CKCarl Kinkade

Carl Kinkade

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

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Previous Organizations / Institutes

The organizations / institutes from the scholar's other articles in the past ten years


Carl Kinkade has a total of 21 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Modernizing Vaccination Data System: Design, Development, and Deployment of a Digital Vaccination Registry in Liberia, 2023–2025

    by Olorunsogo Bidemi Adeoye, Dieula Delissaint Tchoualeu, Patrick K. Konwloh, Halima Abdu, Calvin Coleman, Abizeyimana Aime Theophile, Anthony Lucene Fortune, Yuah Nemah, Carl Kinkade, Oluwasegun Joel Adegoke, et al.

    Background: Liberia modernized vaccination data systems in 2023–2025 by piloting a District Health Information System (DHIS2)-based Digital Vaccination Registry (Electronic Immunization Registry, EIR) to address the limitations of paper-based workflows and of a proprietary COVID-19 electronic platform (offline gaps, lack of unique identifiers, performance issues and cost). Objective: To assess a pilot platform by evaluating training, registry use and device management, utility for routine immunization, vaccine logistics and Adverse Events Following Immunization (AEFI) data, and routine immunization data quality in the DHIS2 mobile application compared with paper registers. Methods: Using the Public Health Informatics Institute’s Collaborative Requirements Development Methodology, stakeholders defined requirements, trained users and implemented a pilot. Mixed methods were used; a mini data audit was performed, and qualitative data were collected across 19 facilities in Montserrado, Gbarpolu and Grand Bassa. Seventy-eight health workers were trained to use the DHIS2 mobile application. Results: The future state design replaces paper aggregation steps with real-time mobile entry to a national registry and dashboard. Dual entry persisted during high-volume periods. The mini data audit found discrepancies between facility paper registers and DHIS2-EIR entries for child enrollment data and, Bacillus Calmette Guérin and Diphtheria–Pertussis–Tetanus dose administration records Participants attributed these discrepancies to internet and device problems and challenges navigating the system. Participants requested a training manual, improved connectivity at point of service, integration with supportive supervision, additional staff and system features (field to record hospital number, automated next visit date, and vaccination status prompts). Conclusions: Lessons from the pilot will inform country-wide implementation, including planned linkage with electronic birth and death registration to enable a unique child identifier and reduce manual errors and delays.

  • Open Access

    A comparison of smartphones to paper-based questionnaires for routine influenza sentinel surveillance, Kenya, 2011–2012

    by Henry N Njuguna, Deborah L Caselton, Geoffrey O Arunga, Gideon O Emukule, Dennis K Kinyanjui, Rosalia M Kalani, Carl Kinkade, Phillip M Muthoka, Mark A Katz, Joshua A Mott

    For disease surveillance, manual data collection using paper-based questionnaires can be time consuming and prone to errors. We introduced smartphone data collection to replace paper-based data collection for an influenza sentinel surveillance system in four hospitals in Kenya. We compared the quality, cost and timeliness of data collection between the smartphone data collection system and the paper-based system. Since 2006, the Kenya Ministry of Health (MoH) with technical support from the Kenya Medical Research Institute/Centers for Disease Control and Prevention (KEMRI/CDC) conducted hospital-based sentinel surveillance for influenza in Kenya. In May 2011, the MOH replaced paper-based collection with an electronic data collection system using Field Adapted Survey Toolkit (FAST) on HTC Touch Pro2 smartphones at four sentinel sites. We compared 880 paper-based questionnaires dated Jan 2010-Jun 2011 and 880 smartphone questionnaires dated May 2011-Jun 2012 from the four surveillance sites. For each site, we compared the quality, cost and timeliness of each data collection system. Incomplete records were more likely seen in data collected using pen-and-paper compared to data collected using smartphones (adjusted incidence rate ratio (aIRR) 7, 95% CI: 4.4-10.3). Errors and inconsistent answers were also more likely to be seen in data collected using pen-and-paper compared to data collected using smartphones (aIRR: 25, 95% CI: 12.5-51.8). Smartphone data was uploaded into the database in a median time of 7 days while paper-based data took a median of 21 days to be entered (p < 0.01). It cost USD 1,501 (9.4%) more to establish the smartphone data collection system ($17,500) than the pen-and-paper system (USD $15,999). During two years, however, the smartphone data collection system was $3,801 (7%) less expensive to operate ($50,200) when compared to pen-and-paper system ($54,001). Compared to paper-based data collection, an electronic data collection system produced fewer incomplete data, fewer errors and inconsistent responses and delivered data faster. Although start-up costs were higher, the overall costs of establishing and running the electronic data collection system were lower compared to paper-based data collection system. Electronic data collection using smartphones has potential to improve timeliness, data integrity and reduce costs.