Rapid diagnostic test kit as a source of DNA in comparison with filter paper for malaria molecular surveillance and drug resistance monitoring: A cross-sectional study

Rapid diagnostic test kit as a source of DNA in comparison with filter paper for malaria molecular surveillance and drug resistance monitoring: A cross-sectional study | 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 Rapid diagnostic test kit as a source of DNA in comparison with filter paper for malaria molecular surveillance and drug resistance monitoring: A cross-sectional study Bereket Tadesse Woldegiorgis, Biniam Wondale, Girum Tamiru, Bernt Lindtjørn, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8080012/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Molecular surveillance of malaria and drug resistance monitoring typically use dried blood samples (DBS) on filter papers. However, the use of Rapid Diagnostic Test (RDT) kits presents a promising yet unexplored alternative DNA source. This study aimed to assess the efficiency of DNA recovery from used RDT kits for molecular malaria surveillance and drug resistance monitoring by comparing its performance with the conventional filter paper DBS method. Methods Four hundred seventeen paired samples of RDT kits and DBS on filter paper were collected from malaria-positive cases at six health centers in the Gamo Zone of southern Ethiopia. DNA was extracted from both sample types using the Chelex-100 method, followed by nested polymerase chain reaction (PCR) targeting the 18S rRNA gene. Amplification of the 65 paired sub-samples of RDT and DBS-extracted DNA was carried out for the anti-malarial drug resistance gene, pfmdr1 . Nested PCR results from the two sample sources were compared using a 2 by 2 contingency table, along with diagnostic accuracy measures and Cohen’s Kappa agreement analysis. Results Of 417 paired samples, 391 (93.8%) of the DBS-extracted samples and 349 (83.7%) of the RDT-extracted samples were positive for malaria parasites using nested PCR. The diagnostic accuracy of samples extracted from RDT for detecting the Plasmodium parasite was 87.1% (95% Confidence Interval (CI): 83.5–89.9). The sensitivity of samples extracted from RDT for P. falciparum detection was 89.2% (95% CI: 84.7–92.5), while it was 81.9% (95% CI: 74.6–87.6) for P. vivax . The overall Kappa value for the agreement between nested PCR results from DBS and RDT-extracted samples was 0.64 ( P < 0.001). This agreement was more pronounced (a Kappa value of 0.75; P 100,000/µl). The amplification success rate for the pfmdr1 gene was 100% (65/65) for DBS samples and 96.7% (63/65) for the samples from RDT kits. Conclusion Used RDT kits can serve as an alternative DNA source and may be utilized for molecular surveillance of malaria and monitoring drug resistance. Used RDT kit Molecular malaria surveillance Drug resistance monitoring DBS on filter paper Figures Figure 1 Figure 2 Background Malaria is a leading cause of death and illness in most developing countries [ 1 ], making effective surveillance vital for successful control and elimination [ 2 ]. However, in African countries, weak surveillance systems pose a significant challenge for malaria control, alongside other factors such as insecticide and anti-malarial drug resistance [ 3 , 4 ]. Molecular malaria surveillance plays a crucial role in detecting the DNA of Plasmodium parasites, allowing for the monitoring of anti-malarial drug resistance, mapping of the parasites, and understanding of infection dynamics [ 5 , 6 ]. This technique enhances our understanding of transmission patterns, facilitates early detection of drug resistance, and contributes to reducing treatment failures. Furthermore, it can identify low-density infections that are often overlooked by routine diagnostic methods [ 7 ]. While molecular surveillance offers benefits, challenges related to sample transportation and storage impede its full implementation [ 8 , 9 ]. Integrating molecular surveillance with the existing health care system may enhance the overall surveillance framework by leveraging available resources [ 9 ]. Dried blood spots (DBS) are widely used in epidemiological studies and large-scale molecular surveillance of malaria [ 10 ], while rapid diagnostic tests (RDTs) are the primary diagnostic tool in resource-limited settings [ 11 ]. Furthermore, recent evidence suggests that dried blood samples from used RDT kits can serve as a viable alternative to filter paper DBS for molecular surveillance, offering a practical and cost-effective solution. In addition, using the used RDT kits as a source of DNA has the advantage of avoiding invasive procedures in field settings. Unlike DBS, which requires additional finger pricks to obtain sufficient blood volume, the use of RDTs eliminates the need for extra sampling. Because RDTs have a minimal sample volume, DNA extraction must be done in a single attempt, leaving little to no opportunity for re-extraction if the initial attempt fails [ 15 ]. Despite this limitation, archived RDT kits from health facilities, particularly in remote areas, present a valuable resource for secondary applications beyond their initial diagnostic use. These kits can be repurposed for molecular surveillance, quality control assessments, and parasite load quantification, providing an efficient and cost-effective approach to enhance epidemiological monitoring without the need for additional sample collection [ 16 , 17 ]. In Ethiopia, RDTs are used for malaria diagnosis, particularly in rural settings [ 18 ]. This creates an opportunity to use existing resources, which could reduce the costs of DBS preparation and filter paper. Hence, using RDTs for malaria molecular surveillance and drug resistance monitoring may strengthen the surveillance system by simplifying the sample collection process. Although previous studies have demonstrated that extracting Plasmodium parasite DNA from used RDT kits is feasible, the technical aspects, ranging from field sample collection to laboratory analysis, have not been thoroughly studied in the Ethiopian context, particularly in comparison to DBS filter paper. Additionally, most studies have primarily focused on detecting P. falciparum genes, leaving the performance of samples extracted from RDT kits to detect other Plasmodium species, such as P. vivax , and mixed infections inadequately explored. This study hypothesised that the used RDT kits are as effective as DBS samples in recovering Plasmodium parasite DNA. Therefore, this study aimed to evaluate the effectiveness of blood samples extracted from used RDT kits compared to DBS on filter paper in obtaining DNA for malaria molecular surveillance and drug resistance monitoring. Methods Study design A comparative cross-sectional study design was employed to determine the effectiveness of the RDT kit used as a DNA source by comparing it with filter paper DBS. Paired blood samples from the same individuals were used. The downstream molecular procedures (DNA extraction and nested PCR) were the same for both paired blood samples. Participants Eligibility criteria Eligible participants were consecutive patients with malaria, confirmed by microscopy at health centers in the Gamo Zone—specifically Morka, Wacha, Mengeda, Shella Deda, Wajifo, and Gocho—between May and July 2024 (Fig. 1 ). Patients with mixed malaria infection and severe malaria cases were excluded. Test methods Index test The index test in this study was utilizing used RDT kit as a sample collection tool for Plasmodium parasite gene detection. Reference standard The DBS filter paper was selected as the standard reference for evaluating DNA detection rate from used RDT kits, as it is the most widely used method for collecting blood samples [ 10 ]. Sample collection and storage Patients suspected of having malaria at health centers were routinely tested for diagnosis using a microscope. Once confirmed through microscopy to have a mono-infection of either P. falciparum or P. vivax , they were included in the study after obtaining written informed consent. Blood samples for DBS were then collected on Fisher brand qualitative P8 filter papers (Fisher Scientific, China). Simultaneously, tests were conducted using RDT kits (Abbot Bioline, Republic of Korea). The RDT kit and the filter paper samples were air-dried, protected from direct sunlight, and individually sealed in zip-locked plastic bags with silica gel. The samples were kept at room temperature for periods ranging from 35 to 71 days at the respective collection sites. These samples were transported at ambient temperature and stored at – 40°C at the Advanced Medical Entomology and Vector Control Research Laboratory of Arba Minch University. Parasite density quantification using microscopy The parasite density quantification was performed according to the WHO protocol, using microscopic examination and white blood cell (WBC) counts as a reference. Samples with less than 10,000 parasites/µl were considered as low, with 10,000-100,000 parasites/µl considered as moderate, and samples with more than 100,000 parasites/µl were regarded as high parasitaemia [ 19 ]. This approach enabled the stratification of samples by parasite load, allowing for a more robust comparison of diagnostic performance between the two sample sources, RDT and DBS, across a range of parasitaemia levels. By assessing performance at different parasite densities, it becomes possible to evaluate not only overall accuracy but also sensitivity under low- and high-parasite-load conditions. DNA extraction The RDT kit preparation for DNA