district and other regions, 57.5%) ( 34 , 35 ). These similarities are likely due to high transmission and repeated exposure, which promote the development of immunity and asymptomatic infection ( 36 ). Differences in asymptomatic malaria prevalence rates can also be attributed to differences in geographical locations, study design, housing quality, quality of houses, nature of population, sample size, study period, vector control methods, and malaria transmission rates ( 37 ). In this study, parasite densities did not differ significantly between symptomatic and asymptomatic individuals, indicating that silent carriers may contribute substantially to malaria transmission. Thus, we recommend critical surveillance of both symptomatic and asymptomatic malaria in Malawi, along with an evaluation of the detection limits of primary diagnostic tools used in the region. The recent emergence of parasites lacking pfhrp2 and pfhrp3 genes poses a threat to malaria diagnosis and control programmes ( 38 ). The WHO recommends reconsidering the use of HRP2-based diagnostics when more than 5% of clinical P. falciparum infections produce false-negative RDT results due to pfhrp2/3 gene deletions ( 39 , 40 ). Although pfhrp2/3 gene deletions had not previously been reported in Malawi, our study detected pfhrp2 deletions in 2 (0.9%) samples from Mzuzu and 7 (4.4%) samples from Lilongwe. These single gene deletions did not lead to false-negative RDT results, consistent with findings from previous studies from Tanzania and Yemen ( 41 , 42 ). This anomaly could be the consequence of a false-positive RDT result due to cross-reactivity with circulating proteins such as rheumatoid factor in the blood stream ( 43 ), or it could be the result of a prior infection with samples that tested positive for pfhrp2 ( 44 ). Additionally, we observed single pfhrp3 deletions in 4.8% of samples from Mzuzu and 6.9% from Lilongwe. These data further reveal a higher proportion of pfhrp3 deletions compared to pfhrp2 . This finding is significant, as pfhrp3 deletions are believed to occur more prevalent during low transmission seasons, when polyclonal infections are less likely. Similar observations have been identified in Central and Southern America, where malaria transmission is low, with up to 70% of tested samples showing deletions in the pfhrp3 region ( 45 – 47 ). Dual deletions 48 samples (12.3%) were not detected by RDTs, indicating false-negative results and raising significant concerns for malaria diagnosis in the region. These deletions were observed in both symptomatic and asymptomatic population, across both low and high parasitemia. Since RDTs are the primary diagnostic tool in Malawi, false negatives due to gene deletions could lead to missed diagnoses, undermining malaria control efforts. Vigilant monitoring of pfhrp2/3 deletions is therefore critical to avoid undetected infections that could compromise malaria eradication goals. Similar effects of dual deletions haven been observed in other African regions ( 38 ). This study has several important limitations. The samples used in this study were collected between 2020 and 2021; therefore, the study design did not follow the WHO protocol for assessing pfhrp2 deletions ( 48 ). As a result, our prevalence estimates may be over or underestimated. Moreover, a low parasite density in asymptomatic cases may not be suitable for detection of pfhrp2/3 deletions, and for this reason the WHO recommends evaluating deletions in symptomatic patients for more accurate data ( 49 ). However, our use of a multiplex qPCR assay demonstrated a practical approach for detecting pfhrp2/3 deletions even at low parasite densities ( 50 ). Finally, as only two sites were involved in this study, the findings may not be representative of the entire country, emphasizing the need for nationwide surveillance. Conclusions This study provides evidence of pfhrp2 and pfhrp3 gene deletions in P. falciparum isolates from Malawi, highlighting the urgent need for surveillance to assess their prevalence and spread across the country. The high proportion of pfhrp3 deletions requires further investigation into the factors influencing these deletions during the transmission season. Based on these findings, we recommend screening for pfhrp2/3 deletions even in RDT-positive samples, considering the potential for cross-reactivity and false positives caused by lingering pfhrp2/3 antigens after treatment. Our comparative analysis showed that, although RDT remain widely used, their diagnostic sensitivity is compromised in areas with a high prevalence of gene deletions. In contrast, while light microscopy offered greater specificity, it lacked the sensitivity of qPCR, which emerged as the most reliable and accurate method for detecting P. falciparum infections. Overall, this study highlights the critical need to develop alternative diagnostics targets to address the growing challenge posed by pfhrp2/3 deletions in malaria-endemic regions. Abbreviations DBS Dried Blood Sample EQA External Quality Assurance FN False Negative IQR Interquartile Range LDH Lactose Dehydrogenase LM Light Microscopy LOD Limit of Detection RDTs malaria rapid diagnostic tests NPV Negative Predictive Value pfhrp2 Plasmodium falciparum histidine rich protein 2 pfhrp3 Plasmodium falciparum histidine rich protein 3 PPV Positive Predictive Value qPCR quantitative Polymerase Chain Reaction RPD relative parasite density TP True Positive WHO World Health Organization Declarations Ethical approval and consent to participate The study procedures received approval from the National Health Science Committee (NHSRC), a division of Malawi’s Ministry of Health (MoH) (IRB00003905 – Evaluation of Diagnostic Accuracy of the Next Generation Mobile Malaria Diagnostic Kit (miLab TM )), as well as from the Ethical Review Boards at Kangwon National University (KNUIRB- 2023-05-008). Before taking part in the study, all participants provided informed consent. All experiments were performed in accordance with relevant guidelines and regulations. Consent for Publication Not applicable Availability of data and materials The datasets used and/ or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare (HI22C0820) and the National Research Foundation of Korea (NRF) funded by the Ministry of Education (RS-2023-00240627) (J-H. H.). Author Contributions J.M.L., E.M., and J-H.H. wrote and reviewed the main study proposal and experimental design of the study. J.M.L., E.M., H.J., W-J.L., J.H.S., F.F., W.C., W.S.P., S.J.L., and S.N. performed formal data analysis and revised visualization of data set. F.M., F.L., S.J.L., S.N., E-T.H., and J-H.H. collect clinical isolates, performed field diagnosis and provided laboratory strain. J.M.L., E.M., H.J., W-J.L., J.H.S., F.F., and J-H.H. performed the molecular laboratory analysis. J.M.L., E.M., and J-H.H. wrote the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors are grateful for all the staff and patients associated with the clinics and patients in Malawi. Author details Johnsy Mary Louis 1 , [email protected] Author 1 Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea Ernest Mazigo 1,2 , [email protected] (Ph.D.) -First Author 1 Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea 2 Department of Parasitic Diseases, National Institute for Medical Research, Dar es Salaam, Tanzania Hojong Jun 1,3 , [email protected] (Ph.D.) 1 Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea 3 Department of Epidemiology and Tropical Diseases, Faculty of Public Health, Universitas Diponegoro, Semarang, Indonesia Wang-Jong Lee 1,3 , [email protected] (Ph.D.) 1 Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea 3 Department of Epidemiology and Tropical Diseases, Faculty of Public Health, Universitas Diponegoro, Semarang, Indonesia Jadidan Hada Syahada 1 , [email protected] 1 Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea Fadhila Fitriana 1 , [email protected] 1 Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea Fauzi Muh 3 , [email protected] (Ph.D.) (Lecturer) 3 Department of Epidemiology and Tropical Diseases, Faculty of Public Health, Universitas Diponegoro, Semarang, Indonesia Wanjoo Chun 4 , [email protected] (Ph.D.) (Professor) 4 Department of Pharmacology, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea Won Sun Park 5 , [email protected] (Ph.D.) (Professor) 5 Department of Physiology, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea Se Jin Lee 6 , [email protected] (M.D, Ph.D.) (Professor) 6 Department of Obstetrics and Gynecology, Kangwon National University Hospital, Chuncheon, Republic of Korea Sunghun Na 6 , [email protected] (M.D, Ph.D.) (Professor) 6 Department of Obstetrics and Gynecology, Kangwon National University Hospital, Chuncheon, Republic of Korea Feng Lu 7 , [email protected] (Ph.D.) (Professor) 7 Department of Pathogen Biology and Immunology, School of Medicine, Yangzhou University, Yangzhou, China Eun-Teak Han 1 , [email protected] (Ph.D.) (Professor) 1 Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea Jin-Hee Han 1,3,8* [email protected] (Ph.D.)-Co-responding Authour 1 Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea 3 Department of Epidemiology and Tropical Diseases, Faculty of Public Health, Universitas Diponegoro, Semarang, Indonesia 8 Institute of Medical Sciences, Kangwon National University, Chuncheon, Republic of Korea References Mategula D, Gichuki J, Chipeta MG, Chirombo J, Kalonde PK, Gumbo A, et al. 