COVID-19, lockdowns and well-being: Evidence from Google Trends.
Ontology highlight
ABSTRACT:
SUBMITTER: Brodeur A
PROVIDER: S-EPMC7703221 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The spread of COVID-19 and resulting local and national lockdowns have a host of potential consequences for demographic trends. While impacts on mortality and, to some extent, short-term migration flows are beginning to be documented, it is too early to measure actual consequences for family demography. To gain insight into potential future consequences of the lockdown for family demography, we use cross-national Google Trends search data to explore whether trends in searches for words related to fertility, relationship formation, and relationship dissolution changed following lockdowns compared to average, pre-lockdown levels in Europe and the United States. Because lockdowns were not widely anticipated or simultaneous in timing or intensity, we exploit variability over time and between countries (and U.S. states). We use a panel event-study design and difference-in-differences methods, and account for seasonal trends and average country-level (or state-level) differences in searches. We find statistically significant impacts of lockdown timing on changes in searches for terms such as wedding and those related to condom use, emergency contraception, pregnancy tests, and abortion, but little evidence of changes in searches related to fertility. Impacts for union formation and dissolution tended to only be statistically significant at the start of a lockdown with a return to average-levels about 2 to 3 months after lockdown initiation, particularly in Europe. Compared to Europe, returns to average search levels were less evident for the U.S., even 2 to 3 months after lockdowns were introduced. This may be due to the fact, in the U.S., health and social policy responses were less demarcated than in Europe, such that economic uncertainty was likely of larger magnitude. Such pandemic-related economic uncertainty may therefore have the potential to slightly increase already existing polarization in family formation behaviours in the U.S. Alongside contributing to the wider literature on economic uncertainty and family behaviors, this paper also proposes strategies for efficient use of Google Trends data, such as making relative comparisons and testing sensitivity to outliers, and provides a template and cautions for their use in demographic research when actual demographic trends data are not yet available.
| S-EPMC7968661 | biostudies-literature
Project description:Using two novel online surveys collected in May and November 2020, we study the consequences of the COVID-19 pandemic on Spanish households. We document a large and negative effect on household income. By May 2020, the average individual lived in a household that had lost 16% of their pre-pandemic monthly income. Furthermore, this drop was highly unequal: while households in the richest quintile lost 6.8% of their income, those in the poorest quintile lost 27%. We also document that the pandemic deepened the gender-income gap: on average, women experienced a three-percentage point larger income loss than men. While this is consistent with previous findings in the literature, in this paper we document that this effect is driven by women from middle-income households with kids. Finally, we provide evidence that Spanish individuals experienced moderate declines in their levels of psychological well-being. This effect is not different for individuals living in rich or poor households, but the reasons behind well-being losses do differ: richer individuals are more concerned about loss of contact with dear ones, while low-income individuals are more likely to mention loss of income and employment as a key source of emotional distress.
| S-EPMC8576792 | biostudies-literature
Project description:Strict lockdowns have been employed by many of the world's nations as a public health response to COVID-19. However, concerns have been expressed as to how such public health responses disturb the human ecosystem. In this paper, we report on findings from a longitudinal study of Australian parents in which we investigated how state differences in government-mandated lockdowns affect the relationship well-being (i.e., relationship satisfaction and loneliness) of parents. We situated the study of the relational effects of strict lockdowns within the Vulnerability Stress Adaptation Model (VSAM, Karney & Bradbury, 1995) that considers the role of parents' pre-existing vulnerabilities (i.e., psychological distress and attachment insecurity), life stressors (pre-pandemic and COVID-19 stressors), and adaptive relationship processes (constructive communication and perceived partner support). A total of 1942 parents completed 14 waves of assessments of relationship satisfaction and loneliness over a 13.5-month period as well as baseline assessments of personal vulnerabilities, life stressors, and adaptive relationship processes. Parents with high relationship adaptations and low vulnerabilities evidenced the highest relationship well-being (i.e., high satisfaction and low loneliness) during changes in lockdown restrictions, while parents with moderate relationship adaptations and vulnerabilities experienced the poorest well-being. Differences in state lockdown restrictions (i.e., Victoria [long and strict lockdown policy] vs all other states) were associated with differences in relationship well-being for parents with high relationship adaptations. Specifically, Victorian parents experienced significant declines in relationship well-being compared to non-Victorian parents. Our findings provide novel insights into how government-mandated social restrictions can disrupt the relational ecology of parents.
