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Simultaneously tracking the global impact of COVID-19 is challenging because of regional variation in resources and reporting. Leveraging self-reported survey outcomes via an existing international social media network has the potential to provide standardized data streams to support monitoring and decision-making worldwide, in real time, and with limited local resources. The University of Maryland Global COVID-19 Trends and Impact Survey (UMD-CTIS), in partnership with Facebook, has invited daily cross-sectional samples from the social media platform's active users to participate in the survey since its launch on April 23, 2020. We analyzed UMD-CTIS survey data through December 20, 2020, from 31,142,582 responses representing 114 countries/territories weighted for nonresponse and adjusted to basic demographics. We show consistent respondent demographics over time for many countries/territories. Machine Learning models trained on national and pooled global data verified known symptom indicators. COVID-like illness (CLI) signals were correlated with government benchmark data. Importantly, the best benchmarked UMD-CTIS signal uses a single survey item whereby respondents report on CLI in their local community. In regions with strained health infrastructure but active social media users, we show it is possible to define COVID-19 impact trajectories using a remote platform independent of local government resources. This syndromic surveillance public health tool is the largest global health survey to date and, with brief participant engagement, can provide meaningful, timely insights into the global COVID-19 pandemic at a local scale.
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COVID-19/epidemiologia , Vigilância em Saúde Pública/métodos , Mídias Sociais , COVID-19/diagnóstico , Teste para COVID-19 , Estudos Transversais , Métodos Epidemiológicos , Humanos , Internacionalidade , Aprendizado de Máquina , Pandemias/estatística & dados numéricosRESUMO
OBJECTIVE: Rapid-onset Obesity with Hypothalamic Dysfunction, Hypoventilation and Autonomic Dysregulation (ROHHAD), is a severe pediatric disorder of uncertain etiology resulting in hypothalamic dysfunction and frequent sudden death. Frequent co-occurrence of neuroblastic tumors have fueled suspicion of an autoimmune paraneoplastic neurological syndrome (PNS); however, specific anti-neural autoantibodies, a hallmark of PNS, have not been identified. Our objective is to determine if an autoimmune paraneoplastic etiology underlies ROHHAD. METHODS: Immunoglobulin G (IgG) from pediatric ROHHAD patients (n = 9), non-inflammatory individuals (n = 100) and relevant pediatric controls (n = 25) was screened using a programmable phage display of the human peptidome (PhIP-Seq). Putative ROHHAD-specific autoantibodies were orthogonally validated using radioactive ligand binding and cell-based assays. Expression of autoantibody targets in ROHHAD tumor and healthy brain tissue was assessed with immunohistochemistry and mass spectrometry, respectively. RESULTS: Autoantibodies to ZSCAN1 were detected in ROHHAD patients by PhIP-Seq and orthogonally validated in 7/9 ROHHAD patients and 0/125 controls using radioactive ligand binding and cell-based assays. Expression of ZSCAN1 in ROHHAD tumor and healthy human brain tissue was confirmed. INTERPRETATION: Our results support the notion that tumor-associated ROHHAD syndrome is a pediatric PNS, potentially initiated by an immune response to peripheral neuroblastic tumor. ZSCAN1 autoantibodies may aid in earlier, accurate diagnosis of ROHHAD syndrome, thus providing a means toward early detection and treatment. This work warrants follow-up studies to test sensitivity and specificity of a novel diagnostic test. Last, given the absence of the ZSCAN1 gene in rodents, our study highlights the value of human-based approaches for detecting novel PNS subtypes. ANN NEUROL 2022;92:279-291.
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Doenças do Sistema Nervoso Autônomo , Doenças do Sistema Endócrino , Doenças Hipotalâmicas , Síndromes Paraneoplásicas do Sistema Nervoso , Autoanticorpos , Criança , Humanos , Doenças Hipotalâmicas/genética , Hipoventilação/genética , Ligantes , Síndromes Paraneoplásicas do Sistema Nervoso/diagnóstico , SíndromeRESUMO
The growth hormone and insulin-like growth factor (IGF) system is integral to human growth. Genome-wide association studies (GWAS) have identified variants associated with height and located near the genes in this pathway. However, mechanisms underlying these genetic associations are not understood. To investigate the regulation of the genes in this pathway and mechanisms by which regulation could affect growth, we performed GWAS of measured serum protein levels of IGF-I, IGF binding protein-3 (IGFBP-3), pregnancy-associated plasma protein A (PAPP-A2), IGF-II and IGFBP-5 in 838 children (3-18 years) from the Cincinnati Genomic Control Cohort. We identified variants associated with protein levels near IGFBP3 and IGFBP5 genes, which contain multiple signals of association with height and other skeletal growth phenotypes. Surprisingly, variants that associate with protein levels at these two loci do not colocalize with height associations, confirmed through conditional analysis. Rather, the IGFBP3 signal (associated with total IGFBP-3 and IGF-II levels) colocalizes with an association with sitting height ratio (SHR); the IGFBP5 signal (associated with IGFBP-5 levels) colocalizes with birth weight. Indeed, height-associated single nucleotide polymorphisms near genes encoding other proteins in this pathway are not associated with serum levels, possibly excluding PAPP-A2. Mendelian randomization supports a stronger causal relationship of measured serum levels with SHR (for IGFBP-3) and birth weight (for IGFBP-5) than with height. In conclusion, we begin to characterize the genetic regulation of serum levels of IGF-related proteins in childhood. Furthermore, our data strongly suggest the existence of growth-regulating mechanisms acting through IGF-related genes in ways that are not reflected in measured serum levels of the corresponding proteins.