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Cite Share Download PDF Status: Published Journal Publication published 09 Oct, 2025 Read the published version in Infectious Diseases of Poverty → Version 1 posted Editorial decision: Minor revision 08 Jul, 2025 Reviewers agreed at journal 16 May, 2025 Reviewers invited by journal 13 May, 2025 Editor assigned by journal 08 May, 2025 First submitted to journal 08 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6618930","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":455796620,"identity":"ba9891e9-fe4b-4bc1-b99b-fc691a02df3a","order_by":0,"name":"Johnsy Mary Louis","email":"","orcid":"","institution":"Kangwon National University","correspondingAuthor":false,"prefix":"","firstName":"Johnsy","middleName":"Mary","lastName":"Louis","suffix":""},{"id":455796621,"identity":"313c7993-0578-4040-aed2-dff1f7ee0573","order_by":1,"name":"Ernest Mazigo","email":"","orcid":"","institution":"Kangwon National 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(A) \u003c/strong\u003eThe flowchart illustrates the number of successful diagnoses for each field diagnostic tool and region, with the results shown in the green boxes. The laboratory tests performed using quantitative PCR (qPCR) for all participants are displayed in the yellow boxes. qPCR-positive samples were selected for the \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e gene deletion study and compared with RDT results.\u003cstrong\u003e (B) \u003c/strong\u003eThe map shows the location\u003cstrong\u003e \u003c/strong\u003eof the clinical isolate collection sites, where \u003cem\u003ePlasmodium falciparum\u003c/em\u003e infected participants were enrolled. Mzuzu and Lilongwe in Malawi are indicated by red circles.\u003cstrong\u003e \u003c/strong\u003eThe connection lines in the Venn diagram represent the number of participants successfully diagnosed by each field diagnostic method which included microscopy and RDT. The map of Malawi was generated using QGIS 3.34.1.\u003c/p\u003e","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6618930/v1/378c3e26d08826f8460ac8cd.png"},{"id":82887750,"identity":"7f58edab-0572-43db-88f1-c16be340ab1a","added_by":"auto","created_at":"2025-05-16 11:58:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":153391,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalytical validation of field diagnosis performance compared with laboratory tests.\u003cbr\u003e\n(A)\u003c/strong\u003e Analytical validation of the performance of each field diagnostic tool was assessed by comparing it to quantitative PCR. Standard parameters such as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy including their 95% confidence intervals, are presented. \u003cstrong\u003e(B)\u003c/strong\u003e The Spearman correlation between actual parasitemia under light microscopy (LM) and parasite density determined using qPCR was calculated using cultured \u003cem\u003eP. falciparum\u003c/em\u003e 3D7 strain gDNA. The parasitemia was converted to parasites per microliter (p/μL) to compare between field and laboratory tests. The black line indicates the combined data from both study sites (Lilongwe and Mzuzu), with a total of 1,579 isolates used for comparison, showing a significant positive correlation (\u003cem\u003eρ\u003c/em\u003e = 0.722). \u003cstrong\u003e(C)\u003c/strong\u003e The violin plot represents the distribution of qPCR-based relative parasitemia for LM and RDT positive groups. The three horizontal lines within each violin indicate the interquartile range and median. Significance was assessed by a paired t-test (\u003cem\u003ep \u003c/em\u003e= 0.034). The average and min-to-max range are shown in the violin plot for each field diagnosis compared to relative parasitemia calculated by qPCR. \u003cstrong\u003e(D)\u003c/strong\u003eActual parasitemia detected by LM is compared for each diagnostic tool, showing false negative (FN) or true positive (TP) results. The two stars (**) indicate significant differences between the groups. Statistical comparison was performed using the Wilcoxon signed-rank test. The difference in parasitemia between FN and TP was significant for both methods: RDT (\u003cem\u003ep\u003c/em\u003e = 0.0031, **) and qPCR (\u003cem\u003ep\u003c/em\u003e = 0.0054, **\u003cem\u003e)\u003c/em\u003e. The number of false negatives (FN) and true positives (TP) for each method are indicated in parentheses: RDT (FN = 40, TP = 319) and qPCR (FN = 50, TP = 311).\u003c/p\u003e","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6618930/v1/bbfa433d60a87e182a8feaac.png"},{"id":82887743,"identity":"f9d943bf-1fd1-4d3a-8fd3-b1138c14205c","added_by":"auto","created_at":"2025-05-16 11:58:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":103394,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution and association of parasitemia by LM (parasites/μL) and clinical manifestations. \u003c/strong\u003eEach symptom presentation is indicated by “+” (present) and “-” (absent). Parasitemia measured by LM was compared between clinically recorded isolates from Lilongwe and Mzuzu, revealing statistically significant differences between the two regions (Mann-Whiteny test, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6618930/v1/0b231da0f1b35c8ebfa727ab.png"},{"id":82887749,"identity":"58dbfada-c127-47da-af49-aeb29746d905","added_by":"auto","created_at":"2025-05-16 11:58:21","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":170795,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eValidation of multiplex qPCR assay for \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003epfhrp2\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003epfhrp3\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e gene deletion detection. (A) \u003c/strong\u003eLaboratory \u003cem\u003eP. falciparum \u003c/em\u003estrains 3D7 (wild type, \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e present), Dd2 (\u003cem\u003epfhrp2\u003c/em\u003e deletion), and HB3 (\u003cem\u003epfhrp3\u003c/em\u003e deletion) were amplified under optimal multiplex qPCR conditions. The black horizontal line marks the threshold for \u003cem\u003epfhrp2\u003c/em\u003e analysis and \u003cstrong\u003e(B)\u003c/strong\u003e shows multiplex qPCR for \u003cem\u003epfhrp3\u003c/em\u003e gene. \u003cstrong\u003e(C)\u003c/strong\u003e A Standard curve of \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e gene amplification using 10-fold serially diluted parasites, starting from 210,000 parasites/μL. The assay was able to detect as low as 2.1 parasites/μL with an amplification efficiency of 93.13% for \u003cem\u003epfhrp2\u003c/em\u003e and 92.03% for \u003cem\u003epfhrp3\u003c/em\u003e. The regression slope was -3.498 for \u003cem\u003epfhrp2\u003c/em\u003e and -3.529 for \u003cem\u003epfhrp3 \u003c/em\u003egene amplification. The coefficient of determination (R\u003csup\u003e2\u003c/sup\u003e) for both targets was above 0.99, indicating a strong linear correlation. \u003cstrong\u003e(D) \u003c/strong\u003eA\u003cstrong\u003e \u003c/strong\u003edirect comparison between the ratio of \u003cem\u003epfhrp2/3\u003c/em\u003e genes and \u003cem\u003e18S rRNA\u003c/em\u003e gene quantity is shown. The double negative population in the fourth quadrant is considered to have fewer than 5 parasites/μL for \u003cem\u003epfhrp2/3\u003c/em\u003e genes and fewer than 2.1 parasites/μL for the \u003cem\u003e18S rRNA \u003c/em\u003egene. The yellow box indicates \u003cem\u003e18S rRNA-\u003c/em\u003epositive isolates with undetectable \u003cem\u003epfhrp2\u003c/em\u003e or \u003cem\u003epfhrp3\u003c/em\u003e gene amplification, indicating possible gene deletions.\u003c/p\u003e","description":"","filename":"OnlineFigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6618930/v1/575735cbaad7f5246808a42e.png"},{"id":93419914,"identity":"0065d42d-c08f-4170-bb69-78824bb76247","added_by":"auto","created_at":"2025-10-13 16:08:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2567487,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6618930/v1/362444d5-8070-4b07-9a8a-b89f6a1f3ad7.pdf"}],"financialInterests":"","formattedTitle":"First report of pfhrp2 and pfhrp3 gene deletions compromising HRP2-based malaria rapid diagnostic tests in Malawi","fulltext":[{"header":"Background","content":"\u003cp\u003eMalaria is still considered a significant public health concern (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In 2022, there were an estimated 249\u0026nbsp;million cases globally, 94% (233\u0026nbsp;million) of them occurring in sub-Saharan African countries including Malawi. More than 95% of Malawi population live in malaria endemic areas (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In 2021, Malawi contributed to 1.7% of the global malaria cases, 1.2% of global deaths, and 8% of all malaria cases in Eastern and Southern African countries. \u003cem\u003ePlasmodium falciparum\u003c/em\u003e was responsible for more than 95% of malaria infections and deaths in 2021 in Malawi (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSince 2000, a dramatic decrease in global malaria cases and deaths has been reported in sub-Saharan African countries (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The decrease resulted from the scaling-up of interventions including the use of malaria rapid diagnostic