United States Influenza Search Patterns Since the Emergence of COVID-19: Infodemiology Study

BackgroundThe emergence and media coverage of COVID-19 may have affected influenza search patterns, possibly affecting influenza surveillance results using Google Trends.ObjectiveWe aimed to investigate if the emergence of COVID-19 was associated with modifications in influenza search patterns in the United States.MethodsWe retrieved US Google Trends data (relative number of searches for specified terms) for the topics influenza, Coronavirus disease 2019, and symptoms shared between influenza and COVID-19. We calculated the correlations between influenza and COVID-19 search data for a 1-year period after the first COVID-19 diagnosis in the United States (January 21, 2020 to January 20, 2021). We constructed a seasonal autoregressive integrated moving average model and compared predicted search volumes, using the 4 previous years, with Google Trends relative search volume data. We built a similar model for shared symptoms data. We also assessed correlations for the past 5 years between Google Trends influenza data, US Centers for Diseases Control and Prevention influenza-like illness data, and influenza media coverage data.ResultsWe observed a nonsignificant weak correlation (ρ= –0.171; P=0.23) between COVID-19 and influenza Google Trends data. Influenza search volumes for 2020-2021 distinctly deviated from values predicted by seasonal autoregressive integrated moving average models—for 6 weeks within the first 13 weeks after the first COVID-19 infection was confirmed in the United States, the observed volume of searches was higher than the upper bound of 95% confidence intervals for predicted values. Similar results were observed for shared symptoms with influenza and COVID-19 data. The correlation between Google Trends influenza data and CDC influenza-like-illness data decreased after the emergence of COVID-19 (2020-2021: ρ=0.643; 2019-2020: ρ=0.902), while the correlation between Google Trends influenza data and influenza media coverage volume remained stable (2020-2021: ρ=0.746; 2019-2020: ρ=0.707).ConclusionsRelevant differences were observed between predicted and observed influenza Google Trends data the year after the onset of the COVID-19 pandemic in the United States. Such differences are possibly due to media coverage, suggesting limitations to the use of Google Trends as a flu surveillance tool.     

Impact of the COVID-19 pandemic on pediatric and adolescent vaccinations and well child visits in the United States: A database analysis

BackgroundThe COVID-19 pandemic has disrupted healthcare, including immunization practice and well child visit attendance. Maintaining vaccination coverage is important to prevent disease outbreaks and morbidity. We assessed the impact of the COVID-19 pandemic on pediatric and adolescent vaccination administration and well child visit attendance in the United States.MethodsThis cross-sectional study used IBM MarketScan Commercial Database (IMC) with Early View (healthcare claims database) and TriNetX Dataworks Global Network (electronic medical records database) from January 2018–March 2021. Individuals ≤ 18 years of age who were enrolled during the analysis month of interest (IMC with Early View) or had ≥ 1 health encounter at a participating institution (TriNetX Dataworks) were included. We calculated the monthly percent difference between well child visit attendance and vaccine administration rates for 10 recommended pediatric/adolescent vaccines in 2020 and 2021 compared with 2018–2019. Data were stratified by the age groups 0–2 years, 4–6 years, and 9–16 years.ResultsIn IMC with Early View, the average monthly enrollment for children 0–18 years of age was 5.2 million. In TriNetX Dataworks, 12.2 million eligible individuals were included. Well child visits and vaccinations reached the lowest point in April 2020 compared with 2018–2019. Well child visit attendance and vaccine administration rates were inversely related to age, with initial reductions highest for adolescents and lowest for ages 0–2 years. Rates rebounded in June and September 2020 and stabilized to pre-pandemic levels in Fall 2020. Rates dropped below baseline in early 2021 for groups 0–2 years and 4–6 years.ConclusionsWe found substantial disruptions in well child visit attendance and vaccination administration for children and adolescents during the COVID-19 pandemic in 2020 and early 2021. Continued efforts are needed to monitor recovery and catch up to avoid outbreaks and morbidity associated with vaccine-preventable diseases.     