extraction was performed as described elsewhere [ 13 ]. To briefly explain, the cassettes that hold the RDT kit were opened laterally, and the strip was taken out. The proximal part of the nitrocellulose membrane, which had a higher DNA yield than other segments of the strip, was cut out using sterile scissors and forceps and used for extraction [ 13 ]. For the DBS, a 6 mm diameter circle was punched from each DBS sample using a sterile puncher. DNA extraction was performed from both RDT and filter paper DBS using the Chelex-100 extraction method as described elsewhere [ 16 ]. Eluted DNA was stored at -40°C until further analysis. DNA amplification DNA amplification was performed using nested PCR, followed by visualization on a 2% agarose gel [ 20 ]. For the first amplification (Nest 1), a 20 µl master mix, containing Dream Taq Green PCR master mix (ThermoFisher Scientific, Lithuania) along with primers (Merck, UK) and molecular grade water (ThermoFisher Scientific, Lithuania) was combined with 5 µl of the sample DNA to create a total PCR reaction volume of 25 µl. For species identification in the nested-2 reaction, 23 µl of the master mix and 2 µL from Nest 1 were used. The targeted gene for amplification was the small subunit ribosomal RNA (ssrRNA). The PCR cycling parameters and primer sequences were followed [ 20 ]. The final PCR results were categorized into four groups: P. falciparum , P. vivax , a mixed infection of P. falciparum and P. vivax , and negative. The data analysis was conducted accordingly. Data analysis The collected data were analyzed using SPSS version 26. Descriptive statistics (frequencies and percentages for categorical variables, means and ranges for continuous numeric variables) were used to summarize the data. Plasmodium parasite DNA detection rate from RDT kits relative to DBS samples was evaluated by calculating sensitivity and diagnostic accuracy using the OpenEpi online calculator [ 21 ]. The estimated parameters were presented with 95% confidence intervals. The agreement between the two sources of DNA samples was assessed using Cohen’s Kappa (κ) statistic, calculated with both SPSS and the OpenEpi online calculator to determine the strength of agreement beyond what would be expected by chance. The strength of agreement by Kappa was interpreted as: <0.20 (poor), 0.21–0.40 (fair), 0.41–0.60 (moderate), 0.61–0.80 (substantial), and 0.81–1.00 (almost perfect) [ 22 ]. Sub-group analysis was performed for P. falciparum and P. vivax cases to explore species-specific agreement patterns. A P-value less than 0.05 was considered statistically significant. Sample size The objective of the study was to compare the outcomes of nested PCR using samples extracted from DBS and RDT, employing the Kappa value for analysis [ 23 ]. To calculate the sample size needed for each group to compare the Plasmodium parasite DNA detection, we applied the following formula: $$\:N=\frac{(Z\alpha\:/2)2\cdot\:\left[p1\right(1-p1)+p2(1-p2\left)\right]}{{E}^{2}}$$ Where: N = required sample size per group Z = Z-score for the desired confidence level (Z): 95% → Z = 1.96 (two-tailed) K = expected Kappa value (0.5) Morris et al [ 15 ] E = desired margin of error (0.10) Expected efficiency (if unknown, use worst-case): p1 = p2 = 0.5 (maximizes variance) The calculated sample size was 193 participants per group. Using a standard adjustment method that accounts for agreement variability, as measured by Kappa, the initial sample size was adjusted by dividing it by 1-k. Consequently, the sample size for each group was set at 386, resulting in a total of 772 samples. Ultimately, 417 samples were collected for each group, totalling 834 samples. Study description This study served as a baseline for ongoing research assessing antimalarial drug resistance in southern Ethiopia, with a specific focus on identifying alternative sampling methods for detecting Plasmodium parasite DNA. Samples were collected from six health centers in the Gamo Zone, selected based on their high rates of malaria cases. Molecular analyses were conducted using nested PCR. Dried blood spot (DBS) samples that were microscopically confirmed as P. vivax or P. falciparum positive at the health centers were collected on filter paper. In addition, RDT kits (Abbott Bioline Malaria Ag P. falciparum / P. vivax ) used on the same patients were also collected. The number of samples collected from each health center is presented in Table 1 . Table 1 Malaria positive samples collected from the Health Centers in Gamo Zone, Ethiopia, 2024 Name of the Health Centers District Identification done by microscopy P. falciparum P. vivax Total Morka Kucha 52 26 78 Wacha Deramalo 56 0 56 Mengeda Kucha 39 40 79 ShelaDeda Deramalo 39 33 72 Wajifo Mirab Abaya 40 10 50 Gocho Boreda 45 37 82 Total 271 146 417 Quality control All laboratory procedures were performed in accordance with established standard operating procedures (SOPs) to ensure accuracy and reproducibility. Positive and negative controls were included in every batch of DNA extraction and amplification to validate the efficiency of the procedures and ensure the reliability of the results. Every microscopic slide was examined by two microscopists, one at the health centers and one at Arba Minch University. A third person, from the Arba Minch Public Health Institute Laboratory, re-examined discrepant microscopy results. Results A total of 417 paired RDT and DBS-extracted samples were analyzed. Among these, 391 (93.8%) of the DBS-extracted samples (reference standard) and 349 (83.7%) of the RDT-extracted samples (index test) tested positive for Plasmodium parasites (Fig. 2 ). The participants' age ranges from 4 months to 66 years, with a mean age of 14.9 years. Forty-eight percent (200/417) of the cases had low parasite density, followed by moderate parasite density (38.1%; 149/417) (Table 2 ). Table 2 Demographic characteristics of study participants and their parasite densities in samples collected from health centers in Gamo Zone, Ethiopia, 2024 Variables Variables Number Percent Sex Male 247 59.2 Female 170 40.8 Age group (years) 50 18 4.3 Parasite spp. P. falciparum 271 65 P. vivax 146 35 Parasite load Low ( 100000/µl) 9 2.2 Unidentified due to samples smear problem 49 11.8 Total 417 100 Performance of RDT-kit versus DBS as a DNA sources The Plasmodium parasite DNA detected from the DBS was 93.8% (95% CI: 91.1–95.8), while it was 83.7% (95% CI: 79.9–87.0) from the RDT kit. The diagnostic accuracy and sensitivity of samples extracted from RDT were 87.1% and 87.7%, respectively, as presented in Table 3 . Table 3 Performance of RDT-extracted samples for Plasmodium parasite detection compared to DBS extracted samples (n = 417). Microscope positive (n = 417) PCR result of DBS extracted samples (standard) PCR result of the RDT extracted samples Positive Negative Total Positives 343 6 349 Negative 48 20 68 Total 391 26 417 95% confidence interval Summary statistics Percent Lower limit Upper limit Sensitivity (detection rate) 87.7 84.1 90.6 Diagnostic accuracy 87.1 83.5 89.9 Performance of the RDT-kit compared to the DBS as DNA sources for Plasmodium species detection Nested PCR was done for 417-paired samples of DBS and RDT collected from 271 P. falciparum cases and 146 P. vivax cases (Table 4 ). Among 271 P. falciparum cases, 89.3% (242/271; 95% CI: 85.2–92.6) of DBS-extracted and 81.5% (221/271; 95% CI: 76.6–85.8) of RDT-extracted samples tested positive for P. falciparum . Similarly, for the paired sample of P. vivax cases, 91.1% (133/146) of DBS samples and 82.2% (120/146) of RDT samples were positive. Table 4 Nested PCR results from DBS and RDT extracted samples to detect Plasmodium parasite species in Gamo zone, Ethiopia, 2024 Sample collection methods Nested PCR outcomes Microscopy results from health centers P. falciparum (n = 271) P. vivax (n = 146) Total DBS-extracted samples (n = 417) Negative 23 3 26 P. falciparum 221 10 231 P. vivax 6 121 127 Mixed infection 21 12 33 242 (89.3%) (P. falciparum positives including mixed infection) 133 (91.1%) (P. vivax positives including mixed infection) RDT-extracted samples (n = 417) Negative 44 24 68 P. falciparum 214 2 216 P. vivax 6 117 123 Mixed infection 7 3 10 221 (81.5%) (P. falciparum positives including mixed infection) 120 (82.2%) (P. vivax positives including mixed infection) The agreement between nested PCR results from DBS and RDT samples was assessed separately for the two parasite species, revealing a notable difference in DNA detection rates between P. falciparum and P. vivax (Tables 5 and 6 ). For P. falciparum samples extracted from RDTs, the DNA detection rate was 89.2% (95% CI: 84.7–92.5), whereas for P. vivax samples, the rate was 81.9% (95% CI: 74.6–87.6) when compared with DNA extracted from DBS samples. Table 5 Agreement between nested PCR results of DBS and RDT extracted samples for P. falciparum detection based on 2x2 contingency table (n = 271) Microscope positive P. falciparum (n = 271) PCR result of the DBS extracted samples PCR result of the RDT extracted samples Positive Negative Total Positives 216 5 221 Negative 26 24 50 Total 242 29 271 95% confidence interval Summary statistics Percent Lower limit Upper limit Sensitivity (detection rate) 89.2 84.7 92.5 Diagnostic accuracy 88.5 84.2 91.8 Table 6 Agreement between PCR results of DBS and RDT extracted samples for P.vivax detection based on 2x2 contingency table (n = 146) Microscope positive P. vivax (n = 146) PCR result of DBS extracted samples PCR result of the RDT extracted samples Positive Negative Total Positives 109 11 120 