Epidemic modeling for the resurgence of COVID-19 in Chinese local communities
Ontology highlight
ABSTRACT:
SUBMITTER: Peng M
PROVIDER: S-EPMC9085441 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The Coronavirus Disease 2019 (COVID-19) surges worldwide. However, massive imported patients especially into Heilongjiang Province in China recently have been an alert for local COVID-19 outbreak. We collected data from January 23 to March 25 from Heilongjiang province and trained an ordinary differential equation model to fit the epidemic data. We extended the simulation using this trained model to characterize the effect of an imported 'escaper'. We showed that an imported 'escaper' was responsible for the newly confirmed COVID-19 infections from Apr 9 to Apr 19 in Heilongjiang province. Stochastic simulations further showed that significantly increased local contacts among imported 'escaper', its epidemiologically associated cases and susceptible populations greatly contributed to the local outbreak of COVID-19. Meanwhile, we further found that the reported number of asymptomatic patients was markedly lower than model predictions implying a large asymptomatic pool which was not identified. We further forecasted the effect of implementing strong interventions immediately to impede COVID-19 outbreak for Heilongjiang province. Implementation of stronger interventions to lower mutual contacts could accelerate the complete recovery from coronavirus infections in Heilongjiang province. Collectively, our model has characterized the epidemic of COVID-19 in Heilongjiang province and implied that strongly controlled measured should be taken for infected and asymptomatic patients to minimize total infections.
| S-EPMC7256610 | biostudies-literature
Project description:The COVID-19 pandemic has precipitated a global crisis, with more than 1,430,000 confirmed cases and more than 85,000 confirmed deaths globally as of 9 April 20201-4. Mitigation and suppression of new infections have emerged as the two predominant public health control strategies5. Both strategies focus on reducing new infections by limiting human-to-human interactions, which could be both socially and economically unsustainable in the long term. We have developed and analyzed an epidemiological intervention model that leverages serological tests6,7 to identify and deploy recovered individuals8 as focal points for sustaining safer interactions via interaction substitution, developing what we term 'shield immunity' at the population scale. The objective of a shield immunity strategy is to help to sustain the interactions necessary for the functioning of essential goods and services9 while reducing the probability of transmission. Our shield immunity approach could substantively reduce the length and reduce the overall burden of the current outbreak, and can work synergistically with social distancing. The present model highlights the value of serological testing as part of intervention strategies, in addition to its well-recognized roles in estimating prevalence10,11 and in the potential development of plasma-based therapies12-15.
| S-EPMC8272982 | biostudies-literature
Project description:The introduction of COVID-19 vaccination passes (VPs) by many countries coincided with the Delta variant fast becoming dominant across Europe. A thorough assessment of their impact on epidemic dynamics is still lacking. Here, we propose the VAP-SIRS model that considers possibly lower restrictions for the VP holders than for the rest of the population, imperfect vaccination effectiveness against infection, rates of (re-)vaccination and waning immunity, fraction of never-vaccinated, and the increased transmissibility of the Delta variant. Some predicted epidemic scenarios for realistic parameter values yield new COVID-19 infection waves within two years, and high daily case numbers in the endemic state, even without introducing VPs and granting more freedom to their holders. Still, suitable adaptive policies can avoid unfavorable outcomes. While VP holders could initially be allowed more freedom, the lack of full vaccine effectiveness and increased transmissibility will require accelerated (re-)vaccination, wide-spread immunity surveillance, and/or minimal long-term common restrictions.
| S-EPMC9053266 | biostudies-literature
Project description:COVID-19 epidemic doubling time by Chinese province was increasing from January 20 through February 9, 2020. The harmonic mean of the arithmetic mean doubling time estimates ranged from 1.4 (Hunan, 95% CI, 1.2-2.0) to 3.1 (Xinjiang, 95% CI, 2.1-4.8), with an estimate of 2.5 days (95% CI, 2.4-2.6) for Hubei.
| S-EPMC7216847 | biostudies-literature
Project description:While China experienced a peak and decline in coronavirus disease 2019 (COVID-19) cases at the start of 2020, regional outbreaks continuously emerged in subsequent months. Resurgences of COVID-19 have also been observed in many other countries. In Guangzhou, China, a small outbreak, involving less than 100 residents, emerged in March and April 2020, and comprehensive and near-real-time genomic surveillance of SARS-CoV-2 was conducted. When the numbers of confirmed cases among overseas travelers increased, public health measures were enhanced by shifting from self-quarantine to central quarantine and SARS-CoV-2 testing for all overseas travelers. In an analysis of 109 imported cases, we found diverse viral variants distributed in the global viral phylogeny, which were frequently shared within households but not among passengers on the same flight. In contrast to the viral diversity of imported cases, local transmission was predominately attributed to two specific variants imported from Africa, including local cases that reported no direct or indirect contact with imported cases. The introduction events of the virus were identified or deduced before the enhanced measures were taken. These results show the interventions were effective in containing the spread of SARS-CoV-2, and they rule out the possibility of cryptic transmission of viral variants from the first wave in January and February 2020. Our study provides evidence and emphasizes the importance of controls for overseas travelers in the context of the pandemic and exemplifies how viral genomic data can facilitate COVID-19 surveillance and inform public health mitigation strategies.
| S-EPMC8373212 | biostudies-literature
Project description:Coronavirus disease 2019 (COVID-19) broke out first in Wuhan City, Hubei Province, China. In the process of controlling the pandemic, many Chinese medical staff (MS) were infected. We used government data, post mortem reports, and the medical literature on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, as well as prevention-and-control guidelines from the government, hospitals and media, to discuss the main risks factors faced by MS. We suggest that, when dealing with a similar pandemic in the future, guidance on personal protective equipment must be provided and materials reserved in advance. Also, the emergency response of medical institutions should be enhanced, and information shared with other countries facing identical severe challenges.
