Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the causal agent for COVID-19, is a communicable disease spread through close contact. It is known to disproportionately impact certain communities due to both biological susceptibility and inequitable exposure. In this study, we investigate the most important health, social, and environmental factors impacting the early phases (before July, 2020) of per capita COVID-19 transmission and per capita all-cause mortality in US counties. We aggregate county-level physical and mental health, environmental pollution, access to health care, demographic characteristics, vulnerable population scores, and other epidemiological data to create a large feature set to analyze per capita COVID-19 outcomes. Because of the high-dimensionality, multicollinearity, and unknown interactions of the data, we use ensemble machine learning and marginal prediction methods to identify the most salient factors associated with several COVID-19 outbreak measure. Our variable importance results show that measures of ethnicity, public transportation and preventable diseases are the strongest predictors for both per capita COVID-19 incidence and mortality. Specifically, the CDC measures for minority populations, CDC measures for limited English, and proportion of Black- and/or African-American individuals in a county were the most important features for per capita COVID-19 cases within a month after the pandemic started in a county and also at the latest date examined. For per capita all-cause mortality at day 100 and total to date, we find that public transportation use and proportion of Black- and/or African-American individuals in a county are the strongest predictors. The methods predict that, keeping all other factors fixed, a 10% increase in public transportation use, all other factors remaining fixed at the observed values, is associated with increases mortality at day 100 of 2012 individuals (95% CI [1972, 2356]) and likewise a 10% increase in the proportion of Black- and/or African-American individuals in a county is associated with increases total deaths at end of study of 2067 (95% CI [1189, 2654]). Using data until the end of study, the same metric suggests ethnicity has double the association as the next most important factors, which are location, disease prevalence, and transit factors. Our findings shed light on societal patterns that have been reported and experienced in the U.S. by using robust methods to understand the features most responsible for transmission and sectors of society most vulnerable to infection and mortality. In particular, our results provide evidence of the disproportionate impact of the COVID-19 pandemic on minority populations. Our results suggest that mitigation measures, including how vaccines are distributed, could have the greatest impact if they are given with priority to the highest risk communities.
more »
« less
The times, they are a-changin’: tracking shifts in mental health signals from early phase to later phase of the COVID-19 pandemic in Australia
Introduction Widespread problems of psychological distress have been observed in many countries following the outbreak of COVID-19, including Australia. What is lacking from current scholarship is a national-scale assessment that tracks the shifts in mental health during the pandemic timeline and across geographic contexts. Methods Drawing on 244 406 geotagged tweets in Australia from 1 January 2020 to 31 May 2021, we employed machine learning and spatial mapping techniques to classify, measure and map changes in the Australian public’s mental health signals, and track their change across the different phases of the pandemic in eight Australian capital cities. Results Australians’ mental health signals, quantified by sentiment scores, have a shift from pessimistic (early pandemic) to optimistic (middle pandemic), reflected by a 174.1% (95% CI 154.8 to 194.5) increase in sentiment scores. However, the signals progressively recessed towards a more pessimistic outlook (later pandemic) with a decrease in sentiment scores by 48.8% (95% CI 34.7 to 64.9). Such changes in mental health signals vary across capital cities. Conclusion We set out a novel empirical framework using social media to systematically classify, measure, map and track the mental health of a nation. Our approach is designed in a manner that can readily be augmented into an ongoing monitoring capacity and extended to other nations. Tracking locales where people are displaying elevated levels of pessimistic mental health signals provide important information for the smart deployment of finite mental health services. This is especially critical in a time of crisis during which resources are stretched beyond normal bounds.
more »
« less
- Award ID(s):
- 2028791
- NSF-PAR ID:
- 10345865
- Date Published:
- Journal Name:
- BMJ Global Health
- Volume:
- 7
- Issue:
- 1
- ISSN:
- 2059-7908
- Page Range / eLocation ID:
- e007081
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
more » « less
Objective: The COVID-19 pandemic has put unprecedented stress on essential workers and their children. Limited cross-sectional research has found increases in mental health conditions from workload, reduced income, and isolation among essential workers. Less research has been conducted on children of essential workers. We examined trends in the crisis response of essential workers and their children from April 2020 through August 2021.
