Census tract socioeconomic indicators and COVID-19-associated hospitalization rates—COVID-NET surveillance areas in 14 states, March 1–April 30, 2020

Objectives Some studies suggested more COVID-19-associated hospitalizations among racial and ethnic minorities. To inform public health practice, the COVID-19-associated Hospitalization Surveillance Network (COVID-NET) quantified associations between race/ethnicity, census tract socioeconomic indicators, and COVID-19-associated hospitalization rates. Methods Using data from COVID-NET population-based surveillance reported during March 1–April 30, 2020 along with socioeconomic and denominator data from the US Census Bureau, we calculated COVID-19-associated hospitalization rates by racial/ethnic and census tract-level socioeconomic strata. Results Among 16,000 COVID-19-associated hospitalizations, 34.8% occurred among non-Hispanic White (White) persons, 36.3% among non-Hispanic Black (Black) persons, and 18.2% among Hispanic or Latino (Hispanic) persons. Age-adjusted COVID-19-associated hospitalization rate were 151.6 (95% Confidence Interval (CI): 147.1–156.1) in census tracts with >15.2%–83.2% of persons living below the federal poverty level (high-poverty census tracts) and 75.5 (95% CI: 72.9–78.1) in census tracts with 0%–4.9% of persons living below the federal poverty level (low-poverty census tracts). Among White, Black, and Hispanic persons living in high-poverty census tracts, age-adjusted hospitalization rates were 120.3 (95% CI: 112.3–128.2), 252.2 (95% CI: 241.4–263.0), and 341.1 (95% CI: 317.3–365.0), respectively, compared with 58.2 (95% CI: 55.4–61.1), 304.0 (95%: 282.4–325.6), and 540.3 (95% CI: 477.0–603.6), respectively, in low-poverty census tracts. Conclusions Overall, COVID-19-associated hospitalization rates were highest in high-poverty census tracts, but rates among Black and Hispanic persons were high regardless of poverty level. Public health practitioners must ensure mitigation measures and vaccination campaigns address needs of racial/ethnic minority groups and people living in high-poverty census tracts.

Download Full-text

Abstract P198: Does Neighborhood Poverty Account for Race/Ethnic Differences in Sleep Duration?

Circulation ◽

10.1161/circ.127.suppl_12.ap198 ◽

2013 ◽

Vol 127 (suppl_12) ◽

Author(s):

Bonnie R Bright ◽

Mercedes R Carnethon ◽

Peter John D De Chavez ◽

Kwang-Youn Kim ◽

Kristen L Knutson ◽

...

Keyword(s):

Sleep Duration ◽

Ethnic Differences ◽

Census Tract ◽

Social Stress ◽

Noise Exposure ◽

High Poverty ◽

Sleep Study ◽

White Participant ◽

Neighborhood Poverty ◽

Racial Ethnic

Introduction: Shorter sleep duration and poorer quality sleep are commonly observed in non-white vs. white racial/ethnic groups. Reasons for these racial/ethnic differences are unknown. Our objective is to determine whether neighborhood poverty, which may reflect more noise exposure, crowding and social stress, explains racial/ethnic differences in sleep. Methods: The Chicago Area Sleep Study identified men and women 35-64 years old without sleep apnea via commercially available telephone listings (N=510; 31% Black, 22% Asian, 21% Hispanic, and 26% White). Participant addresses were geocoded, and residence in a census tract with >20% poverty based on American Community Survey data was classified as “high poverty”. Participants wore wrist actigraphs for 7 days (Actiwatch TM ) to determine sleep duration and sleep percentage (percentage of time during the primary sleep interval spent sleeping). Multivariable regression analysis was used to test whether race remained significantly associated with sleep following adjustment for neighborhood poverty. Results: Black (86%) and Hispanic (66%) participants were more likely to live in high poverty areas as compared with Whites (33%) and Asians (6%). In unadjusted analyses, living in a high poverty census tract was associated with a significantly lower mean sleep percentage (β= -1.80, SE=0.42, p<0.01) and a higher odds of sleeping <6 hrs/night (OR=1.65, 95% CI: 1.02, 2.67). However, these associations were attenuated in adjusted models, and they did not account for race differences in sleep (Table). Conclusions: Neighborhood poverty was unassociated with a lower sleep percentage or shorter sleep in adjusted models, and it did not account for racial/ethnic differences in sleep. Further investigation of specific features of neighborhood poverty (e.g., crime, crowding) and household environment factors that may explain racial/ethnic differences in sleep is warranted.

