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Background and Objectives: Geographic accessibility predicts pediatric preventive care utilization, including vaccine uptake. However, spatial inequities in the pediatric coronavirus disease 2019 (COVID-19) vaccination rollout remain underexplored. We assessed the spatial accessibility of vaccination sites and analyzed predictors of vaccine uptake., Methods: In this cross-sectional study of pediatric COVID-19 vaccinations from the US Vaccine Tracking System as of July 29, 2022, we described spatial accessibility by geocoding vaccination sites, measuring travel times from each Census tract population center to the nearest site, and weighting tracts by their population demographics to obtain nationally representative estimates. We used quasi-Poisson regressions to calculate incidence rate ratios, comparing vaccine uptake between counties with highest and lowest quartile Social Vulnerability Index scores: socioeconomic status (SES), household composition and disability (HCD), minority status and language (MSL), and housing type and transportation., Results: We analyzed 15 233 956 doses administered across 27 526 sites. Rural, uninsured, white, and Native American populations experienced longer travel times to the nearest site than urban, insured, Hispanic, Black, and Asian American populations. Overall Social Vulnerability Index, SES, and HCD were associated with decreased vaccine uptake among children aged 6 months to 4 years (overall: incidence rate ratio 0.70 [95% confidence interval 0.60-0.81]; SES: 0.66 [0.58-0.75]; HCD: 0.38 [0.33-0.44]) and 5 years to 11 years (overall: 0.85 [0.77-0.95]; SES: 0.71 [0.65-0.78]; HCD: 0.67 [0.61-0.74]), whereas social vulnerability by MSL was associated with increased uptake (6 months-4 years: 5.16 [3.59-7.42]; 5 years-11 years: 1.73 [1.44-2.08])., Conclusions: Pediatric COVID-19 vaccine uptake and accessibility differed by race, rurality, and social vulnerability. National supply data, spatial accessibility measurement, and place-based vulnerability indices can be applied throughout public health resource allocation, surveillance, and research., (Copyright © 2024 by the American Academy of Pediatrics.)

The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss requirements for an effective surveillance system to support decision making during a pandemic, drawing on the lessons of COVID-19 in the U.S., while looking to jurisdictions in the U.S. and beyond to learn lessons about the value of specific data types. In this report, we define the range of decisions for which surveillance data are required, the data elements needed to inform these decisions and to calibrate inputs and outputs of transmission-dynamic models, and the types of data needed to inform decisions by state, territorial, local, and tribal health authorities. We define actions needed to ensure that such data will be available and consider the contribution of such efforts to improving health equity., Competing Interests: RS was employed by company Siemens Healthcare Diagnostics. JV was employed by company SIGA Technologies. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Lipsitch, Bassett, Brownstein, Elliott, Eyre, Grabowski, Hay, Johansson, Kissler, Larremore, Layden, Lessler, Lynfield, MacCannell, Madoff, Metcalf, Meyers, Ofori, Quinn, Bento, Reich, Riley, Rosenfeld, Samore, Sampath, Slayton, Swerdlow, Truelove, Varma and Grad.)

Tools to advance antimicrobial stewardship in the primary health care setting, where most antimicrobials are prescribed, are urgently needed. The aim of this study was to evaluate OPEN Stewarship (Online Platform for Expanding aNtibiotic Stewardship), an automated feedback intervention, among a cohort of primary care physicians. We performed a controlled, interrupted time-series study of 32 intervention and 725 control participants, consisting of primary care physicians from Ontario, Canada and Southern Israel, from October 2020 to December 2021. Intervention participants received three personalized feedback reports targeting several aspects of antibiotic prescribing. Study outcomes (overall prescribing rate, prescribing rate for viral respiratory conditions, prescribing rate for acute sinusitis, and mean duration of therapy) were evaluated using multilevel regression models. We observed a decrease in the mean duration of antibiotic therapy (IRR = 0.94; 95% CI: 0.90, 0.99) in intervention participants during the intervention period. We did not observe a significant decline in overall antibiotic prescribing (OR = 1.01; 95% CI: 0.94, 1.07), prescribing for viral respiratory conditions (OR = 0.87; 95% CI: 0.73, 1.03), or prescribing for acute sinusitis (OR = 0.85; 95% CI: 0.67, 1.07). In this antimicrobial stewardship intervention among primary care physicians, we observed shorter durations of therapy per antibiotic prescription during the intervention period. The COVID-19 pandemic may have hampered recruitment; a dramatic reduction in antibiotic prescribing rates in the months before our intervention may have made physicians less amenable to further reductions in prescribing, limiting the generalizability of the estimates obtained.IMPORTANCEAntibiotic overprescribing contributes to antibiotic resistance, a major threat to our ability to treat infections. We developed the OPEN Stewardship (Online Platform for Expanding aNtibiotic Stewardship) platform to provide automated feedback on antibiotic prescribing in primary care, where most antibiotics for human use are prescribed but where the resources to improve antibiotic prescribing are limited. We evaluated the platform among a cohort of primary care physicians from Ontario, Canada and Southern Israel from October 2020 to December 2021. The results showed that physicians who received personalized feedback reports prescribed shorter courses of antibiotics compared to controls, although they did not write fewer antibiotic prescriptions. While the COVID-19 pandemic presented logistical and analytical challenges, our study suggests that our intervention meaningfully improved an important aspect of antibiotic prescribing. The OPEN Stewardship platform stands as an automated, scalable intervention for improving antibiotic prescribing in primary care, where needs are diverse and technical capacity is limited., Competing Interests: The authors declare no conflict of interest.

Background: Seasonal respiratory viruses had lower incidence during their 2019-2020 and 2020-2021 seasons, which overlapped with the COVID-19 pandemic. The widespread implementation of precautionary measures to prevent transmission of SARS-CoV-2 has been seen to also mitigate transmission of seasonal influenza. The COVID-19 pandemic also led to changes in care seeking and access. Participatory surveillance systems have historically captured mild illnesses that are often missed by surveillance systems that rely on encounters with a health care provider for detection., Objective: This study aimed to assess if a crowdsourced syndromic surveillance system capable of detecting mild influenza-like illness (ILI) also captured the globally observed decrease in ILI in the 2019-2020 and 2020-2021 influenza seasons, concurrent with the COVID-19 pandemic., Methods: Flu Near You (FNY) is a web-based participatory syndromic surveillance system that allows participants in the United States to report their health information using a brief weekly survey. Reminder emails are sent to registered FNY participants to report on their symptoms and the symptoms of household members. Guest participants may also report. ILI was defined as fever and sore throat or fever and cough. ILI rates were determined as the number of ILI reports over the total number of reports and assessed for the 2016-2017, 2017-2018, 2018-2019, 2019-2020, and 2020-2021 influenza seasons. Baseline season (2016-2017, 2017-2018, and 2018-2019) rates were compared to the 2019-2020 and 2020-2021 influenza seasons. Self-reported influenza diagnosis and vaccination status were captured and assessed as the total number of reported events over the total number of reports submitted. CIs for all proportions were calculated via a 1-sample test of proportions., Results: ILI was detected in 3.8% (32,239/848,878) of participants in the baseline seasons (2016-2019), 2.58% (7418/287,909) in the 2019-2020 season, and 0.27% (546/201,079) in the 2020-2021 season. Both influenza seasons that overlapped with the COVID-19 pandemic had lower ILI rates than the baseline seasons. ILI decline was observed during the months with widespread implementation of COVID-19 precautions, starting in February 2020. Self-reported influenza diagnoses decreased from early 2020 through the influenza season. Self-reported influenza positivity among ILI cases varied over the observed time period. Self-reported influenza vaccination rates in FNY were high across all observed seasons., Conclusions: A decrease in ILI was detected in the crowdsourced FNY surveillance system during the 2019-2020 and 2020-2021 influenza seasons, mirroring trends observed in other influenza surveillance systems. Specifically, the months within seasons that overlapped with widespread pandemic precautions showed decreases in ILI and confirmed influenza. Concerns persist regarding respiratory pathogens re-emerging with changes to COVID-19 guidelines. Traditional surveillance is subject to changes in health care behaviors. Systems like FNY are uniquely situated to detect disease across disease severity and care seeking, providing key insights during public health emergencies., (©Autumn Gertz, Benjamin Rader, Kara Sewalk, Tanner J Varrelman, Mark Smolinski, John S Brownstein. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 28.12.2023.)

