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  1. Book ; Online: SenPei-CU/COVID-19

    Sen Pei

    COVID-19

    2020  

    Abstract: Code and data for paper Ruiyun Li, Sen Pei, Bin Chen, Yimeng Song, Tao Zhang, Wan Yang, and Jeffrey ... CoV2). (2020). Code is programmed by Sen Pei (contact: sp3449@cumc.columbia.edu). Data are provided ...

    Abstract Code and data for paper Ruiyun Li, Sen Pei, Bin Chen, Yimeng Song, Tao Zhang, Wan Yang, and Jeffrey Shaman. Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2). (2020). Code is programmed by Sen Pei (contact: sp3449@cumc.columbia.edu). Data are provided by Ruiyun Li, Bin Chen, Yimeng Song and Tao Zhang. Abstract Estimation of the prevalence and contagiousness of undocumented novel coronavirus (SARS-CoV2) infections is critical for understanding the overall prevalence and pandemic potential of this disease. Here we use observations of reported infection within China, in conjunction with mobility data, a networked dynamic metapopulation model and Bayesian inference, to infer critical epidemiological characteristics associated with SARS-CoV2, including the fraction of undocumented infections and their contagiousness. We estimate 86% of all infections were undocumented (95% CI: [82%-90%]) prior to January 23, 2020 travel restrictions. Per person, these undocumented infections were 55% as contagious as documented infections ([46%-62%]) and were the source of infection for two-thirds of documented cases. These findings explain the rapid geographic spread of SARS-CoV2 and indicate containment of this virus will be particularly challenging.
    Keywords covid19
    Publishing date 2020-03-06
    Publishing country eu
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Book ; Online: SenPei-CU/COVID-19_US_Projection V1.0

    Sen Pei

    2020  

    Abstract: No description provided. ...

    Abstract No description provided.
    Keywords covid19
    Publishing date 2020-03-21
    Publishing country eu
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Book ; Online: SenPei-CU/Hurricane-COVID

    Sen Pei

    2020  

    Abstract: Code and data for Pei S., Dahl K., Yamana T., Licker R., Shaman J. Compound risks of hurricane evacuation amid the COVID-19 pandemic in the United ... ...

    Abstract Code and data for Pei S., Dahl K., Yamana T., Licker R., Shaman J. Compound risks of hurricane evacuation amid the COVID-19 pandemic in the United States
    Keywords covid19
    Publishing date 2020-09-01
    Publishing country eu
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Aggregating forecasts of multiple respiratory pathogens supports more accurate forecasting of influenza-like illness.

    Sen Pei / Jeffrey Shaman

    PLoS Computational Biology, Vol 16, Iss 10, p e

    2020  Volume 1008301

    Abstract: Influenza-like illness (ILI) is a commonly measured syndromic signal representative of a range of acute respiratory infections. Reliable forecasts of ILI can support better preparation for patient surges in healthcare systems. Although ILI is an ... ...

    Abstract Influenza-like illness (ILI) is a commonly measured syndromic signal representative of a range of acute respiratory infections. Reliable forecasts of ILI can support better preparation for patient surges in healthcare systems. Although ILI is an amalgamation of multiple pathogens with variable seasonal phasing and attack rates, most existing process-based forecasting systems treat ILI as a single infectious agent. Here, using ILI records and virologic surveillance data, we show that ILI signal can be disaggregated into distinct viral components. We generate separate predictions for six contributing pathogens (influenza A/H1, A/H3, B, respiratory syncytial virus, and human parainfluenza virus types 1-2 and 3), and develop a method to forecast ILI by aggregating these predictions. The relative contribution of each pathogen to the total ILI signal is estimated using a Markov Chain Monte Carlo (MCMC) method upon forecast aggregation. We find highly variable overall contributions from influenza type A viruses across seasons, but relatively stable contributions for the other pathogens. Using historical data from 1997 to 2014 at US national and regional levels, the proposed forecasting system generates improved predictions of both seasonal and near-term targets relative to a baseline method that simulates ILI as a single pathogen. The hierarchical forecasting system can generate predictions for each viral component, as well as infer and predict their contributions to ILI, which may additionally help physicians determine the etiological causes of ILI in clinical settings.
    Keywords Biology (General) ; QH301-705.5
    Subject code 333
    Language English
    Publishing date 2020-10-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: SINS/BDS tightly coupled integrated navigation algorithm for hypersonic vehicle

