Epidemic Surveillance in a Low Resource Setting: Lessons from an Evaluation of the Solomon Islands Syndromic Surveillance System, 2017

Background: Solomon Islands is one of the least developed countries in the world. Recognising that timely detection of outbreaks is needed to enable early and effective response to disease outbreaks, the Solomon Islands government introduced a simple syndromic surveillance system in 2011. We conducted the first evaluation of the system and the first exploration of a national experience within the broader multi-country Pacific Syndromic Surveillance System to determine if it is meeting its objectives and to identify opportunities for improvement.

Methods: We used a multi-method approach involving retrospective data collection and statistical analysis, modelling, qualitative research and observational methods.

Results: We found that the system was well accepted, highly relied upon and designed to account for contextual limitations. We found the syndromic algorithm used to identify outbreaks was moderately sensitive, detecting 11.8% (IQR: 6.3-25.0%), 21.3% (IQR: 10.3-36.8%), 27.5% (IQR: 12.8-52.3%) and 40.5% (IQR: 13.5-65.7%) of outbreaks that caused small, moderate, large and very large increases in case presentations to health facilities, respectively. The false alert rate was 10.8% (IQR: 4.8-24.5%). Rural coverage of the system was poor. Limited workforce, surveillance resourcing and other 'upstream' health system factors constrained performance.

Conclusions: The system has made a significant contribution to public health security in Solomon Islands, but remains insufficiently sensitive to detect small-moderate sized outbreaks and hence should not be relied upon as a stand-alone surveillance strategy. Rather, the system should sit within a complementary suite of early warning surveillance activities including event-based, in-patient- and laboratory-based surveillance methods. Future investments need to find a balance between actions to address the technical and systems issues that constrain performance while maintaining simplicity and hence sustainability.