Distinguishing features of Long COVID identified through immune profiling

SARS-CoV-2 infection can result in the development of a constellation of persistent sequelae following acute disease called post-acute sequelae of COVID-19 (PASC) or Long COVID1-3. Individuals diagnosed with Long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions1-3; however, the basic biological mechanisms responsible for these debilitating symptoms are unclear. Here, 215 individuals were included in an exploratory, cross-sectional study to perform multi-dimensional immune phenotyping in conjunction with machine learning methods to identify key immunological features distinguishing Long COVID. Marked differences were noted in specific circulating myeloid and lymphocyte populations relative to matched control groups, as well as evidence of elevated humoral responses directed against SARS-CoV-2 among participants with Long COVID. Further, unexpected increases were observed in antibody responses directed against non-SARS-CoV-2 viral pathogens, particularly Epstein-Barr virus. Analysis of circulating immune mediators and various hormones also revealed pronounced differences, with levels of cortisol being uniformly lower among participants with Long COVID relative to matched control groups. Integration of immune phenotyping data into unbiased machine learning models identified significant distinguishing features critical in accurate classification of Long COVID, with decreased levels of cortisol being the most significant individual predictor. These findings will help guide additional studies into the pathobiology of Long COVID and may aid in the future development of objective biomarkers for Long COVID.

Prevalence of Chronic Diseases, Depression, and Stress among U.S. Child Care Professionals during the COVID-19 Pandemic

ImportanceThere is no published national research reporting child care professionals physical health, depression, or stress during the COVID-19 pandemic. Given their central role in supporting childrens development, child care professionals overall physical and mental health is important. ObjectivesTo evaluate the prevalence of chronic diseases, depression, and stress levels during the COVID-19 pandemic among U.S. child care professionals. DesignIn this large-scale national survey, data were collected through an online survey from May 22, 2020 to June 8, 2020. We analyzed the association of sociodemographic characteristics with four physical health conditions (asthma, heart disease, diabetes, and obesity), depression, and stress weighted to national representativeness. Sociodemographic characteristics included race, ethnicity, age, gender, medical insurance status, and child care type. SettingCenter- and home-based child care. ParticipantsChild care professionals (n = 81,682) from all U.S. states and the District of Columbia. ResultsMean age was 42.1 years (standard deviation = 14.1); 96.0% (n = 78,725) were female, 2.5% (n = 2,033) were male, and 0.3% (n = 225) were non-binary. For physical health conditions, 14.3% (n = 11,717) reported moderate to severe asthma, 6.5% (n = 5,317) diabetes, 4.9% (n = 3,971) heart disease, and 19.8% (n = 16,207) being obese. Regarding mental health, 45.7% (n = 37,376) screened positive for depression and 66.5% (n = 54,381) reported moderate to high stress levels. Race, ethnicity, and gender disparities were evidenced for physical health conditions of child care professionals, but not for mental health during the pandemic. Conclusions and RelevanceOur findings highlight that child care professionals depression rates during the pandemic were much higher than before the pandemic, and depression, stress and asthma rates were higher than U.S. adult depression rates during the pandemic. Given the essential work child care professionals provide during the pandemic, policy makers and public health officials should consider what can be done to support the physical and mental health of child care professionals. Key PointsO_ST_ABSQuestionC_ST_ABSWhat is the prevalence of chronic diseases, depression, and stress among U.S. child care professionals during the COVID-19 pandemic? FindingsIn this survey of 81,682 U.S. child care professionals, 14.3% reported moderate to severe asthma, 6.5% diabetes, 4.9% heart disease, 19.8% being obese, 45.7% screening positive for depression, and 66.5% moderate to high stress levels. MeaningDuring the pandemic, child care professionals reported depression rates much higher than before the pandemic, and asthma, stress, and depression much greater than U.S. adult estimates, highlighting a need for effective supports for the wellbeing of this essential workforce.

