Modeling the time-lag effect of sea surface temperatures on ciguatera poisoning in the South Pacific: Implications for surveillance and response

Ciguatera poisoning (CP), arising from ciguatoxins produced by toxic dinoflagellate Gambierdiscus, is one of the most common food-borne diseases in the South Pacific. Climate change as well as its related events have been hypothesized to a higher abundance and wider presence of toxic dinoflagellates, hence a higher risk of the disease. Yet existing studies assessing the relationship between climate factors and CP are limited or based on old data. In this study, we used prewhitened cross-correlation analysis and auto-regressive integrated moving-average (ARIMA) modeling to develop predictive models of monthly CP incidence in Cook Islands and French Polynesia, two ciguatera-endemic regions in the South Pacific, utilizing the latest epidemiological data. Results reveal the significant time-lagged associations between the monthly CP incidence rate and several indicators relating to sea surface temperature (SST). In particular, SST anomaly is proven to be a strong positive predictor of an increased ciguatera incidence for both countries. If these time-lags can be supported by more investigations, it will allow health authorities to take appropriate actions, to limit or avoid an epidemic risk, especially on high-risk climate scenarios.