BACKGROUND: Hepatitis E virus (HEV), the causative agent of hepatitis E, is a common but self-limiting disease. However, in immunosuppressed kidney transplant 47 recipients (KTRs), HEV infection can become chronic. We investigated risk factors associated with HEV infection among 271 KTRs at the Johns Hopkins Hospital transplanted between 1988 and 2012. METHODS: HEV infection was defined as having positive anti-HEV IgM, anti-HEV IgG, or HEV RNA. The risk factors included: age at transplant, sex, hemodialysis/peritoneal dialysis, plasmapheresis, transfusions, community urbanization, and other socioeconomic factors. Logistic regression was used to determine independent risk factors associated with HEV infection. RESULTS: Out of 271 KTRs, 43 (16%) had HEV infection though not active disease. HEV infection in KTRs was associated with older age (≥45 years; OR = 4.04; 95% CI = 1.81-57 10.03; p = 0.001) and living in communities with low proportions of minorities (OR = 0.22; 95% 58 CI = 0.04-0.90; p = 0.046). CONCLUSION: KTRs who had HEV infection may be at an increased risk of developing chronic HEV.

Background Cardiac complications related to COVID-19 in children and adolescents include ventricular dysfunction, myocarditis, coronary artery aneurysm, and bradyarrhythmias, but tachyarrhythmias are less understood. The goal of this study was to evaluate the frequency, characteristics, and outcomes of children and adolescents experiencing tachyarrhythmias while hospitalized for acute severe COVID-19 or multisystem inflammatory syndrome in children. Methods and Results This study involved a case series of 63 patients with tachyarrhythmias reported in a public health surveillance registry of patients aged <21 years hospitalized from March 15, 2020, to December 31, 2021, at 63 US hospitals. Patients with tachyarrhythmias were compared with patients with severe COVID-19-related complications without tachyarrhythmias. Tachyarrhythmias were reported in 22 of 1257 patients (1.8%) with acute COVID-19 and 41 of 2343 (1.7%) patients with multisystem inflammatory syndrome in children. They included supraventricular tachycardia in 28 (44%), accelerated junctional rhythm in 9 (14%), and ventricular tachycardia in 38 (60%); >1 type was reported in 12 (19%). Registry patients with versus without tachyarrhythmia were older (median age, 15.4 [range, 10.4-17.4] versus 10.0 [range, 5.4-14.8] years) and had higher illness severity on hospital admission. Intervention for treatment of tachyarrhythmia was required in 37 (59%) patients and included antiarrhythmic medication (n=31, 49%), electrical cardioversion (n=11, 17%), cardiopulmonary resuscitation (n=8, 13%), and extracorporeal membrane oxygenation (n=9, 14%). Patients with tachyarrhythmias had longer hospital length of stay than those who did not, and 9 (14%) versus 77 (2%) died. Conclusions Tachyarrhythmias were a rare complication of acute severe COVID-19 and multisystem inflammatory syndrome in children and adolescents and were associated with worse clinical outcomes, highlighting the importance of close monitoring, aggressive treatment, and postdischarge care.

BACKGROUND: It is unclear how acute coronavirus disease 2019 (COVID-19)-directed therapies are used in children with life-threatening COVID-19 in US hospitals. We described characteristics of children hospitalized in the intensive care unit or step-down unit (ICU/SDU) who received COVID-19-directed therapies and the specific therapies administered. METHODS: Between March 15, 2020 and December 27, 2020, children <18 years of age in the ICU/SDU with acute COVID-19 at 48 pediatric hospitals in the United States were identified. Demographics, laboratory values, and clinical course were compared in children who did and did not receive COVID-19-directed therapies. Trends in COVID-19-directed therapies over time were evaluated. RESULTS: Of 424 children in the ICU/SDU, 235 (55%) received COVID-19-directed therapies. Children who received COVID-19-directed therapies were older than those who did not receive COVID-19-directed therapies (13.3 [5.6-16.2] vs 9.8 [0.65-15.9] years), more had underlying medical conditions (188 [80%] vs 104 [55%]; difference = 25% [95% CI: 16% to 34%]), more received respiratory support (206 [88%] vs 71 [38%]; difference = 50% [95% CI: 34% to 56%]), and more died (8 [3.4%] vs 0). Of the 235 children receiving COVID-19-directed therapies, 172 (73%) received systemic steroids and 150 (64%) received remdesivir, with rising remdesivir use over the study period (14% in March/April to 57% November/December). CONCLUSION: Despite the lack of pediatric data evaluating treatments for COVID-19 in critically ill children, more than half of children requiring intensive or high acuity care received COVID-19-directed therapies.

