Characteristics and Outcomes of US Children and Adolescents With Multisystem Inflammatory Syndrome in Children (MIS-C) Compared With Severe Acute COVID-19

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

Data from: Two-scale dispersal estimation for biological invasions via synthetic likelihood

Biological invasions reshape environments and affect the ecological and economic welfare of states and communities. Such invasions advance on multiple spatial scales, complicating their control. When modeling stochastic dispersal processes, intractable likelihoods and autocorrelated data complicate parameter estimation. As with other approaches, the recent synthetic likelihood framework for stochastic models uses summary statistics to reduce this complexity; however, it additionally provides usable likelihoods, facilitating the use of existing likelihood-based machinery. Here, we extend this framework to parameterize multi-scale spatio-temporal dispersal models and compare existing and newly developed spatial summary statistics to characterize dispersal patterns. We provide general methods to evaluate potential summary statistics and present a fitting procedure that accurately estimates dispersal parameters on simulated data. Finally, we apply our methods to quantify the short and long range dispersal of Chagas disease vectors in urban Arequipa, Peru, and assess the feasibility of a purely reactive strategy to contain the invasion

Jerusalen jittered data

This has the Jerusalen data described in the article, with X/Y jittered to prevent exact recognition of infested households (confidentiality issues). X: longitude in UTM, Y: longitude in UTM, OLDSTATUS: status (infested 0/1) in 2009, STATUS: status (infested 0/1) in 2011

Prevalence and Transmission of Trypanosoma cruzi in People of Rural Communities of the High Jungle of Northern Peru.

BACKGROUND:Vector-borne transmission of Trypanosoma cruzi is seen exclusively in the Americas where an estimated 8 million people are infected with the parasite. Significant research in southern Peru has been conducted to understand T. cruzi infection and vector control, however, much less is known about the burden of infection and epidemiology in northern Peru. METHODOLOGY:A cross-sectional study was conducted to estimate the seroprevalence of T. cruzi infection in humans (n=611) and domestic animals [dogs (n=106) and guinea pigs (n=206)] in communities of Cutervo Province, Peru. Sampling and diagnostic strategies differed according to species. An entomological household study (n=208) was conducted to identify the triatomine burden and species composition, as well as the prevalence of T. cruzi in vectors. Electrocardiograms (EKG) were performed on a subset of participants (n=90 T. cruzi infected participants and 170 age and sex-matched controls). The seroprevalence of T. cruzi among humans, dogs, and guinea pigs was 14.9% (95% CI: 12.2-18.0%), 19.8% (95% CI: 12.7-28.7%) and 3.3% (95% CI: 1.4-6.9%) respectively. In one community, the prevalence of T. cruzi infection was 17.2% (95% CI: 9.6-24.7%) among participants < 15 years, suggesting recent transmission. Increasing age, positive triatomines in a participant's house, and ownership of a T. cruzi positive guinea pig were independent correlates of T. cruzi infection. Only one species of triatomine was found, Panstrongylus lignarius, formerly P. herreri. Approximately forty percent (39.9%, 95% CI: 33.2-46.9%) of surveyed households were infested with this vector and 14.9% (95% CI: 10.4-20.5%) had at least one triatomine positive for T. cruzi. The cardiac abnormality of right bundle branch block was rare, but only identified in seropositive individuals. CONCLUSIONS:Our research documents a substantial prevalence of T. cruzi infection in Cutervo and highlights a need for greater attention and vector control efforts in northern Peru

A map and photo depicting the study region in the Peruvian high jungle.

<p>A map of Peru shows the region that contains the Huancabamba River Valley (A) and an inset illustrates where the communities of Casa Blanca, La Esperanza, Campo Florido, Pindoc, Rumiaco and Nuevo Guayaquil are situated (B). A photograph illustrates the town center of Campo Florido to exemplify close proximity of houses, crude housing materials, and mountainous terrain (C). Photo: Alroy.</p

Multivariate analysis for <i>T</i>. <i>cruzi</i> positive serology in people of rural communities in Cajamarca, Peru.

<p>^<i>§</i>Reference category</p><p>Multivariate analysis for <i>T</i>. <i>cruzi</i> positive serology in people of rural communities in Cajamarca, Peru.</p

Univariate analysis, risk factors for <i>T</i>. <i>cruzi</i> positive serology in rural communities of Cajamarca, Peru.

<p>¹ T. cruzi positive human participants that are also described by the covariate category on the left</p><p>N = Human serosurvey participants</p><p>²OR, odds ratio; CI, confidence interval</p><p>^§Reference category</p><p>Univariate analysis, risk factors for <i>T</i>. <i>cruzi</i> positive serology in rural communities of Cajamarca, Peru.</p

A bar graph representing seroprevalence of <i>T</i>. <i>cruzi</i> infection for each age category by community.

<p>Age-specific patterns of seroprevalence by community. In the communities of Campo Florido and Rumiaco, seroprevalence in children is notably high. This is contrary to the trend of cumulative incidence in older people correlating with a higher seroprevalence, as seen in the other communities.</p