Since 8th March 2020 up to the time of writing, we have been producing near real-time weekly estimates of SARS-CoV-2 transmissibility and forecasts of deaths due to COVID-19 for all countries with evidence of sustained transmission, shared online. We also developed a novel heuristic to combine weekly estimates of transmissibility to produce forecasts over a 4-week horizon. Here we present a retrospective evaluation of the forecasts produced between 8th March to 29th November 2020 for 81 countries. We evaluated the robustness of the forecasts produced in real-time using relative error, coverage probability, and comparisons with null models. During the 39-week period covered by this study, both the short- and medium-term forecasts captured well the epidemic trajectory across different waves of COVID-19 infections with small relative errors over the forecast horizon. The model was well calibrated with 56.3% and 45.6% of the observations lying in the 50% Credible Interval in 1-week and 4-week ahead forecasts respectively. The retrospective evaluation of our models shows that simple transmission models calibrated using routine disease surveillance data can reliably capture the epidemic trajectory in multiple countries. The medium-term forecasts can be used in conjunction with the short-term forecasts of COVID-19 mortality as a useful planning tool as countries continue to relax public health measures., Competing Interests: AC has received payment from Pfizer for teaching of mathematical modelling of infectious diseases. All other authors have declared that no competing interests exist. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2023 Bhatia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Continually emerging SARS-CoV-2 variants of concern that can evade immune defenses are driving recurrent epidemic waves of COVID-19 globally. However, the impact of measures to contain the virus and their effect on lineage diversity dynamics are poorly understood. Here, we jointly analyzed international travel, public health and social measures (PHSM), COVID-19 vaccine rollout, SARS-CoV-2 lineage diversity, and the case growth rate (GR) from March 2020 to September 2022 across 63 countries. We showed that despite worldwide vaccine rollout, PHSM are effective in mitigating epidemic waves and lineage diversity. An increase of 10,000 monthly travelers in a single country-to-country route between endemic countries corresponds to a 5.5% (95% CI: 2.9 to 8.2%) rise in local lineage diversity. After accounting for PHSM, natural immunity from previous infections, and waning immunity, we discovered a negative association between the GR of cases and adjusted vaccine coverage (AVC). We also observed a complex relationship between lineage diversity and vaccine rollout. Specifically, we found a significant negative association between lineage diversity and AVC at both low and high levels but not significant at the medium level. Our study deepens the understanding of population immunity and lineage dynamics for future pandemic preparedness and responsiveness.

During the COVID-19 pandemic, open-access platforms that aggregate, link and analyse data were transformative for global public health surveillance. This perspective explores the work of three of these platforms: Our World In Data (OWID), Johns Hopkins University (JHU) COVID-19 Dashboard (later complemented by the Coronavirus Resource Center), and Global.Health, which were presented in the second World Health Organization (WHO) Pandemic and Epidemic Intelligence Innovation Forum. These platforms, operating mostly within academic institutions, added value to public health data that are collected by government agencies by providing additional real-time public health intelligence about the spread of the virus and the evolution of the public health emergency. Information from these platforms was used by health professionals, political decision-makers and members of the public alike. Further engagement between government and non-governmental surveillance efforts can accelerate the improvements needed in public health surveillance overall. Increasing the diversity of public health surveillance initiatives beyond the government sector comes with several benefits: technology innovation in data science, engagement of additional highly skilled professionals, greater transparency and accountability for government agencies, and new opportunities to engage with members of society.

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., (©Christopher Remmel, Gaurav Tuli, Tanner J Varrelman, Aimee R Han, Pakkanan Angkab, Hathairat Kosiyaporn, Chanikarn Netrpukdee, Supatnuj Sorndamrih, Thaksaphon Thamarangsi, John S Brownstein, Christina M Astley. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 13.04.2023.)

A private-academic partnership built the Vaccine Equity Planner (VEP) to help decision-makers improve geographic access to COVID-19 vaccinations across the United States by identifying vaccine deserts and facilities that could fill those deserts. The VEP presented complex, updated data in an intuitive form during a rapidly changing pandemic situation. The persistence of vaccine deserts in every state as COVID-19 booster recommendations develop suggests that vaccine delivery can be improved. Underresourced public health systems benefit from tools providing real-time, accurate, actionable data. ( Am J Public Health . 2023;113(4):363-367. https://doi.org/10.2105/AJPH.2022.307198).

Competing Interests: We thank Syed Arefinul Haque (Network Science Institute, Northeastern University, Boston, MA, USA) and Ben Rader (Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA; Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA) for their assistance. MSM receives funding from the National Institute of General Medical Sciences and National Institutes of Health (R35GM146974). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. NKRS, JSB, and GT declare no competing interests.

The Janssen COVID-19 vaccine came to market in February 2021 as the first non-mRNA and first single-dose formula approved for use in the US. In April 2021, a temporary pause was recommended for the vaccine after the discovery of rare but serious post-vaccination side-effects. We fielded a large-scale nationally representative survey (n = 401,398) on individual confidence in each of the COVID-19 vaccine formulas available in the US before, during, and after this pause. We find widespread loss of confidence in the Janssen vaccine across gender, age, and other demographics, which persisted over time and after lifting of the halt. Despite this drop, overall reasons for remaining unvaccinated were stable and there was a concurrent minor bump in confidence towards other vaccine formulas. This contrast between the persistent reduction in confidence in the Janssen vaccine and the apparent maintenance of the broader campaign's integrity, highlights the complex dynamics and downstream effects of the pause., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

This editorial article aims to highlight advances in artificial intelligence (AI) technologies in five areas: Collaborative AI, Multimodal AI, Human-Centered AI, Equitable AI, and Ethical and Value-based AI in order to cope with future complex socioeconomic and public health issues.

The effectiveness of mask wearing at controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission has been unclear. While masks are known to substantially reduce disease transmission in healthcare settings [D. K. Chu et al., Lancet 395, 1973–1987 (2020); J. Howard et al., Proc. Natl. Acad. Sci. U.S.A. 118, e2014564118 (2021); Y. Cheng et al., Science eabg6296 (2021)], studies in community settings report inconsistent results [H. M. Ollila et al., medRxiv (2020); J. Brainard et al., Eurosurveillance 25, 2000725 (2020); T. Jefferson et al., Cochrane Database Syst. Rev. 11, CD006207 (2020)]. Most such studies focus on how masks impact transmission, by analyzing how effective government mask mandates are. However, we find that widespread voluntary mask wearing, and other data limitations, make mandate effectiveness a poor proxy for mask-wearing effectiveness. We directly analyze the effect of mask wearing on SARS-CoV-2 transmission, drawing on several datasets covering 92 regions on six continents, including the largest survey of wearing behavior (n= 20 million) [F. Kreuter et al., https://gisumd.github.io/COVID-19-API-Documentation (2020)]. Using a Bayesian hierarchical model, we estimate the effect of mask wearing on transmission, by linking reported wearing levels to reported cases in each region, while adjusting for mobility and nonpharmaceutical interventions (NPIs), such as bans on large gatherings. Our estimates imply that the mean observed level of mask wearing corresponds to a 19% decrease in the reproduction number R. We also assess the robustness of our results in 60 tests spanning 20 sensitivity analyses. In light of these results, policy makers can effectively reduce transmission by intervening to increase mask wearing.

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., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. Christina M. Astley reports grants from Flu Lab and from the National Institutes of Health and the National Institute of Diabetes and Digestive and Kidney Diseases during conduct of the study. John S. Brownstein, Autumn Gertz, Benjamin Rader, Kara Sewalk, and Tanner J. Varrelman report grants from Flu Lab during conduct of the study. No other potential conflicts of interest were disclosed.