Trends in COVID-19–Related Medication Use in US Nursing Homes, 2018-2022

ObjectivesLittle is known about how COVID-19 treatment patterns have evolved over time in nursing homes (NHs) despite the devastating effects of COVID-19 in this setting. The aim was to describe changes in COVID-19–related medication use over time among NH residents in the United States.DesignRetrospective cohort study.Setting and ParticipantsThis study used electronic health records (EHR) from 11 different US NH corporations between January 1, 2018, and March 31, 2022.MethodsThe use of medications approved for COVID-19–related conditions or known to be used off-label for COVID-19 during the study period is identified. We described trends in the use of each drug and combined use per 1000 NH residents over calendar time [quarters (Q)].ResultsA total of 59,022 unique residents with the use of an eligible medication were identified. Hydroxychloroquine use sharply increased from 9.8 in 2020Q1 to 30.2 orders per 1000 individuals in 2020Q2. Dexamethasone use increased sharply from 14.8 in 2020Q2 to a peak of 121.9 orders per 1000 individuals in 2020Q4. Azithromycin use increased from 44.1 in 2019Q3 to a peak of 99.9 orders per 1000 individuals in 2020Q4, with a drop in 2020Q3 of 51.3 per 1000 individuals in 2020Q3. Concurrent use of azithromycin and hydroxychloroquine increased sharply from 0.3 in 2020Q1 to 10.6 orders per 1000 residents in 2020Q2 and then drastically decreased to 0.6 per 1000 residents in 2020Q3. Concurrent use of dexamethasone and azithromycin rose considerably from 0.7 in 2020Q2 to 28.2 orders per 1000 residents in 2020Q4.Conclusions and ImplicationsAs in other settings, COVID-19–related medication use in NHs appears to have changed in response to the shifting evidence base and availability of medications during the pandemic. Providers should continue to diligently modify their prescribing as new evidence accrues.     

Explaining the Varying Patterns of COVID-19 Deaths Across the United States: 2-Stage Time Series Clustering Framework

BackgroundSocially vulnerable communities are at increased risk for adverse health outcomes during a pandemic. Although this association has been established for H1N1, Middle East respiratory syndrome (MERS), and COVID-19 outbreaks, understanding the factors influencing the outbreak pattern for different communities remains limited.ObjectiveOur 3 objectives are to determine how many distinct clusters of time series there are for COVID-19 deaths in 3108 contiguous counties in the United States, how the clusters are geographically distributed, and what factors influence the probability of cluster membership.MethodsWe proposed a 2-stage data analytic framework that can account for different levels of temporal aggregation for the pandemic outcomes and community-level predictors. Specifically, we used time-series clustering to identify clusters with similar outcome patterns for the 3108 contiguous US counties. Multinomial logistic regression was used to explain the relationship between community-level predictors and cluster assignment. We analyzed county-level confirmed COVID-19 deaths from Sunday, March 1, 2020, to Saturday, February 27, 2021.ResultsFour distinct patterns of deaths were observed across the contiguous US counties. The multinomial regression model correctly classified 1904 (61.25%) of the counties’ outbreak patterns/clusters.ConclusionsOur results provide evidence that county-level patterns of COVID-19 deaths are different and can be explained in part by social and political predictors.     

Did the Timing of State Mandated Lockdown Affect the Spread of COVID-19 Infection? A County-level Ecological Study in the United States

Objectives:Previous pandemics have demonstrated that several demographic, geographic, and socioeconomic factors may play a role in increased infection risk. During this current coronavirus disease 2019 (COVID-19) pandemic, our aim was to examine the association of timing of lockdown at the county level and aforementioned risk factors with daily case rate (DCR) in the United States.Methods:A cross-sectional study using publicly available data was performed including Americans with COVID-19 infection as of May 24, 2020. The United States counties with >100 000 population and >50 cases per 100 000 people were included. The independent variable was the days required from the declaration of lockdown to reach the target case rate (50/100 000 cases) while the dependent (outcome) variable was the DCR per 100 000 on the day of statistical calculation (May 24, 2020) after adjusting for multiple confounding socio-demographic, geographic, and health-related factors. Each independent factor was correlated with outcome variables and assessed for collinearity with each other. Subsequently, all factors with significant association to the outcome variable were included in multiple linear regression models using stepwise method. Models with best R² value from the multiple regression were chosen.Results:The timing of mandated lockdown order had the most significant association on the DCR per 100 000 after adjusting for multiple socio-demographic, geographic and health-related factors. Additional factors with significant association with increased DCR include rate of uninsured and unemployment.Conclusions:The timing of lockdown order was significantly associated with the spread of COVID-19 at the county level in the United States.     

