Malaria diagnostic update: From conventional to advanced method

Enhanced slime mould algorithm with chaotic and orthogonal optimization-based learning for improved severity prediction accuracy in malaria patient outcomes

Malaria remains a critical health challenge in developing countries, particularly in Africa, where it disproportionately affects vulnerable populations. Accurate malaria severity prediction is important for proper treatment and improved patient survival rates. This study proposes an improved Slime Mould Algorithm (iSMA) to address the limitations of the standard SMA, including slow convergence, poor initialization, local optima entrapment, and imbalance between exploration and exploitation. The iSMA incorporates four key innovations: a Chaotic Initialization Strategy (CIS) to generate a diverse initial population, enhancing solution diversity; an enhanced Opposition-Based Learning (eOBL) mechanism to strengthen exploration; an Orthogonal Learning (OL) strategy to improve the balance between exploration and exploitation while accelerating convergence; and a Restart Strategy (RS) to reinitialize underperforming individuals, effectively preventing entrapment in local optima. Integrating the Random Forest (RF) feature selection process with the Support Vector Machine (SVM) classifier, forming the proposed new model RF-iSMA-SVM, classifies malaria into severe and no-severe cases. The iSMA performed better than nine other recent metaheuristic algorithms, as was broadly exhibited in the benchmark tests conducted on CEC2022 functions. When testing the RF-iSMA-SVM model on malaria datasets from health centers in Sierra Leone, the proposed model demonstrated superior predictive performance compared to recent conventional methods. The results yield an accuracy value of 0.981, specificity of 0.827, sensitivity of 0.974, and a Matthews Correlation Coefficient (MCC) score of 0.794. This shows the significant improvement over the standard techniques used for predicting the severity of malaria, which indicates great potential for healthcare practices and decision-making. These results support the model's reliability and effectiveness in improving the prediction of malaria severity. This study offers a novel practical tool for malaria case management by combining advanced optimization techniques with machine learning. It could enhance healthcare decision-making and improve outcomes for affected populations.

Plasmodium cynomolgi: potential emergence of new zoonotic malaria in Southeast Asia

The reported cases of Plasmodium cynomolgi in Southeast Asia pose a significant public health concern. Sporadic reports of human Plasmodium cynomolgi infections have increased in the past few years, raising attention regarding its potential impact on human populations. Further compounding this issue are the morphological similarities between P. cynomolgi and the human malaria parasite Plasmodium vivax, which may lead to misdiagnosis and underreporting of P. cynomolgi infections. Both in vitro and in vivo studies have shown that P. cynomolgi can effectively invade human reticulocytes using mechanisms like those employed by P. vivax, underscoring its capacity to infect human hosts if given the opportunity. These studies collectively highlight the parasite's potential to establish infections in humans and emphasize the need for molecular diagnostic tools to accurately detect P. cynomolgi. Additionally, challenges in accurate diagnosis and surveillance systems may underestimate the true extent of their impact, making it imperative for healthcare authorities to bolster monitoring efforts and deploy targeted interventions. Strengthening surveillance, improving diagnostic capabilities, and developing targeted vector control strategies are crucial to mitigating the risk of P. cynomolgi becoming a major zoonotic disease like its counterpart, Plasmodium knowlesi. Thus, this review aims to highlight the current understanding of P. cynomolgi infections in human, vector, and macaque hosts based on collated data from previous studies while underscoring the urgent need for enhanced surveillance, accurate diagnostic tools, and effective vector control strategies to mitigate its potential as a significant zoonotic threat in Southeast Asia.

Unveiling the silent threat: Investigating asymptomatic plasmodium infections in Gorgora, Ethiopia through microscopy and loop-mediated isothermal amplification

BACKGROUND

The asymptomatic carriers of the Plasmodium parasite represent a large hidden reservoir of Plasmodium species. These individuals can carry microscopically detectable levels and sub-microscopic levels of Plasmodium parasitemia. As a result, the use of clinical diagnostic methods, such as Rapid Diagnosis Tests (RDTs) and Giemsa microscopy leads to underestimation of the burden of asymptomatic malaria. Thus, the use of highly sensitive molecular methods such as loop-mediated isothermal amplification techniques (LAMP) helps to overcome these limitations and is crucial to reporting the true burden of the disease.

OBJECTIVE

This study aimed to determine the prevalence of Asymptomatic Plasmodium infections (APIs), and evaluate light microscopy for the detection of APIs using the LAMP method as a reference in Gorgora, Western Dembia district, Northwest Ethiopia.

METHOD

A community-based cross-sectional survey was carried out from May 17 to June 30, 2023, among households located in particular kebeles at Gorgora. The study participants were chosen using a multi-stage sampling technique. One Hundred Fifteen households and one household member from each household were selected using systematic random and simple random sampling techniques, respectively. To gather sociodemographic data, semi-structured questionnaires were used. Capillary blood samples were obtained from each study participant and screened for Plasmodium species infections using a LAMP kit and light microscopy. The data were entered into Epi Data version 4.6 and exported to SPSS version 25 for analysis.

RESULTS

The prevalence of APIs through light microscopy examination and LAMP analysis was 6.1% (95%CI: 2.5-12.1) and 11.3% (95%CI: 6.2-18.6) respectively. Using LAMP as a reference, the sensitivity and specificity of microscopy were 53.8% and 100% respectively. Microscopy examination missed six Plasmodium infections that were positive by LAMP analysis. A measure of agreement between LAMP and Microscopy was found to be 0.67(k = 0.67).

CONCLUSIONS

A significant proportion of APIs was found which likely act as a reservoir of transmission. This study also showed a significant number of APIs were missed by microscopy techniques. Thus, efforts to control and eliminate malaria should also consider these sub-microscopic infections.

Addressing low-density malaria infections in India and other endemic part of the world-the opportune time?

