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AbstractAn innovative response mechanism for changed environmental turbulence is based on the proposed qualitative research methodology called hermeneutics, involving understanding ancient texts and applying them to current contexts.

For more than a year, the COVID-19 pandemic has been a major public health issue, affecting the lives of most people around the world. With both people's health and the economy at great risks, governments rushed to control the spread of the virus. Containment measures were heavily enforced worldwide until a vaccine was developed and distributed. Although researchers today know more about the characteristics of the virus, a lot of work still needs to be done in order to completely remove the disease from the population. However, this is true for most of the infectious diseases in existence, including Influenza, Dengue fever, Ebola, Malaria, and Zika virus. Understanding the transmission process of a disease is usually acquired through biological and chemical studies. In addition, mathematical models and computational simulations offer different approaches to predict the number of infectious cases and identify the transmission patterns of a disease. Information obtained helps provide effective vaccination interventions, quarantine and isolation strategies, and treatment plans to reduce disease transmissions and prevent potential outbreaks. The focus of this paper is to investigate the spread of COVID-19 and its effect on a population through mathematical models. Specifically, we use SEIR and SEIR with vaccine models to formulate the spread of COVID-19, where S, E, I, R, and V are susceptible, exposed, infected, recovered, and vaccinated compartments, respectively. With these two models we calculate a central quantity in epidemiology called the basic reproduction number, R0. This helps examine the dynamical behavior of the models and how vaccines can help prevent the spread of the virus.

Working Paper AgFoodTrade ; 2009-10 ; Empirical spatial models of trade that are based on a mathematical programming specification often exhibit a large discrepancy between the equilibrium solution and the observed demand, supply and levels of trade flows among countries. This discrepancy may be due to several causes. Assuming, however, that a trade model is not misspecified - in the sense that all the countries involved in the specific commodity trade have been included in the study and that the relevant policy instruments have been taken into account - the cause of discrepancy may be traced either to imprecision of unit transaction costs or to imprecision in the measurement of the demand and supply functions' parameters, or both. Policy assessments based on this type of imprecise models may be unsatisfactory. This paper presents a methodology for calibrating trade models of increasing complexity which are capable of generating solutions that reproduce the commodity trade flows observed in a given base year among all countries. These models may serve as a springboard for assessing the impact of various policies on demand, supply, prices, trade flows, benefits and losses in the countries under study. ; Les modèles spatiaux de commerce empiriques qui sont basés sur une spécification de programmation mathématique présentent souvent des différences importantes entre la solution d'équilibre et l'offre et la demande et les niveaux de flux commerciaux observés entre nations. Ces différences peuvent être imputables à divers facteurs. Si on suppose que le modèle de commerce est bien spécifié - au sens que tous les pays impliqués dans le commerce d'un produit particulier ont été inclus dans l'analyse et que les politiques ont été prises en compte - la source des divergences peut être attribuée aux imprécisions soit dans les coûts de transaction unitaire soit dans les paramètres des fonctions d'offre et de demande ou les deux à la fois. Les évaluations de politique basées sur ce type de modèle imprécis ne sont pas ...