Bell Palsy Incidence in Patients with Post-COVID: A Retrospective Study

Bell palsy is caused by impaired functioning of the 7th cranial nerve. A disparity in the stable state of the cytokine regulatory axis and a cytokine storm are observed to occur from the binding of the ACE2 to the COVID, and the subsequent functional alterations in the ACE2/AT2R suggest that COVID-19 may use direct or indirect processes to produce neurological symptoms. Increased cases of Bell palsy were reported during the CoV pandemic, so our study aimed to estimate the incidence rate of Bell palsy among COVID-19 patients in South Bangalore, India. Secondary data of patients with Bell palsy were obtained retrospectively from two multispecialty Hospitals in South Bangalore. COVID positive populations were collected between the period of March 2021 and February 2022, and many Bell palsy cases within 3 months of post-Covid period were included. Confirmatory calls were made for patients with Covid Positive who were not diagnosed to discover the occurrence of Bell palsy. A retrospective analysis of Bell palsy cases found 11 incidences between March 2021 and February 2022, when there were 1577 COVID patients in total. According to descriptive statistical analysis, the prevalence of Bell palsy increased by 0.7% during the COVID-19 pandemic. Bell palsy could be considered one of the neurological complications among COVID-19 patients, and appropriate preventative measures should be taken.Copyright © 2023 International Journal of Nutrition, Pharmacology, Neurological Diseases Published by Wolters Kluwer - Medknow.

Patterns in Child Health Outcomes Before and After the COVID-19 Outbreak in India.

This cross-sectional study examines prepandemic-to-postpandemic changes in mortality, nutrition and feeding practices, anthropometry, vaccination, and other measures in a sample of children from the Indian National Family Health Survey.

Uncovering inequities in Covid-19 vaccine coverage for adults and elderly in Brazil: A multilevel study of 2021-2022 data.

Vaccination is crucial for reducing severe COVID-19 cases, hospitalizations, and deaths. However, vaccine access disparities within countries, particularly in low- and middle-income nations, may leave disadvantaged regions and populations behind. This study aimed to investigate potential inequalities in vaccine coverage among Brazilian aged 18 years and older based on demographic, geographic, and socioeconomic characteristics at the municipal level. A total of 389 million vaccination records from the National Immunization Program Information System were analyzed to calculate vaccine coverage rates for the first, second, and booster doses among adults (18-59 years) and elderly (60 + years) vaccinated between January 2021 and December 2022. We analyzed the data by gender and used a three-level (municipalities, states, regions) multilevel regression analysis to assess the association between vaccine coverage and municipal characteristics. Vaccination coverage was higher among the elderly than among adults, particularly for the second and booster doses. Adult women showed higher coverage rates than men (ranging from 118 % to 25 % higher along the analyzed period). Significant inequalities were observed when analyzing the evolution of vaccination coverage by sociodemographic characteristics of municipalities. In the early stages of the vaccination campaign, municipalities with higher per capita Gross Domestic Product (pGDP), educational level, and fewer Black residents reached higher population coverages earlier. In December 2022, adult and elderly booster vaccine coverage was 43 % and 19 %, respectively, higher in municipalities in the highest quintile of educational level. Higher vaccine uptake was also observed in municipalities with fewer Black residents and higher pGDP. Municipalities accounted for most of the variance in vaccine coverage (59.7 %-90.4 % depending on the dose and age group). This study emphasizes the inadequate booster coverage and the presence of socioeconomic and demographic disparities in COVID-19 vaccination rates. These issues must be addressed through equitable interventions to avoid potential disparities in morbidity and mortality.

India's lockdown: an interim report.

The world has continued to change rapidly since the last version of this article was written on May 20, 2020. Yet, as this article goes to press, we are aware of two realities; first, that we cannot perennially chase a moving target, but second, that nothing about the fundamental trends that we have identified appear to have changed. India is firmly in the throes of a vicious pandemic that we can only hope will abate with the development of an effective vaccine. Our plea for the widespread provision of adequate health and medical facilities, adequate protection for the elderly, and transfers to those severely affected by the lockdown are absolutely unchanged in the face of the latest data. In contrast, the brutal enforcement of a lockdown with none of these accompanying measures can only worsen outcomes for the poorest and most vulnerable among the population.

