Cutaneous Leishmaniasis in Israel and Correlation over Time with Average Ambient Temperature

摘要

Background: Israel is endemic for Cutaneous Leishmaniazis (CL). CL is one of the vector-borne diseases that could be affected by climate change. Few studies have examined the relationship between environmental temperature and the sand fly, and little has been published on the relation between the appearance of CL in humans and climatic changes. Aims: to examine the relationship between CL incidence and ambient temperature changes over a long-term period in different regions of the country. Methods: Epidemiology Division of the Ministry of health receives mandatory reporting information on new cases of CL. We used the data reported and processed nationally between the years 1981 - 2011 in all regions of the country. The National Meteorological Service provided access to its data file of temperatures measured every ten minutes in relevant monitoring stations. We calculated weekly moving average of the maximum and minimum temperatures. Using a statistical model, we tested lag correlation between average temperatures and reported CL incidence in the following areas: Jerusalem, Tiberias, Tel-Aviv (TA) and Beer-Sheva (BSh). Results:The maximal temperatures in BSh within 52 weeks (annual cycle) were higher than Jerusalem and TA. The maximum lag was 13 weeks in Jerusalem (r=0.892, 95% CI: 0.818; (0.937 and BSh (r=0.887, 95% CI: 0.810; 0.934). In TA max lag was 12 weeks with r=0.89 (95% CI: 0.815; 0.936). There was a different relationship between climate and CL incidence in the various measurement stations: in the cooler period (41st to 14th weeks) in BSh no significant correlation was found between the number of reported cases and the minimal and maximal temperature - moving lag in the annual cycle. Conclusions: After a latent period of up to 12-14 weeks following high environmental temperatures, an increase in CL incidence was observed. It is important to use this evidence to anticipate and apply preventive measures for CL spread at the optimal times of the year.