Innovative approach to control Zoonotic cutaneous leishmanisis: An Early warning system to predict ZCL outbreaks in Tunisia

Abstract

Purpose: Tunisia is one of the most exposed countries to climate change. The increase in temperature and degree of moisture is a favorable condition for the development of vectors of several diseases. Thus, the zoonotic cutaneous leishmaniasis (ZCL), vector-borne disease highly sensitive to climatic conditions, has seen a dramatic resurgence in parts of the country as Sidi Bouzid, taking advantage of the warming in recent decades. The aim of this work was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Methods & Materials: We used monthly reported ZCL cases from an active surveillance system which was implemented in three rural areas. Bioclimatic variables were monthly data between July 2009 and June 2015, recorded from a private station implemented. We used a generalized additive model (GAM) and a generalized additive mixed model (GAMM) to assess the relation between ZCL incidence and climate factors (temperature, rainfall, relative humidity, wind speed and rodents’ density). Coefficients from the best fit model were used to predict monthly ZCL number for the next season and were compared to observed ones. Results: There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The best-fit model showed significant associations between ZCL incidence and accumulated rainfall lagged 1 month, average temperature lagged 4 months, relative humidity with 4 months lag and rodent's density lagged 2 months. Prediction from GAMM approach gives a good prediction accuracy. The Pearson correlation coefficient value was 0.81. Conclusion: Understanding the role of the environmental and bioclimatic factors in ZCL occurrence can help to guide government policy-makers towards the creation and implementation of more effective policies to tackle the disease, and has important implications for prevention measures.