| S-EPMC10043525 | biostudies-literature
Project description:BackgroundThe outbreak of coronavirus disease 2019 (COVID-19) has posed stress on the health and well-being of both Chinese people and the public worldwide. Global public interest in this new issue largely reflects people's attention to COVID-19 and their willingness to take precautionary actions. This study aimed to examine global public awareness of COVID-19 using Google Trends.MethodsUsing Google Trends, we retrieved public query data for terms of "2019-nCoV + SARS-CoV-2 + novel coronavirus?+?new coronavirus + COVID-19 + Corona Virus Disease 2019" between the 31st December 2019 and the 24th February 2020 in six major English-speaking countries, including the USA, the UK, Canada, Ireland, Australia, and New Zealand. Dynamic series analysis demonstrates the overall change trend of relative search volume (RSV) for the topic on COVID-19. We compared the top-ranking related queries and sub-regions distribution of RSV about COVID-19 across different countries. The correlation between daily search volumes on the topic related to COVID-19 and the daily number of people infected with SARS-CoV-2 was analyzed.ResultsThe overall search trend of RSV regarding COVID-19 increased during the early period of observing time and reached the first apex on 31st January 2020. A shorter response time and a longer duration of public attention to COVID-19 was observed in public from the USA, the UK, Australia, and Canada, than that in Ireland and New Zealand. A slightly positive correlation between daily RSV about COVID-19 and the daily number of confirmed cases was observed (P?<?0.05). People across countries presented a various interest to the RSV on COVID-19, and public awareness of COVID-19 was different in various sub-regions within countries.ConclusionsThe results suggest that public response time to COVID-19 was different across countries, and the overall duration of public attention was short. The current study reminds us that governments should strengthen the publicity of COVID-19 nationally, strengthen the public's vigilance and sensitivity to COVID-19, inform public the importance of protecting themselves with enough precautionary measures, and finally control the spread of COVID-19 globally.
| S-EPMC7182392 | biostudies-literature
Project description:We investigate the antecedents of subjective financial well-being and general well-being during the ongoing COVID-19 pandemic. In an online survey conducted in the midst of COVID-19 pandemic with over 1000 Swedish participants we found that distrust in the government to cope with financial (but not healthcare) challenges of the pandemic was negatively related to the feeling of financial security. In a structural equation model, we also show that trust in government to deal with financial challenges of COVID-19 pandemic has a significant impact on general well-being through the mediating channel of financial well-being. In addition, trust in government to deal with healthcare challenges of COVID-19 pandemic has a significant direct impact on individuals' general well-being. Our findings have important implications for public policy as they highlight the importance of citizens' trust in well-functioning governmental institutions to help cope with not only healthcare, but also financial challenges of an ongoing pandemic.
| S-EPMC8444950 | biostudies-literature
Project description:While incomplete non-medical data has been integrated into prediction models for epidemics, the accuracy and the generalizability of the data are difficult to guarantee. To comprehensively evaluate the ability and applicability of using social media data to predict the development of COVID-19, a new confirmed case prediction algorithm improving the Google Flu Trends algorithm is established, called Weibo COVID-19 Trends (WCT), based on the post dataset generated by all users in Wuhan on Sina Weibo. A genetic algorithm is designed to select the keyword set for filtering COVID-19 related posts. WCT can constantly outperform the highest average test score in the training set between daily new confirmed case counts and the prediction results. It remains to produce the best prediction results among other algorithms when the number of forecast days increases from one to eight days with the highest correlation score from 0.98 (P < 0.01) to 0.86 (P < 0.01) during all analysis period. Additionally, WCT effectively improves the Google Flu Trends algorithm's shortcoming of overestimating the epidemic peak value. This study offers a highly adaptive approach for feature engineering of third-party data in epidemic prediction, providing useful insights for the prediction of newly emerging infectious diseases at an early stage.
| S-EPMC8280378 | biostudies-literature
Project description:The Chilean health authorities have implemented a sanitary strategy known as dynamic quarantine or strategic quarantine to cope with the COVID-19 pandemic. Under this system, lockdowns were established, lifted, or prolonged according to the weekly health authorities' assessment of municipalities' epidemiological situation. The public announcements about the confinement situation of municipalities country-wide are made typically on Tuesdays or Wednesdays before noon, have received extensive media coverage, and generated sharp stock market fluctuations. Municipalities are the smallest administrative division in Chile, with each city broken down typically into several municipalities. We analyze social media behavior in response to the confinement situation of the population at the municipal level. The dynamic quarantine scheme offers a unique opportunity for our analysis, given that municipalities display a high degree of heterogeneity, both in size and in the socioeconomic status of their population. We exploit the variability over time in municipalities' confinement situations, resulting from the dynamic quarantine strategy, and the cross-sectional variability in their socioeconomic characteristics to evaluate the impact of these characteristics on social sentiment. Using event study and panel data methods, we find that proxies for social sentiment based on Twitter queries are negatively related (more pessimistic) to increases in the number of confined people, but with a statistically significant effect concentrated on people from the wealthiest cohorts of the population. For indicators of social sentiment based on Google Trends, we found that search intensity during the periods surrounding government announcements is positively related to increases in the total number of confined people. Still, this effect does not seem to be dependent on the segments of the population affected by the quarantine. Furthermore, we show that the observed heterogeneity in sentiment mirrors heterogeneity in stock market reactions to government announcements. We provide evidence that the observed stock market behavior around quarantine announcements can be explained by the number of people from the wealthiest segments of the population entering or exiting lockdown.
