Improving Accuracy of Malaria Diagnosis in Underserved Rural and Remote Endemic Areas of Sub-Saharan Africa: A Call to Develop Multiplexing Rapid Diagnostic Tests

Population-Based Prevalence of Antibiotic Residuals in Low, Moderate and High Malaria Endemicity Areas in Tanzania

BACKGROUND

Inappropriate antibiotic use drives antimicrobial resistance and remains a global concern. Evidence suggests antibiotic use may be higher among malaria-negative patients compared to malaria-positive ones, but uncertainty persists, particularly in regions with varying malaria prevalence. This study measured antibiotic residuals in three Tanzanian regions with varying malaria epidemiology and analyzed factors influencing their presence.

METHODS

A cross-sectional household survey was conducted in 2015, covering a population of 6000 individuals across three regions of Tanzania. Dried blood spot samples from a subset of participants were analyzed using broad-range tandem mass spectrometry to detect residual antibiotics. Risk factors associated with antibiotic presence, including household healthcare-seeking behaviors, malaria testing, and other relevant variables, were evaluated.

RESULTS

The overall prevalence of residual antibiotics in the study population was 14.4% (438/3036; 95% CI: 11.4-15.8%). Stratified by malaria transmission intensity, antibiotic prevalence was 17.2% (95% CI: 12.9-17.2%) in Mwanza (low), 14.6% (95% CI: 10.6-15.0%) in Mbeya (moderate), and 11.2% (95% CI: 7.9-11.6%) in Mtwara (high). Trimethoprim was the most frequently detected antibiotic (6.1%), followed by sulfamethoxazole (4.4%) and penicillin V (0.001%).

CONCLUSIONS

Residual antibiotic prevalence did not directly correlate with malaria endemicity but was influenced by healthcare practices, including co-prescription of antibiotics and antimalarials. The higher antibiotic use in malaria-negative cases highlights the need for improved diagnostics to reduce unnecessary use and mitigate antimicrobial resistance in malaria-endemic areas.

Epidemiological profile of malaria in a rural community in the Amazon, Mato Grosso State, Brazil, 2011

BACKGROUND

More than 95% of malaria transmission in Brazil occurs in the Legal Amazon Region, which in 2010 recorded around 333,429 cases reported in the Epidemiological Surveillance Information System-Malaria (Sivep_malaria), presenting an annual parasitic incidence (IPA) of 13.1 cases/1000 inhabitants.

METHODS

This was a descriptive study that measured the community prevalence of Plasmodium infection and its relationship with land use in Três Fronteiras District, Colniza Municipality, Mato Grosso State. Data were collected during household visits in July 2011, with blood collection from finger pricks for the preparation of thick smear slides, and completion of a standardized case notification form. A georeferenced database was analysed, with land use evaluated as categorical variables. A kernel density map was built to show the density of cases and their location.

RESULTS

Of the 621 respondents, 68(11%) had Plasmodium infection: 39 (57.4%) with Plasmodium vivax, 27(39.7%) with Plasmodium falciparum and two (2.9%) with mixed infections. Among infected individuals, 49 (72.1%) were men. Cases of malaria were distributed over the district, with greater occurrence of cases per household in open areas close to the mining company and artisanal mining sites. The was a greater density of cases located in the gold mining region.

CONCLUSION

Transmission of malaria in Três Fronteiras District has a heterogeneous distribution. Individuals residing in mining and timber extraction sites have increased occurrence of Plasmodium infection.