Video Compression using Deep Neural Networks

Advanced video compression is required due to the rise of online video content. A strong compression method can help convey video data effectively over a constrained bandwidth. We observed how more internet usage for video conferences, online gaming, and education led to decreased video quality from Netflix, YouTube, and other streaming services in Europe and other regions, particularly during the COVID-19 epidemic. They are represented in standard video compression algorithms as a succession of reference frames after residual frames, and these approaches are limited in their application. Deep learning's introduction and current advancements have the potential to overcome such problems. This study provides a deep learning-based video compression model that meets or exceeds current H.264 standards. © 2022 IEEE.

Clinical Trial Facilitators: A Novel Approach to Support the Execution of Clinical Research at the Study Site Level

In the summer of 2020, there were multiple efforts to establish safe and effective vaccines that would combat the spread of COVID-19. Efforts to eradicate the virus in the United States included Operation Warp Speed (OWS) which was a partnership between the Departments of Health and Human Services (HHS) and Defense (DOD), and the private sector, that aimed to help accelerate control of the COVID-19 pandemic by advancing development, manufacturing, and distribution of vaccines, therapeutics, and diagnostics. As the nation's largest integrated healthcare system, the US Department of Veterans Affairs (VA) was identified as a potential collaborator in several large-scale OWS Phase III clinical trial efforts designed to evaluate the safety and efficacy of various vaccines in development. Given the national (and global) importance of these trials, it was recognized that there would be a need for a coordinated, centralized effort within VA to ensure that its medical centers (sites) would be ready and able to efficiently initiate, recruit, and enroll into these OWS COVID-19 vaccine trials. To accomplish this mission, two groups within the VA Office of Research and Development (ORD) partnered to manage and provide support to these sites and facilitate their execution of these trials. The Partnered Research Program (PRP) is a division of VA ORD that is dedicated to developing partnerships that enhance Veterans' access to high-quality, multi-site clinical trials. PRP has an overall goal of establishing long-term relationships with external organizations that are committed to Veterans' health and VA's clinical research mission. The VA Cooperative Studies Program (CSP) is a clinical research infrastructure embedded within the VA healthcare system. CSP is also a division of the VA ORD and was established to provide coordination for, and enable cooperation on, multi-site clinical trials and epidemiological studies that fall within the purview of VA. Its infrastructure comprises a number of Coordinating Centers that are responsible for the planning and conduct of large multi-site clinical trials in the VA healthcare system. CSP also established a consortium of 10 VA medical centers (VAMCs) called the Network of Dedicated Enrollment Sites (NODES) that have teams (nodes) to provide site-level expertise and innovative approaches in addressing challenges to clinical trial execution. This (poster) outlines the partnership and activities undertaken by VA's PRP and CSP NODES groups to manage and support a large-scale OWS Phase III multi-site clinical trial. It focuses specifically on the determination to designate clinical trial facilitators to study sites, the important role that they played in getting this trial initiated at those sites in a timely fashion, and their work to ensure successful study enrollment.

The Psychological Costs of the COVID-19 Pandemic and Heterogeneous Effects in South Korea: Evidence from a Difference-in-Differences Analysis.

This study estimates the effects of the COVID-19 pandemic on life satisfaction and stress and examines whether these effects vary across different sociodemographic groups using a nationally representative sample in South Korea. We estimate the causal effects of COVID-19 on psychological well-being by exploiting regional variation in the spread of the pandemic in South Korea. While the number of confirmed cases was very small in other provinces in the first half of 2020, the coronavirus spread rapidly in Daegu after an outbreak in one church. We employ a difference-in-differences approach that compares changes in people's life satisfaction and stress before-and-after the initial surge of COVID-19 cases in Daegu and other provinces. Our results show that the proportion of people who are dissatisfied with life increased by 2.8-6.5 percentage points more in Daegu than in other provinces after the COVID-19 outbreak. During the same period, the proportion of people who reported feeling stressed increased more in Daegu than in other provinces by 5.8-8.9 percentage points. Our results also suggest that the negative impact of the COVID-19 outbreak on psychological well-being is significantly greater for men, young adults, middle-aged adults, self-employed workers, and middle-income individuals. On the other hand, the proportion of people who report feeling stressed among the highest-educated (a master's degree or higher) and high-income individuals decreased after the onset of the COVID-19 outbreak.

