COVID-19-Related School Closures, United States, July 27, 2020-June 30, 2022

As part of a multiyear project that monitored illness-related school closures, we conducted systematic daily online searches during July 27, 2020-June 30, 2022, to identify public announcements of COVID-19-related school closures (COVID-SCs) in the United States lasting >1 day. We explored the temporospatial patterns of COVID-SCs and analyzed associations between COVID-SCs and national COVID-19 surveillance data. COVID-SCs reflected national surveillance data: correlation was highest between COVID-SCs and both new PCR test positivity (correlation coefficient [r] = 0.73, 95% CI 0.56-0.84) and new cases (r = 0.72, 95% CI 0.54-0.83) during 2020-21 and with hospitalization rates among all ages (r = 0.81, 95% CI 0.67-0.89) during 2021-22. The numbers of reactive COVID-SCs during 2020-21 and 2021-22 greatly exceeded previously observed numbers of illness-related reactive school closures in the United States, notably being nearly 5-fold greater than reactive closures observed during the 2009 influenza (H1N1) pandemic.

The Impact of Covid-19 State Closure Orders on Consumer Spending, Employment, and Business Revenue

CONTEXT

In response to the COVID-19 pandemic, states across the United States implemented various strategies to mitigate transmission of SARS-CoV-2 (the virus that causes COVID-19).

OBJECTIVE

To examine the effect of COVID-19-related state closures on consumer spending, business revenue, and employment, while controlling for changes in COVID-19 incidence and death.

DESIGN

The analysis estimated a difference-in-difference model, utilizing temporal and geographic variation in state closure orders to analyze their impact on the economy, while controlling for COVID-19 incidence and death.

PARTICIPANTS

State-level data on economic outcomes from the Opportunity Insights data tracker and COVID-19 cases and death data from usafacts.org.

INTERVENTIONS

The mitigation strategy analyzed within this study was COVID-19-related state closure orders. Data on these orders were obtained from state government Web sites containing executive or administrative orders.

MAIN OUTCOME MEASURES

Outcomes include state-level estimates of consumer spending, business revenue, and employment levels.

RESULTS

Analyses showed that although state closures led to a decrease in consumer spending, business revenue, and employment, they accounted for only a small portion of the observed decreases in these outcomes over the first wave of COVID-19.

CONCLUSIONS

The impact of COVID-19 on economic activity likely reflects a combination of factors, in addition to state closures, such as individuals' perceptions of risk related to COVID-19 incidence, which may play significant roles in impacting economic activity.

Community Mitigation of COVID-19 and Portrayal of Testing on TikTok: Descriptive Study

BACKGROUND

COVID-19 testing remains an essential element of a comprehensive strategy for community mitigation. Social media is a popular source of information about health, including COVID-19 and testing information. One of the most popular communication channels used by adolescents and young adults who search for health information is TikTok-an emerging social media platform.

OBJECTIVE

The purpose of this study was to describe TikTok videos related to COVID-19 testing.

METHODS

The hashtag #covidtesting was searched, and the first 100 videos were included in the study sample. At the time the sample was drawn, these 100 videos garnered more than 50% of the views for all videos cataloged under the hashtag #covidtesting. The content characteristics that were coded included mentions, displays, or suggestions of anxiety, COVID-19 symptoms, quarantine, types of tests, results of test, and disgust/unpleasantness. Additional data that were coded included the number and percentage of views, likes, and comments and the use of music, dance, and humor.

RESULTS

The 100 videos garnered more than 103 million views; 111,000 comments; and over 12.8 million likes. Even though only 44 videos mentioned or suggested disgust/unpleasantness and 44 mentioned or suggested anxiety, those that portrayed tests as disgusting/unpleasant garnered over 70% of the total cumulative number of views (73,479,400/103,071,900, 71.29%) and likes (9,354,691/12,872,505, 72.67%), and those that mentioned or suggested anxiety attracted about 60% of the total cumulative number of views (61,423,500/103,071,900, 59.59%) and more than 8 million likes (8,339,598/12,872,505, 64.79%). Independent one-tailed t tests (α=.05) revealed that videos that mentioned or suggested that COVID-19 testing was disgusting/unpleasant were associated with receiving a higher number of views and likes.

CONCLUSIONS

Our finding of an association between TikTok videos that mentioned or suggested that COVID-19 tests were disgusting/unpleasant and these videos' propensity to garner views and likes is of concern. There is a need for public health agencies to recognize and address connotations of COVID-19 testing on social media.

