Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China

Prevention of COVID-19 pandemic through technological innovation: ensuring global innovative capability, absorptive capacity, and adaptive healthcare competency

The study examines the role of technology transfer in preventing communicable diseases, including COVID-19, in a heterogeneous panel of selected 65 countries. The study employed robust least square regression and innovation accounting matrixes to get robust inferences. The results found that overall technological innovation, including innovative capability, absorptive capacity, and healthcare competency, helps reduce infectious diseases, including the COVID-19 pandemic. Patent applications, scientific and technical journal articles, trade openness, hospital beds, and physicians are the main factors supporting the reduction of infectious diseases, including the COVID-19 pandemic. Due to inadequate research and development, healthcare infrastructure expenditures have caused many communicable diseases. The increasing number of mobile phone subscribers and healthcare expenditures cannot minimize the coronavirus pandemic globally. The impulse response function shows an increasing number of patent applications, mobile penetration, and hospital beds that will likely decrease infectious diseases, including COVID-19. In contrast, insufficient resource spending would likely increase death rates from contagious diseases over a time horizon. It is high time to digitalize healthcare policies to control coronavirus worldwide.

Institutional development and the government response to COVID-19 in China

As COVID-19 is pervasive across the globe, governments in different countries face the dilemma of restricting the transmission risk of the virus by social distancing while yet maintaining economic activity. Inadequate social distancing policies lead to more infection cases and deaths, while over stringent social distancing policies have significant economic cost implications. This study investigates the role of local government institutions in striking the balance between saving lives and economic recovery. We based our study on a sample of 28 provincial governments in China during the early outbreak of 2020 when the emergency responses of local governments were synchronous. The findings show that local governments in those provinces with lower degrees of marketization, which were accustomed to directly intervene in the social system, mandatorily quarantined many more close contacts for each confirmed case than those in the more market-oriented provinces whose social distancing policies took economic considerations into account. The 'overdone' (over stringent) social distancing policies in the more state-oriented provinces led to lower human mobility and economic growth. This study highlights the importance of taking economic considerations into account when adopting policies and strategies to combat the spread of COVID-19 and how different institution management cultures lead to different outcomes.

The effectiveness of travel restriction measures in alleviating the COVID-19 epidemic: evidence from Shenzhen, China

With the expansion of the global novel coronavirus disease (COVID-19) pandemic, unprecedented interventions have been widely implemented in many countries, including China. In view of this scenario, this research aims to explore the effectiveness of population mobility restriction in alleviating epidemic transmission during different stages of the outbreak. Taking Shenzhen, a city with a large immigrant population in China, as a case study, the real-time reproduction number of COVID-19 is estimated by statistical methods to represent the dynamic spatiotemporal transmission pattern of COVID-19. Furthermore, migration data between Shenzhen and other provinces are collected to investigate the impact of nationwide population flow on near-real-time dynamic reproductive numbers. The results show that traffic flow control between populated cities has an inhibitory effect on urban transmission, but this effect is not significant in the late stage of the epidemic spread in China. This finding implies that the government should limit international and domestic population movement starting from the very early stage of the outbreak. This work confirms the effectiveness of travel restriction measures in the face of COVID-19 in China and provides new insight for densely populated cities in imposing intervention measures at various stages of the transmission cycle.

High-speed railway and the intercity transmission of epidemics: Evidence from COVID-19 in China

In the context of the COVID-19 outbreak in Wuhan, we investigate the effect of intercity high-speed railway (HSR) connections on intercity transmission of epidemics in the absence of government intervention. Intercity HSR connections increase the number of COVID-19 patients per 10,000 population by 0.029, accounting for 45% of the total infections. Our results remain intact in several robustness assessments. The total economic loss owing to HSR connections to Wuhan is estimated to be USD 0.62 billion. The internal mechanism demonstrates that intercity HSR connections increase intercity COVID-19 transmission by facilitating human mobility between cities. Based on intercity transportation connections, our findings can help the government predict the direction and scope of virus transmission and control the intercity transmission of epidemics.

Bibliometric analysis for economy in COVID-19 pandemic

Since the outbreak of COVID-19, various fields have been damaged to varying degrees, especially in the economic field. According to a comprehensive study of bibliometrics and content analysis, this paper aims at summarizing studies related to the development of the economic field during the COVID-19 epidemic. We search in Web of Science Core Collection using the subjects such as "economics", "economy", "economic", "financial", and then 2274 related documents are collected, which are published from 2020 to 2022. First, this paper uses the mixed qualitative and quantitative analysis methods to analyze the publication status of the countries, institutions, and authors, respectively, and conducts the document co-citation analysis by CiteSpace software. The results showed that the most popular journal is Sustainability, and the most productive research institutions, countries, and authors are primarily located in North American and European countries. Then, it makes an in-depth study of the cooperative network. With the support of Gephi software, this paper employs the social network analysis method to analyze the situation of the country/region cooperation and institutional cooperation. Finally, the content analysis of the related studies is presented to further explore the current challenges. On this basis, this paper analyzes the economic development in the post-epidemic era and draws some conclusions, which provide some references for scholars interested in this field.

The economic damage of COVID-19 on regional economies: an application of a spatial computable general equilibrium model to South Korea

We developed a spatial computable general equilibrium model of South Korea to assess the spatial spillover effects of the COVID-19 pandemic on South Korea's regional economic growth patterns. The model measures a wide range of economic losses, including human health costs at the city and county level, through an analysis of regional producers' profit maximization on the supply side and regional households' utility maximization on the demand side. The model's findings showed that if the level of spatial interaction decreases by 10% as a result of social distancing policies, the national gross domestic product drops by 0.815-0.864%. This loss in economic growth can be further decomposed into 0.729% loss in agglomeration effect, 0.080-0.130% loss in health effect associated with medical treatment and premature mortality, and 0.005% loss in labor effect. The results of the models and simulations shed light on not only the epidemiological effects of social distancing interventions, but also their resultant economic consequences. This ex-ante evaluation of social distancing measures' effects can serve as a guide for future policy decisions made at both the national and regional level, providing policymakers with the tools for tailored solutions that address both regional economic circumstances and the spatial distribution of COVID-19 cases.

