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We retrospectively analyzed spatial factors for coronavirus disease 2019 (COVID-19)-associated community deaths i.e., brought-in-dead (BID) in Lusaka, Zambia, between March and July 2020. A total of 127 cases of BID with geocoordinate data of their houses were identified during the study period. Median interquartile range (IQR) of the age of these cases was 49 (34-70) years old, and 47 cases (37.0%) were elderly individuals over 60 years old. Seventy-five cases (75%) of BID were identified in July 2020, when the total number of cases and deaths was largest in Zambia. Among those whose information regarding their underlying medical condition was available, hypertension was most common (22.9%, 8/35). Among Lusaka's 94 townships, the numbers (median, IQR) of cases were significantly larger in those characterized as unplanned residential areas compared to planned areas (1.0, 0.0-4.0 vs 0.0, 0.0-1.0;p=0.030). The proportion of individuals who require more than 30 minutes to obtain water was correlated with a larger number of BID cases per 105 population in each township (rho=0.28, p=0.006). The number of BID cases was larger in unplanned residential areas, which highlighted the importance of targeted public health interventions specifically to those areas to reduce the total number of COVID-19 associated community deaths in Lusaka. Brought-in-dead surveillance might be beneficial in monitoring epidemic conditions of COVID-19 in such high-risk areas. Furthermore, inadequate access to water, sanitation, and hygiene (WASH) might be associated with such distinct geographical distributions of COVID-19 associated community deaths in Lusaka, Zambia.Copyright © Amos Hamukale et al.
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One Health is an upgrade and optimization of health concepts, which recognizes the integrated health of the human-animal-environment. It emphasizes the use of interdisciplinary collaboration, multi-sectoral coordination, and multi-organizational One Health approaches to solve scientific questions. The surveillance and early warning system is the basis of public health emergency prevention and control. The COVID-19 pandemic and the emerging infectious disease (EID) have put great challenges on the existing surveillance and early warning systems worldwide. Guided by the concept of One Health, we attempt to build a new pattern of integrated surveillance and early warning system for EID. We will detail the system including the One Health-based organizational structure, zoonotic and environmental science surveillance network, EID reporting process, and support and guarantee from education and policy. The integrated surveillance and early warning system for EID constructed here has practical and application prospects, and will provide guidance for the prevention and control of COVID-19 and the possible EID in the future.Copyright © 2022, National Institute of Parasitic Diseases. All rights reserved.
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This article investigates the determinants of Bitcoin returns. The authors consider a comprehensive set of information variables under five categories: macroeconomics, blockchain technology, other assets, stress level, and investor sentiment. Their approach toward this large dataset is built upon dimension-reduction models such as Backward Elimination, least absolute shrinkage and selection operator (LASSO), principal component regression (PCR), and three-pass regression filter (3PRF). The empirical results show that blockchain technology, stress level, and investor sentiment have positive, negative, and positive predicting power on Bitcoin returns, respectively. Macroeconomic variables exhibit insignificant impacts on Bitcoin returns. Other asset variables show little predicting power until 2019, but some become a significant predictor during the COVID-19 pandemic. Overall, the authors caution against using Bitcoin as a risk-hedging device in financial portfolios. They also find that, consistent with other financial assets such as equities, Bitcoin shows increased predictability with a longer return horizon. Due to their empirical results, they also advocate the use of 3PRF;relative to other dimension-reduction methods under consideration, they observe superior performance of 3PRF in predicting both the level and the direction of future Bitcoin returns across all return horizons.
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Most COVID-19 studies commonly report figures of the overall infection at a state- or county-level. This aggregation tends to miss out on fine details of virus propagation. In this paper, we analyze a high-resolution COVID-19 dataset in Cali, Colombia, that records the precise time and location of every confirmed case. We develop a non-stationary spatio-temporal point process equipped with a neural network-based kernel to capture the heterogeneous correlations among COVID-19 cases. The kernel is carefully crafted to enhance expressiveness while maintaining model interpretability. We also incorporate some exogenous influences imposed by city landmarks. Our approach outperforms the state-of-the-art in forecasting new COVID-19 cases with the capability to offer vital insights into the spatio-temporal interaction between individuals concerning the disease spread in a metropolis.
