scholarly journals EpiCollect+: linking smartphones to web applications for complex data collection projects

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 199 ◽  
Author(s):  
David M. Aanensen ◽  
Derek M. Huntley ◽  
Mirko Menegazzo ◽  
Chris I. Powell ◽  
Brian G. Spratt
Keyword(s):  
Data Collection ◽  
Mobile Phone ◽  
Web Application ◽  
Web Applications ◽  
Complex Structure ◽  
Sub Saharan Africa ◽  
Mobile Phone Data ◽  
Complex Data ◽  
Branching Hierarchy ◽  
Media Types

Previously, we have described the development of the generic mobile phone data gathering tool, EpiCollect, and an associated web application, providing two-way communication between multiple data gatherers and a project database. This software only allows data collection on the phone using a single questionnaire form that is tailored to the needs of the user (including a single GPS point and photo per entry), whereas many applications require a more complex structure, allowing users to link a series of forms in a linear or branching hierarchy, along with the addition of any number of media types accessible from smartphones and/or tablet devices (e.g., GPS, photos, videos, sound clips and barcode scanning). A much enhanced version of EpiCollect has been developed (EpiCollect+). The individual data collection forms in EpiCollect+ provide more design complexity than the single form used in EpiCollect, and the software allows the generation of complex data collection projects through the ability to link many forms together in a linear (or branching) hierarchy. Furthermore, EpiCollect+ allows the collection of multiple media types as well as standard text fields, increased data validation and form logic. The entire process of setting up a complex mobile phone data collection project to the specification of a user (project and form definitions) can be undertaken at the EpiCollect+ website using a simple ‘drag and drop’ procedure, with visualisation of the data gathered using Google Maps and charts at the project website. EpiCollect+ is suitable for situations where multiple users transmit complex data by mobile phone (or other Android devices) to a single project web database and is already being used for a range of field projects, particularly public health projects in sub-Saharan Africa. However, many uses can be envisaged from education, ecology and epidemiology to citizen science.

scholarly journals Using Mobile Phone Data Collection Tool, Surveda, for Noncommunicable Disease Surveillance in Five Low- and Middle-income Countries

2020 ◽  
Vol 12 (2) ◽  
Author(s):  
Yang Song ◽  
Rachael Phadnis ◽  
Jennifer Favaloro ◽  
Juliette Lee ◽  
Charles Q. Lau ◽  
...  
Keyword(s):  
Data Collection ◽  
Mobile Phone ◽  
Web Application ◽  
Interactive Voice Response ◽  
Survey Design ◽  
Noncommunicable Disease ◽  
Mobile Phone Data ◽  
Data Collection Methods ◽  
Phone Survey ◽  
Collection Methods

Objectives: The Noncommunicable Disease (NCD) Mobile Phone Survey, a component of the Bloomberg Philanthropies Data for Health Initiative, determines the prevalence of NCDs and their associated risk factors and demonstrates the use of mobile phone administered surveys to supplement periodic national household surveys. The NCD Mobile Phone Survey uses Surveda to administer the survey; Surveda is an open source, multi-modal software specifically developed for the project. The objective of the paper is to describe Surveda, review data collection methods used in participating countries and discuss how Surveda and similar approaches can improve public health surveillance. Methods: Surveda features full-service survey design and implementation through a web application and collects data via Short Messaging Service (SMS), Interactive Voice Response (IVR) or mobile web. Surveda’s survey design process employs five steps: creating a project, creating questionnaires, designing and starting a survey, monitoring survey progress, and exporting survey results. Results: The NCD Mobile Phone Survey has been successfully conducted in five countries, Zambia (2017), Philippines (2018), Morocco (2019), Malawi (2019), and Sri Lanka (2019), with a total of 23,682 interviews completed. Discussion: This approach to data collection demonstrates that mobile phone surveys can supplement face-to-face data collection methods. Furthermore, Surveda offers major advantages including automated mode-switch, question randomization and comparison features. Conclusion: Accurate and timely survey data informs a country’s abilities to make targeted policy decisions while prioritizing limited resources. The high acceptance of Surveda demonstrates that the use of mobile phones for surveillance can deliver accurate and timely data collection.

scholarly journals Quantifying the Impact of Accessibility on Preventive Healthcare in Sub-Saharan Africa Using Mobile Phone Data

