Quantifying the effects of quarantine using an IBM SEIR model on scalefree networks.
Ontology highlight
ABSTRACT:
SUBMITTER: Marquioni VM
PROVIDER: S-EPMC7305517 | biostudies-literature | 2020 Sep
REPOSITORIES: biostudies-literature
Publications
Quantifying the effects of quarantine using an IBM SEIR model on scalefree networks.
Marquioni Vitor M VM de Aguiar Marcus A M MAM
Chaos, solitons, and fractals 20200620
The COVID-19 pandemic led several countries to resort to social distancing, the only known way to slow down the spread of the virus and keep the health system under control. Here we use an individual based model (IBM) to study how the duration, start date and intensity of quarantine affect the height and position of the peak of the infection curve. We show that stochastic effects, inherent to the model dynamics, lead to variable outcomes for the same set of parameters, making it crucial to compu ...[more]
Similar Datasets
Project description:BackgroundAdvanced stages of different renal diseases feature glomerular sclerosis at a histological level which is observed by light microscopy on tissue samples obtained by performing a kidney biopsy. Computer-aided diagnosis (CAD) systems leverage the potential of artificial intelligence (AI) in healthcare to support physicians in the diagnostic process.MethodsWe propose a novel CAD system that processes histological images and discriminates between sclerotic and non-sclerotic glomeruli. To this goal, we designed, tested, and compared two artificial neural network (ANN) classifiers. The former implements a shallow ANN classifying hand-crafted features extracted from Regions of Interest (ROIs) by means of image-processing procedures. The latter, instead, employs the IBM Watson Visual Recognition System, which uses a deep artificial neural network making decisions taking the images as input, without the need to design any procedure for describing images with features. The input dataset consisted of 428 sclerotic glomeruli and 2344 non-sclerotic glomeruli derived from images of kidney biopsies scanned by the Aperio ScanScope System.ResultsBoth AI approaches allowed to very accurately distinguish (mean MCC 0.95 and mean Accuracy 0.99) between sclerotic and non-sclerotic glomeruli. Although the systems may seem interchangeable, the approach based on feature extraction and classification would allow clinicians to gain information on the most discriminating features. In fact, further procedures could explain the classifier's decision by analysing which subset of features impacted the most on the final decision.ConclusionsWe developed a customizable support system that can facilitate the work of renal pathologists both in clinical and research settings.
| S-EPMC8765108 | biostudies-literature
Project description:A local COVID-19 outbreak with two community clusters occurred in a large industrial city, Shaoxing, China, in December 2021 after serial interventions were imposed. We aimed to understand the reason by analysing the characteristics of the outbreak and evaluating the effects of phase-adjusted interventions. Publicly available data from 7 December 2021 to 25 January 2022 were collected to analyse the epidemiological characteristics of this outbreak. The incubation period was estimated using Hamiltonian Monte Carlo method. A well-fitted extended susceptible-exposed-infectious-recovered model was used to simulate the impact of different interventions under various combination of scenarios. There were 387 SARS-CoV-2-infected cases identified, and 8.3% of them were initially diagnosed as asymptomatic cases. The estimated incubation period was 5.4 (95% CI 5.2-5.7) days for all patients. Strengthened measures of comprehensive quarantine based on tracing led to less infections and a shorter duration of epidemic. With a same period of incubation, comprehensive quarantine was more effective in containing the transmission than other interventions. Our findings reveal an important role of tracing and comprehensive quarantine in blocking community spread when a cluster occurred. Regions with tense resources can adopt home quarantine as a relatively affordable and low-impact intervention measure compared with centralized quarantine.
