scholarly journals Evaluation of Aircraft Boarding Scenarios Considering Reduced Transmissions Risks

2020 ◽  
Vol 12 (13) ◽  
pp. 5329 ◽  
Author(s):  
Michael Schultz ◽  
Jörg Fuchte
Keyword(s):  
Physical Distance ◽  
Air Travel ◽  
Transmission Model ◽  
Confined Space ◽  
Infected People ◽  
Transmission Potential ◽  
Remote Locations ◽  
The Individual ◽  
Space Conditions ◽  
Sample Case

Air travel appears as particularly hazardous in a pandemic situation, since infected people can travel worldwide and could cause new breakouts in remote locations. The confined space conditions in the aircraft cabin necessitate a small physical distance between passengers and hence may boost virus transmissions. In our contribution, we implemented a transmission model in a virtual aircraft environment to evaluate the individual interactions between passengers during aircraft boarding and deboarding. Since no data for the transmission is currently available, we reasonably calibrated our model using a sample case from 2003. The simulation results show that standard boarding procedures create a substantial number of possible transmissions if a contagious passenger is present. The introduction of physical distances between passengers decreases the number of possible transmissions by approx. 75% for random boarding sequences, and could further decreased by more strict reduction of hand luggage items (less time for storage, compartment space is always available). If a second door is used for boarding and deboarding, the standard boarding times could be reached. Individual boarding strategies (by seat) could reduce the transmission potential to a minimum, but demand for complex pre-sorting of passengers. Our results also exhibit that deboarding consists of the highest transmission potential and only minor benefits from distance rules and hand luggage regulations.

IS Corona virus (COVID-19) droplets or airborne? Perspectives (Preprint)

2020 ◽  
Author(s):  
Tilahun Beyene Sr
Keyword(s):  
Scientific Community ◽  
Face Mask ◽  
Physical Distance ◽  
Prevention Strategy ◽  
Confined Space ◽  
Effective Prevention ◽  
Body Of Knowledge ◽  
Corona Virus ◽  
Public Areas ◽  
Mode Of Transmission

UNSTRUCTURED Abstract This scientific perspective of mode of transmission of COVID-19 is to aid scientific community in generating hypothesis. The inadequate evidence on SARS-COV-2 transmission has hindered development of effective prevention strategy and resulted in continues pandemic of the COVID-19. Therefore, in this perspective existing evidences are discussed, hypothesis are generated regarding COVID-19 mode of transmission and recommendations are forwarded based on existing body of knowledge. Two meter (2m) physical distance is not completely safe even for large droplets and wearing face mask is a key in prevention of SARS-COV-2 in public areas and confined space.

scholarly journals High COVID-19 transmission potential associated with re-opening universities can be mitigated with layered interventions

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ellen Brooks-Pollock ◽  
Hannah Christensen ◽  
Adam Trickey ◽  
Gibran Hemani ◽  
Emily Nixon ◽  
...  
Keyword(s):  
Prediction Interval ◽  
Mitigation Strategies ◽  
Control Measures ◽  
Transmission Model ◽  
Model Parameters ◽  
Infection Rates ◽  
First Year Students ◽  
Transmission Potential ◽  
Plausible Model ◽  
Effective Option

AbstractControlling COVID-19 transmission in universities poses challenges due to the complex social networks and potential for asymptomatic spread. We developed a stochastic transmission model based on realistic mixing patterns and evaluated alternative mitigation strategies. We predict, for plausible model parameters, that if asymptomatic cases are half as infectious as symptomatic cases, then 15% (98% Prediction Interval: 6–35%) of students could be infected during the first term without additional control measures. First year students are the main drivers of transmission with the highest infection rates, largely due to communal residences. In isolation, reducing face-to-face teaching is the most effective intervention considered, however layering multiple interventions could reduce infection rates by 75%. Fortnightly or more frequent mass testing is required to impact transmission and was not the most effective option considered. Our findings suggest that additional outbreak control measures should be considered for university settings.

