相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。
Article
Multidisciplinary Sciences
Juliette Paireau et al.
Summary: Short-term forecasting of COVID-19 healthcare demand in France was evaluated using 12 individual models and 19 predictors. The inclusion of early predictors significantly improved the accuracy of 14-day forecasts. The ensemble model performed the best or second-best, depending on the evaluation metric, providing a benchmark for future improvements.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Mathematics, Interdisciplinary Applications
Serkan Balli
Summary: The Covid-19 pandemic is the most important health disaster the world has faced in the past eight months, predicting its trend has become a challenge. A study analyzed COVID-19 data and proposed a time series prediction model, estimating the global pandemic will peak at the end of January 2021 with approximately 80 million people cumulatively infected.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Multidisciplinary Sciences
Emrah Gecili et al.
Summary: Predicting the progression of the COVID-19 pandemic using statistical/time series models is crucial for public health planning and policy decision-making. ARIMA and cubic smoothing spline models showed better prediction performance for forecasting future cases, deaths, and recoveries, compared to other models, making them preferable for use in handling the pandemic.
Article
Public, Environmental & Occupational Health
Meng-Chun Chang et al.
Summary: The study analyzed changes in mobility patterns in Taiwan and identified high-risk areas of disease spread. It found that intracity travel reductions have a higher impact on outbreak risk than intercity travel reductions, but both can help narrow the scope of an outbreak and target resources effectively. Multiple factors such as timing, duration, and level of travel reduction together determine the impact on the number of infections.
Article
Infectious Diseases
Bernard Cazelles et al.
Summary: Recent literature strongly supports the hypothesis that restricting mobility and practicing social distancing are crucial in limiting the transmission of SARS-CoV2. The study found a high positive correlation between mobility trends and transmission of SARS-CoV-2, and increased mobility post-lockdown relaxation was significantly associated with increased transmission. Tracking changes in mobility when relaxing mitigation measures is important to anticipate future changes in SARS-CoV-2 spread.
INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES
(2021)
Article
Multidisciplinary Sciences
Steven Riley et al.
Summary: Monitoring the SARS-CoV-2 pandemic in England using a national representative surveillance program based on self-administered swab results from over 594,000 individuals tested between May and the beginning of September 2020 revealed a decline followed by a resurgence in cases, indicative of a second wave. The study suggests that representative community sampling can provide valuable insights for public health responses, especially during periods of low prevalence.
Article
Public, Environmental & Occupational Health
Alexis Zebrowski et al.
Summary: The study found that non-pharmaceutical public health interventions had a greater impact on reducing preventable deaths during the pandemic compared to hospital critical care surge response; tools have been developed to rapidly determine areas where pandemic demand overwhelms local medical capacity.
AMERICAN JOURNAL OF PUBLIC HEALTH
(2021)
Article
Infectious Diseases
Mircea T. Sofonea et al.
Summary: The study developed a parsimonious discrete-time model to analyze the spread of COVID-19 in France, estimating key epidemiological parameters and the impact of lockdown implementation delay. By incorporating memory effects into the model, the accuracy of fitting epidemiological data was greatly improved.
Article
Computer Science, Theory & Methods
Chao Fan et al.
Summary: This study examines the transmission risk of COVID-19 using Facebook data. The results indicate that the reduction in co-location has a delayed effect on the growth of confirmed cases, and significant segregation is found among different counties.
APPLIED NETWORK SCIENCE
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Christophorus Beneditto Aditya Satrio et al.
Summary: The global spread of COVID-19 has caused significant disruptions to daily life, prompting the use of machine learning models to forecast disease trends in Indonesia. Comparisons between the Prophet and ARIMA models showed that Prophet generally outperforms ARIMA, despite its forecasts further deviating from the actual data over time.
5TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND COMPUTATIONAL INTELLIGENCE 2020
(2021)
Article
Multidisciplinary Sciences
Serina Chang et al.
Summary: The study introduces a SEIR model that integrates fine-grained, dynamic mobility networks to simulate the spread of COVID-19 in the ten largest US metropolitan areas. By accurately fitting the real case trajectory, the model identifies the effectiveness of restricting maximum occupancy at locations for curbing infections and reveals the contributions of mobility-related mechanisms to higher infection rates among disadvantaged socioeconomic and racial groups.
Article
Infectious Diseases
Giulia Pullano et al.
Article
Multidisciplinary Sciences
Henrik Salje et al.
Article
Multidisciplinary Sciences
Moritz U. G. Kraemer et al.
Article
Infectious Diseases
Hamada S. Badr et al.
LANCET INFECTIOUS DISEASES
(2020)
Article
Mathematics, Interdisciplinary Applications
Kayode Ayinde et al.
CHAOS SOLITONS & FRACTALS
(2020)
Article
Multidisciplinary Sciences
Vadim A. Karatayev et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2020)
Article
Mathematics, Interdisciplinary Applications
Farah Shahid et al.
CHAOS SOLITONS & FRACTALS
(2020)
Article
Computer Science, Theory & Methods
Juergen Jost et al.
DISCRETE & COMPUTATIONAL GEOMETRY
(2014)
Article
Mathematics
Yann Ollivier
COMPTES RENDUS MATHEMATIQUE
(2007)