| S-EPMC10789923 | biostudies-literature
Project description:In December 2019, the first confirmed case of pneumonia caused by a novel coronavirus was reported. Coronavirus disease 2019 (COVID-19) is currently spreading around the world. The relationships among the pandemic and its associated travel restrictions, social distancing measures, contact tracing, mask-wearing habits and medical consultation efficiency have not yet been extensively assessed. Based on the epidemic data reported by the Health Commission of Wenzhou, we analysed the developmental characteristics of the epidemic and modified the Susceptible-Exposed-Infectious-Removed (SEIR) model in three discrete ways. (1) According to the implemented preventive measures, the epidemic was divided into three stages: initial, outbreak and controlled. (2) We added many factors, such as health protections, travel restrictions and social distancing, close-contact tracing and the time from symptom onset to hospitalisation (TSOH), to the model. (3) Exposed and infected people were subdivided into isolated and free-moving populations. For the parameter estimation of the model, the average TSOH and daily cured cases, deaths and imported cases can be obtained through individual data from epidemiological investigations. The changes in daily contacts are simulated using the intracity travel intensity (ICTI) from the Baidu Migration Big Data platform. The optimal values of the remaining parameters are calculated by the grid search method. With this model, we calculated the sensitivity of the control measures with regard to the prevention of the spread of the epidemic by simulating the number of infected people in various hypothetical situations. Simultaneously, through a simulation of a second epidemic, the challenges from the rebound of the epidemic were analysed, and prevention and control recommendations were made. The results show that the modified SEIR model can effectively simulate the spread of COVID-19 in Wenzhou. The policy of the lockdown of Wuhan, the launch of the first-level Public Health Emergency Preparedness measures on 23 January 2020 and the implementation of resident travel control measures on 31 January 2020 were crucial to COVID-19 control.
| S-EPMC7804084 | biostudies-literature
Project description:All plants used in this study were derived from the IBM 94 (Lee, Sharopova et al. 2002) mapping population and names used in the MIAME information correspond to Stapleton laboratory names. A conversion table identifying the official IBM names is presented below. Maize IBM94 seed was supplied by the Maize Coop and increased at the field nursery in Clayton, NC. For sowing, twelve seeds were placed in six-pack pots filled with sterilized vermiculite. Flats filled with 36 pots were placed in the greenhouse at the University of North Carolina Wilmington with solar illumination and daily watering until the majority of the plants were at the three-leaf stage (8 days). These growth conditions are similar to those used for previous inbred comparisons (Blum, Casati et al. 2004). Glass does not transmit UV-B, therefore, the plants received none of this radiation unless treated as part of the experimental design. For treatment, one set of flats with a six-pot of each line was moved onto irradiation benches with UV313 bulbs (Q-Panel Lab Products, Cleveland, OH USA) mounted 30 cm above the bench and covered with cellulose diacetate (US Plastics, Lima OH, USA). These plants received UV-B at a rate of 0.024 Wm-2, as previously described (Blum et al., 2004) for two hours (11 AM to 1PM) in August 2004. Control plants were placed under UV313 bulbs that were covered with plastic (MylarD, US Plastics, Lima, OH, USA) to block all UV-B radiation. Immediately following irradiation plants were removed from irradiation benches, and both control and experimental groups were allowed to recover for 3 h in the greenhouse. Three hours of recovery allows time for post-transcriptional regulation (such as RNA processing and small RNA cleavage) so that we are measuring the steady-state level of mRNA for each gene. Plants were irradiated centered on solar noon to maximize the amount of sunlight reaching the plants. Following recovery, the second and third seedling leaves of each of the control and experimental plants were harvested and immediately frozen in liquid nitrogen. The second and third replicate sets of plants were irradiated and harvested on succeeding days. Plant tissue batches used for RNA preparation were later used to verify genotypes. Genomic DNA was prepared from crushed tissue samples and PCR products from eleven SSR primers were scored by comparison to parental B73 and Mo17 PCR product sizes. The eleven SSR primers were chosen using and algorithm designed by T. Hudson, Dept. of Computer Science, UNCW; the algorithm allows rapid selection of a minimal