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We examined changes in personal life insurance purchase decisions after a public health event by incorporating perceived health risk and regret into the expected utility function. The model predicts that the epidemic will create incremental insurance demand. Based on the 2003 severe acute respiratory syndrome outbreak in China, we used a panel dataset of 30 provinces from 2000 to 2007 and applied the difference-in-differences method to confirm the prediction empirically. The results showed that the epidemic did not significantly impact the demand for life insurance in the short term but played a role in the long term. People increased their health-care expenditure and premiums for new policies after the severe acute respiratory syndrome event, suggesting that the epidemic changed people's perceived risk and triggered anticipated regret, which increased life insurance demand. Some robustness checks also supported our findings. © 2023 Institute of World Economics and Politics, Chinese Academy of Social Sciences.
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In 2020, a new coronavirus swept the world, and the advent of this disease has a huge impact on our social and economic development. Due to the limited medical resources and regional differences, this model of virtual medicine becomes more valuable. In this paper, we create a virtual medical space based on a metaverse in order to investigate whether the medical model can be freely transformed between virtual and reality. In this process, I first describe different scenarios of virtual medical care in mixed reality, and then we use one of them as an example to develop a medical device. Then we designed the software and hardware of the product and performed the user experience, it includes the interaction and usage scenarios that affect the user. Finally, this medical device will be demonstrated by user experience and feedback. © 2023 The authors and IOS Press.
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Introduction: The Covid-19 pandemic transformed the landscape of the healthcare system. However, how the pandemic may have altered healthcare routines and if these shifts were transient is unclear. We examined the effects of Covid pandemic on dermatology healthcare routines using the electronic health record (EHR) system. Method(s): This retrospective study compared the patterns of actions in University of Rochester Dermatology using the EHR audit trail for 29,862 clinical visits from January 2020-June 2020 and January 2021-March 2021. We used R-coded software, ThreadNet, to characterize clinic visit routines as a network of actions. We examined changes in visit numbers, unique roles (i.e., staff), handoffs (i.e., changes from one role to another role), touchpoints (i.e., block of actions by one role, at one workstation, during one visit) during various phases of the pandemic. Statistical analyses were performed at 0.05 significance level using R. Result(s): Although differences were observed in visit numbers across our pandemic timeframe, these differences were not significant. Reductions in handoffs, touchpoints, and unique staff are observed in March-April 2020 compared to January-February 2020 (p<0.001). Compared to 2021 visits, reductions in unique staff were observed for March-June 2020 (p<0.04). Interestingly, handoffs and touchpoints only showed reductions for March-May 2020 (p<0.001). Conclusion(s): The EHR audit trail enables disruptions healthcare routines visible and measurable. Healthcare routines became simpler during the pandemic and gradually more complex in 2021. Some patterns of actions, such as handoffs and touchpoints, are more affected than others. Further exploration is necessary to fully understand the resiliency of healthcare routines from external disruptions. This research was supported by NSF (HNDS-2120530) and University of Rochester CTSA (UL1 TR002001).Copyright © 2023
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Objective To assess the quality of nucleic acid testing in 43 Novel Coronavirus laboratories of disease control institutions in Qinghai Province that have passed the acceptance inspection, so as to ensure the accuracy and reliability of nucleic acid testing results. Methods Five samples for quality control assessment were distributed to each testing institution. The quality of nucleic acid testing was carried out following the requirements of the testing technical guidelines in the Novel Coronavirus Pneumonia Prevention and Control Program (Seventh Edition) issued by the Chinese Center for Disease Control and Prevention. Each detection reagentwas prepared by the member units participating in the assessment. The nucleic acid detection ability of each institution was evaluated by comparing the testing results with the expected results of the assessment samples. Results Fortythree disease control institutions participated in the assessment, all the testing results were collected within the specified time. The overall compliance rate of this assessment was 100. 00%. A total of 10 manufacturers' nucleic acid extraction kits and 9 manufacturers' nucleic acid amplification kits were involved. One hundred percent of the kits detected the ORF1ab gene and N gene of the Novel Coronavirus. Conclusion The nucleic acid detection capacity of the disease control institutions in Qinghai has been further improved by making this Novel Coronavirus quality control assessment. The assessment createsa solid foundation for the prevention and control of the Novel Coronavirus epidemic in Qinghai. © 2023, Editorial Department of Medical Pest Control. All rights reserved.
