scholarly journals Epidemic dynamics of infectious disease in metropolitan area and its optimal intervention strategy

2015 ◽  
Vol 48 (18) ◽  
pp. 136-140 ◽  
Author(s):  
Kenta Yashima ◽  
Akira Sasaki
Keyword(s):  
Infectious Disease ◽  
Metropolitan Area ◽  
Intervention Strategy ◽  
Epidemic Dynamics ◽  
Optimal Intervention

scholarly journals SPATIAL HETEROGENEITY IN SIMPLE DETERMINISTIC SIR MODELS ASSESSED ECOLOGICALLY

2012 ◽  
Vol 54 (1-2) ◽  
pp. 23-36 ◽  
Author(s):  
E. K. WATERS ◽  
H. S. SIDHU ◽  
G. N. MERCER
Keyword(s):  
Infectious Disease ◽  
Spatial Heterogeneity ◽  
Disease Transmission ◽  
Herd Immunity ◽  
Epidemic Models ◽  
Final Size ◽  
Infectious Disease Transmission ◽  
Epidemic Dynamics ◽  
Mean Crowding ◽  
Rate Of Movement

AbstractPatchy or divided populations can be important to infectious disease transmission. We first show that Lloyd’s mean crowding index, an index of patchiness from ecology, appears as a term in simple deterministic epidemic models of the SIR type. Using these models, we demonstrate that the rate of movement between patches is crucial for epidemic dynamics. In particular, there is a relationship between epidemic final size and epidemic duration in patchy habitats: controlling inter-patch movement will reduce epidemic duration, but also final size. This suggests that a strategy of quarantining infected areas during the initial phases of a virulent epidemic might reduce epidemic duration, but leave the population vulnerable to future epidemics by inhibiting the development of herd immunity.

scholarly journals Networks and the Epidemiology of Infectious Disease

2011 ◽  
Vol 2011 ◽  
pp. 1-28 ◽  
Author(s):  
Leon Danon ◽  
Ashley P. Ford ◽  
Thomas House ◽  
Chris P. Jewell ◽  
Matt J. Keeling ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Statistical Methods ◽  
Network Theory ◽  
Comprehensive Review ◽  
Epidemic Dynamics ◽  
Network Epidemiology ◽  
Growing Body ◽  
Number Of Publications ◽  
Analytical Approaches ◽  
Epidemiological Parameters

The science of networks has revolutionised research into the dynamics of interacting elements. It could be argued that epidemiology in particular has embraced the potential of network theory more than any other discipline. Here we review the growing body of research concerning the spread of infectious diseases on networks, focusing on the interplay between network theory and epidemiology. The review is split into four main sections, which examine: the types of network relevant to epidemiology; the multitude of ways these networks can be characterised; the statistical methods that can be applied to infer the epidemiological parameters on a realised network; and finally simulation and analytical methods to determine epidemic dynamics on a given network. Given the breadth of areas covered and the ever-expanding number of publications, a comprehensive review of all work is impossible. Instead, we provide a personalised overview into the areas of network epidemiology that have seen the greatest progress in recent years or have the greatest potential to provide novel insights. As such, considerable importance is placed on analytical approaches and statistical methods which are both rapidly expanding fields. Throughout this review we restrict our attention to epidemiological issues.

Simulating compliance behaviour for effective inspection strategies using agent based modelling

2016 ◽  
Vol 118 (4) ◽  
pp. 809-823 ◽  
Author(s):  
Esther van Asselt ◽  
Sjoukje Osinga ◽  
Harry Bremmers
Keyword(s):  
The Netherlands ◽  
Intervention Strategy ◽  
Real Life ◽  
Control Programme ◽  
Intervention Strategies ◽  
Content Type ◽  
Agent Based ◽  
Optimal Intervention ◽  
Compliance Behaviour

Purpose – The purpose of this paper is to simulate compliance behaviour of entrepreneurs in the Netherlands based on the Table of Eleven: 11 factors determining compliance (based on economic, cognitive, social and institutional factors). Design/methodology/approach – An Agent-Based Model (ABM) was developed that could incorporate both individual and group behaviour and allowed to evaluate the effect of various intervention strategies. For this purpose, a case study on the compliance of pig farmers with antibiotics legislation in the Netherlands was used. Findings – The effect of social factors (acceptance of legislation and social influence) on compliance levels was tested as well as the number of inspectors. This showed that the model can help to choose the most optimal intervention strategy depending on the input parameters. Research limitations/implications – Further expansion of the model may be necessary, e.g. including economic factors, in order to reflect real-life situations more closely. Practical implications – The model can be used by inspection services to effectively implement their control programme. Originality/value – The developed ABM is a first attempt to simulate compliance behaviour and as such contributes to the current limited knowledge on effective intervention strategies.

