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Global prediction for mpox epidemic.
Zhang, Li; Huang, Jianping; Yan, Wei; Zhao, Yingjie; Wang, Danfeng; Chen, Bin.
Afiliación
  • Zhang L; College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China.
  • Huang J; College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, 730000, China. Electronic address: hjp@lzu.edu.cn.
  • Yan W; College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China.
  • Zhao Y; College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China.
  • Wang D; Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, 730000, China.
  • Chen B; College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China.
Environ Res ; 243: 117748, 2024 Feb 15.
Article en En | MEDLINE | ID: mdl-38036205
The mpox epidemic had spread worldwide and become an epidemic of international concern. Before the emergence of targeted vaccines and specific drugs, it is necessary to numerically simulate and predict the epidemic. In order to better understand and grasp its transmission situation, and take some countermeasures accordingly when necessary, we predicted and simulated mpox transmission, vaccination and control scenarios using model developed for COVID-19 predictions. The results show that the prediction model can also achieve good results in predicting the mpox epidemic based on modified SEIR model. The total number of people infected with mpox on Dec 31, 2022 reached 83878, while the prediction of the model was 96456 with a relative error of 15%. The United States, Brazil, Spain, France, the United Kingdom and Germany are six countries with serve mpox epidemic. The predictions of their epidemic are 30543, 11191, 7447, 5945, 5606 and 4291 cases respectively, with an average relative error of 20%. If 30% of the population is vaccinated using a vaccine that is 78% effective, the number of infected people will drop by 29%. This shows that the system can be practically applied to the prediction of mpox epidemic and provide corresponding decision-making reference.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Mpox / Epidemias / COVID-19 Límite: Humans País/Región como asunto: America do sul / Brasil / Europa Idioma: En Revista: Environ Res Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Mpox / Epidemias / COVID-19 Límite: Humans País/Región como asunto: America do sul / Brasil / Europa Idioma: En Revista: Environ Res Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos