2021-11-03

School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China.; Mathematical Institute, Leiden University, Leiden, The Netherlands.; School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China.; School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China.

Infectious diseases attack humans from time to time and threaten the lives and survival of people all around the world. An important strategy to prevent the spatial spread of infectious diseases is to restrict population travel. With the reduction of the epidemic situation, when and where travel restrictions can be lifted, and how to organize orderly movement patterns become critical and fall within the scope of this study. We define a novel diffusion distance derived from the estimated mobility network, based on which we provide a general model to describe the spatiotemporal spread of infectious diseases with a random diffusion process and a deterministic drift process of the population. We consequently develop a multi-source data fusion method to determine the population flow in epidemic areas. In this method, we first select available subregions in epidemic areas, and then provide solutions to initiate new travel flux among these subregions. To verify our model and method, we

2020-10-12

School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, China.; School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, China. Electronic address: yxiao@mail.xjtu.edu.cn.; Baidu Inc., Beijing 100094, China.

After diagnosed in Wuhan, COVID-19 spread quickly in mainland China. Though the epidemic in regions outside Hubei in mainland China has maintained a degree of control, evaluating the effectiveness and timeliness of intervention strategies, and predicting the transmission risk of work resumption as well as lifting the lockdown in Hubei province remain urgent. A patch model reflecting the mobility of population between Hubei and regions outside Hubei is formulated, and parameterized based on multiple source data for Hubei and regions outside Hubei. The effective reproduction numbers for Hubei and regions outside Hubei are estimated as 3.59 and 3.26 before Jan 23rd, 2020, but decrease quickly since then and drop below 1 after Jan 31st and Jan 28th, 2020. It is predicted that the new infections in Hubei province will decrease to very low level in mid-March, and the final size is estimated to be about 68,500 cases. The simulations reveal that contact rate after work resumption or lifting

2021-10-18

Prevention Insights, Department of Applied Health Science, School of Public Health Bloomington, Indiana University Bloomington, Bloomington, IN, United States.; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States.; Indiana University Media School, Indiana University Bloomington, Bloomington, IN, United States.; Biostatistics Consulting Center, School of Public Health Bloomington, Indiana University Bloomington, Bloomington, IN, United States.; Biostatistics Consulting Center, School of Public Health Bloomington, Indiana University Bloomington, Bloomington, IN, United States.

BACKGROUND: Trust in science meaningfully contributes to our understanding of people's belief in misinformation and their intentions to take actions to prevent COVID-19. However, no experimental research has sought to intervene on this variable to develop a scalable response to the COVID-19 infodemic. OBJECTIVE: Our study examined whether brief exposure to an infographic about the scientific process might increase trust in science and thereby affect belief in misinformation and intention to take preventive actions for COVID-19. METHODS: This two-arm, parallel-group, randomized controlled trial aimed to recruit a US representative sample of 1000 adults by age, race/ethnicity, and gender using the Prolific platform. Participants were randomly assigned to view either an intervention infographic about the scientific process or a control infographic. The intervention infographic was designed through a separate pilot study. Primary outcomes were trust in science, COVID-19 narrative belief

2021-07-28

Wuhan Britain-China School, No.10 Gutian Rd., Qiaokou District, Wuhan 430022, China.; Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China.; Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China.; Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China.; Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China.

Coronavirus 2019 (COVID-19) is causing a severe pandemic that has resulted in millions of confirmed cases and deaths around the world. In the absence of effective drugs for treatment, non-pharmaceutical interventions are the most effective approaches to control the disease. Although some countries have the pandemic under control, all countries around the world, including the United States (US), are still in the process of controlling COVID-19, which calls for an effective epidemic model to describe the transmission dynamics of COVID-19. Meeting this need, we have extensively investigated the transmission dynamics of COVID-19 from 22 January 2020 to 14 February 2021 for the 50 states of the United States, which revealed the general principles underlying the spread of the virus in terms of intervention measures and demographic properties. We further proposed a time-dependent epidemic model, named T-SIR, to model the long-term transmission dynamics of COVID-19 in the US. It was shown in

2021-06-03

Department of Molecular Biology, Shanghai Centre for Clinical Laboratory, Shanghai, China.; Department of Molecular Biology, Shanghai Centre for Clinical Laboratory, Shanghai, China.; Department of Molecular Biology, Shanghai Centre for Clinical Laboratory, Shanghai, China.; Department of Molecular Biology, Shanghai Centre for Clinical Laboratory, Shanghai, China.; Department of Molecular Biology, Shanghai Centre for Clinical Laboratory, Shanghai, China. Electronic address: xlwang12@126.com.