combination of markers that will distinguish each IBM94 genotype. Total RNA was extracted from frozen tissue using Trizol (Invitrogen Co., Carlsbad, CA). After extraction, RNA was shipped on dry ice to the University of Arizona. Target labeling via RNA amplification and hybridization were in accordance to standard protocols posted on the Maize Microarray Project website (http://www.maizearray.org/maize_protocols.shtml ). Briefly, the target labeling protocol utilizes the Ambion Message Amp II kit to produce cRNA which is indirectly labeled using a dye coupling reaction. All arrays are prehybridized in 1% BSA, 5X SSC, 0.1% SDS. The resulting labeled cRNA (3 ug/slide) is hybridized to the arrays using a 50% formamide, 5X SSC, 0.1% SDS hybridization buffer at 42 C overnight and the arrays are washed using a series of high stringency washes. Official IBM ID Stapleton Laboratory ID Mo005 M2 Mo014 M7 Mo016 M9 Mo017 M10 Mo021 M11 Mo033 M22 Mo034 M23 Mo045 M29 Mo057 M36 Mo060 M38 Mo067 M43 Mo077 M47 Mo265 M51 Mo267 M53 Mo317 M69 Mo325 M73 Mo341 M77 Mo344 M78 Mo352 M81 Mo355 M83 Mo364 M86 Mo365 M87 Mo368 M88 Mo369 M89 Mo383 M55(akaM93) Keywords: Reference design
2009-02-18 | GSE10544 | GEO
Project description:Recent breakouts of several epidemics, such as flu pandemics, are serious threats to human health. The measures of protection against these epidemics are urgent issues in epidemiological studies. Prevention and quarantine are two major approaches against disease spreads. We here investigate the combined effects of these two measures of protection using the SIR model. We use site percolation for prevention and bond percolation for quarantine applying on a lattice model. We find a strong synergistic effect of prevention and quarantine under local interactions. A slight increase in protection measures is extremely effective in the initial disease spreads. Combination of the two measures is more effective than a single protection measure. Our results suggest that the protection policy against epidemics should account for both prevention and quarantine measures simultaneously.
| S-EPMC3216498 | biostudies-literature
Project description:Understanding the spread of infectious diseases is an extremely essential step to preventing them. Thus, correct modeling and simulation approaches are critical for elucidating the transmission of infectious diseases and improving the control of epidemics. The primary objective of this study is to simulate the spread of communicable diseases in an urban rail transit station. Data were collected by a field investigation in the city of Ningbo, China. A SEIR-based model was developed to simulate the spread of infectious diseases in Tianyi station, considering four groups of passengers (susceptible, exposed, infected, and recovered) and a 14-day incubation period. Based on the historical data of infectious diseases, the parameters of the SEIR infectious disease model were clarified, and a sensitivity analysis of the parameters was also performed. The results showed that the contact rate (CR), infectivity (I), and average illness duration (AID) were positively correlated with the number of infections. It was also found that the length of the average incubation time (AIT) was positively correlated with the number of exposed individuals and negatively correlated with the number of infectors. These simulation results provide support for the validity and reliability of using the SEIR model in studies of the spread of epidemics and facilitate the development of effective measures to prevent and control an epidemic.
| S-EPMC8211270 | biostudies-literature
Project description:The novel coronavirus responsible for COVID-19 was first identified in Hubei Province, China in December, 2019. Within a matter of months the virus had spread and become a global pandemic. In addition to international air travel, local travel (e.g. by passenger car) contributes to the geographic spread of COVID-19. We modify the common susceptible-exposed-infectious-removed (SEIR) virus spread model and investigate the extent to which short-term travel associated with driving influences the spread of the virus. We consider the case study of the US state of Minnesota, and calibrated the proposed model with travel and viral spread data. Using our modified SEIR model that considers local short-term travel, we are able to better explain the virus spread than using the long-term travel SEIR model. Short-term travel associated with driving is predicted to be a significant contributor to the historical and future spread of COVID-19. The calibrated model also predicts the proportion of infections that were detected. We find that if driving trips remain at current levels, a substantial increase in COVID-19 cases may be observed in Minnesota, while decreasing intrastate travel could help contain the virus spread.