Tempo-Spatial Modelling of the Spread of COVID-19 in Urban Spaces

The relationship between the social structure of urban spaces and the evolution of the COVID-19 pandemic is becoming increasingly evident. Analyzing the socio-spatial structure in relation to cases may be one of the keys to explaining the ways in which this contagious disease and its variants spread. The aim of this study is to propose a set of variables selected from the social context and the spatial structure and to evaluate the temporal spread of infections and their different degrees of intensity according to social areas. We define a model to represent the relationship between the socio-spatial structure of the urban space and the spatial distribution of pandemic cases. We draw on the theory of social area analysis and apply multivariate analysis techniques to check the results in the urban space of the city of Malaga (Spain). The proposed model should be considered capable of explaining the functioning of the relationships between societal structure, socio-spatial segregation, and the spread of the pandemic. In this paper, the study of the origins and consequences of COVID-19 from different scientific perspectives is considered a necessary approach to understanding this phenomenon. The personal and social consequences of the pandemic have been exceptional and have changed many aspects of social life in urban spaces, where it has also had a greater impact. We propose a geostatistical analysis model that can explain the functioning of the relationships between societal structure, socio-spatial segregation, and the temporal evolution of the pandemic. Rather than an aprioristic theory, this paper is a study by the authors to interpret the disparity in the spread of the pandemic as shown by the infection data.

Individualism Versus Collectivism and the Early-Stage Transmission of COVID-19

We propose a perspective based on the individualism versus collectivism (IC) cultural distinction to understand the diverging early-stage transmission outcomes of COVID-19 between countries. Since individualism values personal freedom, people in such cultures would be less likely to make the collective action of staying at home and less likely to support compulsory measures. As a reaction to the public will, governments of individualistic societies would be more hesitant to take compulsory measures, leading to the delay of necessary responses. With processed COVID-19 data that can provide a fair comparison, we find that COVID-19 spread much faster in more individualistic societies than in more collectivistic societies. We further use pronoun drop and absolute latitude as the instruments for IC to address reverse causality and omitted variable bias. The results are robust to different measures. We propose to consider the role of IC not only for understanding the current pandemic but also for thinking about future trends in the world.

Covid-19, Fiscal Policies, and Small-and-Medium-Sized Firm Survival: Evidence From the Cross-Country Matching Analysis

OBJECTIVE

The present study examines the effect of fiscal policies on firm survival for small-and-medium-sized enterprises in the cross-country level firm-level data.

RESEARCH DESIGN

A propensity score matching analysis is utilised for the post-COVID-19 period firms by using the World Bank Enterprise Follow-up Surveys for the pandemic period. Small-and-medium-sized enterprises are essential to the economy; firm failures can increase in a pandemic.

RESULTS

The obtained findings show that the effect of fiscal policies has an essential effect on small-and-medium-sized enterprises survival in the COVID-19 pandemic period by using a cross-country heterogenous firm-level sample.

CONCLUSIONS

In this context, the present study shed new light on the link between COVID-19-related fiscal policies and small-and-medium-sized firm survival in developing countries.

How Does Government Efficiency Affect Health Outcomes? The Empirical Evidence from 156 Countries

This paper uses the unbalanced panel data of 156 countries during the period of 2002 to 2018 to explore the possible impact of government efficiency on health outcomes. Firstly, we used the fixed-effect model to examine the relationship between government efficiency and health outcomes and found that the increase in government efficiency can significantly improve health outcomes. Then, a series of robustness checks were carried out, which confirmed the reliability of the above result. Thirdly, this paper conducted a heterogeneity analysis from the perspective of life cycle. Fourthly, this paper investigated the mechanisms of the impact of government efficiency on health outcomes from the perspectives of economic growth, health innovation, education and corruption control. Finally, this paper studied the moderating effects of the ruling party’s ideology and democracy on the relationship between government efficiency and health outcomes. The findings of this study provide some references for governments to improve health outcomes.

International Trade of Masks and COVID-19 Pandemic Containment

This study analyzes the impact of the exports of China's masks and other antivirus supplies on the people from the importing countries who are subject to the severe pandemic during the coronavirus disease 2019 (COVID-19) pandemic. Our main data include the COVID-19 cases data of countries around the world published by Johns Hopkins University and the data of China's exports of masks or other antivirus supplies to these countries from the Chinese Customs Database. Using cross-sectional data of about 180 countries and multiple regression analysis, we find that the antivirus supplies from China have played an important role in combating the COVID-19 pandemic. Specifically, China's masks are shipped to countries around the world, and these masks can improve the recovery rate and protect people against the COVID-19 pandemic. Our findings are relevant to global efforts in the COVID-19 pandemic containment.

Artificial intelligence against the first wave of COVID-19: evidence from China

BACKGROUND

The COVID-19 pandemic unexpectedly broke out at the end of 2019. Due to the highly contagious, widespread, and risky nature of this disease, the pandemic prevention and control has been a tremendous challenge worldwide. One potentially powerful tool against the COVID-19 pandemic is artificial intelligence (AI). This study systematically assessed the effectiveness of AI in infection prevention and control during the first wave of COVID-19 in China.  METHODS: To better evaluate the role of AI in a pandemic emergency, we focused on the first-wave COVID-19 in the period from the early December 2019 to the end of April 2020 across 304 cities in China. We employed three sets of dependent variables to capture various dimensions of the effect of AI: (1) the time to the peak of cumulative confirmed cases, (2) the case fatality rate and whether there were severe cases, and (3) the number of local policies for work and production resumption and the time span to having the first such policy. The main explanatory variable was the local AI development measured by the number of AI patents. To fit the features of different dependent variables, we employed a variety of estimation methods, including the OLS, Tobit, Probit, and Poisson estimations. We included a large set of control variables and added interaction terms to test the mechanisms through which AI took an effect.

RESULTS

Our results showed that AI had highly significant effects on (1) screening and detecting the disease, and (2) monitoring and evaluating the epidemic evolution. Specifically, AI was useful to screen and detect the COVID-19 in cities with high cross-city mobility. Also, AI played an important role for production resumption in cities with high risk to reopen. However, there was limited evidence supporting the effectiveness of AI in the diagnosis and treatment of the disease.

CONCLUSIONS

These results suggested that AI can play an important role against the pandemic.

Dynamic Demand Evaluation of COVID-19 Medical Facilities in Wuhan Based on Public Sentiment

Medical facilities are an important part of urban public facilities and a vital pillar for the survival of citizens at critical times. During the rapid spread of coronavirus disease (COVID-19), Wuhan was forced into lockdown with a severe shortage of medical resources and high public tension. Adequate allocation of medical facilities is significant to stabilize citizens’ emotions and ensure their living standards. This paper combines text sentiment analysis techniques with geographic information system (GIS) technology and uses a coordination degree model to evaluate the dynamic demand for medical facilities in Wuhan based on social media data and medical facility data. This study divided the epidemic into three phases: latent, outbreak and stable, from which the following findings arise: Public sentiment changed from negative to positive. Over half of the subdistricts in three phases were in a dysfunctional state, with a circular distribution of coordination levels decreasing from the city center to the outer. Thus, when facing major public health emergencies, Wuhan revealed problems of uneven distribution of medical facilities and unreasonable distribution of grades. This study aims to provide a basis and suggestions for the city to respond to major public health emergencies and optimize the allocation of urban medical facilities.

