COVID-19 imposed huge burdens and obligations on public health and epidemiology centers to elevate the role of periodic surveillance and case tracing in order to cease the spread of the pandemic. As a result, nations globally are developing various digital solutions for accurate surveillance, reporting of new cases, tracing contacts, and monitoring public health. Traditional tracking and reporting methods have been replaced by intelligent solutions for accurate and efficient reporting. Tools such smart phones, portable devices, and drones have been incorporated in these solutions. These devices produce large amount of data on daily basis and need to be processed instantly to battle the spread of the virus and this is where AI is needed. While the need for AI in disease control and surveillance is clear, the application of AI methods and machine learning algorithms in this field needs further studies. This paper is a systematic review of using AI in COVID-19 surveillance literature to answer the following questions: 1. What AI-based methods are used globally for COVID-19 surveillance? 2. How effective are these methods, and 3. What are the methods used in the Kingdom of Saudi Arabia.
Software And Hardware