scholarly journals Inferring the Hidden Cascade Infection over Erdös-Rényi (ER) Random Graph

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1894
Author(s):  
Jaeyoung Choi
Keyword(s):  
Random Graph ◽  
Control Strategies ◽  
Effective Control ◽  
Recovery Algorithm ◽  
Global Properties ◽  
Diffusion Dynamics ◽  
Partially Observed ◽  
Underlying Network ◽  
The Impact ◽  
Recovery Problem

Finding hidden infected nodes is extremely important when information or diseases spread rapidly in a network because hints regarding the global properties of the diffusion dynamics can be provided, and effective control strategies for mitigating such spread can be derived. In this study, to understand the impact of the structure of the underlying network, a cascade infection-recovery problem is considered over an Erdös-Rényi (ER) random graph when a subset of infected nodes is partially observed. The goal is to reconstruct the underlying cascade that is likely to generate these observations. To address this, two algorithms are proposed: (i) a Neighbor-based recovery algorithm (NBRA(α)), where 0≤α≤1 is a control parameter, and (ii) a BFS tree-source-based recovery algorithm (BSRA). The first one simply counts the number of infected neighbors for candidate hidden cascade nodes and computes the possibility of infection from the neighbors by controlling the parameter α. The latter estimates the cascade sources first and computes the infection probability from the sources. A BFS tree approximation is used for the underlying ER random graph with respect to the sources for computing the infection probability because of the computational complexity in general loopy graphs. We then conducted various simulations to obtain the recovery performance of the two proposed algorithms. As a result, although the NBRA(α) uses only local information of the neighboring infection status, it recovers the hidden cascade infection well and is not significantly affected by the average degree of the ER random graph, whereas the BSRA works well on a local tree-like structure.

scholarly journals The use of light spectrum blocking films to reduce populations of Drosophila suzukii Matsumura in fruit crops

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Michelle T. Fountain ◽  
Amir Badiee ◽  
Sebastian Hemer ◽  
Alvaro Delgado ◽  
Michael Mangan ◽  
...  
Keyword(s):  
Control Strategies ◽  
Field Trials ◽  
Biological Data ◽  
Insect Vision ◽  
Invasive Pest ◽  
Effective Control ◽  
Fruit Crops ◽  
Light Spectrum ◽  
Drosophila Suzukii ◽  
The Impact

Abstract Spotted wing drosophila, Drosophila suzukii, is a serious invasive pest impacting the production of multiple fruit crops, including soft and stone fruits such as strawberries, raspberries and cherries. Effective control is challenging and reliant on integrated pest management which includes the use of an ever decreasing number of approved insecticides. New means to reduce the impact of this pest that can be integrated into control strategies are urgently required. In many production regions, including the UK, soft fruit are typically grown inside tunnels clad with polyethylene based materials. These can be modified to filter specific wavebands of light. We investigated whether targeted spectral modifications to cladding materials that disrupt insect vision could reduce the incidence of D. suzukii. We present a novel approach that starts from a neuroscientific investigation of insect sensory systems and ends with infield testing of new cladding materials inspired by the biological data. We show D. suzukii are predominantly sensitive to wavelengths below 405 nm (ultraviolet) and above 565 nm (orange & red) and that targeted blocking of lower wavebands (up to 430 nm) using light restricting materials reduces pest populations up to 73% in field trials.

Introduction to pertussis transmission and epidemiological dynamics

Pertussis ◽  
2018 ◽  
pp. 6-25
Author(s):  
Pejman Rohani ◽  
Samuel V. Scarpino
Keyword(s):  
Control Strategies ◽  
Age Distribution ◽  
Population Level ◽  
Vaccine Uptake ◽  
Effective Control ◽  
Transmission Potential ◽  
Epidemic Period ◽  
The Impact ◽  
Pertussis Epidemiology

