A UNIVERSAL BASIC INCOME FOR BRAZIL: FISCAL AND DISTRIBUTIONAL EFFECTS OF ALTERNATIVE SCHEMES

The Covid-19 pandemic outbreak has led to an increasing interest in universal basic income (UBI) proposals, as it exposed the inadequacy of traditional welfare systems to provide basic financial security to a large share of the population. In this paper, we use a static tax-benefit microsimulation model to analyse the fiscal and distributional effects of the hypothetical implementation in Brazil of alternative UBI schemes that partially replace the existing tax-transfer system. The results indicate that introducing a UBI/Flat Tax system in the country could be both extremely effective in reducing poverty and inequality and economically viable. © 2023, Universidade Federal do Rio de Janeiro. All rights reserved.

An Agent-Based and Microsimulated Model of the Epidemiology Impact of Closure of Schools during the Covid-19 Pandemic in the Region of Aysen in Chile

This paper analyzes the impact on the spread of the COVID-19 virus of making virtual the educational system in the Region of Aysen in Chile. The analyzes is made through a mix of agent-based modelling and microsim-ulation techniques, using multiple sources of administrative and census data. The behavior of 103,000 habitants of the region is modeled during each one of the seven days of the week, for 10 weeks. The diffusion of the virus is mod-eled as consequence of the social interaction of the individuals in five different environments: home, the transportation system, at work, the educational sys-tem and in places of entertainment. The results show that the closure of the educational system is important to flatten the curve of contagious. In a world where people don't do social distancing, it could lower R0 by one unit.

Activity-based integrated modelling for assessing COVID-19 impacts on transport operations and emissions

This study combines an integrated transport, land-use, and energy (iTLE) modeling system with traffic microsimulation model and emission simulator for a holistic analysis of COVID-19 pandemic related changes in traffic flows and emissions. An activity-based travel demand model within iTLE informs pandemic traffic operation scenarios for traffic microsimulation modeling. Link-based simulation outputs inform a finer-grained emission estimation process within a MOtor Vehicle Emission Simulator. Results suggest that the overall network performance improves during lockdown as average delays and queue time decrease by 42.04% and 5.9% respectively compared to pre-COVID condition. Emission results reveal that GHG emissions significantly decrease (64%) in lockdown while it starts increasing gradually in post-pandemic period. Link-based emission analysis indicates that major arterial streets achieve a significant reduction in air pollutant emission. The findings of this study will help transportation planners, engineers, and policymakers to devise effective policies for the improvement of transport operations and emissions.

Simulations of Policy Responses and Interventions to Promote Inclusive Adaptation to and Recovery from the COVID-19 Crisis in Ghana

We assess the impact of COVID-19 shocks on household welfare and the effectiveness of select policies implemented to reduce their impact on welfare in Ghana. We adopt a microsimulation approach to assess the effects of COVID-19 on household welfare. Welfare fell by 34.2% to 41.9% between March and June 2020. Over the same period, the poverty headcount and the Gini index increased by 9 to 10.5 percentage points and 0.4 to 0.6 points respectively. The number of poor people increased by 2.8 to 3.2 million. The hardest-hit sector was education, with agriculture, forestry and fishing, trade and repairs, manufacturing, and other services also affected. The effects vary for men, women and children. While women experienced the largest decline in welfare, men experienced the highest increase in poverty incidence. The three policies selected reduced poverty marginally but were unable to offset the increase in poverty that occurred between March and June. The estimated cost of the three policies is GHS3.7 billion excluding administrative costs, which equates to approximately 1% of 2020 GDP © 2022, Cooke et al

Impact of the Covid-19 Pandemic on Monetary Child Poverty in Morocco

The Covid-19 pandemic had a very quick and damaging impact on several economies around the world, including in Morocco. This economy was hit hard with some sectors strongly exposed to the impact on the households and their children. In this article, we built a micro-simulation model and use it jointly with an input-output model to assess the distributional impact of COVID-19 and mitigation measures targeting households in Morocco with a focus on children living in poor households. Our original results show that the crisis has led to a fairly significant increase in poverty, with more pronounced effects in the urban area. Children under 5 years of age and young adults (over 18 years of age) are the most affected. Just over half a million children under the age of 18 would fall into poverty as a result of the pandemic. The mitigation measures put in place by the government and additional measures we designed and simulated further reduce the negative impact of the pandemic. In addition, the number of vulnerable rural population has decreased in both rural and urban areas. However, the two scenarios focusing on mitigation of the effects of the pandemic do not fully compensate for the negative effects of the pandemic in the urban area as opposed to rural areas. When we focus our analysis by age category, the incidence rates of vulnerability decrease to their initial rates for children under 5 years of age and decrease very slightly for youth aged 5 to 17 years at the national level. However, we find that this vulnerability is deeper and more severe even after the implementation of compensatory measures © 2022, Abdelkhalek et al

Projected long-term effects of colorectal cancer screening disruptions following the COVID-19 pandemic.