Impact of COVID-19 on trade in services

During past shocks (e.g., the 2008-2009 global financial crisis), the services trade was found to be more resilient than the goods trade; however, the ongoing novel coronavirus (COVID-19) pandemic has restricted cross-border mobility, which is disastrous to the services trade because it often requires physical proximity between suppliers and consumers. We empirically examined the impact of COVID-19 on the services trade using quarterly data from 146 countries in 2019 and 2020. Its severity is measured according to the number of cases, the number of deaths, and an index measuring the severity of lockdown orders. We found that the pandemic had a more significantly negative impact on the services trade than the goods trade, particularly on the import side. Moreover, the extent of the impact varied among disaggregated services sectors, reflecting the nature of services. Travel services were the most severely affected, followed by transport and construction services, which are largely related to the international movement of people and goods. On the other hand, other services typically provided as cross-border supply, including computer services, experienced almost no significant effect.

Credit constraints and the severity of COVID-19 impact: Empirical evidence from enterprise surveys

The COVID-19 pandemic decreases firm revenue and raises the demand for liquidity, resulting in increased financial stress for firms throughout the world. In attempts to mitigate the impact of the COVID-19 crisis, governments have established a range of credit programs to provide credit to firms with poor liquidity. However, the efficacy of those relief programs has been low, and the relief funds do not reach the businesses most in need of liquidity injection, indicating a need to identify firms that are the most vulnerable during the crisis. We first combine the standard Enterprises Surveys and the follow-up surveys on the economic consequences of the COVID-19 pandemic. The sample firms are used to test how credit constraint conditions and firm characteristics affect the severity of the COVID-19 impact on firm performance. Our empirical results indicate that small firms and firms with limited access to finance are more likely to be severely affected by the crisis. Firms with foreign ownership and that are located in small cities are less at-risk. Compared to the 2008 Global Financial Crisis, COVID-19 less severely affects credit-constrained firms and foreign-owned firms and more severely affects small and medium-sized enterprises (SMEs).

Cities in the epidemic, the epidemic in cities: Reconstruction of COVID-19 development in Polish cities

The Covid-19 pandemic, with its epicentres in cities, came as the most severe social, economic and financial shock of the 21st century. The reconstruction of the pandemic spread in cities, the determination of factors conducive to and preventing from SARS-CoV-2 virus infections as well as searching for the ways to combat it and its effects have become the subject of many studies and analyses. The results presented in this article are part of this research. The study covered 20 large Polish cities with different functions, in the set of which: (1) the course of the infection process (by means of a rarely used trajectory method) was determined as well as its temporal variation (variance), (2) cities were classified in terms of the similarity of the epidemic process (correlation analysis), and (3) the factors conducive to infections presented in the literature (using a multivariate regression method) were verified. In this case the investigation was also carried out on the set of 66 large cities. Generally, the relative number of infections (per 10,000 inhabitants), i.e. the intensity of infections, was used as the basis for the analysis. The research has shown that the size, function and location within the country have no influence on the course and intensity of the epidemic in particular cities. Unfortunately, it was not possible to identify factors that could be responsible for infections, or at least that could determine the risk of infections (no confirmed impact on infections of population density, the level of poverty, the proportion of a post-working age population or the level of people's health). Thus, the obtained results testify to the individual nature of the spread of the epidemic in each city and to the possible influence of other explanatory features on the infection level than those considered in this investigation, or to the level of infections as the effect of the synergetic interaction of more than just socio-economic features. The solution to this issue remains open, as it seems, not only in the case of Polish cities.

Key links in network interactions: Assessing route-specific travel restrictions in China during the Covid-19 pandemic

We consider a model of network interactions where the outcome of a unit depends on the outcomes of the connected units. We determine the key network link, i.e., the network link whose removal results in the largest reduction in the aggregate outcomes, and examine a measure that quantifies the contribution of a network link to the aggregate outcomes. We provide an example examining the spread of Covid-19 in China. Travel restrictions were imposed to limit the spread of infectious diseases. As uniform restrictions can be inefficient and incur unnecessarily high costs, we examine the design of restrictions that target specific travel routes. Our approach may be generalized to multiple countries to guide policies during epidemics ranging from ex ante route-specific travel restrictions to ex post health measures based on travel histories, and from the initial travel restrictions to the phased reopening.

Assessing urban resilience to public health disaster using the rough analytic hierarchy process method: A regional study in China

In the context of frequent occurrences of disasters worldwide, disaster-coping capability is imperative for risk reduction and contemporary emergency management. The global COVID-19 pandemic since 2020 has further highlighted the significance of resilience construction at different geographical scales. Overall, the conceptual cognition of resilience in disaster management covers multiple elements and has diverse yielding on regional assessment. This study assesses the local resilience to the public health disaster in the prefecture-level cities, focusing on two dimensions consisting of vulnerability and capability in the targeted provincial region of Jiangsu in China. To this end, based on the vulnerability-capability framework, the Rough Analytic Hierarchy Process (Rough AHP) method was applied to the resilience assessment. Drawing upon the criteria derived from literature, the criteria weights were determined with the RAHP method and we assessed urban resilience with census data. In addition, the hierarchical factors contributing to urban resilience were determined using robustness analysis. This research provides constructive ideas for regional disaster reduction and contributes to the government's capability to improve urban resilience.

Symptoms of psychological distress amongst women during the COVID-19 pandemic in Saudi Arabia

BACKGROUND

Since the emergence of the COVID-19 pandemic in early 2020, several countries are still struggling to contain its spread. Apart from economic challenges, the pandemic has had a negative impact on the mental health and psychological well-being of millions of people worldwide. The effects of COVID-19 are disproportionate depending on sociodemographic characteristics. The aim of this study was to investigate the impact of COVID-19 on psychological distress among women in Saudi Arabia.

METHODS

Data were extracted from an online cross-sectional self-reported questionnaire conducted to measure symptoms of psychological distress during the COVID-19 pandemic in Saudi Arabia from 3 May to 8 May 2020. The study included a sample of 1527 women. The questionnaire was based on the COVID-19 Peritraumatic Distress Index (CPDI) tool to categorise women who responded to the questionnaire as experiencing normal, mild, or severe levels of distress. Sociodemographic factors related to different levels of psychological distress among women were examined using descriptive analysis and multinomial logistic regression models.

RESULTS

Overall, 44% of the respondents indicated symptoms of psychological distress due to the COVID-19 pandemic. Approximately 36% of women showed symptoms of mild psychological distress, with 8% of women experiencing a severe distress level. The results also revealed particularly high levels of psychological distress among younger women and female healthcare workers.