BACKGROUND: Previous studies of severe acute respiratory syndrome coronavirus 2 infection in infants have incompletely characterized factors associated with severe illness or focused on infants born to mothers with coronavirus disease 2019 (COVID-19). Here we highlight demographics, clinical characteristics and laboratory values that differ between infants with and without severe acute COVID-19. METHODS: Active surveillance was performed by the Overcoming COVID-19 network to identify children and adolescents with severe acute respiratory syndrome coronavirus 2-related illness hospitalized at 62 sites in 31 states from March 15 to December 27, 2020. We analyzed patients aged >7 days to <1 year hospitalized with symptomatic acute COVID-19. RESULTS: We report 232 infants aged >7 days to <1 year hospitalized with acute symptomatic COVID-19 from 37 US hospitals in our cohort from March 15 to December 27, 2020. Among 630 cases of severe COVID-19 in patients aged >7 days to <18 years, 128 (20.3%) were infants. In infants with severe illness from the entire study period, the median age was 2 months, 66% were from racial and ethnic minority groups, 66% were previously healthy, 73% had respiratory complications, 13% received mechanical ventilation and <1% died. CONCLUSIONS: Infants accounted for over a fifth of children aged <18 years hospitalized for severe acute COVID-19, commonly manifesting with respiratory symptoms and complications. Although most infants hospitalized with COVID-19 did not suffer significant complications, longer term outcomes remain unclear. Notably, 75% of infants with severe disease were <6 months of age in this cohort study period, which predated maternal COVID-19 vaccination, underscoring the importance of maternal vaccination for COVID-19 in protecting the mother and infant.

IMPORTANCE: Refinement of criteria for multisystem inflammatory syndrome in children (MIS-C) may inform efforts to improve health outcomes. OBJECTIVE: To compare clinical characteristics and outcomes of children and adolescents with MIS-C vs those with severe coronavirus disease 2019 (COVID-19). SETTING, DESIGN, AND PARTICIPANTS: Case series of 1116 patients aged younger than 21 years hospitalized between March 15 and October 31, 2020, at 66 US hospitals in 31 states. Final date of follow-up was January 5, 2021. Patients with MIS-C had fever, inflammation, multisystem involvement, and positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcriptase-polymerase chain reaction (RT-PCR) or antibody test results or recent exposure with no alternate diagnosis. Patients with COVID-19 had positive RT-PCR test results and severe organ system involvement. EXPOSURE: SARS-CoV-2. MAIN OUTCOMES AND MEASURES: Presenting symptoms, organ system complications, laboratory biomarkers, interventions, and clinical outcomes. Multivariable regression was used to compute adjusted risk ratios (aRRs) of factors associated with MIS-C vs COVID-19. RESULTS: Of 1116 patients (median age, 9.7 years; 45% female), 539 (48%) were diagnosed with MIS-C and 577 (52%) with COVID-19. Compared with patients with COVID-19, patients with MIS-C were more likely to be 6 to 12 years old (40.8% vs 19.4%; absolute risk difference [RD], 21.4% [95% CI, 16.1%-26.7%]; aRR, 1.51 [95% CI, 1.33-1.72] vs 0-5 years) and non-Hispanic Black (32.3% vs 21.5%; RD, 10.8% [95% CI, 5.6%-16.0%]; aRR, 1.43 [95% CI, 1.17-1.76] vs White). Compared with patients with COVID-19, patients with MIS-C were more likely to have cardiorespiratory involvement (56.0% vs 8.8%; RD, 47.2% [95% CI, 42.4%-52.0%]; aRR, 2.99 [95% CI, 2.55-3.50] vs respiratory involvement), cardiovascular without respiratory involvement (10.6% vs 2.9%; RD, 7.7% [95% CI, 4.7%-10.6%]; aRR, 2.49 [95% CI, 2.05-3.02] vs respiratory involvement), and mucocutaneous without cardiorespiratory involvement (7.1% vs 2.3%; RD, 4.8% [95% CI, 2.3%-7.3%]; aRR, 2.29 [95% CI, 1.84-2.85] vs respiratory involvement). Patients with MIS-C had higher neutrophil to lymphocyte ratio (median, 6.4 vs 2.7, P < .001), higher C-reactive protein level (median, 152 mg/L vs 33 mg/L; P < .001), and lower platelet count (<150 ×103 cells/μL [212/523 {41%} vs 84/486 {17%}, P < .001]). A total of 398 patients (73.8%) with MIS-C and 253 (43.8%) with COVID-19 were admitted to the intensive care unit, and 10 (1.9%) with MIS-C and 8 (1.4%) with COVID-19 died during hospitalization. Among patients with MIS-C with reduced left ventricular systolic function (172/503, 34.2%) and coronary artery aneurysm (57/424, 13.4%), an estimated 91.0% (95% CI, 86.0%-94.7%) and 79.1% (95% CI, 67.1%-89.1%), respectively, normalized within 30 days. CONCLUSIONS AND RELEVANCE: This case series of patients with MIS-C and with COVID-19 identified patterns of clinical presentation and organ system involvement. These patterns may help differentiate between MIS-C and COVID-19.