Resolving the long-term, population-level consequences of changes in pertussis epidemiology, arising from bacterial evolution, shifts in vaccine-induced immunity, or changes in surveillance, are key challenges for devising effective control strategies. This chapter reviews some of the key features of pertussis epidemiology, together with the underlying epidemiological principles that set the context for their interpretation. These include the relationship between the age distribution of cases and pertussis transmission potential, the impact of vaccine uptake on incidence, periodicity and age incidence, as well as spatially explicit recurrent pertussis epidemics and associated extinction frequency. This review highlights some of the predictable and consistent aspects of pertussis epidemiology (e.g. the systematic increase in the inter-epidemic period with the introduction of whole-cell vaccines) and a number of important heterogeneities, including variations in contemporary patterns of incidence and geographic spread.

scholarly journals Schistosoma transmission in a dynamic seasonal environment and its impact on the effectiveness of disease control

2020 ◽  
Author(s):  
Qimin Huang ◽  
David Gurarie ◽  
Martial Ndeffo-Mbah ◽  
Emily Li ◽  
Charles H King
Keyword(s):  
Seasonal Variation ◽  
Intermediate Host ◽  
Control Strategies ◽  
Control Measures ◽  
Seasonal Effects ◽  
Effective Control ◽  
Optimal Timing ◽  
Snail Population ◽  
Dynamics And Control ◽  
The Impact

Abstract Background A seasonal transmission environment including seasonal variation of snail population density and human-snail contact patterns can affect the dynamics of Schistosoma infection and the success of control interventions. In projecting control outcomes, conventional modeling approaches have often ignored seasonality by using simplified intermediate-host modeling, or by restricting seasonal effects through use of yearly averaging. Methods We used mathematical analysis and numerical simulation to estimate the impact of seasonality on disease dynamics and control outcomes, and to evaluate whether seasonal averaging or intermediate-host reduction can provide reliable predictions of control outcomes. We also examined whether seasonality could be used as leverage in creation of effective control strategies. Results We found models that used seasonal averaging could grossly overestimate infection burden and underestimate control outcomes in highly seasonal environments. We showed that proper intra-seasonal timing of control measures could make marked improvement on the long-term burden reduction for Schistosoma transmission control, and we identified the optimal timing for each intervention. Seasonal snail control, implemented alone, was less effective than mass drug administration, but could provide additive impact in reaching control and elimination targets. Conclusion Seasonal variation makes Schistosoma transmission less sustainable and easier to control than predicted by earlier modeling studies.

scholarly journals Dynamics for a non-autonomous fall armyworm-maize interaction model with a saturation functional response

2021 ◽  
Vol 19 (1) ◽  
pp. 146-168
Author(s):  
Salamida Daudi ◽  
◽  
Livingstone Luboobi ◽  
Moatlhodi Kgosimore ◽  
Dmitry Kuznetsov ◽  
...  
Keyword(s):  
Functional Response ◽  
Seasonal Variations ◽  
Complex Dynamics ◽  
Control Strategies ◽  
Interaction Model ◽  
Fall Armyworm ◽  
Effective Control ◽  
Basic Model ◽  
Periodic Environment ◽  
The Impact

<abstract><p>In this study, we present a non-autonomous model with a Holling type II functional response, to study the complex dynamics for fall armyworm-maize biomass interacting in a periodic environment. Understanding how seasonal variations affect fall armyworm-maize dynamics is critical since maize is one of the most important cereals globally. Firstly, we study the dynamical behaviours of the basic model; that is, we investigate positive invariance, boundedness, permanence, global stability and non-persistence. We then extended the model to incorporate time dependent controls. We investigate the impact of reducing fall armyworm egg and larvae population, at minimal cost, through traditional methods and use of chemical insecticides. We noted that seasonal variations play a significant role on the patterns for all fall armyworm populations (egg, larvae, pupae and moth). We also noted that in all scenarios, the optimal control can greatly reduce the sizes of fall armyworm populations and in some scenarios, total elimination may be attained. The modeling approach presented here provides a framework for designing effective control strategies to manage the fall armyworm during outbreaks.</p></abstract>

scholarly journals Agent-Based Modeling of the Hajj Rituals with the Possible Spread of COVID-19