| S-EPMC7430766 | biostudies-literature
Project description:BackgroundMass incarceration, commonly associated with overcrowding and inadequate health resources for incarcerated people, creates a fertile environment for the spread of the coronavirus disease 2019 (COVID-19) in U.S. correctional facilities. The exact role that correctional facilities play in enhancing COVID-19 spread and enabling community re-emergence of COVID-19 is unknown.MethodsWe constructed a novel stochastic model of COVID-19 transmission to estimate the impact of correctional facilities, specifically jails and state prisons, for enhancing disease transmission and enabling disease re-emergence in local communities. Using our model, we evaluated scenarios of testing and quarantining infected incarcerated people at 0.0, 0.5, and 1.0 times the rate that occurs for infected people in the community for population sizes of 5, 10, and 20 thousand people.ResultsOur results illustrate testing and quarantining an incarcerated population of 800 would reduce the probability of a major outbreak in the local community. In addition, testing and quarantining an incarcerated population would prevent between 10 to 2640 incidences of COVID-19 per year, and annually save up to 2010 disability-adjusted life years, depending on community size.ConclusionsManaging COVID-19 in correctional facilities is essential to mitigate risks to community health, and thereby stresses the importance of improving the health standards of incarcerated people.
| S-EPMC9108375 | biostudies-literature
Project description:BackgroundThe coronavirus disease 2019 (COVID-19) is rapidly spreading in China and more than 30 countries over last two months. COVID-19 has multiple characteristics distinct from other infectious diseases, including high infectivity during incubation, time delay between real dynamics and daily observed number of confirmed cases, and the intervention effects of implemented quarantine and control measures.MethodsWe develop a Susceptible, Un-quanrantined infected, Quarantined infected, Confirmed infected (SUQC) model to characterize the dynamics of COVID-19 and explicitly parameterize the intervention effects of control measures, which is more suitable for analysis than other existing epidemic models.ResultsThe SUQC model is applied to the daily released data of the confirmed infections to analyze the outbreak of COVID-19 in Wuhan, Hubei (excluding Wuhan), China (excluding Hubei) and four first-tier cities of China. We found that, before January 30, 2020, all these regions except Beijing had a reproductive number R > 1, and after January 30, all regions had a reproductive number R < 1, indicating that the quarantine and control measures are effective in preventing the spread of COVID-19. The confirmation rate of Wuhan estimated by our model is 0.0643, substantially lower than that of Hubei excluding Wuhan (0.1914), and that of China excluding Hubei (0.2189), but it jumps to 0.3229 after February 12 when clinical evidence was adopted in new diagnosis guidelines. The number of unquarantined infected cases in Wuhan on February 12, 2020 is estimated to be 3,509 and declines to 334 on February 21, 2020. After fitting the model with data as of February 21, 2020, we predict that the end time of COVID-19 in Wuhan and Hubei is around late March, around mid March for China excluding Hubei, and before early March 2020 for the four tier-one cities. A total of 80,511 individuals are estimated to be infected in China, among which 49,510 are from Wuhan, 17,679 from Hubei (excluding Wuhan), and the rest 13,322 from other regions of China (excluding Hubei). Note that the estimates are from a deterministic ODE model and should be interpreted with some uncertainty.ConclusionsWe suggest that rigorous quarantine and control measures should be kept before early March in Beijing, Shanghai, Guangzhou and Shenzhen, and before late March in Hubei. The model can also be useful to predict the trend of epidemic and provide quantitative guide for other countries at high risk of outbreak, such as South Korea, Japan, Italy and Iran.Supplementary materialsThe supplementary materials can be found online with this article at 10.1007/s40484-020-0199-0.
| S-EPMC7095099 | biostudies-literature
Project description:A mathematical model was developed to evaluate and compare the effects and intensity of the coronavirus disease 2019 prevention and control measures in Chinese provinces. The time course of the disease with government intervention was described using a dynamic model. The estimated government intervention parameters and area difference between with and without intervention were considered as the intervention intensity and effect, respectively. The model of the disease time course without government intervention predicted that by April 30, 2020, about 3.08% of the population would have been diagnosed with coronavirus disease 2019 in China. Guangdong Province averted the most cases. Comprehensive intervention measures, in which social distancing measures may have played a greater role than isolation measures, resulted in reduced infection cases. Shanghai had the highest intervention intensity. In the context of the global coronavirus disease 2019 pandemic, the prevention and control experience of some key areas in China (such as Shanghai and Guangdong) can provide references for outbreak control in many countries.
| S-EPMC8117536 | biostudies-literature
Project description:The impact of variable infection risk by race and ethnicity on the dynamics of SARS-CoV-2 spread is largely unknown. Here, we fit structured compartmental models to seroprevalence data from New York State and analyze how herd immunity thresholds (HITs), final sizes, and epidemic risk change across groups. A simple model where interactions occur proportionally to contact rates reduced the HIT, but more realistic models of preferential mixing within groups increased the threshold toward the value observed in homogeneous populations. Across all models, the burden of infection fell disproportionately on minority populations: in a model fit to Long Island serosurvey and census data, 81% of Hispanics or Latinos were infected when the HIT was reached compared to 34% of non-Hispanic whites. Our findings, which are meant to be illustrative and not best estimates, demonstrate how racial and ethnic disparities can impact epidemic trajectories and result in unequal distributions of SARS-CoV-2 infection. K.C.M. was supported by National Science Foundation GRFP grant DGE1745303. Y.H.G. and M.L. were funded by the Morris-Singer Foundation. M.L. was supported by SeroNet cooperative agreement U01 CA261277.
| S-EPMC8221808 | biostudies-literature