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., Competing Interests: We have read the journal’s policy and the authors of this manuscript have the following competing interests: IIB has consulted to BlueDot, a social benefit corporation that tracks the spread of emerging infectious diseases. DNF reports personal consultant fees from Pfizer, AstraZeneca, and Seqirus, outside the submitted work. This does not alter our adherence to PLOS ONE policies on sharing data and materials

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., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

It is widely acknowledged that infectious diseases have wrought immense havoc on human society, being regarded as adversaries from which humanity cannot elude. In recent years, the advancement of Artificial Intelligence (AI) technology has ushered in a revolutionary era in the realm of infectious disease prevention and control. This evolution encompasses early warning of outbreaks, contact tracing, infection diagnosis, drug discovery, and the facilitation of drug design, alongside other facets of epidemic management. This article presents an overview of the utilization of AI systems in the field of infectious diseases, with a specific focus on their role during the COVID-19 pandemic. The article also highlights the contemporary challenges that AI confronts within this domain and posits strategies for their mitigation. There exists an imperative to further harness the potential applications of AI across multiple domains to augment its capacity in effectively addressing future disease outbreaks., (© 2024 Wiley Periodicals LLC.)

Background: Research has demonstrated the negative impact of racism on health, yet the measurement of racial sentiment remains challenging. This article provides practical guidance on using social media data for measuring public sentiment., Methods: We describe the main steps of such research, including data collection, data cleaning, binary sentiment analysis, and visualization of findings. We randomly sampled 55,844,310 publicly available tweets from 1 January 2011 to 31 December 2021 using Twitter's Application Programming Interface. We restricted analyses to US tweets in English using one or more 90 race-related keywords. We used a Support Vector Machine, a supervised machine learning model, for sentiment analysis., Results: The proportion of tweets referencing racially minoritized groups that were negative increased at the county, state, and national levels, with a 16.5% increase at the national level from 2011 to 2021. Tweets referencing Black and Middle Eastern people consistently had the highest proportion of negative sentiment compared with all other groups. Stratifying temporal trends by racial and ethnic groups revealed unique patterns reflecting historical events specific to each group, such as the killing of George Floyd regarding sentiment of posts referencing Black people, discussions of the border crisis near the 2018 midterm elections and anti-Latinx sentiment, and the emergence of COVID-19 and anti-Asian sentiment., Conclusions: This study demonstrates the utility of social media data as a quantitative means to measure racial sentiment over time and place. This approach can be extended to a range of public health topics to investigate how changes in social and cultural norms impact behaviors and policy.A supplemental digital video is available at http://links.lww.com/EDE/C91., Competing Interests: The authors report no conflicts of interest., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Multiple voluntary surveillance platforms were developed across the world in response to the COVID-19 pandemic, providing a real-time understanding of population-based COVID-19 epidemiology. During this time, testing criteria broadened and health-care policies matured. We aimed to test whether there were consistent associations of symptoms with SARS-CoV-2 test status across three surveillance platforms in three countries (two platforms per country), during periods of testing and policy changes., Methods: For this observational study, we used data of observations from three volunteer COVID-19 digital surveillance platforms (Carnegie Mellon University and University of Maryland Facebook COVID-19 Symptom Survey, ZOE COVID Symptom Study app, and the Corona Israel study) targeting communities in three countries (Israel, the UK, and the USA; two platforms per country). The study population included adult respondents (age 18-100 years at baseline) who were not health-care workers. We did logistic regression of self-reported symptoms on self-reported SARS-CoV-2 test status (positive or negative), adjusted for age and sex, in each of the study cohorts. We compared odds ratios (ORs) across platforms and countries, and we did meta-analyses assuming a random effects model. We also evaluated testing policy changes, COVID-19 incidence, and time scales of duration of symptoms and symptom-to-test time., Findings: Between April 1 and July 31, 2020, 514 459 tests from over 10 million respondents were recorded in the six surveillance platform datasets. Anosmia-ageusia was the strongest, most consistent symptom associated with a positive COVID-19 test (robust aggregated rank one, meta-analysed random effects OR 16·96, 95% CI 13·13-21·92). Fever (rank two, 6·45, 4·25-9·81), shortness of breath (rank three, 4·69, 3·14-7·01), and cough (rank four, 4·29, 3·13-5·88) were also highly associated with test positivity. The association of symptoms with test status varied by duration of illness, timing of the test, and broader test criteria, as well as over time, by country, and by platform., Interpretation: The strong association of anosmia-ageusia with self-reported positive SARS-CoV-2 test was consistently observed, supporting its validity as a reliable COVID-19 signal, regardless of the participatory surveillance platform, country, phase of illness, or testing policy. These findings show that associations between COVID-19 symptoms and test positivity ranked similarly in a wide range of scenarios. Anosmia, fever, and respiratory symptoms consistently had the strongest effect estimates and were the most appropriate empirical signals for symptom-based public health surveillance in areas with insufficient testing or benchmarking capacity. Collaborative syndromic surveillance could enhance real-time epidemiological investigations and public health utility globally., Funding: National Institutes of Health, National Institute for Health Research, Alzheimer's Society, Wellcome Trust, and Massachusetts Consortium on Pathogen Readiness., Competing Interests: Declaration of interests ZOE Global codeveloped the app pro bono for non-commercial purposes. JW, JCP, and SG work for ZOE Global, and TDS is a consultant for ZOE Global. LHN, DAD, and ATC previously participated as investigators on a diet study unrelated to this work, which was supported by ZOE Global. ATC reports personal fees from Pfizer, Bayer Pharma, and Boehringer Ingelheim, outside the submitted work. All other authors declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Until broad vaccination coverage is reached and effective therapeutics are available, controlling population mobility (ie, changes in the spatial location of a population that affect the spread and distribution of pathogens) is one of the major interventions used to reduce transmission of SARS-CoV-2. However, population mobility differs across locations, which could reduce the effectiveness of pandemic control measures. Here we assess the extent to which socioeconomic factors are associated with reductions in population mobility during the COVID-19 pandemic, at both the city level in China and at the country level worldwide., Methods: In this retrospective, observational study, we obtained anonymised daily mobile phone location data for 358 Chinese cities from Baidu, and for 121 countries from Google COVID-19 Community Mobility Reports. We assessed the intra-city movement intensity, inflow intensity, and outflow intensity of each Chinese city between Jan 25 (when the national emergency response was implemented) and Feb 18, 2020 (when population mobility was lowest) and compared these data to the corresponding lunar calendar period from the previous year (Feb 5 to March 1, 2019). Chinese cities were classified into four socioeconomic index (SEI) groups (high SEI, high-middle SEI, middle SEI, and low SEI) and the association between socioeconomic factors and changes in population mobility were assessed using univariate and multivariable linear regression. At the country level, we compared six types of mobility (residential, transit stations, workplaces, retail and recreation, parks, and groceries and pharmacies) 35 days after the implementation of the national emergency response in each country and compared these to data from the same day of the week in the baseline period (Jan 3 to Feb 6, 2020). We assessed associations between changes in the six types of mobility and the country's sociodemographic index using univariate and multivariable linear regression., Findings: The reduction in intra-city movement intensity in China was stronger in cities with a higher SEI than in those with a lower SEI (r=-0·47, p<0·0001). However, reductions in inter-city movement flow (both inflow and outflow intensity) were not associated with SEI and were only associated with government control measures. In the country-level analysis, countries with higher sociodemographic and Universal Health Coverage indexes had greater reductions in population mobility (ie, in transit stations, workplaces, and retail and recreation) following national emergency declarations than those with lower sociodemographic and Universal Health Coverage indexes. A higher sociodemographic index showed a greater reduction in mobility in transit stations (r=-0·27, p=0·0028), workplaces (r=-0·34, p=0·0002), and areas retail and recreation (rxs=-0·30, p=0·0012) than those with a lower sociodemographic index., Interpretation: Although COVID-19 outbreaks are more frequently reported in larger cities, our analysis shows that future policies should prioritise the reduction of risks in areas with a low socioeconomic level-eg, by providing financial assistance and improving public health messaging. However, our study design only allows us to assess associations, and a long-term study is needed to decipher causality., Funding: Chinese Ministry of Science and Technology, Research Council of Norway, Beijing Municipal Science & Technology Commission, Beijing Natural Science Foundation, Beijing Advanced Innovation Program for Land Surface Science, National Natural Science Foundation of China, China Association for Science and Technology., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Competing Interests: IIB reports consulting for BlueDot, a social benefit corporation that tracks the spread of emerging infectious diseases. DNF reports personal fees from Pfizer, AstraZeneca, and Seqirus, outside the submitted work. This research was supported by the Department of Medicine COVID-19 Funding Opportunity, University of Toronto (LL-S). LL-S is supported by the University of Toronto, the Women's College Institute for Health System Solutions and Virtual Care, and The Peter Gilgan Centre for Women's Cancers at Women's College Hospital, in partnership with the Canadian Cancer Society. Acute Care Enhanced Surveillance is funded by the Ministry of Health and administrative support is provided by Kingston, Frontenac and Lennox & Addington Public Health. Data for this study were obtained from the Ontario Ministry of Health and Long-term Care as part of the province's emergency modelling table. The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Objectives. To examine the extent to which the phrases, "COVID-19" and "Chinese virus" were associated with anti-Asian sentiments. Methods. Data were collected from Twitter's Application Programming Interface, which included the hashtags "#covid19" or "#chinesevirus." We analyzed tweets from March 9 to 23, 2020, corresponding to the week before and the week after President Donald J. Trump's tweet with the phrase, "Chinese Virus." Our analysis focused on 1 273 141 hashtags. Results. One fifth (19.7%) of the 495 289 hashtags with #covid19 showed anti-Asian sentiment, compared with half (50.4%) of the 777 852 hashtags with #chinesevirus. When comparing the week before March 16, 2020, to the week after, there was a significantly greater increase in anti-Asian hashtags associated with #chinesevirus compared with #covid19 ( P  < .001). Conclusions. Our data provide new empirical evidence supporting recommendations to use the less-stigmatizing term "COVID-19," instead of "Chinese virus."