2021 ◽  
Vol 13 (12) ◽  
pp. 6923
Author(s):  
Ali M. Al-Shaery ◽  
Bilal Hejase ◽  
Abdessamad Tridane ◽  
Norah S. Farooqi ◽  
Hamad Al Jassmi
Keyword(s):  
Control Strategies ◽  
Control Measure ◽  
Agent Based Modeling ◽  
Control Measures ◽  
Effective Control ◽  
Mass Gathering ◽  
Agent Based Model ◽  
Agent Based ◽  
Crowd Dynamics ◽  
The Impact

With the coronavirus (COVID-19) pandemic continuing to spread around the globe, there is an unprecedented need to develop different approaches to containing the pandemic from spreading further. One particular case of importance is mass-gathering events. Mass-gathering events have been shown to exhibit the possibility to be superspreader events; as such, the adoption of effective control strategies by policymakers is essential to curb the spread of the pandemic. This paper deals with modeling the possible spread of COVID-19 in the Hajj, the world’s largest religious gathering. We present an agent-based model (ABM) for two rituals of the Hajj: Tawaf and Ramy al-Jamarat. The model aims to investigate the effect of two control measures: buffers and face masks. We couple these control measures with a third control measure that can be adopted by policymakers, which is limiting the capacity of each ritual. Our findings show the impact of each control measure on the curbing of the spread of COVID-19 under the different crowd dynamics induced by the constraints of each ritual.

Characterizing the effectiveness of COVID-19 mitigation measures: A data-centric approach (Preprint)

2020 ◽  
Author(s):  
Lukman Olagoke ◽  
Ahmet E. Topcu
Keyword(s):  
Control Measure ◽  
Control Measures ◽  
World Health ◽  
Mitigation Measures ◽  
Effective Control ◽  
The World ◽  
Decision Making Processes ◽  
And Performance ◽  
Health Organization ◽  
The Impact

BACKGROUND COVID-19 represents a serious threat to both national health and economic systems. To curb this pandemic, the World Health Organization (WHO) issued a series of COVID-19 public safety guidelines. Different countries around the world initiated different measures in line with the WHO guidelines to mitigate and investigate the spread of COVID-19 in their territories. OBJECTIVE The aim of this paper is to quantitatively evaluate the effectiveness of these control measures using a data-centric approach. METHODS We begin with a simple text analysis of coronavirus-related articles and show that reports on similar outbreaks in the past strongly proposed similar control measures. This reaffirms the fact that these control measures are in order. Subsequently, we propose a simple performance statistic that quantifies general performance and performance under the different measures that were initiated. A density based clustering of based on performance statistic was carried out to group countries based on performance. RESULTS The performance statistic helps evaluate quantitatively the impact of COVID-19 control measures. Countries tend show variability in performance under different control measures. The performance statistic has negative correlation with cases of death which is a useful characteristics for COVID-19 control measure performance analysis. A web-based time-line visualization that enables comparison of performances and cases across continents and subregions is presented. CONCLUSIONS The performance metric is relevant for the analysis of the impact of COVID-19 control measures. This can help caregivers and policymakers identify effective control measures and reduce cases of death due to COVID-19. The interactive web visualizer provides easily digested and quick feedback to augment decision-making processes in the COVID-19 response measures evaluation. CLINICALTRIAL Not Applicable

scholarly journals Power Hardware-in-the-Loop-Based Performance Analysis of Different Converter Controllers for Fast Active Power Regulation in Low-Inertia Power Systems

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3274
Author(s):  
Jose Rueda Torres ◽  
Zameer Ahmad ◽  
Nidarshan Veera Kumar ◽  
Elyas Rakhshani ◽  
Ebrahim Adabi ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Power Systems ◽  
Real Time ◽  
Control Strategies ◽  
Active Power ◽  
Power Electronic ◽  
Hardware In The Loop ◽  
Digital Controllers ◽  
Power Regulation ◽  
The Impact

