Development of a subgenomic clone system for Kyasanur Forest disease virus

Kyasanur Forest Disease Classification Framework Using Novel Extremal Optimization Tuned Neural Network in Fog Computing Environment

Kyasanur Forest Disease (KFD) is a life-threatening tick-borne viral infectious disease endemic to South Asia and has been taking so many lives every year in the past decade. But recently, this disease has been witnessed in other regions to a large extent and can become an epidemic very soon. In this paper, a new fog computing based e-Healthcare framework has been proposed to monitor the KFD infected patients in an early phase of infection and control the disease outbreak. For ensuring high prediction rate, a novel Extremal Optimization tuned Neural Network (EO-NN) classification algorithm has been developed using hybridization of the extremal optimization with the feed-forward neural network. Additionally, a location based alert system has also been suggested to provide the global positioning system (GPS)-based location information of each KFD infected user and the risk-prone zones as early as possible to prevent the outbreak. Furthermore, a comparative study of proposed EO-NN with state of art classification algorithms has been carried out and it can be concluded that EO-NN outperforms others with an average accuracy of 91.56%, a sensitivity of 91.53% and a specificity of 97.13% respectively in classification and accurate identification of risk-prone areas.

Tick-Borne Viruses

Ticks are important vectors for the transmission of pathogens including viruses. The viruses carried by ticks also known as tick-borne viruses (TBVs), contain a large group of viruses with diverse genetic properties and are concluded in two orders, nine families, and at least 12 genera. Some members of the TBVs are notorious agents causing severe diseases with high mortality rates in humans and livestock, while some others may pose risks to public health that are still unclear to us. Herein, we review the current knowledge of TBVs with emphases on the history of virus isolation and identification, tick vectors, and potential pathogenicity to humans and animals, including assigned species as well as the recently discovered and unassigned species. All these will promote our understanding of the diversity of TBVs, and will facilitate the further investigation of TBVs in association with both ticks and vertebrate hosts.