Negative 24 2 26 Total 133 13 146 95% confidence interval Summary statistics Percent Lower Limit Upper Limit Sensitivity (detection rate) 81.9 74.5 87.5 Diagnostic Accuracy 76.0 68.5 82.2 The agreement between PCR results from RDT-extracted and DBS-extracted samples was evaluated across parasite load categories (high, medium, and low) using SPSS. The agreement within the low parasite load category was lower (Kappa value = 0.58) than within the medium (Kappa value = 0.77) and high (Kappa value = 0.75) parasite load categories. However, the overall Kappa value was 0.64 (P < 0.001). Detection of mixed infection of P. falciparum and P. vivax Although all the samples analyzed were identified as mono-infections using a microscope at the health centers, the nested PCR result showed a mixed infection of P. falciparum and P. vivax. From the total of 417 paired samples of RDT and DBS, 33 (7.9%) of the DBS-extracted samples and 10 (2.4%) of the RDT-kit-extracted samples were found to be mixed infections of P. falciparum and P. vivax. Eight of the 33 mixed infections detected from DBS samples, were also detected by RDT extracted samples. The sensitivity (detection rate) for detecting mixed infection in samples extracted from RDT was 24.2% (95% CI: 12.8, 42.0). Amplification success rate for P. falciparum drug resistance gene ( pfmdr1) Amplification of the pfmdr1 gene by nested PCR was performed on 65 paired samples of RDT and DBS to determine whether RDT-extracted DNA was equivalent to that of DBS-extracted DNA. From the 65 paired samples, 100% (65/65) of DBS extracted DNA and 96.7% (63/65) of RDT extracted DNA were amplified using nested PCR and visualized by gel electrophoresis. The calculated sensitivity was 96.92% (95% CI: 89.5–99.2). Discussion The principal finding of this study is that DNA extracted from used rapid diagnostic test (RDT) kits collected from health centers in the Gamo Zone, Ethiopia, demonstrated performance comparable to that of DNA extracted from DBS on filter paper. When DBS samples were used as the reference standard, RDT-derived DNA showed a higher detection rate for P. falciparum than for P. vivax . This difference likely reflects the typically higher parasite densities observed in P. falciparum infections compared with those of P. vivax . RDTs offer significant advantages for malaria diagnosis, as they are widely used and allow health professionals or health extension workers to store used test kits and send them to regional laboratories. These used RDTs provide a valuable source of DNA for molecular surveillance of malaria parasites and antimalarial drug resistance. This approach enables periodic molecular monitoring without requiring additional resources or specialized training for health workers in remote settings [ 12 , 24 ]. The WHO recommends delivering DBS samples to molecular laboratories within 15 days; for longer preservation, storage at − 20°C or − 80°C is advised. In this study, however, samples were kept at room temperature for 35–71 days before being transferred to − 40°C storage. Previous studies have reported that storage for up to six months does not significantly affect the quality of parasite DNA or the success rates of amplification [ 15 , 16 , 26 ]. Nonetheless, extended storage may reduce both the quality and quantity of DNA [ 25 , 26 ]. Moreover, drug resistance genes have been successfully identified from RDT kit samples stored for 3–9 months, although with a lower amplification success rate [ 14 ]. Another study apparently showed that samples stored for 6 to 32 months had a similar amplification success rate of P. falciparum molecular markers [ 27 ]. While RDTs are useful, they have several significant limitations for comprehensive surveillance and analysis. As a single-use sample source, RDTs do not allow for the re-extraction of DNA for confirmatory testing if needed [ 15 ]. Additionally, processing large sample volumes is complicated by the labor-intensive requirement of manually opening through the hard plastic casing to access the nitrocellulose strip inside, as mentioned in another study [ 13 ]. The performance of samples obtained from RDT kits for amplification of the pfmdr1 drug resistance gene was comparable to that of filter paper DBS. This finding aligns with a previous study conducted in Sweden, which used samples collected from Zanzibar [ 15 ]. These results suggest that RDT kits can serve as reliable tools for collecting samples in drug resistance surveillance studies. The small sample size resulting from the initial exclusion criteria may render the findings about mixed infection less reliable. Conclusions The present study demonstrated that used RDT kits could serve as an alternative and reliable source of Plasmodium parasite DNA for molecular surveillance and drug resistance monitoring in settings where RDTs are used routinely for malaria diagnosis. Archived RDT kits provide a practical option for large scale studies focusing on P. falciparum , making them valuable for molecular surveillance. Further study is recommended to investigate the effectiveness of DNA samples extracted from used RDT kit for detection of mixed infections of P. falciparum and P. vivax . Abbreviations RDT Rapid Diagnostic Test DBS Dried Blood Sample PCR Polymerase Chain Reaction DNA Deoxyribonucleic Acid Declarations Acknowledgements We acknowledge the management staff of the health center for their support in facilitating the data collection process. We also thank the laboratory technicians at the health centers for their collaboration during the sample collection. Most importantly, we recognize the study participants for their willingness to provide samples and share information. Additionally, we extend our thanks to Mr. Alemayehu Letebo for his technical assistance during the molecular laboratory work. Authors' contributions B.T: Conceptualization, methodology, writing the manuscript, data collection, laboratory work and data analysis. B.W: Methodology, field supervision, reviewing and editing the manuscript. G.T: Laboratory work. B.L: Conceptualization, reviewing and editing the manuscript, supervision, methodology. F.M: Conceptualization, reviewing and editing the manuscript, methodology, laboratory supervision and field supervision. Funding: This study received funding from the Norwegian Program for Capacity Development in Higher Education and Research for Development (Grant No. QZA-21/0162). Availability of data and materials The datasets used in this study are available from the corresponding author on reasonable request. Ethics approval and consent to participate Ethical approval for the study was obtained from the Arba Minch University Institutional Review Board, with reference number IRB/23127/2024. Written consent was obtained from all participants or their guardians in the case of minors. Consent for publication: Not applicable Competing interests: None to declare References Li J, Docile HJ, Fisher D, Pronyuk K, Zhao L. Current Status of Malaria Control and Elimination in Africa: Epidemiology, Diagnosis, Treatment, Progress and Challenges. J Epidemiol Glob Health. 2024;14:561–79. Fountain A, Ye Y, Roca-Feltrer A, Alexander K, Rowe, Camara A, Fofana A, et al. Surveillance as a Core Intervention to Strengthen Malaria Control Programs in Moderate to High Transmission Settings. Am J Trop Med Hyg. 2023;108:8–13. Lourenço C, Tatem AJ, Atkinson PM, Cohen JM, Pindolia D, Bhavnani D, et al. Strengthening surveillance systems for malaria elimination: a global landscaping of system performance, 2015–2017. 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Woldegiorgis","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYBACAyBmbACx2BsbHwApHj4itRhIMPAcPgzi8LARr0XCLU0CJEJQizl778OHMyr+1Bnc4DGr/JpjJ8PGwPzw0Q08Wix7jhsbbjhjIGFwu8fstuy2ZKDD2IyNc/A57EYam+TDNgMJsztnzG5LbmMGauFhk8ar5f4z9p8P/wG13MgxK5bcVk+ElhtsbIwbG0Ba0tIYP247TFiLZU8as+SMY8aS+88cPizNuO04DxszAb+Ysx9j/NhTI8cv2d7Y+PHntmp7fvbmh4/xaUEBzDxgkljlIMD4gxTVo2AUjIJRMGIAAKPdR/Mlu48JAAAAAElFTkSuQmCC","orcid":"","institution":"Arba Minch University","correspondingAuthor":true,"prefix":"","firstName":"Bereket","middleName":"Tadesse","lastName":"Woldegiorgis","suffix":""},{"id":557882714,"identity":"3215732c-cda7-4704-941c-4b086c99e8ff","order_by":1,"name":"Biniam Wondale","email":"","orcid":"","institution":"Arba Minch University","correspondingAuthor":false,"prefix":"","firstName":"Biniam","middleName":"","lastName":"Wondale","suffix":""},{"id":557882715,"identity":"f1997f79-ad20-40c7-b424-0375c05b2512","order_by":2,"name":"Girum Tamiru","email":"","orcid":"","institution":"Arba Minch University","correspondingAuthor":false,"prefix":"","firstName":"Girum","middleName":"","lastName":"Tamiru","suffix":""},{"id":557882716,"identity":"7133922b-10d8-4f45-8406-4ec7749b3114","order_by":3,"name":"Bernt Lindtjørn","email":"","orcid":"","institution":"Arba Minch University","correspondingAuthor":false,"prefix":"","firstName":"Bernt","middleName":"","lastName":"Lindtjørn","suffix":""},{"id":557882717,"identity":"369571d8-8ccc-430d-90f0-8f31e515d615","order_by":4,"name":"Fekadu Massebo","email":"","orcid":"","institution":"Arba Minch University","correspondingAuthor":false,"prefix":"","firstName":"Fekadu","middleName":"","lastName":"Massebo","suffix":""}],"badges":[],"createdAt":"2025-11-10 18:53:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8080012/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8080012/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98426826,"identity":"de9ed1cd-cfca-4783-bad5-8e719066c42d","added_by":"auto","created_at":"2025-12-17 