An early warning system for Crimean-Congo haemorrhagic fever seasonality in Turkey based on remote sensing technology

Abstract

In the last few years, Crimean-Congo haemorrhagic fever (CCHF) has been reported as an emerging tickborne disease in Turkey. This paper deals with the preparation of an early warning system, aimed to predict the beginning of the CCHF season in Turkey based on a clear, simple and repeatable remotely-sensed signal. Decadal (mean of 10 days) values of the normalized difference vegetation index (NDVI) at 1 km resolution were used on a set of 952 confirmed, accurately geo-referenced, clinical cases between 2003 and 2006. A prerequisite is that the signal should be observable between 2 and 3 decadals before a given moment of the season to be of value as early warning. Decadals marking the 10th percentile or the 25th quartile in the frequency distribution of case reporting were selected as markers for the beginning of season of risk. Neither raw nor accumulated decadal NDVI signals were able to predict the onset of this season. However, when we defined the NDVI anomaly (NDVIa) as the positive difference between decadal NDVI values and the average for the previous year, this standardized measure gave a homogeneous overview of the changes in the NDVI signal producing a NDVIa slope for the decadals 10 to 13 that was always greater than 0. We conclude that observing this slope over time can be used as an early-warning system as it would predict the build-up of the number of cases 20 days in advance with an accuracy of 82% (10th percentile) or 98% (25th quartile).

Keywords

• Crimean-Congo haemorrhagic fever, early warning, Turkey, normalized difference vegetation index, remote sensing.