    Kai Chen / Sen-sen Pei / Cheng-zhi Zeng / Gang Ding

    Scientific Reports, Vol 12, Iss 1, Pp 1-

    2022  Volume 15

    Abstract: Abstract A tightly coupled integrated navigation system (TCINS) for hypersonic vehicles is proposed when the satellite signals are disturbed. Firstly, the architecture of the integrated navigation system for the hypersonic vehicle is introduced. This ... ...

    Abstract Abstract A tightly coupled integrated navigation system (TCINS) for hypersonic vehicles is proposed when the satellite signals are disturbed. Firstly, the architecture of the integrated navigation system for the hypersonic vehicle is introduced. This system applies fiber SINS, BeiDou satellite receiver (BDS) and System On a Parogrammable Chip (SOPC) missile-born computer. Subsequently, the SINS mechanization for hypersonic vehicle is presented. The J2 model is employed for the normal gravity of the near space. An algorithm for updating the attitude, velocity and position is designed. State equations and measurement equations of SINS/BDS tightly coupled integrated navigation for hypersonic vehicle are given, and a scheme of validity for satellite data is designed. Finally, the SINS/BDS tightly coupled vehicle field tests and hardware-in-the-loop (HWIL) simulation tests are carried out. The vehicle field test and HWIL simulation results show that the heading angle error of tightly coupled integrated navigation is within 0.2°, the pitch and roll angle errors are within 0.05°, the maximum velocity error is 0.3 m/s, and the maximum position error is 10 m.
    Keywords Medicine ; R ; Science ; Q
    Subject code 629
    Language English
    Publishing date 2022-04-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Optimizing respiratory virus surveillance networks using uncertainty propagation

    Sen Pei / Xian Teng / Paul Lewis / Jeffrey Shaman

    Nature Communications, Vol 12, Iss 1, Pp 1-

    2021  Volume 10

    Abstract: Lack of a widespread surveillance network hampers accurate infectious disease forecasting. Here the authors provide a framework to optimize the selection of surveillance site locations and show that accurate forecasting of respiratory diseases for ... ...

    Abstract Lack of a widespread surveillance network hampers accurate infectious disease forecasting. Here the authors provide a framework to optimize the selection of surveillance site locations and show that accurate forecasting of respiratory diseases for locations without surveillance is feasible.
    Keywords Science ; Q
    Language English
    Publishing date 2021-01-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Association of public health and social measures on the hand-foot-mouth epidemic in South Korea

    Sukhyun Ryu / Changhee Han / Sheikh Taslim Ali / Chiara Achangwa / Bingyi Yang / Sen Pei

    Journal of Infection and Public Health, Vol 16, Iss 6, Pp 859-

    2023  Volume 864

    Abstract: Background: School based-measures such as school closure and school holidays have been considered a viable intervention during the hand-foot-mouth disease (HFMD) epidemic. The aim of this study was to explore the association of nationwide public health ... ...

    Abstract Background: School based-measures such as school closure and school holidays have been considered a viable intervention during the hand-foot-mouth disease (HFMD) epidemic. The aim of this study was to explore the association of nationwide public health and social measures (PHSMs) including planned school vacation on the transmissibility and attack rate of the HFMD epidemic in South Korea. Methods: In this study, we used Korean national surveillance data on HFMD from 2014 to 2019 to estimate the temporal changes in HFMD transmissibility (instantaneous reproductive number, Rt). Furthermore, to assess the changes in the HFMD attack rate, we used a stochastic transmission model to simulate the HFMD epidemic with no school vacation and nationwide PHSMs in 2015 South Korea. Results: We found that school vacations and 2015 PHSMs were associated with the reduced Rt by 2–7 % and 13 %, respectively. Model projections indicated school vacations and 2015 PHSMs were associated with reduced HFMD attack rate by an average of 1.10 % (range: 0.38–1.51 %). Conclusions: PHSMs likely have a larger association with reduced HFMD transmissibility than school-based measures alone (i.e. school vacations). Preventive measures targeting preschoolers could be considered as potential options for reducing the future burden of HFMD.
    Keywords Hand-foot-and-mouth disease ; School holidays ; Vacation ; Nonpharmaceutical measure ; Public health and social measures ; Transmissibility ; Infectious and parasitic diseases ; RC109-216 ; Public aspects of medicine ; RA1-1270
    Subject code 370
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Inference of transmission dynamics and retrospective forecast of invasive meningococcal disease.