Shifting from high- to low-malaria transmission accompanies a higher proportion of asymptomatic low-density malaria infections (LDMI). Currently, several endemic countries, such as India, are experiencing this shift as it is striving to eliminate malaria. LDMI is a complex concept for which there are several important questions yet unanswered on its natural history, infectiousness, epidemiology, and pathological and clinical impact. India is on the right path to eliminating malaria, but it is facing the LDMI problem. A brief discussion on the concept and definitions of LDMI is beforehand presented. Also, an exhaustive review and critical analysis of the existing literature on LDMI in malaria-endemic areas, including India, are included in this review. Finally, we opine that addressing LDMI in India is ethically and pragmatically achievable, and a pool of sine qua non conditions is required to efficiently and sustainably eliminate malaria.

Asymptomatic malaria infections and associated risk factors in malaria-eliminating settings of Nong District, Savannakhet Province, Lao People's Democratic Republic

BACKGROUND

As the Lao People's Democratic Republic is nearing malaria elimination, asymptomatic malaria infections remain a challenge to address. Control measures focusing on symptomatic persons do not effectively work for asymptomatic infections which often go undetected by conventional diagnostic tools. It is therefore crucial to understand the burden of asymptomatic malaria for tailored interventions to eliminate the disease. This study assessed the prevalence of asymptomatic malaria infections with associated risk factors in an endemic district of Savannakhet province.

METHODS

In March 2024, a cross-sectional study was conducted in three villages of Nong District. Blood samples were collected from the fingertips of the participants for Plasmodium parasite identification using microscopy and Loop-mediated Isothermal Amplification (LAMP); those aged 13 years and above were also interviewed. Mann-Whitney U test and Fisher's exact test were performed to compare the medians of different age and temperature groups and determine the association between predictor variables and outcome variables respectively.

RESULTS

A total of 622 individuals participated in this survey; Plasmodium parasites were detected in 2.1% (13/622) of participants. The prevalence of asymptomatic malaria was 1.8% (11/622). Plasmodium vivax accounted for 15.4% (2/13) of all positive cases. The remaining species could not be identified. Farmers aged 15 years and above accounted for 81.8% of the asymptomatic infections. Ninety percent (90%) of the participants used bed nets in the village. Among interviewed participants, 23.6% reported not using mosquito bed nets in the forest; 21.3% of the participants who had been to the forest were nighttime forest workers.

CONCLUSIONS

This study revealed a prevalence of 1.8% of asymptomatic malaria infections in the study areas with the majority of the infections clustered among farmers, and an important proportion of these populations not using protective measures in the forest. These findings showed that malaria reservoirs are notable with a lack of use of protective measures, which could threaten malaria control and elimination efforts. Therefore, malaria elimination in Lao PDR by 2030 would need interventions targeting high-risk adult populations for screening with sensitive tools coupled with sensitization on protective measures and asymptomatic malaria.

Exploring Biomarkers for Malaria: Advances in Early Detection and Asymptomatic Diagnosis

Malaria is a tropical disease caused by the Plasmodium parasite, which was responsible for 249 million cases worldwide in 2022. Malaria is currently diagnosed using RDTs, PCR-based methods, or blood smear microscopy. Ideal biomarkers have been identified for malaria, with the potential for improving treatment, diagnosis, and overall clinical outcomes. This review discusses the types of existing biomarkers and the opportunities for new biomarkers to be used as diagnostic components in detecting Plasmodium, including in terms of sensitivity, detection limit, specificity, and the species of Plasmodium that can be detected. Following a comparison, five main ideal malaria biomarkers were identified, namely HRP2, pLDH, hemozoin, aldolase, and pGDH. These biomarkers distinguished themselves markedly from the others in terms of specificity in Plasmodium detection, sensitivity in analysis, and the use of non-invasive samples. Several other biomarkers, such as CRP, Ang-1, Ang-2, and PCT, show potential for malaria detection in terms of their ability to differentiate disease severity, and the levels of these biomarkers can be determined in the body for comparison with malaria parasitemia. Of the five ideal biomarkers, hemozoin and aldolase can still be developed regarding the types of samples used and their sensitivity to different Plasmodium species. Further research on the biomarkers CRP, Ang-1, Ang-2, and PCT is still needed to evaluate their potential.

Analysis of diagnostic biomarkers for malaria: Prospects on rapid diagnostic test (RDT) development

Accurate malaria diagnosis remains a formidable challenge in remote regions of malaria-endemic areas globally. Existing diagnostic methods predominantly rely on microscopy and rapid diagnostic tests (RDTs). While RDTs offer advantages such as rapid results and reduced dependence on highly skilled technicians compared to microscopy, persistent challenges emphasize the critical need to identify novel diagnostic biomarkers to further enhance RDT based malaria diagnosis. This comprehensive review presents a range of promising diagnostic targets. These targets could be useful in developing more robust, accurate, and effective diagnostic tools. Such tools are crucial for the detection of the Plasmodium falciparum (P.falcipaum) malaria parasite. The potential biomarkers discussed here significantly address the challenges posed by HRP2 gene deletion in P.falciparum. Researchers, RDT manufacturers, industrial and other stakeholders involved in malaria diagnosis can harness the crucial information described in this article, to drive the development of advanced RDTs as viable alternatives. By diversifying the available tools for diagnosis, we can attempt to enhance our ability to knock out malaria effectively and contribute to better health outcomes for people residing in malaria-endemic regions. This review serves as a valuable resource for advancing research and development in the field of malaria diagnostics, ultimately aiding to the global fight against this devastating ancient disease.

Epidemiological characteristics and molecular identification of Plasmodium species among cases of imported malaria in Kuwait during the COVID-19 pandemic

Cases of imported malaria are reported each year in several malaria non-endemic countries, including Kuwait. PCR testing is the ideal method for identification of the infecting Plasmodium spp. The present study documented the epidemiologic characteristics of molecularly confirmed cases of imported malaria in Kuwait during the first year of COVID-19 pandemic. During the period from February 2020 to February 2021, 100 travelers with suspected malaria who had come from malaria-endemic countries of Africa (n = 60) and Asia (n = 40) were examined. Malaria diagnosis was made by microscopy of blood-stained smears and confirmed by a multiplex real-time PCR assay. Samples with discordant species identification results were sequenced. A total of 27 cases (27%) [P. falciparum, 14; P. vivax, 11; P. ovale, 1; mixed P. falciparum and P. malariae, 1] were detected, of whom 12 came to Kuwait for the first time and 15 were returning after visiting their home countries. Most of the returning travelers (12 out of 15 cases, 80%) had not received malaria chemoprophylaxis. Most cases of falciparum malaria (13/15) were Africans while most of the vivax cases (9/11) were Asians. Malaria was more common among subjects entering Kuwait for the first time (OR = 4.025, CI 1.07,15.1) and illiterates (OR = 13.8, CI 1.8,101.4). In conclusion, imported malaria caused mainly by P. falciparum and P. vivax was an ongoing problem during the COVID-19 pandemic. Travel history and education level were significant predictors of malaria among suspected cases.