Download Full-text

2325. Relationship Between Neighborhood Census-Tract-Level Poverty and Respiratory Syncytial Virus Infection in hospitalized Adults in the San Francisco Bay area, CA 2015–2017

Open Forum Infectious Diseases ◽

10.1093/ofid/ofz360.2003 ◽

2019 ◽

Vol 6 (Supplement_2) ◽

pp. S798-S798

Author(s):

Jenna Holmen ◽

Bryanna Cikesh ◽

Lindsay Kim ◽

Art Reingold

Keyword(s):

Respiratory Syncytial Virus ◽

San Francisco ◽

Census Tract ◽

San Francisco Bay ◽

San Francisco Bay Area ◽

Poverty Level ◽

Census Tracts ◽

Bay Area ◽

Census Tract Level ◽

Syncytial Virus

Abstract Background In the United States, respiratory syncytial virus (RSV) is a leading cause of admission for adults with respiratory illness. In adults > 50 years of age, it accounts for up to 12% of medically-attended acute respiratory illnesses and has a case fatality proportion of ~6–8%. Poverty can have an important influence on health. Few studies have evaluated the relationship of RSV incidence and poverty level, and no identified studies have evaluated this relationship among adults. We evaluated the incidence of RSV-associated hospitalizations in adults in the San Francisco Bay Area, CA by census-tract-level poverty. Methods Medical record data abstraction was conducted for all adults with a laboratory-confirmed RSV infection who were admitted to a hospital within the 3 counties comprising the catchment area (Alameda, Contra Costa, and San Francisco counties) during the 2015–2016 and 2016–2017 RSV seasons. Patient addresses were geocoded to their corresponding census-tract (CT). Census tracts were divided into four levels of poverty based on American Community Survey data of percentage of people living below the poverty level: 0–4.9%, 5–9.9%, 10-–9.9%, and ³20%. Incidence rates were calculated by dividing the number of RSV cases in each CT poverty-level (numerator) by the number of adults living in each CT poverty level (denominator), as determined from the 2010 US census, and standardized for age. Results There were 526 RSV case-patients with demographic characteristics as outlined in Table 1. The highest incidence of RSV-associated hospitalization was in CTs associated with the highest levels of poverty (>20%). However, the second highest incidence of RSV-associated hospitalization occurred among adults living in CTs with <5% poverty (Figure 1 and Table 2). Conclusion The incidence rate of RSV-associated hospitalization in adults appears to be positively correlated with highest census-tract level of poverty; however, there is a high incidence among adults living in the lowest poverty census-tracts. Disclosures All authors: No reported disclosures.

Download Full-text

Abstract 136: Disparities in Out of Hospital Cardiac Arrest Care and Outcomes in Texas

Circulation ◽

10.1161/circ.142.suppl_4.136 ◽

2020 ◽

Vol 142 (Suppl_4) ◽

Author(s):

Ryan Huebinger ◽

Henry Wang ◽

Jeff Jarvis ◽

Cameron Decker ◽

Robert Dickson ◽

...