tests (RDTs) for detection of malaria infections, which was recommended by the WHO in the early 1990s. Since its deployment, RDTs have considerably facilitated early malaria diagnosis procedures, especially in rural malaria endemic regions and other areas where good microscopy is not feasible. For instance, of 3.1\u0026nbsp;billion RDTs that were sold between 2010 and 2020, 81% were used in sub-Saharan countries, making it the primary malaria diagnostic technique. However, although the use of RDTs is increasing, the global rise in isolates with \u003cem\u003eP. falciparum histidine-rich proteins\u003c/em\u003e (\u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e) gene deletions is challenging their efficacy (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccurate diagnosis of malaria is a fundamental strategy for its control (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). RDTs detect \u003cem\u003ePlasmodium\u003c/em\u003e specific antigens, primarily histidine-rich protein 2 (HRP2) or parasite-specific lactose dehydrogenase (pLDH) antigen, from a drop of blood in malaria positive patients (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The kits specific for \u003cem\u003eP. falciparum\u003c/em\u003e are designed to capture histidine-rich protein 2 (PfHRP2), which is encoded by the \u003cem\u003epfhrp2\u003c/em\u003e gene located in the sub-telomeric region of chromosome 8 (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The \u003cem\u003epfhrp2\u003c/em\u003e gene is 85\u0026ndash;90% homology in nucleotide sequence-flanking repeats similar to \u003cem\u003epfhrp3\u003c/em\u003e, which causes them to cross-react in RDTs (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). As RDTs detect an inert protein component of \u003cem\u003eP. falciparum\u003c/em\u003e parasites, detection methods using PfHRP2/PfHRP3 are thus limited as proxy measures of parasite density. The sensitivity of RDTs falls sharply when parasite density drops below 100 to 500 parasites/\u0026micro;L (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Moreover, the persistence of PfHRP2/PfHRP3 in the bloodstream for several weeks after parasite clearance has been a matter of concern regarding the accuracy of RDT (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on the WHO guidelines, each country should establish the status and surveillance of gene deletion trends over time (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Re-assessment of the national diagnostic strategy has to be done when more than 5% of \u003cem\u003eP. falciparum\u003c/em\u003e clinical infections are missed by HRP2-based RDTs (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). This study aimed to investigate the prevalence of \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003epfhrp2/3\u003c/em\u003e gene deletions in isolates from Mzuzu and Lilongwe, Malawi. Additionally, it assessed how \u003cem\u003epfhrp2/3\u003c/em\u003e gene deletions and parasite density impact the accuracy, sensitivity, and specificity of RDTs and microscopy. Importantly, this is the first study to report the presence of \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e gene deletions in Malawi. The identification of \u003cem\u003eP. falciparum\u003c/em\u003e parasites lacking these genes, along with their detection patterns using field diagnostic tools, provides valuable evidence of the effectiveness of the current malaria surveillance and diagnostic strategies in the country.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy site, population, and sampling\u003c/h2\u003e \u003cp\u003eSamples were collected from Lilongwe and Mzuzu referral hospitals in Malawi from December 2020 to June 2021. The study targeted individuals of all age groups who were visiting the hospitals for treatments. The two referral hospitals were purposively selected because they serve a large proportion of the population and are in high malaria transmission settings. Approximately 15% of Malawi\u0026rsquo;s population resides in Lilongwe, while Mzuzu is reported to be the fastest-growing city in terms of population. Both regions are reported to have among the highest population at risk of malaria (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). In this study, a total of 1,582 patients blood samples were collected, 396 (25.0%) blood samples from Lilongwe and 1,186 (75.0%) blood samples from Mzuzu hospitals (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The sample size was not statistically predetermined; instead, it was based on the number of eligible participants available during the study period. This convenience sampling approach aimed to collect as many samples as possible to support meaningful molecular and diagnostic analyses.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClinical sample collection and handling\u003c/h3\u003e\n\u003cp\u003eAll procedures were performed by skilled and trained technicians working at the local hospitals. At each selected hospital, participants were consulted and screened for eligibility to participate in the study. After obtaining voluntary informed consent, blood was drawn using the finger-prick method with a sterile lancet and capillary tube. Malaria was diagnosed using a histidine rich protein 2 (HRP2)-based rapid diagnostic test (RDT) as part of the routine procedure in local health facilities (Paracheck-Pf\u0026reg;, Orchid Biomedical Systems, Goa, India). Simultaneously, approximately 250 \u0026micro;L of venous whole blood was collected into K2 EDTA tubes (BD Vacutainer krackeler scientific) and homogeneously mixed by inverting 10 times. If venous blood had already been collected for other clinically necessary tests, any leftover blood was used for the study instead.\u003c/p\u003e \u003cp\u003eImmediately after whole blood collection, two thin Giemsa-stained blood smears were prepared for malaria diagnoses by microscopy. Each slide was examined independently by two skilled microscopists. In cases of discordant results, a third microscopist was involved. All microscopists had received formal training in malaria microscopy, underwent and competency assessments, and participated in routine internal quality control and external quality assurance (EQA) programs to ensure accuracy and reliability. Microscopists were blinded to each other\u0026rsquo;s results reported by the other.\u003c/p\u003e \u003cp\u003e Dried blood spots (DBS) were prepared from the remaining whole blood of each participant. DBS papers were packed separately into plastic bags with silica gels and then shipped to Kangwon National University (KNU) in Republic of Korea, where qPCR was conducted for malaria diagnosis and detection of \u003cem\u003epfhrp2/3\u003c/em\u003e deletions.\u003c/p\u003e \u003cp\u003e \u003cb\u003eP. falciparum in vitro\u003c/b\u003e \u003cb\u003eculture and gDNA extraction for\u003c/b\u003e \u003cb\u003epfhrp2/3\u003c/b\u003e \u003cb\u003econtrol preparation\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo determine the limit of detection (LoD) of qPCR diagnosis targeting the \u003cem\u003e18S rRNA\u003c/em\u003e gene and \u003cem\u003epfhrp2/3\u003c/em\u003e detection based on parasite count, \u003cem\u003eP. falciparum\u003c/em\u003e strains 3D7 (ATCC) (wildtype, west Africa origin), Dd2 (\u003cem\u003epfhrp2\u003c/em\u003e deletion, Indochina origin), and HB3 (\u003cem\u003epfhrp3\u003c/em\u003e deletion, Honduras origin) were cultured using human erythrocytes at 2% \u003cem\u003ehematocrit\u003c/em\u003e in RPMI-1640 medium (Invitrogen, CA). The culture medium was supplemented with 2.3 g/L sodium bicarbonate, 0.05 g/L hypoxanthine, 10% Albumax I solution, and 10 mg/mL gentamicin. Cultures were maintained in a gas mixture of 90% N\u003csub\u003e2\u003c/sub\u003e, 5% O\u003csub\u003e2\u003c/sub\u003e, and 5% CO\u003csub\u003e2\u003c/sub\u003e and incubated at 37\u0026deg;C. Thin blood films were prepared following standard protocols, and parasitemia was measured by Giemsa staining under a microscope at 100X magnification. Once ring-stage of parasites reached 5% after synchronization, genomic DNA (gDNA) was extracted from the cultured samples (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). For the clinical isolates gDNA extraction, one spot (10 mm in diameter) was punched from each dried blood spot (DBS) paper, cut into several pieces, and transferred into individual sterile 1.5 mL microcentrifuge tubes. DNA was extracted using the QIAamp DNA Mini Kits (Qiagen, Hilden, Germany), according to manufacturer\u0026rsquo;s instructions with 50 \u0026micro;L of final elution.