Methods: We investigated the impact during 3 periods of the pandemic on workers and their children using anonymized data from the Crisis Text Line on crisis help-seeking texts for thoughts of suicide or active suicidal ideation (desire, intent, capability, time frame), abuse (emotional, physical, sexual, unspecified), anxiety/stress, grief, depression, isolation, bullying, eating or body image, gender/sexual identity, self-harm, and substance use. We used generalized estimating equations to study the longitudinal change in crisis response across the later stages of the pandemic using adjusted odds ratios (aORs) for worker status and crisis outcomes.
Results: Results demonstrated higher odds of crisis outcomes for thoughts of suicide (aOR = 1.06; 95% CI, 1.00-1.12) and suicide capability (aOR = 1.14; 95% CI, 1.02-1.27) among essential workers than among nonessential workers. Children of essential workers had higher odds of substance use than children of nonessential workers (aOR = 1.33; 95% CI, 1.08-1.65), particularly for Indigenous American children (aOR = 2.76; 95% CI, 1.35-5.36). Essential workers (aOR = 1.17; 95% CI, 1.07-1.27) and their children (aOR = 1.18; 95% CI, 1.07-1.30) had higher odds of grief than nonessential workers and their children.
Conclusion: Essential workers and their children had elevated crisis outcomes. Immediate and low-cost psychologically supportive interventions are needed to mitigate the mental health impacts of the COVID-19 pandemic on these populations.
-
null (Ed.)Abstract Background Cross-sectional studies have found that the coronavirus disease 2019 (COVID-19) pandemic has negatively affected population-level mental health. Longitudinal studies are necessary to examine trajectories of change in mental health over time and identify sociodemographic groups at risk for persistent distress. Purpose To examine the trajectories of mental distress between March 10 and August 4, 2020, a key period during the COVID-19 pandemic. Methods Participants included 6,901 adults from the nationally representative Understanding America Study, surveyed at baseline between March 10 and 31, 2020, with nine follow-up assessments between April 1 and August 4, 2020. Mixed-effects logistic regression was used to examine the association between date and self-reported mental distress (measured with the four-item Patient Health Questionnaire) among U.S. adults overall and among sociodemographic subgroups defined by sex, age, race/ethnicity, household structure, federal poverty line, and census region. Results Compared to March 11, the odds of mental distress among U.S. adults overall were 1.84 (95% confidence interval [CI] = 1.65–2.07) times higher on April 1 and 1.92 (95% CI = 1.62–2.28) times higher on May 1; by August 1, the odds of mental distress had returned to levels comparable to March 11 (odds ratio [OR] = 0.80, 95% CI = 0.66–0.96). Females experienced a sharper increase in mental distress between March and May compared to males (females: OR = 2.29, 95% CI = 1.85–2.82; males: OR = 1.53, 95% CI = 1.15–2.02). Conclusions These findings highlight the trajectory of mental health symptoms during an unprecedented pandemic, including the identification of populations at risk for sustained mental distress.more » « less
-
more » « less
Importance The COVID-19 pandemic has been notable for the widespread dissemination of misinformation regarding the virus and appropriate treatment.
Objective To quantify the prevalence of non–evidence-based treatment for COVID-19 in the US and the association between such treatment and endorsement of misinformation as well as lack of trust in physicians and scientists.
Design, Setting, and Participants This single-wave, population-based, nonprobability internet survey study was conducted between December 22, 2022, and January 16, 2023, in US residents 18 years or older who reported prior COVID-19 infection.
Main Outcome and Measure Self-reported use of ivermectin or hydroxychloroquine, endorsing false statements related to COVID-19 vaccination, self-reported trust in various institutions, conspiratorial thinking measured by the American Conspiracy Thinking Scale, and news sources.