Keyword(s):

High School ◽

Cardiac Arrest ◽

Hospital Discharge ◽

Census Tract ◽

High School Graduation ◽

Census Tracts ◽

Bystander Cpr ◽

School Graduation ◽

Racial Ethnic ◽

Hospital Cardiac Arrest

Background: Minorities and impoverished persons experience disparities in access to healthcare. Large inequalities in out-of-hospital cardiac arrest (OHCA) care have been described. We sought to characterize racial and socioeconomic disparities in OHCA care and outcomes in Texas. Hypothesis: There are census tract level disparities in OHCA care and outcomes in Texas. Methods: We analyzed Texas-Cardiac Arrest Registry to Enhance Survival (CARES) data from 13 EMS agencies providing care in 15 counties to roughly 30% of the state population. We included all adult (>=18 year) OHCA from 1/1/14 through 12/31/18 with complete data. Using census tract data, we stratified census tracts into racial/ethnic categories: >50% non-Hispanic/Latino white, >50% black, and >50% Hispanic/Latino. We also stratified census tracts into neighborhoods above and below the median for socioeconomic characteristics: household income, employment rate, and high school graduation. We defined outcomes as bystander CPR rates, public bystander AED use, and survival to hospital discharge. Using mixed models, we analyzed the associations between outcomes and neighborhood (1) racial/ethnic categories and (2) socioeconomic categories. Results: We included data on 18,487 OHCAs from 1,727 census tracts. Relative to white neighborhoods, black neighborhoods had a significantly lower rate of bystander AED use (OR 0.3, CI 0.1-0.9), and Latino neighborhoods had a lower rate of bystander CPR (OR 0.7, CI 0.6-0.8), bystander AED use (OR 0.4, CI 0.3-0.6) and survival to hospital discharge (OR 0.9, CI 0.8-0.98). Lower income was associated with a lower rate of bystander CPR (OR 0.8, CI 0.7-0.8), bystander AED use (OR 0.5, 0.4-0.8), and survival to hospital discharge (OR 0.6, CI 0.5-0.9). Lower high school graduation was associated with a lower rate of bystander CPR (OR 0.8, CI 0.7-0.9) and bystander AED use (OR 0.6, CI 0.4-0.9). High unemployment was associated with lower rates of bystander CPR (OR 0.9, CI 0.8-0.94) and bystander AED use (OR 0.7, CI 0.5-0.99). Conclusion: Minority and poor neighborhoods in Texas experience large and unacceptable disparities in OHCA bystander response and outcomes. These data present an important opportunity for targeted resuscitation training and quality improvement.

Download Full-text

The Relationship Between Census Tract Poverty and Shiga Toxin–Producing E. coli Risk, Analysis of FoodNet Data, 2010–2014

Open Forum Infectious Diseases ◽

10.1093/ofid/ofy148 ◽

2018 ◽

Vol 5 (7) ◽

Cited By ~ 2

Author(s):

James L Hadler ◽

Paula Clogher ◽

Jennifer Huang ◽

Tanya Libby ◽

Alicia Cronquist ◽

...

Keyword(s):

New York ◽

Shiga Toxin ◽

Census Tract ◽

Care Seeking ◽

Poverty Level ◽

Surveillance Network ◽

Census Tracts ◽

E Coli ◽

Uremic Syndrome ◽

The Relationship

Abstract Background The relationship between socioeconomic status and Shiga toxin–producing Escherichia coli (STEC) is not well understood. However, recent studies in Connecticut and New York City found that as census tract poverty (CTP) decreased, rates of STEC increased. To explore this nationally, we analyzed surveillance data from laboratory-confirmed cases of STEC from 2010–2014 for all Foodborne Disease Active Surveillance Network (FoodNet) sites, population 47.9 million. Methods Case residential data were geocoded and linked to CTP level (2010–2014 American Community Survey). Relative rates were calculated comparing incidence in census tracts with <20% of residents below poverty with those with ≥20%. Relative rates of age-adjusted 5-year incidence per 100 000 population were determined for all STEC, hospitalized only and hemolytic-uremic syndrome (HUS) cases overall, by demographic features, FoodNet site, and surveillance year. Results There were 5234 cases of STEC; 26.3% were hospitalized, and 5.9% had HUS. Five-year incidence was 10.9/100 000 population. Relative STEC rates for the <20% compared with the ≥20% CTP group were >1.0 for each age group, FoodNet site, surveillance year, and race/ethnic group except Asian. Relative hospitalization and HUS rates tended to be higher than their respective STEC relative rates. Conclusions Persons living in lower CTP were at higher risk of STEC than those in the highest poverty census tracts. This is unlikely to be due to health care–seeking or diagnostic bias as it applies to analysis limited to hospitalized and HUS cases. Research is needed to better understand exposure differences between people living in the lower vs highest poverty-level census tracts to help direct prevention efforts.