scholarly journals On the effect of postponing pregnancy in a Zika transmission model

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Edy Soewono ◽  
Glenn Lahodny
Keyword(s):  
Stochastic Analysis ◽  
Infection Intensity ◽  
Disease Outbreak ◽  
Recruitment Rate ◽  
The Other ◽  
Transmission Model ◽  
Basic Reproductive Ratio ◽  
Numerical Investigations ◽  
The Individual ◽  
Endemic State

AbstractWe construct a Zika transmission model to investigate the effect of postponing pregnancy on the infection intensity. We perform analytical and numerical investigations for deterministic and stochastic analysis to obtain the basic reproductive ratio, endemic state, probability of disease extinction, and the probability of outbreak. The results indicate that by reducing the pregnancy rate the mosquito-to-human ratio increases, and, consequently, the basic reproductive ratio increases. Simultaneously, the probability of disease extinction decreases, and the probability of disease outbreak increases. On the other hand, the endemic state of infected infants initially increases with the decrease of the pregnancy recruitment rate, up to a certain level, and decreases as the recruitment rate of pregnancy tends to zero. This work highlights that postponing pregnancy that gives the individual temporary protection for unexpected infected newborns may increase the population infectivity.

scholarly journals Ensemble bootstrap methodology for forecasting dynamic growth processes using differential equations: application to epidemic outbreaks

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Gerardo Chowell ◽  
Ruiyan Luo
Keyword(s):  
Differential Equations ◽  
Ensemble Method ◽  
Transmission Model ◽  
Logistic Growth ◽  
Ensemble Modeling ◽  
Growth Processes ◽  
Probabilistic Forecasts ◽  
Forecasting Performance ◽  
Dynamic Growth ◽  
The Individual

AbstractBackgroundEnsemble modeling aims to boost the forecasting performance by systematically integrating the predictive accuracy across individual models. Here we introduce a simple-yet-powerful ensemble methodology for forecasting the trajectory of dynamic growth processes that are defined by a system of non-linear differential equations with applications to infectious disease spread.MethodsWe propose and assess the performance of two ensemble modeling schemes with different parametric bootstrapping procedures for trajectory forecasting and uncertainty quantification. Specifically, we conduct sequential probabilistic forecasts to evaluate their forecasting performance using simple dynamical growth models with good track records including the Richards model, the generalized-logistic growth model, and the Gompertz model. We first test and verify the functionality of the method using simulated data from phenomenological models and a mechanistic transmission model. Next, the performance of the method is demonstrated using a diversity of epidemic datasets including scenario outbreak data of theEbola Forecasting Challengeand real-world epidemic data outbreaks of including influenza, plague, Zika, and COVID-19.ResultsWe found that the ensemble method that randomly selects a model from the set of individual models for each time point of the trajectory of the epidemic frequently outcompeted the individual models as well as an alternative ensemble method based on the weighted combination of the individual models and yields broader and more realistic uncertainty bounds for the trajectory envelope, achieving not only better coverage rate of the 95% prediction interval but also improved mean interval scores across a diversity of epidemic datasets.ConclusionOur new methodology for ensemble forecasting outcompete component models and an alternative ensemble model that differ in how the variance is evaluated for the generation of the prediction intervals of the forecasts.

