The National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
JMIR Public Health Surveill. 2022 Jun 23;8(6):e35343. doi: 10.2196/35343.
COVID-19 was first reported in 2019, and the Chinese government immediately carried out stringent and effective control measures in response to the epidemic.
Nonpharmaceutical 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.
Time 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.
We 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.
Our 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.
2019 年首次报告了 COVID-19 疫情，中国政府立即针对疫情采取了严格有效的控制措施。
非药物干预（NPIs）也可能对其他传染病的发病率产生影响。然而，这种减少的潜在解释尚不清楚。因此，在本研究中，我们旨在研究 COVID-19 预防政策对中国其他传染病（主要为乙类传染病）的影响。
从国家卫生健康委员会的公共数据集提取了 2017 年至 2021 年 23 种法定传染病的时间序列数据集。计算了 COVID-19 爆发前后每种传染病的几个指标（峰值和波谷幅度、感染选择性、首选爆发时间、振荡强度）。
我们发现，COVID-19 的预防和控制政策对其他传染病的爆发具有很强的显著减少效果。在严格的控制政策下，COVID-19 爆发后观察到明显的事件相关波谷（ERT），其减少幅度与 COVID-19 之前疾病的感染选择性和首选爆发时间有关。我们还计算了 COVID-19 爆发前后的振荡强度，发现爆发前明显更强，与波谷幅度无关。
我们的结果直接表明，COVID-19 的预防政策对控制大多数乙类传染病具有即时的额外益处，几个因素（感染选择性、首选爆发时间）可能促成了疫情的减少。本研究可能为实施非药物干预措施以控制更广泛的传染病提供指导。