16:38:48","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":175085,"visible":true,"origin":"","legend":"","description":"","filename":"BereketTadesse.RDT.10.11.2025.Manuscript.docx","url":"https://assets-eu.researchsquare.com/files/rs-8080012/v1/e2fa88fb16c34b16a64add78.docx"},{"id":98048619,"identity":"f80b1493-545b-414f-98e9-8eed0b80268c","added_by":"auto","created_at":"2025-12-12 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1","display":"","copyAsset":false,"role":"figure","size":47459,"visible":true,"origin":"","legend":"\u003cp\u003eMap showing the six health centers included in the study area\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8080012/v1/930af57f1659397b5a32b3a7.jpg"},{"id":98048623,"identity":"d2428ede-99d9-4a4d-8648-dad1b77e0db1","added_by":"auto","created_at":"2025-12-12 08:34:37","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":346028,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of study\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8080012/v1/079eca9da966690c189e28f4.jpg"},{"id":98444725,"identity":"a84232ee-0086-4a83-a391-8b26f8f49fbc","added_by":"auto","created_at":"2025-12-17 17:17:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1530264,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8080012/v1/c740d69b-ba3d-49a5-ac79-e5aa5d27c86b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rapid diagnostic test kit as a source of DNA in comparison with filter paper for malaria molecular surveillance and drug resistance monitoring: A cross-sectional study","fulltext":[{"header":"Background","content":"\u003cp\u003eMalaria is a leading cause of death and illness in most developing countries [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], making effective surveillance vital for successful control and elimination [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, in African countries, weak surveillance systems pose a significant challenge for malaria control, alongside other factors such as insecticide and anti-malarial drug resistance [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMolecular malaria surveillance plays a crucial role in detecting the DNA of \u003cem\u003ePlasmodium\u003c/em\u003e parasites, allowing for the monitoring of anti-malarial drug resistance, mapping of the parasites, and understanding of infection dynamics [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This technique enhances our understanding of transmission patterns, facilitates early detection of drug resistance, and contributes to reducing treatment failures. Furthermore, it can identify low-density infections that are often overlooked by routine diagnostic methods [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. While molecular surveillance offers benefits, challenges related to sample transportation and storage impede its full implementation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Integrating molecular surveillance with the existing health care system may enhance the overall surveillance framework by leveraging available resources [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDried blood spots (DBS) are widely used in epidemiological studies and large-scale molecular surveillance of malaria [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], while rapid diagnostic tests (RDTs) are the primary diagnostic tool in resource-limited settings [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Furthermore, recent evidence suggests that dried blood samples from used RDT kits can serve as a viable alternative to filter paper DBS for molecular surveillance, offering a practical and cost-effective solution. In addition, using the used RDT kits as a source of DNA has the advantage of avoiding invasive procedures in field settings. Unlike DBS, which requires additional finger pricks to obtain sufficient blood volume, the use of RDTs eliminates the need for extra sampling. Because RDTs have a minimal sample volume, DNA extraction must be done in a single attempt, leaving little to no opportunity for re-extraction if the initial attempt fails [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Despite this limitation, archived RDT kits from health facilities, particularly in remote areas, present a valuable resource for secondary applications beyond their initial diagnostic use. These kits can be repurposed for molecular surveillance, quality control assessments, and parasite load quantification, providing an efficient and cost-effective approach to enhance epidemiological monitoring without the need for additional sample collection [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn Ethiopia, RDTs are used for malaria diagnosis, particularly in rural settings [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This creates an opportunity to use existing resources, which could reduce the costs of DBS preparation and filter paper. Hence, using RDTs for malaria molecular surveillance and drug resistance monitoring may strengthen the surveillance system by simplifying the sample collection process.\u003c/p\u003e\u003cp\u003eAlthough previous studies have demonstrated that extracting \u003cem\u003ePlasmodium\u003c/em\u003e parasite DNA from used RDT kits is feasible, the technical aspects, ranging from field sample collection to laboratory analysis, have not been thoroughly studied in the Ethiopian context, particularly in comparison to DBS filter paper. Additionally, most studies have primarily focused on detecting \u003cem\u003eP. falciparum\u003c/em\u003e genes, leaving the performance of samples extracted from RDT kits to detect other \u003cem\u003ePlasmodium\u003c/em\u003e species, such as \u003cem\u003eP. vivax\u003c/em\u003e, and mixed infections inadequately explored.\u003c/p\u003e\u003cp\u003eThis study hypothesised that the used RDT kits are as effective as DBS samples in recovering \u003cem\u003ePlasmodium\u003c/em\u003e parasite DNA. Therefore, this study aimed to evaluate the effectiveness of blood samples extracted from used RDT kits compared to DBS on filter paper in obtaining DNA for malaria molecular surveillance and drug resistance monitoring.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design\u003c/h2\u003e\u003cp\u003eA comparative cross-sectional study design was employed to determine the effectiveness of the RDT kit used as a DNA source by comparing it with filter paper DBS. Paired blood samples from the same individuals were used. The downstream molecular procedures (DNA extraction and nested PCR) were the same for both paired blood samples.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eEligibility criteria\u003c/h2\u003e\u003cp\u003e Eligible participants were consecutive patients with malaria, confirmed by microscopy at health centers in the Gamo Zone\u0026mdash;specifically Morka, Wacha, Mengeda, Shella Deda, Wajifo, and Gocho\u0026mdash;between May and July 2024 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Patients with mixed malaria infection and severe malaria cases were excluded.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTest methods\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eIndex test\u003c/h2\u003e\u003cp\u003eThe index test in this study was utilizing used RDT kit as a sample collection tool for \u003cem\u003ePlasmodium\u003c/em\u003e parasite gene detection.\u003c/p\u003e\u003cp\u003e\u003cb\u003eReference standard\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe DBS filter paper was selected as the standard reference for evaluating DNA detection rate from used RDT kits, as it is the most widely used method for collecting blood samples [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eSample collection and storage\u003c/h2\u003e\u003cp\u003ePatients suspected of having malaria at health centers were routinely tested for diagnosis using a microscope. Once confirmed through microscopy to have a mono-infection of either \u003cem\u003eP. falciparum\u003c/em\u003e or \u003cem\u003eP. vivax\u003c/em\u003e, they were included in the study after obtaining written informed consent. Blood samples for DBS were then collected on Fisher brand qualitative P8 filter papers (Fisher Scientific, China). Simultaneously, tests were conducted using RDT kits (Abbot Bioline, Republic of Korea). The RDT kit and the filter paper samples were air-dried, protected from direct sunlight, and individually sealed in zip-locked plastic bags with silica gel. The samples were kept at room temperature for periods ranging from 35 to 71 days at the respective collection sites. These samples were transported at ambient temperature and stored at \u0026ndash; 40\u0026deg;C at the Advanced Medical Entomology and Vector Control Research Laboratory of Arba Minch University.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eParasite density quantification using microscopy\u003c/h3\u003e\n\u003cp\u003eThe parasite density quantification was performed according to the WHO protocol, using microscopic examination and white blood cell (WBC) counts as a reference. Samples with less than 10,000 parasites/\u0026micro;l were considered as low, with 10,000-100,000 parasites/\u0026micro;l considered as moderate, and samples with more than 100,000 parasites/\u0026micro;l were regarded as high parasitaemia [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This approach enabled the stratification of samples by parasite load, allowing for a more robust comparison of diagnostic performance between the two sample sources, RDT and DBS, across a range of parasitaemia levels. By assessing performance at different parasite densities, it becomes possible to evaluate not only overall accuracy but also sensitivity under low- and high-parasite-load conditions.