Results A total of 13 438 individuals (mean [SD] age, 42.7 [16.1] years; 9150 [68.1%] female and 4288 [31.9%] male) who reported prior COVID-19 infection were included in this study. In this cohort, 799 (5.9%) reported prior use of hydroxychloroquine (527 [3.9%]) or ivermectin (440 [3.3%]). In regression models including sociodemographic features as well as political affiliation, those who endorsed at least 1 item of COVID-19 vaccine misinformation were more likely to receive non–evidence-based medication (adjusted odds ratio [OR], 2.86; 95% CI, 2.28-3.58). Those reporting trust in physicians and hospitals (adjusted OR, 0.74; 95% CI, 0.56-0.98) and in scientists (adjusted OR, 0.63; 95% CI, 0.51-0.79) were less likely to receive non–evidence-based medication. Respondents reporting trust in social media (adjusted OR, 2.39; 95% CI, 2.00-2.87) and in Donald Trump (adjusted OR, 2.97; 95% CI, 2.34-3.78) were more likely to have taken non–evidence-based medication. Individuals with greater scores on the American Conspiracy Thinking Scale were more likely to have received non–evidence-based medications (unadjusted OR, 1.09; 95% CI, 1.06-1.11; adjusted OR, 1.10; 95% CI, 1.07-1.13).
Conclusions and Relevance In this survey study of US adults, endorsement of misinformation about the COVID-19 pandemic, lack of trust in physicians or scientists, conspiracy-mindedness, and the nature of news sources were associated with receiving non–evidence-based treatment for COVID-19. These results suggest that the potential harms of misinformation may extend to the use of ineffective and potentially toxic treatments in addition to avoidance of health-promoting behaviors.
-
more » « less
Importance Marked elevation in levels of depressive symptoms compared with historical norms have been described during the COVID-19 pandemic, and understanding the extent to which these are associated with diminished in-person social interaction could inform public health planning for future pandemics or other disasters.
Objective To describe the association between living in a US county with diminished mobility during the COVID-19 pandemic and self-reported depressive symptoms, while accounting for potential local and state-level confounding factors.
Design, Setting, and Participants This survey study used 18 waves of a nonprobability internet survey conducted in the United States between May 2020 and April 2022. Participants included respondents who were 18 years and older and lived in 1 of the 50 US states or Washington DC.
Main Outcome and Measure Depressive symptoms measured by the Patient Health Questionnaire-9 (PHQ-9); county-level community mobility estimates from mobile apps; COVID-19 policies at the US state level from the Oxford stringency index.
Results The 192 271 survey respondents had a mean (SD) of age 43.1 (16.5) years, and 768 (0.4%) were American Indian or Alaska Native individuals, 11 448 (6.0%) were Asian individuals, 20 277 (10.5%) were Black individuals, 15 036 (7.8%) were Hispanic individuals, 1975 (1.0%) were Pacific Islander individuals, 138 702 (72.1%) were White individuals, and 4065 (2.1%) were individuals of another race. Additionally, 126 381 respondents (65.7%) identified as female and 65 890 (34.3%) as male. Mean (SD) depression severity by PHQ-9 was 7.2 (6.8). In a mixed-effects linear regression model, the mean county-level proportion of individuals not leaving home was associated with a greater level of depression symptoms (β, 2.58; 95% CI, 1.57-3.58) after adjustment for individual sociodemographic features. Results were similar after the inclusion in regression models of local COVID-19 activity, weather, and county-level economic features, and persisted after widespread availability of COVID-19 vaccination. They were attenuated by the inclusion of state-level pandemic restrictions. Two restrictions, mandatory mask-wearing in public (β, 0.23; 95% CI, 0.15-0.30) and policies cancelling public events (β, 0.37; 95% CI, 0.22-0.51), demonstrated modest independent associations with depressive symptom severity.
Conclusions and Relevance In this study, depressive symptoms were greater in locales and times with diminished community mobility. Strategies to understand the potential public health consequences of pandemic responses are needed.
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1136/bmjgh-2021-007081