Declining influenza vaccination rates in an underserved pediatric primary care center during the COVID-19 pandemic

BackgroundInfluenza vaccination rates are decreasing in the United States. Disinformation surrounding COVID-related public health protections and SARS-CoV-2 vaccine roll-out may have unintended consequences impacting pediatric influenza vaccination. We assessed influenza vaccination rates before and during the COVID-19 pandemic in one pediatric primary care center, serving a minoritized population.MethodsA cross-sectional study assessed influenza vaccination rates for children aged 6 months to 12 years over the following influenza seasons (September-May): 1) 2018–19 and 2019–20 (pre-pandemic), and 2) 2020–21 and 2021–22 (intra-pandemic). Demographics and responses to social risk questionnaires were extracted from electronic health records. Total tetanus vaccinations across influenza seasons served as approximations of general vaccination rates. Generalized linear regression models with robust standard errors evaluated differences in demographics, social risks, and influenza vaccination rates by season. Multivariable logistic regression with robust standard errors evaluated associations between influenza season, demographics, social risks, and influenza vaccination.ResultsMost patients were young (mean age ～ 6 years), non-Hispanic Black (～80%), and publicly insured (～90%). Forty-two percent of patients eligible to receive the influenza vaccine who were seen in 2019–20 influenza season received the influenza vaccine, compared to 30% in 2021–22. Influenza and tetanus vaccination rates decreased during the COVID-19 pandemic (p < 0.01). The 2020–21 and 2021–22 influenza seasons, older age, Black race, and self-pay were associated with decreased influenza vaccine administration (p < 0.05).ConclusionsInfluenza vaccination rates within one pediatric primary care center decreased during the COVID-19 pandemic and have not rebounded, particularly for older children, those identifying as Black, and those without insurance.     

Psychological Distress and Heavy Alcohol Consumption Among U.S. Young Women During the COVID-19 Pandemic

IntroductionThe predictors of heavy drinking among U.S. young women during the COVID-19 pandemic are not well-examined. This study aims to determine the prospective relationship between COVID-19 psychological distress and heavy alcohol use among U.S. young adult women.DesignThis study used the COVID-19 Adult Resilience Experiences Study (CARES) data collected from April 13, 2020, to August 31, 2020 (T₁) and September 21, 2020, to March 15, 2021 (T₂). Among the young adults (ages 18–30) who participated in both surveys, a total of 684 identified as women (including transgender women) and were included in the analysis. Three or more drinks as a typical intake were defined as heavy drinking. Psychological distress in T₁ was measured using scores for financial stress, COVID-19–related worry, and COVID-19–related grief. A series of logistic regression analyses were performed to identify risk factors associated with young women's heavy drinking during the pandemic.ResultsTwenty-two and one-half percent of young women reported heavy drinking in a typical intake. After controlling for covariates, women who reported high levels of COVID-19–related grief were more likely to report heavy drinking (odds ratio, 1.06; 95% confidence interval [CI], 1.01–1.13; p < .05). Those with high levels of COVID-19–related worry were less likely to report drinking heavily (odds ratio, 0.90; 95% confidence interval, 0.85–0.97; p < .01).ConclusionsThose who suffer from a deeper sense of COVID-19–related grief are particularly at risk of heavy drinking and should be targeted for outreach and clinical intervention. Further research is necessary to determine the long-term impacts of the pandemic on heavy drinking among young women and should include a more comprehensive assessment of psychological distress.     

Shifting US Patterns of COVID-19 Mortality by Race and Ethnicity From June–December 2020

ObjectivesThe COVID-19 pandemic has disproportionately affected racial and ethnic minorities in the United States and has been devastating for residents of nursing homes (NHs). However, evidence on racial and ethnic disparities in COVID-19–related mortality rates within NHs and how that has changed over time has been limited. This study examines the impact of a high proportion of minority residents in NHs on COVID-19–related mortality rates over a 30-week period.DesignLongitudinal study.Setting and ParticipantsCenters for Medicare & Medicaid Services Nursing Home COVID-19 Public Use File data from 50 states from June 1, 2020, to December 27, 2020.MethodsWe linked data from 11,718 NHs to (1) Nursing Home Compare data, (2) the Long-Term Care: Facts on Care in the U.S., and (3) US county-level data on COVID cases and deaths. Our primary independent variable was proportion of minority residents (blacks and Hispanics) in NHs and its association with mortality rate over time.ResultsDuring the first 6 weeks from June 1, 2020, NHs with a higher proportion of black residents reported more COVID-19 deaths per 1000 followed by NHs with a higher proportion of Hispanic residents. Between 7 and 12 weeks, NHs with a higher proportion of Hispanic residents reported more deaths per 1000, followed by NHs with a higher proportion of black residents. However, after 23 weeks (mid-November 2020), NHs serving a higher proportion of white residents reported more deaths per 1000 than NHs serving a high proportion of black and Hispanic residents.Conclusions and ImplicationsThe disparities in COVID-19–related mortality for nursing homes serving minority residents is evident for the first 12 weeks of our study period. Policy interventions and the equitable distribution of vaccine are required to mitigate the impact of systemic racial injustice on health outcomes of people of color residing in NHs.     