Download Full-text

Abstract 005: Violent Crime, Physical Inactivity, And Obesity: Examining Differences In Spatial Relationships By Racial/ethnic Composition Of Community Residents

Circulation ◽

10.1161/circ.143.suppl_1.005 ◽

2021 ◽

Vol 143 (Suppl_1) ◽

Author(s):

Chelsea R Singleton ◽

Fikriyah Winata ◽

Oluwafikayo S Adeyemi ◽

Kaustubh V Parab ◽

Susan Aguiñaga

Keyword(s):

Violent Crime ◽

Census Tract ◽

Crime Rate ◽

Physical Inactivity ◽

Ethnic Composition ◽

Census Tracts ◽

Census Tract Level ◽

Violent Crime Rate ◽

Community Residents ◽

Racial Ethnic

Introduction: Violent crime (e.g., homicide, aggravated assault) is a major public health issue that disproportionately affects communities of color in large urban centers. Studies have reported that residents in high crime communities are less likely to engage in physical activity. There is limited understanding of how violent crime influences physical inactivity and obesity at the community level. We aimed to address this gap by examining differences in spatial relationships between violent crime rate, physical inactivity, and obesity by racial/ethnic composition of community residents in Chicago, IL. Hypothesis: We assessed the hypothesis that violent crime rate is associated with the prevalence of physical inactivity and obesity at the census tract level in Chicago, IL. Methods: We conducted an ecological assessment of 2018 census tract data obtained from various sources. We used data from the City of Chicago to calculate per capita violent crime rate (number of incidents per 1,000 residents) for all census tracts (N = 801). Data on physical inactivity and obesity prevalence (%) were acquired from the CDC. Socio-demographic data (i.e., % Non-Hispanic (NH) White, % NH Black, % Hispanic, median household income) were obtained from the census bureau. We examined spatial lag and error models to determine if violent crime rate is associated with % physical inactivity and % obesity after controlling for socio-demographic characteristics and amenity availability (i.e., per capita outdoor parks and grocery stores). Stratified models were examined to identify differences in associations among majority NH White, NH Black, and Hispanic census tracts (defined as ≥ 50% representation). Results: NH Black census tracts (n = 278) had significantly higher rates of violent crime, physical inactivity, and obesity than Hispanic (n = 169) and NH White tracts (n = 240). Overall, violent crime rate was positivity associated with % physical inactivity (p<0.001) but not % obesity (p=0.77) in Chicago after controlling for covariates. Stratified models revealed that violent crime rate was positively associated with % physical inactivity (p<0.001) and % obesity (p=0.01) among NH Black tracts. Violent crime rate was not associated with % physical inactivity or % obesity among Hispanic and NH White census tracts. Conclusions: Racial/ethnic composition of residents appears to influence census-tract level associations between violent crime rate, physical inactivity, and obesity. Violent crime appears to be more relevant to physical inactivity and obesity in Chicago’s NH Black communities compared to Hispanic and NH White communities.

Download Full-text

HIV Clustering in Mississippi: Spatial Epidemiological Study to Inform Implementation Science in the Deep South (Preprint)

10.2196/preprints.8773 ◽

2017 ◽

Author(s):

Thomas J Stopka ◽

Lauren Brinkley-Rubinstein ◽

Kendra Johnson ◽

Philip A Chan ◽

Marga Hutcheson ◽

...

