9,750 research outputs found

    Zika virus and the never-ending story of emerging pathogens and transfusion medicine

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    In the last few years, the transfusion medicine community has been paying special attention to emerging vector-borne diseases transmitted by arboviruses. Zika virus is the latest of these pathogens and is responsible for major outbreaks in Africa, Asia and, more recently, in previously infection-naïve territories of the Pacific area. Many issues regarding this emerging pathogen remain unclear and require further investigation. National health authorities have adopted different prevention strategies. The aim of this review article is to discuss the currently available, though limited, information and the potential impact of this virus on transfusion medicine

    Machine learning in drug supply chain management during disease outbreaks: a systematic review

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    The drug supply chain is inherently complex. The challenge is not only the number of stakeholders and the supply chain from producers to users but also production and demand gaps. Downstream, drug demand is related to the type of disease outbreak. This study identifies the correlation between drug supply chain management and the use of predictive parameters in research on the spread of disease, especially with machine learning methods in the last five years. Using the Publish or Perish 8 application, there are 71 articles that meet the inclusion criteria and keyword search requirements according to Kitchenham's systematic review methodology. The findings can be grouped into three broad groupings of disease outbreaks, each of which uses machine learning algorithms to predict the spread of disease outbreaks. The use of parameters for prediction with machine learning has a correlation with drug supply management in the coronavirus disease case. The area of drug supply risk management has not been heavily involved in the prediction of disease outbreaks

    Challenges in efforts to control Yellow fever outbreaks in Brazil since 2016: a literature review

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    Yellow fever is a vector-borne disease transmitted to humans and non-human primates through the bite of an infected mosquito. The disease is preventable with a live-attenuated vaccine, which is considered safe, effective, and provides lifelong immunity. Since 2016, Brazil has experienced an influx of Yellow fever outbreaks throughout the country due to the expansion of the virus. This literature review examines factors contributing to the expansion of Yellow fever throughout Brazil and identifies challenges to Yellow fever prevention and control efforts ongoing throughout the country. A systematic literature search was conducted, and twenty-nine relevant articles were found to meet the selection criteria of Yellow fever, Brazil, challenges, and population health. This review of literature revealed lack of Yellow fever immunity, adverse effects of vaccination, deforestation, fractional dosing, and various vaccine supply chain challenges to be the leading challenges facing the Yellow fever control efforts in Brazil since 2016. In the interest of public health, these findings are significant because they have shown that initiating additional prevention methods and revising policies in turn could exceedingly end the Yellow fever epidemic in Brazil, while simultaneously reducing morbidity and mortality of this vaccine-preventable disease

    The Medecins Sans Frontieres Intervention in the Marburg Hemorrhagic Fever Epidemic, Uige, Angola, 2005. I. Lessons Learned in the Hospital.

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    When the epidemic of Marburg hemorrhagic fever occurred in Uige, Angola, during 2005, the international response included systems of case detection and isolation, community education, the burial of the dead, and disinfection. However, despite large investments of staff and money by the organizations involved, only a fraction of the reported number of cases were isolated, and many cases were detected only after death. This article describes the response of Medecins Sans Frontieres Spain within the provincial hospital in Uige, as well as the lessons they learned during the epidemic. Diagnosis, management of patients, and infection control activities in the hospital are discussed. To improve the acceptability of the response to the host community, psychological and cultural factors need to be considered at all stages of planning and implementation in the isolation ward. More interventional medical care may not only improve survival but also improve acceptability

    Invasive Species Management: Foot-and-Mouth Disease in the U.S. Beef Industry

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    A conceptual bio-economic framework that integrates dynamic epidemiologicaleconomic processes was designed to analyze the effects of invasive species introduction on decision-making in a livestock sector (e.g., production and feeding). The framework integrates an epidemiological model, a dynamic livestock production model, domestic consumption, and international trade. The integrated approach captures producer and consumer responses to, and welfare outcomes of, livestock disease outbreaks, as well as alternative invasive species management policies. Scenarios of foot-and-mouth disease are simulated to demonstrate the usefulness of the framework in facilitating invasive species policy design.bio-economics, livestock, invasive species, foot-and-mouth disease, beef cattle production, Livestock Production/Industries,