Acceptability of a COVID-19 vaccine among adults in the United States: How many people would get vaccinated?

BackgroundCoronavirus disease 2019 (COVID-19) was declared a pandemic in March 2020. Several prophylactic vaccines against COVID-19 are currently in development, yet little is known about people’s acceptability of a COVID-19 vaccine.MethodsWe conducted an online survey of adults ages 18 and older in the United States (n = 2,006) in May 2020. Multivariable relative risk regression identified correlates of participants’ willingness to get a COVID-19 vaccine (i.e., vaccine acceptability).ResultsOverall, 69% of participants were willing to get a COVID-19 vaccine. Participants were more likely to be willing to get vaccinated if they thought their healthcare provider would recommend vaccination (RR = 1.73, 95% CI: 1.49–2.02) or if they were moderate (RR = 1.09, 95% CI: 1.02–1.16) or liberal (RR = 1.14, 95% CI: 1.07–1.22) in their political leaning. Participants were also more likely to be willing to get vaccinated if they reported higher levels of perceived likelihood getting a COVID-19 infection in the future (RR = 1.05, 95% CI: 1.01–1.09), perceived severity of COVID-19 infection (RR = 1.08, 95% CI: 1.04–1.11), or perceived effectiveness of a COVID-19 vaccine (RR = 1.46, 95% CI: 1.40–1.52). Participants were less likely to be willing to get vaccinated if they were non-Latinx black (RR = 0.81, 95% CI: 0.74–0.90) or reported a higher level of perceived potential vaccine harms (RR = 0.95, 95% CI: 0.92–0.98).ConclusionsMany adults are willing to get a COVID-19 vaccine, though acceptability should be monitored as vaccine development continues. Our findings can help guide future efforts to increase COVID-19 vaccine acceptability (and uptake if a vaccine becomes available).     

Trust in government,intention to vaccinate and COVID-19 vaccine hesitancy: A comparative survey of five large cities in the United States,United Kingdom,and Australia

BackgroundThere is widespread hesitancy towards COVID-19 vaccines in the United States, United Kingdom, and Australia.ObjectiveTo identify predictors of willingness to vaccinate against COVID-19 in five cities with varying COVID-19 incidence in the US, UK, and Australia.DesignOnline, cross-sectional survey of adults from Dynata’s research panel in July-September 2020.Participants, settingAdults aged 18 and over in Sydney, Melbourne, London, New York City, or Phoenix.Main outcomes and measuresWillingness to receive a COVID-19 vaccine; reason for vaccine intention.Statistical methodsTo identify predictors of intention to receive a COVID-19 vaccine, we used Poisson regression with robust error estimation to produce prevalence ratios.ResultsThe proportion willing to receive a COVID-19 vaccine was 70% in London, 71% NYC, 72% in Sydney, 76% in Phoenix, and 78% in Melbourne. Age was the only sociodemographic characteristic that predicted willingness to receive a COVID-19 vaccine in all five cities. In Sydney and Melbourne, participants with high confidence in their current government had greater willingness to receive the vaccine (PR = 1.24; 95% CI = 1.07–1.44 and PR = 1.38; 95% CI = 1.74–1.62), while participants with high confidence in their current government in NYC and Phoenix were less likely to be willing to receive the vaccine (PR = 0.78; 95% CI = 0.72–0.85 and PR = 0.85; 95% CI = 0.76–0.96).LimitationsConsumer panels can be subject to bias and may not be representative of the general population.ConclusionsSuccess for COVID-19 vaccination programs requires high levels of vaccine acceptance. Our data suggests more than 25% of adults may not be willing to receive a COVID-19 vaccine, but many of them were not explicitly anti-vaccination and thus may become more willing to vaccinate over time. Among the three countries surveyed, there appears to be cultural differences, political influences, and differing experiences with COVID-19 that may affect willingness to receive a COVID-19 vaccine.     