Study on the dielectrophoretic characteristics of malaria-infected red blood cells

Malaria is a tropical disease caused by parasites in the genus Plasmodium, which still presents 241 million cases and nearly 627,000 deaths recently. In this work, we used the dielectrophoresis (DEP) to characterize red blood cells in a microchannel. The purpose of this work is to determine the difference between the normal and the malaria-infected cells based on the DEP characteristics. The samples were infected cells and normal red blood cells, which were either prepared in culture or obtained from volunteers. Diamond-shaped and curved micropillars were used to create different degrees of DEP in the gap between them. The DEP crossover frequencies were observed with the diamond-shaped micropillars. The cell velocity under negative dielectrophoresis (nDEP) at a low frequency was examined with the curved micropillars. The measured lower crossover frequencies were remarkably different between the malaria-infected cells and the normal cells, whereas the higher crossover frequencies were similar among the samples. The velocity under nDEP was lower for the infected cells than the normal cells. The results imply that the malaria infection significantly decreases the capacitance but increases the conductance of the cell membrane, whereas a change in cytoplasmic conductivity may occur in a later stage of infection.

Malaria therapeutics: are we close enough?

Malaria is a vector-borne parasitic disease caused by the apicomplexan protozoan parasite Plasmodium. Malaria is a significant health problem and the leading cause of socioeconomic losses in developing countries. WHO approved several antimalarials in the last 2 decades, but the growing resistance against the available drugs has worsened the scenario. Drug resistance and diversity among Plasmodium strains hinder the path of eradicating malaria leading to the use of new technologies and strategies to develop effective vaccines and drugs. A timely and accurate diagnosis is crucial for any disease, including malaria. The available diagnostic methods for malaria include microscopy, RDT, PCR, and non-invasive diagnosis. Recently, there have been several developments in detecting malaria, with improvements leading to achieving an accurate, quick, cost-effective, and non-invasive diagnostic tool for malaria. Several vaccine candidates with new methods and antigens are under investigation and moving forward to be considered for clinical trials. This article concisely reviews basic malaria biology, the parasite's life cycle, approved drugs, vaccine candidates, and available diagnostic approaches. It emphasizes new avenues of therapeutics for malaria.

Malaria Diagnosis Using Paper-Based Immunoassay for Clinical Blood Sampling and Analysis by a Miniature Mass Spectrometer

In this work, we have developed a paper-based microfluidic device capable of remote biofluid collection followed by an analysis of the dried clinical samples using a miniature mass spectrometer. We have evaluated a portable mass spectrometer as a possible surveillance platform by analyzing the clinical malaria samples (whole blood) collected from Ghana. We synthesized pH-sensitive ionic probes and coupled them with monoclonal antibodies specific to the Plasmodium falciparum histidine-rich protein 2 (PfHRP2) malaria antigen. We then used the antibody-ionic probe conjugates in a paper-based immunoassay to capture PfHRP2 antigen from untreated whole blood. After the immunoassay, the bound ionic probes were cleaved, and the released mass tags were analyzed through an on-chip paper spray mass spectrometry strategy. During process optimization, we determined the detection limit for PfHRP2 in untreated human serum to be 0.216 nmol/L when using the miniature mass spectrometer. This sensitivity is comparable to the World Health Organization's suggested threshold of 0.227 nmol/L for PfHRP2, proving that our method will be applicable to diagnose symptomatic malaria infection (≥200 parasites per μL blood). The paper device can be stored at room temperature for at least 25 days without affecting the clinical outcome, with each stored paper chip offering good repeatability and reproducibility (RSD = 4-12%). The stability and sensitivity of the developed paper-based immunoassay platform will allow miniature mass spectrometers to be used for point-of-care malaria detection as well as in large-scale surveillance screening to aid eradication programs.

Misdiagnosis of Plasmodium vivax in a Case of Mixed Malaria, Lead to Wrong Anti-Cancer Chemotherapy, Splenectomy, and Partial Hepatectomy Due to Relapse: A Case Report

Malaria is a multilateral parasitic infection, which causes wonderful mortality and morbidity worldwide. It sometimes accompanied a quaint appearance. An Iranian 50-year-old man was admitted to Omid, hospital, a specialized cancer hospital in Isfahan, Iran. Because of a 15-year persisted anemia due to misdiagnose of vivax malaria led him to three courses of anticancer chemotherapy and splenectomy. His blood smears were sent to the Department of Parasitology, School of Medicine, Isfahan University of Medical Sciences, Iran. Our findings from his history, file documents, clinical signs and symptoms, and parasitological and molecular assessments revealed an interesting case, which is reported.

