COVID-19, Artificial Intelligence and Wastewater-based Epidemiology

Özyaman F., Yılmaz Ö.

Artificial Intelligence Theory and Applications, cilt.2, sa.1, ss.319-323, 2021 (Hakemli Dergi)

Özet

The ongoing COVID-19 pandemic is a health emergency globally. Wastewater-based epidemiology (WBE) supported with artificial intelligence (AI) is a noninvasive, efficient, population-wide, cost-effective, complementary tool in detecting SARSCoV-2 in wastewater and providing early warnings of ongoing and future pandemics. The combination of WBE, AI, nanotechnology, predictions, surveillance and modeling is important for early detection and prevention of pandemics. Examples of new, rapid, automated, sensitive and quantitative methods aided with AI are Droplet-Digital-PCR, Point-of -Care, biosensors, biomarkers, and combinations of biosensors, microfluidic and paper-based instruments. The combination of edge computing, AI and blockchain is used for precise results, rapid data processing and sharing. WBE computational model and simulation show the feasibility, advantages, disadvantages of WBE with the temperature, water use and travel time variables. Model predicting the fecal-oral transmission way according to the percentages of intrinsic disorder and hardness of viral shell, SARS-CoV-2 is resistant and are shed in high numbers from the body. WBE is used to monitor the new variants, community vaccination results and to detect the infected person by near-source tracking. Pandemic’s effect on water cycle can be compensated by water industry digitalization such as using the data of public health and wastewater. AI is also useful in planning the post-COVID-19 cities and the treatment plants by models. WBE supported with AI is an important approach for early detection, control of the COVID-19 pandemic and protection of public health. Further studies are required to overcome the challenges and for improvement.