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Estatura/genética , Hormônio do Crescimento/genética , Proteína 3 de Ligação a Fator de Crescimento Semelhante à Insulina/genética , Proteína 5 de Ligação a Fator de Crescimento Semelhante à Insulina/genética , Fator de Crescimento Insulin-Like I/genética , Adolescente , Peso ao Nascer/genética , Criança , Pré-Escolar , Feminino , Predisposição Genética para Doença/genética , Estudo de Associação Genômica Ampla , Humanos , Proteína 3 de Ligação a Fator de Crescimento Semelhante à Insulina/sangue , Proteína 5 de Ligação a Fator de Crescimento Semelhante à Insulina/sangue , Fator de Crescimento Insulin-Like II/genética , Masculino , Análise da Randomização Mendeliana , Proteína Plasmática A Associada à Gravidez/genética , Postura SentadaRESUMO
COVID-19 testing provides information regarding exposure and transmission risks, guides preventative measures (e.g., if and when to start and end isolation and quarantine), identifies opportunities for appropriate treatments, and helps assess disease prevalence (1). At-home rapid COVID-19 antigen tests (at-home tests) are a convenient and accessible alternative to laboratory-based diagnostic nucleic acid amplification tests (NAATs) for SARS-CoV-2, the virus that causes COVID-19 (2-4). With the emergence of the SARS-CoV-2 B.1.617.2 (Delta) and B.1.1.529 (Omicron) variants in 2021, demand for at-home tests increased (5). At-home tests are commonly used for school- or employer-mandated testing and for confirmation of SARS-CoV-2 infection in a COVID-19-like illness or following exposure (6). Mandated COVID-19 reporting requirements omit at-home tests, and there are no standard processes for test takers or manufacturers to share results with appropriate health officials (2). Therefore, with increased COVID-19 at-home test use, laboratory-based reporting systems might increasingly underreport the actual incidence of infection. Data from a cross-sectional, nonprobability-based online survey (August 23, 2021-March 12, 2022) of U.S. adults aged ≥18 years were used to estimate self-reported at-home test use over time, and by demographic characteristics, geography, symptoms/syndromes, and reasons for testing. From the Delta-predominant period (August 23-December 11, 2021) to the Omicron-predominant period (December 19, 2021-March 12, 2022)§ (7), at-home test use among respondents with self-reported COVID-19-like illness¶ more than tripled from 5.7% to 20.1%. The two most commonly reported reasons for testing among persons who used an at-home test were COVID-19 exposure (39.4%) and COVID-19-like symptoms (28.9%). At-home test use differed by race (e.g., self-identified as White [5.9%] versus self-identified as Black [2.8%]), age (adults aged 30-39 years [6.4%] versus adults aged ≥75 years [3.6%]), household income (>$150,000 [9.5%] versus $50,000-$74,999 [4.7%]), education (postgraduate degree [8.4%] versus high school or less [3.5%]), and geography (New England division [9.6%] versus West South Central division [3.7%]). COVID-19 testing, including at-home tests, along with prevention measures, such as quarantine and isolation when warranted, wearing a well-fitted mask when recommended after a positive test or known exposure, and staying up to date with vaccination,** can help reduce the spread of COVID-19. Further, providing reliable and low-cost or free at-home test kits to underserved populations with otherwise limited access to COVID-19 testing could assist with continued prevention efforts.
