Technology in survey data collection: Cost-effective advances from resource-constrained settings

In resource-constrained settings with minimal infrastructure and lack of ubiquitous Internet and cellular satellite technology, paper-based methods for survey data collection are standard. However, digital data collection is becoming more common in limited-resource settings, and has been employed in several countries in sub-Saharan Africa. In addition to the clear advantages of digital survey data collection (increased security, efficiency, precision; decreased human error and labor), this method also has cost advantages compared to paper-based methods. One study conducted in Tanzania assessed the feasibility and acceptability of using electronic data capture, comparing it to paper-based data collection (Thriemer et al., 2012). The digital method resulted in nearly US$6,000 of savings, amounting to approximately 25% of the cost needed for paper-based data collection. Another study (Ali et al., 2010) reduced costs by approximately US$10,000 in using personal digital assistants (PDAs) compared to paper-based surveys. Despite the large capital investment needed to purchase the hardware, costs were offset by savings on hiring fewer data entry clerks, lower labor expenditures, fewer computers, less paper, and decreased printing. In Western Kenya, Were and colleagues (2010) saved US$0.06 per participant after transitioning from paper-based to a PDA/GPS-based system used during data collection. The Suubi+Adherence study (PI: Ssewamala; 1R01HD074949-01) will use digital software to collect baseline and follow-up data from nearly 800 HIV-positive adolescents ages 11-16 years in southern Uganda – a country facing the same scarcity and infrastructural challenges as much of the rest of the African sub-continent. Ssewamala and colleagues will demonstrate the cost-effectiveness of digital data collection compared to paper-based methods employed in previous and ongoing studies with a comparable demographic in the same study region. The use of digital data collection has implications for hardware and software developers; as well as clinicians and researchers working in sub-Saharan Africa and other resource-constrained settings.