当前位置: X-MOL 学术Artif. Intell. Rev. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Prediction of global spread of COVID-19 pandemic: a review and research challenges
Artificial Intelligence Review ( IF 12.0 ) Pub Date : 2021-07-16 , DOI: 10.1007/s10462-021-09988-w
Saloni Shah 1 , Aos Mulahuwaish 1 , Kayhan Zrar Ghafoor 2, 3 , Halgurd S Maghdid 4
Affiliation  

Since the initial reports of the Coronavirus surfacing in Wuhan, China, the novel virus currently without a cure has spread like wildfire across the globe, the virus spread exponentially across all inhabited continent, catching local governments by surprise in many cases and bringing the world economy to a standstill. As local authorities work on a response to deal with the virus, the scientific community has stepped in to help analyze and predict the pattern and conditions that would influence the spread of this unforgiving virus. Using existing statistical modeling tools to the latest artificial intelligence technology, the scientific community has used public and privately available data to help with predictions. A lot of this data research has enabled local authorities to plan their response—whether that is to deploy tightly available medical resources like ventilators or how and when to enforce policies to social distance, including lockdowns. On the one hand, this paper shows what accuracy of research brings to enable fighting this disease; while on the other hand, it also shows what lack of response from local authorities can do in spreading this virus. This is our attempt to compile different research methods and comparing their accuracy in predicting the spread of COVID-19.

更新日期:2021-07-18
down
wechat
bug