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COVID-19 , Adolescente , Adulto , Idoso , COVID-19/diagnóstico , COVID-19/epidemiologia , COVID-19/prevenção & controle , Teste para COVID-19 , Estudos Transversais , Humanos , SARS-CoV-2 , Estados Unidos/epidemiologiaRESUMO
OBJECTIVE: Poor metabolic health and unhealthy lifestyle factors have been associated with risk and severity of COVID-19, but data for diet are lacking. We aimed to investigate the association of diet quality with risk and severity of COVID-19 and its interaction with socioeconomic deprivation. DESIGN: We used data from 592 571 participants of the smartphone-based COVID-19 Symptom Study. Diet information was collected for the prepandemic period using a short food frequency questionnaire, and diet quality was assessed using a healthful Plant-Based Diet Score, which emphasises healthy plant foods such as fruits or vegetables. Multivariable Cox models were fitted to calculate HRs and 95% CIs for COVID-19 risk and severity defined using a validated symptom-based algorithm or hospitalisation with oxygen support, respectively. RESULTS: Over 3 886 274 person-months of follow-up, 31 815 COVID-19 cases were documented. Compared with individuals in the lowest quartile of the diet score, high diet quality was associated with lower risk of COVID-19 (HR 0.91; 95% CI 0.88 to 0.94) and severe COVID-19 (HR 0.59; 95% CI 0.47 to 0.74). The joint association of low diet quality and increased deprivation on COVID-19 risk was higher than the sum of the risk associated with each factor alone (Pinteraction=0.005). The corresponding absolute excess rate per 10 000 person/months for lowest vs highest quartile of diet score was 22.5 (95% CI 18.8 to 26.3) among persons living in areas with low deprivation and 40.8 (95% CI 31.7 to 49.8) among persons living in areas with high deprivation. CONCLUSIONS: A diet characterised by healthy plant-based foods was associated with lower risk and severity of COVID-19. This association may be particularly evident among individuals living in areas with higher socioeconomic deprivation.
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COVID-19/etiologia , Dieta/efeitos adversos , Adolescente , Adulto , Idoso , COVID-19/epidemiologia , COVID-19/prevenção & controle , Inquéritos sobre Dietas , Dieta Saudável , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Fatores de Risco , Índice de Gravidade de Doença , Fatores Socioeconômicos , Inquéritos e Questionários , Adulto JovemRESUMO
BACKGROUND: Obesity and its associated diseases are major health problems characterized by extensive metabolic disturbances. Understanding the causal connections between these phenotypes and variation in metabolite levels can uncover relevant biology and inform novel intervention strategies. Recent studies have combined metabolite profiling with genetic instrumental variable (IV) analysis (Mendelian randomization) to infer the direction of causality between metabolites and obesity, but often omitted a large portion of untargeted profiling data consisting of unknown, unidentified metabolite signals. METHODS: We expanded upon previous research by identifying body mass index (BMI)-associated metabolites in multiple untargeted metabolomics datasets, and then performing bidirectional IV analysis to classify metabolites based on their inferred causal relationships with BMI. Meta-analysis and pathway analysis of both known and unknown metabolites across datasets were enabled by our recently developed bioinformatics suite, PAIRUP-MS. RESULTS: We identified ten known metabolites that are more likely to be causes (e.g., alpha-hydroxybutyrate) or effects (e.g., valine) of BMI, or may have more complex bidirectional cause-effect relationships with BMI (e.g., glycine). Importantly, we also identified about five times more unknown than known metabolites in each of these three categories. Pathway analysis incorporating both known and unknown metabolites prioritized 40 enriched (p < 0.05) metabolite sets for the cause versus effect groups, providing further support that these two metabolite groups are linked to obesity via distinct biological mechanisms. CONCLUSIONS: These findings demonstrate the potential utility of our approach to uncover causal connections with obesity from untargeted metabolomics datasets. Combining genetically informed causal inference with the ability to map unknown metabolites across datasets provides a path to jointly analyze many untargeted datasets with obesity or other phenotypes. This approach, applied to larger datasets with genotype and untargeted metabolite data, should generate sufficient power for robust discovery and replication of causal biological connections between metabolites and various human diseases.
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Metaboloma , Obesidade/metabolismo , Índice de Massa Corporal , Causalidade , Biologia Computacional , Humanos , Metabolômica , Obesidade/genéticaRESUMO
BACKGROUND: A fundamental precept of the carbohydrate-insulin model of obesity is that insulin secretion drives weight gain. However, fasting hyperinsulinemia can also be driven by obesity-induced insulin resistance. We used genetic variation to isolate and estimate the potentially causal effect of insulin secretion on body weight. METHODS: Genetic instruments of variation of insulin secretion [assessed as insulin concentration 30 min after oral glucose (insulin-30)] were used to estimate the causal relationship between increased insulin secretion and body mass index (BMI), using bidirectional Mendelian randomization analysis of genome-wide association studies. Data sources included summary results from the largest published metaanalyses of predominantly European ancestry for insulin secretion (n = 26037) and BMI (n = 322154), as well as individual-level data from the UK Biobank (n = 138541). Data from the Cardiology and Metabolic Patient Cohort study at Massachusetts General Hospital (n = 1675) were used to validate genetic associations with insulin secretion and to test the observational association of insulin secretion and BMI. RESULTS: Higher genetically determined insulin-30 was strongly associated with higher BMI (ß = 0.098, P = 2.2 × 10-21), consistent with a causal role in obesity. Similar positive associations were noted in sensitivity analyses using other genetic variants as instrumental variables. By contrast, higher genetically determined BMI was not associated with insulin-30. CONCLUSIONS: Mendelian randomization analyses provide evidence for a causal relationship of glucose-stimulated insulin secretion on body weight, consistent with the carbohydrate-insulin model of obesity.
