ABSTRACT
Purpose>By designing a system dynamics model in the form of a multimodal transportation system, this study for the first time seeks to reduce costs and time, and increase customer satisfaction by considering uncertainties in the intra city transit system, especially demand uncertainty and provide a prototype system to prove the capability of the dynamical system.Design/methodology/approach>The paper tried to model the factors affecting the intra city multimodal transportation system by defining different scenarios in the cause-and-effect model. The maps and results developed according to system dynamics modeling principles are discussed.Findings>Four scenarios were considered given the factors affecting the urban transportation system to implement the transportation information system for reducing the material and non-material costs of wrong planning of the intra city transit system. After implementing the scenarios, scenario two was selected under the following conditions: advertising for cultural development, support of authorities by efforts such as street widening to reduce traffic, optimize infrastructure, increase and optimize public transport and etc.Originality/value>The value of this paper is considering uncertainty in traffic optimization;taking into account behavioral and demand indicators such as cultural promotion, official support, early childhood learning, traffic hours and the impact of traveler social status;investigating the factors affecting the system under investigation and the reciprocal effects of these factors and real-world simulation by considering the factors and effects between them.
ABSTRACT
The outbreak of the emerging SARS-CoV-2 virus has highlighted the challenges of detecting viral infections, especially in resource-limited settings. The SARS-CoV-2 virus transmission chain is interrupted when screening and diagnosis can be performed on a large scale by identifying asymptomatic or moderately symptomatic patients. Diagnosis of COVID-19 with reverse transcription polymerase chain reaction (RT-PCR) has been limited due to inadequate access to complex, expensive equipment and reagents, which has impeded efforts to reduce the spread of virus transmission. Recently, the development of several diagnostic platforms based on the CRISPR-Cas system has reduced the dependence on RT-PCR. The first CRISPR-based diagnostic test for SARS-CoV-2 was recently approved by the U.S. Food and Drug Administration. The biosensing systems have several important features that make them suitable for point-of-care tests, including the speed of design and synthesis of each platform in less than a few days, an assay time of 1-2 h, and the cost of materials and reagents less than one dollar per test. The HUDSON-SHERLOCK and STOPCovid biosensing systems, as field-deployable and rapid diagnostic tests, can detect low-copy viruses in body fluids without nucleic acid extraction and with minimal equipment. In addition, Cas13-based treatment strategies could potentially be an effective antiviral strategy for the prevention and treatment of emerging pandemic viruses such as SARS-CoV-2. In this review, we describe recent advances in CRISPR-based diagnostic platforms with an emphasis on their use in the rapid diagnosis and potential treatment of COVID-19.