A Pan Plasmodium lateral flow recombinase polymerase amplification assay for monitoring malaria parasites in vectors and human populations

Robust diagnostic tools and surveillance are crucial for malaria control and elimination efforts. Malaria caused by neglected Plasmodium parasites is often underestimated due to the lack of rapid diagnostic tools that can accurately detect these species. While nucleic-acid amplification technologies stand out as the most sensitive methods for detecting and confirming Plasmodium species, their implementation in resource-constrained settings poses significant challenges. Here, we present a Pan Plasmodium recombinase polymerase amplification lateral flow (RPA-LF) assay, capable of detecting all six human infecting Plasmodium species in low resource settings. The Pan Plasmodium RPA-LF assay successfully detected low density clinical infections with a preliminary limit of detection between 10-100 fg/µl for P. falciparum. When combined with crude nucleic acid extraction, the assay can serve as a point-of-need tool for molecular xenomonitoring. This utility was demonstrated by screening laboratory-reared Anopheles stephensi mosquitoes fed with Plasmodium-infected blood, as well as field samples of An. funestus s.l. and An. gambiae s.l. collected from central Africa. Overall, our proof-of-concept Pan Plasmodium diagnostic tool has the potential to be applied for clinical and xenomonitoring field surveillance, and after further evaluation, could become an essential tool to assist malaria control and elimination.

ISCCM Position Statement on the Management of Severe Malaria in Intensive Care Unit

Malaria is a worldwide health concern, but a great majority of cases occur in tropical countries like India. With almost 95% of Indian population living in malaria endemic regions, India contributes to most of the global malaria cases and deaths, outside of African countries. Despite significant advances towards malaria control and eradication, mortality associated with severe malaria remains particularly high. Changing epidemiology, vulnerable patient population, overlapping symptomatology, and limited availability of parenteral preparations of artemisinin derivatives pose significant challenges in management of severe malaria. Further, the dearth of large-scale randomized trials from the developing countries makes it difficult to establish evidence-based guidelines pertaining to their situation. Thus, this position paper aims to provide guidance to critical care physicians across the country on managing patients with severe malaria in intensive care units (ICUs).

HOW TO CITE THIS ARTICLE

Hegde A, Chhallani AK, Gupta B, Kadapatti K, Karnad D, Maheshwarappa HM, et al. ISCCM Position Statement on the Management of Severe Malaria in Intensive Care Unit. Indian J Crit Care Med 2024;28(S2):S59-S66.

Embedded-deep-learning-based sample-to-answer device for on-site malaria diagnosis

Improvements in digital microscopy are critical for the development of a malaria diagnosis method that is accurate at the cellular level and exhibits satisfactory clinical performance. Digital microscopy can be enhanced by improving deep learning algorithms and achieving consistent staining results. In this study, a novel miLab™ device incorporating the solid hydrogel staining method was proposed for consistent blood film preparation, eliminating the use of complex equipment and liquid reagent maintenance. The miLab™ ensures consistent, high-quality, and reproducible blood films across various hematocrits by leveraging deformable staining patches. Embedded-deep-learning-enabled miLab™ was utilized to detect and classify malarial parasites from autofocused images of stained blood cells using an internal optical system. The results of this method were consistent with manual microscopy images. This method not only minimizes human error but also facilitates remote assistance and review by experts through digital image transmission. This method can set a new paradigm for on-site malaria diagnosis. The miLab™ algorithm for malaria detection achieved a total accuracy of 98.86% for infected red blood cell (RBC) classification. Clinical validation performed in Malawi demonstrated an overall percent agreement of 92.21%. Based on these results, miLab™ can become a reliable and efficient tool for decentralized malaria diagnosis.

EasyNAT Malaria: a simple, rapid method to detect Plasmodium species using cross-priming amplification technology

Malaria infection remains a serious threat to human health worldwide. Rapid and accurate detection technology is crucial for preventing malaria transmission and minimizing damage. We aimed to establish and validate a new rapid molecular detection method for malaria, called EasyNAT Malaria Assay, targeting Plasmodium vivax, Plasmodium falciparum, Plasmodium ovale, and Plasmodium malariae. The analytical performance of EasyNAT Malaria Assay was determined using positive materials. We identified 42 clinical samples as malaria positive and 95 negative samples. Each sample was examined by four methods: light microscopy, rapid diagnostic test, EasyNAT Malaria Assay, and digital PCR. Diagnostic accuracy and clinical performance were evaluated. The limit of detection (LOD)95% of EasyNAT Malaria was consistently 40 parasites/mL. It specifically amplified Plasmodium and performed with reliable repeatability and reproducibility. In 137 clinical samples, EasyNAT Malaria detected four more positive samples than microscopic examination and two more positive samples than rapid diagnostic test (RDT). One clinical sample was positive only under digital PCR. However, no significant differences statistically in sensitivity or specificity were observed. Compared with microscopy, the total, positive, and negative concordance rates of EasyNAT were 97.08%, 100%, and 95.79%, respectively. Enhanced diagnostic accuracy of EasyNAT Malaria in patients who had taken anti-malarial medication before their clinical appointment was observed. The EasyNAT Malaria Assay has good detection efficiency for clinical samples, presents a promising molecular detection tool in clinical practice, and is particularly suitable for rapid screening of high-risk populations in the emergency room.

IMPORTANCE

This study established and validated EasyNAT Malaria Assay as a promising molecular detection tool for malaria screening of high-risk populations in clinical practice. This novel isothermal amplification method may effectively facilitate the rapid diagnosis of malaria and prevent its transmission.