Keyword(s):

Public Health ◽

African Americans ◽

Spatial Epidemiology ◽

Mississippi Delta ◽

Hiv Infections ◽

High School Education ◽

Deep South ◽

Poverty Level ◽

Census Tracts ◽

Factors Associated

BACKGROUND In recent years, more than half of new HIV infections in the United States occur among African Americans in the Southeastern United States. Spatial epidemiological analyses can inform public health responses in the Deep South by identifying HIV hotspots and community-level factors associated with clustering. OBJECTIVE The goal of this study was to identify and characterize HIV clusters in Mississippi through analysis of state-level HIV surveillance data. METHODS We used a combination of spatial epidemiology and statistical modeling to identify and characterize HIV hotspots in Mississippi census tracts (n=658) from 2008 to 2014. We conducted spatial analyses of all HIV infections, infections among men who have sex with men (MSM), and infections among African Americans. Multivariable logistic regression analyses identified community-level sociodemographic factors associated with HIV hotspots considering all cases. RESULTS There were HIV hotspots for the entire population, MSM, and African American MSM identified in the Mississippi Delta region, Southern Mississippi, and in greater Jackson, including surrounding rural counties (P<.05). In multivariable models for all HIV cases, HIV hotspots were significantly more likely to include urban census tracts (adjusted odds ratio [AOR] 2.01, 95% CI 1.20-3.37) and census tracts that had a higher proportion of African Americans (AOR 3.85, 95% CI 2.23-6.65). The HIV hotspots were less likely to include census tracts with residents who had less than a high school education (AOR 0.95, 95% CI 0.92-0.98), census tracts with residents belonging to two or more racial/ethnic groups (AOR 0.46, 95% CI 0.30-0.70), and census tracts that had a higher percentage of the population living below the poverty level (AOR 0.51, 95% CI 0.28-0.92). CONCLUSIONS We used spatial epidemiology and statistical modeling to identify and characterize HIV hotspots for the general population, MSM, and African Americans. HIV clusters concentrated in Jackson and the Mississippi Delta. African American race and urban location were positively associated with clusters, whereas having less than a high school education and having a higher percentage of the population living below the poverty level were negatively associated with clusters. Spatial epidemiological analyses can inform implementation science and public health response strategies, including improved HIV testing, targeted prevention and risk reduction education, and tailored preexposure prophylaxis to address HIV disparities in the South.

Download Full-text

1717. Relationship between Neighborhood Census-tract Level Poverty and Respiratory Syncytial Virus (RSV)-associated Hospitalizations in U.S. adults, 2015-2017

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa439.1895 ◽

2020 ◽

Vol 7 (Supplement_1) ◽

pp. S842-S843

Author(s):

Jenna Holmen ◽

Art Reingold ◽

Erica Bye ◽

Lindsey Kim ◽

Evan J Anderson ◽

...

Keyword(s):

