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Background: Kyasanur forest disease (KFD), known as monkey fever, was for the first time reported in 1957 from the Shivamogga district of Karnataka. But since 2011, it has been spreading to the neighbouring state of Kerala, Goa, Maharashtra, and Tamil Nadu. The disease is transmitted to humans, monkeys and by the infected bite of ticks Haemaphysalis spinigera. It is known that deforestation and ecological changes are the main reasons for KFD emergence, but the bio-climatic understanding and emerging pathways remain unknown.Methods: The present study aims to understand the bio-climatic determinants of distribution of tick vector of KFD in southern India using the Maximum Entropy (MaxEnt) model. The analysis was done using 34 locations of Haemaphysalis spinigera occurrence and nineteen bio-climatic variables from WorldClim. Climatic variables contribution was assessed using the Jackknife test and mean AUC 0.859, indicating the model performs with very high accuracy.Results: Most influential variables affecting the spatial distribution of Haemaphysalis spinigera were the average temperature of the warmest quarter (bio10, contributed 32.5%), average diurnal temperature range (bio2, contributed 21%), precipitation of wettest period (bio13, contributed 17.6%), and annual precipitation (bio12, contributed 11.1%). The highest probability of Haemaphysalis spinigera presence was found when the mean warmest quarter temperature ranged between 25.4 and 30 °C. The risk of availability of the tick increased noticeably when the mean diurnal temperature ranged between 8 and 10 °C. The tick also preferred habitat having an annual mean temperature (bio1) between 23 and 26.2 °C, mean temperature of the driest quarter (bio9) between 20 and 28 °C, and mean temperature of the wettest quarter (bio8) between 22.5 and 25 °C.Conclusions: The results have established the relationship between bioclimatic variables and KFD tick distribution and mapped the potential areas for KFD in adjacent areas wherein surveillance for the disease is warranted for early preparedness before the occurrence of outbreaks etc. The modelling approach helps link bio-climatic variables with the present and predicted distribution of Haemaphysalis spinigera tick. [ABSTRACT FROM AUTHOR]

Background: Ever since Crimean-Congo hemorrhagic fever [CCHF] discovered in India, several outbreaks of this disease have been recorded in Gujarat State, India. During the year 2011 to 2015 several districts of Gujarat and Rajasthan state (Sirohi) found to be affected with CCHF including the positivity among ticks and livestock. During these years many infected individuals succumbed to this disease; which subsequently led to nosocomial infections. Herein, we report CCHF cases recorded from Rajasthan state during January 2015. This has affected four individuals apparently associated with one suspected CCHF case admitted in a private hospital in Jodhpur, Rajasthan. Case presentation: A 30-year-old male was hospitalized in a private hospital in Jodhpur, Rajasthan State, who subsequently had developed thrombocytopenia and showed hemorrhagic manifestations and died in the hospital. Later on, four nursing staff from the same hospital also developed the similar symptoms (Index case and Case A, B, C). Index case succumbed to the disease in the hospital at Jodhpur followed by the death of the case A that was shifted to AIIMS hospital, Delhi due to clinical deterioration. Blood samples of the index case and Case A, B, C were referred to the National institute of Virology, Pune, India for CCHF diagnosis from the different hospitals in Rajasthan, Delhi and Gujarat. However, a sample of deceased suspected CCHF case was not referred. Subsequently, blood samples of 5 nursing staff and 37 contacts (Case D was one of them) from Pokhran area, Jaisalmer district were referred to NIV, Pune. Conclusions: It clearly indicated that nursing staff acquired a nosocomial infection while attending the suspected CCHF case in an Intensive Care Unit of a private hospital in Jodhpur. However, one case was confirmed from the Pokhran area where the suspected CCHF case was residing. This case might have got the infection from suspected CCHF case or through other routes. CCHF strain associated with these nosocomial infections shares the highest identity with Afghanistan strain and its recent introduction from Afghanistan cannot be ruled out. However, lack of active surveillance, unawareness among health care workers leads to such nosocomial infections. [ABSTRACT FROM AUTHOR]