Evaluation of the short- and long-term impacts of the COVID-19 pandemic on bus ridership in Miyazaki City, Japan

We used a Bayesian structural time series (BSTS) model to evaluate the short- and long-term impacts of the coronavirus disease 2019 (COVID-19) pandemic on transit ridership. We accessed smart-card data from Miyazaki City, Japan. We defined attributes based on card types (commuters, students and elders) and aggregated attributes (high-frequency users and "frequently used bus-stop pairs”) and analyzed the differences between all users and the extracted groups. Among card types, the short-term impact on elders was almost identical to that of all users, however, the short-term impact of the pandemic on commuters was much smaller and that of students was much larger than that of all users. The long-term trend of commuters was less fluctuated than that of all users. The long-term ridership recovery of students was higher than that of all users. Among aggregated attributes, the short-term impact was smaller on "high-frequency users” than on all users: the decrease in ridership immediately after the appearance of COVID-19 was smaller among "high-frequency users” than among all users. The long-term recoveries in the riderships of the extracted subsets were slower than the recoveries of riderships of all users. © 2023 The Authors

The Impact of Gastronomic Tourism on Thailand Economy: Under the Situation of COVID-19 Pandemic.

With the COVID-19 pandemic's complexity and inexorable devastation, this research article attempts to forecast Thailand's economic move forward through gastronomic tourism promotion. The dynamic input-output (I-O) model was the primary method for classifying gastronomic activities in tourism I-O data, which was investigated sector by sector. The Ministry of Tourism and Sports in Bangkok, Thailand, officially gathered the 2017 I-O table. To briefly explain the empirical results, it found that the main sectors of gastronomic tourism that highly impact Thailand's economy are the processing and preserving of foods, other foods, food and beverage serving activities, and other food services. In terms of forecasting during the period of the COVID-19 pandemic, the Bayesian Structural Time Series (BSTS) based on the dynamic input-output (I-O) model suggests that approximately 1% to 2% of Thailand's gastronomic tourism will be able to contribute to the GDP of this country substantially. By the way, if this research result is significant, then both the private sector and the government sector need to be concerned and promote those sectors as much as they can.

The Immediate Impact of Covid19 on Tourism Employment in Spain: Debunking the Myth of Job Precariousness?

This note explores the immediate impact that the COVID-19 crisis has had on tourist and non-tourist employment in Spain as a result of the state of alarm and period of confinement decreed from March 14th. The employment and self-employment series drawn from the Social Security affiliation data corresponding to the period between January 2017 and April 2020 are examined using the classical Box–Jenkins method (ARIMA) and the more recent Bayesian Structural Time-Series Models.

Spatiotemporal impact of non-pharmaceutical interventions against COVID-19 on the incidence of infectious diarrhea in Xi'an, China.

Background: Non-pharmaceutical interventions (NPIs) against COVID-19 may prevent the spread of other infectious diseases. Our purpose was to assess the effects of NPIs against COVID-19 on infectious diarrhea in Xi'an, China. Methods: Based on the surveillance data of infectious diarrhea, and the different periods of emergence responses for COVID-19 in Xi'an from 2011 to 2021, we applied Bayesian structural time series model and interrupted time series model to evaluate the effects of NPIs against COVID-19 on the epidemiological characteristics and the causative pathogens of infectious diarrhea. Findings: A total of 102,051 cases of infectious diarrhea were reported in Xi'an from 2011 to 2021. The Bayesian structural time series model results demonstrated that the cases of infectious diarrhea during the emergency response period was 40.38% lower than predicted, corresponding to 3,211 fewer cases, during the COVID-19 epidemic period of 2020-2021. The reduction exhibited significant variations in the demography, temporal and geographical distribution. The decline in incidence was especially evident in children under 5-years-old, with decreases of 34.09% in 2020 and 33.99% in 2021, relative to the 2017-2019 average. Meanwhile, the incidence decreased more significantly in industrial areas. Interpretation: NPIs against COVID-19 were associated with short- and long-term reductions in the incidence of infectious diarrhea, and this effect exhibited significant variations in epidemiological characteristics.

The impact of COVID-19 outbreak on the Mauritian export trade: a disaggregated analysis

Purpose>This study aims at evaluating the effect of the COVID-19 pandemic on the export trade system for Mauritius during the first half of 2020 (January 2020–June 2020).Design/methodology/approach>An initial analysis of the monthly export time series data proves that on the whole, the series have diverged from their actual trends after the outbreak of the COVID-19 pandemic: observed values are less than those predicted by the selected optimal forecast models. The authors subsequently employ the Bayesian structural time series (BSTS) framework for causal analysis to estimate the impact of the COVID-19 pandemic on the island's export system.Findings>Overall, the findings show that the COVID-19 pandemic has a statistically significant and negative impact on the Mauritian export trade system, with the five main export trading partners and sectors the most affected. Despite that the impact in some cases is not apparent for the period of study, the results indicate that total exports will surely be affected by the pandemic in the long run. Nevertheless, this depends on the measures taken both locally and globally to mitigate the spread of the pandemic.Originality/value>This study thus contributes to the growing literature on the economic impacts of the COVID-19 pandemic by focussing on a small island economy.

COVID-19, Stimulus, Vaccination and Stock Market Performance

Although the COVID-19 outbreak harms economies and causes panic among investors, stock markets keep climbing and few researchers have addressed the problem. This study finds that the negative effect exists only in the short run. When Fed provides stimulus packages to support the economy, especially after vaccine campaigns, this impact changes from negative to positive. The rationale is that the combination of stimulus packages and COVID-19 vaccines makes announcements of confirmed cases to become a buy signal for optimist investors. The investors think that stock markets will soon correct themselves and increase;hence, they buy stocks and then wait for the market to catch up. As a result, the stock market performance increases with the increase in total COVID-19 confirmed cases. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Executive orders or public fear: What caused transit ridership to drop in Chicago during COVID-19?