\u003c/p\u003e\n\u003ch3\u003eDNA extraction\u003c/h3\u003e\n\u003cp\u003eThe RDT kit preparation for DNA extraction was performed as described elsewhere [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. To briefly explain, the cassettes that hold the RDT kit were opened laterally, and the strip was taken out. The proximal part of the nitrocellulose membrane, which had a higher DNA yield than other segments of the strip, was cut out using sterile scissors and forceps and used for extraction [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. For the DBS, a 6 mm diameter circle was punched from each DBS sample using a sterile puncher. DNA extraction was performed from both RDT and filter paper DBS using the Chelex-100 extraction method as described elsewhere [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Eluted DNA was stored at -40\u0026deg;C until further analysis.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eDNA amplification\u003c/h2\u003e\u003cp\u003eDNA amplification was performed using nested PCR, followed by visualization on a 2% agarose gel [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. For the first amplification (Nest 1), a 20 \u0026micro;l master mix, containing Dream Taq Green PCR master mix (ThermoFisher Scientific, Lithuania) along with primers (Merck, UK) and molecular grade water (ThermoFisher Scientific, Lithuania) was combined with 5 \u0026micro;l of the sample DNA to create a total PCR reaction volume of 25 \u0026micro;l. For species identification in the nested-2 reaction, 23 \u0026micro;l of the master mix and 2 \u0026micro;L from Nest 1 were used. The targeted gene for amplification was the small subunit ribosomal RNA (ssrRNA). The PCR cycling parameters and primer sequences were followed [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The final PCR results were categorized into four groups: \u003cem\u003eP. falciparum\u003c/em\u003e, \u003cem\u003eP. vivax\u003c/em\u003e, a mixed infection of \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. vivax\u003c/em\u003e, and negative. The data analysis was conducted accordingly.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eThe collected data were analyzed using SPSS version 26. Descriptive statistics (frequencies and percentages for categorical variables, means and ranges for continuous numeric variables) were used to summarize the data. \u003cem\u003ePlasmodium\u003c/em\u003e parasite DNA detection rate from RDT kits relative to DBS samples was evaluated by calculating sensitivity and diagnostic accuracy using the OpenEpi online calculator [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The estimated parameters were presented with 95% confidence intervals. The agreement between the two sources of DNA samples was assessed using Cohen\u0026rsquo;s Kappa (κ) statistic, calculated with both SPSS and the OpenEpi online calculator to determine the strength of agreement beyond what would be expected by chance. The strength of agreement by Kappa was interpreted as: \u0026lt;0.20 (poor), 0.21\u0026ndash;0.40 (fair), 0.41\u0026ndash;0.60 (moderate), 0.61\u0026ndash;0.80 (substantial), and 0.81\u0026ndash;1.00 (almost perfect) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Sub-group analysis was performed for \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. vivax\u003c/em\u003e cases to explore species-specific agreement patterns. A P-value less than 0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eSample size\u003c/h2\u003e\u003cp\u003eThe objective of the study was to compare the outcomes of nested PCR using samples extracted from DBS and RDT, employing the Kappa value for analysis [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. To calculate the sample size needed for each group to compare the \u003cem\u003ePlasmodium\u003c/em\u003e parasite DNA detection, we applied the following formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:N=\\frac{(Z\\alpha\\:/2)2\\cdot\\:\\left[p1\\right(1-p1)+p2(1-p2\\left)\\right]}{{E}^{2}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhere:\u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;required sample size per group\u003c/p\u003e\u003cp\u003eZ\u0026thinsp;=\u0026thinsp;Z-score for the desired confidence level (Z): 95% \u0026rarr; Z\u0026thinsp;=\u0026thinsp;1.96 (two-tailed)\u003c/p\u003e\u003cp\u003eK\u0026thinsp;=\u0026thinsp;expected Kappa value (0.5) Morris et al [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eE\u0026thinsp;=\u0026thinsp;desired margin of error (0.10)\u003c/p\u003e\u003cp\u003eExpected efficiency (if unknown, use worst-case): p1\u0026thinsp;=\u0026thinsp;p2\u0026thinsp;=\u0026thinsp;0.5 (maximizes variance)\u003c/p\u003e\u003cp\u003eThe calculated sample size was 193 participants per group. Using a standard adjustment method that accounts for agreement variability, as measured by Kappa, the initial sample size was adjusted by dividing it by 1-k. Consequently, the sample size for each group was set at 386, resulting in a total of 772 samples. Ultimately, 417 samples were collected for each group, totalling 834 samples.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eStudy description\u003c/h2\u003e\u003cp\u003eThis study served as a baseline for ongoing research assessing antimalarial drug resistance in southern Ethiopia, with a specific focus on identifying alternative sampling methods for detecting \u003cem\u003ePlasmodium\u003c/em\u003e parasite DNA. Samples were collected from six health centers in the Gamo Zone, selected based on their high rates of malaria cases. Molecular analyses were conducted using nested PCR.\u003c/p\u003e\u003cp\u003eDried blood spot (DBS) samples that were microscopically confirmed as \u003cem\u003eP. vivax\u003c/em\u003e or \u003cem\u003eP. falciparum\u003c/em\u003e positive at the health centers were collected on filter paper. In addition, RDT kits (Abbott Bioline Malaria Ag \u003cem\u003eP. falciparum\u003c/em\u003e/\u003cem\u003eP. vivax\u003c/em\u003e) used on the same patients were also collected. The number of samples collected from each health center is presented in 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\u003eMalaria positive samples collected from the Health Centers in Gamo Zone, Ethiopia, 2024\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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=\"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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eName of the Health Centers\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDistrict\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eIdentification done by microscopy\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP. falciparum\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP. vivax\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\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\u003cp\u003eMorka\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKucha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWacha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDeramalo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMengeda\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKucha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eShelaDeda\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDeramalo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWajifo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMirab Abaya\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGocho\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoreda\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e271\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e146\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e417\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eQuality control\u003c/h2\u003e\u003cp\u003eAll laboratory procedures were performed in accordance with established standard operating procedures (SOPs) to ensure accuracy and reproducibility. Positive and negative controls were included in every batch of DNA extraction and amplification to validate the efficiency of the procedures and ensure the reliability of the results. Every microscopic slide was examined by two microscopists, one at the health centers and one at Arba Minch University. A third person, from the Arba Minch Public Health Institute Laboratory, re-examined discrepant microscopy results.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 417 paired RDT and DBS-extracted samples were analyzed. Among these, 391 (93.8%) of the DBS-extracted samples (reference standard) and 349 (83.7%) of the RDT-extracted samples (index test) tested positive for \u003cem\u003ePlasmodium\u003c/em\u003e parasites (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe participants' age ranges from 4 months to 66 years, with a mean age of 14.9 years. Forty-eight percent (200/417) of the cases had low parasite density, followed by moderate parasite density (38.1%; 149/417) (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\u003eDemographic characteristics of study participants and their parasite densities in samples collected from health centers in Gamo Zone, Ethiopia, 2024\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eAge group (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u0026ndash;14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u0026ndash;49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e213\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e51.