Combining genomics and epidemiology to track mumps virus transmission in the United States.

Unusually large outbreaks of mumps across the United States in 2016 and 2017 raised questions about the extent of mumps circulation and the relationship between these and prior outbreaks. We paired epidemiological data from public health investigations with analysis of mumps virus whole genome sequences from 201 infected individuals, focusing on Massachusetts university communities. Our analysis suggests continuous, undetected circulation of mumps locally and nationally, including multiple independent introductions into Massachusetts and into individual communities. Despite the presence of these multiple mumps virus lineages, the genomic data show that one lineage has dominated in the US since at least 2006. Widespread transmission was surprising given high vaccination rates, but we found no genetic evidence that variants arising during this outbreak contributed to vaccine escape. Viral genomic data allowed us to reconstruct mumps transmission links not evident from epidemiological data or standard single-gene surveillance efforts and also revealed connections between apparently unrelated mumps outbreaks.

Invasive Meningococcal Disease Among People Experiencing Homelessness-United States, 2016-2019.

BACKGROUND: Recently, several invasive meningococcal disease (IMD) outbreaks caused by Neisseria meningitidis have occurred among people experiencing homelessness (PEH). However, overall IMD risk among PEH is not well described. We compared incidence and characteristics of IMD among PEH and persons not known to be experiencing homelessness (non-PEH) in the United States. METHODS: We analyzed 2016-2019 IMD data from the National Notifiable Diseases Surveillance System and enhanced meningococcal disease surveillance. Incidence was calculated using US census data and point-in-time counts from the US Department of Housing and Urban Development. RESULTS: Of cases from states participating in enhanced surveillance during 2016-2019 (n = 1409), 45 cases (3.2%) occurred among PEH. Annual incidence was higher among PEH (2.12 cases/100 000) than non-PEH (0.11 cases/100 000; relative risk, 19.8; 95% confidence interval [CI], 14.8-26.7). Excluding outbreak-associated cases (PEH n = 18, 40%; non-PEH n = 98, 7.2%), incidence among PEH remained elevated compared to incidence in non-PEH (relative risk, 12.8; 95% CI, 8.8-18.8). Serogroup C was identified in 68.2% of PEH cases compared to 26.4% in non-PEH (P < .0001). CONCLUSIONS: PEH are at increased risk for IMD. Further assessment is needed to determine the feasibility and potential impact of meningococcal vaccination for PEH in the United States.

Outbreak of SARS-CoV-2 Infections, Including COVID-19 Vaccine Breakthrough Infections, Associated with Large Public Gatherings - Barnstable County, Massachusetts, July 2021.

During July 2021, 469 cases of COVID-19 associated with multiple summer events and large public gatherings in a town in Barnstable County, Massachusetts, were identified among Massachusetts residents; vaccination coverage among eligible Massachusetts residents was 69%. Approximately three quarters (346; 74%) of cases occurred in fully vaccinated persons (those who had completed a 2-dose course of mRNA vaccine [Pfizer-BioNTech or Moderna] or had received a single dose of Janssen [Johnson & Johnson] vaccine ≥14 days before exposure). Genomic sequencing of specimens from 133 patients identified the B.1.617.2 (Delta) variant of SARS-CoV-2, the virus that causes COVID-19, in 119 (89%) and the Delta AY.3 sublineage in one (1%). Overall, 274 (79%) vaccinated patients with breakthrough infection were symptomatic. Among five COVID-19 patients who were hospitalized, four were fully vaccinated; no deaths were reported. Real-time reverse transcription-polymerase chain reaction (RT-PCR) cycle threshold (Ct) values in specimens from 127 vaccinated persons with breakthrough cases were similar to those from 84 persons who were unvaccinated, not fully vaccinated, or whose vaccination status was unknown (median = 22.77 and 21.54, respectively). The Delta variant of SARS-CoV-2 is highly transmissible (1); vaccination is the most important strategy to prevent severe illness and death. On July 27, CDC recommended that all persons, including those who are fully vaccinated, should wear masks in indoor public settings in areas where COVID-19 transmission is high or substantial.* Findings from this investigation suggest that even jurisdictions without substantial or high COVID-19 transmission might consider expanding prevention strategies, including masking in indoor public settings regardless of vaccination status, given the potential risk of infection during attendance at large public gatherings that include travelers from many areas with differing levels of transmission.