Defining a malaria diagnostic pathway from innovation to adoption: Stakeholder perspectives on data and evidence gaps

Malaria, a major global health concern, requires effective diagnostic tools for patient care, disease control, and elimination. The pathway from concept to the adoption of diagnostic products is complex, involving multiple steps and stakeholders. To map this process, our study introduces a malaria-specific diagnostic pathway, synthesising existing frameworks with expert insights. Comprising six major stages and 31 related activities, the pathway retains the core stages from existing frameworks and integrates essential malaria diagnostic activities, such as WHO prequalification processes, global stakeholder involvement, and broader health systems considerations. To understand the scope and availability of evidence guiding the activities along this pathway, we conducted an online survey with 113 participants from various stages of the malaria diagnostic pathway. The survey assessed perceptions on four critical attributes of evidence: clear requirements, alignment with user needs, accuracy and reliability, and public and free availability. It also explored the types of evidence used and the challenges and potential solutions related to evidence generation and use. Respondents reported using a broad range of formal and informal data sources. Findings indicated differing levels of agreement on the attributes across pathway stages, with notable challenges in the Approvals and Manufacturing stage and consistent concerns regarding the public availability of data/evidence. The study offers valuable insights for optimising evidence generation and utilisation across the malaria diagnostic pathway. It highlights the need for enhanced stakeholder collaboration, improved data availability, and increased funding to support effective evidence generation, sharing, and use. We propose actionable solutions, including the use of public data repositories, progressive data sharing policies, open-access publishing, capacity-building initiatives, stakeholder engagement forums, and innovative funding solutions. The developed framework and study insights have broader applications, offering a model adaptable for other diseases, particularly for neglected tropical diseases, which face similar diagnostic challenges.

Comparative evaluation of the diagnostic accuracies of four different malaria rapid diagnostic test kits available in Ghana

Malaria rapid diagnostic test (mRDT) kit is one of the techniques for diagnosing malaria. Due to its inherent advantages over the microscopy technique, several brands of the kit have flooded malaria endemic countries, without prior in-country evaluation. Two of such mRDT kits are Oscar (India) and Standard Q (Korea Republic). In this study, the performance of Oscar and Standard Q mRDT kits were compared to First Response (India) and CareStart (USA) mRDTs, which have been evaluated and deployed for use approved by the Ministry of Health (MOH). In this comparative study, whole blood samples were collected from patients suspected of malaria. Plasmodium falciparum was detected in each sample using nested polymerase chain reaction (nPCR), microscopy and the four mRDTs. The sensitivities, specificities, accuracies, positive and negative predictive values and accuracies of the mRDTs were determined using nPCR as a reference technique. Kappa statistic was used to determine the level of agreement among the techniques. Two hundred (200) blood samples were analyzed in this study. The overall detection rates of P. falciparum by microscopy, First Response, CareStart, Oscar-PfHRP2, Standard Q mRDT kits and nPCR were 31.5%, 34.5%, 33.5%, 32%, 31% and 43% (x2 = 6.1, p = 0.046), respectively. The accuracies of CareStart and First Response were comparable (90.5% vs. 89.5%). Further, comparing their sensitivities, Oscar-PfHRP2 was 74.4% (95% confidence interval (CI): 63.9-83.2) while that of Standard Q was 72.1% (95% CI: 61.4-81.2), with comparable accuracies (Oscar-PfHRP2-89% and Standard Q -88%). Apart from First Response that was 98.3% specific, the others were 100% specific. Kappa test revealed perfect diagnostic agreement (κ = 0.90-0.98) among the four mRDTs. That notwithstanding, Oscar-PfHRP2 agreed better with CareStart (κ = 0.94) and First Response (κ = 0.92) compared to the agreement between Standard Q and, CareStart (κ = 0.92) and First Response (κ = 0.90). Taken together, the diagnostic performance of the four mRDT kits were statistically similar. That notwithstanding, new mRDT kits should be evaluated prior to deployment for use.

Unsuspected Malaria Diagnosed on a Routine Peripheral Smear Review

Prompt diagnosis of malaria infection is critical for effective management, yet it can be challenging due to varying incubation periods and the need for physician-initiated laboratory workups. We present a case of a 40-year-old male with fever and dark-colored urine, initially evaluated for sepsis. Plasmodium vivax was incidentally identified on a peripheral smear review after obtaining a remote travel history from a malaria-endemic area. Consultation with the Centers for Disease Control confirmed the diagnosis, emphasizing the importance of thorough travel history assessment and timely laboratory investigation in suspected cases of malaria. This case underscores the significance of early diagnosis in managing this potentially life-threatening infection.

Exploring mosquito abundance and Plasmodium infection through nested-PCR: implications for disease surveillance and control

The Plasmodium is responsible for malaria which poses a major health threat, globally. This study is based on the estimation of the relative abundance of mosquitoes, and finding out the correlations of meteorological parameters (temperature, humidity and rainfall) with the abundance of mosquitoes. In addition, this study also focused on the use of nested PCR (species-specific nucleotide sequences of 18S rRNA genes) to explore the Plasmodium spp. in female Anopheles. In the current study, the percentage relative abundance of Culex mosquitoes was 57.65% and Anopheles 42.34% among the study areas. In addition, the highest number of mosquitoes was found in March in district Mandi Bahauddin at 21 °C (Tmax = 27, Tmin = 15) average temperature, 69% average relative humidity and 131 mm rainfall, and these climatic factors were found to affect the abundance of the mosquitoes, directly or indirectly. Molecular analysis showed that overall, 41.3% of the female Anopheles pools were positive for genus Plasmodium. Among species, the prevalence of Plasmodium (P.) vivax (78.1%) was significantly higher than P. falciparum (21.9%). This study will be helpful in the estimation of future risk of mosquito-borne diseases along with population dynamic of mosquitoes to enhance the effectiveness of vector surveillance and control programs.

Molecular Research on Plasmodium Infection and Immunity

The WHO's global strategy for malaria targets a reduction of at least 90% of both incidence and mortality rates for 2030 [...].

