Dataset Information

Mobile phone imaging and cloud-based analysis for standardized malaria detection and reporting.

ABSTRACT: Rapid diagnostic tests (RDTs) have been widely deployed in low-resource settings. These tests are typically read by visual inspection, and accurate record keeping and data aggregation remains a substantial challenge. A successful malaria elimination campaign will require new strategies that maximize the sensitivity of RDTs, reduce user error, and integrate results reporting tools. In this report, an unmodified mobile phone was used to photograph RDTs, which were subsequently uploaded into a globally accessible database, REDCap, and then analyzed three ways: with an automated image processing program, visual inspection, and a commercial lateral flow reader. The mobile phone image processing detected 20.6 malaria parasites/microliter of blood, compared to the commercial lateral flow reader which detected 64.4 parasites/microliter. Experienced observers visually identified positive malaria cases at 12.5 parasites/microliter, but encountered reporting errors and false negatives. Visual interpretation by inexperienced users resulted in only an 80.2% true negative rate, with substantial disagreement in the lower parasitemia range. We have demonstrated that combining a globally accessible database, such as REDCap, with mobile phone based imaging of RDTs provides objective, secure, automated, data collection and result reporting. This simple combination of existing technologies would appear to be an attractive tool for malaria elimination campaigns.

SUBMITTER: Scherr TF

PROVIDER: S-EPMC4921854 | biostudies-other | 2016

REPOSITORIES: biostudies-other

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Mobile phone imaging and cloud-based analysis for standardized malaria detection and reporting.

Scherr Thomas F TF Gupta Sparsh S Wright David W DW Haselton Frederick R FR

Scientific reports 20160627

Rapid diagnostic tests (RDTs) have been widely deployed in low-resource settings. These tests are typically read by visual inspection, and accurate record keeping and data aggregation remains a substantial challenge. A successful malaria elimination campaign will require new strategies that maximize the sensitivity of RDTs, reduce user error, and integrate results reporting tools. In this report, an unmodified mobile phone was used to photograph RDTs, which were subsequently uploaded into a glob ...[more]

PMID: 27345590

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Project description:BackgroundTo achieve malaria elimination in the Greater Mekong Subregion, including Myanmar, it is necessary to ensure all malaria cases are detected, treated, and reported in a timely manner. Mobile phone-based applications for malaria reporting, case management, and surveillance implemented at a community-level may overcome reporting limitations associated with current paper-based reporting (PBR), but their effectiveness in this context is unknown.MethodsA mixed methods evaluation study was undertaken to determine the effectiveness of a national Malaria Case-Based Reporting (MCBR) mobile phone application in improving malaria case reporting compared to the existing PBR reporting system in Myanmar. Methods included secondary analysis of malaria case report data, questionnaires, focus group discussions and field observations of community volunteers, interviews and direct observations of malaria programme stakeholders, and cost analysis. Using a combination of these approaches the following areas were investigated: data quality and completeness, data access and usage, capacity for timely reporting, the acceptability, functionality, and ease of use of the application and facilitators and barriers to its use, and the relative cost of MCBR compared to the PBR system.ResultsCompared to PBR, MCBR enabled more accurate and complete data to be reported in a much timelier manner, with 63% of MCBR users reporting they transmit rapid diagnostic test outcomes within 24 h, compared to 0% of PBR users. MCBR was favoured by integrated community malaria volunteers and their supervisors because of its efficiency. However, several technical and operational challenges associated with internet coverage, data transmission, and e-literacy were identified and stakeholders reported not being confident to rely solely on MCBR data for programmatic decision-making.ConclusionsImplementation of MCBR provided timely and accurate data for malaria surveillance. Findings from this evaluation study will enable the optimization of an application-based reporting system for malaria monitoring and surveillance in the Greater Mekong Subregion and advance systems to track progress towards, and certify, the achievement of malaria elimination targets.

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.

Project description:ObjectiveTo evaluate the feasibility of a phone camera and cloud service-based workflow to image bone specimens and print their three-dimensional (3D) models for anatomical education.DesignThe images of four typical human bone specimens, photographed by a phone camera, were aligned and converted into digital images for incorporation into a digital model through the Get3D website and submitted to an online 3D printing platform to obtain the 3D printed models. The fidelity of the 3D digital, printed models relative to the original specimens, was evaluated through anatomical annotations and 3D scanning.SettingThe Morphologic Science Experimental Center, Central South University, China.ParticipantsSpecimens of four typical bones-the femur, rib, cervical vertebra and skull-were used to evaluate the feasibility of the workflow.Outcome measuresThe gross fidelity of anatomical features within the digital models and 3D printed models was evaluated first using anatomical annotations in reference to Netter's Atlas of Human Anatomy. The measurements of the deviation were quantised and visualised for analysis in Geomagic Control 2015.ResultsAll the specimens were reconstructed in 3D and printed using this workflow. The overall morphology of the digital and 3D printed models displayed a large extent of similarity to the corresponding specimens from a gross anatomical perspective. A high degree of similarity was also noticed in the quantitative analysis, with distance deviations ≤2 mm present among 99% of the random sampling points that were tested.ConclusionThe photogrammetric digitisation workflow adapted in the present study demonstrates fairly high precision with relatively low cost and fewer equipment requirements. This workflow is expected to be used in morphological/anatomical science education, particularly in institutions and schools with limited funds or in certain field research projects involving the fast acquisition of 3D digital data on human/animal bone specimens or on other remains.

