Coronavirus disease 2019 epidemic prediction in Shanghai under the “dynamic zero-COVID policy” using time-dependent SEAIQR model

Ma, Yifei; Xu, Shujun; An, Q.; Mengxia, Qin; Li, Sitian; Kangkang, Lu; Li, Jiantao; Lijian, Lei; Li, He; Yu, Hongmei; Xie, Jun

doi:10.1016/j.jobb.2022.06.002

Cited by 22 publications

(19 citation statements)

References 36 publications

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“…First, our model was based on a series of parameter assumptions, assuming equal infection and recovery opportunities for each individual. Nevertheless, differences in factors such as age, gender, and immune status could have had an important impact on the risk and effectiveness of disease transmission in reality, which was also a major limitation of the SEIR model 9,13,16,41 . Second, the model only considered the number of infections, without taking into account the specific types of infections and the clinical burden associated with disease severity, hospitalization, or mortality rates.…”

Section: Discussionmentioning

confidence: 99%

“…Currently, there are various mathematical models available for infectious diseases. Among these models, the classic susceptible–exposed–infected–recovered (SEIR) model, based on epidemiological principles, has played a significant role in studying disease transmission and developing public health policies for infectious diseases, such as COVID‐19, monkeypox, hepatitis B, and influenza 8–17 . The SEIR model and its modifications can describe the dynamic spread of infectious diseases in a population, including changes in population size at different stages (incubation, infection, and recovery), as well as key information about the speed and duration of disease transmission.…”

Section: Introductionmentioning

confidence: 99%

“…Among these models, the classic susceptible-exposed-infected-recovered (SEIR) model, based on epidemiological principles, has played a significant role in studying disease transmission and developing public health policies for infectious diseases, such as COVID-19, monkeypox, hepatitis B, and influenza. [8][9][10][11][12][13][14][15][16][17] The SEIR model and its modifications can describe the dynamic spread of infectious diseases in a population, including changes in population size at different stages (incubation, infection, and recovery), as well as key information about the speed and duration of disease transmission. Moreover, by adjusting the parameters of the model (such as vaccination coverage rates and effective contact rates), it is possible to simulate the impact of different intervention measures on the speed and scope of disease transmission, which provides valuable insights for public health decisionmaking.…”

mentioning

confidence: 99%

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Simulating the impact of optimized prevention and control measures on the transmission of monkeypox in the United States: A model‐based study

Cao,

Fang,

Chen

et al. 2024

Journal of Medical Virology

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This study aimed to develop a modified susceptible‐exposed–infected–recovered (SEIR) model to evaluate monkeypox epidemics in the United States and explore more optimized prevention and control measures. To further assess the impact of public health measures on the transmission of monkeypox, different intervention scenarios were developed based on the classic SEIR model, considering reducing contact, enhancing vaccination, diagnosis delay, and environmental transmission risk, respectively. We evaluated the impact of different measures by simulating their spread in different scenarios. During the simulation period, 8709 people were infected with monkeypox. The simulation analysis showed that: (1) the most effective measures to control monkeypox transmission during the early stage of the epidemic were reducing contact and enhancing vaccination, with cumulative infections at 51.20% and 41.90% of baseline levels, respectively; (2) shortening diagnosis time would delay the peak time of the epidemic by 96 days; and (3) the risk of environmental transmission of monkeypox virus was relatively low. This study indirectly proved the effectiveness of the prevention and control measures, such as reducing contact, enhancing vaccination, shortening diagnosis time, and low risk of environmental transmission, which also provided an important reference and containment experience for nonepidemic countries.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Simulating the impact of optimized prevention and control measures on the transmission of monkeypox in the United States: A model‐based study

Cao,

Fang,

Chen

et al. 2024

Journal of Medical Virology

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“…Chinese government has implemented and optimized the "dynamic zero-COVID policy" for effective combating Omicron. 36,37…”

Section: Omicron Infection In Chinamentioning

confidence: 99%

“…To date, a variety of public health policies worldwide have been implemented for managing the COVID‐19 pandemic according to the national conditions of various countries. Chinese government has implemented and optimized the “dynamic zero‐COVID policy” for effective combating Omicron 36,37 …”

Section: Omicron Infection In Chinamentioning

confidence: 99%

Emergence of SARS‐CoV‐2 Omicron variant and strategies for tackling the infection

Long

Wang

et al. 2022

Immunity Inflam & Disease

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Introduction: Nowadays, emerging SARS-CoV-2 Omicron, the novel highly mutated VOC, has quickly spread as the dominant variant in over 190 countries worldwide through the first part of 2022, which is influencing the infectivity, transmissibility, pathogenicity, and severity of COVID-19 pandemic. Additionally, clinical cases and experimental studies have reported that Omicron variant likely leads to weakened immune protection elicited by infection, antibody therapies, and vaccines. The new wave, from late February, 2022, was escalated abruptly by higher levels of transmission of Omicron BA.2 sublineage in China.Methods and Results: Following a systematic database search, this review summarizes the salient features of Omicron sublineages, and their impact on transmissibility, disease severity as well as the efficacy of the available vaccines and treatment against the Omicron. Conclusion:We hope this study will provide a scientific reference for alleviating the burden of COVID-19.

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A vaccination-based COVID-19 model: Analysis and prediction using Hamiltonian Monte Carlo

Jdid,

Benbrahim,

Kabbaj

et al. 2024

Heliyon

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Coronavirus disease 2019 epidemic prediction in Shanghai under the “dynamic zero-COVID policy” using time-dependent SEAIQR model

Cited by 22 publications

References 36 publications

Simulating the impact of optimized prevention and control measures on the transmission of monkeypox in the United States: A model‐based study

Simulating the impact of optimized prevention and control measures on the transmission of monkeypox in the United States: A model‐based study

Emergence of SARS‐CoV‐2 Omicron variant and strategies for tackling the infection

A vaccination-based COVID-19 model: Analysis and prediction using Hamiltonian Monte Carlo

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