CONCLUSION

The COVID-19 pandemic highly contributes to psychological distress among women in Saudi Arabia. Therefore, it is essential to establish medium- and long-term strategies that target the most vulnerable women affected by the COVID-19 pandemic.

Modelling changing patterns in the COVID‐19 geographical distribution: Madrid’s case

We analyse the transmission factors shaping the spatial distribution of COVID‐19 infections during the distinct phases of the pandemic’s first wave in Madrid, Spain, by fitting a spatial regression model capturing neighbourhood effects between municipalities. Our findings highlight that factors such as population, mobility, and tourism were instrumental in the days before the national lockdown. As a result, already in the early part of the lockdown phase, a geographical pattern emerged in the spread of the disease, along with the positive (negative) impact of age (wealth) on virus transmission. Thereafter, spatial links between municipalities weakened, as the influences of mobility and tourism were eroded by mass quarantine. However, in the de‐escalation phase, mobility reappeared, reinforcing the geographical pattern, an issue that policymakers must pay heed to. Indeed, a counterfactual analysis shows that the number of infections without the lockdown would have been around 170% higher.

Rethinking urban density, vitality and healthy environment in the post-pandemic city: The case of Istanbul

The present study aims to examine the relationship between urban vitality, healthy environment and density through the city of Istanbul, which is going through the Covid-19 outbreak. In this context, an online survey was conducted to measure the assessments of the residents living in districts with different density categories regarding the neighborhoods and the city they live in. The evaluations made by the citizens in the dimensions of vitality, mobility, safety, healthiness, cleanliness, orderliness were reduced to two main factors as "urban vitality" and "healthy environment" using Principal Components Analysis. Then, the evaluations regarding these six variables and two factors were subjected to cross-inquiries with the personal, residential and district characteristics. Urban residents were also asked to evaluate the city life before and after the Covid-19 outbreak. The main findings of the study reveal that there is a statistically significant difference between the density levels of the districts in terms of the perception of urban vitality and some sub-variables of healthy environment. Also, there is an observed change in the thoughts about urban life in Istanbul due to the outbreak.

A Review on Building Design as a Biomedical System for Preventing COVID-19 Pandemic

Sustainable design methods aim to obtain architectural solutions that assure the coexistence and welfare of human beings, inorganic structures, and living things that constitute ecosystems. The novel coronavirus emergence, inadequate vaccines against the present severe acute respiratory syndrome-coronavirus-(SARS-CoV-2), and increases in microbial resistance have made it essential to review the preventative approaches used during pre-antibiotic periods. Apart from low carbon emissions and energy, sustainable architecture for facilities, building designs, and digital modeling should incorporate design approaches to confront the impacts of communicable infections. This review aims to determine how architectural design can protect people and employees from harm; it models viewpoints to highlight the architects’ roles in combating coronavirus disease 2019 (COVID-19) and designing guidelines as a biomedical system for policymakers. The goals include exploring the hospital architecture evolution and the connection between architectural space and communicable infections and recommending design and digital modeling strategies to improve infection prevention and controls. Based on a wide-ranging literature review, it was found that design methods have often played important roles in the prevention and control of infectious diseases and could be a solution for combating the wide spread of the novel coronavirus or coronavirus variants or delta.

Factors Associated With the Health and Economic Effects of the COVID-19 Pandemic in the Peruvian Textile Sector, 2020-2021

The article identifies the factors associated with the health and economic effects of the COVID-19 pandemic on people working in the textile industry of Lima, Peru, during 2021. The study was conducted in Peru's largest textile emporium, so-called Gamarra. The study design is observational and cross-sectional, with two models with two temporal samples for the first and second waves of the COVID-19 pandemic. The first model measures the chance of getting sick from COVID-19. The second model measures the economic impact by the variations in incomes. Inferential statistics are employed, using the chi-square test. The p-value (p < 0.05) is evaluated to decide the statistical significance of the variables. Of 820 workers included, 48% work in street trading, 45% are ≤ 35 years of age and 15% are foreign migrants. Logistic regression analysis for the first model reveals an association between infection by a family member, people breaking quarantine, foreign nationality, not having hygienic services and having a chronic disease, with the highest probability of COVID-19 infection. Regarding economic impact, an association is found between educational level, being ≥45 years of age and infection of a family member, with a greater probability of variation in income.

Evidence of the Relationship between Social Vulnerability and the Spread of COVID-19 in Urban Spaces

Modeling the social-spatial structure of urban spaces can facilitate the development of guidelines aimed at curbing the spread of the COVID-19 pandemic while also acting as an instrument that helps decision-making concerning mitigation policies. The modeling process starts with categorization of urban spaces based on the concept of social vulnerability. A model is created based on this concept and the theory of analysis of social areas. Statistical techniques of factor analysis and geostatistics are applied. This generates a map of social differentiation that, when related to data on the evolution of the contagion, generates a multidimensional model of social vulnerability. The application of this model towards people (social structure) and the environment where they live (spatial structure) is specified. Our model assumes the uniqueness of cities, and it is intended to be a broadly applicable model that can be extrapolated to other urban areas if pertinent revisions are made. Our work demonstrates that aspects of the social and urban structures may be validly used to analyze and explain the spatial spread of COVID-19.

Egyptian Consensus on the Role of Lung Ultrasonography During the Coronavirus Disease 2019 Pandemic

BACKGROUND & AIMS

Coronavirus disease 2019 (COVID-19) is a global health problem, presenting with symptoms ranging from mild nonspecific symptoms to serious pneumonia. Early screening techniques are essential in the diagnosis and assessment of disease progression. This consensus was designed to clarify the role of lung ultrasonography versus other imaging modalities in the COVID-19 pandemic.

METHODS

A multidisciplinary team consisting of experts from different specialties (ie, pulmonary diseases, infectious diseases, intensive care unit and emergency medicine, radiology, and public health) who deal with patients with COVID-19 from different geographical areas was classified into task groups to review the literatures from different databases and generate 10 statements. The final consensus statements were based on expert physically panelists' discussion held in Cairo July 2021 followed by electric voting for each statement.

RESULTS

The statements were electronically voted to be either "agree," "not agree," or "neutral." For a statement to be accepted to the consensus, it should have 80% agreement.

CONCLUSION

Lung ultrasonography is a rapid and useful tool, which can be performed at bedside and overcomes computed tomography limitations, for screening and monitoring patients with COVID-19 with an accepted accuracy rate.