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Objective To assess the quality of nucleic acid testing in 43 Novel Coronavirus laboratories of disease control institutions in Qinghai Province that have passed the acceptance inspection, so as to ensure the accuracy and reliability of nucleic acid testing results. Methods Five samples for quality control assessment were distributed to each testing institution. The quality of nucleic acid testing was carried out following the requirements of the testing technical guidelines in the Novel Coronavirus Pneumonia Prevention and Control Program (Seventh Edition) issued by the Chinese Center for Disease Control and Prevention. Each detection reagentwas prepared by the member units participating in the assessment. The nucleic acid detection ability of each institution was evaluated by comparing the testing results with the expected results of the assessment samples. Results Fortythree disease control institutions participated in the assessment, all the testing results were collected within the specified time. The overall compliance rate of this assessment was 100. 00%. A total of 10 manufacturers' nucleic acid extraction kits and 9 manufacturers' nucleic acid amplification kits were involved. One hundred percent of the kits detected the ORF1ab gene and N gene of the Novel Coronavirus. Conclusion The nucleic acid detection capacity of the disease control institutions in Qinghai has been further improved by making this Novel Coronavirus quality control assessment. The assessment createsa solid foundation for the prevention and control of the Novel Coronavirus epidemic in Qinghai. © 2023, Editorial Department of Medical Pest Control. All rights reserved.
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Human mobility estimation is crucial during the COVID-19 pandemic due to its significant guidance for policymakers to make non-pharmaceutical interventions. While deep learning approaches outperform conventional estimation techniques on tasks with abundant training data, the continuously evolving pandemic poses a significant challenge to solving this problem due to data non-stationarity, limited observations, and complex social contexts. Prior works on mobility estimation either focus on a single city or lack the ability to model the spatio-temporal dependencies across cities and time periods. To address these issues, we make the first attempt to tackle the cross-city human mobility estimation problem through a deep meta-generative framework. We propose a Spatio-Temporal Meta-Generative Adversarial Network (STORM-GAN) model that estimates dynamic human mobility responses under a set of social and policy conditions related to COVID-19. Facilitated by a novel spatio-temporal task-based graph (STTG) embedding, STORM-GAN is capable of learning shared knowledge from a spatio-temporal distribution of estimation tasks and quickly adapting to new cities and time periods with limited training samples. The STTG embedding component is designed to capture the similarities among cities to mitigate cross-task heterogeneity. Experimental results on real-world data show that the proposed approach can greatly improve estimation performance and outperform baselines. © 2022 IEEE.
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In the context of COVID-19 pandemic, schools from China and even in the world have carried out online teaching. Currently, online teaching has turned"future”into"reality” and created phenomenon of"taking home as school”. The existing geographical literature has paid little attention to the practices of home schooling and construction of learning space at home in the special context of the pandemic. Borrowing the concept of alternative education space from geography of education, and employing questionnaire survey and semi-structured depth interview as research methods, this paper aims to examine college students' practices and processes of place-making of home schooling during the pandemic. The tension and strategies of spatial negotiation during home schooling are unfolded. Furthermore, this paper explores students' perception of home and school after experiencing home schooling. The findings include: (1) Home schooling during the pandemic is a complex process of integration between educational space and home space, which produces rich social implication that enriches the spatial meaning of educating and learning at home. (2) Construction of space of home schooling involves reconciliation between study and livelihood-making, as well as study and ordinary family activities. Among them the area and quality of learning space are closely related to economic and social conditions of family and community. Once learning practice is embedded in family daily life and space, the boundary between learning space and family space becomes blurred, which brings disturbance to home learning. (3) Students have the initiative and autonomy to construct learning space at home, and flexibly use space, time and identity strategies to interpret the spatio-temporal relationship between home space and learning space and to coordinate the identity expression of "family” and "student”. Through learning practices, home space is endowed with new educational meanings. The findings of this study enrich the current research on home space in the context of COVID-19 pandemic, echo geographers' raising concern on the construction of multiple educational space, and has great significance for understanding the relationship between education, learning practice and everyday space, as well as reflecting and supporting the needs of home schooling of different groups. © 2022, Science Press. All rights reserved.
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With the frequent occurrence of COVID-19 virus, online learning is currently the response of most educational institutions. However, in online learning, teachers do not have enough grasp of students' learning status, so how to assess student concentration in online learning is of great significance. In order to reduce the interference of classroom teaching, this paper adopt a non-contact observation method to analyze and evaluate the students' facial features. Considering that student concentration is a fuzzy variable, a reasonable weight of each factor is constructed in combination with the analytic hierarchy method, and a framework for identifying the concentration of online learning that integrates multi-source data is proposed. Finally, the effect of concentration assessment was verified by experiments. © 2022 IEEE.
