Dataset Information

The Malaria System MicroApp: A New, Mobile Device-Based Tool for Malaria Diagnosis.

ABSTRACT:

Background

Malaria is a public health problem that affects remote areas worldwide. Climate change has contributed to the problem by allowing for the survival of Anopheles in previously uninhabited areas. As such, several groups have made developing news systems for the automated diagnosis of malaria a priority.

Objective

The objective of this study was to develop a new, automated, mobile device-based diagnostic system for malaria. The system uses Giemsa-stained peripheral blood samples combined with light microscopy to identify the Plasmodium falciparum species in the ring stage of development.

Methods

The system uses image processing and artificial intelligence techniques as well as a known face detection algorithm to identify Plasmodium parasites. The algorithm is based on integral image and haar-like features concepts, and makes use of weak classifiers with adaptive boosting learning. The search scope of the learning algorithm is reduced in the preprocessing step by removing the background around blood cells.

Results

As a proof of concept experiment, the tool was used on 555 malaria-positive and 777 malaria-negative previously-made slides. The accuracy of the system was, on average, 91%, meaning that for every 100 parasite-infected samples, 91 were identified correctly.

Conclusions

Accessibility barriers of low-resource countries can be addressed with low-cost diagnostic tools. Our system, developed for mobile devices (mobile phones and tablets), addresses this by enabling access to health centers in remote communities, and importantly, not depending on extensive malaria expertise or expensive diagnostic detection equipment.

SUBMITTER: Oliveira AD

PROVIDER: S-EPMC5424126 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Malaria System MicroApp: A New, Mobile Device-Based Tool for Malaria Diagnosis.

Oliveira Allisson Dantas AD Prats Clara C Espasa Mateu M Zarzuela Serrat Francesc F Montañola Sales Cristina C Silgado Aroa A Codina Daniel Lopez DL Arruda Mercia Eliane ME I Prat Jordi Gomez JG Albuquerque Jones J

JMIR research protocols 20170425 4

<h4>Background</h4>Malaria is a public health problem that affects remote areas worldwide. Climate change has contributed to the problem by allowing for the survival of Anopheles in previously uninhabited areas. As such, several groups have made developing news systems for the automated diagnosis of malaria a priority.<h4>Objective</h4>The objective of this study was to develop a new, automated, mobile device-based diagnostic system for malaria. The system uses Giemsa-stained peripheral blood sa ...[more]

PMID: 28442456

Similar Datasets

Project description:BackgroundEarly and accurate diagnosis of malaria is critical to the success of malaria elimination. However, the current mainstay of malaria diagnosis in the field, such as light microscopy and rapid diagnostic tests (RDTs), have limitations due to low parasite density or mutation in diagnostic markers.MethodsWe evaluated an inexpensive, robust, rapid, malaria diagnostic device, called Gazelle, that employs magneto-optical detection to identify haemozoin crystals (Hz) produced by all species of human malaria parasites in infected individuals. A beam of polarised light is passed through the lysed diluted blood sample under the influence of high (~.55T) and low magnetic fields. The difference in light transmission through the sample between the high and low magnetic fields indicates presence of Hz, suggesting possible malarial infection. A total of 300 febrile patients were screened at the malaria clinic of Indian Council of Medical Research-National Institute of Research in Tribal Health (ICMR-NIRTH), Jabalpur, India, from August 2018 to November 2018. Malaria diagnosis was done using four diagnostic methods: Gazelle, light microscopy, RDT, and malaria specific Polymerase Chain Reaction (PCR). Measures of diagnostic accuracy were compared.FindingsOut of 300 febrile patients enroled and tested for the presence of malaria parasites, 262 patient samples were included in the final analysis. The sensitivity and specificity of Gazelle was 98% and 97% in comparison to light microscopy, 82% and 99% to PCR and 78% and 99% to RDT, respectively. The results of the four diagnostic methods were comparable and statistically no significant differences in sensitivity or specificity was observed between these methods. Enhanced diagnostic accuracy of Gazelle in malaria patients with no prior history of malaria treatment was observed in this study.InterpretationThe diagnostic ability of Gazelle was comparable to light microscopy and better than RDTs even in low parasitemia and in presence of pfhrp2/3 deletion mutant parasites. Gazelle may be a novel valuable diagnostic tool in resource poor settings where (i) microscopy is not feasible and (ii) pfhrp2/3gene deleted parasite are present. Its speed, cost-efficiency, and alternative to lack of microscopists makes it an important adjunct in field settings.FundingHemexDx, India.

Project description:BackgroundProper inhaler device usage is paramount for control of underlying obstructive airway disease. Hence, education to healthcare professionals who will eventually educate patients need to be done effectively. We developed an application for mobile devices for education on six medical inhaler devices, the metered-dose inhaler (MDI), Turbuhaler, Accuhaler, Breezhaler, Ellipta and Respimat, and studied if there were any difference between the application and the manufacturer's instructions on inhaler technique. The aim of this study is to see if inhaler education via a mobile phone app is comparable to manual instruction for health care professions.MethodsParticipants, who were nursing students, were randomized to learn the inhaler devices via the manufacturer's instruction guide or a mobile device app designed specifically for education on inhaler devices.ResultsThere were 45 participants in each group. 78% of them were females with a median age of 21 (IQR 3). 67% used an Apple mobile device and the remainder used an Android device. The mobile device showed better total improvement points for the Turbuhaler device (262 vs 287 points; P = 0.02). Participants learning from the manufacturer's guide had a significantly higher total improvement points in the Breezhaler (370 vs 327 points; P < 0.01) and Ellipta (214 vs 174 points; P < 0.01) device. Both interventions showed improvement in total scores for demonstrating the correct usage of all inhaler devices. MDI has the least number of correct steps for both interventions. The participants' reported their mean (SD) self-rated knowledge was significantly higher for those using the app for all devices as compared to those that did not (4.33 (0.68) vs 4.73 (0.42); P = < 0.01). Self-reported confidence level was found to be higher in the mobile app group, but this was not statistically significant. The app was well received and scored of 4.42 of 5 with regards to its quality.ConclusionUsing a mobile inhaler app is just as effective to teach inhaler device techniques to healthcare professionals and is likely a more convenient, versatile and important adjunct to learning.Trial registrationNational Healthcare Group Ethics Board (2018/00960).