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Carboidratos da Dieta/administração & dosagem , Secreção de Insulina/genética , Análise da Randomização Mendeliana , Obesidade/genética , Obesidade/metabolismo , Índice de Massa Corporal , Estudos de Coortes , Jejum , Estudo de Associação Genômica Ampla , Glucose/administração & dosagem , Humanos , Resistência à Insulina , Modelos Biológicos , Polimorfismo de Nucleotídeo Único , Reprodutibilidade dos TestesRESUMO
BACKGROUND: Participatory surveillance of self-reported symptoms and vaccination status can be used to supplement traditional public health surveillance and provide insights into vaccine effectiveness and changes in the symptoms produced by an infectious disease. The University of Maryland COVID Trends and Impact Survey provides an example of participatory surveillance that leveraged Facebook's active user base to provide self-reported symptom and vaccination data in near real-time. METHODS: Here, we develop a methodology for identifying changes in vaccine effectiveness and COVID-19 symptomatology using the University of Maryland COVID Trends and Impact Survey data from three middle-income countries (Guatemala, Mexico, and South Africa). We implement conditional logistic regression to develop estimates of vaccine effectiveness conditioned on the prevalence of various definitions of self-reported COVID-like illness in lieu of confirmed diagnostic test results. RESULTS: We highlight a reduction in vaccine effectiveness during Omicron-dominated waves of infections when compared to periods dominated by the Delta variant (median change across COVID-like illness definitions: -0.40, IQR[-0.45, -0.35]. Further, we identify a shift in COVID-19 symptomatology towards upper respiratory type symptoms (i.e., cough and sore throat) during Omicron periods of infections. Stratifying COVID-like illness by the National Institutes of Health's (NIH) description of mild and severe COVID-19 symptoms reveals a similar level of vaccine protection across different levels of COVID-19 severity during the Omicron period. CONCLUSIONS: Participatory surveillance data alongside methodologies described in this study are particularly useful for resource-constrained settings where diagnostic testing results may be delayed or limited.
Surveys that are sent out to users of social media can be used to supplement traditional methods to monitor the spread of infectious diseases. This has the potential to be particularly useful in areas where other data is unavailable, such as areas with less surveillance of infectious disease prevalence and access to infectious disease diagnostics. We used data from a survey available to users of the social media platform Facebook to collect information about any potential symptoms of COVID-19 infection and vaccines received during the COVID-19 pandemic. We found a potential reduction in vaccine effectiveness and change in symptoms when the Omicron variant was known to be circulating compared to the earlier Delta variant. This method could be adapted to monitor the spread of COVID-19 and other infectious diseases in the future, which might enable the impact of infectious diseases to be recognized more quickly.
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BACKGROUND: Continuous glucose monitor (CGM) use improves type 1 diabetes (T1D) outcomes, yet children from diverse backgrounds and on public insurance have worse outcomes and lower CGM utilization. Using novel CGM data acquisition and analysis of two T1D cohorts, we test the hypothesis that T1D youth from different backgrounds experience disparities in meaningful CGM use following both T1D diagnosis and CGM uptake. METHODS: Cohorts drawn from a pediatric T1D program were followed for one year beginning at diagnosis (n = 815, 2016-2020) or CGM uptake (n = 1392, 2015-2020). Using chart and CGM data, CGM start and meaningful use outcomes between racial/ethnic and insurance groups were compared using median days, one-year proportions, and survival analysis. RESULTS: Publicly compared with privately insured were slower to start CGM (233, 151 days, P < .01), had fewer use-days in the year following uptake (232, 324, P < .001), and had faster first discontinuation rates (hazard ratio [HR] = 1.61, P < .001). Disparities were more pronounced among Hispanic and black compared with white subjects for CGM start time (312, 289, 149, P = .0013) and discontinuation rates (Hispanic HR = 2.17, P < .001; black HR = 1.45, P = .038), and remained even among privately insured (Hispanic/black HR = 1.44, P = .0286). CONCLUSIONS: Given the impact of insurance and race/ethnicity on CGM initiation and use, it is imperative that we target interventions to support universal access and sustained CGM use to mitigate the potential impact of provider biases and systemic disadvantage and racism. By enabling more equitable and meaningful T1D technology use, such interventions will begin to alleviate outcome disparities between youth with T1D from different backgrounds.