Invasive Pneumococcal Disease After 2 Decades of Pneumococcal Conjugate Vaccine Use.

OBJECTIVES: We sought to describe the evolving epidemiology of invasive pneumococcal disease (IPD) among children in Massachusetts, United States, over the last 2 decades during which sequential 7-valent pneumococcal conjugate vaccines (PCV7) and 13-valent PCVs (PCV13) were implemented. METHODS: Cases of IPD in children aged <18 years were detected between 2002 and 2021 through an enhanced population-based, statewide surveillance system. Streptococcus pneumoniae isolates from normally sterile sites were serotyped and evaluated for antimicrobial susceptibility. IPD incidence rates and rate ratios with 95% confidence intervals (CIs) were calculated. RESULTS: We identified 1347 IPD cases. Incidence of IPD in children aged <18 years declined 72% over 2 decades between 2002 and 2021 (incidence rate ratios 0.28, 95% CI 0.18-0.45). IPD rates continued to decline after replacement of PCV7 with PCV13 (incidence rate ratios 0.25, 95% CI 0.16-0.39, late PCV7 era [2010] versus late PCV13 era [2021]). During the coronavirus disease 2019 pandemic years, 2020 to 2021, the rate of IPD among children aged <18 years reached 1.6 per 100 000, the lowest incidence observed over the 20 years. In PCV13 era, approximately one-third of the IPD cases in children aged >5 years had at least 1 underlying condition (98, 30.3%). Serotypes 19A and 7F contributed 342 (48.9%) of all cases before implementation of PCV13 (2002-2010). Serotype 3 (31, 8.6%), and non-PCV13 serotypes 15B/C (39, 10.8%), 33F (29, 8.0%), 23B (21, 0.8%), and 35B (17, 4.7%) were responsible for 37.8% of cases in PCV13 era (2011-2021). Penicillin nonsusceptibility continued to decline (9.8% vs 5.3% in pre-/late PCV13 era, P = .003), however has become more common among non-PCV13 serotypes compared with vaccine serotypes (14.8% vs 1.4%, P < .001). CONCLUSIONS: Robust ongoing surveillance networks are critical for identifying emerging serotypes and development of next-generation vaccine formulations.

Assessing the utility of COVID-19 case reports as a leading indicator for hospitalization forecasting in the United States.

Identifying data streams that can consistently improve the accuracy of epidemiological forecasting models is challenging. Using models designed to predict daily state-level hospital admissions due to COVID-19 in California and Massachusetts, we investigated whether incorporating COVID-19 case data systematically improved forecast accuracy. Additionally, we considered whether using case data aggregated by date of test or by date of report from a surveillance system made a difference to the forecast accuracy. Evaluating forecast accuracy in a test period, after first having selected the best-performing methods in a validation period, we found that overall the difference in accuracy between approaches was small, especially at forecast horizons of less than two weeks. However, forecasts from models using cases aggregated by test date showed lower accuracy at longer horizons and at key moments in the pandemic, such as the peak of the Omicron wave in January 2022. Overall, these results highlight the challenge of finding a modeling approach that can generate accurate forecasts of outbreak trends both during periods of relative stability and during periods that show rapid growth or decay of transmission rates. While COVID-19 case counts seem to be a natural choice to help predict COVID-19 hospitalizations, in practice any benefits we observed were small and inconsistent.

Assessing the utility of COVID-19 case reports as a leading indicator for hospitalization forecasting in the United States.