THE SPACES OF MYTH IN KAZUO ISHIGURO’S THE REMAINS OF THE DAY: EXPLORING THE INTERSECTIONS OF MEMORY AND HISTORY

Ensemble ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 234-242
Author(s):  
Medha Bhadra Chowdhury ◽  
Keyword(s):  
Identity Politics ◽  
Cultural Beliefs ◽  
Traditional Values ◽  
Confined Space ◽  
Spatial Dimensions ◽  
Temporal Expressions ◽  
Spatio Temporal ◽  
Post War ◽  
The Individual ◽  
Historical Past

Kazuo Ishiguro’s The Remains of the Day (1989) reconstructs the experiences of an ageing butler, Stevens, trapped within the confined space of the house he has served in for many years. The contours of memory are drawn along the spatial dimensions of the house which serve as a space of contestation between traditional values and emergent cultural beliefs in the post-war period. Physical modifications on the architecture produce continuities and alterations within the subject, who inhabits the space. This paper seeks to explore the dynamics of remembering and forgetting which are determined by the sites of memory and which trace historical changes as well as shifts in identity politics in Ishiguro’s novel. The paper critically assesses the idea of space, its functional dimension and mythic commemoration in relation to a symbolic historical past. It examines the development of subjectivity through the expansion of memory embodied in material form and the complex relationship between history and myth-making, which complicates individual identity. This paper further proposes that these spatio-temporal expressions can be understood as not only confined to the individual but may be extended to the domain of public memory and contextualized in a post-war British cultural politics of grief.

scholarly journals The Role of Migration in Maintaining the Transmission of Avian Influenza in Waterfowl: A Multisite Multispecies Transmission Model along East Asian-Australian Flyway

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Akira Endo ◽  
Hiroshi Nishiura
Keyword(s):  
Avian Influenza ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Temporal Variations ◽  
Transmission Model ◽  
Global Dynamics ◽  
Long Distance ◽  
Transmission Potential ◽  
Influenza Transmission

Background. Migratory waterfowl annually migrate over the continents along the routes known as flyways, serving as carriers of avian influenza virus across distant locations. Prevalence of influenza varies with species, and there are also geographical and temporal variations. However, the role of long-distance migration in multispecies transmission dynamics has yet to be understood. We constructed a mathematical model to capture the global dynamics of avian influenza, identifying species and locations that contribute to sustaining transmission.Methods. We devised a multisite, multispecies SIS (susceptible-infectious-susceptible) model, and estimated transmission rates within and between species in each geographical location from prevalence data. Parameters were directly sampled from posterior distribution under Bayesian inference framework. We then analyzed contribution of each species in each location to the global patterns of influenza transmission.Results. Transmission and migration parameters were estimated by Bayesian posterior sampling. The basic reproduction number was estimated at 1.1, slightly above the endemic threshold. Mallard was found to be the most important host with the highest transmission potential, and high- and middle-latitude regions appeared to act as hotspots of influenza transmission. The local reproduction number suggested that the prevalence of avian influenza in the Oceania region is dependent on the inflow of infected birds from other regions.Conclusion. Mallard exhibited the highest transmission rate among the species explored. Migration was suggested to be a key factor of the global prevalence of avian influenza, as transmission is locally sustainable only in the northern hemisphere, and the virus could be extinct in the Oceania region without migration.

scholarly journals Optimal Strategies for Dengue Prevention and Control during Daily Commuting between Two Residential Areas

Processes ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 197 ◽  
Author(s):  
Daniel Lasluisa ◽  
Edwin Barrios ◽  
Olga Vasilieva
Keyword(s):  
Optimal Strategies ◽  
Control Measures ◽  
Transmission Model ◽  
Human Populations ◽  
Personal Protection ◽  
Residential Areas ◽  
Protection Measures ◽  
Infected People ◽  
Mosquito Nets ◽  
Dengue Prevention

: In this paper, we report an application for the mathematical theory of dynamic optimization for design of optimal strategies that account for daily commuting of human residents, aiming to reduce vector-borne infections (dengue) among human populations. Our analysis is based on a two-patch dengue transmission model amended with control variables that represent personal protection measures aimed at reduction of the number of contacts between mosquitoes and human hosts (e.g., the use of repellents, mosquito nets, or insecticide-treated clothing). As a result, we have proposed and numerically solved an optimal control problem to minimize the costs associated with the application of control measures, while also minimizing the total number of dengue-infected people in both residential areas. Our principal goal was to identify an optimal strategy for personal protection that renders the maximal number of averted human infections per unit of invested cost, and this goal has been accomplished on the grounds of cost-effectiveness analysis.