    Cost-benefit analysis of foot and mouth disease control in Ethiopia

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    Foot and mouth disease (FMD) occurs endemically in Ethiopia. Quantitative insights on its national economic impact and on the costs and benefits of control options are, however, lacking to support decision making in its control. The objectives of this study were, therefore, to estimate the annual costs of FMD in cattle production systems of Ethiopia, and to conduct an ex ante cost-benefit analysis of potential control alternatives.<br/><br/>The annual costs of FMD were assessed based on production losses, export losses and control costs. The total annual costs of FMD under the current status quo of no official control program were estimated at 1354 (90% CR: 864–2042) million birr. The major cost (94%) was due to production losses. The costs and benefits of three potential control strategies: 1) ring vaccination (reactive vaccination around outbreak area supported by animal movement restrictions, 2) targeted vaccination (annual preventive vaccination in high risk areas plus ring vaccination in the rest of the country), and 3) preventive mass vaccination (annual preventive vaccination of the whole national cattle population) were compared with the baseline scenario of no official control program. Experts were elicited to estimate the influence of each of the control strategies on outbreak incidence and number of cases per outbreak. Based on these estimates, the incidence of the disease was simulated stochastically for 10 years. Preventive mass vaccination was epidemiologically the most efficient control strategy by reducing the national outbreak incidence below 5% with a median time interval of 3 years, followed by targeted vaccination strategy with a corresponding median time interval of 5 years. On average, all evaluated control strategies resulted in positive net present values. The ranges in the net present values were, however, very wide, including negative values. The targeted vaccination strategy was the most economic strategy with a median benefit cost ratio of 4.29 (90%CR: 0.29–9.63). It was also the least risky strategy with 11% chance of a benefit cost ratio of less than one.<br/><br/>The study indicates that FMD has a high economic impact in Ethiopia. Its control is predicted to be economically profitable even without a full consideration of gains from export. The targeted vaccination strategy is shown to provide the largest economic return with a relatively low risk of loss. More studies to generate data, especially on production impact of the disease and effectiveness of control measures are needed to improve the rigor of future analysis.<br/

    Invasive Species Management: Foot-and-Mouth Disease in the U.S. Beef Industry

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    A conceptual bioeconomic framework that integrates dynamic epidemiological-economic processes was designed to analyze the effects of invasive species introduction on decision making in a livestock sector (e.g., production and feeding). The framework integrates an epidemiological model, a dynamic livestock production model, domestic consumption, and international trade. The integrated approach captures producer and consumer responses and welfare outcomes of livestock disease outbreaks, as well as alternative invasive species management policies. Scenarios of foot-and-mouth disease are simulated to demonstrate the usefulness of the framework in facilitating invasive species policy design.livestock, invasive species, foot-and-mouth disease, beef cattle production, Livestock Production/Industries,

    Resilient Strategies and Sustainability in Agri-Food Supply Chains in the Face of High-Risk Events