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMolecular diagnosis of\u003c/b\u003e \u003cb\u003eP. falciparum\u003c/b\u003e \u003cb\u003einfections by quantitative PCR (qPCR)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMolecular diagnosis targeting the \u003cem\u003e18S rRNA\u003c/em\u003e gene of \u003cem\u003eP. falciparum\u003c/em\u003e was performed using qPCR with previously published primers (Forward primer: ATTGCTTTTGAGAGGTTTTGTTACTTT, Reverse primer: GCTGTAGTATTCAAACACAATGAACTCAA) and a probe (FAM-CATAACAGACGGGTAGTCAT) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The qPCR assay components and cyclic conditions were slightly modified to optimize performance. Briefly, each qPCR reactions were conducted in a total volume of 20 \u0026micro;L, including 10 \u0026micro;L of 2X Prime Time Gene expression Master Mix with ROX reference dye (Integrated DNA technologies, IA), 1 \u0026micro;L of template DNA (gDNA), 0.5 \u0026micro;M of each of the primers, and 0.25 \u0026micro;M of each TaqMan Probes. Reactions were run on an AriaMx Real-Time PCR system (Agilent Technologies, CA) under the following cycling conditions: an initial hot-start polymerase activation at 95℃ for 10 minutes, followed by 45 cycles of denaturation at 95℃ for 15 seconds and annealing at 65℃ for 65 seconds. A standard curve for the qPCR diagnosis was prepared using \u003cem\u003eP. falciparum\u003c/em\u003e 3D7 strain parasites cultured \u003cem\u003ein vitro\u003c/em\u003e at 5% ring-stage. All qPCR reactions were performed in duplicate, and for each test, a tenfold serial dilution of the standard curve was included.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCharacterization of\u003c/b\u003e \u003cb\u003epfhrp2\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003epfhrp3\u003c/b\u003e \u003cb\u003edeletions in\u003c/b\u003e \u003cb\u003eP. falciparum\u003c/b\u003e \u003cb\u003epositive samples\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA multiplex qPCR was performed to identify \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e deletions. The multiplex reactions were run together with the cultured \u003cem\u003eP. falciparum\u003c/em\u003e 3D7 as standard controls. Published primer sequences for \u003cem\u003epfhrp2\u003c/em\u003e (Forward: GTATTATCCGCTGCCGTTTTTGCC; Reverse: CATCTACATGTGCTTGATTTTCGT) and \u003cem\u003epfhrp3\u003c/em\u003e (Forward: ATATTATCCGCTGCCGTTTTTGCT; Reverse: CCTGCATGTGCTTGACTTTCGT) and probes (PfHRP2: FAM-TTCCGCATTTAATAATAACTTGTGTAGC, and PfHRP3: HEX-CTCCGAATTTAACAATAACTTGTTTAGC) were adapted for the multiplex qPCR platform (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). These primers were tested with varying gDNA concentrations extracted from \u003cem\u003ePf3D7\u003c/em\u003e, \u003cem\u003ePfDd2\u003c/em\u003e and \u003cem\u003ePfHB3\u003c/em\u003e strains, corresponding to parasite count in tenfold serial dilution from 210,000 parasites/\u0026micro;L to 0.21 parasites/\u0026micro;L. Reactions were conducted in a total volume of 10 \u0026micro;L, including 5 \u0026micro;L of 2X Prime Time Gene expression Master Mix with ROX reference dye (Integrated DNA technologies), 1 \u0026micro;L of template DNA (gDNA), 0.5 \u0026micro;M of each of the primers, and 0.25 \u0026micro;M of each TaqMan Probes. Reactions were conducted on an AriaMx Real-Time PCR system (Agilent Technologies) with the following cycling conditions: hot-start polymerase activation at 95℃ for 5 minutes, followed by 45 cycles of denaturation at 95℃ for 15 seconds and annealing at 60℃ for 35 seconds.\u003c/p\u003e \u003cp\u003eTo establish molecular surveillance criteria for the \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e genes, a cutoff of relative parasitemia based on the \u003cem\u003e18S rRNA\u003c/em\u003e gene of under 5 parasites/\u0026micro;L, as described elsewhere, was implemented (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Hence, in this analysis, samples with less than 5 parasites/\u0026micro;L in \u003cem\u003e18S rRNA\u003c/em\u003e gene detection were considered analytically negative for \u003cem\u003eP. falciparum\u003c/em\u003e infection and were excluded from \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e gene detection.\u003c/p\u003e\n\u003ch3\u003eCase definitions\u003c/h3\u003e\n\u003cp\u003eSymptomatic malaria is defined by the presence of malaria-related symptoms (vomiting, headache, and body temperature\u0026thinsp;\u0026gt;\u0026thinsp;37\u0026deg;C) within the past 2 days and at the time of examination, along with detectable malaria parasites in blood. Clinical manifestations data were collected using a structured questionnaire administered to all participants, which included questions about the presence of these symptoms within the specified timeframe. Asymptomatic malaria is defined as the presence of detectable parasites in the blood without any malaria-related symptoms during the past week or at the time of the survey, and with no history of antimalaria drug use within the past week.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe qPCR data were visualized by Agilent AriaMx 1.8 software (Agilent Technologies) and statistically analyzed with GraphPad Prism 8 software. A log transformation of parasitemia was performed to compare detection by microscopy and qPCR. Correlation analysis of parasitemia was conducted using spearman correlation (\u003cem\u003eρ\u003c/em\u003e) and linear regression via Sigma Plot software v12. Actual parasitemia measured by microscopy and relative parasitemia from 18S rRNA qPCR were summarized as means and correlated to assess the agreement between log-transformed parasite values. An unpaired \u003cem\u003et\u003c/em\u003e-test was used to compare the two diagnostic methods, while differences in asymptomatic and symptomatic cases between the two regions were analyzed using the Mann\u0026ndash;Whitney test. The Wilcoxon signed-rank test was used to compare paired numeric values. Statistical analysis of clinical specimen diagnosis was conducted with MEDCALC statistical, available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.medcalc.org/calc/diagnostic_test.php\u003c/span\u003e\u003cspan address=\"https://www.medcalc.org/calc/diagnostic_test.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Data were organized into double-entry tables to calculate sensitivity, specificity, and positive and negative predictive values for each test at 95% confidence intervals.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthics statement\u003c/h3\u003e\n\u003cp\u003e The study procedures were approved by the National Health Science Committee (NHSRC), a division of Malawi\u0026rsquo;s Ministry of Health (MoH) (IRB00003905 \u0026ndash; Evaluation of Diagnostic Accuracy of the Next Generation Mobile Malaria Diagnostic Kit (miLab\u0026trade;)), as well as by the Ethical Review Board at Kangwon National University (KWNUIRB-2023-05-008). Before participating in the study, all participants provided informed consent. All experiments were conducted in accordance with relevant guidelines and regulations.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003ePrevalence of\u003c/b\u003e \u003cb\u003eP. falciparum\u003c/b\u003e \u003cb\u003ein Lilongwe and Mzuzu, Malawi\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 1,582 participants were enrolled in the study, including 396 (25.0%) from Lilongwe and 1,186 (75.0%) from Mzuzu (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Malaria-related symptoms were recorded for all participants at the time of sample collection. Of the collected samples, 1,528 (96.6%) and 1,563 (98.8%) were successfully tested using light microscopy (LM) and malaria rapid diagnostic tests (RDT), respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). A total of 1,514 (95.7%) samples were tested by both diagnostic methods. Molecular diagnosis for \u003cem\u003eP. falciparum\u003c/em\u003e was performed on all 1,582 (100%) isolates using quantitative PCR (qPCR) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eOverall, malaria positive rate based on field-based diagnostic tools was significantly higher in Lilongwe (30.6% by LM and 53.4% by RDT) compared to Mzuzu (21.0% by LM and 21.2% by RDT). Across both regions, the overall prevalence was 23.5% by LM and 29.2% by RDT (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In contrast, the laboratory-based qPCR method detected a higher overall prevalence of 31.5% (499/1,582 samples) compared to the field diagnostic tools (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eP. falciparum\u003c/em\u003e prevalence based on each diagnostic tools in Lilongwe and Mzuzu, Malawi\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDiagnostic tool\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eLilongwe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMzuzu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo. of\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eNo. of\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)*\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eNo. of Positive\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eNo. of\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)*\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eNo. of Positive\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eNo. of\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)*\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroscopy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e121\u003c/p\u003e \u003cp\u003e(30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e274\u003c/p\u003e \u003cp\u003e(69.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e395\u003c/p\u003e \u003cp\u003e(99.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e238\u003c/p\u003e \u003cp\u003e(21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e895\u003c/p\u003e \u003cp\u003e(79.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1,133\u003c/p\u003e \u003cp\u003e(95.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e359\u003c/p\u003e \u003cp\u003e(23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1,169\u003c/p\u003e \u003cp\u003e(76.