scholarly journals Post‐outbreak African horse sickness surveillance: A scenario tree evaluation in South Africa’s controlled area

2020 ◽  
Author(s):  
John Duncan Grewar ◽  
Thibaud Porphyre ◽  
Evan S. Sergeant ◽  
Camilla Theresa Weyer ◽  
Peter Neil Thompson
Keyword(s):  
Scenario Tree ◽  
African Horse Sickness ◽  
Tree Evaluation

scholarly journals Benefit–Risk Assessment of the French Surveillance Protocol of Apparently Healthy Biting Dogs and Cats for Human Rabies Prevention

2021 ◽  
Vol 8 (7) ◽  
pp. 132
Author(s):  
Guillaume Crozet ◽  
Tiffany Charmet ◽  
Florence Cliquet ◽  
Emmanuelle Robardet ◽  
Barbara Dufour ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Traffic Accidents ◽  
Scenario Tree ◽  
Human Rabies ◽  
Post Exposure Prophylaxis ◽  
Policy Makers ◽  
Benefit Risk Assessment ◽  
Surveillance Protocol ◽  
Exposure Prophylaxis ◽  
Apparently Healthy

In France, apparently healthy dogs and cats that bite humans must undergo an observation period of 15 days with three veterinary visits to ascertain that they remain healthy, indicating that no zoonotic transmission of rabies virus occurred via salivary presymptomatic excretion. This surveillance protocol is mandatory for all pets that have bitten humans, despite France’s rabies-free status in non-flying mammals (i.e., a very low rabies risk). In this context, we aimed to perform a benefit–risk assessment of the existing regulatory surveillance protocol of apparently healthy biting animals, as well as alternative surveillance protocols. A scenario-tree modelling approach was used to consider the possible successions of events between a dog or cat bite and a human death attributed to either rabies or to lethal harm associated with the surveillance protocol (e.g., lethal traffic accidents when traveling to veterinary clinics or anti-rabies centers). The results demonstrated that the current French surveillance protocol was not beneficial, as more deaths were generated (traffic accidents) than avoided (by prompt post-exposure prophylaxis administration). We showed here that less stringent risk-based surveillance could prove more appropriate in a French context. The results in this study could allow policy-makers to update and optimize rabies management legislation.

scholarly journals Sustainable Scheduling of the Production in the Aluminum Furnace Hot Rolling Section with Uncertain Demand

2021 ◽  
Vol 13 (14) ◽  
pp. 7708
Author(s):  
Yiping Huang ◽  
Qin Yang ◽  
Jinfeng Liu ◽  
Xiao Li ◽  
Jie Zhang
Keyword(s):  
Hot Rolling ◽  
Production Scheduling ◽  
Demand Uncertainty ◽  
Flow Shop ◽  
Operation Time ◽  
Decision Time ◽  
Scenario Tree ◽  
Mixed Integer ◽  
Rolling Horizon ◽  
The Sustainable Development

In order to reduce the energy consumption of furnaces and save costs in the product delivery time, the focus of this paper is to discuss the uncertainty of demand in the rolling horizon and to globally optimize the sustainability of the production in the aluminum furnace hot rolling section in environmental and economic dimensions. First, the triples α/β/γ are used to describe the production scheduling in the aluminum furnace hot rolling section as the scheduling of flexible flow shop, satisfied to constraints of demand uncertainty, operation logic, operation time, capacity and demand, objectives of minimizing the residence time of the ingot in the furnace and minimizing the makespan. Second, on the basis of describing the uncertainty of demand in rolling horizon with the scenario tree, a multi-objective mixed integer linear programming (MILP) optimization model for sustainable production in the aluminum furnace hot rolling section is formulated. Finally, an aluminum alloy manufacturer is taken as an example to illustrate the proposed model. The computational results show that when the objective weight combination takes the value of α=0.7, β=0.3, the sustainability indicators of the environmental and economic dimensions can be optimized to the maximum extent possible at the same time. Increasingly, managerial suggestions associated with the trade-off between environmental and economic dimensions are presented. Scheduling in the rolling horizon can optimize the production process of the aluminum furnace hot rolling section globally, indicating that it is more conducive to the sustainable development of the environment and economic dimensions than scheduling in a single decision time period.

scholarly journals Establishment of different plasmid only-based reverse genetics systems for the recovery of African horse sickness virus