Pediatric Malaria: Global and North American Perspectives

Malaria is a leading cause of death in children less than 5 years of age globally, and a common cause of fever in the returning North American traveler. New tools in the fight against malaria have been developed over the past decades: potent artemisinin derivatives; rapid diagnostic tests; long-lasting insecticidal bed nets; and a new vaccine, RTS,S/AS01. Thwarting these advances, parasite and Anopheles vector resistance are emerging. In the meantime, clinicians will continue to see malaria among febrile travelers from the tropics. Early recognition, diagnosis, and treatment can be lifesaving, but rely on the vigilance of frontline clinicians.

Vector-borne protozoal infections of the CNS: cerebral malaria, sleeping sickness and Chagas disease

PURPOSE OF REVIEW

Malaria, Chagas Disease and Human African Trypanosomiasis are vector-borne protozoan illnesses, frequently associated with neurological manifestations. Intriguing but ignored, limited mainly to resource-limited, tropical settings, these disorders are now coming to light because of globalisation and improved diagnosis and treatment. Enhanced understanding of these illnesses has prompted this review.

RECENT FINDINGS

Methods of diagnosis have currently transitioned from blood smear examinations to immunological assays and molecular methods. Tools to assess neurological involvement, such as magnetic resonance imaging, are now increasingly available in regions and countries with high infection loads. Sleep and other electrophysiological technologies (electroencephalography, actigraphy) are also promising diagnostic tools but requiring field-validation. Access to treatments was formerly limited, even as limitations of agents used in the treatment are increasingly recognised. Newer agents are now being developed and trialled, encouraged by improved understanding of the disorders' molecular underpinnings.

SUMMARY

Prompt diagnosis and treatment are crucial in ensuring cure from the infections. Attention should also be due to the development of globally applicable treatment guidelines, the burden of neurological sequelae and elimination of the zoonoses from currently endemic regions.

Convolutional neural networks to automate the screening of malaria in low-resource countries

Malaria is an infectious disease caused by Plasmodium parasites, transmitted through mosquito bites. Symptoms include fever, headache, and vomiting, and in severe cases, seizures and coma. The World Health Organization reports that there were 228 million cases and 405,000 deaths in 2018, with Africa representing 93% of total cases and 94% of total deaths. Rapid diagnosis and subsequent treatment are the most effective means to mitigate the progression into serious symptoms. However, many fatal cases have been attributed to poor access to healthcare resources for malaria screenings. In these low-resource settings, the use of light microscopy on a thin blood smear with Giemsa stain is used to examine the severity of infection, requiring tedious and manual counting by a trained technician. To address the malaria endemic in Africa and its coexisting socioeconomic constraints, we propose an automated, mobile phone-based screening process that takes advantage of already existing resources. Through the use of convolutional neural networks (CNNs), we utilize a SSD multibox object detection architecture that rapidly processes thin blood smears acquired via light microscopy to isolate images of individual red blood cells with 90.4% average precision. Then we implement a FSRCNN model that upscales 32 × 32 low-resolution images to 128 × 128 high-resolution images with a PSNR of 30.2, compared to a baseline PSNR of 24.2 through traditional bicubic interpolation. Lastly, we utilize a modified VGG16 CNN that classifies red blood cells as either infected or uninfected with an accuracy of 96.5% in a balanced class dataset. These sequential models create a streamlined screening platform, giving the healthcare provider the number of malaria-infected red blood cells in a given sample. Our deep learning platform is efficient enough to operate exclusively on low-tier smartphone hardware, eliminating the need for high-speed internet connection.