The Psychological Costs of the COVID-19 Pandemic and Heterogeneous Effects in South Korea: Evidence from a Difference-in-Differences Analysis

This study estimates the effects of the COVID-19 pandemic on life satisfaction and stress and examines whether these effects vary across different sociodemographic groups using a nationally representative sample in South Korea. We estimate the causal effects of COVID-19 on psychological well-being by exploiting regional variation in the spread of the pandemic in South Korea. While the number of confirmed cases was very small in other provinces in the first half of 2020, the coronavirus spread rapidly in Daegu after an outbreak in one church. We employ a difference-in-differences approach that compares changes in people’s life satisfaction and stress before-and-after the initial surge of COVID-19 cases in Daegu and other provinces. Our results show that the proportion of people who are dissatisfied with life increased by 2.8–6.5 percentage points more in Daegu than in other provinces after the COVID-19 outbreak. During the same period, the proportion of people who reported feeling stressed increased more in Daegu than in other provinces by 5.8–8.9 percentage points. Our results also suggest that the negative impact of the COVID-19 outbreak on psychological well-being is significantly greater for men, young adults, middle-aged adults, self-employed workers, and middle-income individuals. On the other hand, the proportion of people who report feeling stressed among the highest-educated (a master’s degree or higher) and high-income individuals decreased after the onset of the COVID-19 outbreak.

Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases.

The study aims to analyze inequalities in Covid-19 outcomes in Brazil in 2020/2021 according to the per capita Gross Domestic Product (pcGDP) of municipalities. All cases of Severe Acute Respiratory Syndrome (SARS) who were hospitalized or died, regardless of hospitalization, registered in Brazil in 2020 and 2021 were analyzed (n = 2,902,742), including those with a confirmed diagnosis of Covid-19 (n = 1,894,165). We calculated lethality due to Covid-19, the performance of diagnostic tests among patients with SARS, and the hospital care received by those with Covid-19 according to the pcGDP of the patients' municipalities of residence. Data were analyzed for each epidemiological week and the risk of each outcome was estimated using Poisson regression. Municipalities in the lowest pcGDP decile had (i) 30% (95%CI 28%-32%) higher lethality from Covid-19, (ii) three times higher proportion of patients with SARS without the collection of biological material for the diagnosis of Covid-19, (iii) 16% (95%CI 15%-16%) higher proportion of SARS patients testing in a period longer than two days from the onset of symptoms, (iv) 140% (95%CI 134%-145%) higher absence of CT scan use. There is deep socioeconomic inequality among Brazilian municipalities regarding the occurrence of Covid-19 negative outcomes.

INDIA’S LOCKDOWN*

In response to the Covid-19 pandemic, a prolonged and stringent lockdown unaccompanied by adequate State provisioning of welfare support could lead to distress and loss of life in developing countries like India. The problem is particularly acute in settings with widespread informality and casual labor arrangements, along with inadequate private savings to withstand a crisis. Lives compromised by the rigors of lockdown would then need to be weighed against lives rescued from Covid-19 infection, with the further complication of reckoning whose lives - either lost or saved - would be involved in the tradeoff. This leads to what might be termed a “lives versus lives” perspective on the problem. That perspective, while still favoring a lockdown - provided compensatory relief measures are fully implemented - leads to the prescription of a relaxed lockdown when those measures are inadequate. Such a prescription is strengthened when the vast majority of the population is under the age of 60. In the relaxed lockdown, the working-age population is allowed to work, while affording protection to the elderly and pursuing a relentless campaign of testing, tracing and quarantining. This approach to the problem is discussed in the present chapter. © 2022 selection and editorial matter, Rajib Bhattacharyya, Ananya Ghosh Dastidar and Soumyen Sikdar;individual chapters, the contributors.

The Cancer Genomics Cloud enables bioinformatics training in a hybrid educational world

