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. 2013 Sep 16;8(9):e74570.
doi: 10.1371/journal.pone.0074570. eCollection 2013.

A Novel Electronic Data Collection System for Large-Scale Surveys of Neglected Tropical Diseases

Free PMC article

A Novel Electronic Data Collection System for Large-Scale Surveys of Neglected Tropical Diseases

Jonathan D King et al. PLoS One. .
Free PMC article


Background: Large cross-sectional household surveys are common for measuring indicators of neglected tropical disease control programs. As an alternative to standard paper-based data collection, we utilized novel paperless technology to collect data electronically from over 12,000 households in Ethiopia.

Methodology: We conducted a needs assessment to design an Android-based electronic data collection and management system. We then evaluated the system by reporting results of a pilot trial and from comparisons of two, large-scale surveys; one with traditional paper questionnaires and the other with tablet computers, including accuracy, person-time days, and costs incurred.

Principle findings: The electronic data collection system met core functions in household surveys and overcame constraints identified in the needs assessment. Pilot data recorders took 264 (standard deviation (SD) 152 sec) and 260 sec (SD 122 sec) per person registered to complete household surveys using paper and tablets, respectively (P = 0.77). Data recorders felt a lack of connection with the interviewee during the first days using electronic devices, but preferred to collect data electronically in future surveys. Electronic data collection saved time by giving results immediately, obviating the need for double data entry and cross-correcting. The proportion of identified data entry errors in disease classification did not differ between the two data collection methods. Geographic coordinates collected using the tablets were more accurate than coordinates transcribed on a paper form. Costs of the equipment required for electronic data collection was approximately the same cost incurred for data entry of questionnaires, whereas repeated use of the electronic equipment may increase cost savings.

Conclusions/significance: Conducting a needs assessment and pilot testing allowed the design to specifically match the functionality required for surveys. Electronic data collection using an Android-based technology was suitable for a large-scale health survey, saved time, provided more accurate geo-coordinates, and was preferred by recorders over standard paper-based questionnaires.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.


Figure 1
Figure 1. Example screen shot: looping fields for members grouped within a household record.
As seen in a novel Android application for collecting data in household surveys.
Figure 2
Figure 2. Capturing the identification number from a barcode-labeled stool specimen.
As conducted during an integrated survey of neglected tropical diseases in Amhara National Regional state, Ethiopia in 2011.
Figure 3
Figure 3. Distance between the recorded location of a surveyed household and the cluster centroid.
Households surveyed in trachoma impact assessments in South Wollo (paper-based questionnaire 2010) and South Gondar (electronic data collection 2011), Ethiopia.
Figure 4
Figure 4. Proportion of total time (person days) required to complete survey activities by collection method.
Time as implemented using paper-based questionnaire and Android-based electronic form in two large-scale (360 clusters each) trachoma impact assessments in Ethiopia 2010 and 2011.

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Grant support

Funding was provided through Lions Club International Foundation and The Carter Center Sight First Initiative. Staff from The Carter Center were involved in the study design,data collection, analysis, decision to publish, and preparation of the manuscript.