The Effect of COVID-19 on Infectious Disease to Outpatient of Children: A Machine Learning Study
Dan Li1, Dan Xiang1, Shun-Xian Zhang2,3,4 and Jin-Xin Zheng2,3*
1 Department of NICU, the Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, 310003, People’s Republic of China.
2 School of Global Health, Chinese Centre for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People’s Republic of China.
3 National Institute of Parasitic Diseases at Chinese Centre for Disease Control and Prevention (Chinese Centre for Tropical Diseases Research), National Health Commission of the People’s Republic of China (NHC) Key Laboratory of Parasite and Vector Biology, World Health Organization (WHO) Collaborating Centre for Tropical Diseases, National Centre for International Research On Tropical Diseases of the Chinese Ministry of Science and Technology, Shanghai, 200025, People’s Republic of China.
4 Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, People’s Republic of China.
*Corresponding Author: Jin-Xin Zheng, National Institute of Parasitic Diseases at Chinese Centre for Disease Control and Prevention (Chinese Centre for Tropical Diseases Research), National Health Commission of the People’s Republic of China (NHC) Key Laboratory of Parasite and Vector Biology, World Health Organization (WHO) Collaborating Centre for Tropical Diseases, National Centre for International Research On Tropical Diseases of the Chinese Ministry of Science and Technology, Shanghai, 200025, People’s Republic of China.
DOI: https://doi.org/10.58624/SVOAPD.2023.02.042
Received: July 18, 2023 Published: August 07, 2023
Abstract
The outbreak of coronavirus disease 2019 (COVID-19) has had a significant impact worldwide. However, the effects of COVID-19 on human enteroviruses such as Herpangina and Hand, Foot, and Mouth Disease (HFMD) in children are still not fully understood. This study aimed to analyze the reported cases of Herpangina and HFMD among child outpatients in Hangzhou, China, from January 2018 to June 2021, before, during, and after the COVID-19 outbreak. Machine learning approaches were employed to analyze the time series data of Herpangina and HFMD from 2018 to 2019 and predict the trends and seasonal patterns from 2020 to 2021. The seasonal patterns at weekly and monthly levels were compared across the three stages of the COVID-19 outbreak. Prior to 2020, the reported incidence of Herpangina and HFMD exhibited a certain degree of seasonal periodicity. However, following the COVID-19 outbreak in 2020, there was a sharp decrease in the cases of Herpangina and HFMD, followed by a rebound in the first half of 2021. The observed cases reached their highest peak in July 2020, showing a decrease of 93.6% for Herpangina and 96.5% for HFMD compared to the predicted values. These findings indicate that the COVID-19 outbreak had a significant impact on the transmission of Herpangina and HFMD. Therefore, integrated strategies should be implemented to control and prevent the resurgence of Herpangina and HFMD, alongside the effective management of COVID-19.
Keywords: Herpangina; HFMD; Machine Learning; COVID-19
Citation: Li D, Xiang D, Zhang SX, Zheng JX. The Effect of COVID-19 on Infectious Disease to Outpatient of Children: A Machine Learning Study. SVOA Paediatrics 2023, 2:4, 102-112.