Mathematics of Public Health最新文献

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Mathematics of the Pandemic 流行病的数学
Mathematics of Public Health Pub Date : 2021-09-07 DOI: 10.1007/978-3-030-85053-1_16
M. Murty, V. Murty
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引用次数: 0
A Logistic Growth Model with Logistically Varying Carrying Capacity for Covid-19 Deaths Using Data from Ontario, Canada 基于加拿大安大略省数据的Covid-19死亡物流承载能力变化的Logistic增长模型
Mathematics of Public Health Pub Date : 2021-09-07 DOI: 10.1007/978-3-030-85053-1_3
Georges Bucyibaruta, C. Dean, E. Renouf
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引用次数: 0
Learning COVID-19 Mitigation Strategies Using Reinforcement Learning 使用强化学习学习COVID-19缓解策略
Mathematics of Public Health Pub Date : 2021-09-07 DOI: 10.1007/978-3-030-85053-1_12
Nicholas Denis, Alexander El-Hajj, Blair Drummond, Yamina Abiza, Krishna Chaitanya Gopaluni
{"title":"Learning COVID-19 Mitigation Strategies Using Reinforcement Learning","authors":"Nicholas Denis, Alexander El-Hajj, Blair Drummond, Yamina Abiza, Krishna Chaitanya Gopaluni","doi":"10.1007/978-3-030-85053-1_12","DOIUrl":"https://doi.org/10.1007/978-3-030-85053-1_12","url":null,"abstract":"","PeriodicalId":389354,"journal":{"name":"Mathematics of Public Health","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114555214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Real-Time Prediction of the End of an Epidemic Wave: COVID-19 in China as a Case-Study 疫情结束的实时预测——以中国新冠肺炎疫情为例
Mathematics of Public Health Pub Date : 2021-09-07 DOI: 10.1007/978-3-030-85053-1_8
Q. Griette, Zhihua Liu, P. Magal, Robin N. Thompson
{"title":"Real-Time Prediction of the End of an Epidemic Wave: COVID-19 in China as a Case-Study","authors":"Q. Griette, Zhihua Liu, P. Magal, Robin N. Thompson","doi":"10.1007/978-3-030-85053-1_8","DOIUrl":"https://doi.org/10.1007/978-3-030-85053-1_8","url":null,"abstract":"","PeriodicalId":389354,"journal":{"name":"Mathematics of Public Health","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128667282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Describing, Modelling and Forecasting the Spatial and Temporal Spread of COVID-19: A Short Review 描述、建模和预测COVID-19时空传播:简要综述
Mathematics of Public Health Pub Date : 2021-02-04 DOI: 10.1007/978-3-030-85053-1_2
Julien Arino
{"title":"Describing, Modelling and Forecasting the Spatial and Temporal Spread of COVID-19: A Short Review","authors":"Julien Arino","doi":"10.1007/978-3-030-85053-1_2","DOIUrl":"https://doi.org/10.1007/978-3-030-85053-1_2","url":null,"abstract":"","PeriodicalId":389354,"journal":{"name":"Mathematics of Public Health","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126103534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 16
Don't wait, re-escalate: delayed action results in longer duration of COVID-19 restrictions 不要等待,重新升级:延迟行动将导致COVID-19限制的持续时间更长
Mathematics of Public Health Pub Date : 2020-11-06 DOI: 10.1101/2020.11.04.20226316
A. Hurford, James Watmough
{"title":"Don't wait, re-escalate: delayed action results in longer duration of COVID-19 restrictions","authors":"A. Hurford, James Watmough","doi":"10.1101/2020.11.04.20226316","DOIUrl":"https://doi.org/10.1101/2020.11.04.20226316","url":null,"abstract":"We use a simple linear SIR model with case importation to determine the relationship between the timing of restrictions, duration of measures necessary to return the incidence to a set point, and the final size of the outbreak. We conclude from our analysis that delaying re-escalation of restrictions leads to increased duration of control measures and larger outbreaks. Conversely, earlier re-escalation results in shorter disruptions, smaller outbreaks, and consequently, lower economic and social costs.","PeriodicalId":389354,"journal":{"name":"Mathematics of Public Health","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117004448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Generalized Additive Models to Capture the Death Rates in Canada COVID-19 捕获加拿大COVID-19死亡率的广义加性模型
Mathematics of Public Health Pub Date : 2020-07-05 DOI: 10.1007/978-3-030-85053-1_7
F. Izadi
{"title":"Generalized Additive Models to Capture the Death Rates in Canada COVID-19","authors":"F. Izadi","doi":"10.1007/978-3-030-85053-1_7","DOIUrl":"https://doi.org/10.1007/978-3-030-85053-1_7","url":null,"abstract":"","PeriodicalId":389354,"journal":{"name":"Mathematics of Public Health","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122832949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Diverse local epidemics reveal the distinct effects of population density, demographics, climate, depletion of susceptibles, and intervention in the first wave of COVID-19 in the United States 不同的地方流行病揭示了人口密度、人口结构、气候、易感人群的消耗和对美国第一波COVID-19的干预的不同影响
