Predicting the Incident Cases of Emerging Infectious Disease Using a Bayesian Probability Model - China, February 2020.

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?: The exact number of incident cases of emerging infectious diseases on a daily basis is of great importance to the disease control and prevention, but it is not directly available from the current surveillance system in time. WHAT IS ADDED BY THIS REPORT?: In this study, a Bayesian statistical method was proposed to estimate the posterior parameters of the gamma probability distribution of the lag time between the onset date and the reporting time based on the surveillance data. And then the posterior parameters and corresponding cumulative gamma probability distribution were used to predict the actual number of new incident cases and the number of unreported cases per day. The proposed method was used for predicting COVID-19 incident cases from February 5 to February 26, 2020. The final results show that Bayesian probability model predictions based on data reported by February 28, 2020 are very close to those actually reported a month later. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?: This research provides a Bayesian statistical approach for early estimation of the actual number of cases of incidence based on surveillance data, which is of great value in the prevention and control practice of epidemics.

Bibliometric Analysis on Utilization of New Information Technology in the Prevention and Control of COVID-19 - China, 2020.

INTRODUCTION: New information technology (IT) has been applied to prevent and control coronavirus disease 2019 (COVID-19) in many regions of China since the outbreak of COVID-19. This study aims to illustrate the current status and key areas of the application of new IT in the prevention and control of COVID-19. METHODS: Literature related to the prevention and control of COVID-19 with new IT since 2020 was retrieved from China National Knowledge Internet and Wanfang Literature databases, the two most authoritative databases in China. CiteSpace 5.7.R2 was used to analyze the institutions, authors, and keywords of the articles. The application of new IT is determined by keywords and highly cited documents. RESULTS: A total of 1,711 articles were included, as the number of publications has been continually increasing over the investigation period. The six hot topics of new IT applied in COVID-19 were big data, artificial intelligence, Internet+, blockchain, Internet of Things, and 5G. The most productive institution is University of Chinese Academy of Sciences, and the most productive author in this field is Tao Pei, whose article, "Multi-level Spatial Distribution Estimation Model of the Inter-Regional Migrant Population Using Multi-Source Spatio-Temporal Big Data: A Case Study of Migrants from Wuhan During the Spread of COVID-19," was highly cited. DISCUSSION: This study could help medical professionals understand the application status and research trends of new IT in the prevention and control of COVID-19. This paper also helps researchers find potential co-operative institutions and partners.

Antibody seroprevalence in the epicenter Wuhan, Hubei, and six selected provinces after containment of the first epidemic wave of COVID-19 in China.

BACKGROUND: China implemented containment measures to stop SARS-CoV-2 transmission in response to the COVID-19 epidemic. After the first epidemic wave, we conducted population-based serological surveys to determine extent of infection, risk factors for infection, and neutralization antibody levels to assess the real infections in the random sampled population. METHODS: We used a multistage, stratified cluster random sampling strategy to conduct serological surveys in three areas - Wuhan, Hubei Province outside Wuhan, and six provinces selected on COVID-19 incidence and containment strategy. Participants were consenting individuals >1 year old who resided in the survey area >14 days during the epidemic. Provinces screened sera for SARS-CoV-2-specific IgM, IgG, and total antibody by two lateral flow immunoassays and one magnetic chemiluminescence enzyme immunoassay; positive samples were verified by micro-neutralization assay. FINDINGS: We enrolled 34,857 participants (overall response rate, 92%); 427 were positive by micro-neutralization assay. Wuhan had the highest weighted seroprevalence (4•43%, 95% confidence interval [95%CI]=3•48%-5•62%), followed by Hubei-ex-Wuhan (0•44%, 95%CI=0•26%-0•76%), and the other provinces (<0•1%). Living in Wuhan (adjusted odds ratio aOR=13•70, 95%CI= 7•91-23•75), contact with COVID-19 patients (aOR=7•35, 95%CI=5•05-10•69), and age over 40 (aOR=1•36, 95%CI=1•07-1•72) were significantly associated with SARS-CoV-2 infection. Among seropositives, 101 (24%) reported symptoms and had higher geometric mean neutralizing antibody titers than among the 326 (76%) without symptoms (30±2•4 vs 15±2•1, p<0•001). INTERPRETATION: The low overall extent of infection and steep gradient of seropositivity from Wuhan to the outer provinces provide evidence supporting the success of containment of the first wave of COVID-19 in China. SARS-CoV-2 infection was largely asymptomatic, emphasizing the importance of active case finding and physical distancing. Virtually the entire population of China remains susceptible to SARS-CoV-2; vaccination will be needed for long-term protection. FUNDING: This study was supported by the Ministry of Science and Technology (2020YFC0846900) and the National Natural Science Foundation of China (82041026, 82041027, 82041028, 82041029, 82041030, 82041032, 82041033).

One Hundred Days of Coronavirus Disease 2019 Prevention and Control in China.

The epidemic of novel coronavirus disease was first reported in China in late December 2019 and was brought under control after some 2 months in China. However, it has become a global pandemic, and the number of cases and deaths continues to increase outside of China. We describe the emergence of the pandemic, detail the first 100 days of China's response as a phase 1 containment strategy followed by phase 2 containment, and briefly highlight areas of focus for the future. Specific, simple, and pragmatic strategies used in China for risk assessment, prioritization, and deployment of resources are described. Details of implementation, at different risk levels, of the traditional public health interventions are shared. Involvement of society in mounting a whole country response and challenges experienced with logistics and supply chains are described. Finally, the methods China is employing to cautiously restart social life and economic activity are outlined.