From the lockdown to the new normal: individual mobility and local labor market characteristics following the COVID-19 pandemic in Italy

Italy was among the first countries to introduce drastic measures to reduce individual mobility in order to slow the diffusion of COVID-19. The first measures imposed by the central authorities on March 8, 2020, were unanticipated and highly localized, focusing on 26 provinces. Additional nationwide measures were imposed after one day, and were removed only after June 3. Looking at these watershed moments of the pandemic, this paper explores the impact of the adoption of localized restrictions on changes in individual mobility in Italy using a spatial discontinuity approach. Results show that these measures lowered individual mobility by 7 percentage points on top of the reduction in mobility recorded in the adjacent untreated areas. The study also fills a gap in the literature in that it looks at the changes in mobility after the nationwide restrictions were lifted and shows how the recovery in mobility patterns is related to various characteristics of local labour markets. Areas with a higher proportion of professions exposed to diseases, more suitable for flexible work arrangements, and with a higher share of fixed-term contracts before the pandemic are characterised by a smaller increase in mobility after re-opening.

Perspectives on factors influencing transmission of COVID-19 in Zambia: a qualitative study of health workers and community members

OBJECTIVE

To explore the health professionals' and community members' perspectives on the factors influencing transmission of the novel COVID-19 in Zambia.

DESIGN

An exploratory qualitative study using in-depth interviews as data collection technique.

SETTING

Four primary healthcare facilities and local communities of Lusaka city and Chirundu international border town under Lusaka province, Zambia.

PARTICIPANTS

Purposive sampling of 60 study participants comprising health professionals (n=15) and community members (n=45). Health staff were health inspectors and surveillance officers. Community members included public market traders, civic and religious leaders, immigration officers, bus and international truck drivers.

RESULTS

Both health professionals and community members were aware of the COVID-19 pandemic, the preventive and control measures. Nevertheless, stark differences were observed on the two groups' perspectives on COVID-19 and the factors influencing its transmission. Most health staff expressed high personal risk and susceptibility to the disease and a positive attitude towards the prevention and control measures. Conversely, myths and misconceptions influenced most community members' perspectives on the disease and their attitude towards the COVID-19 guidelines. Participants were unanimous on the low levels of adherence to the COVID-19 preventive and control measures in the community. Reasons for non-adherence included limited information on COVID-19, negative attitude towards COVID-19 guidelines, social movement and travel patterns, networks and interactions, living and work conditions, water and sanitation facilities, and observation of behaviours of important role models such as politicians and other community leaders. These factors were perceived to increase the risk of COVID-19 transmission.

CONCLUSION

These findings highlight important factors influencing transmission of COVID-19 in Zambia. Future interventions should focus on providing information to mitigate myths and misconceptions, increasing people's risk perception to the disease, and improving attitude towards the prevention and control interventions and mitigating structural and socioeconomic barriers.

How the COVID-19 pandemic affects job sentiments of rural teachers

This study investigates how the COVID-19 pandemic has affected teachers' job-specific stresses and their enthusiasm for the teaching occupation. We use unique data from China that cover the periods before and after the start of the pandemic and apply various estimation methods. We find that, among rural young teachers, the pandemic has caused higher teaching stress and career development stress and has reduced passion toward the teaching occupation. We investigate the working channels of the pandemic, including changes in job-related activities and social network. After controlling for possible working channels, the COVID-19 pandemic still shows a strong direct impact on job sentiments.

Dynamic governance of the first wave of Covid-19 in Tunisia: An interoperability analysis

This study proposes an interoperability index of the measures taken by the Tunisian government during the first wave of the coronavirus disease 2019 (COVID‐19) pandemic. In the first part, we present the process of decision making as a revised and adjusted process in continuous upgrading, based on the dynamic governance process in times of crisis. In the second part, we estimate an index that records the strictness of government policies in each subperiod and the degree of interoperability between the Tunisian pandemic responses against COVID‐19 using subperiod instantiations. Our empirical findings show that the pandemic management strategy in Tunisia during the first wave was adjusted by incorporating new pandemic policies and changing the stringency levels over time. After estimating the interoperability index, we found that the measures taken early in a subperiod interact directly with the next successive subperiod in the decision process, but they interact indirectly with other successive subperiods.

The pandemic management strategy in Tunisia during the first wave has been adjusted by incorporating new pandemic policies and changing the stringency levels over time.

Tunisia has reached the highest level of the strictness of government policies, after 18 days of initial responses taken during the first wave in a stepwise manner.

The measures taken early in a subperiod interact directly with the next successive subperiod in the decision‐making process, but they interact indirectly with other successive subperiods.

Pandemic crisis cannot be managed or defeated with a single measure or policy, even at the highest stringency level. Instead, it is managed with several policy responses that interreact together over time.

The establishment of a dynamic and flexible decision‐making process can be useful in managing a future health crisis in countries whose public health systems suffer from several shortcomings.

The impact of 2020 French municipal elections on the spread of COVID-19

Soon after the onset of the COVID-19 pandemic, the French government decided to still hold the first round of the 2020 municipal elections as scheduled on March 15. What was the impact of these elections on the spread of COVID-19 in France? Answering this question leads to intricate econometric issues as omitted variables may drive both epidemiological dynamics and electoral turnout, and as a national lockdown was imposed at almost the same time as the elections. In order to disentangle the effect of the elections from that of confounding factors, we first predict each department's epidemiological dynamics using information up to the election. We then take advantage of differences in electoral turnout across departments to identify the impact of the election on prediction errors in hospitalizations. We report a detrimental effect of the first round of the election on hospitalizations in locations that were already at relatively advanced stages of the epidemic. Estimates suggest that the elections accounted for at least 3,000 hospitalizations, or 11% of all hospitalizations by the end of March. Given the sizable health cost of holding elections during an epidemic, promoting ways of voting that reduce exposure to COVID-19 is key until the pandemic shows signs of abating.

Face Masks to Combat Coronavirus (COVID-19)-Processing, Roles, Requirements, Efficacy, Risk and Sustainability

Increasingly prevalent respiratory infectious diseases (e.g., COVID-19) have posed severe threats to public health. Viruses including coronavirus, influenza, and so on can cause respiratory infections. A pandemic may potentially emerge owing to the worldwide spread of the virus through persistent human-to-human transmission. However, transmission pathways may vary; respiratory droplets or airborne virus-carrying particles can have a key role in transmitting infections to humans. In conjunction with social distancing, hand cleanliness, and other preventative measures, the use of face masks is considered to be another scientific approach to combat ubiquitous coronavirus. Different types of face masks are produced using a range of materials (e.g., polypropylene, polyacrylonitrile, polycarbonate, polyurethane, polystyrene, polyester and polyethylene) and manufacturing techniques (woven, knitted, and non-woven) that provide different levels of protection to the users. However, the efficacy and proper disposal/management of the used face masks, particularly the ones made of non-biodegradable polymers, pose great environmental concerns. This review compiles the recent advancements of face masks, covering their requirements, materials and techniques used, efficacy, challenges, risks, and sustainability towards further enhancement of the quality and performance of face masks.