BACKGROUND: For pandemic preparedness, researchers used online systematic searches to track unplanned school closures (USCs). We determine if Twitter provides complementary data. METHODS: Twitter handles of Michigan public schools and school districts were identified. All tweets associated with these handles were downloaded. USC-related tweets were identified using 5 keywords. Descriptive statistics and multivariable logistic regression were performed in R. RESULTS: Among 3469 Michigan public schools, 2003 maintained their own active Twitter accounts or belonged to school districts with active Twitter accounts. Of these 2003 schools, in 2015-2016 school year, at least 1 USC announcement was identified for 349 schools via the current method only, 678 schools via Twitter only, and 562 schools via both methods. No USC announcements were identified for 414 schools. Rural schools were less likely than city schools to have active Twitter coverage (adjusted relative risk [adjRR] = 0.3956, 95% confidence interval [CI] 0.3312-0.4671), and to announce USCs on Twitter (adjRR = 0.5692, 95% CI 0.4645-0.6823), but more likely to have USCs identified by the current method (adjRR = 1.4545, 95% CI 1.3545-1.5490). CONCLUSIONS: Each method identified USCs that were missed by the other. Our results suggested that identifying USCs on Twitter is complementary to the current method.

OBJECTIVE: Hurricane Harvey, which made landfall in Texas on August 24, 2017, caused catastrophic damage that resulted in the closure of many schools and school districts across 4 states. We evaluated the underlying reasons and characteristics of the unplanned school closures to gain insight on how communities may cope with recommended preemptive closures as an intervention for pandemic influenza. METHODS: Information was extracted from news articles, school websites, and Twitter and Facebook posts previously collected through daily systematic searches of Google, Google News, and Lexis-Nexis. This information was sorted into predefined categories describing the characteristics that may be associated with unplanned school closures that occur during a natural disaster. RESULTS: Across Texas, Louisiana, Kentucky, and Tennessee, there were 3026 unplanned closures. Sixty-three percent of the closures occurred in Texas. The main reasons for the closures were flooding, power outages, and structural damage. The closed schools in Texas were sometimes used as shelters or as locations for providing food or other resources. CONCLUSION: School closures associated with Hurricane Harvey were attributed to both the effects of the hurricane and use for resource allocation. These findings can help inform preparedness planning and response for future hurricane seasons and other large-scale emergencies.

BACKGROUND: The Office of Advanced Molecular Detection (OAMD), Centers for Disease Control and Prevention (CDC), manages a Twitter profile (@CDC_AMD). To our knowledge, no prior study has analyzed a CDC Twitter handle's entire contents and all followers. OBJECTIVE: This study aimed to describe the contents and followers of the Twitter profile @CDC_AMD and to assess if attaching photos or videos to tweets posted by @CDC_AMD would increase retweet frequency. METHODS: Data of @CDC_AMD were retrieved on November 21, 2016. All followers (N=809) were manually categorized. All tweets (N=768) were manually coded for contents and whether photos or videos were attached. Retweet count for each tweet was recorded. Negative binomial regression models were applied to both the original and the retweet corpora. RESULTS: Among the 809 followers, 26.0% (210/809) were individual health professionals, 11.6% (94/809) nongovernmental organizations, 3.3% (27/809) government agencies' accounts, 3.3% (27/809) accounts of media organizations and journalists, and 0.9% (7/809) academic journals, with 54.9% (444/809) categorized as miscellaneous. A total of 46.9% (360/768) of @CDC_AMD's tweets referred to the Office's website and their current research; 17.6% (135/768) referred to their scientists' publications. Moreover, 80% (69/86) of tweets retweeted by @CDC_AMD fell into the miscellaneous category. In addition, 43.4% (333/768) of the tweets contained photos or videos, whereas the remaining 56.6% (435/768) did not. Attaching photos or videos to original @CDC_AMD tweets increases the number of retweets by 37% (probability ratio=1.37, 95% CI 1.13-1.67, P=.002). Content topics did not explain or modify this association. CONCLUSIONS: This study confirms CDC health communicators' experience that original tweets created by @CDC_AMD Twitter profile sharing images or videos (or their links) received more retweets. The current policy of attaching images to tweets should be encouraged.