The aftermath of the initial phase of the COVID-19 pandemic may contribute to the widening of disparities in colorectal cancer (CRC) outcomes due to differential disruptions to CRC screening. This comparative microsimulation analysis uses two CISNET CRC models to simulate the impact of ongoing screening disruptions induced by the COVID-19 pandemic on long-term CRC outcomes. We evaluate three channels through which screening was disrupted: delays in screening, regimen switching, and screening discontinuation. The impact of these disruptions on long-term CRC outcomes was measured by the number of life-years lost due to CRC screening disruptions compared to a scenario without any disruptions. While short-term delays in screening of 3-18 months are predicted to result in minor life-years loss, discontinuing screening could result in much more significant reductions in the expected benefits of screening. These results demonstrate that unequal recovery of screening following the pandemic can widen disparities in CRC outcomes and emphasize the importance of ensuring equitable recovery to screening following the pandemic.

Differences in COVID-19 Policies and Income Distribution: A Cross-Country Comparison

This paper looks at the distribution of disposable income by deciles to indicate how specific mitigating measures have influenced income groups and considers the effectiveness of different combinations of containment measures in the European Union. Simulations using the EUROMOD tax-benefit microsimulation model imply that the mitigating effects of the simulated measures are regressive, with a bigger influence on the bottom part of the income distribution. It is also observed that old democracies benefit from these measures more than new democracies. Surprisingly, our results further reveal that for the two highest decile income groups, the COVID-19 containment measures are stronger in new democracies. Finally, a qualitative comparative analysis of 19 EU countries suggests that each country should apply mixes of containment measures that fit its own context. Although there is no one-size-fits-all policy, old democracies seem more successful at handling the consequences of the COVID-19 crisis than new democracies. This study complements the literature as it shows how COVID-19 measures have influenced household income groups, and second, it adds to earlier studies by clarifying that only specific context-dependent combinations of containment measures are successful at preventing the loss of people's living standards, thereby giving policymakers the necessary leeway to formulate effective policies.

The ‘German Job Miracle' and Its Impact on Income Inequality: A Decomposition Study

In the last 15 years before the COVID-19 crisis, Germany has experienced a strong and continuous increase in employment - the ‘German job miracle'. During this period, income inequality, which had previously increased sharply, remained relatively stable. This paper analyzes the impact of employment changes on disposable income inequality between 2004 and 2015 and gives an answer to the question why inequality remained constant despite the dramatic increase in employment. It is the first study to examine the effect of changing labor supply patterns due to changes in policies, wages and preferences, as well as the role that labor market constraints have played for inequality of disposable income. It finds that inequality would have increased further due to a transforming population structure, but increasing employment and policy changes almost completely offset this development. The results show that employment growth due to the reduction of labor market constraints has been more important in slowing down the increase in inequality than changes in labor supply © 2023, Mühlhan

Assessing the poverty impact of the COVID-19-induced tourism crisis in Tanzania: a social accounting matrix microsimulation analysis

The COVID-19 pandemic has caused major disruptions to international tourism and has stimulated research interest. This study examines links between COVID-19-induced tourism disruption and poverty in Tanzania. Unlike previous studies linking COVID-19, tourism and poverty, this paper uses a social accounting matrix (SAM) microsimulation analysis that allows decomposition of poverty indices by population subgroup and assessment of the drivers of aggregate poverty. The results of the SAM multiplier analysis indicate that all households will experience reduced incomes, and that this effect will be more pronounced in urban than rural households. The microsimulation results suggest that the COVID-19-induced tourism crisis will exacerbate the poverty headcount, poverty gap and poverty severity, with urban and rural non-farm households being most affected. The results of the poverty decomposition show that the growth effect has a stronger impact than the inequality effect on increased poverty. Poverty increases and inequality decreases simultaneously. The paper suggests several demand- and supply-side policies that may help to build tourism resilience and recovery and alleviate poverty in Tanzania in the post-COVID world.