Incidence Rate ◽

Census Tract ◽

Case Fatality ◽

Demographic Characteristics ◽

Emerging Infections ◽

Poverty Level ◽

Catchment Areas ◽

Syncytial Virus ◽

Four Levels ◽

The U.S

Abstract Background In the U.S., RSV is increasingly recognized as a cause of hospitalization for adults with respiratory illness. In adults > 50 years of age, it accounts for up to 12% of medically-attended acute respiratory illnesses and has a case fatality proportion of ~ 6–8%. Poverty can have important influences on health on both the individual level as well as the community level. Few studies have evaluated the relationship of RSV and poverty level, and no identified studies have evaluated this relationship among adults. We evaluated the incidence of RSV-associated hospitalizations in adults across multiple sites in the U.S. by census-tract (CT) level poverty. Methods Medical record data abstraction was conducted for all adults with a laboratory-confirmed RSV infection admitted to a hospital within the Centers for Disease Control and Prevention’s Emerging Infections Program catchment areas within California, Georgia, Maryland, Minnesota, New York, and Tennessee during the 2015–2017 RSV seasons (October-April). Patient addresses were geocoded to their corresponding CT. CTs were divided into four levels of poverty, as selected in prior publications, based on American Community Survey data of percentage of people living below the poverty level: 0–4.9%, 5–9.9%, 10-19.9%, and ³20%. Incidence rates were calculated by dividing the number of RSV cases in each CT poverty-level (numerator) by the number of adults living in each CT poverty level (denominator), as determined from the 2010 US census, and standardized for age. Results There were 1713 RSV case-patients with demographic characteristics (Table 1). The incidence of RSV-associated hospitalizations of adults increased with increasing CT level poverty (Figure 1 and Table 2). The risk of RSV-associated hospitalization was 2.58 times higher in census tracts with the highest (20%) versus the lowest (< 5%) percentages of individuals living below the poverty level. Table 1: Demographic characteristics of adults with an RSV-associated hospitalization, 2015-2017. Figure 1. Age-adjusted incidence rate of RSV-associated hospitalizations of adults by census-tract poverty level, 2015-2017 Table 2. Incidence rate ratios for RSV-associated hospitalizations of adults by census-tract poverty level, 2015-2017. Conclusion The incidence rate of RSV-associated hospitalization in adults appears to have a positive association with increasing CT level of poverty; however, this trend reached significance only among cases living in CTs with higher percentages of poverty (≥ 10%). Disclosures Evan J. Anderson, MD, Sanofi Pasteur (Scientific Research Study Investigator)

Download Full-text

Locking down behavioural compliance: The role of emotion and emotion regulation in breaches of COVID-19 mitigation measures in Aotearoa New Zealand

Journal of Health Psychology ◽

10.1177/13591053211029994 ◽

2021 ◽

pp. 135910532110299

Author(s):

Terise Broodryk ◽

Kealagh Robinson

Keyword(s):

Public Health ◽

Young Adults ◽

New Zealand ◽

Health Behaviours ◽

Mitigation Measures ◽

Aotearoa New Zealand ◽

High Knowledge ◽

The Cost ◽

Insight Into

Although anxiety and worry can motivate engagement with COVID-19 preventative behaviours, people may cognitively reframe these unpleasant emotions, restoring wellbeing at the cost of public health behaviours. New Zealand young adults ( n = 278) experiencing nationwide COVID-19 lockdown reported their worry, anxiety, reappraisal and lockdown compliance. Despite high knowledge of lockdown policies, 92.5% of participants reported one or more policy breaches ( M = 2.74, SD = 1.86). Counter to predictions, no relationships were found between anxiety or worry with reappraisal or lockdown breaches. Findings highlight the importance of targeting young adults in promoting lockdown compliance and offer further insight into the role of emotion during a pandemic.

Download Full-text

1719. Respiratory Syncytial Virus-Associated Hospitalization Rates among US Infants: A Systematic Review and Meta-Analysis

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa439.1897 ◽

2020 ◽

Vol 7 (Supplement_1) ◽

pp. S843-S843

Author(s):

John M McLaughlin ◽

Farid L Khan ◽

Heinz-Josef Schmitt ◽

Yasmeen Agosti ◽

Luis Jodar ◽

...

Keyword(s):