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    [EN] Agri-food supply chains (AFSCs) are very vulnerable to high risks such as pandemics, causing economic and social impacts mainly on the most vulnerable population. Thus, it is a priority to implement resilient strategies that enable AFSCs to resist, respond and adapt to new market challenges. At the same time, implementing resilient strategies impact on the social, economic and environmental dimensions of sustainability. The objective of this paper is twofold: analyze resilient strategies on AFSCs in the literature and identify how these resilient strategies applied in the face of high risks affect the achievement of sustainability dimensions. The analysis of the articles is carried out in three points: consequences faced by agri-food supply chains due to high risks, strategies applicable in AFSCs, and relationship between resilient strategies and the achievement of sustainability dimensions.Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS "Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems" (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCA-RISE-2015.Zavala-Alcívar, A.; Verdecho Sáez, MJ.; Alfaro Saiz, JJ. (2020). Resilient Strategies and Sustainability in Agri-Food Supply Chains in the Face of High-Risk Events. IFIP Advances in Information and Communication Technology. 598:560-570. https://doi.org/10.1007/978-3-030-62412-5_46S560570598Gray, R.: Agriculture, transportation, and the COVID-19 crisis. Can. J. Agric. Econ. 68, 239–243 (2020)Queiroz, M.M., Ivanov, D., Dolgui, A., Fosso Wamba, S.: Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review. Ann. Oper. Res. (2020). https://doi.org/10.1007/s10479-020-03685-7Hobbs, J.: Food supply chains during the COVID-19 pandemic. Can. J. Agric. Econ. 68, 171–176 (2020)Shashi, P., Centobelli, P., Cerchione, R., Ertz, M.: Managing supply chain resilience to pursue business and environmental strategies. Bus. Strateg. Environ. 29(3), 1215–1246 (2019)Ivanov, D.: Predicting the impacts of epidemic outbreaks on global supply chains: a simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case. Transp. Res. Part E Logist. Transp. Rev. 136, 101922 (2020)Mamani, H., Chick, S.E., Simchi-Levi, D.: A game-theoretic model of international influenza vaccination coordination. Manage. Sci. 59(7), 1650–1670 (2013)Liu, M., Zhang, D.: A dynamic logistics model for medical resources allocation in an epidemic control with demand forecast updating. J. Oper. Res. Soc. 67, 841–852 (2016)Hessel, L.: Pandemic influenza vaccines: meeting the supply, distribution and deployment challenges. Influenza Other Respir. Viruses 3, 165–170 (2009)Orenstein, W., Schaffner, W.: Lessons learned: role of influenza vaccine production, distribution, supply, and demand—what it means for the provider. Am. J. Med. 121, S22–S27 (2008)Büyüktahtakın, I., Des-Bordes, E., Kıbış, E.: A new epidemics–logistics model: Insights into controlling the Ebola virus disease in West Africa. Eur. J. Oper. Res. 26, 1046–1063 (2018)Anparasan, A., Lejeune, M.: Analyzing the response to epidemics: concept of evidence-based Haddon matrix. J. Humanit. Logist. Supply Chain Manag. 7, 266–283 (2017)Anparasan, A.A., Lejeune, M.A.: Data laboratory for supply chain response models during epidemic outbreaks. Ann. Oper. Res. 270, 53–64 (2018). https://doi.org/10.1007/s10479-017-2462-yAnparasan, A., Lejeune, M.: Resource deployment and donation allocation for epidemic outbreaks. Ann. Oper. Res. 283, 9–32 (2019). https://doi.org/10.1007/s10479-016-2392-0Ivanov, D., Dolgui, A.: Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak. Int. J. Prod. Res. 58, 2904–2915 (2020)Ivanov, D.: Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic. Ann. Oper. Res. (2020). https://doi.org/10.1007/s10479-020-03640-6Ekici, A., Keskinocak, P., Swann, J.: Modeling influenza pandemic and planning food distribution. Manuf. Serv. Oper. Manag. 16, 11–27 (2014)Miranda, R., Schaffner, D.: Virus risk in the food supply chain. Curr. Op. Food Sci. 30, 43–48 (2019)Magalhães, A., Rossi, A., Zattar, I., Marques, M., Seleme, R.: Food traceability technologies and foodborne outbreak occurrences. Br. Food J. 121, 3362–3379 (2019)Denyer, D., Tranfield, D.: Producing a systematic review. In: Buchanan, D., Bryman, A. (eds.) The Sage Handbook of Organizational Research Methods, pp. 671–689. SAGE Publications Ltd., London (2009)Christopher, M., Peck, H.: Building the resilient supply chain. Int. J. Logist. Manag. 15, 1–14 (2004)Dolgui, A., Ivanov, D., Sokolov, B.: Ripple effect in the supply chain: an analysis and recent literature. Int. J. Prod. Res. 56, 414–430 (2018)Jüttner, U., Peck, H., Christopher, M.: Supply chain risk management: outlining an agenda for future research. Int. J. Logist. Res. 6, 197–210 (2003)Behzadi, G., O’Sullivan, M., Olsen, T., Zhang, A.: Agribusiness supply chain risk management: a review of quantitative decision models. Omega (United Kingdom) 79, 21–42 (2018)Kleindorfer, P., Saad, G.: Managing disruption risks in supply chains. Pr. Op. Man. 14, 53–68 (2005)Vishnu, C., Sridharan, R., Gunasekaran, A., Ram Kumar, P.: Strategic capabilities for managing risks in supply chains: current state and research futurities. J. Adv. Manag. Res. 17(2), 173–211 (2019)Deaton, B., Deaton, B.: Food security and Canada’s agricultural system challenged by COVID-19. Can. J. Agric. Econ. 68(2), 143–149 (2020)Richards, T., Rickard, B.: COVID-19 impact on fruit and vegetable markets. C. J. Ag. Ec. 68(2), 189–194 (2020)Larue, B.: Labor issues and COVID-19. Can. J. Agric. Econ. Can. d’agroeconomie (2020). https://doi.org/10.1111/cjag.12233Hollnagel, E.: Epilogue: RAG: the resilience analysis grid. In: Hollnagel, E., Paries, J., Woods, D., Wreathall, J. (eds.) Resilience Engineering in Practice: A Guidebook. Ashgate Pr., pp. 275–296 (2011)Ponomarov, S., Holcomb, M.: Understanding the concept of supply chain resilience. Int. J. Logist. Manag. 