scholarly journals Modelling control measures to reduce the impact of pandemic influenza among schoolchildren

2007 ◽  
Vol 136 (8) ◽  
pp. 1035-1045 ◽  
Author(s):  
S.-C. CHEN ◽  
C.-M. LIAO
Keyword(s):  
Elementary School ◽  
Pandemic Influenza ◽  
Age Groups ◽  
Integrated Approach ◽  
Control Measures ◽  
Transmission Model ◽  
Transmission Potential ◽  
Vaccination Coverage Rate ◽  
Control Programmes ◽  
The Impact

SUMMARYWe coupled the Wells–Riley equation and the susceptible–exposed–infected–recovery (SEIR) model to quantify the impact of the combination of indoor air-based control measures of enhanced ventilation and respiratory masking in containing pandemic influenza within an elementary school. We integrated indoor environmental factors of a real elementary school and aetiological characteristics of influenza to estimate the age-specific risk of infection (P) and basic reproduction number (R0). We combined the enhanced ventilation rates of 0·5, 1, 1·5, and 2/h and respiratory masking with 60%, 70%, 80%, and 95% efficacies, respectively, to predict the reducing level of R0. We also took into account the critical vaccination coverage rate among schoolchildren. Age-specific P and R0 were estimated respectively to be 0·29 and 16·90; 0·56 and 16·11; 0·59 and 12·88; 0·64 and 16·09; and 0·07 and 2·80 for five age groups 4–6, 7–8, 9–10, 11–12, and 25–45 years, indicating pre-schoolchildren have the highest transmission potential. We conclude that our integrated approach, employing the mechanism of transmission of indoor respiratory infection, population-dynamic transmission model, and the impact of infectious control programmes, is a powerful tool for risk profiling prediction of pandemic influenza among schoolchildren.

scholarly journals Trade-offs between individual and ensemble forecasts of an emerging infectious disease

2021 ◽  
Author(s):  
Rachel J Oidtman ◽  
Elisa Omodei ◽  
Moritz U. G. Kraemer ◽  
Carlos A. Casteneda-Orjuela ◽  
Erica Cruz-Rivera ◽  
...  
Keyword(s):  
Human Mobility ◽  
Emerging Infectious Diseases ◽  
Transmission Model ◽  
Ensemble Model ◽  
Emerging Pathogens ◽  
Coupled Models ◽  
Forecast Performance ◽  
Transmission Potential ◽  
Trade Offs ◽  
Probabilistic Forecasts

When new pathogens emerge, numerous questions arise about their future spread, some of which can be addressed with probabilistic forecasts. The many uncertainties about the epidemiology of emerging pathogens can make it difficult to choose among model structures and assumptions, however. To assess the potential for uncertainties about emerging pathogens to affect forecasts of their spread, we evaluated the performance of a suite of 16 forecasting models in the context of the 2015-2016 Zika epidemic in Colombia. Each model featured a different combination of assumptions about the role of human mobility in driving transmission, spatiotemporal variation in transmission potential, and the number of times the virus was introduced. All models used the same core transmission model and the same iterative data assimilation algorithm to generate forecasts. By assessing forecast performance through time using logarithmic scoring with ensemble weighting, we found that which model assumptions had the most ensemble weight changed through time. In particular, spatially coupled models had higher ensemble weights in the early and late phases of the epidemic, whereas non-spatial models had higher ensemble weights at the peak of the epidemic. We compared forecast performance of the equally-weighted ensemble model to each individual model and identified a trade-off whereby certain individual models outperformed the ensemble model early in the epidemic but the ensemble model outperformed all individual models on average. On balance, our results suggest that suites of models that span uncertainty across alternative assumptions are necessary to obtain robust forecasts in the context of emerging infectious diseases.

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