Uncovering the diversity of pathogenic invaders: insights into protozoa, fungi, and worm infections

Post COVID-19, there has been renewed interest in understanding the pathogens challenging the human health and evaluate our preparedness towards dealing with health challenges in future. In this endeavour, it is not only the bacteria and the viruses, but a greater community of pathogens. Such pathogenic microorganisms, include protozoa, fungi and worms, which establish a distinct variety of disease-causing agents with the capability to impact the host's well-being as well as the equity of ecosystem. This review summarises the peculiar characteristics and pathogenic mechanisms utilized by these disease-causing organisms. It features their role in causing infection in the concerned host and emphasizes the need for further research. Understanding the layers of pathogenesis encompassing the concerned infectious microbes will help expand targeted inferences with relation to the cause of the infection. This would strengthen and augment benefit to the host's health along with the maintenance of ecosystem network, exhibiting host-pathogen interaction cycle. This would be key to discover the layers underlying differential disease severities in response to similar/same pathogen infection.

Comparison of Three Methods to Extract Plasmodium falciparum DNA from Whole Blood and Dried Blood Spots

This study aimed to compare the effectiveness of three DNA extraction methods: the GF-1 Blood DNA Extraction Kit (GF-1 BD Kit), which employs a spin column along with lysing and washing buffers; the tris-ethylenediaminetetraacetic acid and proteinase K (TE-pK) method, which utilizes a combination of TE buffer and proteinase K for cell lysis; and DNAzol® Direct (DN 131), a single reagent combined with heating for the extraction process. Plasmodium falciparum DNA was extracted from both whole blood and dried blook spots (DBSs), with consideration of DNA concentration, purity, cost, time requirement, and limit of parasite detection (LOD) for each method. The target gene in this study was 18S rRNA, resulting in a 395-bp product using specific primers. In the comparative analysis, the DN 131 method yielded significantly higher DNA quantities from whole blood and DBSs than the GF-1 BD Kit and TE-pK methods. In addition, the DNA purity obtained from whole blood and DBSs using the GF-1 BD Kit significantly exceeded that obtained using the TE-pK and DN 131 methods. For LOD, the whole blood extracted using the DN 131, GF-1 BD Kit, and TE-pK methods revealed 0.012, 0.012, and 1.6 parasites/µL, respectively. In the case of DBSs, the LODs for the DN 131, GF-1 BD Kit, and TE-pK methods were 1.6, 8, and 200 parasites/µL, respectively. The results revealed that the TE-pK method was the most cost-effective, whereas the DN 131 method showed the simplest protocol. These findings offer alternative approaches for extracting Plasmodium DNA that are particularly well-suited for large-scale studies conducted in resource-limited settings.

Molecular detection and identification of Plasmodium spp. isolated from captive-bred cynomolgus monkeys in Bogor, Indonesia

Background and Aim

Asian macaques are natural hosts of several Plasmodium species. Some monkey malaria parasites may infect humans and cause zoonotic infections. This study was conducted to estimate the prevalence of monkey malaria parasites in Bogor, Indonesia, based on molecular detection and identification, particularly in cynomolgus monkeys, which have a wide geographic distribution and share extensive habitats with humans. These data are needed to evaluate the status of simian malaria among macaques in Bogor and to study the potential risks to human health. These updated data will provide sufficient information for implementing malaria control strategies in the future and for developing a potential malaria vaccine using monkeys as an animal model.

Materials and Methods

Blood samples of 274 cynomolgus monkeys (Macaca fascicularis) were collected and identified using microscopy. DNA was extracted from positive blood samples and analyzed using polymerase chain reaction (PCR) to amplify the small subunit ribosomal RNA (SSU rRNA) target gene using consensus primers for Plasmodium species. The PCR-positive samples were then nucleotide-sequenced using commercial sequencing services, analyzed using the BioEdit program, and aligned using Basic Local Alignment Search Tool from the National Center for Biotechnology Information. Phylogenetic trees were constructed using MEGA 11.0 and the neighbor-joining (NJ) method to determine the kinship of Plasmodium. Bootstrapping was performed using 500 replicates to assess the robustness of tree topologies.

Results

Thirty-eight of the 274 microscopically positive samples for Plasmodium spp. were also positive using PCR, resulting in a 1640 bp amplicon. Further, analysis using nucleotide sequencing confirmed that these positive samples were Plasmodium inui with more than 99% nucleotide identity compared to GenBank sequences. Phylogenetic tree analysis of the SSU rRNA partial gene showed that all our isolates clustered and were closely related to a P. inui strain isolated from cynomolgus macaques in South China in 2011.

Conclusion

P. inui is the predominant malaria parasite in cynomolgus monkeys from Bogor.

The Laboratory Diagnosis of Malaria: A Focus on the Diagnostic Assays in Non-Endemic Areas

Even if malaria is rare in Europe, it is a medical emergency and programs for its control should ensure both an early diagnosis and a prompt treatment within 24-48 h from the onset of the symptoms. The increasing number of imported malaria cases as well as the risk of the reintroduction of autochthonous cases encouraged laboratories in non-endemic countries to adopt diagnostic methods/algorithms. Microscopy remains the gold standard, but with limitations. Rapid diagnostic tests have greatly expanded the ability to diagnose malaria for rapid results due to simplicity and low cost, but they lack sensitivity and specificity. PCR-based assays provide more relevant information but need well-trained technicians. As reported in the World Health Organization Global Technical Strategy for Malaria 2016-2030, the development of point-of-care testing is important for the improvement of diagnosis with beneficial consequences for prompt/accurate treatment and for preventing the spread of the disease. Despite their limitations, diagnostic methods contribute to the decline of malaria mortality. Recently, evidence suggested that artificial intelligence could be utilized for assisting pathologists in malaria diagnosis.