Early influenza vaccination rates decline in children during the COVID-19 pandemic

BackgroundThis investigation sought to determine whether early season rates of pediatric influenza vaccination changed in a season when there was a concurrent COVID-19 pandemic.MethodsThis study used cohort and cross sectional data from an academic primary care division in Southcentral Pennsylvania that serves approximately 17,500 patients across 4 practice sites. Early season (prior to November 1) vaccination rates in 2018, 2019 and 2020 were recorded for children, age 6 months to 17 years. To explore the impact of COVID-19 on vaccination, we fit a model with a logit link (estimated via generalized estimating equations to account for clustering by patient over time) on calendar year, adjusted for race, ethnicity, age, and insurance type. We examined interaction effects of demographic covariates with calendar year.ResultsEarly vaccination rates were lower in 2020 (29.7%) compared with 2018 and 2019 (34.2% and 33.3%). After adjusting for covariates and accounting for clustering over time, the odds of early vaccination in 2020 were 19% lower compared to 2018 (OR 0.81, 95% CI: 0.78–0.85). In 2020, children with private insurance were more likely to receive early vaccination than in 2018 (OR 1.51, 95% CI: 1.04–1.15), whereas children with public insurance were less likely to receive early vaccination in 2020 than in 2018 (OR 0.62, 95% CI: 1.38–1.65).ConclusionsEarly influenza vaccination rates declined in a year with a concurrent COVID-19 pandemic. Modeling that accounts for individual trends and demographic variables identified specific populations with lower odds of early vaccination in 2020. Additional research is needed to investigate whether the COVID-19 pandemic impacted parental intent to obtain the influenza vaccine, or introduced barriers to healthcare access.     

Racial/Ethnic Differences in Risk Factors Associated With Severe COVID-19 Among Older Adults With ADRD

ObjectiveTo examine racial/ethnic differences in risk factors, and their associations with COVID-19–related outcomes among older adults with Alzheimer’s disease and related dementias (ADRD).DesignObservational study.Setting and ParticipantsNational Medicare claims data and the Minimum Data Set 3.0 from April 1, 2020, to December 31, 2020, were linked in this study. We included community-dwelling fee-for-service Medicare beneficiaries with ADRD, diagnosed with COVID-19 between April 1, 2020, and December 1, 2020 (N = 138,533).MethodsTwo outcome variables were defined: hospitalization within 14 days and death within 30 days of COVID-19 diagnosis. We obtained information on individual sociodemographic characteristics, chronic conditions, and prior health care utilization based on the Medicare claims and the Minimum Dataset. Machine learning methods, including lasso regression and discriminative pattern mining, were used to identify risk factors in racial/ethnic subgroups (ie, White, Black, and Hispanic individuals). The associations between identified risk factors and outcomes were evaluated using logistic regression and compared across racial/ethnic subgroups using the coefficient comparison approach.ResultsWe found higher risks of COVID-19–related outcomes among Black and Hispanic individuals. The areas under the curve of the models with identified risk factors were 0.65 to 0.68 for mortality and 0.61 to 0.62 for hospitalization across racial/ethnic subgroups. Although some identified risk factors (eg, age, gender) for COVID-19–related outcomes were common among all racial/ethnic subgroups, other risk factors (eg, hypertension, obesity) varied by racial/ethnic subgroups. Furthermore, the associations between some common risk factors and COVID-19–related outcomes also varied by race/ethnicity. Being male was related to 138.2% (95% CI: 1.996–2.841), 64.7% (95% CI: 1.546–1.755), and 37.1% (95% CI: 1.192–1.578) increased odds of death among Hispanic, White, and Black individuals, respectively. In addition, the racial/ethnic disparity in COVID-19–related outcomes could not be completely explained by the identified risk factors.Conclusions and ImplicationsRacial/ethnic differences were detected in the likelihood of having COVID-19–related outcomes, specific risk factors, and relationships between specific risk factors and COVID-19–related outcomes. Future research is needed to elucidate the reasons for these differences.     