| S-EPMC8277056 | biostudies-literature
Project description:The COVID-19 outbreak has become one of the largest public health crises of our time. Governments have responded by implementing self-isolation and physical distancing measures that have profoundly impacted daily life throughout the world. In this study, we aimed to investigate how people experience the activities, interactions, and settings of their lives during the pandemic. The sample (N = 604) was assessed in Ireland on the 25 March 2020, following the closure of schools and non-essential businesses. We examined within-person variance in emotional well-being and how people spend their time. We found that while most time was spent in the home (74%), time spent outdoors (8%) was associated with markedly raised positive affect and reduced negative emotions. Exercising, going for walks, gardening, pursuing hobbies, and taking care of children were the activities associated with the greatest affective benefits. Home-schooling children and obtaining information about COVID-19 were ranked lowest of all activities in terms of emotional experience. These findings highlight activities that may play a protective role in relation to well-being during the pandemic, the importance of setting limits for exposure to COVID-19-related media coverage, and the need for greater educational supports to facilitate home-schooling during this challenging period.
| S-EPMC7361840 | biostudies-literature
Project description:This study assesses how the implementation and lifting of non-pharmaceutical policy interventions (NPIs), deployed by most governments, to curb the COVID-19 pandemic, were associated with individuals' mental well-being (MWB) across 28 European countries. This is done both for the general population and across key-groups. We analyze longitudinal data for 15,147 respondents from three waves of the Eurofound-"Living, Working and COVID-19" survey, covering the period April 2020-March 2021. MWB is measured by the WHO-5 index. Our evidence suggests that restriction on international travel, private gatherings, and contact tracing (workplace closures) were negatively (positively) associated with MWB by about, respectively, -0.63 [95% CI: -0.79 to -0.47], -0.24 [95% CI: -0.38 to -0.10], and -0.22 [95% CI: -0.36 to -0.08] (0.29 [95% CI: 0.11 to 0.48]) points. These results correspond to -3.9%, -1.5%, and -1.4% (+1.8%) changes compared to pre-pandemic levels. However, these findings mask important group-differences. Women compared to men fared worse under stay-at-home requirements, internal movement restrictions, private gatherings restrictions, public events cancellation, school closures, and workplace closures. Those residing with children below 12, compared to those who do not, fared worse under public events cancellation, school closures and workplace closures. Conversely, those living with children 12-17, compared to those who do not, fared better under internal movement restrictions and public events cancelling. Western-Europeans vis-à-vis Eastern-Europeans fared better under NPIs limiting their mobility and easing their debts, whereas they fared worse under health-related NPIs. This study provides timely evidence of the rise in inequalities during the COVID-19 pandemic and offers strategies for mitigating them.
| S-EPMC8920116 | biostudies-literature
Project description:During the unprecedented situation that all countries around the globe are facing due to the Coronavirus disease 2019 (COVID-19) pandemic, which has also had severe socioeconomic consequences, it is imperative to explore novel approaches to monitoring and forecasting regional outbreaks as they happen or even before they do so. To that end, in this paper, the role of Google query data in the predictability of COVID-19 in the United States at both national and state level is presented. As a preliminary investigation, Pearson and Kendall rank correlations are examined to explore the relationship between Google Trends data and COVID-19 data on cases and deaths. Next, a COVID-19 predictability analysis is performed, with the employed model being a quantile regression that is bias corrected via bootstrap simulation, i.e., a robust regression analysis that is the appropriate statistical approach to taking against the presence of outliers in the sample while also mitigating small sample estimation bias. The results indicate that there are statistically significant correlations between Google Trends and COVID-19 data, while the estimated models exhibit strong COVID-19 predictability. In line with previous work that has suggested that online real-time data are valuable in the monitoring and forecasting of epidemics and outbreaks, it is evident that such infodemiology approaches can assist public health policy makers in addressing the most crucial issues: flattening the curve, allocating health resources, and increasing the effectiveness and preparedness of their respective health care systems.
| S-EPMC7692493 | biostudies-literature