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COVID-19 vaccination rates among children have stalled, while new coronavirus strains continue to emerge. To improve child vaccination rates, policymakers must better understand parental preferences and reasons for COVID-19 vaccination among their children. Cross-sectional surveys were administered online to 30,174 US parents with at least one child of COVID-19 vaccine eligible age (5-17 years) between January 1 and May 9, 2022. Participants self-reported willingness to vaccinate their child and reasons for refusal, and answered additional questions about demographics, pandemic related behavior, and vaccination status. Willingness to vaccinate a child for COVID-19 was strongly associated with parental vaccination status (multivariate odds ratio 97.9, 95% confidence interval 86.9-111.0). The majority of fully vaccinated (86%) and unvaccinated (84%) parents reported concordant vaccination preferences for their eligible child. Age and education had differing relationships by vaccination status, with higher age and education positively associated with willingness among vaccinated parents. Among all parents unwilling to vaccinate their children, the two most frequently reported reasons were possible side effects (47%) and that vaccines are too new (44%). Unvaccinated parents were much more likely to list a lack of trust in government (41% to 21%, p < .001) and a lack of trust in scientists (34% to 19%, p < .001) as reasons for refusal. Cluster analysis identified three groups of unwilling parents based on their reasons for refusal to vaccinate, with distinct concerns that may be obscured when analyzed in aggregate. Factors associated with willingness to vaccinate children and reasons for refusal may inform targeted approaches to increase vaccination.
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INTRODUCTION: Children with self-limited delayed puberty (DP) (constitutional delay) enter puberty after variable waiting times, and the factors associated with their eventual pubertal timing are not well understood. METHODS: We conducted a retrospective study of 99 girls and 228 boys with self-limited DP at an academic medical center between 2000 and 2015. To define features and potential subtypes of self-limited DP, we performed group-based trajectory modeling on childhood growth and latent-variable factor analysis on clinical characteristics. We then conducted time-to-event analyses to identify associations with pubertal timing. RESULTS: We identified two distinct growth trajectories in individuals with self-limited DP: one with stable and the other with declining height percentiles. Latent-variable factor analysis identified five factors underlying clinical variation that appear to correspond to genetic height potential, body mass index, childhood growth, parental pubertal delay, and medical issues (attention-deficit/hyperactivity disorder and inhaled glucocorticoid use). We observed correlations between pubertal timing and bone age (p = 0.01), childhood height (p = 0.004), and midparental target height (p < 0.001), but not with parental pubertal delay or with testosterone treatment in boys. CONCLUSIONS: By illustrating the heterogeneity within self-limited DP and identifying factors underlying this heterogeneity, our study suggests that there may be multiple causes of self-limited DP. However, our ability to determine when puberty will eventually occur remains limited. Dissecting self-limited DP into its component subtypes may inform future studies of the mechanisms contributing to pubertal delay as well as studies of the short- and long-term outcomes of self-limited DP.
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Puberdade Tardia , Testosterona , Humanos , Masculino , Feminino , Criança , Puberdade Tardia/tratamento farmacológico , Estudos Retrospectivos , Testosterona/uso terapêutico , Fatores de Tempo , Índice de Massa Corporal , Constituição CorporalRESUMO
BACKGROUND: The third most severe COVID-19 wave in the middle of 2021 coincided with the dual challenges of limited vaccine supply and lagging acceptance in Bangkok, Thailand. Understanding of persistent vaccine hesitancy during the "608" campaign to vaccinate those aged over 60 years and 8 medical risk groups was needed. On-the-ground surveys place further demands on resources and are scale limited. We leveraged the University of Maryland COVID-19 Trends and Impact Survey (UMD-CTIS), a digital health survey conducted among daily Facebook user samples, to fill this need and inform regional vaccine rollout policy. OBJECTIVE: The aims of this study were to characterize COVID-19 vaccine hesitancy, frequent reasons for hesitancy, mitigating risk behaviors, and the most trusted sources of COVID-19 information through which to combat vaccine hesitancy in Bangkok, Thailand during the 608 vaccine campaign. METHODS: We analyzed 34,423 Bangkok UMD-CTIS responses between June and October 2021, coinciding with the third COVID-19 wave. Sampling consistency and representativeness of the UMD-CTIS respondents were evaluated by comparing distributions of demographics, 608 priority groups, and vaccine uptake over time with source population data. Estimates of vaccine hesitancy in Bangkok and 608 priority groups were tracked over time. Frequently cited hesitancy reasons and trusted information sources were identified according to the 608 group and degree of hesitancy. Kendall tau was used to test statistical associations between vaccine acceptance and vaccine hesitancy. RESULTS: The Bangkok UMD-CTIS respondents had similar demographics over weekly samples and compared to the Bangkok source population. Respondents self-reported fewer pre-existing health conditions compared to census data overall but had a similar prevalence of the important COVID-19 risk factor diabetes. UMD-CTIS vaccine uptake rose in parallel with national vaccination statistics, while vaccine hesitancy and degree of hesitancy declined (-7% hesitant per week). Concerns about vaccination side effects (2334/3883, 60.1%) and wanting to wait and see (2410/3883, 62.1%) were selected most frequently, while "not liking vaccines" (281/3883, 7.2%) and "religious objections" (52/3883, 1.3%) were selected least frequently. Greater vaccine acceptance was associated positively with wanting to "wait and see" and negatively with "don't believe I need (the vaccine)" (Kendall tau 0.21 and -0.22, respectively; adjusted P<.001). Scientists and health experts were most frequently cited as trusted COVID-19 information sources (13,600/14,033, 96.9%), even among vaccine hesitant respondents. CONCLUSIONS: Our findings provide policy and health experts with evidence that vaccine hesitancy was declining over the study timeframe. Hesitancy and trust analyses among the unvaccinated support Bangkok policy measures to address vaccine safety and efficacy concerns through health experts rather than government or religious officials. Large-scale surveys enabled by existing widespread digital networks offer an insightful minimal-infrastructure resource for informing region-specific health policy needs.