Estimating COVID-19 Hospitalizations in the United States With Surveillance Data Using a Bayesian Hierarchical Model: Modeling Study

BackgroundIn the United States, COVID-19 is a nationally notifiable disease, meaning cases and hospitalizations are reported by states to the Centers for Disease Control and Prevention (CDC). Identifying and reporting every case from every facility in the United States may not be feasible in the long term. Creating sustainable methods for estimating the burden of COVID-19 from established sentinel surveillance systems is becoming more important.ObjectiveWe aimed to provide a method leveraging surveillance data to create a long-term solution to estimate monthly rates of hospitalizations for COVID-19.MethodsWe estimated monthly hospitalization rates for COVID-19 from May 2020 through April 2021 for the 50 states using surveillance data from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) and a Bayesian hierarchical model for extrapolation. Hospitalization rates were calculated from patients hospitalized with a lab-confirmed SARS-CoV-2 test during or within 14 days before admission. We created a model for 6 age groups (0-17, 18-49, 50-64, 65-74, 75-84, and ≥85 years) separately. We identified covariates from multiple data sources that varied by age, state, and month and performed covariate selection for each age group based on 2 methods, Least Absolute Shrinkage and Selection Operator (LASSO) and spike and slab selection methods. We validated our method by checking the sensitivity of model estimates to covariate selection and model extrapolation as well as comparing our results to external data.ResultsWe estimated 3,583,100 (90% credible interval [CrI] 3,250,500-3,945,400) hospitalizations for a cumulative incidence of 1093.9 (992.4-1204.6) hospitalizations per 100,000 population with COVID-19 in the United States from May 2020 through April 2021. Cumulative incidence varied from 359 to 1856 per 100,000 between states. The age group with the highest cumulative incidence was those aged ≥85 years (5575.6; 90% CrI 5066.4-6133.7). The monthly hospitalization rate was highest in December (183.7; 90% CrI 154.3-217.4). Our monthly estimates by state showed variations in magnitudes of peak rates, number of peaks, and timing of peaks between states.ConclusionsOur novel approach to estimate hospitalizations for COVID-19 has potential to provide sustainable estimates for monitoring COVID-19 burden as well as a flexible framework leveraging surveillance data.     

Prevention Measures for COVID-19 and Changes in Kawasaki Disease Incidence

BackgroundKawasaki disease is suspected to be triggered by previous infection. The prevention measures for coronavirus disease 2019 (COVID-19) have reportedly reduced transmission of certain infectious diseases. Under these circumstances, the prevention measures for COVID-19 may reduce the incidence of Kawasaki disease.MethodsWe conducted a retrospective study using registration datasets of patients with Kawasaki disease who were diagnosed in all 11 inpatient pediatric facilities in Yamanashi Prefecture. The eligible cases were 595 cases that were diagnosed before the COVID-19 pandemic (from January 2015 through February 2020) and 38 cases that were diagnosed during the COVID-19 pandemic (from March through November 2020). Incidence of several infectious disease were evaluated using data from the Infectious Disease Weekly Report conducted by the National Institute of Infectious Diseases.ResultsEpidemics of various infectious diseases generally remained at low levels during the first 9 months (March through November 2020) of the COVID-19 pandemic. Moreover, the incidence of COVID-19 was 50–80 times lower than the incidence in European countries and the United States. The total number of 38 cases with Kawasaki disease for the 9 months during the COVID-19 pandemic was 46.3% (−3.5 standard deviations [SDs] of the average [82.0; SD, 12.7 cases] for the corresponding 9 months of the previous 5 years. None of the 38 cases was determined to be triggered by COVID-19 based on their medical histories and negative results of severe acute respiratory syndrome coronavirus 2 testing at admission.ConclusionThese observations provide a new epidemiological evidence for the notion that Kawasaki disease is triggered by major infectious diseases in children.Key words: COVID-19, Kawasaki disease, retrospective database, infectious disease     

Remote Infection Control Assessments of US Nursing Homes During the COVID-19 Pandemic,April to June 2020