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.

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 (R t ) 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 (R t <1). Additionally, mask-wearing in 12 states was evaluated 2 weeks before and after statewide mandates., Findings: 378 207 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)., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Safety precautions and activity restrictions were common in the early, pre-vaccine phases of the COVID-19 pandemic. We hypothesized that higher levels of participation in potentially risky social and other activities would be associated with greater life satisfaction and perceived meaning in life. At the same time, prosocial COVID-preventive activities such as mask wearing should enhance life satisfaction., Method: We assessed the impact of COVID-preventive behaviors on psychological well-being in October 2020. A nationally representative sample of U.S. adults (n = 831) completed a demographic questionnaire, a COVID-related behaviors questionnaire, a Cantril's Ladder item, and the Multidimensional Existential Meaning Scale. Two hierarchical linear models were used to examine the potential impact of COVID-preventive behaviors on life satisfaction and meaning in life while accounting for the influence of demographic factors., Results: The study revealed significant positive relationships between COVID-preventive behaviors and subjective well-being. Wearing a mask was significantly associated with higher life satisfaction, while maintaining social distancing of six feet and avoiding large groups were significantly associated with higher perceived meaning in life. Social activities including dining at restaurants and visiting friends and family were also significantly associated with higher life satisfaction and meaning in life, respectively., Conclusion: The study's findings support the conclusion that disease prevention measures such as social distancing and mask wearing do not reduce, and may enhance, subjective well-being during a pandemic. Utilizing the unique context of the COVID-19 pandemic to examine relationships between behavior and subjective well-being, the study also indicates that shallow or medium-depth social activities are likely to be more central to life satisfaction, whereas narrower, deeper social interactions with friends and family are more important to perceived meaning in life., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Objectives: Rapid detection and surveillance of COVID-19 is essential to reducing spread of the virus. Inadequate screening capacity has hampered COVID-19 detection, while traditional infectious disease response has been delayed due to significant demands for healthcare resources, time and personnel. This study investigated whether an online health decision-support tool could supplement COVID-19 surveillance and detection in China and the USA., Setting: Daily website traffic to Thermia was collected from China and the USA, and cross-correlation analyses were used to assess the designated lag time between the daily time series of Thermia sessions and COVID-19 case counts from 22 January to 23 April 2020., Participants: Thermia is a validated health decision-support tool that was modified to include content aimed at educating users about Centers for Disease Control and Prevention recommendations on COVID-19 symptoms. An advertising campaign was released on Microsoft Advertising to refer searches for COVID-19 symptoms to Thermia., Results: The lead times observed for Thermia sessions to COVID-19 case reports was 3 days in China and 19 days in the USA. We found negative cross-correlation between the number of Thermia sessions and rates of influenza A and B, possibly due to the decreasing prevalence of influenza and the lack of specificity of the system for identification of COVID-19., Conclusion: This study suggests that early deployment of an online campaign and modified health decision-support tool may support identification of emerging infectious diseases like COVID-19. Researchers and public health officials should deploy web campaigns as early as possible in an epidemic to detect, identify and engage those potentially at risk to help prevent transmission of the disease., Competing Interests: Competing interests: EY-T is an employee at Microsoft, owner of Bing. All work described in the paper was done as part of his salaried employment., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The coronavirus disease 2019 (COVID-19) pandemic is straining public health systems worldwide, and major non-pharmaceutical interventions have been implemented to slow its spread 1-4 . During the initial phase of the outbreak, dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was primarily determined by human mobility from Wuhan, China 5,6 . Yet empirical evidence on the effect of key geographic factors on local epidemic transmission is lacking 7 . In this study, we analyzed highly resolved spatial variables in cities, together with case count data, to investigate the role of climate, urbanization and variation in interventions. We show that the degree to which cases of COVID-19 are compressed into a short period of time (peakedness of the epidemic) is strongly shaped by population aggregation and heterogeneity, such that epidemics in crowded cities are more spread over time, and crowded cities have larger total attack rates than less populated cities. Observed differences in the peakedness of epidemics are consistent with a meta-population model of COVID-19 that explicitly accounts for spatial hierarchies. We paired our estimates with globally comprehensive data on human mobility and predict that crowded cities worldwide could experience more prolonged epidemics.

Cardiovascular diseases are the leading cause of death globally. As cardiovascular risk factors continuously rise to pandemic levels, there is intense pressure worldwide to improve cardiac care in preventive cardiology, cardio-diagnostics, therapeutics, and interventional cardiology. Artificial intelligence (AI), an advanced branch of computer science has ushered in the fourth industrial revolution with myriad opportunities in healthcare including cardiology. The developed world has embraced the technology, and the pressure not to be left behind is intense for both policymakers and practicing physicians/cardiologists in low to middle-income countries (LMICs) like Nigeria. This is especially daunting for LMICs who are already plagued with a high burden of infectious disease, unemployment, physician burnt, brain drain, and a developing cardiac practice. Should the focus of cardiovascular care be on men or machines? Is the technology sustainable in a low-resource setting? What lessons did we learn from the COVID-19 pandemic? We attempt to zero in on the dilemmas of AI in the Nigerian setting including AI acceptance, the bottlenecks of cardiology practice in Nigeria, the role of AI, and the type of AI that may be adapted to strengthen cardiovascular care of Nigerians., (Copyright © 2024 Copyright: © 2024 Nigerian Journal of Clinical Practice.)

The current study investigated adolescents' experiences of COVID-19 anti-Chinese discrimination (i.e., vicariously witnessed, directly experienced), the consequences for mental health, and the moderating role of general pandemic stress. During Summer 2020, 106 adolescents (43% Latino/a/x, 19% Asian American, 13% Black/African American, 26% biracial/multiracial/other; 58% female) participated in a 14-day daily diary study. Path analyses revealed that more experiences of vicarious COVID-19 anti-Chinese discrimination were associated with greater anxious mood, depressed mood, and mental health stress, while direct COVID-19 anti-Chinese discrimination was unrelated to mental health outcomes. The interaction between vicarious COVID-19 anti-Chinese discrimination and general COVID-19 stress was significant for depressed mood; simple slope analyses showed that for adolescents reporting high levels of COVID-19 stress, more frequent experiences of vicarious COVID-19 anti-Chinese discrimination were associated with greater severity in depressed mood, but this link was nonsignificant for those reporting low levels of general pandemic stress. Findings from the current study underscore the pernicious effects of vicarious COVID-19 anti-Chinese discrimination on the mental health of minoritized youth beyond solely Asian Americans. Additionally, the results evince the need for future pandemic-response efforts to craft public health messaging that avoids the racialization of disease and subsequent stigmatization of ethnic-minority communities., (© 2023. W. Montague Cobb-NMA Health Institute.)