The Cancer Genomics Cloud (CGC), powered by Seven Bridges, is an NCI-funded platform that streamlines access to large cancer datasets, bioinformatic tools, and cloud computation for cancer researchers. The attributes of the CGC designed to democratize data analysis also make it ideal for training the next generation of data scientists. During the Covid-19 pandemic, it has become clear that remote/virtual learning is of great importance for workforce development, and that reducing barriers to high quality educational resources is critical for many populations. Here we present our best practices for education of bioinformatics using the CGC, taking advantage of both distributed cloud networks and platform features to enhance learning. Our best practices methods are focused on a systematic approach that takes the instructor and students through a typical bioinformatics workflow in their field of research. Briefly, the organizational structure of the CGC, known as “projects,” contains all aspects of an analysis, including data files, tools, and tool settings. Projects have fine-grained permission settings, which allow the owner to securely share their project for viewing or editing. An instructor can generate an example analysis from start to finish then share an entire project with trainees. Both students and instructors have access to the same data on the cloud, so the teacher can pre-populate the projects with specific files, ensuring the same starting point. All members within the project can communicate, including adding notes directly on the results, allowing students to troubleshoot in real time with the teacher. Instructors can manage costs for the whole class through the CGC's billing system. The CGC also provides Public Projects for self-guided training, where a researcher can learn by example using the data, tools, and completed tasks within the project, including detailed instructions embedded in markdown language. We have successfully used these methods to train masters students in bioinformatics at Georgetown University for three years, as well as high school students, college students, and current cancer researchers. This approach to virtual learning of bioinformatics can democratize training for the next generation of data scientists. The FAIR practices built into the CGC enables education across all levels of expertise, empowering users to drive cancer research from any stage of their career.

Assessing the prevalence of young children living in households prepared for COVID-19 in 56 low- and middle-income countries.

BACKGROUND: The COVID-19 pandemic and governments' attempts to contain it are negatively affecting young children's health and development in ways we are only beginning to understand and measure. Responses to the pandemic are driven largely by confining children and families to their homes. This study aims to assess the levels of and associated socioeconomic disparities in household preparedness for protecting young children under the age of five from being exposed to communicable diseases, such as COVID-19, in low- and middle-income countries (LMICs). METHODS: Using data from nationally representative household surveys in 56 LMICs since 2016, we estimated the percentages of young children under the age of five living in households prepared for communicable diseases (e.g., COVID-19) and associated residential and wealth disparities at the country- and aggregate-level. Preparedness was defined on the basis of space for quarantine, adequacy of toilet facilities and hand hygiene, mass media exposure at least once a week, and phone ownership. Disparities within countries were measured as the absolute gap in two domains-household wealth and residential area - and compared across regions and country income groups. RESULTS: The final data set included 766,313 children under age five. On average, 19.4% of young children in the 56 countries lived in households prepared for COVID-19, ranging from 0.6% in Ethiopia in 2016 to 70.9% in Tunisia in 2018. In close to 90% of countries (50), fewer than 50% of young children lived in prepared households. Young children in rural areas or in the poorest households were less likely to live in prepared households than their counterparts. CONCLUSIONS: A large portion of young children under the age of five in LMICs were living in households that did not meet all preparedness guidelines for preventing COVID-19 and caring for patients at home. This study highlights the need to ensure all families in LMICs have the means to prevent the spread of the pandemic or other communicable illnesses to young children during pandemics.

Measuring Covid Mortality

The most widely used measure of covid mortality is a headcount ratio of deaths due to covid, as captured by the case fatality rate, which is the ratio of covid deaths to covid cases. This is a relative measure of mortality, in contrast to the absolute measure of an aggregate headcount, as captured by the gross or aggregate fatality, which is just the raw (non-normalized) number of covid deaths. The present note examines two elementary principles which a measure of mortality (like one of poverty or urbanisation or unemployment) might be expected to satisfy. These are what are called the probability principle and the subgroup consistency principle respectively. Headcount ratios are found to satisfy the first principle but not the second, and aggregate headcounts to satisfy the second principle but not the first, which makes neither variety of a headcount measure satisfactory on its own, and by itself. This note advances the case of a “mixed” measure, as intermediate between ratio and aggregate measures, expressed as a geometric mean of the case fatality rate and the gross fatality. The ranking of countries by mortality is found to be a variable function of the precise mortality indicator employed. © 2022 Human Development and Capability Association.

