Objective: Understanding long-term disaster effects is key to building theories of recovery and informing policymaking. Findings regarding long-term recovery are inconsistent, with some scholars finding that disasters have little long-term impact, and others asserting otherwise. To assist in resolving this discord, we apply a conceptual framework and computational model of community resilience (“COPEWELL”) that places community functioning (CF) at the center of evaluating the effects of disaster over time. Using flooding as a disaster type, we hypothesize a change in baseline CF trend when a flood-related federally declared disaster event occurs. Methods: We used county-level flood-related federally declared disaster events (2010–2014) and selected population demographics to study their effects on annual CF trends among United States counties (N = 3141). Results: In multivariate analysis of baseline CF, we found a significant negative relationship of prior five-year flood status, federal regions relative to the Northeast (Region I), lower total earnings, and greater population size. Annual CF trend was 0.09% (95%CI: 0.01%–0.16%). In multivariate analysis, significant predictors included baseline CF (β = −0.0178, −0.0047–−0.0309), any concurrent flood-related federally declared disaster events (−0.0024, −0.0040–−0.0008), ten-year prior flood events (−0.0017, −0.0034–−0.0000) and concurrent population change (−0.0186, −0.0338–−0.0035). Conclusions: Recent floods depress baseline CF, while concurrent and ten-year-ago floods depress trend in CF. Resilience may potentially be modified by raising baseline CF and maintaining population over time.
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