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1,528\u003c/p\u003e \u003cp\u003e(96.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRDT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e206\u003c/p\u003e \u003cp\u003e(53.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e180\u003c/p\u003e \u003cp\u003e(46.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e386\u003c/p\u003e \u003cp\u003e(97.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e250\u003c/p\u003e \u003cp\u003e(21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e927\u003c/p\u003e \u003cp\u003e(78.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1,177\u003c/p\u003e \u003cp\u003e(99.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e456\u003c/p\u003e \u003cp\u003e(29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1,107\u003c/p\u003e \u003cp\u003e(70.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1,563\u003c/p\u003e \u003cp\u003e(98.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eqPCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e214\u003c/p\u003e \u003cp\u003e(54.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e182\u003c/p\u003e \u003cp\u003e(46.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e396\u003c/p\u003e \u003cp\u003e(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e283\u003c/p\u003e \u003cp\u003e(23.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e903\u003c/p\u003e \u003cp\u003e(76.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1,186\u003c/p\u003e \u003cp\u003e(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e497\u003c/p\u003e \u003cp\u003e(31.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1,085\u003c/p\u003e \u003cp\u003e(68.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1,582\u003c/p\u003e \u003cp\u003e(100.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e* Number of isolates (%) accessible by each diagnostic tool among the total participants.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eComparison of field diagnostic performance and the effect of parasite density\u003c/h3\u003e\n\u003cp\u003eIn reference to qPCR, RDT showed higher sensitivity of 78.5% (95% CI: 74.6%-82.1%) but lower specificity at 93.6% (92.0%-95.0%) when compared to light microscopy (LM), which had a sensitivity of 64.8% (95% CI: 60.3%-69.1%) and specificity of 95.4% (95% CI: 94.0%-96.6%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The positive predictive value (PPV), which is the probability that the disease is present when the test is positive, was higher for microscopy (LM) at 86.63% (95% CI: 82.98\u0026ndash;89.59%), while the negative predictive value (NPV), which is the probability that the disease is not present when the test is negative, was higher for RDT at 90.4% (95% CI: 88.9\u0026ndash;91.8%). Diagnostic accuracy in this study was defined as the proportional of true positive and true negative among all individuals tested and was higher for RDT (88.8%, 95% CI: 87.1%-90.3%) than for LM (85.8%, 95% CI: 84.0%-87.5%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eUnder LM detection, parasitemia was significantly lower in Mzuzu (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 46,805\u0026thinsp;\u0026plusmn;\u0026thinsp;113,152 parasites/\u0026micro;L) than in Lilongwe (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 57,931\u0026thinsp;\u0026plusmn;\u0026thinsp;85,397 parasites/\u0026micro;L) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A strong positive correlation was observed between parasitemia quantified by LM in the field and relative parasite density estimated by 18S rRNA based qPCR in the laboratory (\u003cem\u003eρ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.722, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating a consistent association between the two methods (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). However, regression analysis suggested that qPCR may systematically yield lower parasite density estimates compared to LM.\u003c/p\u003e \u003cp\u003eThe parasitemia levels detected by field diagnostic methods differed significantly, with LM showing a median of 1,488 parasites/\u0026micro;L (IQR: 5,877.9) and RDT showing a median of 882.4 parasites/\u0026micro;L (IQR: 4,108.2; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0344) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Based on parasite density, the performance of both LM and RDT was evaluated for infections above 2.4 parasites/\u0026micro;L, which corresponds to the detection limit of the qPCR method used as the reference standard in the study regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eWhen Comparing LM to RDT and qPCR, the differences in parasitemia between false negative (FN) and true positive (TP) results showed varying average parasitemia levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). In this study, false negative results refer to samples that tested negative by both RDT and qPCR but were positive by LM, while true positive results are those that tested positive by both RDT and qPCR. False negative cases had averages of 9,964.5 parasites/\u0026micro;L in RDT, and 8961.4 parasites/\u0026micro;L in qPCR, while true positive cases exhibited averages of 55,431.0 parasites/\u0026micro;L in RDT, and 56,918.6 parasites/\u0026micro;L in qPCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). These differences in parasitemia levels between FN and TP detected by RDT and qPCR, when compared with LM, were statistically significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). These results indicate that the sensitivity of RDT and qPCR is strongly influenced by parasite density.\u003c/p\u003e\n\u003ch3\u003eDistribution of parasitemia levels and associated symptoms in malaria positive participants\u003c/h3\u003e\n\u003cp\u003eParticipants were recruited based on their availability at local hospitals, rather than clinical suspicion of malaria. To assess differences in clinical manifestation patterns across the study regions, symptoms related to malaria, such as vomiting, headache, and body temperature (\u0026gt;\u0026thinsp;37\u0026deg;C) were recorded. In Lilongwe, 114 out of 121 (94.2%) \u003cem\u003eP. falciparum\u003c/em\u003e-positive participants identified by LM did not have any specific symptoms related to malaria, while the remaining 7 (5.8%) were symptomatic (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In contrast, in Mzuzu, 231 out of 238 (97.1%) LM positive participants were symptomatic, with either single or mixed clinical manifestation, while 8 participants (3.4%) were asymptomatic (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the asymptomatic individuals from both Lilongwe and Mzuzu, LM positive isolates did not show a statistically significant difference (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.43). The overall average parasitemia under LM was significantly different between clinically recorded isolates in Lilongwe (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;121, 57,931\u0026thinsp;\u0026plusmn;\u0026thinsp;85,397 parasites/\u0026micro;L) and Mzuzu (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;239, 45,262\u0026thinsp;\u0026plusmn;\u0026thinsp;111,561 parasites/\u0026micro;L) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). These results clearly indicate that the degree of symptom onset differed significantly between the two regions, while parasitemia levels did not differ.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eMolecular validation of\u003c/b\u003e \u003cb\u003epfhrp2\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003epfhrp3\u003c/b\u003e \u003cb\u003egene deletions using qPCR in field isolates\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo detect and confirm molecular surveillance of \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e gene deletions, a multiplex qPCR-based assay was performed (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Genomic DNA from three different \u003cem\u003eP. falciparum in vitro\u003c/em\u003e cultured strains (3D7, Dd2, and HB3) were used to optimize and validate the assay for \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e gene deletions status. The \u003cem\u003eP. falciparum\u003c/em\u003e 3D7 strain exhibits both the \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e genes, while the Dd2 strain has a single gene deletion of the \u003cem\u003epfhrp2\u003c/em\u003e, and the HB3 strain has a deletion of the \u003cem\u003epfhrp3\u003c/em\u003e gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). To establish molecular surveillance criteria for detecting deletion of \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e genes in clinical isolates, a cutoff of relative parasitemia below 5 parasites/\u0026micro;L based on the \u003cem\u003e18S rRNA\u003c/em\u003e gene was employed as described elsewhere (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Relative parasitemia in \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e deleted isolates was estimated by comparing the Cq values of these target genes to those of a reference gene (\u003cem\u003eP.falciparum\u003c/em\u003e 3D7 strain). This relative quantification approach was used to determine the presence or absence of \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e gene targets based on their amplification profiles.