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To combat the spread of the COVID-19 virus, countries enforced quarantines, physical and social restrictions on people. These restrictions left many feeling isolated and lonely due to prolonged quarantines and lockdowns. This raises questions about using robots as social support to alleviate these symptoms, while still complying with restrictions and regulations. Since acceptance of social robots as companions has traditionally been low, an event like COVID-19 could change acceptance of robots as social companions as loneliness can influence the likelihood of anthropomorphizing nonhuman agents. Here, we aimed to see if loneliness, due to COVID-19 restrictions, influence the Uncanny Valley pattern that prior work has shown. As such, participants saw robot images that varied in physical human-likeness and were asked to evaluate them regarding trustworthiness, mind perception and likability. The measurements were obtained once before COVID-19 (in 2016) and once at the peak of the pandemic in September 2020. Results show that ratings of mind perception and likability were significantly impacted by the pandemic, with less pronounced UV patterns for those who experienced the COVID-19 pandemic. However, no differences in the UV pattern was observed on trust. Post-hoc analyses also illustrated that people were more likely to judge machinelike robots negatively, which could be due to increased loneliness/anxiety. These data suggest that loneliness attenuates UV patterns that are observed in "Uncanny” robots and that people have more favorable attitudes towards humanlike robots when feeling lonely, which provides important considerations for the use of humanlike robots as social companions. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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As a common antioxidant and antimicrobial agent in plants, luteolin has a variety of pharmacological activities and biological effects, the ability to specifically bind proteins and thus inhibit novel coronaviruses and treat asthma. Here, Co doped nitrogen-containing carbon frameworks/MoS2−MWCNTs (Co@NCF/MoS2−MWCNTs) nanocomposites have been synthesized and successfully applied to electrochemical sensors. X-ray photoelectron spectroscopy, scanning electron microscopy and X-ray diffraction were used to examine the morphology and structure of the samples. Meanwhile, the electrochemical behavior of Co@NCF/MoS2−MWCNTs was investigated. Due to its excellent electrical conductivity, electrocatalytic activity and adsorption, it is used for the detection of luteolin. The Co@NCF/MoS2−MWCNTs/GCE sensor can detect luteolin in a linear range from 0.1 nM to 1.3 μM with a limit of detection of 0.071 nM. Satisfactory results were obtained for the detection of luteolin in natural samples. In addition, the redox mechanism and electrochemical reaction sites of luteolin were investigated by the scan rate of CV curves and density functional theory. This work demonstrates for the first time the combination of ZIF-67-derived Co@NCF and MoS2−MWCNTs as electrochemical sensors for the detection of luteolin, which opens a new window for the sensitive detection of luteolin. © 2022 Elsevier Ltd
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This study collected epidemic data of COVID-19 in Zhengzhou from January 1 to January 20 in 2022. The epidemiological characteristics of the local epidemic in Zhengzhou High-tech Zone caused by the SARS-CoV-2 Delta variant were analyzed through epidemiological survey and big data analysis, which could provide a scientific basis for the prevention and control of the Delta variant. In detail, a total of 276 close contacts and 599 secondary close contacts were found in this study. The attack rate of close contacts and secondary close contacts was 5.43% (15/276) and 0.17% (1/599), respectively. There were 10 confirmed cases associated with the chain of transmission. Among them, the attack rates in close contacts of the first, second, third, fourth and fifth generation cases were 20.00% (5/25), 17.86% (5/28), 0.72% (1/139) and 14.81% (4/27), 0 (0/57), respectively. The attack rates in close contacts after sharing rooms/beds, having meals, having neighbor contacts, sharing vehicles with the patients, having same space contacts, and having work contacts were 26.67%, 9.10%, 8.33%, 4.55%, 1.43%, and 0 respectively. Collectively, the local epidemic situation in Zhengzhou High-tech Zone has an obvious family cluster. Prevention and control work should focus on decreasing family clusters of cases and community transmission.
Subject(s)
COVID-19 , Epidemics , Humans , SARS-CoV-2 , IncidenceABSTRACT
Plasmonic metasurface biosensing has shown great potential in label-free detection of bio-nanoparticles with various sizes, such as cancer antigens, exosomes and SARS-CoV-2 virus. It typically relies on the immunoassay, but current studies usually neglect the perfect size matching between each target bio-nanoparticle and the surface near-field domain, which should be very critical for the enhancement of detection performance. In order to maximize the immunodetection capability for each bio-nanoparticle, we propose a plasmonic meta-biosensor based on the field-customized mechanism. Our design overcomes the serious interference of biofunctionalization and accomplishes a sensitivity of 27 times higher than the conventional nanoplasmonic counterpart. Our method also builds the important basis of single bio-nanoparticle immunodetection by a plasmonic metasurface. The customized plasmonic metasensing study implies a promising way towards ultra-low concentration biosensing or even single bio-nanoparticle detection for high-performance point-of-care-testing in the near future. © 1995-2012 IEEE.