α-Satellite: An AI-Driven System and Benchmark Datasets for Dynamic COVID-19 Risk Assessment in the United States

The fast evolving and deadly outbreak of coronavirus disease (COVID-19) has posed grand challenges to human society. To slow the spread of virus infections and better respond for community mitigation, by advancing capabilities of artificial intelligence (AI) and leveraging the large-scale and up-to-date data generated from heterogeneous sources (e.g., disease related data, demographic, mobility and social media data), in this work, we propose and develop an AI-driven system (named α-Satellite), as an initial offering, to provide dynamic COVID-19 risk assessment in the United States. More specifically, given a point of interest (POI), the system will automatically provide risk indices associated with it in a hierarchical manner (e.g., state, county, POI) to enable people to select appropriate actions for protection while minimizing disruptions to daily life. To comprehensively evaluate our system for dynamic COVID-19 risk assessment, we first conduct a set of empirical studies; and then we validate it based on a real-world dataset consisting of 5,060 annotated POIs, which achieves the area of under curve (AUC) of 0.9202. As of June 18, 2020, α-Satellite has had 56,980 users. Based on the feedback from its large-scale users, we perform further analysis and have three key findings: i) people from more severe regions (i.e., with larger numbers of COVID-19 cases) have stronger interests using our system to assist with actionable information; ii) users are more concerned about their nearby areas in terms of COVID-19 risks; iii) the user feedback about their perceptions towards COVID-19 risks of their query POIs indicate the challenge of public concerns about the safety versus its negative effects on society and the economy. Our system and generated datasets have been made publicly accessible via our website.

Social approaches to COVID-19 pandemic response: effectiveness and practicality in sub-Saharan Africa

INTRODUCTION

the threat of the coronavirus disease 2019 (COVID-19) pandemic to health systems and communities in sub-Saharan Africa (SSA) is enormous. Social approaches such as distancing measures are essential components of the public health response to respiratory-related infectious disease outbreaks. Due to socio-economic and broader peculiarities of SSA countries, social approaches that were effective elsewhere may have limited practicality in these contexts, and if practical; may yield different or even adverse results. We highlighted the effectiveness of these social approaches and their practicality in SSA.

METHODS

we conducted a comprehensive literature search through multiple databases, to identify articles relevant to social distancing. Findings were thematically summarized.

RESULTS

our review found emerging and varying empirical evidence on the effectiveness of social approaches in the control and mitigation of the COVID-19 pandemic; thus, limiting its applicability in SSA contexts. Nonetheless, our review demonstrates that the effectiveness and practicality of social approaches in SSA contexts will depend on available resources; timing, duration, and intensity of the intervention; and compliance. Weak political coordination, anti-science sentiments, distrust of political leaders and limited implementation of legal frameworks can also affect practicality.

CONCLUSION

to overcome these challenges, tailoring and adaptation of these measures to different but unique contexts for maximum effectiveness, and investment in social insurance mechanisms, are vital.

COVID-19 and Bangladesh: Challenges and How to Address Them

As the coronavirus outbreak quickly surges worldwide, many countries are adopting non-therapeutic preventive measures, which include travel bans, remote office activities, country lockdown, and most importantly, social distancing. However, these measures face challenges in Bangladesh, a lower-middle-income economy with one of the world's densest populations. Social distancing is difficult in many areas of the country, and with the minimal resources the country has, it would be extremely challenging to implement the mitigation measures. Mobile sanitization facilities and temporary quarantine sites and healthcare facilities could help mitigate the impact of the pandemic at a local level. A prompt, supportive, and empathic collaboration between the Government, citizens, and health experts, along with international assistance, can enable the country to minimize the impact of the pandemic.

Effect of winter school breaks on influenza-like illness, Argentina, 2005-2008

School closures are used to reduce seasonal and pandemic influenza transmission, yet evidence of their effectiveness is sparse. In Argentina, annual winter school breaks occur during the influenza season, providing an opportunity to study this intervention. We used 2005-2008 national weekly surveillance data of visits to a health care provider for influenza-like illness (ILI) from all provinces. Using Serfling-specified Poisson regressions and population-based census denominators, we developed incidence rate ratios (IRRs) for the 3 weeks before, 2 weeks during, and 3 weeks after the break. For persons 5-64 years of age, IRRs were <1 for at least 1 week after the break. Observed rates returned to expected by the third week after the break; overall decrease among persons of all ages was 14%. The largest decrease was among children 5-14 years of age during the week after the break (37% lower IRR). Among adults, effects were weaker and delayed. Two-week winter school breaks significantly decreased visits to a health care provider for ILI among school-aged children and nonelderly adults.