COVID-19 Vaccine Uptake among U.S. Child Care Providers

STRUCUTRED ABSTRACTO_ST_ABSObjectivesC_ST_ABSEnsuring a high COVID-19 vaccine uptake among U.S. child care providers is crucial to mitigating the public health implications of child-to-staff and staff-to-child transmission of SARS-CoV-2; however, the vaccination rate among this group is unknown. MethodsTo characterize the vaccine uptake among U.S. child care providers, we conducted a cross-sectional survey of the child care workforce. Providers were identified through various national databases and state registries. A link to the survey was sent via email between May 26 and June 23, 2021. Out of 44,771 potential respondents, 21,663 responded (48.4%). ResultsOverall COVID-19 vaccine uptake among U.S. child care providers (78.1%, 95% CI [77.3% to 78.9%]) was higher than that of the U.S. adult population (65%). Vaccination rates varied from 53.5% to 89.4% between states. Vaccine uptake differed significantly (p < .01) based on respondent age (70.0% for ages 25-34, 91.5% for ages 75-84), race (70.0% for Black or African Americans, 92.5% for Asian-Americans), annual household income (70.7% for <$35,000, 85.0% for>$75,000), and childcare setting (72.9% for home-based, 79.7% for center-based). ConclusionsCOVID-19 vaccine uptake among U.S. child care providers was higher than that of the general U.S. adult population. Those who were younger, lower income, Black or African American, resided in states either in the Mountain West or the South, and/or worked in home-based childcare programs reported the lowest rates of vaccination; state public health leaders and lawmakers should prioritize these subgroups for placement on the policy agenda to realize the largest gains in vaccine uptake among providers. Tables of Contents SummaryThis article describes the results of a national survey of childcare providers to determine the overall COVID-19 vaccine uptake and the gaps in vaccine coverage. Whats Known on This SubjectEnsuring a high COVID-19 vaccine uptake among U.S. child care providers is crucial to mitigating the public health implications of child-to-staff and staff-to-child transmission of SARS-CoV-2; however, the vaccination rate among this group is unknown. What This Study AddsWhile the vaccine uptake among U.S. child care providers was higher than that of U.S. adults, certain subgroups continue to warrant focused attention for outreach and/or placement on the policy agenda.

COVID-19 Vaccine Acceptance and Hesitancy in Low and Middle Income Countries, and Implications for Messaging

We analyze COVID-19 vaccine acceptance across 15 survey samples covering ten low- and middle-income countries (LMICs) in Asia, Africa, and South America, Russia (an upper-middle-income country), and the United States, using survey responses from 44,260 individuals. We find considerably higher willingness to take a COVID-19 vaccine in LMIC samples (80% on average) compared to the United States (65%) and Russia (30%). Vaccine acceptance was primarily explained by an interest in personal protection against COVID-19, while concern about side effects was the most commonly expressed reason for reluctance. Health workers were the most trusted sources of information about COVID-19 vaccines. Our findings suggest that prioritizing vaccine distribution to LMICs should yield high returns in promoting global immunization coverage, and that vaccination campaigns in these countries should focus on translating acceptance into uptake. Messaging highlighting vaccine efficacy and safety, delivered by healthcare workers, may be most effective in addressing remaining hesitancy.

Beliefs about Mask Efficacy and the Effect of Social Norms on Mask Wearing Intentions for COVID-19 Risk Reduction

In the absence of widespread vaccination for COVID-19, governments and public health officials have advocated for the public to wear masks during the pandemic. The decision to wear a mask in public is likely affected by both beliefs about its efficacy and the prevalence of the behavior. Greater mask use in the community may encourage others to follow this norm, but it also creates an incentive for individuals to free ride on the protection afforded to them by others. We report the results of two vignette-based experiments conducted in the United States and Italy to examine the causal relationship between beliefs, social norms, and reported intentions to engage in mask promoting behavior. We find that providing factual information about how masks protect others increases the likelihood that someone would wear a mask or encourage others to do so in the United States, but not in Italy. There is no effect of providing information about how masks protect the wearer in either country. Additionally, greater mask use increases intentions to wear a mask and encourage someone else to wear theirs properly in both the United States and Italy. Thus, community mask use may be self-reinforcing.

National interest may require distributing COVID-19 vaccines to other countries

As the clinical trials for COVID-19 vaccine progress, understanding how to distribute the initially scarce doses is of paramount importance and a quantitative analysis of the trade-offs involved in domestic-only versus cooperative distribution is still missing. In this study we use a network Susceptible-Infected-Removed (SIR) model to show under which circumstances it is in a countrys self-interest to ensure other countries can also obtain a COVID-19 vaccine rather than focusing only on vaccination of their own residents. In particular, we focus our analysis on the USs decision and estimate the internal burden of COVID-19 disease under different scenarios about vaccine cooperation. We show that in scenarios in which the US has reached the threshold for domestic herd immunity, the US may find it optimal to donate doses to other countries with lower vaccination coverage, as this would allow for a sharp reduction in the inflow of infected individuals from abroad.