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Objective To explore the potential regulatory mechanism of Xuebijing injection in the treatment of COVID-19 by using network pharmacology and molecular docking methods. Methods Corresponding target genes of all the active ingredients of Xuebijing injection were obtained by using the pharmacological database and analysis platform of TCM System (TCMSP). And intersections with the COVID-19 gene-related targets in GeneCards database, OMIM database, PharmGkb database, TTD database and DrugBank database using the R programming language. Thus, the core target of Xubijing injection in COVID-19 treatment was obtained;Cytoscape 3.7.2 software was used to construct TCM - compound - target network;PPI network of intersection target was obtained by STRING;Utilized data packets to perform gene ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to predict the mechanism of overlapping targets. Finally, molecular docking technology was implemented to dock key active ingredients with PPI core protein. Results GO functional enrichment analysis included 1 818 biological processes (BP), 20 cellular components (CC) and 89 molecular functions (MF). The first 30 KEGG related pathways involved inflammation and immune response, such as rheumatoid arthritis signaling pathway, IL-17 signaling pathway, Th17 cell differentiation pathway, hypoxia-inducible factor (HIF-1) signaling pathway, JAK-Stat signaling pathway, inflammatory bowel disease signaling pathway, NF-κB signaling pathway, etc. Quercetin, cryptotanshinone, luteolin, β -carotene can affect IL1B, STAT3, AKT1, VEGFA and other overlapping targets. Meanwhile, quercetin may exert anti-inflammatory, antiviral and immune responses through IL1B binding to treat COVID-19. Conclusion This study reveals that chemical components in Xuebijing injection are involved in multiple biological processes and pathways in COVID-19 treatment through binding to key target proteins. © 2022. China Tropical Medicine. All rights reserved.
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Since the outbreak of the coronavirus disease 2019 (COVID-19), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been found in wastewater frequently worldwide. Based on the wastewater-based epidemiology (WBE), wastewater surveillance of SARS-CoV-2 can complement population surveillance for COVID-19. Quantification of viral load and genome sequencing of SARS-CoV-2 can help early warning of COVID-19 outbreaks, early identification of asymptomatic cases, assessment of infection scale, prediction of pandemic trend status, and identification of virus sources to provide scientific basis for polices for the prevention and control. Accordingly, here, the sources of SARS-CoV-2 in wastewater at home and abroad and the major factors affecting the survival of virus were reviewed. Common methods to concentrate, detect and quantify SARS-CoV-2 were reviewed, with an overview of global surveillance projects, progresses, and remaining scientific issues. Some shortcomings of the current procedures, including the lack of sufficient information on distribution characteristics and infectivity of SARS-CoV-2 in wastewater and limited development and application of prediction models were also discussed. WBE can provide insight into the scientific prevention and control of COVID-19 in the face of current or future pandemics in China, and enhance China′s ability to deal with the surveillance and early warning, epidemic scale assessment, and accurate policy-making for the infectious and non-infectious diseases. © 2022 Editorial Board, Research of Environmental Sciences. All rights reserved.
