Full-year adjustment for modelling COVID-19 policies in SOUTHMOD tax-benefit microsimulation models

2021 ◽  
Author(s):  
Katrin Gasior ◽  
Helen Barnes ◽  
Maria Jouste ◽  
Jesse Lastunen ◽  
David McLennan ◽  
...  
Keyword(s):  
Microsimulation Models

scholarly journals Effects of cancer screening restart strategies after COVID-19 disruption

2021 ◽  
Vol 124 (9) ◽  
pp. 1516-1523
Author(s):  
Lindy M. Kregting ◽  
Sylvia Kaljouw ◽  
Lucie de Jonge ◽  
Erik E. L. Jansen ◽  
Elleke F. P. Peterse ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Catching Up ◽  
Incidence And Mortality ◽  
Specific Mortality ◽  
Cancer Specific Mortality ◽  
Catch Up ◽  
Microsimulation Models ◽  
The Impact

Abstract Background Many breast, cervical, and colorectal cancer screening programmes were disrupted due to the COVID-19 pandemic. This study aimed to estimate the effects of five restart strategies after the disruption on required screening capacity and cancer burden. Methods Microsimulation models simulated five restart strategies for breast, cervical, and colorectal cancer screening. The models estimated required screening capacity, cancer incidence, and cancer-specific mortality after a disruption of 6 months. The restart strategies varied in whether screens were caught up or not and, if so, immediately or delayed, and whether the upper age limit was increased. Results The disruption in screening programmes without catch-up of missed screens led to an increase of 2.0, 0.3, and 2.5 cancer deaths per 100 000 individuals in 10 years in breast, cervical, and colorectal cancer, respectively. Immediately catching-up missed screens minimised the impact of the disruption but required a surge in screening capacity. Delaying screening, but still offering all screening rounds gave the best balance between required capacity, incidence, and mortality. Conclusions Strategies with the smallest loss in health effects were also the most burdensome for the screening organisations. Which strategy is preferred depends on the organisation and available capacity in a country.

Simplex-Based Calibration of Traffic Microsimulation Models with Intelligent Transportation Systems Data

2003 ◽  
Vol 1855 (1) ◽  
pp. 80-89 ◽  
Author(s):  
Kyu-Ok Kim ◽  
L. R. Rilett
Keyword(s):  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
System Modeling ◽  
Intelligent Transportation ◽  
Simplex Algorithm ◽  
Transportation System ◽  
Transportation Systems ◽  
Test Bed ◽  
Morning Peak ◽  
Microsimulation Models

In recent years, microsimulation has become increasingly important in transportation system modeling. A potential issue is whether these models adequately represent reality and whether enough data exist with which to calibrate these models. There has been rapid deployment of intelligent transportation system (ITS) technologies in most urban areas of North America in the last 10 years. While ITSs are developed primarily for real-time traffic operations, the data are typically archived and available for traffic microsimulation calibration. A methodology, based on the sequential simplex algorithm, that uses ITS data to calibrate microsimulation models is presented. The test bed is a 23-km section of Interstate 10 in Houston, Texas. Two microsimulation models, CORSIM and TRANSIMS, were calibrated for two different demand matrices and three periods (morning peak, evening peak, and off-peak). It was found for the morning peak that the simplex algorithm had better results then either the default values or a simple, manual calibration. As the level of congestion decreased, the effectiveness of the simplex approach also decreased, as compared with standard techniques.

Evaluating the Operational Efficiency of Two Versions of Super Diverging Diamond Interchange Design: A Case Study in Denver, Colorado

2021 ◽  
pp. 036119812110372
Author(s):  
Muhammad Tahmidul Haq ◽  
Amirarsalan Mehrara Molan ◽  
Khaled Ksaibati
Keyword(s):  
Research Effort ◽  
Traffic Signals ◽  
Operational Efficiency ◽  
Traffic Demand ◽  
Operational Analysis ◽  
Signal Coordination ◽  
Traffic Volumes ◽  
Microsimulation Models ◽  
Better Than

This paper aims to advance the current research on the new super diverging diamond interchange (super DDI) design by evaluating the operational efficiency using real-world locations. As part of a comprehensive research effort on improving the performance of failing service interchanges in the mountain-plains region, the study identified three interchanges (Interstate 225 and Mississippi Avenue, Interstate 25 and 120th Avenue, and Interstate 25 and Hampden Avenue) at Denver, Colorado as the potential candidates to model for future retrofit. Four interchange designs (i.e., existing CDI [conventional diamond interchange], DDI, super DDI-1, and super DDI-2) were tested in this study. The operational analysis was conducted using VISSIM and Synchro. Several microsimulation models (120 scenarios with 600 runs in total) were created with three peak hours (a.m., noon, and p.m.) for existing (the year 2020) and projected (the year 2030) traffic volumes. The study considered two simulation networks: (1) when no adjacent traffic signal exists, to determine how the four interchange designs would perform if there were no adjacent signals or they were far away from the interchange; and (2) when there are two adjacent traffic signals, to evaluate the performance of the four interchanges in a bigger corridor with signal coordination needed. An important finding is that super DDI designs outperformed DDI with adjacent signals and higher traffic demand, while DDI performed similarly to or sometimes insignificantly better than super DDI if no adjacent intersections were located in the vicinity and if the demand was lower than the DDI’s capacity.

Simulating Earnings in Dynamic Microsimulation Models

2017 ◽  
pp. 381-412
Author(s):  
Cathal O'Donoghue ◽  
Ross H. Leach ◽  
Stephen Hynes
Keyword(s):  
Microsimulation Models

Introduction

2021 ◽  
pp. 3-24
Author(s):  
Cathal O'Donoghue
Keyword(s):  
Income Distribution ◽  
Labour Supply ◽  
Distribution Analysis ◽  
Unit Of Analysis ◽  
Environmental Models ◽  
Simulation Based ◽  
Ex Ante ◽  
Static Models ◽  
Spatial Microsimulation ◽  
Microsimulation Models

This chapter serves as an introduction to the book Practical Microsimulation Modelling. It provides as context a description of microsimulation modelling, a simulation-based tool with a micro-unit of analysis that can be used for ex-ante analysis. The methodology is motivated as a mechanism of abstracting from reality to help us understand complexity better. It describes the main analytical objectives of users of microsimulation models in the field of income distribution analysis. The chapter then describes in turn the main methods of microsimulation considered in the book: hypothetical models, static models, behavioural models (labour supply and consumption), environmental models, decomposing inequality, dynamic microsimulation models, and spatial microsimulation models. The chapter concludes by providing an outline of the book.

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