Bronchoscopic management of tracheobronchial mucormycosis

Introduction: Mucormycosis is a catastrophic, opportunistic infection with a high mortality rate. Incidence of Pulmonary mucormycosis has gone up in the post covid-19 era. Treatment includes combined surgical and medical therapy. Mucormycosis involving major airway is difficult to treat because, the surgical options are limited. We present a case series of tracheobronchial mucormycosis, managed by combined bronchoscopic interventions and medical therapy. Case Series: Case 1: 30 years old diabetic female presented with stridor. Bronchoscopy showed mass lesion arising from carina extending to lower trachea causing obstruction. Biopsy revealed Mucormycosis. The lesion was completely debulked by using rigid bronchoscopy, cryoprobe, electrosurgical knife. Intravenous amphotericin was for 6 weeks. Follow-up bronchoscopy showed no recurrence. Case 2: 45 years old diabetic male who had Covid-19 recently, presented with cough. Bronchoscopy revealed near-total occlusion left main bronchus by fleshy lesion destroying medial wall and communicating with the mediastinum. Lesion was removed by bronchoscopic methods and intra-lesional amphotericin was injected in multiple sittings along with intravenous amphotericin therapy followed by oral posaconazole. Follow-up bronchoscopy showed complete healing of left main bronchus. Case 3: 25-year-old diabetic male, presented with stridor. Bronchoscopy revealed complete destruction of the upper trachea by necrotic infection extending to paratracheal tissue on right side. Silicon tracheal stent was placed to stabilize trachea and patient was continued on intra-lesional and intravenous amphotericin therapy. Interim bronchoscopy in after 2 weeks showed partial healing of the lesion however patient missed for follow up after 3 weeks of amphotericin therapy. Conclusion: Surgical options for tracheobronchial mucormycosis are limited. Bronchoscopic methods may be tried to treat the disease locally along with intravenous amphotericin therapy when Surgical options are exhausted.

Severe progressive fibrosing interstitial lung disease post COVID 19 infection

Background: Majority of COVID 19 patients that are hospitalized are with respiratory illness including pneumonia and ARDS.The acute manifestations of COVID 19 has been well documented however long-term sequelae from acute COVID 19 remain speculative. Chronic lung disease including IPF is a risk factor for poorer prognosis in COVID 19 infection. Case Study: A 52-year-old male patient presented to emergency department with history of dyspnea on and off for past 6 months increased over last two days, cough with expectoration for past 2 months. Eight months back he was treated for COVID 19 pneumonia with dexamethasone and maximal oxygen requirement of 2L via nasal cannula. CT chest showed diffuse GGO's in bilateral upper and lower lobes with CT severity score of 20/25. Patient was discharged with no oxygen requirement with saturation of 96% on room air. On arrival to the hospital, patient was tachypneic and in type 1 respiratory failure, requiring 10L of oxygen. CT chest showed honeycombing with consolidation and traction bronchiectasis. Discussion: Advanced fibrosis and poor lung function are associated with severe disease and poorer prognosis in COVID 19 infection. CD 209L receptors has been implied in the pathogenesis of progressive ILD in COVID 19 infection. Conclusion: Early detection of potential cases of post- COVID 19 pulmonary fibrosis may give a chance to prevent or at least modify such disabling complication.

CRISIS Ventilator: Pilot Study of a Three-Dimensional-Printed Gas-Powered Resuscitator in a Porcine Model

The coronavirus disease of 2019 (COVID-19) has altered medical practice around the globe and revealed critical deficiencies in hospital supply chains ranging from adequate personal protective equipment to life-sustaining ventilators for critically ill hospitalized patients. We developed the CRISIS ventilator, a gas-powered resuscitator that functions without electricity, and which can be manufactured using hobby-level three-dimensional (3D) printers and standard off-the-shelf equipment available at the local hardware store. CRISIS ventilators were printed and used to ventilate sedated female Yorkshire pigs over 24-h. Pulmonary and hemodynamic values were recorded throughout the 24-h run, and serial arterial blood samples were obtained to assess ventilation and oxygenation. Lung tissue was obtained from each pig to evaluate for signs of inflammatory stress. All five female Yorkshire pigs survived the 24-h study period without suffering from hypoxemia, hypercarbia, or severe hypotension requiring intervention. One animal required rescue at the beginning of the experiment with a traditional ventilator due to leakage around a defective tracheostomy balloon. The wet/dry ratio was 6.74 +/- 0.19 compared to historical controls of 7.1 +/- 4.2 (not significantly different). This proof-of-concept study demonstrates that our 3D-printed CRISIS ventilator can ventilate and oxygenate a porcine model over the course of 24-h with stable pulmonary and hemodynamic function with similar levels of ventilation-related inflammation when compared with a previous control porcine model. Our work suggests that virtual stockpiling with just-in-time 3D-printed equipment, like the CRISIS ventilator, can temporize shortages of critical infrastructure needed to sustain life for hospitalized patients.