Diabetes, a chronic metabolic disorder disrupting blood sugar regulation, has emerged as a prominent silent pandemic. Uncontrolled diabetes predisposes an individual to develop fatal complications like cardiovascular disorders, kidney damage, and neuropathies and aggravates the severity of treatable infections. Escalating cases of Type 1 and Type 2 diabetes correlate with a global upswing in diabetes-linked mortality. As a growing global concern with limited preventive interventions, diabetes necessitates extensive research to mitigate its healthcare burden and assist ailing patients. An altered immune system exacerbated by chronic hyperinflammation heightens the susceptibility of diabetic individuals to microbial infections, including notable viruses like SARS-CoV-2, dengue, and influenza. Given such a scenario, we scrutinized the literature and compiled molecular pathways and signaling cascades related to immune compartments in diabetics that escalate the severity associated with the above-mentioned viral infections in them as compared to healthy individuals. The pathogenesis of these viral infections that trigger diabetes compromises both innate and adaptive immune functions and pre-existing diabetes also leads to heightened disease severity. Lastly, this review succinctly outlines available treatments for diabetics, which may hold promise as preventive or supportive measures to effectively combat these viral infections in the former., (© 2023 International Union of Biochemistry and Molecular Biology.)

Purpose: To examine within-individual time trends in mental well-being and factors influencing heterogeneity of these trends., Methods: Longitudinal telephone survey of adults over 3 waves from the New York City (NYC) Metropolitan area during the COVID-19 Pandemic. Participants reported depression using the Patient Health Questionnaire (PHQ)-8, anxiety using the Generalized Anxiety Disorder (GAD)-7, and past 30-day increases in tobacco or alcohol use at each wave. Adjusted mixed effects logistic regression models assessed time trends in mental well-being., Results: There were 1227 respondents. Over 3 study waves, there were statistically significant decreasing time trends in the odds of each outcome (adjusted OR (95% CI) 0.47 (0.37, 0.60); p < 0.001 for depression; aOR (95% CI) 0.55 (0.45, 0.66); p < 0.001 for anxiety; aOR (95% CI) 0.50 (0.35, 0.71); p < 0.001 for past 30-day increased tobacco use; aOR (95% CI) 0.31 (0.24, 0.40); p < 0.001 for past 30-day increased alcohol use). Time trends for anxiety varied by race and ethnicity (p value for interaction = 0.05, 4 df); anxiety declined over time among white, Black, Hispanic, and Other race and ethnicity but not among Asian participants., Conclusions: In a demographically varied population from the NYC Metropolitan area, depression, anxiety and increased substance use were common during the first months of the pandemic, but decreased over the following year. While this was consistently the case across most demographic groups, the odds of anxiety among Asian participants did not decrease over time., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.)

Background: The COVID-19 pandemic has caused significant disruptions to everyday life and has had social, political, and financial consequences that will persist for years. Several initiatives with intensive use of technology were quickly developed in this scenario. However, technologies that enhance epidemiological surveillance in contexts with low testing capacity and healthcare resources are scarce. Therefore, this study aims to address this gap by developing a data science model that uses routinely generated healthcare encounter records to detect possible new outbreaks early in real-time., Methods: We defined an epidemiological indicator that is a proxy for suspected cases of COVID-19 using the health records of Emergency Care Unit (ECU) patients and text mining techniques. The open-field dataset comprises 2,760,862 medical records from nine ECUs, where each record has information about the patient's age, reported symptoms, and the time and date of admission. We also used a dataset where 1,026,804 cases of COVID-19 were officially confirmed. The records range from January 2020 to May 2022. Sample cross-correlation between two finite stochastic time series was used to evaluate the models., Results: For patients with age 18 years, we find time-lag () = 72 days and cross-correlation () ~ 0.82, = 25 days and ~ 0.93, and = 17 days and ~ 0.88 for the first, second, and third waves, respectively., Conclusions: In conclusion, the developed model can aid in the early detection of signs of possible new COVID-19 outbreaks, weeks before traditional surveillance systems, thereby anticipating in initiating preventive and control actions in public health with a higher likelihood of success., (© 2024. The Author(s).)

Although it is widely acknowledged that racialized minorities may report lower COVID-19 vaccine willingness compared to non-Hispanic white individuals, what is less known, however, is whether the willingness to receive the COVID-19 vaccine also differs by citizenship. Understanding disparities in vaccine willingness by citizenship is particularly important given the misleading rhetoric of some political leaders regarding vaccine eligibility by citizenship status. This study used the 2020 California Health Interview Survey (n = 21,949) to examine disparities in vaccine willingness by race/ethnicity and citizenship among Asian, Latinx, and non-Hispanic white individuals. Overall, 77.7% of Californians indicated that they were willing to receive the COVID-19 vaccine if it was made available. However, there were distinct differences by race/ethnicity and citizenship. Asian people, regardless of citizenship, had the highest predicted probability of vaccine willingness, accounting for demographic, socioeconomic, and health factors. Non-citizen Latinx and non-citizen non-Hispanic white people had higher predicted probabilities of vaccine willingness compared to their US-born counterparts, accounting for demographic, socioeconomic, and health factors. Our results reveal that although vaccine willingness may be high among non-citizen individuals, it may not necessarily translate into actual vaccine uptake. Furthermore, while individual-level factors may account for some of the differences in vaccine willingness by race/ethnicity and citizenship, other institutional and structural barriers prevent vaccine uptake., (© 2022. W. Montague Cobb-NMA Health Institute.)

Background: COVID-19 disrupted elective operations, cancer screening, and routine medical care while simultaneously overwhelming hospital staff and supplies. Operations for gastrointestinal (GI) malignancies rely on endoscopic screening, staging, and neoadjuvant therapy (NAT), each of which was disrupted by the pandemic. The aim was to evaluate the effect of the COVID-19 pandemic on the US national rates of gastrointestinal oncologic operations., Methods: The Vizient Clinical Data Base® was queried for oncologic operations for esophageal, gastric, and colorectal malignancies with and without NAT from March 2019 to March 2022. Control chart analysis examined operative volume over time while Wilcoxon rank sum tests were used to compare mean monthly volume before and during the pandemic., Results: A total of 95,912 patients were identified over 36 months; 5.8% esophageal, 6.3% gastric, 77.5% colonic, and 10.4% rectal operations. Esophageal operative volume decreased for 9 months during the pandemic and was significantly lower during than before the pandemic (p=0.002). Gastric operations decreased for 10 months early in the pandemic, but rebounded so that after 2 years volumes were unchanged (p=0.49). Colonic operations experienced a sharp decrease for 4 months at the beginning of the pandemic, but volumes quickly increased and overall were unchanged (p=0.29). Rectal operations decreased for 13 months and were significantly lower during than before the pandemic (p=0.018). Oncologic operations for patients receiving NAT varied., Conclusion: COVID-19 significantly disrupted the volume of gastrointestinal oncologic operations in the USA. Esophageal and rectal oncologic operations experienced prolonged and significant reductions while gastric and colonic oncologic operations transiently decreased but rebounded during the pandemic., (© 2023. The Society for Surgery of the Alimentary Tract.)

