Changes in Temporal Properties of Notifiable Infectious Disease Epidemics in China During the COVID-19 Pandemic: Population-Based Surveillance Study
BackgroundCOVID-19 was first reported in 2019, and the Chinese government immediately carried out stringent and effective control measures in response to the epidemic. ObjectiveNonpharmaceutical interventions (NPIs) may have impacted incidences of other infectious...
| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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JMIR Publications
2022-06-01
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| Series: | JMIR Public Health and Surveillance |
| Online Access: | https://publichealth.jmir.org/2022/6/e35343 |
| _version_ | 1827858231556308992 |
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| author | Xixi Zhao Meijia Li Naem Haihambo Jianhua Jin Yimeng Zeng Jinyi Qiu Mingrou Guo Yuyao Zhu Zhirui Li Jiaxin Liu Jiayi Teng Sixiao Li Ya-nan Zhao Yanxiang Cao Xuemei Wang Yaqiong Li Michel Gao Xiaoyang Feng Chuanliang Han |
| author_facet | Xixi Zhao Meijia Li Naem Haihambo Jianhua Jin Yimeng Zeng Jinyi Qiu Mingrou Guo Yuyao Zhu Zhirui Li Jiaxin Liu Jiayi Teng Sixiao Li Ya-nan Zhao Yanxiang Cao Xuemei Wang Yaqiong Li Michel Gao Xiaoyang Feng Chuanliang Han |
| author_sort | Xixi Zhao |
| collection | DOAJ |
| description |
BackgroundCOVID-19 was first reported in 2019, and the Chinese government immediately carried out stringent and effective control measures in response to the epidemic.
ObjectiveNonpharmaceutical interventions (NPIs) may have impacted incidences of other infectious diseases as well. Potential explanations underlying this reduction, however, are not clear. Hence, in this study, we aim to study the influence of the COVID-19 prevention policies on other infectious diseases (mainly class B infectious diseases) in China.
MethodsTime series data sets between 2017 and 2021 for 23 notifiable infectious diseases were extracted from public data sets from the National Health Commission of the People’s Republic of China. Several indices (peak and trough amplitudes, infection selectivity, preferred time to outbreak, oscillatory strength) of each infectious disease were calculated before and after the COVID-19 outbreak.
ResultsWe found that the prevention and control policies for COVID-19 had a strong, significant reduction effect on outbreaks of other infectious diseases. A clear event-related trough (ERT) was observed after the outbreak of COVID-19 under the strict control policies, and its decreasing amplitude is related to the infection selectivity and preferred outbreak time of the disease before COVID-19. We also calculated the oscillatory strength before and after the COVID-19 outbreak and found that it was significantly stronger before the COVID-19 outbreak and does not correlate with the trough amplitude.
ConclusionsOur results directly demonstrate that prevention policies for COVID-19 have immediate additional benefits for controlling most class B infectious diseases, and several factors (infection selectivity, preferred outbreak time) may have contributed to the reduction in outbreaks. This study may guide the implementation of nonpharmaceutical interventions to control a wider range of infectious diseases. |
| first_indexed | 2024-03-12T12:51:57Z |
| format | Article |
| id | doaj.art-bef236fcabe847dead505c044333c865 |
| institution | Directory Open Access Journal |
| issn | 2369-2960 |
| language | English |
| last_indexed | 2024-03-12T12:51:57Z |
| publishDate | 2022-06-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Public Health and Surveillance |