Identifying data streams that can consistently improve the accuracy of epidemiological forecasting models is challenging. Using models designed to predict daily state-level hospital admissions due to COVID-19 in California and Massachusetts, we investigated whether incorporating COVID-19 case data systematically improved forecast accuracy. Additionally, we considered whether using case data aggregated by date of test or by date of report from a surveillance system made a difference to the forecast accuracy. Evaluating forecast accuracy in a test period, after first having selected the best-performing methods in a validation period, we found that overall the difference in accuracy between approaches was small, especially at forecast horizons of less than two weeks. However, forecasts from models using cases aggregated by test date showed lower accuracy at longer horizons and at key moments in the pandemic, such as the peak of the Omicron wave in January 2022. Overall, these results highlight the challenge of finding a modeling approach that can generate accurate forecasts of outbreak trends both during periods of relative stability and during periods that show rapid growth or decay of transmission rates. While COVID-19 case counts seem to be a natural choice to help predict COVID-19 hospitalizations, in practice any benefits we observed were small and inconsistent.

Racial and Ethnic Disparities in Multisystem Inflammatory Syndrome in Children in the United States, March 2020 to February 2021.

BACKGROUND: The incidence of multisystem inflammatory syndrome in children (MIS-C) varies by race and ethnicity. This study assessed whether disparities in MIS-C in the United States by race and ethnicity exceed known disparities in coronavirus disease 2019 (COVID-19) incidence. METHODS: We compared the distribution of race and ethnicity among patients with MIS-C (<21 years of age, termed children) with onset March 2020 to February 2021 to that of children with COVID-19 and in the general population. Analysis was restricted to 369 counties with high completeness of race and ethnicity reporting for MIS-C and COVID-19. For each racial and ethnic group, observed numbers of patients with MIS-C were compared with expected numbers (observed/expected ratio) in children with COVID-19 and in the general population within these counties. RESULTS: Compared with children in the general population, MIS-C was more frequent among Hispanic (139% of expected) and non-Hispanic Black children (183%) and less frequent among non-Hispanic White (64%) and non-Hispanic Asian children (48%). Compared with children with COVID-19, MIS-C was more frequent in non-Hispanic Black children (207% of expected) and less frequent in non-Hispanic White children (68%); however, frequency was not different among Hispanic (102%) and non-Hispanic Asian (74%) children. CONCLUSIONS: Disparities in MIS-C by race and ethnicity exist, even after controlling for COVID-19 disparities and geographic variations. The high proportion of MIS-C among Hispanic children and low proportion among non-Hispanic Asian children align with COVID-19 rates, while the high proportion among non-Hispanic Black children and low proportion among non-Hispanic White children are not explainable by COVID-19 rates.

Incidence of Multisystem Inflammatory Syndrome in Children Among US Persons Infected With SARS-CoV-2.

