Electronic Data Management for Vaccine Trials in Low Resource Settings: Upgrades, Scalability, and Impact of ODK.

Background: ODK provides software and standards that are popular solutions for off-grid electronic data collection and has substantial code overlap and interoperability with a number of related software products including CommCare, Enketo, Ona, SurveyCTO, and KoBoToolbox. These tools provide open-source options for off-grid use in public health data collection, management, analysis, and reporting. During the 2018-2020 Ebola epidemic in the North Kivu and Ituri regions of Democratic Republic of Congo, we used these tools to support the DRC Ministère de la Santé RDC and World Health Organization in their efforts to administer an experimental vaccine (VSV-Zebov-GP) as part of their strategy to control the transmission of infection. Method: New functions were developed to facilitate the use of ODK, Enketo and R in large scale data collection, aggregation, monitoring, and near-real-time analysis during clinical research in health emergencies. We present enhancements to ODK that include a built-in audit-trail, a framework and companion app for biometric registration of ISO/IEC 19794-2 fingerprint templates, enhanced performance features, better scalability for studies featuring millions of data form submissions, increased options for parallelization of research projects, and pipelines for automated management and analysis of data. We also developed novel encryption protocols for enhanced web-form security in Enketo. Results: Against the backdrop of a complex and challenging epidemic response, our enhanced platform of open tools was used to collect and manage data from more than 280,000 eligible study participants who received VSV-Zebov-GP under informed consent. These data were used to determine whether the VSV-Zebov-GP was safe and effective and to guide daily field operations. Conclusions: We present open-source developments that make electronic data management during clinical research and health emergencies more viable and robust. These developments will also enhance and expand the functionality of a diverse range of data collection platforms that are based on the ODK software and standards.

Electronic data capture for large scale typhoid surveillance, household contact tracing, and health utilisation survey: Strategic Typhoid Alliance across Africa and Asia.

Electronic data capture systems (EDCs) have the potential to achieve efficiency and quality in collection of multisite data. We quantify the volume, time, accuracy and costs of an EDC using large-scale census data from the STRATAA consortium, a comprehensive programme assessing population dynamics and epidemiology of typhoid fever in Malawi, Nepal and Bangladesh to inform vaccine and public health interventions. A census form was developed through a structured iterative process and implemented using Open Data Kit Collect running on Android-based tablets. Data were uploaded to Open Data Kit Aggregate, then auto-synced to MySQL-defined database nightly. Data were backed-up daily from three sites centrally, and auto-reported weekly. Pre-census materials' costs were estimated. Demographics of 308,348 individuals from 80,851 households were recorded within an average of 14.7 weeks range (13-16) using 65 fieldworkers. Overall, 21.7 errors (95% confidence interval: 21.4, 22.0) per 10,000 data points were found: 13.0 (95% confidence interval: 12.6, 13.5) and 24.5 (95% confidence interval: 24.1, 24.9) errors on numeric and text fields respectively. These values meet standard quality threshold of 50 errors per 10,000 data points. The EDC's total variable cost was estimated at US$13,791.82 per site. In conclusion, the EDC is robust, allowing for timely and high-volume accurate data collection, and could be adopted in similar epidemiological settings.

Mapping for Health in Cameroon: Polio Legacy and Beyond.

During the poliovirus outbreak in Cameroon from October 2013 to April 2015, the Ministry of Public Health's Expanded Program on Immunization requested technical support to improve mapping of health district boundaries and health facility locations for more effective planning and analysis of polio program data. In December 2015, teams collected data on settlements, health facilities, and other features using smartphones. These data, combined with high-resolution satellite imagery, were used to create new health area and health district boundaries, providing the most accurate health sector administrative boundaries to date for Cameroon. The new maps are useful to and used by the polio program as well as other public health programs within Cameroon such as the District Health Information System and the Emergency Operations Center, demonstrating the value of the Global Polio Eradication Initiative's legacy.

Evaluation of an Android-based mHealth system for population surveillance in developing countries.

OBJECTIVE: In parts of the developing world traditionally modeled healthcare systems do not adequately meet the needs of the populace. This can be due to imbalances in both supply and demand--there may be a lack of sufficient healthcare and the population most at need may be unable or unwilling to take advantage of it. Home-based care has emerged as a possible mechanism to bring healthcare to the populace in a cost-effective, useful manner. This study describes the development, implementation, and evaluation of a mobile device-based system to support such services. MATERIALS AND METHODS: Mobile phones were utilized and a structured survey was implemented to be administered by community health workers using Open Data Kit. This system was used to support screening efforts for a population of two million persons in western Kenya. RESULTS: Users of the system felt it was easy to use and facilitated their work. The system was also more cost effective than pen and paper alternatives. DISCUSSION: This implementation is one of the largest applications of a system utilizing handheld devices for performing clinical care during home visits in a resource-constrained environment. Because the data were immediately available electronically, initial reports could be performed and important trends in data could thus be detected. This allowed adjustments to the programme to be made sooner than might have otherwise been possible. CONCLUSION: A viable, cost-effective solution at scale has been developed and implemented for collecting electronic data during household visits in a resource-constrained setting.