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Background Severe malaria (SM) is a fatal multi-system disease which accounted for an estimated 619,000 deaths in 2021. Less than 30% of children presenting with SM are diagnosed and treated promptly, resulting in increased mortality and neurologic impairments in survivors. Studies have identified cytokine profiles that differentiate the various clinical manifestations of malaria (severe and uncomplicated). However, the diagnostic capability of these cytokines in differentiating between the disease states in terms of cut-off values has not yet been determined. Methods The plasma levels of 22 pro-inflammatory cytokines (Eotaxin/CCL 11, interferon-gamma (IFN-γ), interleukin (IL)- 2, IL-6, IL-1β, IL-12p40/p70, IL-17A, RANTES, MCP-1, IL-15, IL-5, IL-1RA, IL-2R, IFN-α, IP-10, TNF, MIG, MIP-1α, MIP-1β, IL-7, IL-8 and Granulocyte Macrophage-Colony Stimulating Factor (GM-CSF), and 3 anti-inflammatory cytokines-(IL-4, IL-13 and IL-10) in patients with SM, uncomplicated malaria (UM) and other febrile conditions, were measured and compared using the Human Cytokine Magnetic 25-Plex Panel. The receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic value of these cytokines. Results The level of the pro-inflammatory cytokine, IL-17A, was significantly higher in the SM group as compared to the UM group. Levels of the anti-inflammatory cytokines however did not differ significantly among the SM and UM groups. Only IL-1β and IL-17A showed good diagnostic potential after ROC curve analysis. Conclusion The data show that levels of pro-inflammatory cytokines correlate with malaria disease severity. IL-1β and IL-17A showed good diagnostic potentials and can be considered for use in clinical practice to target treatment.

Sepsis defined as a dysregulated immune response is a major cause of morbidity in children. In sub-Saharan Africa, the clinical features of sepsis overlap with other frequent infections such as malaria, thus sepsis is usually misdiagnosed in the absence of confirmatory tests. Therefore, it becomes necessary to identify biomarkers that can be used to distinguish sepsis from other infectious diseases. We measured and compared the plasma levels of 18 cytokines (Th1 [GM-CSF, IFN-γ, TNF-α, IL-1β, 1L-2, IL-6, IL-8, IL-12/IL-23p40, IL-15], Th2[IL-4, IL-5, IL-13), Th17 [IL17A], Regulatory cytokine (IL-10) and 7 chemokines (MCP-1/CCL2, MIP-1α/CCL3, MIP-1β/CCL4, RANTES/CCL5, Eotaxin/CCL11, MIG/CXCL9 and IP-10/CXCL10 using the Human Cytokine Magnetic 25-Plex Panel in plasma samples obtained from children with sepsis, clinical malaria and other febrile conditions. Children with sepsis had significantly higher levels of IL-1β, IL-12 and IL-17A compared to febrile controls but lower levels of MIP1-β/CCL4, RANTES/CCL5 and IP10/CXCL10 when compared to children with malaria and febrile controls. Even though levels of most inflammatory responses were higher in malaria compared to sepsis, children with sepsis had a higher pro-inflammatory to anti-inflammatory ratio which seemed to be mediated by mostly monocytes. A principal component analysis and a receiver operator characteristic curve analysis, identified seven potential biomarkers; IL-1β, IL-7, IL-12, IL-1RA, RANTES/CCL5, MIP1β/CCL4 and IP10/CXCL10 that could discriminate children with sepsis from clinical malaria and other febrile conditions. The data suggests that sepsis is associated with a higher pro-inflammatory environment. These pro-inflammatory cytokines/chemokines could further be evaluated for their diagnostic potential to differentiate sepsis from malaria and other febrile conditions in areas burdened with infectious diseases.