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eParasite spp.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eP. falciparum\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e271\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eP. vivax\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e146\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eParasite load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow (\u0026lt;\u0026thinsp;10000/\u0026micro;l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedium (10000\u0026ndash;100000/\u0026micro;l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh (\u0026gt;\u0026thinsp;100000/\u0026micro;l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnidentified due to samples smear problem\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e417\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003ePerformance of RDT-kit versus DBS as a DNA sources\u003c/h2\u003e\u003cp\u003eThe \u003cem\u003ePlasmodium\u003c/em\u003e parasite DNA detected from the DBS was 93.8% (95% CI: 91.1\u0026ndash;95.8), while it was 83.7% (95% CI: 79.9\u0026ndash;87.0) from the RDT kit. The diagnostic accuracy and sensitivity of samples extracted from RDT were 87.1% and 87.7%, respectively, as presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePerformance of RDT-extracted samples for \u003cem\u003ePlasmodium\u003c/em\u003e parasite detection compared to DBS extracted samples (n\u0026thinsp;=\u0026thinsp;417).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMicroscope positive (n\u0026thinsp;=\u0026thinsp;417)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003ePCR result of DBS extracted samples (standard)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCR result of the RDT extracted samples\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositives\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e349\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e391\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e417\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003e95% confidence interval\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSummary statistics\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLower limit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUpper limit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSensitivity (detection rate)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e87.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e84.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e90.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiagnostic accuracy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e87.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e89.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePerformance of the RDT-kit compared to the DBS as DNA sources for\u003c/b\u003e \u003cb\u003ePlasmodium\u003c/b\u003e \u003cb\u003especies detection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNested PCR was done for 417-paired samples of DBS and RDT collected from 271 \u003cem\u003eP. falciparum\u003c/em\u003e cases and 146 \u003cem\u003eP. vivax\u003c/em\u003e cases (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Among 271 \u003cem\u003eP. falciparum\u003c/em\u003e cases, 89.3% (242/271; 95% CI: 85.2\u0026ndash;92.6) of DBS-extracted and 81.5% (221/271; 95% CI: 76.6\u0026ndash;85.8) of RDT-extracted samples tested positive for \u003cem\u003eP. falciparum\u003c/em\u003e. Similarly, for the paired sample of \u003cem\u003eP. vivax\u003c/em\u003e cases, 91.1% (133/146) of DBS samples and 82.2% (120/146) of RDT samples were positive.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNested PCR results from DBS and RDT extracted samples to detect \u003cem\u003ePlasmodium\u003c/em\u003e parasite species in Gamo zone, Ethiopia, 2024\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSample collection methods\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNested PCR outcomes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eMicroscopy results from health centers\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP. falciparum\u003c/em\u003e\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;271)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP. vivax\u003c/em\u003e\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;146)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eDBS-extracted samples (n\u0026thinsp;=\u0026thinsp;417)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eP. falciparum\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e231\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eP. vivax\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e127\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMixed infection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e242 (89.3%)\u003c/p\u003e\u003cp\u003e\u003cem\u003e(P. falciparum\u003c/em\u003e positives including mixed infection)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e133 (91.1%)\u003c/p\u003e\u003cp\u003e\u003cem\u003e(P. vivax\u003c/em\u003e positives including mixed infection)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eRDT-extracted samples (n\u0026thinsp;=\u0026thinsp;417)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eP. falciparum\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e216\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eP. vivax\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e123\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMixed infection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e221 (81.5%)\u003c/p\u003e\u003cp\u003e\u003cem\u003e(P. falciparum\u003c/em\u003e positives including mixed infection)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e120 (82.2%)\u003c/p\u003e\u003cp\u003e\u003cem\u003e(P. vivax\u003c/em\u003e positives including mixed infection)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe agreement between nested PCR results from DBS and RDT samples was assessed separately for the two parasite species, revealing a notable difference in DNA detection rates between \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. vivax\u003c/em\u003e (Tables\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). For \u003cem\u003eP. falciparum\u003c/em\u003e samples extracted from RDTs, the DNA detection rate was 89.2% (95% CI: 84.7\u0026ndash;92.5), whereas for \u003cem\u003eP. vivax\u003c/em\u003e samples, the rate was 81.9% (95% CI: 74.6\u0026ndash;87.6) when compared with DNA extracted from DBS samples.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAgreement between nested PCR results of DBS and RDT extracted samples for \u003cem\u003eP. falciparum\u003c/em\u003e detection based on 2x2 contingency table (n\u0026thinsp;=\u0026thinsp;271)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMicroscope positive \u003cem\u003eP. falciparum\u003c/em\u003e\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;271)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003ePCR result of the DBS extracted samples\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCR result of the RDT extracted samples\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositives\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e221\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e271\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003e95% confidence interval\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSummary statistics\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLower limit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUpper limit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSensitivity (detection rate)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e89.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e84.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e92.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiagnostic accuracy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e88.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e84.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e91.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAgreement between PCR results of DBS and RDT extracted samples for \u003cem\u003eP.vivax\u003c/em\u003e detection based on 2x2 contingency table (n\u0026thinsp;=\u0026thinsp;146)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMicroscope positive \u003cem\u003eP. vivax\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;146)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003ePCR result of DBS extracted samples\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCR result of the RDT extracted samples\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositives\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e146\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003e95% confidence interval\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSummary statistics\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLower Limit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUpper Limit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSensitivity (detection rate)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e81.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e87.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiagnostic Accuracy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e76.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e82.