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe analytical limit of detection (LoD) for the multiplex qPCR targeting both \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e genes using the \u003cem\u003eP. falciparum\u003c/em\u003e 3D7 strain was estimated to be 2.1 parasites/\u0026micro;L, with qPCR efficiencies of 93.1% and 92.3%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). The LoD for the \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e genes was approximately 10 times higher than that of the \u003cem\u003e18S rRNA\u003c/em\u003e gene (0.21 parasites/\u0026micro;L) when detected by qPCR. A significant positive correlation was observed between the \u003cem\u003e18S rRNA\u003c/em\u003e gene and \u003cem\u003epfhrp2\u003c/em\u003e (\u003cem\u003eρ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.898), and between and \u003cem\u003e18S rRNA\u003c/em\u003e with \u003cem\u003epfhrp3\u003c/em\u003e (\u003cem\u003eρ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.900) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). In this analysis, samples with less than 5 parasites/\u0026micro;L based on \u003cem\u003e18S rRNA\u003c/em\u003e gene detection were considered analytically negative and excluded from the further gene deletion analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003cb\u003eDeletions of\u003c/b\u003e \u003cb\u003epfhrp2 and pfhrp3\u003c/b\u003e \u003cb\u003egenes in isolates from Mzuzu and Lilongwe, Malawi\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMultiplex qPCR assays were performed on 488 clinical isolates confirmed as \u003cem\u003eP. falciparum\u003c/em\u003e positive by qPCR to assess \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e gene deletion. Based on the inclusion criteria for gene deletions analysis, 160 isolates from Lilongwe and 231 isolates from Mzuzu were included in the final dataset. In Lilongwe, \u003cem\u003epfhrp2\u003c/em\u003e single gene deletions were detected in 7 isolates (4.4%) with a relative parasite density of 1,460\u0026thinsp;\u0026plusmn;\u0026thinsp;3,705 parasites/\u0026micro;L, calculated from the \u003cem\u003e18S rRNA\u003c/em\u003e gene (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In Mzuzu, 2 isolates (0.9%) showed \u003cem\u003epfhrp2\u003c/em\u003e single gene deletions, with a relative parasite density of 11.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70 parasites/\u0026micro;L, which was marginally lower than in Lilongwe. Single \u003cem\u003epfhrp3\u003c/em\u003e gene deletions were detected in 11 isolates (6.9%) in Lilongwe and 11 isolates (4.8%) in Mzuzu. The parasite density was 615.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1,785 parasites/\u0026micro;L in Lilongwe and 168.5\u0026thinsp;\u0026plusmn;\u0026thinsp;433.4 parasites/\u0026micro;L in Mzuzu (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Dual gene deletions, which lead to false negatives in RDT, were detected in 24 isolates (15.0%) in Lilongwe and 24 isolates (10.4%) in Mzuzu, with parasite densities of 26.36\u0026thinsp;\u0026plusmn;\u0026thinsp;37.52 parasites/\u0026micro;L and 167.2\u0026thinsp;\u0026plusmn;\u0026thinsp;570.5 parasites/\u0026micro;L, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Overall, deletions in either the \u003cem\u003epfhrp2\u003c/em\u003e, \u003cem\u003epfhrp3\u003c/em\u003e or both genes were confirmed in 79 isolates (20.2%) in Malawi (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e gene deletion status in Lilongwe and Mzuzu, Malawi.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eΔpfhrp2\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cem\u003eΔpfhrp3\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eΔpfhrp2\u003c/em\u003e and \u003cem\u003e3\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eNo deletion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRPD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eRPD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eRPD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eRPD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLilongwe\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(4.4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1,460\u0026thinsp;\u0026plusmn;\u0026thinsp;3,705\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(6.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e615.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1,785\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e24\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(15.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e26.36\u0026thinsp;\u0026plusmn;\u0026thinsp;37.52\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e118\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(73.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e17,291\u0026thinsp;\u0026plusmn;\u0026thinsp;38,647\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e160\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMzuzu\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(0.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e11.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(4.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e168.5\u0026thinsp;\u0026plusmn;\u0026thinsp;433.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e24\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(10.4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e167.2\u0026thinsp;\u0026plusmn;\u0026thinsp;570.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e194\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(84.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e3,408\u0026thinsp;\u0026plusmn;\u0026thinsp;7,039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e231\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(2.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e22\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(5.6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e48\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(12.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e312\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(79.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e391\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e*RPD: relative parasite density (parasites/\u0026micro;L, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;S.D.)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study was conducted to determine the prevalence of \u003cem\u003eP. falciparum\u003c/em\u003e in Malawi and the contribution of \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e gene deletion to the effectiveness of malaria diagnostic tools. As the Global Technical Strategy on Malaria 2016\u0026ndash;2030 aims for a malaria-free world by 2030, surveillance of \u003cem\u003epfhrp2/3\u003c/em\u003e deletions is essential for monitoring progress towards this goal (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). As malaria transmission declines in endemic countries, the proportion of low-density infections among both symptomatic and asymptomatic individuals are likely to increase, which may reduce the utility of light microscopy (LM) and malaria rapid diagnostic tests (RDTs). Both methods have been shown to underestimate malaria prevalence in such cases.\u003c/p\u003e \u003cp\u003eIn Malawi, as in many malaria-endemic countries, LM and RDTs remain the primary tools for malaria diagnosis. Therefore, it is essential to evaluate the effectiveness of these diagnostic tools (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Molecular techniques, particularly PCR-based methods, are known for their higher sensitivity in malaria detection (\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Our findings indicate that while both LM and RDTs are highly specific, LM generally has a lower detection rate compared to RDTs (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). This is due to several factors that limit LM efficiency, including reliance on reader expertise, slide preparation quality, and its detection threshold. Although HRP2/3-based RDTs offer higher sensitivity, they can produce false-positive results due to the prolonged persistence of HRP2/3 antigens following parasite clearance (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). In this study, when qPCR used as a reference standard, RDT showed a higher sensitivity (78.50%) making them more effective than LM in detecting malaria in the studied regions. Conversely, LM showed higher specificity (95.42%) compared to RDTs. This aligns with a study from Nigeria (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), suggesting that RDTs may detect low-density infections or lingering HRP2/3 antigens post-infection, which LM could miss (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). So far, comparative analysis of LM and RDT provided the rate of false positives and true positives both of which have implications for malaria control and intervention in Malawi.