Government Intervention, Human Mobility, and COVID-19: A Causal Pathway Analysis from 121 Countries

Based on data from 121 countries, the study assesses the dynamic effect and causality path of the government epidemic prevention policies and human mobility behaviors on the growth rates of COVID-19 new cases and deaths. Our results find that both policies and behaviors influenced COVID-19 cases and deaths. The direct effect of policies on COVID-19 was more than the indirect effect. Policies influence behaviors, and behaviors react spontaneously to information. Further, masks give people a false sense of security and increase mobility. The close public transport policy increased COVID-19 new cases. We also conducted sensitivity analysis and found that some policies hold robustly, such as the policies of school closing, restrictions on gatherings, stay-at-home requirements, international travel controls, facial coverings, and vaccination. The counterfactual tests suggest that, as of early March 2021, if governments had mandated masking policies early in the epidemic, the cases and deaths would have been reduced by 18% and 14% separately. If governments had implemented vaccination policies early in the pandemic, the cases and deaths would have been reduced by 93% and 62%, respectively. Without public transportation closures, cases and deaths would have been reduced by 40% and 10%, respectively.

A Literature Review on the Role of Social Determinants in Post-Disaster Public Health

Introduction: Social determinants are closely related to public health disparities, and they affect health both directly and indirectly. Furthermore, social and economic conditions are often associated with a natural disaster that impacts people’s health. Methods: This study used the Pubmed database, Science direct, and Proquest through the keywords “Determinan Sosial; Kesehatan Masyarakat; Pascabencana (Social Determinants; Public Health; Post-Disaster)”. Furthermore, the studies found are open access, not a type of review and were filtered over the last five years. The Pubmed databases found 1308 studies, which were screened based on inclusion and exclusion criteria to obtain a total of 7 studies for review. Result: The role of social support shows a significant effect on a person’s stress symptoms. Moreover, environmental factors play an important role in post-disaster public health. Therefore, policies and countermeasures in disaster recovery need to continuously focus on health issues and social relations in the long term. Conclusion: Social determinants have an important role in post-disaster public health.

The lockdown, mobility, and spatial health disparities in COVID-19 pandemic: A case study of New York City

The world has adopted unprecedented lockdown as the key method to mitigate COVID-19; yet its effect on pandemic outcomes and health disparities remains largely unknown. Adopting a multilevel conceptual framework, this research investigates how city-level lockdown policy and public transit system shape mobility and thus intra-city health disparities, using New York City as a case study. With a spatial method and multiple sources of data, this research demonstrates the uneven impact of the lockdown policy and public transit system in shaping local pandemic outcomes. Census tracts with people spending more time at home have lower infection and death rates, while those with a higher density of transit stations have higher infection and death rates. Residential profile matters and census tracts with a higher concentration of disadvantaged population, such as Blacks, Hispanics, poor and elderly people, and people with no health insurance, have higher infection and death rates. Spatial analyses identify clusters where the lockdown policy was not effective and census tracts that share similar pandemic characteristics. Through the lens of mobility, this research advances knowledge of health disparities by focusing on institutional causes for health disparities and the role of the government through intervention policy and public transit system.

Atmospheric Organic Nitrogen Deposition in Strategic Water Sources of China after COVID-19 Lockdown

Atmospheric nitrogen deposition (AND) may lead to water acidification and eutrophication. In the five months after December 2019, China took strict isolation and COVID-19 prevention measures, thereby causing lockdowns for approximately 1.4 billion people. The Danjiangkou Reservoir refers to the water source in the middle route of South-to-North Water Diversion Project in China, where the AND has increased significantly; thus, the human activities during the COVID-19 period is a unique case to study the influence of AND to water quality. This work monitored the AND distribution around the Danjiangkou Reservoir, including agricultural, urban, traffic, yard, and forest areas. After lockdown, the DTN, DON, and Urea-N were 1.99 kg · hm⁻² · month⁻¹, 0.80 kg · hm⁻² · month⁻¹, and 0.15 kg · hm⁻² · month⁻¹, respectively. The detected values for DTN, DON, and Urea-N in the lockdown period decreased by 9.6%, 30.4%, and 28.97%, respectively, compared to 2019. The reduction in human activities is the reason for the decrease. The urban travel intensity in Nanyang city reduced from 6 to 1 during the lockdown period; the 3 million population which should normally travel out from city were in isolation at home before May. The fertilization action to wheat and orange were also delayed.

Roles of Economic Development Level and Other Human System Factors in COVID-19 Spread in the Early Stage of the Pandemic

We identified four distinct clusters of 151 countries based on COVID-19 prevalence rate from 1 February 2020 to 29 May 2021 by performing nonparametric K-means cluster analysis (KmL). We forecasted future development of the clusters by using a nonlinear 3-parameter logistic (3PL) model, and found that peak points of development are the latest for Cluster I and earliest for Cluster IV. Based on partial least squares structural equation modeling (PLS-SEM) for the first twenty weeks after 1 February 2020, we found that the prevalence rate of COVID-19 has been significantly influenced by major elements of human systems. Better health infrastructure, more restriction of human mobility, higher urban population density, and less urban environmental degradation are associated with lower levels of prevalence rate (PR) of COVID-19. The most striking discovery of this study is that economic development hindered the control of COVID-19 spread among countries in the early stage of the pandemic. Highlights: While richer countries have advantages in health and other urban infrastructures that may alleviate the prevalence rate of COVID-19, the combination of high economic development level and low restriction on human mobility has led to faster spread of the virus in the first 20 weeks after 1 February 2020.

Ordinal Logistic Regression Analysis in Determining Factors Associated with Socioeconomic Status of Household in Tepi Town, Southwest Ethiopia

Background

Socioeconomic status (SES) refers to an individual's or group's social position or class, which is often determined by a combination of education, income, and occupation. Knowing factors that affect the SES of the society might help to take action and improve their economy. In addition, using an ordinal logistic regression model for ordered SES outcomes will yield suitable results and conclusions. This study aimed to utilize an ordinal logistic regression model to find the factors associated with SES for households in Tepi town, Southwest Ethiopia.

Methods

The community-based cross-sectional study was carried out in Tepi town, southwest Ethiopia, with data collected from 382 households using a simple random sample technique. The ordinal logistic regression models were evaluated and contrasted for proper accounting of ordinal form. In addition, to come up with a better model, we compared fitted ordinal logistic models with the likelihood-ratio test and AIC criteria. We performed data analysis using STATA version 16.