Virology ◽  
2016 ◽  
Vol 499 ◽  
pp. 144-155 ◽  
Author(s):  
Andelé M. Conradie ◽  
Liesel Stassen ◽  
Henk Huismans ◽  
Christiaan A. Potgieter ◽  
Jacques Theron
Keyword(s):  
Reverse Genetics ◽  
African Horse Sickness ◽  
African Horse Sickness Virus

scholarly journals A review of African horse sickness and its implications for Ireland

2012 ◽  
Vol 65 (1) ◽  
Author(s):  
Geoffrey M Thompson ◽  
Stephen Jess ◽  
Archie K Murchie
Keyword(s):  
African Horse Sickness

Design of hydrogen supply chains under demand uncertainty – a case study of passenger transport in Germany

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Anton Ochoa Bique ◽  
Leonardo K. K. Maia ◽  
Ignacio E. Grossmann ◽  
Edwin Zondervan
Keyword(s):  
Stochastic Optimization ◽  
Demand Uncertainty ◽  
Programming Model ◽  
Cost Minimization ◽  
Water Electrolysis ◽  
Scenario Tree ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Strong Impact ◽  
Hydrogen Supply

Abstract A strategy for the design of a hydrogen supply chain (HSC) network in Germany incorporating the uncertainty in the hydrogen demand is proposed. Based on univariate sensitivity analysis, uncertainty in hydrogen demand has a very strong impact on the overall system costs. Therefore we consider a scenario tree for a stochastic mixed integer linear programming model that incorporates the uncertainty in the hydrogen demand. The model consists of two configurations, which are analyzed and compared to each other according to production types: water electrolysis versus steam methane reforming. Each configuration has a cost minimization target. The concept of value of stochastic solution (VSS) is used to evaluate the stochastic optimization results and compare them to their deterministic counterpart. The VSS of each configuration shows significant benefits of a stochastic optimization approach for the model presented in this study, corresponding up to 26% of infrastructure investments savings.

Ecological Niche Modeling Predicting the Potential Distribution of African Horse Sickness Virus from 2020 - 2060

2021 ◽  
Author(s):  
Ayalew Assefa ◽  
Abebe Tibebu ◽  
Amare Bihon ◽  
Alemu Dagnachew ◽  
Yimer Muktar
Keyword(s):  
Solar Radiation ◽  
Ecological Niche ◽  
Annual Precipitation ◽  
Maximum Temperature ◽  
Mean Annual Precipitation ◽  
African Horse Sickness ◽  
Diurnal Range ◽  
Annual Minimum Temperature ◽  
Precipitation Seasonality ◽  
Vector Borne

Abstract African horse sickness is a vector-borne, non-contagious and highly infectious disease of equines caused by African Horse Sickness viruses (AHSv) that mainly affect horses. The occurrence of the disease causes huge economic impacts because of its fatality rate is high, trade ban and disease control costs. In planning of vectors and vector borne diseases, the application of Ecological niche models (ENM) used an enormous contribution in exactly delineating the suitable habitats of the vector. We developed an ENM with the objective of delineating the global suitability of AHSv outbreaks retrospective based on data records from 2005–2019. The model was developed in R software program using Biomod2 package with an Ensemble modeling technique. Predictive environmental variables like mean diurnal range, mean precipitation of driest month(mm), precipitation seasonality (cv), mean annual maximum temperature (oc), mean annual minimum temperature (oc) mean precipitation of warmest quarter(mm), mean precipitation of coldest quarter (mm) mean annual precipitation (mm), solar radiation (kj /day), elevation/altitude (m), wind speed (m/s) were used to develop the model. From these variables, solar radiation, mean maximum temperature, average annual precipitation, altitude and precipitation seasonality contributed 36.83%, 17.1%, 14.34%, 7.61%, and 6.4%, respectively. The model depicted the sub-Sahara African continent as the most suitable area for the virus. Mainly Senegal, Burkina Faso, Niger, Nigeria, Ethiopia, Sudan, Somalia, South Africa, Zimbabwe, Madagascar and Malawi are African countries identified as highly suitable countries for the virus. Besides, OIE-listed disease-free countries like India, Australia, Brazil, Paraguay and Bolivia have been found suitable for the virusThis model can be used as an epidemiological tool in planning control and surveillance of diseases nationally or internationally.

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