20, 124–143 (2009)Wu, T., Huang, S., Blackhurst, J., Zhang, X., Wang, S.: Supply chain risk management: an agent-based simulation to study the impact of retail stockouts. IEEE Trans. Eng. Manag. 60, 676–686 (2013)Schmitt, A., Singh, M.: A quantitative analysis of disruption risk in a multi-echelon supply chain. Int. J. Prod. Econ. 139, 22–32 (2012)Vroegindewey, R., Hodbod, J.: Resilience of agricultural value chains in developing country contexts: a framework and assessment approach. Sustainability 10, 916 (2018)Behzadi, G., O’Sullivan, M., Olsen, T., Scrimgeour, F., Zhang, A.: Robust and resilient strategies for managing supply disruptions in an agribusiness supply chain. Int. J. Prod. Econ. 191, 207–220 (2017)Bottani, E., Murino, T., Schiavo, M., Akkerman, R.: Resilient food supply chain design: modelling framework and metaheuristic solution approach. Comput. Ind. Eng. 135, 177–198 (2019)Meuwissen, M., et al.: A framework to assess the resilience of farming systems. Agric. Syst. 176, 102656 (2019)Dutta, P., Shrivastava, H.: The design and planning of an integrated supply chain for perishable products under uncertainties: a case study in milk industry. J. Model. Manag. (2020). https://doi.org/10.1108/JM2-03-2019-0071Aboah, J., Wilson, M., Rich, M., Lyne, M.: Operationalising resilience in tropical agricultural value chains. Supply Chain Manag. 24, 271–300 (2019)Ravulakollu, A., Urciuoli, L., Rukanova, B., Tan, Y., Hakvoort, R.: Risk based framework for assessing resilience in a complex multi-actor supply chain domain. Supply Chain Forum 19, 266–281 (2018)Das, K.: Integrating lean, green, and resilience criteria in designing a sustainable food supply chain. Proc. Int. Conf. Ind. Eng. Oper. Manag. 2018, 462–473 (2018)Zhu, Q., Krikke, H.: Managing a sustainable and resilient perishable food supply chain (PFSC) after an outbreak. Sustainability 12, 5004 (2020)Rozhkov, M., Ivanov, D.: Contingency production-inventory control policy for capacity disruptions in the retail supply chain with perishable products. IFAC-PapersOnLine 51, 1448–1452 (2018)Yavari, M., Zaker, H.: Designing a resilient-green closed loop supply chain network for perishable products by considering disruption in both supply chain and power networks. Comput. Chem. Eng. 134, 106680 (2020)Ye, F., Hou, G., Li, Y., Fu, S.: Managing bioethanol supply chain resiliency: a risk-sharing model to mitigate yield uncertainty risk. Ind. Manag. Data Syst. 118, 1510–1527 (2018)Jabbarzadeh, A., Fahimnia, B., Sheu, J., Moghadam, H.: Designing a supply chain resilient to major disruptions and supply/demand interruptions. Transp. Res. Part B Methodol. 94, 121–149 (2016)O’Leary, D.: Evolving information systems and technology research issues for COVID-19 and other pandemics. J. Organ. Comput. Electron. Commer. 30, 1–8 (2020)Zavala-Alcívar, A., Verdecho, M.-J., Alfaro-Saiz, J.-J.: A conceptual framework to manage resilience and increase sustainability in the supply chain. Sustainability 12(16), 6300 (2020)Fahimni, B., Jabbarzadeh, A.: Marrying supply chain sustainability and resilience: a match made in heaven. Transp. Res. Part E Logist. Transp. Rev. 91, 306–324 (2016)Verdecho, M.-J., Alarcón-Valero, F., Pérez-Perales, D., Alfaro-Saiz, J.-J., Rodríguez-Rodríguez, R.: A methodology to select suppliers to increase sustainability within supply chains. CEJOR (2020). https://doi.org/10.1007/s10100-019-00668-3Bai, C., Sarkis, J.: Integrating sustainability into supplier selection with grey system and rough set methodologies. Int. J. Prod. Econ. 124(1), 252–264 (2010)Bai, C., Sarkis, J.: Green supplier development: analytical evaluation using rough set theory. J. Clean. Prod. 18, 1200–1210 (2010)Valipour, S., Safaei, A., Fallah, H.: Resilient supplier selection and segmentation in grey environment. J. Clean. Prod. 207, 1123–1137 (2019)Zimmer, K., Fröhling, M., Schultmann, F.: Sustainable supplier management – a review of models supporting sustainable supplier selection, monitoring and development. Int. J. Prod. Res. 54, 1412–1442 (2016)Yang, S., Xiao, Y., Kuo, Y.: The supply chain design for perishable food with stochastic demand. Sustainability 9, 1195 (2017)Zahiri, B., Zhuang, J., Mohammadi, M.: Toward an integrated sustainable-resilient supply chain: a pharmaceutical case study. Transp. Res. Part E Logist. Transp. Rev. 103, 109–142 (2017)Duong, L., Chong, J.: Supply chain collaboration in the presence of disruptions: a literature review. Int. J. Prod. Res. 58, 3488–3507 (2020
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