BackgroundNursing homes (NHs) provide care in a congregate setting for residents at high risk of severe outcomes from SARS-CoV-2 infection. In spring 2020, NHs were implementing new guidance to minimize SARS-CoV-2 spread among residents and staff.ObjectiveTo assess whether telephone and video-based infection control assessment and response (TeleICAR) strategies could efficiently assess NH preparedness and help resolve gaps.DesignWe incorporated Centers for Disease Control and Prevention COVID-19 guidance for NH into an assessment tool covering 6 domains: visitor restrictions; health care personnel COVID-19 training; resident education, monitoring, screening, and cohorting; personal protective equipment supply; core infection prevention and control (IPC); and communication to public health. We performed TeleICAR consultations on behalf of health departments. Adherence to each element was documented and recommendations provided to the facility.Setting and ParticipantsHealth department–referred NHs that agreed to TeleICAR consultation.MethodsWe assessed overall numbers and proportions of NH that had not implemented each infection control element (gap) and proportion of NH that reported making ≥1 change in practice following the assessment.ResultsDuring April 13 to June 12, 2020, we completed TeleICAR consultations in 629 NHs across 19 states. Overall, 524 (83%) had ≥1 implementation gap identified; the median number of gaps was 2 (interquartile range: 1-4). The domains with the greatest number of facilities with gaps were core IPC practices (428/625; 68%) and COVID-19 education, monitoring, screening, and cohorting of residents (291/620; 47%).Conclusions and ImplicationsTeleICAR was an alternative to onsite infection control assessments that enabled public health to efficiently reach NHs across the United States early in the COVID-19 pandemic. Assessments identified widespread gaps in core IPC practices that put residents and staff at risk of infection. TeleICAR is an important strategy that leverages infection control expertise and can be useful in future efforts to improve NH IPC.     

COVID-19 vaccine perceptions and hesitancy amongst parents of school-aged children during the pediatric vaccine rollout

BackgroundThe United States has the highest number of total cases and deaths due to coronavirus disease 2019 (COVID-19) worldwide (Johns Hopkins COVID Dashboard, 2021). Despite COVID-19 vaccine availability, uptake in the United States has been slow and vaccine hesitancy has been a significant barrier to achieving widespread vaccine uptake. Understanding determinants of vaccine acceptance is essential to implement successful population health interventions to increase COVID-19 vaccination.MethodsWe developed an anonymous cross-sectional parent survey to assess factors associated with parent and child COVID-19 vaccine acceptance and hesitancy during the initial pediatric vaccine rollout amongst adolescents 16 years +. The survey was sent via email to 25,308 parents registered to the Alachua County Public School System in May 2021 and remained active until July 2021.FindingsThere were a total of 2,620 survey responses. Overall, 31.5 % of parents with children ages 16 years + reported their child had received the COVID-19 vaccine, 65.2 % reported their (eligible) child had not received the vaccine, and 3.3 % reported their child was scheduled for the vaccine. A majority of parents (60.9 %) reported they planned to vaccinate all of their children once the COVID-19 vaccine was available for their children’s age. COVID-19 vaccine uptake in adolescents ages 16 + reported by Hispanic and White parents was two times higher than that reported by Black parents. Parent COVID-19 and influenza vaccine uptake were associated with increased child COVID-19 vaccination. The most commonly reported reasons why parents chose not to have their child vaccinated against COVID-19 were concerns about long–term negative side effects (75.7 %) and a negative reaction (56.5 %). Medical providers were reported as the most trusted source of information.ConclusionOur study provides insight into determinants of vaccine acceptance, vaccine hesitancy, and trusted sources of information that may be helpful to develop targeted interventions to increase youth COVID-19 vaccination.     

The Impact of Funding Inpatient Treatments for COVID-19 on Health Equity in the United States: A Distributional Cost-Effectiveness Analysis

ObjectivesWe conducted a distributional cost-effectiveness analysis (DCEA) to evaluate how Medicare funding of inpatient COVID-19 treatments affected health equity in the United States.MethodsA DCEA, based on an existing cost-effectiveness analysis model, was conducted from the perspective of a single US payer, Medicare. The US population was divided based on race and ethnicity (Hispanic, non-Hispanic black, and non-Hispanic white) and county-level social vulnerability index (5 quintile groups) into 15 equity-relevant subgroups. The baseline distribution of quality-adjusted life expectancy was estimated across the equity subgroups. Opportunity costs were estimated by converting total spend on COVID-19 inpatient treatments into health losses, expressed as quality-adjusted life-years (QALYs), using base-case assumptions of an opportunity cost threshold of $150 000 per QALY gained and an equal distribution of opportunity costs across equity-relevant subgroups.ResultsMore socially vulnerable populations received larger per capita health benefits due to higher COVID-19 incidence and baseline in-hospital mortality. The total direct medical cost of inpatient COVID-19 interventions in the United States in 2020 was estimated at $25.83 billion with an estimated net benefit of 735 569 QALYs after adjusting for opportunity costs. Funding inpatient COVID-19 treatment reduced the population-level burden of health inequality by 0.234%. Conclusions remained robust across scenario and sensitivity analyses.ConclusionsTo the best of our knowledge, this is the first DCEA to quantify the equity implications of funding COVID-19 treatments in the United States. Medicare funding of COVID-19 treatments in the United States could improve overall health while reducing existing health inequalities.     