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Vacinas contra COVID-19 , COVID-19 , Humanos , Pessoa de Meia-Idade , Idoso , COVID-19/epidemiologia , COVID-19/prevenção & controle , Tailândia/epidemiologia , Estudos Transversais , VacinaçãoRESUMO
BACKGROUND: Limitations in laboratory diagnostic capacity impact population surveillance of COVID-19. It is currently unknown whether participatory surveillance tools for COVID-19 correspond to government-reported case trends longitudinally and if it can be used as an adjunct to laboratory testing. The primary objective of this study was to determine whether self-reported COVID-19-like illness reflected laboratory-confirmed COVID-19 case trends in Ontario Canada. METHODS: We retrospectively analyzed longitudinal self-reported symptoms data collected using an online tool-Outbreaks Near Me (ONM)-from April 20th, 2020, to March 7th, 2021 in Ontario, Canada. We measured the correlation between COVID-like illness among respondents and the weekly number of PCR-confirmed COVID-19 cases and provincial test positivity. We explored contemporaneous changes in other respiratory viruses, as well as the demographic characteristics of respondents to provide context for our findings. RESULTS: Between 3,849-11,185 individuals responded to the symptom survey each week. No correlations were seen been self-reported CLI and either cases or test positivity. Strong positive correlations were seen between CLI and both cases and test positivity before a previously documented rise in rhinovirus/enterovirus in fall 2020. Compared to participatory surveillance respondents, a higher proportion of COVID-19 cases in Ontario consistently came from low-income, racialized and immigrant areas of the province- these groups were less well represented among survey respondents. INTERPRETATION: Although digital surveillance systems are low-cost tools that have been useful to signal the onset of viral outbreaks, in this longitudinal comparison of self-reported COVID-like illness to Ontario COVID-19 case data we did not find this to be the case. Seasonal respiratory virus transmission and population coverage may explain this discrepancy.
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COVID-19/patologia , Avaliação de Sintomas/tendências , Adolescente , Adulto , Idoso , COVID-19/diagnóstico , COVID-19/virologia , Feminino , Humanos , Internet , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Ontário , Vigilância da População , Estudos Retrospectivos , SARS-CoV-2/genética , SARS-CoV-2/isolamento & purificação , Autorrelato , Adulto JovemRESUMO
BACKGROUND: COVID-19 vaccine distribution is at risk of further propagating the inequities of COVID-19, which in the United States (US) has disproportionately impacted the elderly, people of color, and the medically vulnerable. We sought to measure if the disparities seen in the geographic distribution of other COVID-19 healthcare resources were also present during the initial rollout of the COVID-19 vaccine. METHODS: Using a comprehensive COVID-19 vaccine database (VaccineFinder), we built an empirically parameterized spatial model of access to essential resources that incorporated vaccine supply, time-willing-to-travel for vaccination, and previous vaccination across the US. We then identified vaccine deserts-US Census tracts with localized, geographic barriers to vaccine-associated herd immunity. We link our model results with Census data and two high-resolution surveys to understand the distribution and determinates of spatially accessibility to the COVID-19 vaccine. RESULTS: We find that in early 2021, vaccine deserts were home to over 30 million people, >10% of the US population. Vaccine deserts were concentrated in rural locations and communities with a higher percentage of medically vulnerable populations. We also find that in locations of similar urbanicity, early vaccination distribution disadvantaged neighborhoods with more people of color and older aged residents. CONCLUSION: Given sufficient vaccine supply, data-driven vaccine distribution to vaccine deserts may improve immunization rates and help control COVID-19.