The COVID-19 pandemic has induced significant transit ridership losses worldwide. This paper conducts a quantitative analysis to reveal contributing factors to such losses, using data from the Chicago Transit Authority's bus and rail systems before and after the COVID-19 outbreak. It builds a sequential statistical modeling framework that integrates a Bayesian structural time-series model, a dynamics model, and a series of linear regression models, to fit the ridership loss with pandemic evolution and regulatory events, and to quantify how the impacts of those factors depend on socio-demographic characteristics. Results reveal that, for both bus and rail, remote learning/working answers for the majority of ridership loss, and their impacts depend highly on socio-demographic characteristics. Findings from this study cast insights into future evolution of transit ridership as well as recovery campaigns in the post-pandemic era.

College reopening and community spread of COVID-19 in the United States.

OBJECTIVE: After months of lockdown due to the COVID-19 outbreak, the US postsecondary institutions implemented different instruction approaches to bring their students back for the Fall 2020 semester. Given public health concerns with reopening campuses, the study evaluated the impact of Fall 2020 college reopenings on COVID-19 transmission within the 632 US university counties. STUDY DESIGN: This was a retrospective and observational study. METHODS: Bayesian Structural Time Series (BSTS) models were conducted to investigate the county-level COVID-19 case increases during the first 21 days of Fall 2020. The case increase for each county was estimated by comparing the observed time series (actual daily cases after school reopening) to the BSTS counterfactual time series (predictive daily cases if not reopening during the same time frame). We then used multilevel models to examine the associations between opening approaches (in-person, online, and hybrid) and county-level COVID-19 case increases within 21 and 42 days after classes began. The multigroup comparison between mask and non-mask-required states for these associations were also performed, given that the statewide guidelines might moderate the effects of college opening approaches. RESULTS: More than 80% of our university county sample did not experience a significant case increase in Fall 2020. There were no significant relationships between opening approaches and community transmission in both mask-required and non-mask-required states. Only small metropolitan counties and counties with a non-community college or a higher percentage of student population showed significantly positive associations with the case number increase within the first 21-day period of Fall 2020. For the longer 42-day period, the counties with a higher percentage of the student population showed a significant case increase. CONCLUSION: The overall findings underscored the outcomes of US higher education reopening efforts when the vaccines were still under development in Fall 2020. For individual county results, we invite the college- and county-level decision-makers to interpret their results using our web application.

The effect of the COVID-19 pandemic on mental health calls for police service.

Drawing upon seven years of police calls for service data (2014-2020), this study examined the effect of the COVID-19 pandemic on calls involving persons with perceived mental illness (PwPMI) using a Bayesian Structural Time Series. The findings revealed that PwPMI calls did not increase immediately after the beginning of the pandemic in March 2020. Instead, a sustained increase in PwPMI calls was identified in August 2020 that later became statistically significant in October 2020. Ultimately, the analysis revealed a 22% increase in PwPMI calls during the COVID-19 pandemic than would have been expected had the pandemic not taken place. The delayed effect of the pandemic on such calls points to a need for policymakers to prioritize widely accessible mental health care that can be deployed early during public health emergencies thus potentially mitigating or eliminating the need for increased police intervention, as was the case here. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40163-021-00157-6.

The Economic Impact of the SARS-COV-2 (COVID-19) Pandemic in Spain.

BACKGROUND: The COVID-19 pandemic has hit both the Spanish economy and the population's health hard. The result is an unprecedented economic and social crisis due to uncertainty about the remedy and the socioeconomic effects on people's lives. METHODS: We performed a retrospective analysis of the macroeconomic impact of the COVID-19 pandemic in 2020 using key indicators of the Spanish economy for the 17 Autonomous Communities (ACs) of the country. National statistics were examined in the search for impacts or anomalies occurring since the beginning of the pandemic. To estimate the strength of the impact on each of the indicators analyzed, we used Bayesian structural time series. We also calculated the correlation between the rate of GDP decline during 2020 and the cumulative incidence of COVID-19 cases per 100,000 inhabitants in the ACs. RESULTS: In 2020, the cumulative impact on the gross domestic product was of -11.41% (95% credible interval: -13.46; -9.29). The indicator for business turnover changed by -9.37% (-12.71; -6.07). The Spanish employment market was strongly affected; our estimates showed a cumulative increase of 11.9% (4.27; 19.45) in the rate of unemployment during 2020. The worst indicators were recorded in the ACs most economically dependent on the services sector. There was no statistical association between the incidence of COVID-19 in 2020 and the fall in GDP in the ACs. CONCLUSIONS: Our estimates portray a dramatic situation in Spain, where the COVID-19 crisis has had more serious economic and health consequences than in other European countries. The productive system in Spain is too dependent on sectors vulnerable to the pandemic, and it is necessary to design and implement profound changes through the European Next Generation program.

Quantifying what could have been - The impact of the Australian and New Zealand governments' response to COVID-19.

BACKGROUND: The Australian and New Zealand governments both initiated strict social distancing measures in response to the COVID-19 pandemic in late March. It remains difficult to quantify the impact this had in reducing the spread of the virus. METHODS: Bayesian structural time series model provide a model to quantify the scenario in which these government-level interventions were not placed. Our models predict these strict social distancing measures caused a 79% and 61% reduction in the daily cases of COVID-19 across Australia and New Zealand respectively. CONCLUSION: This provides both evidence and impetus for governments considering similar measures in response to COVID-19 and other pandemics.