Telehealth Demand Trends During the COVID-19 Pandemic in the Top 50 Most Affected Countries: Infodemiological Evaluation

BackgroundThe COVID-19 pandemic has led to urgent calls for the adoption of telehealth solutions. However, public interest and demand for telehealth during the pandemic remain unknown.ObjectiveWe used an infodemiological approach to estimate the worldwide demand for telehealth services during COVID-19, focusing on the 50 most affected countries and comparing the demand for such services with the level of information and communications technology (ICT) infrastructure available.MethodsWe used Google Trends, the Baidu Index (China), and Yandex Keyword Statistics (Russia) to extract data on worldwide and individual countries’ telehealth-related internet searches from January 1 to July 7, 2020, presented as relative search volumes (RSV; range 0-100). Daily COVID-19 cases and deaths were retrieved from the World Health Organization. Individual countries’ ICT infrastructure profiles were retrieved from the World Economic Forum Report.ResultsAcross the 50 countries, the mean RSV was 18.5 (SD 23.2), and the mean ICT index was 62.1 (SD 15.0). An overall spike in worldwide telehealth-related RSVs was observed from March 11, 2020 (RSV peaked to 76.0), which then tailed off in June-July 2020 (mean RSV for the period was 25.8), but remained higher than pre-March RSVs (mean 7.29). By country, 42 (84%) manifested increased RSVs over the evaluation period, with the highest observed in Canada (RSV=100) and the United States (RSV=96). When evaluating associations between RSV and the ICT index, both the United States and Canada demonstrated high RSVs and ICT scores (≥70.3). In contrast, European countries had relatively lower RSVs (range 3.4-19.5) despite high ICT index scores (mean 70.3). Several Latin American (Brazil, Chile, Colombia) and South Asian (India, Bangladesh, Pakistan) countries demonstrated relatively higher RSVs (range 13.8-73.3) but low ICT index scores (mean 44.6), indicating that the telehealth demand outstrips the current ICT infrastructure.ConclusionsThere is generally increased interest and demand for telehealth services across the 50 countries most affected by COVID-19, highlighting the need to scale up telehealth capabilities, during and beyond the pandemic.     

Influenza vaccination uptake among Canadian adults before and during the COVID-19 pandemic: An analysis of the Canadian Longitudinal study on Aging (CLSA)

IntroductionUnderstanding how influenza vaccine uptake changed during the 2020/2021 influenza season compared to previous pre-pandemic seasons is a key priority, as is identifying the relationship between prior influenza vaccination and COVID-19 vaccine willingness.MethodsWe analyzed data from a large, nationally representative cohort of Canadian residents aged 50 and older to assess influenza vaccination status three times between 2015 and 2020. We investigated: 1) changes in self-reported influenza vaccine uptake, 2) predictors of influenza vaccine uptake in 2020/2021, and 3) the association between influenza vaccination history and self-reported COVID-19 vaccine willingness using logistic regression models.ResultsAmong 23,385 participants analyzed for aims 1–2, influenza vaccination increased over time: 14,114 (60.4%) in 2015–2018, 15,692 (67.1%) in 2019/2020, and 19,186 (82.0%; combining those already vaccinated and those planning to get a vaccine) in 2020/2021. After controlling for socio-demographics, history of influenza vaccination was most strongly associated with influenza vaccination in 2020/2021 (adjusted odds ratio [aOR] 147.9 [95% CI: 120.9–180.9]); this association remained after accounting for multiple health and pandemic-related factors (aOR 140.3 [95% CI: 114.5–171.8]). To a lesser degree, those more concerned about COVID-19 were also more likely to report influenza vaccination in fall 2020, whereas those reporting a very negative impact of the pandemic were less likely to get vaccinated. Among 23,819 participants with information on COVID-19 vaccine willingness during the last quarter of 2020 (aim 3), prior influenza vaccination was most strongly associated with willingness to get a COVID-19 vaccine (aOR 15.1 [95% CI: 13.5–16.8] for those who had received influenza vaccine at all previous timepoints versus none).ConclusionsOur analysis highlights the importance of previous vaccination in driving vaccination uptake and willingness. Efforts to increase vaccination coverage for influenza and COVID-19 should target individuals who do not routinely engage with immunization services regardless of demographic factors.