Modeling Dynamic Network Strategies for SARS-CoV-2 Control on a Cruise Ship

SARS-CoV-2 outbreaks have occurred on several nautical vessels, driven by the high-density contact networks on these ships. Optimal strategies for prevention and control that account for realistic contact networks are needed. We developed a network-based transmission model for SARS-CoV-2 on the Diamond Princess outbreak to characterize transmission dynamics and to estimate the epidemiological impact of outbreak control and prevention measures. This model represented the dynamic multi-layer network structure of passenger-passenger, passengercrew, and crew-crew contacts, both before and after the large-scale network lockdown imposed on the ship in response to the disease outbreak. Model scenarios evaluated variations in the timing of the network lockdown, reduction in contact intensity within the sub-networks, and diagnosis-based case isolation on outbreak prevention. We found that only extreme restrictions in contact patterns during network lockdown and idealistic clinical response scenarios could avert a major COVID-19 outbreak. Contact network changes associated with adequate outbreak prevention were the restriction of passengers to their cabins, with limited passenger-crew contacts. Clinical response strategies required for outbreak prevention included early mass screening with an ideal PCR test (100% sensitivity) and immediate case isolation upon diagnosis. Public health restrictions on optional leisure activities like these should be considered until longer-term effective solutions such as a COVID-19 vaccine become widely available.

COVID-19 Risk Perception Among U.S. Adults: Changes from February to May 2020

The COVID-19 pandemic continues to detrimentally impact the United States. Using a survey, we collected demographic and COVID-19 risk perception, behavior, knowledge, and attitude data from 672 adults across the U.S. in May 2020. These variables were compared with the results from a survey in February 2020. Participants who were older (55+ years; M = 6.3, SD = 2.0), identified as Native American/Alaska Native (M = 6.8, SD = 1.0) or Asian (M = 6.0, SD = 2.0), and those who had contracted (M = 6.8, SD = 2.0) or knew someone who had contracted COVID-19 (M = 6.2, SD = 1.7) reported higher perceived risk. Health behaviors, such as physical distancing, have shown to impact infectious disease trajectories. As the U.S. reopens its economy, public health officials and politicians must formulate culturally appropriate and evidence-based messaging and policies, based on the publics COVID-19 risk perceptions, to encourage preventive behaviors.

Aligning SARS-CoV-2 Indicators via an Epidemic Model: Application to Hospital Admissions and RNA Detection in Sewage Sludge

Ascertaining the state of coronavirus outbreaks is crucial for public health decision-making. Absent repeated representative viral test samples in the population, public health officials and researchers alike have relied on lagging indicators of infection to make inferences about the direction of the outbreak and attendant policy decisions. Recently researchers have shown that SARS-CoV-2 RNA can be detected in municipal sewage sludge with measured RNA concentrations rising and falling suggestively in the shape of an epidemic curve while providing an earlier signal of infection than hospital admissions data. The present paper presents a SARS-CoV-2 epidemic model to serve as a basis for estimating the incidence of infection, and shows mathematically how modeled transmission dynamics translate into infection indicators by incorporating probability distributions for indicator-specific time lags from infection. Hospital admissions and SARS-CoV-2 RNA in municipal sewage sludge are simultaneously modeled via maximum likelihood scaling to the underlying transmission model. The results demonstrate that both data series plausibly follow from the transmission model specified, provide a direct estimate of the reproductive number R0 = 2.38, and suggest that the detection of viral RNA in sewage sludge leads hospital admissions by 4.6 days on average.

Determinants of COVID-19 Vaccine Acceptance in the U.S.

BackgroundThe COVID-19 pandemic continues to adversely affect the U.S., which leads globally in total cases and deaths. As COVID-19 vaccines are under development, public health officials and policymakers need to create strategic vaccine-acceptance messaging to effectively control the pandemic and prevent thousands of additional deaths. MethodsUsing an online platform, we surveyed the U.S. adult population in May 2020 to understand risk perceptions about the COVID-19 pandemic, acceptance of a COVID-19 vaccine, and trust in sources of information. These factors were compared across basic demographics. FindingsOf the 672 participants surveyed, 450 (67%) said they would accept a COVID-19 vaccine if it is recommended for them. Males (72%), older adults ([≥]55 years; 78%), Asians (81%), and college and/or graduate degree holders (75%) were more likely to accept the vaccine. When comparing reported influenza vaccine uptake to reported acceptance of the COVID-19 vaccine: 1) participants who did not complete high school had a very low influenza vaccine uptake (10%), while 60% of the same group said they would accept the COVID-19 vaccine; 2) unemployed participants reported lower influenza uptake and lower COVID-19 vaccine acceptance when compared to those employed or retired; and, 3) black Americans reported lower influenza vaccine uptake and lower COVID-19 vaccine acceptance than nearly all other racial groups. Lastly, we identified geographic differences with Department of Health and Human Services regions 2 (New York) and 5 (Chicago) reporting less than 50 percent COVID-19 vaccine acceptance. InterpretationAlthough our study found a 67% acceptance of a COVID-19 vaccine, there were noticeable demographic and geographical disparities in vaccine acceptance. Before a COVID-19 vaccine is introduced to the U.S., public health officials and policymakers must prioritize effective COVID-19 vaccine-acceptance messaging for all Americans, especially those who are most vulnerable. FundingThe study was funded by the Yale Institute for Global Health.