Background: At the beginning of the COVID-19 pandemic in the United States in the spring of 2020, many Americans avoided the healthcare system, while those with COVID-19 symptoms were faced with decisions about seeking healthcare services for this novel virus., Methods: Using a probability sample (n = 1088) from the Michigan adult population of PCR-confirmed COVID-19 cases who were diagnosed prior to July 31, 2020, we used logistic regression to examine sociodemographic and symptom severity predictors of care-seeking behaviors. The analyses examined three different outcomes: (1) whether respondents sought care and, among those who sought care, whether they sought care from (2) a primary care provider or (3) an emergency room. Final models were adjusted for sex, age, race and ethnicity, income, education, marital status, living arrangement, health insurance, and self-reported symptom severity., Results: We found that participants ages 65 and older had 4.00 times higher odds of seeking care than 18-34-year-olds (95% CI: 2.21, 7.24), while adults reporting very severe symptoms had roughly 15 times higher odds of seeking care than those with mild symptoms (95% CI: 7.73, 27.01). Adults who were non-Hispanic Black or were uninsured had lower odds of seeking care from a primary care physician versus seeking care from other locations in comparison to adults who were non-Hispanic White or were privately insured, respectively (non-Hispanic Black: aOR = 0.27, 95% CI: 0.16, 0.44; Uninsured: aOR = 0.19, 95% CI: 0.09, 0.42). Conversely, adults who were older or reported more severe symptoms had higher odds of seeking care from an emergency room versus other locations in comparison to adults who were younger or reported less severe symptoms (Age 65+: aOR = 2.96, 95% CI: 1.40, 6.28; Very Severe Symptoms: aOR = 6.63, 95% CI: 3.33, 13.20)., Conclusions: Our results suggest differential utilization of healthcare services early in the COVID-19 pandemic. Further analyses are needed to examine the reasons for these differences., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Prior studies have mainly examined factors regarding COVID-19 vaccination intentions. This study investigated the factors associated with COVID-19 vaccination behaviors in Korean adults. A total of 620 adults recruited from a survey company between July and August 2021 completed an online survey asking about their personal characteristics, health beliefs, and COVID-19 vaccination status. The collected data were analyzed using descriptive statistics, Pearson's χ2 test, independent-samples t test, and logistic regression analysis. Less than half the participants received COVID-19 vaccinations, whereas 56.3% did not. The full regression model explained 33.3% of the variance in COVID-19 vaccination status. Age older than 60 years, perception of feeling healthy, presence of chronic diseases, past flu shot experiences, and five health belief model factors were significant factors associated with COVID-19 vaccination behaviors. COVID-19 vaccination intention was the most closely related factor (odds ratio, 12.37; 95% confidence interval, 3.54-43.26; P < .001). Vaccinated participants were more likely than unvaccinated to perceive susceptibility to COVID-19 infection, benefits, self-efficacy, moral responsibility, and subjective norms regarding COVID-19 vaccination. Based on the results, vaccinated and unvaccinated individuals showed different attitudes toward COVID-19 infection and vaccination. This study suggests that COVID-19 vaccination intentions lead to actual vaccination behavior., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Travel restrictions, while delaying the spread of an emerging disease from the source, could inflict substantial socioeconomic burden. Travel-related policies, such as quarantine and testing of travelers, may be considered as alternative strategies to mitigate the negative impact of travel bans. We developed a meta-population, delay-differential model to evaluate a strategy that combines testing of travelers prior to departure from the source of infection with quarantine and testing at exit from quarantine in the destination population. Our results, based on early parameter estimates of SARS-CoV-2 infection, indicate that testing travelers at exit from quarantine is more effective in delaying case importation than testing them before departure or upon arrival. We show that a 1-day quarantine with an exit test could outperform a longer, 3-day quarantine without testing in delaying the outbreak peak. Rapid, large-scale testing capacities with short turnaround times provide important means of detecting infectious cases and reducing case importation, while shortening quarantine duration for travelers at destination., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: During the recent coronavirus disease 2019 (COVID-19) pandemic, preferences for factors associated with vaccines have been evaluated. Three oral antiviral drugs have been approved in Japan for patients with mild-to-moderate I COVID-19 symptoms. Although preferences for the drugs may also depend on various factors, these have not been fully evaluated., Methods: A conjoint analysis was performed based on an online survey in August 2022 to estimate the intangible costs of factors associated with oral antiviral drugs for COVID-19. Respondents were individuals aged 20-69 across Japan. The attributes included the company (Japanese/foreign) that developed the drug, formulation and size of the drug, frequency of administration per day, number of tablets/capsules per dose, number of days until no longer infectious to others, and out-of-pocket expenses. A logistic regression model was applied to estimate the utility of each level for each attribute. The intangible costs were calculated by comparing the utility to the out-of-pocket attribute., Results: Responses were collected from 11,303 participants. The difference between levels was the largest for companies that developed a drug; the intangible costs were JPY 5390 higher for the foreign company than for the Japanese company. The next largest difference was in the number of days until one is no longer infectious. For the same formulation, the intangible cost was lower for small sizes than large sizes. For similar-sized tablets and capsules, the intangible cost was lower for tablets than capsules. These tendencies were similar regardless of COVID-19 infection history and the presence of risk factors for severe COVID-19 in the respondents., Conclusion: Intangible costs for factors associated with oral antiviral drugs among the Japanese population were estimated. The results may change as the number of people with a history of COVID-19 infection increases and significant progress is made regarding treatments., (© 2023. The Author(s).)

Objective: To investigate how often patients are diagnosed with new-onset tinnitus within 21 days after COVID-19 vaccination in comparison to after three other common vaccinations: influenza, Tdap (tetanus, diphtheria, and acellular pertussis), and polysaccharide pneumococcus., Methods: The TriNetX Analytics Network, a federated health research network that aggregates the de-identified electronic health record (EHR) data of over 78 million patients, was queried for patients receiving each vaccination. Instances of new-onset tinnitus within 21 days of vaccination were recorded and reported., Results: Out of 2,575,235 patients receiving a first dose of the mRNA COVID-19 vaccine without any prior tinnitus diagnosis, 0.038% (95% CI: 0.036%-0.041%) of patients had a new diagnosis of tinnitus within 21 days. There was a higher risk of a new tinnitus diagnosis after the influenza vaccine (RR: 1.95, 95% CI: 1.72-2.21), Tdap vaccine (RR: 2.36, 95% CI: 1.93-2.89), and pneumococcal vaccine (RR: 1.97, 95% CI: 1.48-2.64) than after the first dose of the COVID-19 vaccine. There was a lower risk of a new tinnitus diagnosis after the second dose of COVID-19 than after the first dose (RR: 0.80, 95% CI: 0.71-0.91)., Conclusion: The rate of newly diagnosed tinnitus acutely after the first dose of the COVID-19 vaccine is very low. There was a higher risk of newly diagnosed tinnitus after influenza, Tdap, and pneumococcal vaccinations than after the COVID-19 vaccine. The present findings can help to address COVID-19 vaccine hesitancy during the ongoing pandemic., Level of Evidence: Level 3 Laryngoscope, 133:1722-1725, 2023., (© 2022 The Authors. The Laryngoscope published by Wiley Periodicals LLC on behalf of The American Laryngological, Rhinological and Otological Society, Inc.)