Project description:This expert consensus document represents an initiative by the European Neuroendocrine Tumor Society (ENETS) to provide guidance for synoptic reporting of radiological examinations critical to the diagnosis, grading, staging and treatment of neuroendocrine neoplasms (NENs). Template drafts for initial tumor staging and follow-up by computed tomography (CT) and magnetic resonance imaging (MRI) were established, based on existing institutional and organisational reporting templates relevant for NEN imaging, and applying the RadLex lexicon of radiological information (Radiological Society of North America), for consistency regarding the radiological terms. During the ENETS Scientific Advisory Board meeting 2018, the template drafts were subject to iterative interdisciplinary discussions among experts in imaging, surgery, gastroenterology, oncology and pathology. Members of the imaging group stated a strong preference for a combination of limited and standardised options by way of drop-down menus. Separate templates were produced for the initial work-up and for follow-up, respectively. To provide a detailed description of the radiological findings of the primary tumor and its local extension and spread, different templates were developed for bronchial, pancreatic and gastrointestinal NENs for CT and MRI, respectively. Each template was structured in 10 sections: clinical details, comparative imaging modality, acquisition technique, primary tumor findings, regional lymph node metastases, distant metastases, TNM classification, reference lesions according to RECIST 1.1, additional findings and conclusion. Two templates were developed for follow-up, for CT and MRI, respectively, and were specifically focused on assessment of therapy response. These included a qualitative response assessment, such as decrease of vascularisation and presence of necrosis, and a quantitative assessment according to RECIST 1.1 and the modified RECIST (mRECIST) for assessing tumor response following transarterial chemoembolisation.

Project description:The electroencephalography (EEG) signal has a high complexity, and the process of extracting clinically relevant features is achieved by visual analysis of the recordings. The interobserver agreement in EEG interpretation is only moderate. This is partly due to the method of reporting the findings in free-text format. The purpose of our endeavor was to create a computer-based system for EEG assessment and reporting, where the physicians would construct the reports by choosing from predefined elements for each relevant EEG feature, as well as the clinical phenomena (for video-EEG recordings). A working group of EEG experts took part in consensus workshops in Dianalund, Denmark, in 2010 and 2011. The faculty was approved by the Commission on European Affairs of the International League Against Epilepsy (ILAE). The working group produced a consensus proposal that went through a pan-European review process, organized by the European Chapter of the International Federation of Clinical Neurophysiology. The Standardised Computer-based Organised Reporting of EEG (SCORE) software was constructed based on the terms and features of the consensus statement and it was tested in the clinical practice. The main elements of SCORE are the following: personal data of the patient, referral data, recording conditions, modulators, background activity, drowsiness and sleep, interictal findings, "episodes" (clinical or subclinical events), physiologic patterns, patterns of uncertain significance, artifacts, polygraphic channels, and diagnostic significance. The following specific aspects of the neonatal EEGs are scored: alertness, temporal organization, and spatial organization. For each EEG finding, relevant features are scored using predefined terms. Definitions are provided for all EEG terms and features. SCORE can potentially improve the quality of EEG assessment and reporting; it will help incorporate the results of computer-assisted analysis into the report, it will make possible the build-up of a multinational database, and it will help in training young neurophysiologists.

Project description:Improving the speed of outbreak detection and reporting at the community level are critical in managing the threat of emerging infectious diseases, many of which are zoonotic. The widespread use of mobile phones, including in rural areas, constitutes a potentially effective tool for real-time surveillance of infectious diseases. Using longitudinal data from a disease surveillance system implemented in 1500 households in rural Kenya, we test the effectiveness of mobile phone animal syndromic surveillance by comparing it with routine household animal health surveys, determine the individual and household correlates of its use and examine the broader implications for surveillance of zoonotic diseases. A total of 20 340 animal and death events were reported from the community through the two surveillance systems, half of which were confirmed as valid disease events. The probability of an event being valid was 2.1 times greater for the phone-based system, compared with the household visits. Illness events were 15 times (95% CI 12.8, 17.1) more likely to be reported through the phone system compared to routine household visits, but not death events (OR 0.1 (95% CI 0.09, 0.11)). Disease syndromes with severe presentations were more likely to be reported through the phone system. While controlling for herd and flock sizes owned, phone ownership was not a determinant of using the phone-based surveillance system, but the lack of a formal education, and having additional sources of income besides farming were associated with decreased likelihood of reporting through the phone system. Our study suggests that a phone-based surveillance system will be effective at detecting outbreaks of diseases such as Rift Valley fever that present with severe clinical signs in animal populations, but in the absence of additional reporting incentives, it may miss early outbreaks of diseases such as avian influenza that present primarily with mortality. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.

Dataset Information

Mobile phone imaging and cloud-based analysis for standardized malaria detection and reporting.

Publications

Mobile phone imaging and cloud-based analysis for standardized malaria detection and reporting.

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