The impact of the COVID-19 pandemic on poverty and inequality in Mexico

The objective is to quantify the effect of the COVID-19 pandemic on employment, poverty and inequality in Mexico. The methodology is based on a probit model to identify individuals at risk of employment loss, whose earnings are set to zero in ENIGH 2018 to match changes in employment and earnings observed in between December 2019 and the May 2020 according to ENOE and ETOE surveys, respectively. MEXMOD, Mexico's microsimulation model, is used to simulate tax-benefit policies based on the pre-COVID and COVID-scenarios. The results show that there was a loss of 12.1 million jobs. Poverty reached 60.16% and extreme poverty reached 29.73%;inequality grew 8.2%. It is recommended to strengthen social policy with extra funding (taxing the rich) to achieve greater redistribution. The limitation is that income distribution is held constant as we do not have ENIGH 2020. The originality is to offer timely measures of poverty and inequality using microsimulation techniques to overcome the lack of data during the pandemic. The research concludes that there are not automatic stabilizers to cope COVID-19 negative effects and cash-transfers are not sufficient to do so. © 2021 The Author(s).

Probabilistic microsimulation to examine the cost-effectiveness of hospital admission screening strategies for carbapenemase-producing enterobacteriaceae (CPE) in the United Kingdom.

BACKGROUND: Antimicrobial resistance has been recognised as a global threat with carbapenemase- producing-Enterobacteriaceae (CPE) as a prime example. CPE has similarities to COVID-19 where asymptomatic patients may be colonised representing a source for onward transmission. There are limited treatment options for CPE infection leading to poor outcomes and increased costs. Admission screening can prevent cross-transmission by pre-emptively isolating colonised patients. OBJECTIVE: We assess the relative cost-effectiveness of screening programmes compared with no- screening. METHODS: A microsimulation parameterised with NHS Scotland date was used to model scenarios of the prevalence of CPE colonised patients on admission. Screening strategies were (a) two-step screening involving a clinical risk assessment (CRA) checklist followed by microbiological testing of high-risk patients; and (b) universal screening. Strategies were considered with either culture or polymerase chain reaction (PCR) tests. All costs were reported in 2019 UK pounds with a healthcare system perspective. RESULTS: In the low prevalence scenario, no screening had the highest probability of cost-effectiveness. Among screening strategies, the two CRA screening options were the most likely to be cost-effective. Screening was more likely to be cost-effective than no screening in the prevalence of 1 CPE colonised in 500 admitted patients or more. There was substantial uncertainty with the probabilities rarely exceeding 40% and similar results between strategies. Screening reduced non-isolated bed-days and CPE colonisation. The cost of screening was low in relation to total costs. CONCLUSION: The specificity of the CRA checklist was the parameter with the highest impact on the cost-effectiveness. Further primary data collection is needed to build models with less uncertainty in the parameters.

UrbanPop: A spatial microsimulation framework for exploring demographic influences on human dynamics

Ensuring the social equity of planning measures in social systems requires an understanding of human dynamics, particularly how individual relationships, activities, and interactions intersect with individual needs. Spatial microsimulation models (SMSMs) support planning for human security goals by representing human dynamics through realistic, georeferenced synthetic populations, that a) provide a complete representation of social systems while b) also protecting individual privacy. In this paper, we present UrbanPop, an open and reproducible SMSM framework for analysis of human dynamics with high spatial, temporal, and demographic resolution. UrbanPop creates synthetic populations of demographically detailed worker and student agents, positioning them first at probable nighttime locations (home), then moving them to probable daytime locations (work/school). Summary aggregations of these populations match the granular detail available at the census block group level in the American Community Survey Summary File (SF), providing realistic approximations of the actual population. UrbanPop users can select particular demographic traits important in their application, resulting in a highly tailored agent population. We first lay out UrbanPop's baseline methodology, including population synthesis, activity modeling, and diagnostics, then demonstrate these capabilities by developing case studies of shifting population distributions and high-risk populations in Knox County, TN during the global COVID-19 pandemic. • Individual demographics, location, and activities influence population responses to transformational events. • Increased telework rates, school closures altered daytime population distributions early in the COVID-19 pandemic. • Spatial heterogeneity of high-risk individuals during COVID-19 pandemic during both nighttime and daytime. [ FROM AUTHOR]

Implications of COVID-19 and mitigation measures on gender and the Zimbabwean economy.