\u003c/p\u003e \u003cp\u003eIn this study, we found that the prevalence rate of asymptomatic malaria was higher in Lilongwe (28.9%) than Mzuzu district (0.8%). This finding was comparable to a study conducted from December 2019 to April 2020 on asymptomatic malaria in blood donors from the central zone of Malawi, which reported 18.5% asymptomatic malaria cases in Lilongwe and 8.6% in Mzuzu from northern zone (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Other studies in Malawi have reported asymptomatic malaria prevalence rates of 42% among school age children, and 14.1% in younger children (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Similar trends have been observed in countries such as Ethiopia (Pawe, 14.5%) (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), Nigeria (77.6%) (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), Cameroon (Douala, 28.9%) (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), and Tanzania (Bagamoyo district and other regions, 57.5%) (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). These similarities are likely due to high transmission and repeated exposure, which promote the development of immunity and asymptomatic infection (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Differences in asymptomatic malaria prevalence rates can also be attributed to differences in geographical locations, study design, housing quality, quality of houses, nature of population, sample size, study period, vector control methods, and malaria transmission rates (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). In this study, parasite densities did not differ significantly between symptomatic and asymptomatic individuals, indicating that silent carriers may contribute substantially to malaria transmission. Thus, we recommend critical surveillance of both symptomatic and asymptomatic malaria in Malawi, along with an evaluation of the detection limits of primary diagnostic tools used in the region.\u003c/p\u003e \u003cp\u003eThe recent emergence of parasites lacking \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e genes poses a threat to malaria diagnosis and control programmes (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). The WHO recommends reconsidering the use of HRP2-based diagnostics when more than 5% of clinical \u003cem\u003eP. falciparum\u003c/em\u003e infections produce false-negative RDT results due to \u003cem\u003epfhrp2/3\u003c/em\u003e gene deletions (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Although \u003cem\u003epfhrp2/3\u003c/em\u003e gene deletions had not previously been reported in Malawi, our study detected \u003cem\u003epfhrp2\u003c/em\u003e deletions in 2 (0.9%) samples from Mzuzu and 7 (4.4%) samples from Lilongwe. These single gene deletions did not lead to false-negative RDT results, consistent with findings from previous studies from Tanzania and Yemen (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). This anomaly could be the consequence of a false-positive RDT result due to cross-reactivity with circulating proteins such as rheumatoid factor in the blood stream (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e), or it could be the result of a prior infection with samples that tested positive for \u003cem\u003epfhrp2\u003c/em\u003e (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Additionally, we observed single \u003cem\u003epfhrp3\u003c/em\u003e deletions in 4.8% of samples from Mzuzu and 6.9% from Lilongwe. These data further reveal a higher proportion of \u003cem\u003epfhrp3\u003c/em\u003e deletions compared to \u003cem\u003epfhrp2\u003c/em\u003e. This finding is significant, as \u003cem\u003epfhrp3\u003c/em\u003e deletions are believed to occur more prevalent during low transmission seasons, when polyclonal infections are less likely. Similar observations have been identified in Central and Southern America, where malaria transmission is low, with up to 70% of tested samples showing deletions in the \u003cem\u003epfhrp3\u003c/em\u003e region (\u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Dual deletions 48 samples (12.3%) were not detected by RDTs, indicating false-negative results and raising significant concerns for malaria diagnosis in the region. These deletions were observed in both symptomatic and asymptomatic population, across both low and high parasitemia. Since RDTs are the primary diagnostic tool in Malawi, false negatives due to gene deletions could lead to missed diagnoses, undermining malaria control efforts. Vigilant monitoring of \u003cem\u003epfhrp2/3\u003c/em\u003e deletions is therefore critical to avoid undetected infections that could compromise malaria eradication goals. Similar effects of dual deletions haven been observed in other African regions (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study has several important limitations. The samples used in this study were collected between 2020 and 2021; therefore, the study design did not follow the WHO protocol for assessing \u003cem\u003epfhrp2\u003c/em\u003e deletions (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). As a result, our prevalence estimates may be over or underestimated. Moreover, a low parasite density in asymptomatic cases may not be suitable for detection of \u003cem\u003epfhrp2/3\u003c/em\u003e deletions, and for this reason the WHO recommends evaluating deletions in symptomatic patients for more accurate data (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). However, our use of a multiplex qPCR assay demonstrated a practical approach for detecting \u003cem\u003epfhrp2/3\u003c/em\u003e deletions even at low parasite densities (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). Finally, as only two sites were involved in this study, the findings may not be representative of the entire country, emphasizing the need for nationwide surveillance.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study provides evidence of \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e gene deletions in \u003cem\u003eP. falciparum\u003c/em\u003e isolates from Malawi, highlighting the urgent need for surveillance to assess their prevalence and spread across the country. The high proportion of \u003cem\u003epfhrp3\u003c/em\u003e deletions requires further investigation into the factors influencing these deletions during the transmission season. Based on these findings, we recommend screening for \u003cem\u003epfhrp2/3\u003c/em\u003e deletions even in RDT-positive samples, considering the potential for cross-reactivity and false positives caused by lingering \u003cem\u003epfhrp2/3\u003c/em\u003e antigens after treatment.\u003c/p\u003e \u003cp\u003eOur comparative analysis showed that, although RDT remain widely used, their diagnostic sensitivity is compromised in areas with a high prevalence of gene deletions. In contrast, while light microscopy offered greater specificity, it lacked the sensitivity of qPCR, which emerged as the most reliable and accurate method for detecting \u003cem\u003eP. falciparum\u003c/em\u003e infections. Overall, this study highlights the critical need to develop alternative diagnostics targets to address the growing challenge posed by \u003cem\u003epfhrp2/3\u003c/em\u003e deletions in malaria-endemic regions.\u003c/p\u003e"},{"header":"Abbreviations","content":" \u003cp\u003eDBS Dried Blood Sample\u003c/p\u003e \u003cp\u003eEQA External Quality Assurance\u003c/p\u003e \u003cp\u003eFN False Negative\u003c/p\u003e \u003cp\u003eIQR Interquartile Range\u003c/p\u003e \u003cp\u003eLDH Lactose Dehydrogenase\u003c/p\u003e \u003cp\u003eLM Light Microscopy\u003c/p\u003e \u003cp\u003eLOD Limit of Detection\u003c/p\u003e \u003cp\u003eRDTs malaria rapid diagnostic tests\u003c/p\u003e \u003cp\u003eNPV Negative Predictive Value\u003c/p\u003e \u003cp\u003epfhrp2 \u003cem\u003ePlasmodium falciparum\u003c/em\u003e histidine rich protein 2\u003c/p\u003e \u003cp\u003epfhrp3 \u003cem\u003ePlasmodium falciparum\u003c/em\u003e histidine rich protein 3\u003c/p\u003e \u003cp\u003ePPV Positive Predictive Value\u003c/p\u003e \u003cp\u003eqPCR quantitative Polymerase Chain Reaction\u003c/p\u003e \u003cp\u003eRPD relative parasite density\u003c/p\u003e \u003cp\u003eTP True Positive\u003c/p\u003e \u003cp\u003eWHO World Health Organization\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study procedures received approval from the National Health Science Committee (NHSRC), a division of Malawi\u0026rsquo;s Ministry of Health (MoH) (IRB00003905 \u0026ndash; Evaluation of Diagnostic Accuracy of the Next Generation Mobile Malaria Diagnostic Kit (miLab\u003csup\u003eTM\u003c/sup\u003e)), as well as from the Ethical Review Boards at Kangwon National University (KNUIRB- 2023-05-008). Before taking part in the study, all participants provided informed consent. All experiments were performed in accordance with relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/ or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Korea Health Technology R\u0026amp;D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health \u0026amp; Welfare (HI22C0820) and the National Research Foundation of Korea (NRF) funded by the Ministry of Education (RS-2023-00240627) (J-H. H.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.M.L., E.M., and J-H.H. wrote and reviewed the main study proposal and experimental design of the study. J.M.L., E.M., H.J., W-J.L., J.H.S., F.F., W.C., W.S.P., S.J.L., and S.N. performed formal data analysis and revised visualization of data set. F.M., F.L., S.J.L., S.N., E-T.H., and J-H.H. collect clinical isolates, performed field diagnosis and provided laboratory strain. J.M.L., E.M., H.J., W-J.L., J.H.S., F.F., and J-H.H. performed the molecular laboratory analysis. J.M.L., E.M., and J-H.H. wrote the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful for all the staff and patients associated with the clinics and patients in Malawi.