A comprehensive analysis of climate change impact on crimean-congo hemorrhagic fever spread (Russia, Kazakhstan, Turkey and Iran from 1999 to 2022)

Introduction: Crimean-Congo Hemorrhagic Fever (CCHF), a highly dangerous vector-borne disease transmitted by Hyalomma ticks, is endemic in Africa, the Middle East, Southeastern Europe, and parts of Asia. Global warming is causing notable shifts in the epidemiology of vector-borne diseases. Predicted climate changes, including temperature increases, may extend the geographical distribution of CCHF, necessitating the identification of climatic factors to enhance epidemiological and preventive measures in endemic areas and estimate potential territorial spread. Methods: The aim of this retrospective study was to assess the impact of climate change, specifically mean annual temperature, highest mean annual temperature, lowest mean annual temperature, and annual precipitation, on the incidence of CCHF in Russia, Kazakhstan, Turkey and Iran from 1999 to 2022. Statistical analyses were performed using Pearson correlation, regression with panel data using dummy variables for each country over time. Multiple linear regression analysis with stepwise exclusion of factors was also used. Results were considered significant at p < 0.05 in all analyses. Results: In the regression analysis incorporating data on disease incidence in individual countries over the studied timeframe, no statistically significant associations were discerned between the incidence of CCHF and climatic factors. However, upon removing the influence of individual countries, annual precipitation emerged as a statistically significant factor (b=1.600, s.e.=0.192, p<0.001), underscoring the potential impact of climate changes on the temporal dynamics of CCHF spread. The model exhibited statistical significance (p < 0.001), reflecting 60.3% of the variance in CCHF cases attributable to the considered factors. Multiple linear regression results indicate statistically significant relationships: Annual average maximum surface air temperature°C (b=27,645, s.e.= 7,859, p<0.001), Annual Precipitation (b=1,473, s.e.= 0,197, p<0.001). The model exhibited statistical significance (p < 0.001), reflecting 39.2% of the variance in CCHF cases attributable to the considered factors. Discussion: These results correspondent to with existing epidemiological data, affirming the positive correlation between CCHF incidence and temperature observed in Iran, Turkey, and Bulgaria. While the focus was on four specific countries, this study contributes to the growing evidence linking climate change to infectious disease epidemiology. The identified climate factors, temperature and precipitation, can serve as early warning indicators of potential disease outbreaks, improving surveillance and preparedness, particularly in endemic regions. Conclusion: The multidirectional dynamics of CCHF incidence in Russia, Kazakhstan, Turkey and Iran are driven by complex interactions with climate variables, highlighting the need for collaborative and interdisciplinary cooperation in molecular virology, immunology, vaccinology, entomology, veterinary medicine and public health to reduce the risks of CCHF infection. A holistic understanding of these complex interactions is critical for developing targeted and effective strategies to mitigate CCHF in the face of ongoing climate change.