Epidemiology ◽  
2015 ◽  
Vol 26 (2) ◽  
pp. 223-228 ◽  
Author(s):  
Amy Wesolowski ◽  
Wendy Prudhomme O’Meara ◽  
Andrew J. Tatem ◽  
Samson Ndege ◽  
Nathan Eagle ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Sub Saharan Africa ◽  
Mobile Phone Data ◽  
Preventive Healthcare ◽  
Sub Saharan ◽  
The Impact

scholarly journals Implementation of Mobile Phone Data Collection in the Conduct EPI Comprehensive Review in East and Southern African Countries

2021 ◽  
Vol Special Issue (2) ◽  
pp. 55-62
Author(s):  
Isah Mohammed Bello ◽  
Abubakar Sadiq Umar ◽  
Godwin Ubong Akpan ◽  
Joseph Okeibunor ◽  
Chukwudi Shibeshi ◽  
...  
Keyword(s):  
Data Collection ◽  
Mobile Phone ◽  
Real Time ◽  
Mobile Phones ◽  
Health Sector ◽  
Mobile Phone Data ◽  
Data Detection ◽  
Time Data ◽  
African Countries ◽  
Comprehensive Review

Mobile phone data collection tools are increasingly becoming very usable collecting, collating and analysing data in the health sector. In this paper, we documented the experiences with mobile phone data collection, collation and analysis in 5 countries of the East and Southern African, using Open Data Kit (ODK), where questionnaires were designed and coded on an XML form, uploaded and data collected using Android-Based mobile phones, with a web-based system to monitor data in real-time during EPI comprehensive review. The ODK interface supports in real-time monitoring of the flow of data, detection of missing or incomplete data, coordinate location of all locations visited, embedded charts for basic analysis. It also minimized data quality errors at entry level with the use of validation codes and constraint developed into the checklist. These benefits, combined with the improvement that mobile phones offer over paper-based in terms of timeliness, data loss, collation, and real-time data collection, analysis and uploading difficulties, make mobile phone data collection a feasible method of data collection that needs to be further explored in the conduct of all surveys in the organization.

The Emerging Role of Citizen Science and Geospatial Big Data in Supporting the SDGs

2020 ◽  
Author(s):  
Steffen Fritz
Keyword(s):  
Sustainable Development ◽  
Big Data ◽  
Data Collection ◽  
Mobile Phone ◽  
Citizen Science ◽  
National Level ◽  
Well Being ◽  
Data Sources ◽  
Mobile Phone Data ◽  
Development Goals

<p>In September 2015, the United Nations ratified the 17 Sustainable Development Goals (SDGs), which are comprised of a further 169 targets and 232 indicators for monitoring progress on poverty, well-being and major environmental and socio-economic problems, both nationally and globally. Much of the data used for SDG monitoring comes from censuses, surveys and other administrative data provided by national statistical offices, government agencies and international organizations. However, traditional data collection can be costly and infrequent, and the information can become outdated very quickly. Moreover, reporting is generally at the national level, so spatial variations of indicators within a country are not often available, yet this information is critical for effective spatial planning. Without knowing where issues are occurring in space, we cannot implement targeted solutions. Hence, there is currently a lack of data needed for effective monitoring and implementation of the SDGs.</p><p>Non-traditional data sources such as those arising from citizen science and geospatial big data, e.g., satellite imagery, mobile phone data, social media, etc. are part of the current ‘data revolution’, all of which have potential use in SDG monitoring and implementation. This lecture will provide an overview of these new and emerging non-traditional data sources in monitoring the SDGs, providing a range of examples from citizen science, Earth Observation (including the work of the Group on Earth Observations) and mobile phone data, among others. Where relevant, we will touch upon disaster risk reduction. Finally, actions will be presented that are currently happening to promote the data revolution for sustainable development and what is still needed to make tangible progress on SDG implementation using these new data sources as well as how the engagement of citizens in data collection can trigger transformative and behavioral change.</p>

scholarly journals Knowledge and Skill Retention of a Mobile Phone Data Collection Protocol in Rural Liberia

2014 ◽  
Vol 59 (2) ◽  
pp. 176-183 ◽  
Author(s):  
Michelle L. Munro ◽  
Jody R. Lori ◽  
Carol J. Boyd ◽  
Pamela Andreatta
Keyword(s):  
Data Collection ◽  
Mobile Phone ◽  
Mobile Phone Data ◽  
Skill Retention
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