Method, system and device for predicting number of accumulated infection people of epidemic situations in regions of novel coronavirus

• Main Authors: WANG YIJUN, YANG ZIFENG, HE JIANXING, TAN JUNDONG, ZHONG MING, ZENG ZHIQI, LIU YONG, WANG KE, WANG YAONAN
• Format: Patent
• Language: Chinese; English
• Published: 15.06.2021
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a method, system and device for predicting the number of accumulated infected people of epidemic situations in regions of novel coronavirus, and belongs to the field of artificial intelligence assisted infectious disease dynamics. The problems that a traditional infectious disease prediction model has confirmation time delay, real confirmation data of each day cannot be determined, and the accuracy of a prediction result is low are solved. The method comprises the following steps: flipping a time sequence A0 of a newly added diagnosed number, carrying out convolution on the flipped A0 by using delay day number distribution from infection to diagnose, flipping a sequence after convolution, and recording a vector after flipping as A1; dividing the time sequence A1 of the newly added diagnosed number of people by a vector A2 after overturning of a cumulative distribution function of gamma distribution to obtain a time sequence A3 of the newly added diagnosed number of people after right d