The SARS-CoV-2 is a deceptive virus. Despite the remarkable progress in genetic sequencing and subsequent vaccine development, the world continues to grapple with the ominous threats of rapidly appearing SARS-CoV-2 variants. The objective of this manuscript is to rank world countries based on the anticipated scope of COVID-19 morbidity and mortality, measured in terms of prevalence per 1 million persons, from the lowest to the highest. The ranking of 162 countries is based on predictions of empirical models, which include three explanatory variables: hospital beds per thousand persons, population density, and the median age of the country's population. Referring to the COVID-19 scope of morbidity, the lowest likelihood of infection is obtained in Niger and Mali, where the dominant characteristic is the young median age (15.1-16.4 years). Referring to the COVID-19 scope of mortality, the lowest likelihood is obtained in Singapore. For Singapore, the dominant feature is the high population density. The optimal solution is intensive vaccination campaigns in the initial phase of the pandemic, particularly among countries with low GDP per capita. Yet, vaccinations may work only where the personal immune system is healthy and thus respond by creating antibodies to the SARS-CoV2 virus. Referring to populations that lack the natural protection of the healthy immune system and thus cannot be vaccinated (e.g., old people, cancer patients undergoing chemotherapy treatments), a complementary solution might be coordination between countries and the establishment of field hospitals, testing laboratories, isolation of areas, humanitarian aid-in the same manner of treatment in other disasters like earthquakes., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: The 2019 novel coronavirus (COVID-19) pandemic has been associated with poor mental health outcomes and widened health disparities in the United States. Given the inter-relationship between psychosocial factors and functional outcomes in orthopaedic surgery, it is important that we understand whether patients presenting for musculoskeletal care during the pandemic were associated with worse physical and mental health than before the pandemic's onset., Questions/purposes: (1) Did patients seen for an initial visit by an orthopaedic provider during the COVID-19 pandemic demonstrate worse physical function, pain interference, depression, and/or anxiety than patients seen before the pandemic, as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) instrument? (2) During the COVID-19 pandemic, did patients living in areas with high levels of social deprivation demonstrate worse patterns of physical function, pain interference, depression, or anxiety on initial presentation to an orthopaedic provider than patients living in areas with low levels of social deprivation, compared with prepandemic PROMIS scores?, Methods: This was a retrospective, comparative study of new patient evaluations that occurred in the orthopaedic department at a large, urban tertiary care academic medical center. During the study period, PROMIS computer adaptive tests were routinely administered to patients at clinical visits. Between January 1, 2019, and December 31, 2019, we identified 26,989 new patients; we excluded 4% (1038 of 26,989) for being duplicates, 4% (1034 of 26,989) for having incomplete demographic data, 44% (11,925 of 26,989) for not having a nine-digit home ZIP Code recorded, and 5% (1332 of 26,989) for not completing all four PROMIS computer adaptive tests of interest. This left us with 11,660 patients in the "before COVID-19" cohort. Between January 1, 2021 and December 31, 2021, we identified 30,414 new patients; we excluded 5% (1554 of 30,414) for being duplicates, 4% (1142 of 30,414) for having incomplete demographic data, 41% (12,347 of 30,414) for not having a nine-digit home ZIP Code recorded, and 7% (2219 of 30,414) for not completing all four PROMIS computer adaptive tests of interest. This left us with 13,152 patients in the "during COVID-19" cohort. Nine-digit home ZIP Codes were used to determine patients' Area Deprivation Indexes, a neighborhood-level composite measure of social deprivation. To ensure that patients included in the study represented our overall patient population, we performed univariate analyses on available demographic and PROMIS data between patients included in the study and those excluded from the study, which revealed no differences (results not shown). In the before COVID-19 cohort, the mean age was 57 ± 16 years, 60% (7046 of 11,660) were women, 86% (10,079 of 11,660) were White non-Hispanic, and the mean national Area Deprivation Index percentile was 47 ± 25. In the during COVID-19 cohort, the mean age was 57 ± 16 years, 61% (8051 of 13,152) were women, 86% (11,333 of 13,152) were White non-Hispanic, and the mean national Area Deprivation Index percentile was 46 ± 25. The main outcome measures in this study were the PROMIS Physical Function ([PF], version 2.0), Pain Interference ([PI], version 1.1), Depression (version 1.0), and Anxiety (version 1.0). PROMIS scores follow a normal distribution with a mean t-score of 50 and a standard deviation of 10. Higher PROMIS PF scores indicate better self-reported physical capability, whereas higher PROMIS PI, Depression, and Anxiety scores indicate more difficulty managing pain, depression, and anxiety symptoms, respectively. Clinically meaningful differences in PROMIS scores between the cohorts were based on a minimum clinically important difference (MCID) threshold of 4 points. Multivariable linear regression models were created to determine whether presentation to an orthopaedic provider during the pandemic was associated with worse PROMIS scores than for patients who presented before the pandemic. Regression coefficients (ß) represent the estimated difference in PROMIS scores that would be expected for patients who presented during the pandemic compared with patients who presented before the pandemic, after adjusting for confounding variables. Regression coefficients were evaluated in the context of clinical importance and statistical significance. Regression coefficients equal to or greater than the MCID of 4 points were considered clinically important, whereas p values < 0.05 were considered statistically significant., Results: We found no clinically important differences in baseline physical and mental health PROMIS scores between new patients who presented to an orthopaedic provider before the COVID-19 pandemic and those who presented during the COVID-19 pandemic (PROMIS PF: ß -0.2 [95% confidence interval -0.43 to 0.03]; p = 0.09; PROMIS PI: ß 0.06 [95% CI -0.13 to 0.25]; p = 0.57; PROMIS Depression: ß 0.09 [95% CI -0.14 to 0.33]; p = 0.44; PROMIS Anxiety: ß 0.58 [95% CI 0.33 to 0.84]; p < 0.001). Although patients from areas with high levels of social deprivation had worse PROMIS scores than patients from areas with low levels of social deprivation, patients from areas with high levels of social deprivation demonstrated no clinically important differences in PROMIS scores when groups before and during the pandemic were compared (PROMIS PF: ß -0.23 [95% CI -0.80 to 0.33]; p = 0.42; PROMIS PI: ß 0.18 [95% CI -0.31 to 0.67]; p = 0.47; PROMIS Depression: ß 0.42 [95% CI -0.26 to 1.09]; p = 0.23; PROMIS Anxiety: ß 0.84 [95% CI 0.16 to 1.52]; p = 0.02)., Conclusion: Contrary to studies describing worse physical and mental health since the onset of the COVID-19 pandemic, we found no changes in the health status of orthopaedic patients on initial presentation to their provider. Although large-scale action to mitigate the effects of worsening physical or mental health of orthopaedic patients may not be needed at this time, orthopaedic providers should remain aware of the psychosocial needs of their patients and advocate on behalf of those who may benefit from intervention. Our study is limited in part to patients who had the self-agency to access specialty orthopaedic care, and therefore may underestimate the true changes in the physical or mental health status of all patients with musculoskeletal conditions. Future longitudinal studies evaluating the impact of specific COVID-19-related factors (for example, delays in medical care, social isolation, or financial loss) on orthopaedic outcomes may be helpful to prepare for future pandemics or natural disasters., Level of Evidence: Level II, prognostic study., Competing Interests: Each author certifies that there are no funding or commercial associations (consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article related to the author or any immediate family members. All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research® editors and board members are on file with the publication and can be viewed on request., (Copyright © 2023 by the Association of Bone and Joint Surgeons.)

COVID-19 inequities have been well-documented. We evaluated whether higher rates of severe COVID-19 in racial and ethnic minority groups were driven by higher infection rates by evaluating if disparities remained when analyses were restricted to people with infection. We conducted a retrospective cohort study of adults insured through Kaiser Permanente (Colorado, Northwest, Washington), follow-up in March-September 2020. Laboratory results and hospitalization diagnosis codes identified individuals with COVID-19. Severe COVID-19 was defined as invasive mechanical ventilation or mortality. Self-reported race and ethnicity, demographics, and medical comorbidities were extracted from health records. Modified Poisson regression estimated adjusted relative risks (aRRs) of severe COVID-19 in full cohort and among individuals with infection. Our cohort included 1,052,774 individuals, representing diverse racial and ethnic minority groups (e.g., 68,887 Asian, 41,243 Black/African American, 93,580 Hispanic or Latino/a individuals). Among 7,399 infections, 442 individuals experienced severe COVID-19. In the full cohort, severe COVID-19 aRRs for Asian, Black/African American, and Hispanic individuals were 2.09 (95% CI: 1.36, 3.21), 2.02 (1.39, 2.93), and 2.09 (1.57, 2.78), respectively, compared to non-Hispanic Whites. In analyses restricted to individuals with COVID-19, all aRRs were near 1, except among Asian Americans (aRR 1.82 [1.23, 2.68]). These results indicate increased incidence of severe COVID-19 among Black/African American and Hispanic individuals is due to higher infection rates, not increased susceptibility to progression. COVID-19 disparities most likely result from social, not biological, factors. Future work should explore reasons for increased severe COVID-19 risk among Asian Americans. Our findings highlight the importance of equity in vaccine distribution., (© 2022. W. Montague Cobb-NMA Health Institute.)