    Jaime Cascante-Vega / Marta Galanti / Katharina Schley / Sen Pei / Jeffrey Shaman

    PLoS Computational Biology, Vol 19, Iss 10, p e

    2023  Volume 1011564

    Abstract: The pathogenic bacteria Neisseria meningitidis, which causes invasive meningococcal disease (IMD), predominantly colonizes humans asymptomatically; however, invasive disease occurs in a small proportion of the population. Here, we explore the seasonality ...

    Abstract The pathogenic bacteria Neisseria meningitidis, which causes invasive meningococcal disease (IMD), predominantly colonizes humans asymptomatically; however, invasive disease occurs in a small proportion of the population. Here, we explore the seasonality of IMD and develop and validate a suite of models for simulating and forecasting disease outcomes in the United States. We combine the models into multi-model ensembles (MME) based on the past performance of the individual models, as well as a naive equally weighted aggregation, and compare the retrospective forecast performance over a six-month forecast horizon. Deployment of the complete vaccination regimen, introduced in 2011, coincided with a change in the periodicity of IMD, suggesting altered transmission dynamics. We found that a model forced with the period obtained by local power wavelet decomposition best fit and forecast observations. In addition, the MME performed the best across the entire study period. Finally, our study included US-level data until 2022, allowing study of a possible IMD rebound after relaxation of non-pharmaceutical interventions imposed in response to the COVID-19 pandemic; however, no evidence of a rebound was found. Our findings demonstrate the ability of process-based models to retrospectively forecast IMD and provide a first analysis of the seasonality of IMD before and after the complete vaccination regimen.
    Keywords Biology (General) ; QH301-705.5
    Subject code 330
    Language English
    Publishing date 2023-10-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Forecasting influenza in Europe using a metapopulation model incorporating cross-border commuting and air travel.

    Sarah C Kramer / Sen Pei / Jeffrey Shaman

    PLoS Computational Biology, Vol 16, Iss 10, p e

    2020  Volume 1008233

    Abstract: Past work has shown that models incorporating human travel can improve the quality of influenza forecasts. Here, we develop and validate a metapopulation model of twelve European countries, in which international translocation of virus is driven by ... ...

    Abstract Past work has shown that models incorporating human travel can improve the quality of influenza forecasts. Here, we develop and validate a metapopulation model of twelve European countries, in which international translocation of virus is driven by observed commuting and air travel flows, and use this model to generate influenza forecasts in conjunction with incidence data from the World Health Organization. We find that, although the metapopulation model fits the data well, it offers no improvement over isolated models in forecast quality. We discuss several potential reasons for these results. In particular, we note the need for data that are more comparable from country to country, and offer suggestions as to how surveillance systems might be improved to achieve this goal.
    Keywords Biology (General) ; QH301-705.5
    Language English
    Publishing date 2020-10-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Role of meteorological factors in the transmission of SARS-CoV-2 in the United States

    Yiqun Ma / Sen Pei / Jeffrey Shaman / Robert Dubrow / Kai Chen

    Nature Communications, Vol 12, Iss 1, Pp 1-

    2021  Volume 9

    Abstract: The role of meteorological factors in SARS-COV-2 transmission is not well understood. Here, the authors use county-level data from the United States to the end of 2020 and find evidence of a moderate association between increased transmissibility and ... ...

    Abstract The role of meteorological factors in SARS-COV-2 transmission is not well understood. Here, the authors use county-level data from the United States to the end of 2020 and find evidence of a moderate association between increased transmissibility and cold, dry weather and low ultraviolet radiation.
    Keywords Science ; Q
    Language English
    Publishing date 2021-06-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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