Importance: Multisystem inflammatory syndrome in children (MIS-C) is associated with recent or current SARS-CoV-2 infection. Information on MIS-C incidence is limited. Objective: To estimate population-based MIS-C incidence per 1 000 000 person-months and to estimate MIS-C incidence per 1 000 000 SARS-CoV-2 infections in persons younger than 21 years. Design, Setting, and Participants: This cohort study used enhanced surveillance data to identify persons with MIS-C during April to June 2020, in 7 jurisdictions reporting to both the Centers for Disease Control and Prevention national surveillance and to Overcoming COVID-19, a multicenter MIS-C study. Denominators for population-based estimates were derived from census estimates; denominators for incidence per 1 000 000 SARS-CoV-2 infections were estimated by applying published age- and month-specific multipliers accounting for underdetection of reported COVID-19 case counts. Jurisdictions included Connecticut, Georgia, Massachusetts, Michigan, New Jersey, New York (excluding New York City), and Pennsylvania. Data analyses were conducted from August to December 2020. Exposures: Race/ethnicity, sex, and age group (ie, ≤5, 6-10, 11-15, and 16-20 years). Main Outcomes and Measures: Overall and stratum-specific adjusted estimated MIS-C incidence per 1 000 000 person-months and per 1 000 000 SARS-CoV-2 infections. Results: In the 7 jurisdictions examined, 248 persons with MIS-C were reported (median [interquartile range] age, 8 [4-13] years; 133 [53.6%] male; 96 persons [38.7%] were Hispanic or Latino; 75 persons [30.2%] were Black). The incidence of MIS-C per 1 000 000 person-months was 5.1 (95% CI, 4.5-5.8) persons. Compared with White persons, incidence per 1 000 000 person-months was higher among Black persons (adjusted incidence rate ratio [aIRR], 9.26 [95% CI, 6.15-13.93]), Hispanic or Latino persons (aIRR, 8.92 [95% CI, 6.00-13.26]), and Asian or Pacific Islander (aIRR, 2.94 [95% CI, 1.49-5.82]) persons. MIS-C incidence per 1 000 000 SARS-CoV-2 infections was 316 (95% CI, 278-357) persons and was higher among Black (aIRR, 5.62 [95% CI, 3.68-8.60]), Hispanic or Latino (aIRR, 4.26 [95% CI, 2.85-6.38]), and Asian or Pacific Islander persons (aIRR, 2.88 [95% CI, 1.42-5.83]) compared with White persons. For both analyses, incidence was highest among children aged 5 years or younger (4.9 [95% CI, 3.7-6.6] children per 1 000 000 person-months) and children aged 6 to 10 years (6.3 [95% CI, 4.8-8.3] children per 1 000 000 person-months). Conclusions and Relevance: In this cohort study, MIS-C was a rare complication associated with SARS-CoV-2 infection. Estimates for population-based incidence and incidence among persons with infection were higher among Black, Hispanic or Latino, and Asian or Pacific Islander persons. Further study is needed to understand variability by race/ethnicity and age group.

Phylogenetic analysis of SARS-CoV-2 in Boston highlights the impact of superspreading events.

Analysis of 772 complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from early in the Boston-area epidemic revealed numerous introductions of the virus, a small number of which led to most cases. The data revealed two superspreading events. One, in a skilled nursing facility, led to rapid transmission and significant mortality in this vulnerable population but little broader spread, whereas other introductions into the facility had little effect. The second, at an international business conference, produced sustained community transmission and was exported, resulting in extensive regional, national, and international spread. The two events also differed substantially in the genetic variation they generated, suggesting varying transmission dynamics in superspreading events. Our results show how genomic epidemiology can help to understand the link between individual clusters and wider community spread.

Phylogenetic analysis of SARS-CoV-2 in the Boston area highlights the role of recurrent importation and superspreading events.

SARS-CoV-2 has caused a severe, ongoing outbreak of COVID-19 in Massachusetts with 111,070 confirmed cases and 8,433 deaths as of August 1, 2020. To investigate the introduction, spread, and epidemiology of COVID-19 in the Boston area, we sequenced and analyzed 772 complete SARS-CoV-2 genomes from the region, including nearly all confirmed cases within the first week of the epidemic and hundreds of cases from major outbreaks at a conference, a nursing facility, and among homeless shelter guests and staff. The data reveal over 80 introductions into the Boston area, predominantly from elsewhere in the United States and Europe. We studied two superspreading events covered by the data, events that led to very different outcomes because of the timing and populations involved. One produced rapid spread in a vulnerable population but little onward transmission, while the other was a major contributor to sustained community transmission, including outbreaks in homeless populations, and was exported to several other domestic and international sites. The same two events differed significantly in the number of new mutations seen, raising the possibility that SARS-CoV-2 superspreading might encompass disparate transmission dynamics. Our results highlight the failure of measures to prevent importation into MA early in the outbreak, underscore the role of superspreading in amplifying an outbreak in a major urban area, and lay a foundation for contact tracing informed by genetic data.