Diagnosis and management of malaria in the intensive care unit

Malaria is responsible for approximately three-quarters of a million deaths in humans globally each year. Most of the morbidity and mortality reported are from Sub-Saharan Africa and Asia, where the disease is endemic. In non-endemic areas, malaria is the most common cause of imported infection and is associated with significant mortality despite recent advancements and investments in elimination programs. Severe malaria often requires intensive care unit admission and can be complicated by cerebral malaria, respiratory distress, acute kidney injury, bleeding complications, and co-infection. Intensive care management includes prompt diagnosis and early initiation of effective antimalarial therapy, recognition of complications, and appropriate supportive care. However, the lack of diagnostic capacities due to limited advances in equipment, personnel, and infrastructure presents a challenge to the effective diagnosis and management of malaria. This article reviews the clinical classification, diagnosis, and management of malaria as relevant to critical care clinicians, highlighting the role of diagnostic capacity, treatment options, and supportive care.

iMAGING: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope

INTRODUCTION

Malaria is one of the most prevalent infectious diseases in sub-Saharan Africa, with 247 million cases reported worldwide in 2021 according to the World Health Organization. Optical microscopy remains the gold standard technique for malaria diagnosis, however, it requires expertise, is time-consuming and difficult to reproduce. Therefore, new diagnostic techniques based on digital image analysis using artificial intelligence tools can improve diagnosis and help automate it.

METHODS

In this study, a dataset of 2571 labeled thick blood smear images were created. YOLOv5x, Faster R-CNN, SSD, and RetinaNet object detection neural networks were trained on the same dataset to evaluate their performance in Plasmodium parasite detection. Attention modules were applied and compared with YOLOv5x results. To automate the entire diagnostic process, a prototype of 3D-printed pieces was designed for the robotization of conventional optical microscopy, capable of auto-focusing the sample and tracking the entire slide.

RESULTS

Comparative analysis yielded a performance for YOLOv5x on a test set of 92.10% precision, 93.50% recall, 92.79% F-score, and 94.40% mAP0.5 for leukocyte, early and mature Plasmodium trophozoites overall detection. F-score values of each category were 99.0% for leukocytes, 88.6% for early trophozoites and 87.3% for mature trophozoites detection. Attention modules performance show non-significant statistical differences when compared to YOLOv5x original trained model. The predictive models were integrated into a smartphone-computer application for the purpose of image-based diagnostics in the laboratory. The system can perform a fully automated diagnosis by the auto-focus and X-Y movements of the robotized microscope, the CNN models trained for digital image analysis, and the smartphone device. The new prototype would determine whether a Giemsa-stained thick blood smear sample is positive/negative for Plasmodium infection and its parasite levels. The whole system was integrated into the iMAGING smartphone application.

CONCLUSION

The coalescence of the fully-automated system via auto-focus and slide movements and the autonomous detection of Plasmodium parasites in digital images with a smartphone software and AI algorithms confers the prototype the optimal features to join the global effort against malaria, neglected tropical diseases and other infectious diseases.

A Systematic Review and Meta-Analysis Exploring Variations in Copper Levels between Individuals with Malaria and Uninfected Controls

Micronutrient insufficiency has been implicated in malaria pathogenesis. However, the role of copper in malaria remains inconclusive. This study aimed to investigate the association between copper levels and malaria pathogenesis, providing a deeper understanding of copper's role in the disease. A systematic review was conducted following the registered protocol in PROSPERO (CRD42023439732). Multiple databases, including Embase, MEDLINE, Ovid, PubMed, Scopus, and Google Scholar, were searched for relevant studies reporting blood copper levels in patients with malaria. The Joanna Briggs Institute critical appraisal checklist was used for assessing methodological quality. Qualitative and quantitative syntheses were employed, organizing, and summarizing the findings of the included studies. To calculate the standardized mean difference (Hedge's g) and 95% confidence intervals (CIs), a random-effects model was used. After screening the databases, 16 studies were included. Most studies (52.9%) reported that individuals with malaria had significantly higher copper levels than uninfected controls. The meta-analysis, based on 16 studies, showed no significant difference in copper levels between patients with malaria and uninfected controls overall (p = 0.39; Hedges' g, 0.38; 95% CI, -0.48 to 1.25; I2, 98.73%). Subgroup analysis showed a significant difference in copper levels between patients with malaria and uninfected controls among studies conducted in Asia (p < 0.01; Hedges' g, 1.74; 95% CI, 1.04 to 2.44; I2, 90.88%; five studies) and studies employing plasma blood samples (p < 0.01; Hedges' g, 1.13; 95% CI, 0.60 to 2.07; I2, 93.11%; four studies). The qualitative synthesis of the reviewed studies suggests a complex relationship between copper levels and malaria. The meta-analysis results showed no significant difference in copper levels between patients with malaria and uninfected controls overall. However, subgroup analyses based on various factors, including continent and blood sample type, showed copper level variations. These findings highlight the need for further research to better understand the role of copper in malaria pathogenesis by considering geographical factors and the blood sample type used for copper level measurement.

First field and laboratory evaluation of LAMP assay for malaria diagnosis in Cubal, Angola

BACKGROUND

Malaria is a globally distributed infectious disease. According to the World Health Organization, Angola is one of the six countries that account for over half the global malaria burden in terms of both malaria cases and deaths. Diagnosis of malaria still depends on microscopic examination of thin and thick blood smears and rapid diagnostic tests (RDTs), which often lack analytical and clinical sensitivity. Molecular methods could overcome these disadvantages. The aim of this study was to evaluate, for the first time to our knowledge, the performance of a loop-mediated isothermal amplification (LAMP) for the diagnosis of malaria in an endemic area in Cubal, Angola, and to assess the reproducibility at a reference laboratory.

METHODS

A total of 200 blood samples from patients attended at Hospital Nossa Senhora da Paz, Cubal, Angola, were analysed for Plasmodium spp. detection by microscopy, RDTs, and LAMP. LAMP assay was easily performed in a portable heating block, and the results were visualized by a simple colour change. Subsequently, the samples were sent to a reference laboratory in Spain to be reanalysed by the same colorimetric LAMP assay and also in real-time LAMP format.

RESULTS

In field tests, a total of 67/200 (33.5%) blood samples were microscopy-positive for Plasmodium spp., 98/200 RDT positive, and 112/200 (56%) LAMP positive. Using microscopy as reference standard, field LAMP detected more microscopy-positive samples than RDTs (66/67; 98% vs. 62/67; 92.5%). When samples were reanalysed at a reference laboratory in Spain using both colorimetric and real-time assays, the overall reproducibility achieved 84.5%.