Future electrical power systems will be dominated by power electronic converters, which are deployed for the integration of renewable power plants, responsive demand, and different types of storage systems. The stability of such systems will strongly depend on the control strategies attached to the converters. In this context, laboratory-scale setups are becoming the key tools for prototyping and evaluating the performance and robustness of different converter technologies and control strategies. The performance evaluation of control strategies for dynamic frequency support using fast active power regulation (FAPR) requires the urgent development of a suitable power hardware-in-the-loop (PHIL) setup. In this paper, the most prominent emerging types of FAPR are selected and studied: droop-based FAPR, droop derivative-based FAPR, and virtual synchronous power (VSP)-based FAPR. A novel setup for PHIL-based performance evaluation of these strategies is proposed. The setup combines the advanced modeling and simulation functions of a real-time digital simulation platform (RTDS), an external programmable unit to implement the studied FAPR control strategies as digital controllers, and actual hardware. The hardware setup consists of a grid emulator to recreate the dynamic response as seen from the interface bus of the grid side converter of a power electronic-interfaced device (e.g., type-IV wind turbines), and a mockup voltage source converter (VSC, i.e., a device under test (DUT)). The DUT is virtually interfaced to one high-voltage bus of the electromagnetic transient (EMT) representation of a variant of the IEEE 9 bus test system, which has been modified to consider an operating condition with 52% of the total supply provided by wind power generation. The selected and programmed FAPR strategies are applied to the DUT, with the ultimate goal of ascertaining its feasibility and effectiveness with respect to the pure software-based EMT representation performed in real time. Particularly, the time-varying response of the active power injection by each FAPR control strategy and the impact on the instantaneous frequency excursions occurring in the frequency containment periods are analyzed. The performed tests show the degree of improvements on both the rate-of-change-of-frequency (RoCoF) and the maximum frequency excursion (e.g., nadir).

scholarly journals Estimating asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan: a mathematical modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xi Huo ◽  
Jing Chen ◽  
Shigui Ruan
Keyword(s):  
Disease Transmission ◽  
Large Scale ◽  
Transmission Rate ◽  
Control Strategies ◽  
Herd Immunity ◽  
Antibody Prevalence ◽  
Screening Process ◽  
Vaccination Programs ◽  
Prevalence Level ◽  
The Impact

Abstract Background The COVID-19 outbreak in Wuhan started in December 2019 and was under control by the end of March 2020 with a total of 50,006 confirmed cases by the implementation of a series of nonpharmaceutical interventions (NPIs) including unprecedented lockdown of the city. This study analyzes the complete outbreak data from Wuhan, assesses the impact of these public health interventions, and estimates the asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan. Methods By taking different stages of the outbreak into account, we developed a time-dependent compartmental model to describe the dynamics of disease transmission and case detection and reporting. Model coefficients were parameterized by using the reported cases and following key events and escalated control strategies. Then the model was used to calibrate the complete outbreak data by using the Monte Carlo Markov Chain (MCMC) method. Finally we used the model to estimate asymptomatic and undetected cases and approximate the overall antibody prevalence level. Results We found that the transmission rate between Jan 24 and Feb 1, 2020, was twice as large as that before the lockdown on Jan 23 and 67.6% (95% CI [0.584,0.759]) of detectable infections occurred during this period. Based on the reported estimates that around 20% of infections were asymptomatic and their transmission ability was about 70% of symptomatic ones, we estimated that there were about 14,448 asymptomatic and undetected cases (95% CI [12,364,23,254]), which yields an estimate of a total of 64,454 infected cases (95% CI [62,370,73,260]), and the overall antibody prevalence level in the population of Wuhan was 0.745% (95% CI [0.693%,0.814%]) by March 31, 2020. Conclusions We conclude that the control of the COVID-19 outbreak in Wuhan was achieved via the enforcement of a combination of multiple NPIs: the lockdown on Jan 23, the stay-at-home order on Feb 2, the massive isolation of all symptomatic individuals via newly constructed special shelter hospitals on Feb 6, and the large scale screening process on Feb 18. Our results indicate that the population in Wuhan is far away from establishing herd immunity and provide insights for other affected countries and regions in designing control strategies and planing vaccination programs.

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