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Enlightenment on oscillatory properties of 23 class B notifiable infectious diseases in the mainland of China from 2004 to 2020.
Han, Chuanliang; Li, Meijia; Haihambo, Naem; Cao, Yu; Zhao, Xixi.
  • Han C; State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
  • Li M; Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, Brussels, Belgium.
  • Haihambo N; Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, Brussels, Belgium.
  • Cao Y; State Key Laboratory of Earth Surface Process and Resource Ecology and Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing, China.
  • Zhao X; Beijing Anding Hospital, Capital Medical University, Beijing, China.
PLoS One ; 16(6): e0252803, 2021.
Article in English | MEDLINE | ID: covidwho-1453123
ABSTRACT
A variety of infectious diseases occur in mainland China every year. Cyclic oscillation is a widespread attribute of most viral human infections. Understanding the outbreak cycle of infectious diseases can be conducive for public health management and disease surveillance. In this study, we collected time-series data for 23 class B notifiable infectious diseases from 2004 to 2020 using public datasets from the National Health Commission of China. Oscillatory properties were explored using power spectrum analysis. We found that the 23 class B diseases from the dataset have obvious oscillatory patterns (seasonal or sporadic), which could be divided into three categories according to their oscillatory power in different frequencies each year. These diseases were found to have different preferred outbreak months and infection selectivity. Diseases that break out in autumn and winter are more selective. Furthermore, we calculated the oscillation power and the average number of infected cases of all 23 diseases in the first eight years (2004 to 2012) and the next eight years (2012 to 2020) since the update of the surveillance system. A strong positive correlation was found between the change of oscillation power and the change in the number of infected cases, which was consistent with the simulation results using a conceptual hybrid model. The establishment of reliable and effective analytical methods contributes to a better understanding of infectious diseases' oscillation cycle characteristics. Our research has certain guiding significance for the effective prevention and control of class B infectious diseases.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Seasons / Algorithms / Communicable Diseases / Disease Outbreaks / Models, Theoretical Type of study: Diagnostic study / Experimental Studies / Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0252803

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Seasons / Algorithms / Communicable Diseases / Disease Outbreaks / Models, Theoretical Type of study: Diagnostic study / Experimental Studies / Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0252803