Recent reports have compared the analytical sensitivities of some SARS-CoV-2 RT-PCR assays, but differences in the viral materials used for these evaluations made comprehensive conclusions difficult. We carried out a direct comparison of the analytical sensitivities of 14 conventional and three rapid RT-PCR assays for the detection of SARS-CoV-2. The comparison was performed utilizing a certified reference material for SARS-CoV-2 RNA that was serially two-fold diluted in RNA storage solution. Our results show that the analytical sensitivities of the 17 assays varied within an 8-fold range (100-800 copies/mL). Moreover, a trend with some rapid assays yielding slightly higher analytical sensitivities (2- to 4-fold) compared with conventional assays was observed. We conclude that most of the RT-PCR assays can be used for routine COVID-19 diagnosis, but some assays with the poorest analytical sensitivities may lead to false-negative results when used to identify asymptomatic individuals

2021-02-09

Department of Hearing and Speech Rehabilitation, Binzhou Medical University, Yantai 264003, China.; Department of Hearing and Speech Rehabilitation, Binzhou Medical University, Yantai 264003, China.; Department of Hearing and Speech Rehabilitation, Binzhou Medical University, Yantai 264003, China.; Department of Hearing and Speech Rehabilitation, Binzhou Medical University, Yantai 264003, China.; Department of Hearing and Speech Rehabilitation, Binzhou Medical University, Yantai 264003, China.; Department of Hearing and Speech Rehabilitation, Binzhou Medical University, Yantai 264003, China.; Department of Hearing and Speech Rehabilitation, Binzhou Medical University, Yantai 264003, China.; Division of Biological Sciences and Interdisciplinary Neuroscience Program, University of Missouri-Columbia, Missouri, MO 65211, USA.

BACKGROUND: This study compares the mental health and psychological response of students with or without hearing loss during the recurrence of the COVID-19 pandemic in Beijing, the capital of China. It explores the relevant factors affecting mental health and provides evidence-driven strategies to reduce adverse psychological impacts during the COVID-19 pandemic. METHODS: We used the Chinese version of depression, anxiety, and stress scale 21 (DASS-21) to assess the mental health and the impact of events scale-revised (IES-R) to assess the COVID-19 psychological impact. RESULTS: The students with hearing loss are frustrated with their disability and particularly vulnerable to stress symptoms, but they are highly endurable in mitigating this negative impact on coping with their well-being and responsibilities. They are also more resilient psychologically but less resistant mentally to the pandemic impacts than the students with normal hearing. Their mental and psychological response to

2020-02-10

The Interdisplinary Research Center for Mathematics and Life Sciences, Xi’an; Jiaotong University, Xi’an, 710049, People’s Republic of China Laboratory for Industrial and Applied Mathematics, Department of Mathematics and ; Statistics, York University, Toronto, Ontario, M3J 1P3, Canada Laboratory for Industrial and Applied Mathematics, Department of Mathematics and ; Statistics, York University, Toronto, Ontario, M3J 1P3, Canada School of Mathematics and Information Science, Shaanxi Normal University, Xi’an, ; 710119, People’s Republic of China The Interdisplinary Research Center for Mathematics and Life Sciences, Xi’an; Jiaotong University, Xi’an, 710049, People’s Republic of China The Interdisplinary Research Center for Mathematics and Life Sciences, Xi’an; Jiaotong University, Xi’an, 710049, People’s Republic of China

The basic reproduction number of an infectious agent is the average number of infections one case can generate over the course of the infectious period, in a naïve, uninfected population. It is well-known that the estimation of this number may vary due to several methodological issues, including different assumptions and choice of parameters, utilized models, used datasets and estimation period. With the spreading of the novel coronavirus (2019-nCoV) infection, the reproduction number has been found to vary, reflecting the dynamics of transmission of the coronavirus outbreak as well as the case reporting rate. Due to significant variations in the control strategies, which have been changing over time, and thanks to the introduction of detection technologies that have been rapidly improved, enabling to shorten the time from infection/symptoms onset to diagnosis, leading to faster confirmation of the new coronavirus cases, our

2020-02-10

The Interdisplinary Research Center for Mathematics and Life Sciences, Xi’an; Jiaotong University, Xi’an, 710049, People’s Republic of China Laboratory for Industrial and Applied Mathematics, Department of Mathematics and ; Statistics, York University, Toronto, Ontario, M3J 1P3, Canada Laboratory for Industrial and Applied Mathematics, Department of Mathematics and ; Statistics, York University, Toronto, Ontario, M3J 1P3, Canada School of Mathematics and Information Science, Shaanxi Normal University, Xi’an, ; 710119, People’s Republic of China The Interdisplinary Research Center for Mathematics and Life Sciences, Xi’an; Jiaotong University, Xi’an, 710049, People’s Republic of China The Interdisplinary Research Center for Mathematics and Life Sciences, Xi’an; Jiaotong University, Xi’an, 710049, People’s Republic of China