CONCLUSIONS

This is the first study to our knowledge in which LAMP has been clinically evaluated on blood samples in a resource-poor malaria-endemic area. The colorimetric LAMP proved to be more sensitive than microscopy and RDTs for malaria diagnosis in field conditions. Furthermore, LAMP showed an acceptable level of reproducibility in a reference laboratory. The possibility to use LAMP in a real-time format in a portable device reinforces the reliability of the assay for molecular diagnosis of malaria in resource-poor laboratories in endemic areas.

Malaria misdiagnosis in the routine health system in Arba Minch area district in southwest Ethiopia: an implication for malaria control and elimination

BACKGROUND

Plasmodium falciparum and Plasmodium vivax are coendemic in Ethiopia, with different proportion in different settings. Microscopy is the diagnostic tool in Ethiopian health centres. Accurate species-specific diagnosis is vital for appropriate treatment of cases to interrupt its transmission. Therefore, this study assessed the status of species-specific misdiagnosis by microscope compared with polymerase chain reaction (PCR).

METHODS

A health facility based cross-sectional study was conducted from November 2019 to January 2020 in Kolla Shelle Health centre, Arba Minch Zuria district. The study population were suspected malaria cases, who visited the health centre for a diagnosis and treatment. Consecutive microscopy positive cases as well as a sample of microscopically negative cases were included for molecular analysis by polymerase chain reaction (PCR).

RESULTS

254 microscopically negative and 193 microscopically positive malaria suspects were included. Of the 193 malaria positive cases, 46.1% [95% confidence interval (CI) 38.9-53.4] (89/193) were P. falciparum infection, 52.3% (95% CI 45.0-59.5) (101/193) were P. vivax infection, and 1.6% (3/193) had mixed infection of P. falciparum and P. vivax. Of the microscopically positive cases of P. falciparum, 3.4% (3/89) were P. vivax and 11.2% (10/89) were mixed infections with P. falciparum and P. vivax and a single case was negative molecularly. Similarly, of the microscopically positive P. vivax cases, 5.9% (6/101) were P. falciparum and 1% (1/101) was mixed infection. Single case was negative by molecular technique. Of the 254 microscopically negative cases, 0.8% were tested positive for P. falciparum and 2% for P. vivax by PCR. Considering molecular technique as a reference, the sensitivity of microscopy for detecting P. falciparum was 89.2% and for P. vivax, it was 91.2%. The specificity of microscopy for detecting P. falciparum was 96.1% and for P. vivax, it was 97.7%. However, the sensitivity of microscopy in detecting mixed infection of P. falciparum and P. vivax was low (8.3%).

CONCLUSION

There were cases left untreated or inappropriately treated due to the species misidentification. Therefore, to minimize this problem, the gaps in the microscopic-based malaria diagnosis should be identified. It is recommended to regularly monitor the competency of malaria microscopists in the study area to improve species identification and diagnosis accuracy.

Seasonal Trends with the Comparison of Venous and Capillary Blood for Diagnosis of Malaria among Children in Karachi, Pakistan

Background

More than 250 million people are infected by malaria parasites annually while around one million children less than 5 years of age die every year due to malaria. We aimed to assess the seasonal trends and usefulness of capillary and venous blood for rapid diagnosis of malaria.

Methods

This cross-sectional study of 18 months duration was conducted at the National Institute of Child Health (NICH), Karachi. All patients reporting fever as chief complaint were recruited as study subjects. A semi-structured questionnaire was used to collect demographic information, presenting complaints, awareness of caregivers regarding malaria, preventive measures and history of malaria fever. Three ml Venous (2-3ml) as well as peripheral blood (3-4 drops) samples of all patients were collected for microscopy and rapid diagnostic tests (RDTs).

Results

Out of total 477 patients with fever Venous and Capillary Blood RDTs methods detected 33(6.9%) and 30(6.3%) as the malaria positive while Venous and Capillary Blood Microscopy detected 30(6.1%) and 32(6.7%) cases respectively. Plasmodium Vivax infection was the most prevalent (87.9%) and majority (39.39%) of the cases occurred in the quarter, July to September.

Conclusion

July to September is the peak season for malaria and P. Vivax (87.9%) is the predominant strain in Karachi. Venous and capillary blood are equally useful for malaria diagnosis however, convenience and less invasiveness may justify the preference of capillary blood over venous blood for early diagnosis of malaria.

Malaria Detection Using Advanced Deep Learning Architecture

Malaria is a life-threatening disease caused by parasites that are transmitted to humans through the bites of infected mosquitoes. The early diagnosis and treatment of malaria are crucial for reducing morbidity and mortality rates, particularly in developing countries where the disease is prevalent. In this article, we present a novel convolutional neural network (CNN) architecture for detecting malaria from blood samples with a 99.68% accuracy. Our method outperforms the existing approaches in terms of both accuracy and speed, making it a promising tool for malaria diagnosis in resource-limited settings. The CNN was trained on a large dataset of blood smears and was able to accurately classify infected and uninfected samples with high sensitivity and specificity. Additionally, we present an analysis of model performance on different subtypes of malaria and discuss the implications of our findings for the use of deep learning in infectious disease diagnosis.

CRISPR-Cas13 in malaria parasite: Diagnosis and prospective gene function identification

Malaria caused by Plasmodium is still a serious public health problem. Genomic editing is essential to understand parasite biology, elucidate mechanical pathways, uncover gene functions, identify novel therapeutic targets, and develop clinical diagnostic tools. Recent advances have seen the development of genomic diagnostic technologies and the emergence of genetic manipulation toolbox comprising a host of several systems for editing the genome of Plasmodium at the DNA, RNA, and protein level. Genomic manipulation at the RNA level is critical as it allows for the functional characterization of several transcripts. Of notice, some developed artificial RNA genome editing tools hinge on the endogenous RNA interference system of Plasmodium. However, Plasmodium lacks a robust RNAi machinery, hampering the progress of these editing tools. CRISPR-Cas13, which belongs to the VI type of the CRISPR system, can specifically bind and cut RNA under the guidance of crRNA, with no or minimal permanent genetic scar on genes. This review summarizes CRISPR-Cas13 system from its discovery, classification, principle of action, and diagnostic platforms. Further, it discusses the application prospects of Cas13-based systems in Plasmodium and highlights its advantages and drawbacks.