scholarly journals A Delay Differential Equation approach to model the COVID-19 pandemic

2021 ◽  
Author(s):  
Ilya Kiselev ◽  
I.R. Akberdin ◽  
F.A. Kolpakov
Keyword(s):  
Infectious Disease ◽  
Incubation Period ◽  
Population Group ◽  
Mass Action ◽  
Virus Spread ◽  
Disease Epidemiology ◽  
Epidemic Dynamics ◽  
Infectious Disease Epidemiology ◽  
Mass Action Law ◽  
Delay Differential

SEIR (Susceptible - Exposed - Infected - Recovered) approach is a classic modeling method that has frequently been applied to the study of infectious disease epidemiology. However, in the vast majority of SEIR models and models derived from them transitions from one population group to another are described using the mass-action law which assumes population homogeneity. That causes some methodological limitations or even drawbacks, particularly inability to reproduce observable dynamics of key characteristics of infection such as, for example, the incubation period and progression of the disease's symptoms which require considering different time scales as well as probabilities of different disease trajectories. In this paper, we propose an alternative approach to simulate the epidemic dynamics that is based on a system of differential equations with time delays to precisely reproduce a duration of infectious processes (e.g. incubation period of the virus) and competing processes like transition from infected state to the hospitalization or recovery. The suggested modeling approach is fundamental and can be applied to the study of many infectious disease epidemiology. However, due to the urgency of the COVID-19 pandemic we have developed and calibrated the delay-based model of the epidemic in Germany and France using the BioUML platform. Additionally, the stringency index was used as a generalized characteristic of the non-pharmaceutical government interventions implemented in corresponding countries to contain the virus spread. The numerical analysis of the calibrated model demonstrates that adequate simulation of each new wave of the SARS-CoV-2 virus spread requires dynamic changes in the parameter values during the epidemic like reduction of the population adherence to non-pharmaceutical interventions or enhancement of the infectivity parameter caused by an emergence of novel virus strains with higher contagiousness than original one. Both models may be accessed and simulated at https://gitlab.sirius-web.org/covid-19/dde-epidemiology-model utilizing visual representation as well as Jupyter Notebook.

scholarly journals Urban rail transport and SARS-CoV-2 infections: an ecological study in Lisbon Metropolitan Area

2020 ◽  
Author(s):  
Milton Severo ◽  
Ana Isabel Ribeiro ◽  
Raquel Lucas ◽  
Teresa Leao ◽  
Henrique Barros
Keyword(s):  
Metropolitan Area ◽  
Public Transportation ◽  
Socioeconomic Deprivation ◽  
Mitigation Measures ◽  
Epidemiological Surveillance ◽  
Infection Rates ◽  
Railway Stations ◽  
Small Areas ◽  
Epidemic Dynamics ◽  
Relative Risks

Introduction: Large number of passengers, limited space and shared surfaces can transform public transportation into a hub of epidemic spread. This study was conducted to investigate whether proximity to railway stations, a proxy for utilization, was associated with higher rates of SARS-CoV-2 infection across small-areas of Lisbon Metropolitan Area (Portugal). Methods: The number of SARS-CoV-2 confirmed infections from March 2 until July 5, 2020 at parish-level was obtained from the National Epidemiological Surveillance System. We used a Geographic Information System to estimate proximity to railway stations from the six railway lines operating in the area. Then, we fitted a quasi-Poisson generalized linear regression model to estimate the relative risks (RR) and corresponding 95% Confidence Intervals (95%CI). Results: Between May 2 and July 5, 2020, there were a total of 17,168 SARS-CoV-2 infections in the Lisbon Metropolitan Area, with wide disparities between parishes. Globally, parishes near one of the railway lines (Sintra) presented significantly higher SARS-CoV-2 infection rates (RR=1.42, 95%CI 1.16, 1.75) compared to those parishes located far away from railway stations, while the opposite happened for parishes near other railway lines (Sado/Fertagus), whose infection rates were significantly lower than those observed in parishes located far away from railway stations (RR=0.66, 95%CI 0.50, 0.87). However, the associations varied according to the stage of the epidemic and according to mitigation measures in place. Regression results also revealed an increasing influence of socioeconomic deprivation on SARS-CoV-2 infections. Conclusions: We found no consistent association between proximity to railway stations and SARS-CoV-2 infection rates in the most affected metropolitan area of the country, suggesting that other factors (e.g. socioeconomic deprivation) might play a more prominent role in the epidemic dynamics.

