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Informed Outbreak Response: Adaptive Strategies to Account for Behavior and Context in Containing Ebola

Laura Skrip, Postdoctoral Research Scientist, Institute for Disease Modeling

Laura Skrip, Postdoctoral Research Scientist

Background The west African Ebola epidemic (2014–15) necessitated behavior change in settings with prevalent and pre-existing unmet needs as well as extensive mechanisms for local community action. We aimed to assess spatial and temporal trends in community-reported needs and associations with behavior change, community engagement, and the overall outbreak situation in Sierra Leone.

Methods We conducted a retrospective, mixed-methods study using data from a large-scale community engagement and social mobilization program (the Social Mobilization Action Consortium, SMAC) in Sierra Leone. Community-voiced concerns expressed during 12,096 visits by SMAC mobilizers were automatically classified using a supervised machine learning algorithm and used to describe the evolution of satisfied and unsatisfied needs (basic, security, autonomy, respect, and social support) between Nov 12, 2014, and Dec 18, 2015, and across 14 districts. Via Bayesian hierarchical regression modelling, we investigated associations between needs categories and behaviors (numbers of individuals referred to treatment within 24 h of symptom onset or deaths responded to with safe and dignified burials) and the role of community engagement program status (initial versus follow-up visit) in the association between satisfied versus unsatisfied needs and behaviors.

Findings In general, significant associations were observed between unsatisfied needs categories and both prompt referrals to treatment and safe burials. Most notably, communities expressing unsatisfied capacity needs reported 14% fewer safe burials (relative risk [RR] 0·86, 95% credible interval [CrI] 0·82–0·91) and 24% fewer prompt referrals to treatment (RR 0·76, 0·70–0·83) than did those without unsatisfied capacity needs. The exception was expression of unsatisfied basic needs, which was associated with significantly fewer prompt referrals only (RR 0·86, 95% CrI 0·79–0·93). Compared with triggering visits by community mobilisers, follow-up visits were associated with 40% more prompt referrals (RR 1·40, 95% CrI 1·30–1·50) and 8% more safe burials (RR 1·08, 1·02–1·14).

Conclusion Community-based development of locally feasible, locally owned action plans, with the support of community mobilisers, has potential to address unmet needs for more sustained behavior change in outbreak settings.