Assessing effects of reopening policies on COVID-19 pandemic in Texas with a data-driven transmission model

Yu, Decai; Zhu, Gen; Zhang, Chenguang; Soltanalizadeh, Babak; Wang, Xia; Tang, Sanyi; Wu, Hulin

doi:10.1016/j.idm.2021.02.001

Cited by 9 publications

(7 citation statements)

References 13 publications

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“…These compartmental structures reflect better the actual situation of intervention. For example, some studies have modeled intervention measures for patients with different infection status, which were common in reality: isolating asymptomatic infections at home, admitting symptomatic infections to hospital [ 40 ], and admitting severe patients to ICU for treatment [ 41 ], etc. The recovered individuals were also divided into different compartments according to whether they had been detected or not, symptomatic or asymptomatic [ 37 ].…”

Section: Resultsmentioning

confidence: 99%

Compartmental structures used in modeling COVID-19: a scoping review

et al. 2022

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Background The coronavirus disease 2019 (COVID-19) epidemic, considered as the worst global public health event in nearly a century, has severely affected more than 200 countries and regions around the world. To effectively prevent and control the epidemic, researchers have widely employed dynamic models to predict and simulate the epidemic’s development, understand the spread rule, evaluate the effects of intervention measures, inform vaccination strategies, and assist in the formulation of prevention and control measures. In this review, we aimed to sort out the compartmental structures used in COVID-19 dynamic models and provide reference for the dynamic modeling for COVID-19 and other infectious diseases in the future. Main text A scoping review on the compartmental structures used in modeling COVID-19 was conducted. In this scoping review, 241 research articles published before May 14, 2021 were analyzed to better understand the model types and compartmental structures used in modeling COVID-19. Three types of dynamics models were analyzed: compartment models expanded based on susceptible-exposed-infected-recovered (SEIR) model, meta-population models, and agent-based models. The expanded compartments based on SEIR model are mainly according to the COVID-19 transmission characteristics, public health interventions, and age structure. The meta-population models and the agent-based models, as a trade-off for more complex model structures, basic susceptible-exposed-infected-recovered or simply expanded compartmental structures were generally adopted. Conclusion There has been a great deal of models to understand the spread of COVID-19, and to help prevention and control strategies. Researchers build compartments according to actual situation, research objectives and complexity of models used. As the COVID-19 epidemic remains uncertain and poses a major challenge to humans, researchers still need dynamic models as the main tool to predict dynamics, evaluate intervention effects, and provide scientific evidence for the development of prevention and control strategies. The compartmental structures reviewed in this study provide guidance for future modeling for COVID-19, and also offer recommendations for the dynamic modeling of other infectious diseases. Graphical Abstract "Image missing"

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Section: Resultsmentioning

confidence: 99%

Compartmental structures used in modeling COVID-19: a scoping review

et al. 2022

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“…If not feasible due to public health system constraints, tracing and isolation of only household contacts is also found to significantly reduce the doubling time of the epidemic. A US-based modelling study [ 62 ] finds that increasing the capacity for detection, contact tracing and quarantine by at-least two folds would control the cases from rising during medium risk reopening (effective contact rate increased by three–five folds was considered as medium risk opening in the study).…”

Section: Resultsmentioning

confidence: 99%

Exit strategies from lockdowns due to COVID-19: a scoping review

Misra¹,

Joshi²,

Sarwal

et al. 2022

BMC Public Health

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Introduction In response to the ongoing COVID-19 pandemic, countries have adopted various degrees of restrictive measures on people to reduce COVID-19 transmission. These measures have had significant social and economic costs. In the absence of therapeutics, and low vaccination coverage, strategies for a safe exit plan from a lockdown are required to mitigate the transmission and simultaneously re-open societies. Most countries have outlined or have implemented lockdown exit plans. The objective of this scoping review is to (a) identify and map the different strategies for exit from lockdowns, (b) document the effects of these exit strategies, and (c) discuss features of successful exit strategies based on the evidence. Methods A five-step approach was used in this scoping review: (a) identifying the research question and inclusion/exclusion criteria; (b) searching the literature using keywords within PubMed and WHO databases; (c) study selection; (d) data extraction; (e) collating results and qualitative synthesis of findings. Results Of the 406 unique studies found, 107 were kept for full-text review. Studies suggest the post-peak period as optimal timing for an exit, supplemented by other triggers such as sufficient health system capacity, and increased testing rate. A controlled and step-wise exit plan which is flexible and guided by information from surveillance systems is optimal. Studies recommend continued use of non-pharmaceutical interventions such as physical distancing, use of facemasks, and hygiene measures, in different combinations when exiting from a lockdown, even after optimal vaccination coverage has been attained. Conclusion Reviewed studies have suggested adopting a multi-pronged strategy consisting of different approaches depending on the context. Among the different exit strategies reviewed (phase-wise exit, hard exit, and constant cyclic patterns of lockdown), phase-wise exit appears to be the optimal exit strategy.

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“…Some attempts to elucidate the effects of different levels of economic activity on the spread of coronavirus in the context of exit strategies relied more commonly on applying different specifications of the susceptible/exposed/infective/recovered (SEIR) model. Using the SEIR model as their methodological anchor, authors estimated the COVID-19 epidemic parameters based on the data of reported infected cases and deaths in different parts of the world to predict the future epidemics of COVID-19 under different reopening policies (Chang et al 2020 ; Liu et al 2020 ; Yu et al 2021 ). This section takes an alternative route to assess the COVID-19 exit strategy designed to gradually lift interventions introduced to control the outbreak in the State of São Paulo.…”

Section: Economic Activity and The Spread Of Covid-19mentioning

confidence: 99%