Public Health ◽

Respiratory Syncytial Virus ◽

Active Surveillance ◽

Meta Analysis ◽

The United States ◽

Administrative Claims ◽

Prevention Strategies ◽

Hospitalization Rates ◽

Syncytial Virus ◽

The Impact

Abstract Background Understanding the true magnitude of infant respiratory syncytial virus (RSV) burden is critical for determining the potential public-health benefit of RSV prevention strategies. Although global reviews of infant RSV burden exist, none have summarized data from the United States or evaluated how RSV burden estimates are influenced by variations in study design. Methods We performed a systematic literature review and meta-analysis of studies describing RSV-associated hospitalization rates among US infants. We also examined the impact of key study characteristics on these estimates. Results After review of 3058 articles through January 2020, we identified 25 studies with 31 unique estimates of RSV-associated hospitalization rates. Among US infants < 1 year of age, annual rates ranged from 8.4 to 40.8 per 1000 with a pooled rate= 19.4 (95%CI= 17.9–20.9). Study type was associated with RSV hospitalization rates (P =.003), with active surveillance studies having pooled rates per 1000 (11.1; 95%CI: 9.8–12.3) that were half that of studies based on administrative claims (21.4; 95%CI: 19.5–23.3) or modeling approaches (23.2; 95%CI: 20.2–26.2). Conclusion Applying the pooled rates identified in our review to the 2020 US birth cohort suggests that 73,680 to 86,020 RSV-associated infant hospitalizations occur each year. To date, public-health officials have used conservative estimates from active surveillance as the basis for defining US infant RSV burden. The full range of RSV-associated hospitalization rates identified in our review better characterizes the true RSV burden in infants and can better inform future evaluations of RSV prevention strategies. Disclosures John M. McLaughlin, PhD, Pfizer (Employee, Shareholder) Farid L. Khan, MPH, Pfizer (Employee, Shareholder) Heinz-Josef Schmitt, MD, Pfizer (Employee, Shareholder) Yasmeen Agosti, MD, Pfizer (Employee, Shareholder) Luis Jodar, PhD, Pfizer (Employee, Shareholder) Eric Simões, MD, Pfizer (Consultant, Research Grant or Support) David L. Swerdlow, MD, Pfizer (Employee, Shareholder)

Download Full-text

A shift from science to politics : a content analysis of COVID-19 Videos on YouTube (Preprint)

10.2196/preprints.33948 ◽

2021 ◽

Author(s):

Chyun-Fung Shi ◽

Matthew C So ◽

Sophie Stelmach ◽

Arielle Earn ◽

David J D Earn ◽

...

Keyword(s):

Public Health ◽

Social Media ◽

Content Analysis ◽

Large Scale ◽

Control Measures ◽

Mitigation Measures ◽

Health Campaigns ◽

Public Attention ◽

Conflicting Information ◽

Social Media Platforms

BACKGROUND The COVID-19 pandemic is the first pandemic where social media platforms relayed information on a large scale, enabling an “infodemic” of conflicting information which undermined the global response to the pandemic. Understanding how the information circulated and evolved on social media platforms is essential for planning future public health campaigns. OBJECTIVE This study investigated what types of themes about COVID-19 were most viewed on YouTube during the first 8 months of the pandemic, and how COVID-19 themes progressed over this period. METHODS We analyzed top-viewed YouTube COVID-19 related videos in English from from December 1, 2019 to August 16, 2020 with an open inductive content analysis. We coded 536 videos associated with 1.1 billion views across the study period. East Asian countries were the first to report the virus, while most of the top-viewed videos in English were from the US. Videos from straight news outlets dominated the top-viewed videos throughout the outbreak, and public health authorities contributed the fewest. Although straight news was the dominant COVID-19 video source with various types of themes, its viewership per video was similar to that for entertainment news and YouTubers after March. RESULTS We found, first, that collective public attention to the COVID-19 pandemic on YouTube peaked around March 2020, before the outbreak peaked, and flattened afterwards despite a spike in worldwide cases. Second, more videos focused on prevention early on, but videos with political themes increased through time. Third, regarding prevention and control measures, masking received much less attention than lockdown and social distancing in the study period. CONCLUSIONS Our study suggests that a transition of focus from science to politics on social media intensified the COVID-19 infodemic and may have weakened mitigation measures during the first waves of the COVID-19 pandemic. It is recommended that authorities should consider co-operating with reputable social media influencers to promote health campaigns and improve health literacy. In addition, given high levels of globalization of social platforms and polarization of users, tailoring communication towards different digital communities is likely to be essential.

Download Full-text