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e The agreement between PCR results from RDT-extracted and DBS-extracted samples was evaluated across parasite load categories (high, medium, and low) using SPSS. The agreement within the low parasite load category was lower (Kappa value\u0026thinsp;=\u0026thinsp;0.58) than within the medium (Kappa value\u0026thinsp;=\u0026thinsp;0.77) and high (Kappa value\u0026thinsp;=\u0026thinsp;0.75) parasite load categories. However, the overall Kappa value was 0.64 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cb\u003eDetection of mixed infection of\u003c/b\u003e \u003cb\u003eP. falciparum\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eP. vivax\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAlthough all the samples analyzed were identified as mono-infections using a microscope at the health centers, the nested PCR result showed a mixed infection of \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. vivax.\u003c/em\u003e From the total of 417 paired samples of RDT and DBS, 33 (7.9%) of the DBS-extracted samples and 10 (2.4%) of the RDT-kit-extracted samples were found to be mixed infections of \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. vivax.\u003c/em\u003e Eight of the 33 mixed infections detected from DBS samples, were also detected by RDT extracted samples. The sensitivity (detection rate) for detecting mixed infection in samples extracted from RDT was 24.2% (95% CI: 12.8, 42.0).\u003c/p\u003e\u003cp\u003e\u003cb\u003eAmplification success rate for\u003c/b\u003e \u003cb\u003eP. falciparum\u003c/b\u003e \u003cb\u003edrug resistance gene (\u003c/b\u003e\u003cb\u003epfmdr1)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAmplification of the \u003cem\u003epfmdr1\u003c/em\u003e gene by nested PCR was performed on 65 paired samples of RDT and DBS to determine whether RDT-extracted DNA was equivalent to that of DBS-extracted DNA. From the 65 paired samples, 100% (65/65) of DBS extracted DNA and 96.7% (63/65) of RDT extracted DNA were amplified using nested PCR and visualized by gel electrophoresis. The calculated sensitivity was 96.92% (95% CI: 89.5\u0026ndash;99.2).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe principal finding of this study is that DNA extracted from used rapid diagnostic test (RDT) kits collected from health centers in the Gamo Zone, Ethiopia, demonstrated performance comparable to that of DNA extracted from DBS on filter paper. When DBS samples were used as the reference standard, RDT-derived DNA showed a higher detection rate for \u003cem\u003eP. falciparum\u003c/em\u003e than for \u003cem\u003eP. vivax\u003c/em\u003e. This difference likely reflects the typically higher parasite densities observed in \u003cem\u003eP. falciparum\u003c/em\u003e infections compared with those of \u003cem\u003eP. vivax\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eRDTs offer significant advantages for malaria diagnosis, as they are widely used and allow health professionals or health extension workers to store used test kits and send them to regional laboratories. These used RDTs provide a valuable source of DNA for molecular surveillance of malaria parasites and antimalarial drug resistance. This approach enables periodic molecular monitoring without requiring additional resources or specialized training for health workers in remote settings [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe WHO recommends delivering DBS samples to molecular laboratories within 15 days; for longer preservation, storage at \u0026minus;\u0026thinsp;20\u0026deg;C or \u0026minus;\u0026thinsp;80\u0026deg;C is advised. In this study, however, samples were kept at room temperature for 35\u0026ndash;71 days before being transferred to \u0026minus;\u0026thinsp;40\u0026deg;C storage. Previous studies have reported that storage for up to six months does not significantly affect the quality of parasite DNA or the success rates of amplification [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Nonetheless, extended storage may reduce both the quality and quantity of DNA [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Moreover, drug resistance genes have been successfully identified from RDT kit samples stored for 3\u0026ndash;9 months, although with a lower amplification success rate [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Another study apparently showed that samples stored for 6 to 32 months had a similar amplification success rate of \u003cem\u003eP. falciparum\u003c/em\u003e molecular markers [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile RDTs are useful, they have several significant limitations for comprehensive surveillance and analysis. As a single-use sample source, RDTs do not allow for the re-extraction of DNA for confirmatory testing if needed [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Additionally, processing large sample volumes is complicated by the labor-intensive requirement of manually opening through the hard plastic casing to access the nitrocellulose strip inside, as mentioned in another study [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe performance of samples obtained from RDT kits for amplification of the \u003cem\u003epfmdr1\u003c/em\u003e drug resistance gene was comparable to that of filter paper DBS. This finding aligns with a previous study conducted in Sweden, which used samples collected from Zanzibar [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These results suggest that RDT kits can serve as reliable tools for collecting samples in drug resistance surveillance studies.\u003c/p\u003e\u003cp\u003eThe small sample size resulting from the initial exclusion criteria may render the findings about mixed infection less reliable.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe present study demonstrated that used RDT kits could serve as an alternative and reliable source of \u003cem\u003ePlasmodium\u003c/em\u003e parasite DNA for molecular surveillance and drug resistance monitoring in settings where RDTs are used routinely for malaria diagnosis. Archived RDT kits provide a practical option for large scale studies focusing on \u003cem\u003eP. falciparum\u003c/em\u003e, making them valuable for molecular surveillance. Further study is recommended to investigate the effectiveness of DNA samples extracted from used RDT kit for detection of mixed infections of \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. vivax\u003c/em\u003e.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eRDT\u0026nbsp;\u003c/strong\u003eRapid Diagnostic Test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDBS\u0026nbsp;\u003c/strong\u003eDried Blood Sample\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePCR\u0026nbsp;\u003c/strong\u003ePolymerase Chain Reaction\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA\u0026nbsp;\u003c/strong\u003eDeoxyribonucleic Acid\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgements\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eWe acknowledge the management staff of the health center for their support in facilitating the data collection process. We also thank the laboratory technicians at the health centers for their collaboration during the sample collection. Most importantly, we recognize the study participants for their willingness to provide samples and share information. Additionally, we extend our thanks to Mr. Alemayehu Letebo for his technical assistance during the molecular laboratory work.\u003c/p\u003e\n\u003ch2\u003eAuthors' contributions\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eB.T: Conceptualization, methodology, writing the manuscript, data collection, laboratory work and data analysis. B.W: Methodology, field supervision, reviewing and editing the manuscript. G.T: Laboratory work. B.L: Conceptualization, reviewing and editing the manuscript, supervision, methodology. F.M: Conceptualization, reviewing and editing the manuscript, methodology, laboratory supervision and field supervision.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding: This study received funding from the Norwegian Program for Capacity Development in Higher Education and Research for Development (Grant No. QZA-21/0162).\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe datasets used in this study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch2\u003eEthics approval and consent to participate\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eEthical approval for the study was obtained from the Arba Minch University Institutional Review Board, with reference number IRB/23127/2024. Written consent was obtained from all participants or their guardians in the case of minors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication: Not applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interests: None to declare\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLi J, Docile HJ, Fisher D, Pronyuk K, Zhao L. Current Status of Malaria Control and Elimination in Africa: Epidemiology, Diagnosis, Treatment, Progress and Challenges. J Epidemiol Glob Health. 2024;14:561\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFountain A, Ye Y, Roca-Feltrer A, Alexander K, Rowe, Camara A, Fofana A, et al. Surveillance as a Core Intervention to Strengthen Malaria Control Programs in Moderate to High Transmission Settings. Am J Trop Med Hyg. 2023;108:8\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLouren\u0026ccedil;o C, Tatem AJ, Atkinson PM, Cohen JM, Pindolia D, Bhavnani D, et al. Strengthening surveillance systems for malaria elimination: a global landscaping of system performance, 2015\u0026ndash;2017. Malar J. 2019;18:315.