This paper provides a macro-micro modeling analysis of the ex-ante effects of COVID-19 mitigation and recovery policies on macroeconomic and distributional effects, particularly on female and male workers, income distribution, and poverty in Zimbabwe. With an emphasis on modeling gender-disaggregated labor markets and COVID-19 policy responses, the paper presents and combines the most recent data on poverty, gender, and the economy at the national level. The study finds that i) without any government mitigation measures, the gross domestic product will remain below business-as-usual levels; ii) poorer women are hardest hit because they are employed in sectors that are exposed and vulnerable to COVID-19 response measures; and iii) mitigation measures to counteract the negative effects of increases in poverty are effective only in the short term, and additional measures to sustain poverty reduction for the long term to sustain the poverty reductions are required. These results highlight the short-term versus long-term dilemma the government faces when contemplating responses to COVID-19.

The microsimulation modeling as a tool for transport policies assessment: An application to a real case study

Nowadays, alongside the traditional statistical and semi-probabilistic methods, through which it is possible to obtain an estimate of the road network performances whatever its geometric-functional configuration, the use of microscopic traffic simulation techniques is widespread, allowing a "dynamic"approach to the problem (e.g. evaluation of infrastructural interventions, traffic management, etc.). The traffic micro-simulation models are able to analyze and process, instant by instant, the movement of single vehicles on the network, on the basis of laws related to the vehicle movement and the driving behavior. Based on this premise, this study proposes an overview of traffic simulation models, with a focus on the advantages of microsimulation. In this direction, the paper presents an application to a real case study in the city of Catania (Italy), in order to evaluate the impact of different traffic regulation strategies in terms of level of service (LoS), road emissions and fuel consuption through scenario evaluations. First results demonstrates that traffic modeling and the implementation of microsimulation tools represent a valid support for the transport policies assessment, providing a basis for future research steps that will address the simulation of larger areas, through before and after analysis and the evaluation of different key performance indicators. © 2022 Author(s).

UrbanPop: A spatial microsimulation framework for exploring demographic influences on human dynamics

Ensuring the social equity of planning measures in social systems requires an understanding of human dynamics, particularly how individual relationships, activities, and interactions intersect with individual needs. Spatial microsimulation models (SMSMs) support planning for human security goals by representing human dynamics through realistic, georeferenced synthetic populations, that a) provide a complete representation of social systems while b) also protecting individual privacy. In this paper, we present UrbanPop, an open and reproducible SMSM framework for analysis of human dynamics with high spatial, temporal, and demographic resolution. UrbanPop creates synthetic populations of demographically detailed worker and student agents, positioning them first at probable nighttime locations (home), then moving them to probable daytime locations (work/school). Summary aggregations of these populations match the granular detail available at the census block group level in the American Community Survey Summary File (SF), providing realistic approximations of the actual population. UrbanPop users can select particular demographic traits important in their application, resulting in a highly tailored agent population. We first lay out UrbanPop's baseline methodology, including population synthesis, activity modeling, and diagnostics, then demonstrate these capabilities by developing case studies of shifting population distributions and high-risk populations in Knox County, TN during the global COVID-19 pandemic.

The effect of COVID-19 and the wage compensation measure on income-related gender disparities

Many countries implemented wage compensation measures during the COVID-19 crisis to alleviate income losses and avoid employment reductions. We focus on the gender dimension of incomes in Estonia, which has been grappling with the highest gender wage gap in Europe, and investigate whether the crisis and related wage compensation may have worsened existing gender imbalances. Using detailed administrative datasets and EUROMOD microsimulation model, we show that the COVID-19 crisis had a significant negative effect on employment income for both men and women, but the wage compensation implemented in 2020 appeared to cushion these effects. Income losses were slightly higher for men, but the cushioning effect of the compensation was higher for women. Overall, income-related gender disparities did not change significantly during the crisis. Still, the wage compensation measure has contributed to preventing income-related gender disparities increasing further, particularly in the hotels and restaurants sector and wholesale and retail trade sector.

What happens when post-secondary programmes go virtual for COVID-19? Effects of forced telecommuting on travel demand of post-secondary students during the pandemic.