Molecular Method Is Essential to Identify Asymptomatic Malaria Reservoirs: A Successful Experience in the Malaria Elimination Program in Iran

Background: The accurate diagnosis of malaria cases, especially asymptotic and low-parasitemia patients, using robust molecular methods (nested-PCR) have been emphasized. The goal of this study was to detect active cases of malaria in areas with a history of local malaria transmission focusing on the use of molecular tools to ensure that the malaria elimination program has been implemented successfully. Methods: In this cross-sectional study, 816 blood samples were taken from immigrants and local residents of malaria-endemic areas in Hormozgan province, Iran. In order to identify asymptomatic malaria parasite reservoirs, the samples were examined using microscopic, RDT, and nested-PCR techniques. Results: About twelve positive asymptomatic malaria cases were identified when the molecular method (nested-PCR) was used. The positivity rates among immigrants and local residents were 2.07% and 0.93%, respectively. No positive cases were detected using microscopic and RDT methods. Conclusions: The finding of the research emphasize that in addition to microscopy and RDTs methods, sensitive molecular tools as a standard and essential strategy are needed in the diagnosis and detection of asymptomatic parasite reservoir.

Development of CRISPR-Mediated Nucleic Acid Detection Technologies and Their Applications in the Livestock Industry

The rapid rate of virus transmission and pathogen mutation and evolution highlight the necessity for innovative approaches to the diagnosis and prevention of infectious diseases. Traditional technologies for pathogen detection, mostly PCR-based, involve costly/advanced equipment and skilled personnel and are therefore not feasible in resource-limited areas. Over the years, many promising methods based on clustered regularly interspaced short palindromic repeats and the associated protein systems (CRISPR/Cas), i.e., orthologues of Cas9, Cas12, Cas13 and Cas14, have been reported for nucleic acid detection. CRISPR/Cas effectors can provide one-tube reaction systems, amplification-free strategies, simultaneous multiplex pathogen detection, visual colorimetric detection, and quantitative identification as alternatives to quantitative PCR (qPCR). This review summarizes the current development of CRISPR/Cas-mediated molecular diagnostics, as well as their design software and readout methods, highlighting technical improvements for integrating CRISPR/Cas technologies into on-site applications. It further highlights recent applications of CRISPR/Cas-based nucleic acid detection in livestock industry, including emerging infectious diseases, authenticity and composition of meat/milk products, as well as sex determination of early embryos.

Plasmodium malariae Detected by Microscopy in the International Bordering Area of Mizoram, a Northeastern State of India

Northeastern states of India share international borders with Myanmar, China, Bangladesh, and Bhutan, contributing 7.45% of the overall malaria cases in the country. Mizoram accounts for the highest malaria burden in the northeastern states, with perennial transmission in the hilly and deep-forested areas. Plasmodium falciparum (93%) is the most prevalent human Plasmodium species, followed by P. vivax; however, information on P. ovale and P. malariae is negligible. Rapid diagnostic tests (RDTs) are the most preferred malaria diagnostic tool followed by microscopy in this high malaria-endemic region. The present epidemiological study was carried out in July and August 2019 to assess the malaria burden in and around the Chawngte primary health center, Lawngtlai District of Mizoram, using RDTs and microscopy as diagnostic tools. World Health Organization-certified level I microscopists examined the blood smears. Diagnosis using RDTs resulted in 151 malaria cases (P. falciparum: 136; P. vivax: 15) out of 948 screened fever cases. However, blood smear examination detected 179 cases (P. falciparum: 154; P. vivax: 17; mixed P. falciparum + P. vivax infection: 3; P. malariae: 5). Analysis revealed that the risk of malaria infection was higher in the ≥5-year-old subjects than in the under-5 age group. The mean parasite density of P. malariae (1455.00/μL blood) was the lowest; cf. with P. falciparum: 12,275.08/μL blood. Surveillance at the point-of-care level using microscopy was able to detect all the four human Plasmodium species and their mixed infections, including P. malariae, which were missed with RDTs. Thus, the quality of microscopy along with trained manpower should be strengthened to diagnose all human malaria parasite species (particularly P. malariae and P. ovale) until the molecular tools are deployed at the field level to achieve malaria elimination by 2030.

Field Evaluation of a Hemozoin-Based Malaria Diagnostic Device in Puerto Lempira, Honduras

The diagnosis of malaria in Honduras is based mainly on microscopic observation of the parasite in thick smears or the detection of parasite antigens through rapid diagnostic tests when microscopy is not available. The specific treatment of the disease depends exclusively on the positive result of one of these tests. Given the low sensitivity of conventional methods, new diagnostic approaches are needed. This study evaluates the in-field performance of a device (Gazelle™) based on the detection of hemozoin. This was a double-blind study evaluating symptomatic individuals with suspected malaria in the department of Gracias a Dios, Honduras, using blood samples collected from 2021 to 2022. The diagnostic performance of Gazelle™ was compared with microscopy and nested 18ssr PCR as references. The sensitivity and specificity of Gazelle™ were 59.7% and 98.6%, respectively, while microscopy had a sensitivity of 64.9% and a specificity of 100%. The kappa index between microscopy and Gazelle™ was 0.9216 using microscopy as a reference. Both methods show similar effectiveness and predictive values. No statistical differences were observed between the results of the Gazelle™ compared to light microscopy (p = 0.6831). The turnaround time was shorter for Gazelle™ than for microscopy, but the cost per sample was slightly higher for Gazelle™. Gazelle™ showed more false-negative cases when infections were caused by Plasmodium falciparum compared to P. vivax. Conclusions: The sensitivity and specificity of Gazelle™ are comparable to microscopy. The simplicity and ease of use of the Gazelle™, the ability to run on batteries, and the immediacy of its results make it a valuable tool for malaria detection in the field. However, further development is required to differentiate Plasmodium species, especially in those regions requiring differentiated treatment.