Infusing culture in compartmental epidemic models

There has been a recent surge of interest in modeling and forecasting epidemic outbreaks. Human behavior plays a key role in disease transmission and prevention. In this paper, we propose a systematic approach to model the effects of changes in human behavior by infusing socio-cultural factors within compartmentalized epidemic models. In particular, we have identified risk perception beliefs as critical epidemic related socio-cultural factors. We evaluated our model using the 2009 H1N1 epidemic scenario in Mexico and a preliminary COVID-19 scenario in the US. Our results show that including cultural information from even a sparse, small subset of events provides a significant improvement in prediction accuracy and explanatory capabilities. © 2021 IEEE

PREPARE-IBD: Physician responses to disease flares and patient adaptation in relation to events in inflammatory bowel disease during the COVID-19 pandemic: A multicentre cohort analysis

Background: The COVID-19 pandemic continues to pose complex problems across Europe and the world, with rising numbers of infections and the ongoing need for drastic public health interventions. This is difficult for patients with immune-mediated disorders like Inflammatory Bowel Disease (IBD), where immunosuppressive medications may affect susceptibility to serious infection. It was particularly challenging for physicians and patients during the first wave of the pandemic, when it was unclear whether anti-inflammatory flare treatment should be adapted to reduce infection risk, whilst trying to ensure symptomatic control and avoid admission to overwhelmed hospitals. Despite the development of various IBD / COVID-19 databases, the treatment adaptations and outcomes of patients experiencing IBD flares during the COVID-19 pandemic remain undefined. We aimed to compare IBD management and outcomes between pandemic and prepandemic cohorts. Methods: An observational cohort study was performed, comprising patients who contacted IBD teams for a symptom flare between March - June, 2020 in, 60 National Health Service trusts in the United Kingdom. Data were compared to a pre-pandemic cohort after propensity- matching for age and disease severity. Statistical analyses were performed using R (version, 4.1.0, Vienna, Austria). Results: In total, 3728 patients in the pandemic (n=1864) and pre-pandemic (n=1864) cohorts were included. The principal findings were reduced systemic corticosteroid prescription during the pandemic in both Crohn's disease (prednisolone: pandemic, 199/752, 26.5% vs, 263/708, 37.1%;p<0.001) and ulcerative colitis (UC) (prednisolone: pandemic, 372/1112, 33.5% vs, 470/1156, 40.7%, p<0.001), with increases in poorly bioavailable oral corticosteroids in Crohn's (pandemic, 117/752, 15.6% vs, 48/708, 6.8%;p<0.001) and UC (pandemic, 131/1112, 11.8% vs, 60/1156, 5.2%;p<0.001). Ustekinumab (Crohn's and UC) and vedolizumab (UC) treatment also significantly increased during the pandemic. Three-month steroid-free remission was similar in both Crohn's (pandemic, 175/616, 28.4% vs, 195/608, 32.1%;p=0.17) and UC (pandemic, 312/858, 36.4% vs, 404/1006, 40.2%;p=0.095). The, 65 patients experiencing a flare and COVID-19 were more likely to have moderate-to-severely active disease at three months compared to those with a flare alone. Conclusion: Despite several treatment adaptations during the pandemic, steroid-free outcomes were comparable to pre-pandemic levels, though patients with a flare and COVID-19 experienced worse outcomes. These findings have implications for IBD management during future waves or pandemics.

Neighborhood socioeconomic inequality based on everyday mobility predicts COVID-19 infection in San Francisco, Seattle, and Wisconsin.

Race and class disparities in COVID-19 cases are well documented, but pathways of possible transmission by neighborhood inequality are not. This study uses administrative data on COVID-19 cases for roughly 2000 census tracts in Wisconsin, Seattle/King County, and San Francisco to analyze how neighborhood socioeconomic (dis)advantage predicts cumulative caseloads through February 2021. Unlike past research, we measure a neighborhood's disadvantage level using both its residents' demographics and the demographics of neighborhoods its residents visit and are visited by, leveraging daily mobility data from 45 million mobile devices. In all three jurisdictions, we find sizable disparities in COVID-19 caseloads. Disadvantage in a neighborhood's mobility network has greater impact than its residents' socioeconomic characteristics. We also find disparities by neighborhood racial/ethnic composition, which can be explained, in part, by residential and mobility-based disadvantage. Neighborhood conditions measured before a pandemic offer substantial predictive power for subsequent incidence, with mobility-based disadvantage playing an important role.