Integrated digital system for community engagement and community-based surveillance during the 2014-2016 Ebola outbreak in Sierra Leone: lessons for future health emergencies.

Community engagement and community-based surveillance are essential components of responding to infectious disease outbreaks, but real-time data reporting remains a challenge. In the 2014-2016 Ebola outbreak in Sierra Leone, the Social Mobilisation Action Consortium was formed to scale-up structured, data-driven community engagement. The consortium became operational across all 14 districts and supported an expansive network of 2500 community mobilisers, 6000 faith leaders and 42 partner radio stations. The benefit of a more agile digital reporting system became apparent within few months of implementing paper-based reporting given the need to rapidly use the data to inform the fast-evolving epidemic. In this paper, we aim to document the design, deployment and implementation of a digital reporting system used in six high transmission districts. We highlight lessons learnt from our experience in scaling up the digital reporting system during an unprecedented public health crisis. The lessons learnt from our experience in Sierra Leone have important implications for designing and implementing similar digital reporting systems for community engagement and community-based surveillance during public health emergencies.

Community engagement in outbreak response: lessons from the 2014-2016 Ebola outbreak in Sierra Leone.

Documentation of structured community engagement initiatives and real-time monitoring of community engagement activities during large-scale epidemics is limited. To inform such initiatives, this paper analyses the Community Led Ebola Action (CLEA) approach implemented through the Social Mobilization Action Consortium (SMAC) during the 2014-2016 Ebola epidemic in Sierra Leone. The SMAC initiative consisted of a network of 2466 community mobilisers, >6000 religious leaders and 42 local radio stations across all 14 districts of Sierra Leone. Community mobilisers were active in nearly 70% of all communities across the country using the CLEA approach to facilitate community analysis, trigger collective action planning and maintain community action plans over time. CLEA was complemented by interactive radio programming and intensified religious leader engagement.Community mobilisers trained in the CLEA approach used participatory methods, comprised of an initial community 'triggering' event, action plan development and weekly follow-ups to monitor progress on identified action items. Mobilisers collected operational and behavioural data on a weekly basis as part of CLEA. We conducted a retrospective analysis of >50 000 weekly reports from approximately 12 000 communities from December 2014 to September 2015. The data showed that 100% of the communities that were engaged had one or more action plans in place. Out of the 63 110 cumulative action points monitored by community mobilisers, 92% were marked as 'in-progress' (85%) or 'achieved' (7%) within 9 months. A qualitative examination of action points revealed that the in-progress status was indicative of the long-term sustainability of most action points (eg, continuous monitoring of visitors into the community) versus one-off action items that were marked as achieved (eg, initial installation of handwashing station). Analysis of behavioural outcomes of the intervention indicate an increase over time in the fraction of reported safe burials and fraction of reported cases referred for medical care within 24 hours of symptom onset in the communities that were engaged.Through CLEA, we have demonstrated how large-scale, coordinated community engagement interventions can be achieved and monitored in real-time during future Ebola epidemics and other similar epidemics. The SMAC initiative provides a practical model for the design, implementation and monitoring of community engagement, integration and coordination of community engagement interventions with other health emergency response pillars, and adaptive strategies for large-scale community-based operational data collection.