| S-EPMC7822539 | biostudies-literature
Project description:The SEIR (susceptible-exposed-infected-recovered) model has become a valuable tool for studying infectious disease dynamics and predicting the spread of diseases, particularly concerning the COVID pandemic. However, existing models often oversimplify population characteristics and fail to account for differences in disease sensitivity and social contact rates that can vary significantly among individuals. To address these limitations, we have developed a new multi-feature SEIR model that considers the heterogeneity of health conditions (disease sensitivity) and social activity levels (contact rates) among populations affected by infectious diseases. Our model has been validated using the data of the confirmed COVID cases in Allegheny County (Pennsylvania, USA) and Hamilton County (Ohio, USA). The results demonstrate that our model outperforms traditional SEIR models regarding predictive accuracy. In addition, we have used our multi-feature SEIR model to propose and evaluate different vaccine prioritization strategies tailored to the characteristics of heterogeneous populations. We have formulated optimization problems to determine effective vaccine distribution strategies. We have designed extensive numerical simulations to compare vaccine distribution strategies in different scenarios. Overall, our multi-feature SEIR model enhances the existing models and provides a more accurate picture of disease dynamics. It can help to inform public health interventions during pandemics/epidemics.
| S-EPMC10906911 | biostudies-literature
Project description:The COVID-19 pandemic of 2020-21 has been a major challenge to public health systems worldwide. Mathematical models of epidemic are useful tools for assessment of the situation and for providing decision-making support for relevant authorities. We developed and implemented SEIR(MH) model that extends the conventional SEIR model with parameters that define public lockdown (the level and start of lockdown) and the medical system capacity to contain patients. Comparative modeling of four regions in Europe that have similar population sizes and age structures, but different public health systems, was performed: Baden-Württemberg, Lombardy, Belgium, and Switzerland. Modeling suggests that the most effective measure for controlling epidemic is early lockdown (exponential effect), followed by the number of available hospital beds (linear effect if the capacity is insufficient, with diminishing returns when the capacity is sufficient). Dynamic management of lockdown levels is likely to produce better outcomes than strict lockdown.
| S-EPMC8764356 | biostudies-literature
Project description:Quantifying entropy production in various active matter phases will open new avenues for probing self-organization principles in these far-from-equilibrium systems. It has been hypothesized that the dissipation of free energy by active matter systems may be optimized, leading to system trajectories with histories of large dissipation and an accompanying emergence of ordered dynamical states. This interesting idea has not been widely tested. In particular, it is not clear whether emergent states of actomyosin networks, which represent a salient example of biological active matter, self-organize following the principle of dissipation optimization. In order to start addressing this question using detailed computational modelling, we rely on the MEDYAN simulation platform, which allows simulating active matter networks from fundamental molecular principles. We have extended the capabilities of MEDYAN to allow quantification of the rates of dissipation resulting from chemical reactions and relaxation of mechanical stresses during simulation trajectories. This is done by computing precise changes in Gibbs free energy accompanying chemical reactions using a novel formula and through detailed calculations of instantaneous values of the system's mechanical energy. We validate our approach with a mean-field model that estimates the rates of dissipation from filament treadmilling. Applying this methodology to the self-organization of small disordered actomyosin networks, we find that compact and highly cross-linked networks tend to allow more efficient transduction of chemical free energy into mechanical energy. In these simple systems, we observe that spontaneous network reorganizations tend to result in a decrease in the total dissipation rate to a low steady-state value. Future studies might carefully test whether the dissipation-driven adaptation hypothesis applies in this instance, as well as in more complex cytoskeletal geometries.
| S-EPMC6501337 | biostudies-literature