Background: Around the world, policymakers have clearly communicated that COVID-19 vaccination programs need to be accepted by a large proportion of the population to allow life return to normal. However, according to the Center for Disease Control, about 31% of the United States population had not completed the primary vaccination series as of November 2022., Aims: The primary aim of this work is to identify the factors associated by American citizens with the decision to be vaccinated against COVID-19. In addition, the proportion of fatal events from COVID-19 vaccinations was estimated and compared with the data in the VAERS database., Methods: An online survey of COVID-19 health experiences was conducted. Information was collected regarding reasons for and against COVID-19 inoculations, experiences with COVID-19 illness and COVID-19 inoculations by survey respondents and their social circles. Logit regression analyses were carried out to identify factors influencing the likelihood of being vaccinated., Results: A total of 2840 participants completed the survey between December 18 and 23, 2021. 51% (1383 of 2840) of the participants were female and the mean age was 47 (95% CI 46.36-47.64) years. Those who knew someone who experienced a health problem from COVID-19 were more likely to be vaccinated (OR: 1.309, 95% CI 1.094-1.566), while those who knew someone who experienced a health problem following vaccination were less likely to be vaccinated (OR: 0.567, 95% CI 0.461-0.698). 34% (959 of 2840) reported that they knew at least one person who had experienced a significant health problem due to the COVID-19 illness. Similarly, 22% (612 of 2840) of respondents indicated that they knew at least one person who had experienced a severe health problem following COVID-19 vaccination. With these survey data, the total number of fatalities due to COVID-19 inoculation may be as high as 278,000 (95% CI 217,330-332,608) when fatalities that may have occurred regardless of inoculation are removed., Conclusion: Knowing someone who reported serious health issues either from COVID-19 or from COVID-19 vaccination are important factors for the decision to get vaccinated. The large difference in the possible number of fatalities due to COVID-19 vaccination that emerges from this survey and the available governmental data should be further investigated., (© 2023. The Author(s).)

Background: Stringent nonpharmaceutical interventions (NPIs) have been implemented worldwide to combat the COVID-19 pandemic, and the circulation and seasonality of common respiratory viruses have subsequently changed. There have been few multicentre studies or comparisons of the prevalence of respiratory viruses accounting for community-acquired pneumonia (CAP) in hospitalized children between the pre-COVID period and the period after community and school reopening in the setting of the zero-COVID policy., Methods: We included 1543 children with CAP who required hospitalization from November 1, 2020 to April 30, 2021 (period 1), and 629 children with the same conditions from November 1, 2018, to April 30, 2019 (period 2), in our study. All respiratory samples from these patients were screened for six respiratory viruses (respiratory syncytial virus [RSV], adenovirus [ADV], influenza A virus [Flu A], influenza B virus [Flu B], parainfluenza virus type 1 [PIV1], and parainfluenza virus type 3 [PIV3]) using a multiplex real-time PCR assay., Results and Conclusions: The median ages of the enrolled patients at the time of diagnosis were 1.5 years and 1.0 years for period 1 and period 2, respectively. In period 1, viral pathogens were detected in 50.3% (776/1543) of the enrolled patients. The most frequently identified viral pathogen was RSV (35.9%, 554/1543), followed by PIV3 (9.6%, 148/1543), PIV1 (3.6%, 56/1543), ADV (3.4%, 52/1543), Flu A (1.0%, 16/1543), and Flu B (0.8%, 13/1543). The total detection rates of these six viruses in the peak season of CAP were at the pre-COVID level. The prevalence of Flu A decreased dramatically, and circulation activity was low compared to pre-COVID levels, while the incidence of PIV3 increased significantly. There were no significant differences in the detection rates of RSV, ADV, Flu B, and PIV1 between the two periods. Our results showed that respiratory viruses accounted for CAP in hospitalized children at pre-COVID levels as communities and schools reopened within the zero-COVID policy, although the prevalence aetiology spectrum varied., (© 2023. The Author(s).)

Predicting infectious disease outbreak impacts on population, healthcare resources and economics and has received a special academic focus during coronavirus (COVID-19) pandemic. Focus on human disease outbreak prediction techniques in current literature, Marques et al. (Predictive models for decision support in the COVID-19 crisis. Springer, Switzerland, 2021) state that there are four main methods to address forecasting problem: compartmental models, classic statistical models, space-state models and machine learning models. We adopt their framework to compare our research with previous works. Besides being divided by methods, forecasting problems can also be divided by the number of variables that are considered to make predictions. Considering this number of variables, forecasting problems can be classified as univariate, causal and multivariate models. Multivariate approaches have been applied in less than 10% of research found. This research is the first attempt to evaluate, over real time-series data of 3 different countries with univariate and multivariate methods to provide a short-term prediction. In literature we found no research with that scope and aim. A comparison of univariate and multivariate methods has been conducted and we concluded that besides the strong potential of multivariate methods, in our research univariate models presented best results in almost all regions' predictions., (© 2022. The Author(s), under exclusive licence to Society for Mathematical Biology.)

Objective: Little is known regarding the reactogenicity and related SARS-CoV-2 vaccine response in patients with chronic inflammatory disease (CID). Our objective was to characterize the adverse event profile of CID patients following SARS-CoV-2 vaccination and understand the relationship between reactogenicity and immunogenicity of SARS-CoV-2 vaccines., Methods: CID patients and healthy controls eligible to receive messenger RNA (mRNA) SARS-CoV-2 vaccines participated in 3 study visits (pre-vaccine, after dose 1, and after dose 2) in which blood and clinical data were collected. Assessment of adverse events were solicited within 7 days of receiving each dose. Serum anti-SARS-CoV-2 spike IgG ± antibody titers were quantified following vaccination. Statistical analysis was performed utilizing mixed models and tobit regressions, with adjustment for covariates., Results: The present study included 441 participants (322 CID patients and 119 control subjects). Compared to controls, CID patients reported greater symptom severity after dose 1 (P = 0.0001), including more myalgia and fatigue (P < 0.05). For immunogenicity, a higher symptom severity after dose 1 and a higher number of symptoms after dose 2 was associated with higher antibody titers (P ≤ 0.05). Each increase of 1 symptom was associated with a 15.1% increase in antibody titer. Symptom association was strongest with site pain after dose 1 (105%; P = 0.03) and fatigue after dose 2 (113%; P = 0.004)., Conclusion: Patients with CID have a distinct reactogenicity profile following SARS-CoV-2 vaccination compared to controls. Furthermore, there is an association between increased reactogenicity and increased vaccine response. This finding may speak to the more variable immunogenicity in CID patients and may be an important indicator of vaccine response to the novel SARS-CoV-2 vaccines., (© 2022 American College of Rheumatology.)

Introduction: People with cancer are at higher risk of serious illness and death from COVID-19 infection. We investigated COVID-19 vaccine uptake among patients with solid organ and blood cancers and explored factors related to hesitancy., Methods: Cross-sectional online survey of adults with a history of cancer at three health services across metropolitan and regional Victoria. Vaccine hesitancy was measured by the validated Oxford COVID-19 vaccine hesitancy scale., Results: There were 1073 respondents: 56% female; median age 62 years (range 23 - 91). Commonest tumor types included breast 29%, gastrointestinal 19%, hematological 15%, genitourinary 15%, and lung 8%. Thirty-six percent had metastatic disease, and 54% were receiving active anticancer treatment. Eighty-four percent of respondents indicated positive intent toward COVID-19 vaccination, 10% were undecided, and 6% indicated negative attitudes. At least one vaccine dose had been received by 65% of respondents, leaving 35% unvaccinated. Fifty-eight percent of unvaccinated patients answered that they would "definitely" or "probably" take a vaccine. Higher vaccine uptake was significantly associated with older age, male gender, English as first language, longer time since cancer diagnosis, and not being on current anticancer treatment. Concerns regarding vaccine side effects, particularly thrombosis, and the desire for clear medical advice were prominent among unvaccinated respondents., Conclusion: Despite being eligible for COVID-19 vaccination since March 2021, a substantial minority of patients with cancer remained unvaccinated as of August 2021. Targeted communication and educational resources addressing vaccine safety in the context of cancer are key to promoting vaccine uptake in this vulnerable population., (© 2022 John Wiley & Sons Australia, Ltd.)