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJohnsy Mary Louis\u003csup\u003e1\u003c/sup\u003e, [email protected] Author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eErnest Mazigo\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e1,2\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e, [email protected] (Ph.D.)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;-First Author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Department of Parasitic Diseases, National Institute for Medical Research, Dar es Salaam, Tanzania\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHojong Jun\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e1,3\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e, [email protected] (Ph.D.)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eDepartment of Epidemiology and Tropical Diseases, Faculty of Public Health, Universitas Diponegoro, Semarang, Indonesia\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWang-Jong Lee\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e1,3\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e, [email protected]\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(Ph.D.)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eDepartment of Epidemiology and Tropical Diseases, Faculty of Public Health, Universitas Diponegoro, Semarang, Indonesia\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJadidan Hada Syahada\u003csup\u003e1\u003c/sup\u003e, [email protected]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFadhila Fitriana\u003csup\u003e1\u003c/sup\u003e, [email protected]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFauzi Muh\u003csup\u003e3\u003c/sup\u003e, [email protected] (Ph.D.) (Lecturer)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eDepartment of Epidemiology and Tropical Diseases, Faculty of Public Health, Universitas Diponegoro, Semarang, Indonesia\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWanjoo Chun\u003csup\u003e4\u003c/sup\u003e, [email protected]\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(Ph.D.) (Professor)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u0026nbsp;\u003c/sup\u003eDepartment of Pharmacology, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWon Sun Park\u003csup\u003e5\u003c/sup\u003e, [email protected]\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(Ph.D.) (Professor)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e5\u003c/sup\u003e Department of Physiology, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSe Jin Lee\u003csup\u003e6\u003c/sup\u003e, [email protected]\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(M.D, Ph.D.) (Professor)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e6\u003c/sup\u003e Department of Obstetrics and Gynecology, Kangwon National University Hospital, Chuncheon, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSunghun Na\u003csup\u003e6\u003c/sup\u003e, [email protected]\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(M.D, Ph.D.) (Professor)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e6\u003c/sup\u003e Department of Obstetrics and Gynecology, Kangwon National University Hospital, Chuncheon, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFeng Lu\u003csup\u003e7\u003c/sup\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\[email protected]\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(Ph.D.)\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(Professor)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e7\u003c/sup\u003e Department of Pathogen Biology and Immunology, School of Medicine, Yangzhou University, Yangzhou, China\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEun-Teak Han\u003csup\u003e1\u003c/sup\u003e, [email protected]\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(Ph.D.) (Professor)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJin-Hee Han\u003csup\u003e1,3,8*\u0026nbsp;\u003c/sup\[email protected]\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(Ph.D.)-Co-responding Authour\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eDepartment of Epidemiology and Tropical Diseases, Faculty of Public Health, Universitas Diponegoro, Semarang, Indonesia\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e8\u003c/sup\u003e Institute of Medical Sciences, Kangwon National University, Chuncheon, Republic of Korea\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMategula D, Gichuki J, Chipeta MG, Chirombo J, Kalonde PK, Gumbo A, et al. 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False-negative RDT results and implications of new reports of P. falciparum histidine-rich protein 2/3 gene deletions2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrignard L, Nolder D, Sepulveda N, Berhane A, Mihreteab S, Kaaya R, et al. A novel multiplex qPCR assay for detection of Plasmodium falciparum with histidine-rich protein 2 and 3 (pfhrp2 and pfhrp3) deletions in polyclonal infections. EBioMedicine. 2020;55:102757.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"infectious-diseases-of-poverty","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"idop","sideBox":"Learn more about [Infectious Diseases of Poverty](http://idpjournal.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/idop/default.aspx","title":"Infectious Diseases of Poverty","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Plasmodium falciparum, pfhrp2, pfhrp3, gene deletion, diagnostic accuracy, rapid diagnostic test","lastPublishedDoi":"10.21203/rs.3.rs-6618930/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6618930/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHRP2-based rapid diagnostic tests (RDTs) are widely used for malaria diagnosis in Malawi, but their accuracy may be compromised by \u003cem\u003ePlasmodium falciparum\u003c/em\u003e parasites lacking the \u003cem\u003epfhrp2\u003c/em\u003e and \u003cem\u003epfhrp3\u003c/em\u003e genes. While such deletions have been reported in other malaria-endemic countries, their presence and diagnostic impact in Malawi remain unknown.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted between December 2020 and June 2021, enrolling 1,582 participants from referral hospitals in Mzuzu (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1,186) and Lilongwe (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;396). Malaria diagnosis was performed using RDTs, microscopy, and qPCR. A total of 391 \u003cem\u003eP. falciparum\u003c/em\u003e positive samples were analyzed for \u003cem\u003epfhrp2/pfhr3\u003c/em\u003e gene deletions using multiplex qPCR.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eMalaria prevalence was higher in Lilongwe (45.2%) than in Mzuzu (22.9%). Infections in Lilongwe were predominantly asymptomatic (94.2%), whereas Mzuzu had mostly symptomatic cases (97.1%). RDTs demonstrated higher sensitivity (78.5%) than microscopy (64.8%), but slightly lower specificity, with 93.6% for RDT compared to 95.4% for microscopy. Dual \u003cem\u003epfhrp2/3\u003c/em\u003e gene deletions were found in 24 (15.0%) isolates from Lilongwe and 24 (10.4%) from Mzuzu. All dual-deleted samples were false negative by RDT but were positive by microscopy and qPCR.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study is the first to report \u003cem\u003epfhrp2/3\u003c/em\u003e gene deletions in Malawi. The presence of these deletions may compromise the performance of HRP2-based RDTs, indicating the need to reassess diagnostic strategies in affected regions.\u003c/p\u003e","manuscriptTitle":"First report of pfhrp2 and pfhrp3 gene deletions compromising HRP2-based malaria rapid diagnostic tests in Malawi","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-16 11:58:16","doi":"10.21203/rs.3.rs-6618930/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2025-07-09T01:42:35+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-05-16T08:02:28+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-13T07:45:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-09T02:16:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Infectious Diseases of Poverty","date":"2025-05-08T05:19:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"infectious-diseases-of-poverty","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"idop","sideBox":"Learn more about [Infectious Diseases of Poverty](http://idpjournal.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/idop/default.aspx","title":"Infectious Diseases of Poverty","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"17234b02-93ee-40f0-bea3-53b064cbb48d","owner":[],"postedDate":"May 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-13T16:05:38+00:00","versionOfRecord":{"articleIdentity":"rs-6618930","link":"https://doi.org/10.1186/s40249-025-01368-8","journal":{"identity":"infectious-diseases-of-poverty","isVorOnly":false,"title":"Infectious Diseases of Poverty"},"publishedOn":"2025-10-09 15:58:23","publishedOnDateReadable":"October 9th, 2025"},"versionCreatedAt":"2025-05-16 11:58:16","video":"","vorDoi":"10.1186/s40249-025-01368-8","vorDoiUrl":"https://doi.org/10.1186/s40249-025-01368-8","workflowStages":[]},"version":"v1","identity":"rs-6618930","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6618930","identity":"rs-6618930","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}