Project description:BackgroundNew hemocytometric parameters can be used to differentiate causes of acute febrile illness (AFI). We evaluated a software algorithm-Infection Manager System (IMS)-which uses hemocytometric data generated by Sysmex hematology analyzers, for its accuracy to detect bacteremia in AFI patients with and without malaria in Burkina Faso. Secondary aims included comparing the accuracy of IMS with C-reactive protein (CRP) and procalcitonin (PCT).MethodsIn a prospective observational study, patients of ≥ three-month-old (range 3 months- 90 years) presenting with AFI were enrolled. IMS, blood culture and malaria diagnostics were done upon inclusion and additional diagnostics on clinical indication. CRP, PCT, viral multiplex PCR on nasopharyngeal swabs and bacterial- and malaria PCR were batch-tested retrospectively. Diagnostic classification was done retrospectively using all available data except IMS, CRP and PCT results.FindingsA diagnosis was affirmed in 549/914 (60.1%) patients and included malaria (n = 191) bacteremia (n = 69), viral infections (n = 145), and malaria-bacteremia co-infections (n = 47). The overall sensitivity, specificity, and negative predictive value (NPV) of IMS for detection of bacteremia in patients of ≥ 5 years were 97.0% (95% CI: 89.8-99.6), 68.2% (95% CI: 55.6-79.1) and 95.7% (95% CI: 85.5-99.5) respectively, compared to 93.9% (95% CI: 85.2-98.3), 39.4% (95% CI: 27.6-52.2), and 86.7% (95% CI: 69.3-96.2) for CRP at ≥20mg/L. The sensitivity, specificity and NPV of PCT at 0.5 ng/ml were lower at respectively 72.7% (95% CI: 60.4-83.0), 50.0% (95% CI: 37.4-62.6) and 64.7% (95% CI: 50.1-77.6) The diagnostic accuracy of IMS was lower among malaria cases and patients <5 years but remained equal to- or higher than the accuracy of CRP.InterpretationIMS is a new diagnostic tool to differentiate causes of AFI. Its high NPV for bacteremia has the potential to improve antibiotic dispensing practices in healthcare facilities with hematology analyzers. Future studies are needed to evaluate whether IMS, combined with malaria diagnostics, may be used to rationalize antimicrobial prescription in malaria endemic areas.Trial registrationClinicalTrials.gov (NCT02669823) https://clinicaltrials.gov/ct2/show/NCT02669823.

Project description:BackgroundStrengthening surveillance systems to collect near-real-time case-based data plays a fundamental role in achieving malaria elimination in the Greater Mekong Subregion (GMS). With the advanced and widespread use of digital technology, mHealth is increasingly taking a prominent role in malaria surveillance systems in GMS countries, including Myanmar. In Myanmar's malaria elimination program, an mHealth system called Malaria Case-based Reporting (MCBR) has been applied for case-based reporting of malaria data by integrated community malaria volunteers (ICMVs). However, the sustainability of such mHealth systems in the context of existing malaria elimination programs in Myanmar is unknown.MethodsFocus group discussions were conducted with ICMVs and semi-structured in-depth interviews were conducted with malaria program stakeholders from Myanmar's Ministry of Health and Sports and its malaria program implementing partners. Thematic (deductive followed by inductive) analysis was undertaken using a qualitative descriptive approach.ResultsTechnological and financial constraints such as inadequate internet access, software errors, and insufficient financial resources to support mobile phone-related costs have hampered users' access to MCBR. Poor system integrity, unpredictable reporting outcomes, inadequate human resources for system management, and inefficient user support undermined the perceived quality of the system and user satisfaction, and hence its sustainability. Furthermore, multiple parallel systems with functions overlapping those of MCBR were in use.ConclusionsDespite its effectiveness and efficiency in malaria surveillance, the sustainability of nationwide implementation of MCBR is uncertain. To make it sustainable, stakeholders should deploy a dedicated human workforce with the necessary technical and technological capacities; secure sustainable, long-term funding for implementation of MCBR; find an alternative cost-effective plan for ensuring sustainable system access by ICMVs, such as using volunteer-owned mobile phones for reporting rather than supporting new mobile phones to them; and find a solution to the burden of multiple parallel systems.Trial registrationNot applicable.

Dataset Information

The Malaria System MicroApp: A New, Mobile Device-Based Tool for Malaria Diagnosis.

Background

Objective

Methods

Results

Conclusions

Publications

The Malaria System MicroApp: A New, Mobile Device-Based Tool for Malaria Diagnosis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets