Abstract
COVID-19 is the worst contagious disaster in the history of humankind, triggering a worldwide sickness pandemic. In lacking specialized treatments or immunizations, finding and eliminating the infection source is the best option to decrease disease transmission and lower sickness and degree of fatality among the general public. Generally, few significant barriers are present in the existing system of monitoring the contamination. One of the obstacles is regarding health-related data storage. The user's e-health data is kept in a traditional method that might have been compromised if shared with third parties. Secondly, the current disease tracking technologies fail to monitor diseases numerous ways. The tracing system is either personal or location-based. Apart from these, gathering individual consent and sharing their health data with unknown associations is a real-time problem. We propose a blockchain-based data system that maintains confidentiality with transparency. Users can acquire unlimited and nontampered vital routes as the suggested blockchain solution leverages to link the user/patient and approved solvers. Also, automatically executed smart contracts are constructed to desensitize the user ID and reallocation. The anonymous feature delivered by private blockchain with wireless technologies defends the customer's identity secrecy. We develop a matching approach using machine learning technology. Users may take safeguards in advance by employing our suggested analytical technique for predicting the risk due to infectious source presence.