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      The impact of anti‐COVID‐19 nonpharmaceutical interventions on hand, foot, and mouth disease—A spatiotemporal perspective in Xi'an, northwestern China

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          Abstract

          Growing evidence has shown that anti‐COVID‐19 nonpharmaceutical interventions (NPIs) can support prevention and control of various infectious diseases, including intestinal diseases. However, most studies focused on the short‐term mitigating impact and neglected the dynamic impact over time. This study is aimed to investigate the dynamic impact of anti‐COVID‐19 NPIs on hand, foot, and mouth disease (HFMD) over time in Xi'an City, northwestern China. Based on the surveillance data of HFMD, meteorological and web search data, Bayesian Structural Time Series model and interrupted time series analysis were performed to quantitatively measure the impact of NPIs in sequent phases with different intensities and to predict the counterfactual number of HFMD cases. From 2013 to 2021, a total number of 172,898 HFMD cases were reported in Xi'an. In 2020, there appeared a significant decrease in HFMD incidence (−94.52%, 95% CI: −97.54% to −81.95%) in the first half of the year and the peak period shifted from June to October by a small margin of 6.74% compared to the previous years of 2013 to 2019. In 2021, the seasonality of HFMD incidence gradually returned to the bimodal temporal variation pattern with a significant average decline of 61.09%. In particular, the impact of NPIs on HFMD was more evident among young children (0–3 years), and the HFMD incidence reported in industrial areas had an unexpected increase of 51.71% in 2020 autumn and winter. Results suggested that both direct and indirect NPIs should be implemented as effective public health measures to reduce infectious disease and improve surveillance strategies, and HFMD incidence in Xi'an experienced a significant rebound to the previous seasonality after a prominent decline influenced by the anti‐COVID‐19 NPIs.

          Highlights

          • HFMD transmission changed during the COVID‐19 pandemic; The impact of anti‐COVID‐19 NPIs on HFMD varied between different populations; The responsive NPIs indeed affected the HFMD incidence at different stages with potential long‐term impact.

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          Most cited references33

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          Interrupted time series regression for the evaluation of public health interventions: a tutorial

          Abstract Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at a clearly defined point in time. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical therapy to national public health legislation. Whereas the design shares many properties of regression-based approaches in other epidemiological studies, there are a range of unique features of time series data that require additional methodological considerations. In this tutorial we use a worked example to demonstrate a robust approach to ITS analysis using segmented regression. We begin by describing the design and considering when ITS is an appropriate design choice. We then discuss the essential, yet often omitted, step of proposing the impact model a priori. Subsequently, we demonstrate the approach to statistical analysis including the main segmented regression model. Finally we describe the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders, and we also outline some of the more complex design adaptations that can be used to strengthen the basic ITS design.
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            Effect of non-pharmaceutical interventions to contain COVID-19 in China

            Summary On March 11, 2020, the World Health Organization declared COVID-19 a pandemic 1 . The outbreak containment strategies in China based on non-pharmaceutical interventions (NPIs) appear to be effective 2 , but quantitative research is still needed to assess the efficacy of NPIs and their timings 3 . Using epidemiological and anonymised human movement data 4,5 , here we develop a modelling framework that uses daily travel networks to simulate different outbreak and intervention scenarios across China. We estimated that there were a total of 114,325 COVID-19 cases (interquartile range 76,776 -164,576) in mainland China as of February 29, 2020. Without NPIs, the COVID-19 cases would likely have shown a 67-fold increase (interquartile range 44 - 94) by February 29, 2020, with the effectiveness of different interventions varying. The early detection and isolation of cases was estimated to have prevented more infections than travel restrictions and contact reductions, but combined NPIs achieved the strongest and most rapid effect. The lifting of travel restrictions since February 17, 2020 does not appear to lead to an increase in cases across China if the social distancing interventions can be maintained, even at a limited level of 25% reduction on average through late April. Our findings contribute to an improved understanding of NPIs on COVID-19 and to inform response efforts across the World.
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              Hand, foot and mouth disease: current knowledge on clinical manifestations, epidemiology, aetiology and prevention

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                Author and article information

                Contributors
                13759981783@163.com
                baiyaocdc@163.com
                liukun5959@qq.com
                Journal
                J Med Virol
                J Med Virol
                10.1002/(ISSN)1096-9071
                JMV
                Journal of Medical Virology
                John Wiley and Sons Inc. (Hoboken )
                0146-6615
                1096-9071
                22 March 2022
                22 March 2022
                : 10.1002/jmv.27715
                Affiliations
                [ 1 ] School of Remote Sensing and Information Engineering Wuhan University Wuhan China
                [ 2 ] Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health Air Force Medical University Xi'an China
                [ 3 ] School of Resource and Environmental Science Wuhan University Wuhan China
                [ 4 ] Department of Infectious Disease Control and Prevention Xi'an Center for Disease Prevention and Control Xi'an China
                Author notes
                [*] [* ] Correspondence Zhongjun Shao, Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, 710032 Shaanxi, China.

                Email: 13759981783@ 123456163.com

                Kun Liu, Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, 710032 Shaanxi, China.

                Email: liukun5959@ 123456qq.com

                Yao Bai, Department of Infectious Disease Control and Prevention, Xi'an Center for Disease Prevention and Control, Xi'an, China.

                Email: baiyaocdc@ 123456163.com

                Author information
                http://orcid.org/0000-0003-1847-8208
                Article
                JMV27715
                10.1002/jmv.27715
                9088661
                35277880
                af52314d-a498-484d-a585-42c9a2174af4
                © 2022 Wiley Periodicals LLC

                This article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.

                History
                : 19 February 2022
                : 21 January 2022
                : 01 March 2022
                Page count
                Figures: 6, Tables: 2, Pages: 12, Words: 7392
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 81803289
                Award ID: 42071368
                Funded by: Natural Science Foundation of Shaanxi Province , doi 10.13039/501100007128;
                Award ID: 2020JM‐329
                Funded by: 2022 National Innovation Training Program for college students at Wuhan University
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                corrected-proof
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.5 mode:remove_FC converted:10.05.2022

                Microbiology & Virology
                covid‐19,hand, foot, and mouth disease,nonpharmaceutical interventions,time‐series analysis

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