COVID-19 has affected the elderly, people of color, and individuals with chronic illnesses more than the general population. Large barriers to accessing the COVID-19 vaccine could make this problem worse. We used a website called VaccineFinder, which has information on the location of most COVID-19 vaccine doses in the US, to measure vaccine accessibility in early 2021. We then identified vaccine deserts, defined as small US regions with poor access to the COVID-19 vaccine. We found that over 10% of the US lived in a vaccine desert. Overall, we found that vaccines were less available to people in rural areas, people of color, and individuals with chronic illnesses. It will be important to reverse this pattern and ensure enough vaccines are sent to these communities to help reduce the spread of COVID-19.
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Symptomatic testing programmes are crucial to the COVID-19 pandemic response. We sought to examine United Kingdom (UK) testing rates amongst individuals with test-qualifying symptoms, and factors associated with not testing. We analysed a cohort of untested symptomatic app users (N = 1,237), nested in the Zoe COVID Symptom Study (Zoe, N = 4,394,948); and symptomatic respondents who wanted, but did not have a test (N = 1,956), drawn from a University of Maryland survey administered to Facebook users (The Global COVID-19 Trends and Impact Survey [CTIS], N = 775,746). The proportion tested among individuals with incident test-qualifying symptoms rose from ~20% to ~75% from April to December 2020 in Zoe. Testing was lower with one vs more symptoms (72.9% vs 84.6% p<0.001), or short vs long symptom duration (69.9% vs 85.4% p<0.001). 40.4% of survey respondents did not identify all three test-qualifying symptoms. Symptom identification decreased for every decade older (OR = 0.908 [95% CI 0.883-0.933]). Amongst symptomatic UMD-CTIS respondents who wanted but did not have a test, not knowing where to go was the most cited factor (32.4%); this increased for each decade older (OR = 1.207 [1.129-1.292]) and for every 4-years fewer in education (OR = 0.685 [0.599-0.783]). Despite current UK messaging on COVID-19 testing, there is a knowledge gap about when and where to test, and this may be contributing to the ~25% testing gap. Risk factors, including older age and less education, highlight potential opportunities to tailor public health messages. The testing gap may be ever larger in countries that do not have extensive, free testing, as the UK does.
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Worldwide, racial and ethnic minorities have been disproportionately impacted by COVID-19 with increased risk of infection, its related complications, and death. In the initial phase of population-based vaccination in the United States (U.S.) and United Kingdom (U.K.), vaccine hesitancy may result in differences in uptake. We performed a cohort study among U.S. and U.K. participants who volunteered to take part in the smartphone-based COVID Symptom Study (March 2020-February 2021) and used logistic regression to estimate odds ratios of vaccine hesitancy and uptake. In the U.S. (n = 87,388), compared to white participants, vaccine hesitancy was greater for Black and Hispanic participants and those reporting more than one or other race. In the U.K. (n = 1,254,294), racial and ethnic minority participants showed similar levels of vaccine hesitancy to the U.S. However, associations between participant race and ethnicity and levels of vaccine uptake were observed to be different in the U.S. and the U.K. studies. Among U.S. participants, vaccine uptake was significantly lower among Black participants, which persisted among participants that self-reported being vaccine-willing. In contrast, statistically significant racial and ethnic disparities in vaccine uptake were not observed in the U.K sample. In this study of self-reported vaccine hesitancy and uptake, lower levels of vaccine uptake in Black participants in the U.S. during the initial vaccine rollout may be attributable to both hesitancy and disparities in access.