The basic reproduction number of an infectious agent is the average number of infections one case can generate over the course of the infectious period, in a naïve, uninfected population. It is well-known that the estimation of this number may vary due to several methodological issues, including different assumptions and choice of parameters, utilized models, used datasets and estimation period. With the spreading of the novel coronavirus (2019-nCoV) infection, the reproduction number has been found to vary, reflecting the dynamics of transmission of the coronavirus outbreak as well as the case reporting rate. Due to significant variations in the control strategies, which have been changing over time, and thanks to the introduction of detection technologies that have been rapidly improved, enabling to shorten the time from infection/symptoms onset to diagnosis, leading to faster confirmation of the new coronavirus cases, our

2020-02-06

The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi’an; Jiaotong University, Xi’an 710049, China; btang66@yorku.ca (B.T.); yxiao@mail.xjtu.edu.cn (Y.X.) School of Mathematics and Information Science, Shaanxi Normal University, Xi’an; 710119, China; xiawang@snnu.edu.cn (X.W.); sanyitang219@hotmail.com (S.T.) Laboratory for Industrial and Applied Mathematics, Department of Mathematics and ; Statistics, York University, Toronto, ON M3J 1P3, Canada; crystallee@stu.xjtu.edu.cn (Q.L.); robertobragazzi@gmail.com (N.L.B.) Laboratory for Industrial and Applied Mathematics, Department of Mathematics and ; Statistics, York University, Toronto, ON M3J 1P3, Canada; crystallee@stu.xjtu.edu.cn (Q.L.); robertobragazzi@gmail.com (N.L.B.) School of Mathematics and Information Science, Shaanxi Normal University, Xi’an; 710119, China; xiawang@snnu.edu.cn (X.W.); sanyitang219@hotmail.com (S.T.) The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi’an; Jiaotong University, Xi’an 710049, China; btang66@yorku.ca (B.T.); yxiao@mail.xjtu.edu.cn (Y.X.) The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi’an; Jiaotong University, Xi’an 710049, China; btang66@yorku.ca (B.T.); yxiao@mail.xjtu.edu.cn (Y.X.)

Since the emergence of the first cases in Wuhan, China, the novel coronavirus (2019-nCoV) infection has been quickly spreading out to other provinces and neighboring countries. Estimation of the basic reproduction number by means of mathematical modeling can be helpful for determining the potential and severity of an outbreak and providing critical information for identifying the type of disease interventions and intensity. A deterministic compartmental model was devised based on the clinical progression of the disease, epidemiological status of the individuals, and intervention measures. The estimations based on likelihood and model analysis show that the control reproduction number may be as high as 6.47 (95% CI 5.71–7.23). Sensitivity analyses show that interventions, such as intensive contact tracing followed by quarantine and isolation, can effectively reduce the control reproduction number and transmission risk, with

2020-02-06

The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi’an; Jiaotong University, Xi’an 710049, China; btang66@yorku.ca (B.T.); yxiao@mail.xjtu.edu.cn (Y.X.) School of Mathematics and Information Science, Shaanxi Normal University, Xi’an; 710119, China; xiawang@snnu.edu.cn (X.W.); sanyitang219@hotmail.com (S.T.) Laboratory for Industrial and Applied Mathematics, Department of Mathematics and ; Statistics, York University, Toronto, ON M3J 1P3, Canada; crystallee@stu.xjtu.edu.cn (Q.L.); robertobragazzi@gmail.com (N.L.B.) Laboratory for Industrial and Applied Mathematics, Department of Mathematics and ; Statistics, York University, Toronto, ON M3J 1P3, Canada; crystallee@stu.xjtu.edu.cn (Q.L.); robertobragazzi@gmail.com (N.L.B.) School of Mathematics and Information Science, Shaanxi Normal University, Xi’an; 710119, China; xiawang@snnu.edu.cn (X.W.); sanyitang219@hotmail.com (S.T.) The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi’an; Jiaotong University, Xi’an 710049, China; btang66@yorku.ca (B.T.); yxiao@mail.xjtu.edu.cn (Y.X.) The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi’an; Jiaotong University, Xi’an 710049, China; btang66@yorku.ca (B.T.); yxiao@mail.xjtu.edu.cn (Y.X.)

Since the emergence of the first cases in Wuhan, China, the novel coronavirus (2019-nCoV) infection has been quickly spreading out to other provinces and neighboring countries. Estimation of the basic reproduction number by means of mathematical modeling can be helpful for determining the potential and severity of an outbreak and providing critical information for identifying the type of disease interventions and intensity. A deterministic compartmental model was devised based on the clinical progression of the disease, epidemiological status of the individuals, and intervention measures. The estimations based on likelihood and model analysis show that the control reproduction number may be as high as 6.47 (95% CI 5.71–7.23). Sensitivity analyses show that interventions, such as intensive contact tracing followed by quarantine and isolation, can effectively reduce the control reproduction number and transmission risk, with