Mathematics of Public Health Pub Date : 2020-07-01 DOI: 10.1101/2020.06.30.20143636
N. Afshordi, Benjamin P. Holder, Mohammad Bahrami, Daniel Lichtblau
{"title":"Diverse local epidemics reveal the distinct effects of population density, demographics, climate, depletion of susceptibles, and intervention in the first wave of COVID-19 in the United States","authors":"N. Afshordi, Benjamin P. Holder, Mohammad Bahrami, Daniel Lichtblau","doi":"10.1101/2020.06.30.20143636","DOIUrl":"https://doi.org/10.1101/2020.06.30.20143636","url":null,"abstract":"The SARS-CoV-2 pandemic has caused significant mortality and morbidity worldwide, sparing almost no community. As the disease will likely remain a threat for years to come, an understanding of the precise influences of human demographics and settlement, as well as the dynamic factors of climate, susceptible depletion, and intervention, on the spread of localized epidemics will be vital for mounting an effective response. We consider the entire set of local epidemics in the United States; a broad selection of demographic, population density, and climate factors; and local mobility data, tracking social distancing interventions, to determine the key factors driving the spread and containment of the virus. Assuming first a linear model for the rate of exponential growth (or decay) in cases/mortality, we find that population-weighted density, humidity, and median age dominate the dynamics of growth and decline, once interventions are accounted for. A focus on distinct metropolitan areas suggests that some locales benefited from the timing of a nearly simultaneous nationwide shutdown, and/or the regional climate conditions in mid-March; while others suffered significant outbreaks prior to intervention. Using a first-principles model of the infection spread, we then develop predictions for the impact of the relaxation of social distancing and local climate conditions. A few regions, where a significant fraction of the population was infected, show evidence that the epidemic has partially resolved via depletion of the susceptible population (i.e., \"herd immunity\"), while most regions in the United States remain overwhelmingly susceptible. These results will be important for optimal management of intervention strategies, which can be facilitated using our online dashboard.","PeriodicalId":389354,"journal":{"name":"Mathematics of Public Health","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124919774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
Forecasting Demand for Personal Protective Equipment for Ontario Acute Care Hospitals During the First Wave of the COVID-19 Pandemic 预测安大略省急性护理医院在COVID-19大流行第一波期间对个人防护装备的需求
Mathematics of Public Health Pub Date : 1900-01-01 DOI: 10.1007/978-3-030-85053-1_10
K. Barrett, Y. Nakamachi, T. Ierasts, Y. Khan, S. Mac, D. Naimark, N. Stall, R. Ximenes, Andrew M. Morris, B. Sander
{"title":"Forecasting Demand for Personal Protective Equipment for Ontario Acute Care Hospitals During the First Wave of the COVID-19 Pandemic","authors":"K. Barrett, Y. Nakamachi, T. Ierasts, Y. Khan, S. Mac, D. Naimark, N. Stall, R. Ximenes, Andrew M. Morris, B. Sander","doi":"10.1007/978-3-030-85053-1_10","DOIUrl":"https://doi.org/10.1007/978-3-030-85053-1_10","url":null,"abstract":"","PeriodicalId":389354,"journal":{"name":"Mathematics of Public Health","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134535570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Sub-epidemic Model Forecasts During the First Wave of the COVID-19 Pandemic in the USA and European Hotspots 美国和欧洲热点地区第一波COVID-19大流行亚流行模型预测
Mathematics of Public Health Pub Date : 1900-01-01 DOI: 10.1007/978-3-030-85053-1_5
G. Chowell, R. Rothenberg, K. Roosa, A. Tariq, J. Hyman, R. Luo
{"title":"Sub-epidemic Model Forecasts During the First Wave of the COVID-19 Pandemic in the USA and European Hotspots","authors":"G. Chowell, R. Rothenberg, K. Roosa, A. Tariq, J. Hyman, R. Luo","doi":"10.1007/978-3-030-85053-1_5","DOIUrl":"https://doi.org/10.1007/978-3-030-85053-1_5","url":null,"abstract":"","PeriodicalId":389354,"journal":{"name":"Mathematics of Public Health","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127030002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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