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Vacinas contra COVID-19/administração & dosagem , COVID-19/etnologia , COVID-19/prevenção & controle , SARS-CoV-2/imunologia , Hesitação Vacinal , Vacinação/psicologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Povo Asiático/psicologia , Povo Asiático/estatística & dados numéricos , População Negra/psicologia , População Negra/estatística & dados numéricos , COVID-19/psicologia , Estudos de Coortes , Feminino , Hispânico ou Latino/psicologia , Hispânico ou Latino/estatística & dados numéricos , Humanos , Masculino , Pessoa de Meia-Idade , Grupos Minoritários/psicologia , Grupos Minoritários/estatística & dados numéricos , SARS-CoV-2/genética , Autorrelato , Reino Unido/etnologia , Estados Unidos/epidemiologia , População Branca/psicologia , População Branca/estatística & dados numéricos , Adulto JovemRESUMO
BACKGROUND: Face masks have become commonplace across the USA because of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic. Although evidence suggests that masks help to curb the spread of the disease, there is little empirical research at the population level. We investigate the association between self-reported mask-wearing, physical distancing, and SARS-CoV-2 transmission in the USA, along with the effect of statewide mandates on mask uptake. METHODS: Serial cross-sectional surveys were administered via a web platform to randomly surveyed US individuals aged 13 years and older, to query self-reports of face mask-wearing. Survey responses were combined with instantaneous reproductive number (Rt) estimates from two publicly available sources, the outcome of interest. Measures of physical distancing, community demographics, and other potential sources of confounding (from publicly available sources) were also assessed. We fitted multivariate logistic regression models to estimate the association between mask-wearing and community transmission control (Rt<1). Additionally, mask-wearing in 12 states was evaluated 2 weeks before and after statewide mandates. FINDINGS: 378â207 individuals responded to the survey between June 3 and July 27, 2020, of which 4186 were excluded for missing data. We observed an increasing trend in reported mask usage across the USA, although uptake varied by geography. A logistic model controlling for physical distancing, population demographics, and other variables found that a 10% increase in self-reported mask-wearing was associated with an increased odds of transmission control (odds ratio 3·53, 95% CI 2·03-6·43). We found that communities with high reported mask-wearing and physical distancing had the highest predicted probability of transmission control. Segmented regression analysis of reported mask-wearing showed no statistically significant change in the slope after mandates were introduced; however, the upward trend in reported mask-wearing was preserved. INTERPRETATION: The widespread reported use of face masks combined with physical distancing increases the odds of SARS-CoV-2 transmission control. Self-reported mask-wearing increased separately from government mask mandates, suggesting that supplemental public health interventions are needed to maximise adoption and help to curb the ongoing epidemic. FUNDING: Flu Lab, Google.org (via the Tides Foundation), National Institutes for Health, National Science Foundation, Morris-Singer Foundation, MOOD, Branco Weiss Fellowship, Ending Pandemics, Centers for Disease Control and Prevention (USA).
Assuntos
COVID-19/prevenção & controle , COVID-19/transmissão , Máscaras , Pandemias/prevenção & controle , Adolescente , Adulto , Idoso , Controle de Doenças Transmissíveis/métodos , Estudos Transversais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Distanciamento Físico , Saúde Pública , SARS-CoV-2 , Inquéritos e Questionários , Estados Unidos , Adulto JovemRESUMO
We tested whether pregnant and non-pregnant women differ in COVID-19 symptom profile and severity, and we extended previous investigations on hospitalized pregnant women to those who did not require hospitalization. Two female community-based cohorts (18-44 years) provided longitudinal (smartphone application, N = 1,170,315, n = 79 pregnant tested positive) and cross-sectional (web-based survey, N = 1,344,966, n = 134 pregnant tested positive) data, prospectively collected through self-participatory citizen surveillance in UK, Sweden and USA. Pregnant and non-pregnant were compared for frequencies of events, including SARS-CoV-2 testing, symptoms and hospitalization rates. Multivariable regression was used to investigate symptoms severity and comorbidity effects. Pregnant and non-pregnant women positive for SARS-CoV-2 infection were not different in syndromic severity, except for gastrointestinal symptoms. Pregnant were more likely to have received testing, despite reporting fewer symptoms. Pre-existing lung disease was most closely associated with syndromic severity in pregnant hospitalized. Heart and kidney diseases and diabetes increased risk. The most frequent symptoms among non-hospitalized women were anosmia [63% pregnant, 92% non-pregnant] and headache [72%, 62%]. Cardiopulmonary symptoms, including persistent cough [80%] and chest pain [73%], were more frequent among pregnant who were hospitalized. Consistent with observations in non-pregnant populations, lung disease and diabetes were associated with increased risk of more severe SARS-CoV-2 infection during pregnancy.
Assuntos
COVID-19/complicações , Complicações Infecciosas na Gravidez/fisiopatologia , Adolescente , Adulto , COVID-19/fisiopatologia , COVID-19/virologia , Estudos de Coortes , Estudos Transversais , Feminino , Humanos , Aplicativos Móveis , Gravidez , SARS-CoV-2/isolamento & purificação , Índice de Gravidade de Doença , Adulto JovemRESUMO
Given the continued burden of COVID-19 worldwide, there is a high unmet need for data on the effect of social distancing and face mask use to mitigate the risk of COVID-19. We examined the association of community-level social distancing measures and individual face mask use with risk of predicted COVID-19 in a large prospective U.S. cohort study of 198,077 participants. Individuals living in communities with the greatest social distancing had a 31% lower risk of predicted COVID-19 compared with those living in communities with poor social distancing. Self-reported 'always' use of face mask was associated with a 62% reduced risk of predicted COVID-19 even among individuals living in a community with poor social distancing. These findings provide support for the efficacy of mask-wearing even in settings of poor social distancing in reducing COVID-19 transmission. Despite mass vaccination campaigns in many parts of the world, continued efforts at social distancing and face mask use remain critically important in reducing the spread of COVID-19.