Background Microscopic detection of malaria parasites is labour-intensive, time-consuming, and expertise-demanding. Moreover, the slide interpretation is highly dependent on the staining technique and the technician’s expertise. Therefore, there is a growing interest in next-generation, fully- or semi-integrated microscopes that can improve slide preparation and examination. This study aimed to evaluate the clinical performance of miLab™ (Noul Inc., Republic of Korea), a fully-integrated automated microscopy device for the detection of malaria parasites in symptomatic patients at point-of-care in Sudan. Methods This was a prospective, case–control diagnostic accuracy study conducted in primary health care facilities in rural Khartoum, Sudan in 2020. According to the outcomes of routine on-site microscopy testing, 100 malaria-positive and 90 malaria-negative patients who presented at the health facility and were 5 years of age or older were enrolled consecutively. All consenting patients underwent miLab™ testing and received a negative or suspected result. For the primary analysis, the suspected results were regarded as positive (automated mode). For the secondary analysis, the operator reviewed the suspected results and categorized them as either negative or positive (corrected mode). Nested polymerase chain reaction (PCR) was used as the reference standard, and expert light microscopy as the comparator. Results Out of the 190 patients, malaria diagnosis was confirmed by PCR in 112 and excluded in 78. The sensitivity of miLab™ was 91.1% (95% confidence interval [CI] 84.2–95.6%) and the specificity was 66.7% (95% Cl 55.1–67.7%) in the automated mode. The specificity increased to 96.2% (95% Cl 89.6–99.2%), with operator intervention in the corrected mode. Concordance of miLab with expert microscopy was substantial (kappa 0.65 [95% CI 0.54–0.76]) in the automated mode, but almost perfect (kappa 0.97 [95% CI 0.95–0.99]) in the corrected mode. A mean difference of 0.359 was found in the Bland–Altman analysis of the agreement between expert microscopy and miLab™ for quantifying parasite counts. Conclusion When used in a clinical context, miLab™ demonstrated high sensitivity but low specificity. Expert intervention was shown to be required to improve the device’s specificity in its current version. miLab™ in the corrected mode performed similar to expert microscopy. Before clinical application, more refinement is needed to ensure full workflow automation and eliminate human intervention. Trial registration ClinicalTrials.gov: NCT04558515

Background In the past two decades, there has been a reported decline in malaria in Ghana and the rest of the world; yet it remains the number one cause of mortality and morbidity. Human immuno-deficiency virus (HIV) and sickle cell disease (SCD) share a common geographical space with malaria in sub-Saharan Africa and an interaction between these three conditions has been suggested. This study determined the Plasmodium falciparum and non- P. falciparum status of symptomatic and non-symptomatic residents of Mpraeso in the highlands of Kwahu-South district of Ghana based on evidence of current national decline. The influence of HIV and SCD on malaria was also determined. Methods Participants were 354 symptomatic patients visiting the Kwahu Government Hospital and 360 asymptomatic residents of the district capital. This cross-sectional study was conducted during the minor rainy season (October–December 2014). Rapid diagnostic tests (RDT), blood film microscopy and real-time polymerase chain reaction assessment of blood were done. Participants who tested positive with RDT were treated with artemisinin-based combination therapy; and assessment of venous blood was repeated 7 days after treatment. HIV screening and haemoglobin genotyping was done. Univariate and multivariate regression analysis was used to determine the influence of SCD and HIV. Results Plasmodium falciparum was prevalent at 124/142 (87.3%). Plasmodium malariae was the only non-falciparum species detected at 18/142 (12.7%). HIV and SCD did not significantly increase odds of malaria infection. However, the use of ITN and recent anti-malarial intake significantly decreased the odds of being malaria infected by 0.45-fold and 0.46-fold respectively. Conclusion Plasmodium falciparum and P. malariae infection are the prevailing species in the study area; albeit varying from the national average. HIV and SCD were not associated with the risk of having malaria.

Background Plasmodium falciparum, the most dominant species in sub-Saharan Africa, causes the most severe clinical malaria manifestations. In resource-limited Ghana, where malaria and HIV geographically overlap, histidine-rich protein 2 (HRP2)-based rapid diagnostic test (RDT) is a faster, easier and cheaper alternative to clinical gold standard light microscopy. However, mutations in parasite hrp2 gene may result in missed infections, which have severe implications for malaria control. Methods The performance of a common HRP2-based RDT and expert light microscopy in HIV-positive and HIV-negative children under 5 years old was compared with PCR as laboratory gold standard. Finger-prick capillary blood was tested with First Response ® Malaria Ag P. falciparum (HRP2). Giemsa-stained thick and thin blood films were examined with ≥ 200 high power fields and parasites counted per 200 white blood cells. Nested PCR species identification of P. falciparum was performed and resolved on agarose gel. False negatives from RDT were further tested for deleted pfhrp2/3 and flanking genes, using PCR. The study was performed in two anti-retroviral therapy clinics in Accra and Atibie. Results Out of 401 participants enrolled, 150 were HIV positive and 251 HIV negative. Malaria was more prevalent in children without HIV. Microscopy had a higher sensitivity [100% (99–100)] than RDT [83% (53.5–100)]. Parasites with pfhrp2/3 deletions contributed to missed infections from RDT false negatives. Conclusion Circulation of malaria parasites with pfrhp2/3 deletions in this population played a role in missed infections with RDT. This ought to be addressed if further strides in malaria control are to be made.