Results

Of all 382 household heads, 170 (45.5%), 120 (31.4%), and 92 (24.1%) were at low, medium, and high SES of households, respectively. According to the result of the multivariable, partial proportional odds model (PPOM), age, education level, family size, and the saving habit were significantly associated with the SES of households at a 5% level of significance.

Conclusions

According to the findings of this study, ordinal regression may be a better option in the event of the ordinal form of the outcome. Furthermore, PPOM may be a preferable option if any of the covariates violate the proportionality requirement. Based on the result of this study, the most likely associated indicators with the SES of families in Tepi town, southwest Ethiopia, were family size, age, saving habit, and education level. It is recommended that action should be taken to improve the SES of households.

Urban-rural lifespan disparities and cause-deleted analysis: evidence from China

OBJECTIVES

To examine the length and dispersion level of lifespan for the subnational populations in China, identify the urban-rural gap and sex differences, and analyse the contribution made by causes of death.

SETTING

Cause-specific mortality data extracted from the Chinese Disease Surveillance Points system, grouped by sex and urban/rural residence.

PRIMARY OUTCOME MEASURES

Life expectancy and lifespan disparity are used to measure the length and dispersion level of lifespan, respectively. Cause-specific contributions are obtained by contrasting cause-deleted life expectancy and lifespan disparities with observed values.

PARTICIPANTS

Aggregated national data gathered from over 605 surveillance points across China, covering over 264 million people by 2016 (about 19.14% of the total Chinese population).

RESULTS

In the decade under observation, all subpopulations in China, by area and sex, experienced increases in life expectancy and decreases in lifespan disparity, while causes of deaths contributed differently. For example, based on the 2016 data, if cardiovascular diseases were deleted, there would be an increase in life expectancy that ranges from 5.59 years for urban males to 6.69 years for rural females. However, also lifespan disparity would increase, ranging from 0.81 years for urban females to 1.37 years for rural males.

CONCLUSIONS

In China, the urban-rural gaps in both life expectancy and lifespan disparity are shrinking as the rural residents are catching up fast, while the gender gaps remain large, and even widening. Causes of death with different age distribution patterns contribute differently to the level and direction of the urban-rural and sex differentials in life expectancy and lifespan disparity. Sex differentials were observed in cardiovascular diseases, respiratory diseases, lung and liver cancers, and external causes, while urban-rural differences were found in lung and breast cancers, and external causes.

Spatial Dynamics and Multiscale Regression Modelling of Population Level Indicators for COVID-19 Spread in Malaysia

As COVID-19 dispersion occurs at different levels of gradients across geographies, the application of spatiotemporal science via computational methods can provide valuable insights to direct available resources and targeted interventions for transmission control. This ecological-correlation study evaluates the spatial dispersion of COVID-19 and its temporal relationships with crucial demographic and socioeconomic determinants in Malaysia, utilizing secondary data sources from public domains. By aggregating 51,476 real-time active COVID-19 case-data between 22 January 2021 and 4 February 2021 to district-level administrative units, the incidence, global and local Moran indexes were calculated. Spatial autoregressive models (SAR) complemented with geographical weighted regression (GWR) analyses were executed to determine potential demographic and socioeconomic indicators for COVID-19 spread in Malaysia. Highest active case counts were based in the Central, Southern and parts of East Malaysia regions of Malaysia. Countrywide global Moran index was 0.431 (p = 0.001), indicated a positive spatial autocorrelation of high standards within districts. The local Moran index identified spatial clusters of the main high–high patterns in the Central and Southern regions, and the main low–low clusters in the East Coast and East Malaysia regions. The GWR model, the best fit model, affirmed that COVID-19 spread in Malaysia was likely to be caused by population density (β coefficient weights = 0.269), followed by average household income per capita (β coefficient weights = 0.254) and GINI coefficient (β coefficient weights = 0.207). The current study concluded that the spread of COVID-19 was concentrated mostly in the Central and Southern regions of Malaysia. Population’s average household income per capita, GINI coefficient and population density were important indicators likely to cause the spread amongst communities.

Role of professionalism in response to the COVID-19 pandemic: Does a public health or medical background help?

In response to the outbreak of coronavirus disease 2019 (COVID-19), there have been substantial variations in policy response and performance for disease control and prevention within and across nations. It remains unclear to what extent these variations may be explained by bureaucrats' professionalism, as measured by their educational background or work experience in public health or medicine. To investigate the effects of officials' professionalism on their response to and performance in fighting the COVID-19 pandemic, we collect information from the résumés of government and Party officials in 294 Chinese cities, and integrate this information with other data sources, including weather conditions, city characteristics, COVID-19-related policy measures, and health outcomes. We show that, on average, cities whose top officials had public health or medical backgrounds (PHMBGs) had a significantly lower infection rate than cities whose top officials lacked such backgrounds. We test the mechanisms of these effects and find that cities whose officials had a PHMBG implemented community closure more rapidly than those lacked such backgrounds. Our findings highlight the importance of professionalism in combating the pandemic.

The impact of lockdown on air pollution: Evidence from an instrument

This paper studies the impact of lockdown measures in response to the outbreak of COVID-19 on a prefecture's air pollution in China. To avoid potential endogenous problems, we exploit the bilateral population flow from the Baidu Migration Index to predict prefectures' probability to undertake lockdown measures. Our results using difference-in-differences with the instrumental variable show that a prefecture's lockdown measures significantly reduce its air quality index (AQI) by around 35%, and yet the result for difference-in-differences with OLS is only around 11%. We also find that a prefecture under lockdown reduces its PM 10 and PM 2.5 by around 25% and 35% respectively, and the results of diff-in-diff with OLS are only around 11% and 12%. The sharp difference between these two approaches seems to imply that there is a strong heterogeneity in lockdown stringency across prefectures.

"The better you feel, the harder you fall": Health perception biases and mental health among Chinese adults during the COVID-19 pandemic

The health risks of the current COVID-19 pandemic, together with the drastic mitigation measures taken in many affected nations, pose an obvious threat to public mental health. To assess predictors of poor mental health in the context of the COVID-19 pandemic, this study first implements survey-based measures of health perception biases among Chinese adults during the pandemic. Then, it analyzes their relation to three mental health outcomes: life satisfaction, happiness, and depression (as measured by the CES-D). We show that the health overconfidence displayed by approximately 30% of the survey respondents is a clear risk factor for mental health problems; it is a statistically significant predictor of depression and low levels of happiness and life satisfaction. We also document that these effects are stronger in regions that experienced higher numbers of confirmed COVID-19 cases and deaths. Our results offer clear guidelines for the implementation of effective interventions to temper health overconfidence, particularly in uncontrollable situations like the COVID-19 pandemic.

