Introduction - Non-pharmaceutical interventions (NPIs) are a crucial suite of measures to prevent and control infectious disease outbreaks. They are particularly important for crisis-affected populations that typically reside in settings characterised by overcrowding, inadequate access to healthcare and resource limitations. To describe the landscape of research and identify evidence gaps concerning the acceptability, feasibility, and effectiveness of NPIs among crisis-affected populations and informal settings, we conducted a systematic scoping review of the published evidence.

Methods -  We systematically reviewed peer-reviewed articles published between 1970 and 2020 to collate available evidence on the feasibility, acceptability, and effectiveness of NPIs in crisis-affected populations and informal settlements. We performed quality assessments of each study using a standardised questionnaire.

Results - Our review included 158 studies published in 85 peer-reviewed articles. Most research used low quality study designs. The acceptability, feasibility, and effectiveness of NPIs was highly context dependent. In general, simple and cost-effective interventions such as community-level environmental cleaning and provision of water, sanitation and hygiene services, and distribution of items for personal protection such as insecticide-treated nets, were both highly feasible and acceptable. Logistical, financial, and human resource constraints affected both the implementation and sustainability of measures. Community engagement emerged as a strong factor contributing to the effectiveness of NPIs. Conversely, measures that involve potential restriction on personal liberty such as case isolation were found to be less acceptable to the community.

Conclusion- Overall, the evidence base was patchy, with substantial knowledge gaps between differing between settings and pathogens. Although implementation of NPIs presents unique practical challenges, it is critical that the lessons learned are shared with the wider community to build a robust evidence base.