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOladipo HJ, Tajudeen YA, Oladunjoye IO, Yusuff SI, Yusuf RO, Oluwaseyi EM, et al. Increasing challenges of malaria control in sub-Saharan Africa: Priorities for public health research and policymakers. Ann Med Surg. 2022;81:104366.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMayor A, Ishengoma DS, Proctor JL, Verity R. Sampling for malaria molecular surveillance. Trends Parasitol. 2023;39:954\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStabler TC, Hosch S, Nyakarungu E, Giger JN, Elonga MK, Bibang RN, et al. Integrating local malaria molecular monitoring into regular malaria indicator surveys on Bioko Island: high association between urban communities and low-density infections. Malar J. 2025;24:145.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNsanzabana C. Time to scale up molecular surveillance for anti-malarial drug resistance in sub-saharan Africa. Malar J. 2021;20:401.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHan KT, Han ZY, Zainabadi K. Developing Molecular Surveillance Capacity for Asymptomatic and Drug-Resistant Malaria in a Resource-Limited Setting\u0026mdash;Experiences and Lessons Learned. Am J Trop Med Hyg. 2022;107:222\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDada N, Simpson VJ, Amenga-Etego LN, Oriero E, Miotto O, Torok ME, et al. Towards integrated malaria molecular surveillance in Africa. Trends Parasitol. 2024;40:964\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNain M, Sinha A, Sharma A. Dried blood spots: a robust tool for malaria surveillance in countries targeting elimination. J Vector Borne Dis. 2023;60:11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKerr G, Wini L, Leaburi J, Macdonald J, Russell TL. Utility of rapid diagnostic tests and microscopy to detect malaria in health facilities across the Solomon Islands. Malar J. 2025;24:219.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuirou EA, Schindler T, Hosch S, Donfack OT, Yoboue CA, Kr\u0026auml;henb\u0026uuml;hl S, et al. Molecular malaria surveillance using a novel protocol for extraction and analysis of nucleic acids retained on used rapid diagnostic tests. Sci Rep. 2020;10:12305.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCnops L, Boderie M, Gillet P, Van Esbroeck M, Jacobs J. Rapid diagnostic tests as a source of DNA for Plasmodium species-specific real-time PCR. Malar J. 2011;10:67.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNag S, Ursing J, Rodrigues A, Crespo M, Krogsgaard C, Lund O, et al. Proof of concept: used malaria rapid diagnostic tests applied for parallel sequencing for surveillance of molecular markers of anti-malarial resistance in Bissau, Guinea-Bissau during 2014\u0026ndash;2017. Malar J. 2019;18:252.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMorris U, Aydin-Schmidt B, Shakely D, M\u0026aring;rtensson A, J\u0026ouml;rnhagen L, Ali AS, et al. Rapid diagnostic tests for molecular surveillance of Plasmodium falciparum malaria -assessment of DNA extraction methods and field applicability. Malar J. 2013;12:106.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIshengoma DS, Lwitiho S, Madebe RA, Nyagonde N, Persson O, Vestergaard LS, et al. 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Malar J. 2023;22:281.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSnounou G, Singh B, Nested. PCR Analysis of Plasmodium Parasites. Malar Methods Protoc. New Jersey: Humana; 2002. pp. 189\u0026ndash;204.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSullivan KM, Dean A, Soe MM, OpenEpi. A Web-based Epidemiologic and Statistical Calculator for Public Health. Public Health Rep. 2009;124:471\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcHugh ML. Interrater reliability: the kappa statistic. Biochem Med. 2012;22:276\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSim J, Wright CC. The Kappa Statistic in Reliability Studies: Use, Interpretation, and Sample Size Requirements. Phys Ther. 2005;85:257\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNguyen TT, Nzigou Mombo B, Lalremruata A, Koehne E, Zoleko Manego R, Dimessa Mbadinga LB, et al. DNA recovery from archived RDTs for genetic characterization of Plasmodium falciparum in a routine setting in Lambar\u0026eacute;n\u0026eacute;, Gabon. Malar J. 2019;18:336.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAndrianaranjaka VHI, Ravaoarisoa E, Rakotomanga TA, Ralinoro F, Rakoto DAD, Randrianarivo RH, et al. DNA recovery from used malaria RDT to detect Plasmodium species and to assess Plasmodium falciparum genetic diversity: a pilot study in Madagascar. Malar J. 2022;21:227.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShittu O, Iyiola O, Olufunke O, Olusola A, Chukwuka G, Adekunle M, et al. Enumerating the Yield and Purity of PfDNA from Archived, Newly Used mRDTs and Comparison with DBS from a Malaria-Endemic Focus. Acta Med Marisiensis. 2020;66:2.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSrisutham S, Suwannasin K, Mathema VB, Sriprawat K, Smithuis FM, Nosten F, et al. 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Malar J. 2020;19:193.\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":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Used RDT kit, Molecular malaria surveillance, Drug resistance monitoring, DBS on filter paper","lastPublishedDoi":"10.21203/rs.3.rs-8080012/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8080012/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eMolecular surveillance of malaria and drug resistance monitoring typically use dried blood samples (DBS) on filter papers. However, the use of Rapid Diagnostic Test (RDT) kits presents a promising yet unexplored alternative DNA source. This study aimed to assess the efficiency of DNA recovery from used RDT kits for molecular malaria surveillance and drug resistance monitoring by comparing its performance with the conventional filter paper DBS method.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eFour hundred seventeen paired samples of RDT kits and DBS on filter paper were collected from malaria-positive cases at six health centers in the Gamo Zone of southern Ethiopia. DNA was extracted from both sample types using the Chelex-100 method, followed by nested polymerase chain reaction (PCR) targeting the 18S rRNA gene. Amplification of the 65 paired sub-samples of RDT and DBS-extracted DNA was carried out for the anti-malarial drug resistance gene, \u003cem\u003epfmdr1\u003c/em\u003e. Nested PCR results from the two sample sources were compared using a 2 by 2 contingency table, along with diagnostic accuracy measures and Cohen\u0026rsquo;s Kappa agreement analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOf 417 paired samples, 391 (93.8%) of the DBS-extracted samples and 349 (83.7%) of the RDT-extracted samples were positive for malaria parasites using nested PCR. The diagnostic accuracy of samples extracted from RDT for detecting the \u003cem\u003ePlasmodium\u003c/em\u003e parasite was 87.1% (95% Confidence Interval (CI): 83.5\u0026ndash;89.9). The sensitivity of samples extracted from RDT for \u003cem\u003eP. falciparum\u003c/em\u003e detection was 89.2% (95% CI: 84.7\u0026ndash;92.5), while it was 81.9% (95% CI: 74.6\u0026ndash;87.6) for \u003cem\u003eP. vivax\u003c/em\u003e. The overall Kappa value for the agreement between nested PCR results from DBS and RDT-extracted samples was 0.64 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This agreement was more pronounced (a Kappa value of 0.75; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in patients with high parasite load (\u0026gt;\u0026thinsp;100,000/\u0026micro;l). The amplification success rate for the \u003cem\u003epfmdr1\u003c/em\u003e gene was 100% (65/65) for DBS samples and 96.7% (63/65) for the samples from RDT kits.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eUsed RDT kits can serve as an alternative DNA source and may be utilized for molecular surveillance of malaria and monitoring drug resistance.\u003c/p\u003e","manuscriptTitle":"Rapid diagnostic test kit as a source of DNA in comparison with filter paper for malaria molecular surveillance and drug resistance monitoring: A cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-12 08:34:33","doi":"10.21203/rs.3.rs-8080012/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-14T05:09:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-02T14:43:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"262860725555474610146795298638651868436","date":"2026-02-02T07:22:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-22T14:03:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8502684474979177407188377606011008275","date":"2025-12-22T13:57:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"329939238390485582959878450917226058987","date":"2025-12-19T10:14:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-09T01:02:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-11T11:42:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-11T11:42:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Malaria Journal","date":"2025-11-10T18:48:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e5bbbe3c-470f-43cc-b30e-aedaa3f5f38d","owner":[],"postedDate":"December 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-30T02:25:44+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-12 08:34:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8080012","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8080012","identity":"rs-8080012","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}