The spread and prediction of Ebola virus

Yingyou Chen, Mingzhe Wen, Minghao Geng

Article ID: 386
Vol 1, Issue 1, 2018, Article identifier:

VIEWS - 295 (Abstract) 211 (PDF)


Ebola virus is a potent infectious disease virus that can cause Ebola haemorrhagic fever caused by human and primate. It has high mortality and easy infectivity to form a great obstacle to the steady development of human society. The profound understanding of the virus is particularly important harm. In this paper, a number of mathematical models are established to solve this problem. The software is used to analyze and predict the propagation of Ebola virus. The residual analysis is used to test the model. Finally, the effects of various control measures on controlling the epidemic are analyzed. In order to solve the problem, we will establish the infectious disease model to dynamically describe the spread of the virus in the 'virtual orangutan population'. Considering that the latent population is analyzed in this question, we will improve the model. Join the latent group (), and the migrants are divided into self-healing () and the dead (), to establish a suitable solution to this problem model. According to the relevant data given in the title, differential equations were established. For the second question, this question involves the one-way transmission of the virus across the species, so we can improve the model, on the basis of human contact with orangutans infected groups, the establishment of a one-way model to solve this problem. On the basis of the problem one, the differential equation is established, the model is predicted and tested. In the case of question 3, the number of human susceptible groups is much higher than that of the orangutan infection group by comparing the relevant data with the increase of the cure rate to 80% after the intervention of the outside experts. Therefore, the original data of human populations from experts can be ignored. Since then the virus spreads within a single species, the differential equation can be established according to the model in question 1 and the data values in the virtual human population are predicted. For question 4, the effect of the measures such as the strict enforcement of the various epidemic control measures and the improvement of the drug effect on the control of the epidemic are analyzed by comparing the above-mentioned models with the control measures.

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