scholarly journals COVID-19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability

2020 ◽  
Author(s):  
Arthur Charpentier ◽  
Romuald Elie ◽  
Mathieu Laurière ◽  
Viet Chi Tran
Keyword(s):  
Social Interactions ◽  
Optimal Strategies ◽  
Economic Cost ◽  
Limited Capacity ◽  
Epidemic Dynamics ◽  
Optimal Intervention ◽  
Intervention Measures ◽  
Capacity Level ◽  
Parametric Specification ◽  
Short Transition

AbstractWe consider here an extended SIR model, including several features of the recent COVID-19 outbreak: in particular the infected and recovered individuals can either be detected (+) or undetected (−) and we also integrate an intensive care unit capacity. Our model enables a tractable quantitative analysis of the optimal policy for the control of the epidemic dynamics using both lockdown and detection intervention levers. With parametric specification based on literature on COVID-19, we investigate sensitivity of various quantities on optimal strategies, taking into account the subtle tradeoff between the sanitary and the economic cost of the pandemic, together with the limited capacity level of ICU. We identify the optimal lockdown policy as an intervention structured in 4 successive phases: First a quick and strong lockdown intervention to stop the exponential growth of the contagion; second a short transition phase to reduce the prevalence of the virus; third a long period with full ICU capacity and stable virus prevalence; finally a return to normal social interactions with disappearance of the virus. We also provide optimal intervention measures with increasing ICU capacity, as well as optimization over the effort on detection of infectious and immune individuals.

2. Transmission at different scales

2015 ◽  
pp. 11-26
Author(s):  
Marta L. Wayne ◽  
Benjamin M. Bolker
Keyword(s):  
Infectious Disease ◽  
Mathematical Modelling ◽  
Respiratory Viruses ◽  
Key Factors ◽  
Epidemic Dynamics ◽  
Bodily Fluids ◽  
Sexual Exchange ◽  
Blood Sucking ◽  
Vector Borne ◽  
Water Borne

The term ‘transmission’ defines infectious disease. Respiratory viruses such as influenza are airborne; diseases such as HIV and hepatitis are transmitted through direct, usually sexual, exchange of bodily fluids; water-borne diseases such as cholera can survive in the environment; and vector-borne pathogens have evolved to use other organisms, especially blood-sucking insects and mites, to travel from one host to another. ‘Transmission at different scales’ considers the filters for encounter and compatibility, mathematical modelling of epidemic dynamics, and the key factors of virulence, resistance, and tolerance.

scholarly journals Limiting-Stress-Elimination Hypothesis: Using Non-hormonal Biostimulant to Reduce Stress and Increase Savanna Cowpea [Vigna unguiculata (L.) Walp.] Productivity

2021 ◽  
Vol 12 ◽  
Author(s):  
Acheampong Atta-Boateng ◽  
Graeme P. Berlyn
Keyword(s):  
Vigna Unguiculata ◽  
Crop Production ◽  
Maximum Yield ◽  
Intervention Strategy ◽  
Crop Productivity ◽  
Absolute Maximum ◽  
Total Biomass ◽  
Optimal Intervention ◽  
Limiting Condition ◽  
Resource Conditions

An alternative decision axiom to guide in determining the optimal intervention strategy to maximize cowpea production is proposed. According to the decrement from the maximum concept of Mitscherlich, the decrement from the maximum for each stressor must be minimized to produce the absolute maximum production. In crop production, this means all deficient nutrients must be supplemented to ensure maximum yield and laid the foundation in fertilizer formulation. However, its implementation is not economically feasible in many situations, particularly where multiple environmental factors impact crop productivity as in the case of low resource conditions. We propose and test the hypothesis that yield allocation will increase when the most limiting stressor among prevailing stressors is eliminated at least until the next limiting stressor impacts productivity. We selected drought limiting savanna conditions and cowpea (Vigna unguiculata), adapted to nitrogen dependence. To determine the limiting condition, we measured the response of cowpea to D-sorbitol, nitrogen, and non-hormonal biostimulant (nhB) treatments. The nhB treatment increased total biomass by 45% compared to nitrogen, 13%, and D-sorbitol, 17%, suggesting osmotic stress is more limiting in the observed savanna conditions. The effect of the biostimulant is due to antioxidants and key amino acids that stimulate metabolism and stress resistance. Where nitrogen becomes the next constraining factor, biostimulants can contribute organic nitrogen. The study supports the use of biostimulants as candidate intervention under conditions where crop productivity is limited by multiple or alternating constraints during crop growth.

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