Regional poverty and infection disease: early exploratory evidence from the COVID-19 pandemic

This paper examines the role of regional poverty on the COVID-19 pandemic in the USA. It also explores how the effects differ with the concentration of ethnic minorities. We find that poverty is a significant and consistent determinant of higher COVID-19 infections and fatalities. Prevalent poverty areas experienced higher infections due to economic structure that require hypermobility (high mobility and interpersonal interaction)-more physical human to human contact resulting in higher deaths from limited access to health services. These are also regions where minority groups are concentrated. Disproportionate infections and fatalities occurred within the black, Hispanic, and Asian population. Our evidence is robust to state fixed effects that capture local COVID-19 mitigation policies, multi-level hierarchical modeling, spatial autoregressive assessment, and large sets of county-level health, social, and economic factors. This paper contributes to the literature on health and economic disparities and their resulting consequences for infectious diseases.

Vulnerability to COVID-19 in Pernambuco, Brazil: A geospatial evaluation supported by multiple-criteria decision aid methodology

The paper presents an innovative application to identify areas vulnerable to coronavirus disease 2019 (COVID-19) considering a combination of spatial analysis and a multi-criteria learning approach. We applied this methodology in the state of Pernambuco, Brazil identifying vulnerable areas by considering a set of determinants and risk factors for COVID-19, including demographic, economic and spatial characteristics and the number of human COVID-19 infections. Examining possible patterns over a set number of days taking the number of cases recorded, we arrived at a set of compatible decision rules to explain the relation between risk factors and COVID-19 cases. The results reveal why certain municipalities are critically vulnerable to COVID-19 highlighting locations for which knowledge can be gained about environmental factors.

Developmental Trend of Subjective Well-Being of Weibo Users During COVID-19: Online Text Analysis Based on Machine Learning Method

Currently, the coronavirus disease 2019 (COVID-19) pandemic experienced by the international community has increased the usage frequency of borderless, highly personalized social media platforms of all age groups. Analyzing and modeling texts sent through social media online can reveal the characteristics of the psychological dynamic state and living conditions of social media users during the pandemic more extensively and comprehensively. This study selects the Sina Weibo platform, which is highly popular in China and analyzes the subjective well-being (SWB) of Weibo users during the COVID-19 pandemic in combination with the machine learning classification algorithm. The study first invokes the SWB classification model to classify the SWB level of original texts released by 1,322 Weibo active users during the COVID-19 pandemic and then combines the latent growth curve model (LGCM) and the latent growth mixture model (LGMM) to investigate the developmental trend and heterogeneity characteristics of the SWB of Weibo users after the COVID-19 outbreak. The results present a downward trend and then an upward trend of the SWB of Weibo users during the pandemic as a whole. There was a significant correlation between the initial state and the development rate of the SWB after the COVID-19 outbreak (r = 0.36, p < 0.001). LGMM results show that there were two heterogeneous classes of the SWB after the COVID-19 outbreak, and the development rate of the SWB of the two classes was significantly different. The larger class (normal growth group; n = 1,229, 93.7%) showed a slow growth, while the smaller class (high growth group; n = 93, 6.3%) showed a rapid growth. Furthermore, the slope means across the two classes were significantly different (p < 0.001). Therefore, the individuals with a higher growth rate of SWB exhibited stronger adaptability to the changes in their living environments. These results could help to formulate effective interventions on the mental health level of the public after the public health emergency outbreak.

Reopening schools in a context of low COVID-19 contagion: consequences for teachers, students and their parents

Knowing how school reopenings affect the spread of COVID-19 is crucial when balancing children's right to schooling with contagion management. This paper considers the effects on COVID-19 testing prevalence and the positive test rate of reopening Norwegian schools after a 6-week closure aimed at reducing contagion. We estimate the effects of school reopening on teachers, parents and students using an event study/difference-in-differences design that incorporates comparison groups with minimal exposure to in-person schooling. We find no evidence that COVID-19 incidence increased following reopening among students, parents or teachers pooled across grade levels. We find some suggestive evidence that infection rates among upper secondary school teachers increased; however, the effects are small and transitory. At low levels of contagion, schools can safely be reopened when other social distancing policies remain in place.

Estimating the Economic Effects of the Early Covid-19 Emergency Response in Cities Using Intracity Travel Intensity Data

In the early days of the Covid-19 pandemic, China implemented the most stringent and serious emergency response. To understand the effect of such an emergency response strategy on the economic system, this study proposed a simultaneous overall estimation method using intracity travel intensity data. The overall effect is represented by the difference between intracity travel intensity with and without the emergency response. Using historical data and time series analysis, we compared intracity travel intensity post China’s implementation of the emergency response with predicted intracity travel intensity without such a response. The loss rates, defined by the proportion of intracity travel intensity loss, were calculated for 360 cities within 33 provincial-level regions in China based on data availability. We found that 30 days after the emergency response, 21% of the cities saw over 80% recovery and 10% of the cities showed more than 90% recovery; 45 days after the emergency response, more than 83% of the 360 cities witnessed 80% recovery. The correlation between gross domestic production loss rate and travel intensity loss rate was studied quantitatively to demonstrate the representativeness of the intracity travel intensity loss rate. This indicator was also used to analyze the spatial and temporal patterns of the effects on the economy. The results of this study can help us understand the economic effects caused by the early Covid-19 emergency response and the method can be a reference for fast and real-time economic loss estimation to support emergency response decision making under pandemic conditions.

Adesão ao isolamento social na pandemia de Covid-19 entre professores da educação básica de Minas Gerais, Brasil

RESUMO Este estudo teve por objetivo estimar a prevalência da adesão ao isolamento social e verificar os fatores associados, durante a pandemia de Covid-19, entre professores de Minas Gerais, Brasil. Trata- se de um estudo transversal realizado com uma amostra de 15.641 docentes. Aplicou-se um formulário digital para a coleta dos dados. Foram conduzidas análises descritivas das variáveis, que incluíram adesão ao isolamento social, características sociodemográficas, fatores ocupacionais e condições de saúde au- torrelatadas. Utilizou-se o modelo de regressão de Poisson com variância robusta e se estimaram Razões de Prevalências (RP) com intervalos de 95% de confiança. A prevalência de adesão ao isolamento social foi estimada em 79,8%, cujos fatores associados foram: sexo feminino; faixa etária igual ou superior a 60 anos; viver com o(a) cônjuge; maior carga horária de trabalho; dificuldades no sono; sentimento de tristeza; além de patologias como hipertensão arterial sistêmica, diabetes mellitus, obesidade e doenças respiratórias. Evidenciou-se expressiva prevalência de adesão às medidas de isolamento social entre os docentes, e que a adesão está associada a características sociodemográficas, fatores ocupacionais e condições de saúde dos profissionais da educação.