It is easier with this model to predict epidemics based on precedents!
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Emrullah YiÄŸit
Mehmet Efe Zengin
Mathematicians have developed a new model for CBBR(Case-Based Rate Reasoning) model for predicting dynamics of pandemic. Thanks to this model, the scientists are able to forecast the spread of COVID-19 in Russia. These predictions are made based on data collected from the dynamics of the epidemic in other countries which had this before. The researchers encountered a difficulty when they tried to build such a model in April 2020 since there was no available mathematical data related to dynamics of the COVID-19. No model would work for COVID-19 in that time period. The mathematicians say that use of statistical datas help them to create a range with confidence intervals of weekly basis for new cases at St Petersburg and Moscow. According to the last month of 2020’s forecasting, it was said to be 24,000-27,000 new cases for particular regions. How does this model work? Establishing such a model, providing them with information about the peak of the virus and the load level of the healthcare system. Iterative approach, updating data in real time, enables them to make more accurate predictions. Some significant parameters, the heuristic selection of interval lengths from many different countries make up the basics of the model.
(Dec. 9, 2020)
As we live through, we can not reckon a life without the presence of the knowledge derived from mathematics.
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References:
PhysOrg, St. Petersburg State University, 9 Dec. 2020, phys.org/news/2020-12-mathematicians-epidemics-based.html.
staff, Science X. “Mathematicians Develop a New Model for Predicting Epidemics Based on Precedents.” Phys.org, Phys.org, 9 Dec. 2020, phys.org/news/2020-12-mathematicians-epidemics-based.html.