The outbreak of coronavirus disease 2019 (COVID-19) spreads globally, disrupting every aspect of everyday activities. Countermeasures during the pandemic, such as remote working and learning, proliferated tele-activities worldwide during the COVID -19 pandemic. The prevalence of telecommuting could lead to new activity-travel patterns. It is in the interest of transport demand modellers to capture this developing trend of telecommuting using state-of-art travel demand forecasting techniques. This study develops a modelling framework using activity-based and agent-based microsimulation to forecast activity-travel demand considering telecommuting and the pandemic. For empirical application, the modelling framework investigates changes in travel behaviours in post-secondary students when all major post-secondary institutions in the Greater Toronto Area (GTA), Canada, decided to go virtual during the pandemic. The empirical investigation reveals that enforced telecommuting and the pandemic caused significant mobility drops and shifts in students' trip starting time patterns. While only considering the influence of telecommuting, the empirical exercise reveals noteworthy dynamics between telecommuting and the overall travel demand. Telecommuting could simultaneously reduce the need to commute but also induce discretionary travel. When telecommuting is enforced, students' overall trip rates drop by 14.2%, despite increasing trip rates for all discretionary activities except shopping/market. Moreover, the study demonstrates that it is beneficial to model at-home productive and maintenance episodes when telecommuting is prominent.

Microsimulation Calibration Integrating Synthetic Population Generation and Complex Interaction Clusters to Evaluate COVID-19 Spread

Agent-based microsimulation is a modeling technique used mostly in social sciences;nevertheless, its bottom-up approach to describe a system is helpful for engineering fields as well. Such modeling technique starts by generating a synthetic population to set the units of analysis in the simulation. Some authors have used large synthetic populations of entire cities for different purposes such as solving transportation problems, conducting spatial analysis, and analyzing health care systems. However, generating synthetic populations is still a difficult task, especially for microsimulation models that evaluate COVID-19 spread. Therefore, this chapter proposes an algorithm that generates a synthetic population to evaluate COVID-19 spread in a microsimulation scenario. Each individual in the population is characterized by specific features, such as age, gender, comorbidities, work activities, and school activities. Moreover, the population of individuals is grouped into four clusters: home, work, school, and shopping. In each cluster, the social interaction is stablished using scale-free fully-connected networks. This proposal was validated using data on the second largest city in Colombia, i.e., Medellín, achieving quite promising results (which are close to actual microdata on the population of said city) and a total average error of 4.53%. Future studies could add some new clusters, such as transportation and geographic location. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Activity-based integrated modelling for assessing COVID-19 impacts on transport operations and emissions

This study combines an integrated transport, land-use, and energy (iTLE) modeling system with traffic microsimulation model and emission simulator for a holistic analysis of COVID-19 pandemic related changes in traffic flows and emissions. An activity-based travel demand model within iTLE informs pandemic traffic operation scenarios for traffic microsimulation modeling. Link-based simulation outputs inform a finer-grained emission estimation process within a MOtor Vehicle Emission Simulator. Results suggest that the overall network performance improves during lockdown as average delays and queue time decrease by 42.04% and 5.9% respectively compared to pre-COVID condition. Emission results reveal that GHG emissions significantly decrease (64%) in lockdown while it starts increasing gradually in post-pandemic period. Link-based emission analysis indicates that major arterial streets achieve a significant reduction in air pollutant emission. The findings of this study will help transportation planners, engineers, and policymakers to devise effective policies for the improvement of transport operations and emissions. [ FROM AUTHOR] Copyright of Transportation Letters is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Modelling of Interactions Between Pedestrians and Vehicular Traffic to Promote Active Mobility: The Case of San Benedetto Neighbourhood in Cagliari (Italy)

The COVID-19 has significantly led to changes in the mobility needs and in user travel behavior, due to the measures adopted to reduce the spread of the virus. While on the one hand this has resulted in a reduction in the number of trips, on the other this has entailed an increase in the use of the private car, considered as the safest form of transportation in urban contexts. Thus, administrations and policy makers have to promote actions and strategies to encourage soft mobility (i.e. walking and cycling), viewed as solutions to reduce transport emissions and ensure social distancing. This often implies the need for a redesign of urban spaces as pedestrians experience uncomfortable or unsafe situations about the surrounding environment. Within this framework, the paper proposes a methodological framework to evaluate the interactions between pedestrians and vehicular traffic using a microsimulation approach. The analyzed case study concerns a road intersection within the S. Benedetto neighbourhood in Cagliari (Italy). A scenario assessment has been performed through the computation of several performance indicators related both to private transport (i.e. level of service and emissions) and pedestrian users (i.e. density;speed and crossing time). The comparative analysis of results demonstrates that this research approach could represent a flexible and effective tool in guiding administrations through the decision-making process during the planning and development of projects for redevelopment of urban spaces and the promotion of soft mobility. Further research will focus on an extended study area, by modelling the behaviour of different categories of pedestrians and introducing in-field data. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.