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A clinical trial is a key step in the process of pharmaceutical research and development (R & D). It is a key indicator of the innovative potential of the pharmaceutical industry. ClinicalTrials.gov shows that the average annual growth rate of the total number of clinical trials globally in the past decade (2012-2021) was 20.7%, mainly distributed in Europe and the United States, and the total number of clinical trials registered in China accounted for 6% of the world. According to the statistics of IQVIA Institute for Human Data Science, the global proportion of early-stage R & D pipelines from China-headquartered companies increased from 1% in 2005 to 12% in 2020, which was still far behind that of European and American companies. Among 871 new active substances approved for marketing globally in the past two decades, 522 were for marketing in China, with the high number driven by regulatory acceleration mechanisms from National Medical Products Administration, such as breakthrough and orphan designations and priority reviews. Considering the gap in clinical research strength between China and developed countries such as Europe and the United States, the clinical trial research capacity and level should be improved to assist China in the R & D of innovative drugs. According to the Registration and Information Disclosure Platform for Drug Clinical Studies and the clinical trial institution filing management information platform in China, in the last five years (2017-2021), the average annual growth rates of the total number of new drug clinical trial registration and clinical trial units in China reached 26.9% and 12.6%, respectively. However, clinical trial resources are mainly concentrated in major institutions, municipalities, or provincial capital cities in the eastern and central regions of China, with distributions becoming increasingly polarised. Under the background of China's new medical reforms, the strategic direction of national political support is to motivate equitable access to high-quality clinical trial resources and cross-regional collaborative development of medical institutions by means of medical unions, national clinical medical research centres, Chinese national major projects for new drug innovation and so on. In the context of this background, clinical trial research unions (CTRUs) have been built in China. A CTRU is defined as a consortium formed by medical institutions, sponsors and third-party service institutions of various levels and functions, led by a national clinical medical research centre or clinical trial medical institutions undertaking major national science and technology projects or supporting projects of national key R & D plans, radiating and driving the improvement of clinical trial research capacity in multiple regions. CTRUs develop a multi-level clinical research centre system and collaborative network by vertically and horizontally combining multi-level medical institutions, sponsors and third-party service institutions. All participants of CTRUs are crucial. The leading clinical trial research medical institution, as the core, is responsible for establishing institutional system standards in CTRUs, designing and leading high-quality multi-centre clinical trials, central ethics and personality training. The major clinical trial research medical institutions are responsible for implementing high-quality, multi-centre, complex and high-risk clinical trials. The other member institutions are responsible for implementing basic clinical trials. The sponsors, contract research organizations (CROs), site management organizations (SMOs) and other enterprises are responsible for funding, supporting and promoting the construction of a clinical trial centre system and collaborative network. The specific construction contents of CTRUs include building a clinical trial research resource sharing platform, homogenising clinical trial quality management, constructing a rapid clinical trial process platform, diversified multi-level and multi-form talent training, information intercon ection, deepening strategic cooperation and designing and leading high-level trials. CTRUs have established the selection criteria and assessment exit mechanism and conducted work performance assessments from the dimensions of organisation and implementation, division of labour and cooperation, the connection of clinical trial resources from top to bottom, efficiency and benefit and sustainable development to ensure their good and sustainable development. Through CTRUs, we can achieve high-quality clinical trial resource sharing, improve the clinical trial research capability of member institutions, cultivate high-level skills, such as principal investigators (PIs), sub-investigators, institutional managers and clinical research coordinators (CRCs), and promote the development of clinical trials, economically and with high-quality. Through the trial operation with one member of CTRUs, it was found that the key points should be strengthened in deepening resource sharing, implementing central ethics review, interconnecting information platforms and leading high-quality clinical trials. The construction of CTRUs is an effective means for China's clinical trial research to solve the current problems and change from a `follow-on pattern' to leading high-level and high-quality international multi-centre trials. However, the construction of CTRUs is a complex systematic project. In addition to performing an excellent job in the top-level design and overall planning, CTRUs' specific implementation process and measures need to be continuously explored in the practice process.
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Coronavirus disease 2019 (COVID-19) is an emerging infectious disease, and it is important to detect early and monitor the disease trend for policymakers to make informed decisions. We explored the predictive utility of Baidu Search Index and Baidu Information Index for early warning of COVID-19 and identified search keywords for further monitoring of epidemic trends in Guangxi. A time-series analysis and Spearman correlation between the daily number of cases and both the Baidu Search Index and Baidu Information Index were performed for seven keywords related to COVID-19 from January 8 to March 9, 2020. The time series showed that the temporal distributions of the search terms "coronavirus," "pneumonia" and "mask" in the Baidu Search Index were consistent and had 2 to 3 days' lead time to the reported cases;the correlation coefficients were higher than 0.81. The Baidu Search Index volume in 14 prefectures of Guangxi was closely related with the number of reported cases;it was not associated with the local GDP. The Baidu Information Index search terms "coronavirus" and "pneumonia" were used as frequently as 192,405.0 and 110,488.6 per million population, respectively, and they were also significantly associated with the number of reported cases (r(s) > 0.6), but they fluctuated more than for the Baidu Search Index and had 0 to 14 days' lag time to the reported cases. The Baidu Search Index with search terms "coronavirus," "pneumonia" and "mask" can be used for early warning and monitoring of the epidemic trend of COVID-19 in Guangxi, with 2 to 3 days' lead time.