SARS-CoV-2 RNA concentrations in primary municipal sewage sludge as a leading indicator of COVID-19 outbreak dynamics

We report a time course of SARS-CoV-2 RNA concentrations in primary sewage sludge during the Spring COVID-19 outbreak in a northeastern U.S. metropolitan area. SARS-CoV-2 RNA was detected in all environmental samples, and when adjusted for the time lag, the virus RNA concentrations tracked the COVID-19 epidemiological curve. SARS-CoV-2 RNA concentrations were a leading indicator of community infection ahead of compiled COVID-19 testing data and local hospital admissions. Decisions to implement or relax public health measures and restrictions require timely information on outbreak dynamics in a community.

Measuring voluntary social distancing behavior during the COVID-19 pandemic

Staying home and avoiding unnecessary contact is an important part of the effort to contain COVID-19 and limit deaths. Every state in the United States enacted policies to encourage distancing, and some mandated staying home. Understanding how these policies interact with individuals voluntary responses to the COVID-19 epidemic is critical for estimating the transmission dynamics of the pathogen and assessing the impact of policies. We use the variation in policy responses along with smart device data, which measures the amount of time Americans stayed home, to show that there was substantial voluntary avoidance behavior. We disentangle the extent to which observed shifts in behavior are induced by policy and find evidence of a non-trivial voluntary response to local reported COVID-19 cases and deaths, such that around 45 cases in a home county is associated with the same amount of time at home as a stay-at-home order. People responded to the risk of contracting COVID-19 and to policy orders, though the response to policy orders crowds out or displaces a large share of the voluntary response, suggesting that, during early stages of the U.S. outbreak, better compliance with social distancing recommendations could have been achieved with policy crafted to complement voluntary behavior. Significance StatementAmericans are spending substantially more time at home to reduce the spread of COVID-19. This behavioral shift is a mix of voluntary disease avoidance and policy-induced behavioral changes. Both need to be accounted for. Disentangling voluntary from policy-induced behavioral changes is critical for governments relaxing or renewing restrictions. A substantial share of the behavioral response appears to be voluntary, but this behavior was offset by strong stay-at-home orders. Local testing and rapid reporting is a first step to making better use of voluntary behavioral changes.

Influenza-Negative Influenza-Like Illness (fnILI) Z-Score as a Proxy for Incidence and Mortality of COVID-19

Though ideal for determining the burden of disease, SARS-CoV2 test shortages preclude its implementation as a robust surveillance system in the US. We correlated the use of the derivative influenza-negative influenza-like illness (fnILI) z-score from the CDC as a proxy for incident cases and disease-specific deaths. For every unit increase of fnILI z-score, the number of cases increased by 70.2 (95%CI[5.1,135.3]) and number of deaths increased by 2.1 (95%CI[1.0,3.2]). FnILI data may serve as an accurate outcome measurement to track the spread of the and allow for informed and timely decision-making on public health interventions.

Perceptions of the Adult US Population regarding the Novel Coronavirus Outbreak

BackgroundCOVID-19 outbreak is spreading globally. Although the risk of infection in the US is currently low, it is important to understand the public perception of risk and trust in sources of information to better inform public health messaging. In this study, we surveyed the adult US population to understand their risk perceptions about the COVID-19 outbreak. Methods and FindingsWe used an online platform to survey 718 adults in the US in early February 2020 using a questionnaire that we developed. Our sample was fairly similar to the general adult US population in terms of age, gender, race, ethnicity and education. We found that 69% of the respondents wanted the scientific/public health leadership (either the CDC Director or NIH Director) to lead the US response to COVID-19 outbreak as compared to 14% who wanted the political leadership (either the president or the Congress) to lead the response. Risk perception was low (median score of 5 out of 10) with the respondents trusting health professionals and health officials for information on COVID-19. Majority of the respondents were in favor of strict infection prevention policies to control the outbreak. ConclusionGiven our results, the public health/scientific leadership should be at the forefront of the COVID-19 response to promote trust.