| spelling | doaj.art-bef236fcabe847dead505c044333c8652023-08-28T22:21:50ZengJMIR PublicationsJMIR Public Health and Surveillance2369-29602022-06-0186e3534310.2196/35343Changes in Temporal Properties of Notifiable Infectious Disease Epidemics in China During the COVID-19 Pandemic: Population-Based Surveillance StudyXixi Zhaohttps://orcid.org/0000-0003-1745-8184Meijia Lihttps://orcid.org/0000-0001-8893-3697Naem Haihambohttps://orcid.org/0000-0002-1909-3919Jianhua Jinhttps://orcid.org/0000-0002-3009-8745Yimeng Zenghttps://orcid.org/0000-0003-4753-4328Jinyi Qiuhttps://orcid.org/0000-0001-8675-3158Mingrou Guohttps://orcid.org/0000-0002-3942-0286Yuyao Zhuhttps://orcid.org/0000-0002-4443-886XZhirui Lihttps://orcid.org/0000-0002-9001-9332Jiaxin Liuhttps://orcid.org/0000-0003-0652-9100Jiayi Tenghttps://orcid.org/0000-0002-1320-2846Sixiao Lihttps://orcid.org/0000-0001-8887-5028Ya-nan Zhaohttps://orcid.org/0000-0002-7513-0569Yanxiang Caohttps://orcid.org/0000-0002-2175-5846Xuemei Wanghttps://orcid.org/0000-0002-6842-9888Yaqiong Lihttps://orcid.org/0000-0002-1717-7625Michel Gaohttps://orcid.org/0000-0002-8647-7701Xiaoyang Fenghttps://orcid.org/0000-0003-1065-8597Chuanliang Hanhttps://orcid.org/0000-0002-5734-4790 BackgroundCOVID-19 was first reported in 2019, and the Chinese government immediately carried out stringent and effective control measures in response to the epidemic. ObjectiveNonpharmaceutical interventions (NPIs) may have impacted incidences of other infectious diseases as well. Potential explanations underlying this reduction, however, are not clear. Hence, in this study, we aim to study the influence of the COVID-19 prevention policies on other infectious diseases (mainly class B infectious diseases) in China. MethodsTime series data sets between 2017 and 2021 for 23 notifiable infectious diseases were extracted from public data sets from the National Health Commission of the People’s Republic of China. Several indices (peak and trough amplitudes, infection selectivity, preferred time to outbreak, oscillatory strength) of each infectious disease were calculated before and after the COVID-19 outbreak. ResultsWe found that the prevention and control policies for COVID-19 had a strong, significant reduction effect on outbreaks of other infectious diseases. A clear event-related trough (ERT) was observed after the outbreak of COVID-19 under the strict control policies, and its decreasing amplitude is related to the infection selectivity and preferred outbreak time of the disease before COVID-19. We also calculated the oscillatory strength before and after the COVID-19 outbreak and found that it was significantly stronger before the COVID-19 outbreak and does not correlate with the trough amplitude. ConclusionsOur results directly demonstrate that prevention policies for COVID-19 have immediate additional benefits for controlling most class B infectious diseases, and several factors (infection selectivity, preferred outbreak time) may have contributed to the reduction in outbreaks. This study may guide the implementation of nonpharmaceutical interventions to control a wider range of infectious diseases.https://publichealth.jmir.org/2022/6/e35343 |
| spellingShingle | Xixi Zhao Meijia Li Naem Haihambo Jianhua Jin Yimeng Zeng Jinyi Qiu Mingrou Guo Yuyao Zhu Zhirui Li Jiaxin Liu Jiayi Teng Sixiao Li Ya-nan Zhao Yanxiang Cao Xuemei Wang Yaqiong Li Michel Gao Xiaoyang Feng Chuanliang Han Changes in Temporal Properties of Notifiable Infectious Disease Epidemics in China During the COVID-19 Pandemic: Population-Based Surveillance Study JMIR Public Health and Surveillance |
| title | Changes in Temporal Properties of Notifiable Infectious Disease Epidemics in China During the COVID-19 Pandemic: Population-Based Surveillance Study |
| title_full | Changes in Temporal Properties of Notifiable Infectious Disease Epidemics in China During the COVID-19 Pandemic: Population-Based Surveillance Study |
| title_fullStr | Changes in Temporal Properties of Notifiable Infectious Disease Epidemics in China During the COVID-19 Pandemic: Population-Based Surveillance Study |
| title_full_unstemmed | Changes in Temporal Properties of Notifiable Infectious Disease Epidemics in China During the COVID-19 Pandemic: Population-Based Surveillance Study |
| title_short | Changes in Temporal Properties of Notifiable Infectious Disease Epidemics in China During the COVID-19 Pandemic: Population-Based Surveillance Study |
| title_sort | changes in temporal properties of notifiable infectious disease epidemics in china during the covid 19 pandemic population based surveillance study |
| url | https://publichealth.jmir.org/2022/6/e35343 |
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