Background Malaria control efforts in Ghana have reduced the countrywide average malaria prevalence from 71 % in 2000 to about 51 % in 2012; however, its main focus is on symptomatic malaria. If further progress is to be made, parasite reservoirs in asymptomatic carriers need to be moved into focus. This study profiles asymptomatic Plasmodium spp. parasitaemia amongst residents of mountainous Kwahu-Mpraeso in the Eastern region of Ghana. Methods A cross-sectional study of 360 residents was carried out from October to December 2013. This included recording demographics, malaria testing of asymptomatic residents, and gathering of their malaria history. Assessment of malaria transmission was done with molecular identification of vectors, determination of sporozoite rate, insecticide resistance status and biting pattern. Univariate and multivariate analysis were used to establish risk determinants. Results In Mpraeso, in the Kwahu highland of Eastern Region, children were at higher risk of asymptomatic parasitaemia, thereby contributing to the parasite reservoir and hence sustained malaria transmission. As well, findings suggested Hb AC genotype influenced susceptibility to asymptomatic malaria with 8.03-fold increase in odds (univariate) and 11.92-fold higher odds (multivariate) than the normal Hb AA. The mosquito vector predominant in the area was Anopheles gambiae sensu stricto of the homozygous pyrethroid resistant form (RR); with biting mainly occurring indoors. Conclusion For an effective malaria control in this area, interventions should be formulated and implemented to target asymptomatic parasite reservoirs; especially in children and people with Hb AC. The dominant vector species An. gambiae s.s . and its feeding patterns of biting indoors should also be considered.

Human immunodeficiency virus (HIV) and sickle cell disease (SCD) are regarded as endemic in overlapping geographic areas; however, for most countries only scarce data on the interaction between HIV and SCD and disease burden exist. HIV prevalence in SCD patients varies between 0% and 11.5% in published studies. SCD has been suggested to reduce disease progression of HIV into AIDS. Various interactions of antiretroviral therapy with SCD exist. Both SCD and HIV act as common risk factors for stroke, avascular necrosis, severe splenic dysfunction, pulmonary arterial hypertension, and sepsis, which may result in synergistic increase in risk of developing these diseases. No treatment guidelines regarding SCD with HIV coinfection were identified. Available evidence is mainly based on small clinical studies, thus making strong recommendations difficult. An increased effort to elucidate the precise interactions is warranted to better both diseases and effect more adequate treatment approaches, especially in view of their geographical coprevalence.

Background Microscopic examination is commonly used for malaria diagnosis in the field. However, the lack of well-trained microscopists in malaria-endemic areas impacted the most by the disease is a severe problem. Besides, the examination process is time-consuming and prone to human error. Automated diagnostic systems based on machine learning offer great potential to overcome these problems. This study aims to evaluate Malaria Screener, a smartphone-based application for malaria diagnosis. Methods A total of 190 patients were recruited at two sites in rural areas near Khartoum, Sudan. The Malaria Screener mobile application was deployed to screen Giemsa-stained blood smears. Both expert microscopy and nested PCR were performed to use as reference standards. First, Malaria Screener was evaluated using the two reference standards. Then, during post-study experiments, the evaluation was repeated for a newly developed algorithm, PlasmodiumVF-Net. Results Malaria Screener reached 74.1% (95% CI 63.5–83.0) accuracy in detecting Plasmodium falciparum malaria using expert microscopy as the reference after a threshold calibration. It reached 71.8% (95% CI 61.0–81.0) accuracy when compared with PCR. The achieved accuracies meet the WHO Level 3 requirement for parasite detection. The processing time for each smear varies from 5 to 15 min, depending on the concentration of white blood cells (WBCs). In the post-study experiment, Malaria Screener reached 91.8% (95% CI 83.8–96.6) accuracy when patient-level results were calculated with a different method. This accuracy meets the WHO Level 1 requirement for parasite detection. In addition, PlasmodiumVF-Net, a newly developed algorithm, reached 83.1% (95% CI 77.0–88.1) accuracy when compared with expert microscopy and 81.0% (95% CI 74.6–86.3) accuracy when compared with PCR, reaching the WHO Level 2 requirement for detecting both Plasmodium falciparum and Plasmodium vivax malaria, without using the testing sites data for training or calibration. Results reported for both Malaria Screener and PlasmodiumVF-Net used thick smears for diagnosis. In this paper, both systems were not assessed in species identification and parasite counting, which are still under development. Conclusion Malaria Screener showed the potential to be deployed in resource-limited areas to facilitate routine malaria screening. It is the first smartphone-based system for malaria diagnosis evaluated on the patient-level in a natural field environment. Thus, the results in the field reported here can serve as a reference for future studies.