This article summarizes what is currently known about the 2019 novel coronavirus and offers interim guidance.

People experiencing homelessness (PEH) are at higher risk for chronic health conditions, but clinical characteristics and outcomes for PEH hospitalized with COVID-19 are not known. We analyzed population-based surveillance data of COVID-19-associated hospitalizations during March 1-May 31, 2020. Two percent of the people hospitalized with COVID-19 for whom a housing status was recorded were homeless. Of 199 cases in the analytic sample, most were of racial/ethnic minority groups, and had underlying health conditions. Clinical outcomes such as ICU admission, respiratory support including mechanical ventilation, and deaths were documented. Hispanic and Non-Hispanic Black persons accounted for most mechanical ventilation and deaths. Severe illness was common among persons experiencing homelessness who were hospitalized with COVID-19.

SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is transmitted predominantly by respiratory droplets generated when infected persons cough, sneeze, spit, sing, talk, or breathe. CDC recommends community use of face masks to prevent transmission of SARS-CoV-2 (1). As of October 22, 2020, statewide mask mandates were in effect in 33 states and the District of Columbia (2). This study examined whether implementation of statewide mask mandates was associated with COVID-19-associated hospitalization growth rates among different age groups in 10 sites participating in the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) in states that issued statewide mask mandates during March 1-October 17, 2020. Regression analysis demonstrated that weekly hospitalization growth rates declined by 2.9 percentage points (95% confidence interval [CI] = 0.3-5.5) among adults aged 40-64 years during the first 2 weeks after implementing statewide mask mandates. After mask mandates had been implemented for ≥3 weeks, hospitalization growth rates declined by 5.5 percentage points among persons aged 18-39 years (95% CI = 0.6-10.4) and those aged 40-64 years (95% CI = 0.8-10.2). Statewide mask mandates might be associated with reductions in SARS-CoV-2 transmission and might contribute to reductions in COVID-19 hospitalization growth rates, compared with growth rates during <4 weeks before implementation of the mandate and the implementation week. Mask-wearing is a component of a multipronged strategy to decrease exposure to and transmission of SARS-CoV-2 and reduce strain on the health care system, with likely direct effects on COVID-19 morbidity and associated mortality.

To better understand the antibody landscape changes following influenza virus natural infection and vaccination, we developed a high-throughput multiplex influenza antibody detection assay (MIADA) containing 42 recombinant hemagglutinins (rHAs) (ectodomain and/or globular head domain) from pre-2009 A(H1N1), A(H1N1)pdm09, A(H2N2), A(H3N2), A(H5N1), A(H7N7), A(H7N9), A(H7N2), A(H9N2), A(H13N9), and influenza B viruses. Panels of ferret antisera, 227 paired human sera from vaccinees (children and adults) in 5 influenza seasons (2010 to 2018), and 17 paired human sera collected from real-time reverse transcription-PCR (rRT-PCR)-confirmed influenza A(H1N1)pdm09, influenza A(H3N2), or influenza B virus-infected adults were analyzed by the MIADA. Ferret antisera demonstrated clear strain-specific antibody responses to exposed subtype HA. Adults (19 to 49 years old) had broader antibody landscapes than young children (<3 years old) and older children (9 to 17 years old) both at baseline and post-vaccination. Influenza vaccination and infection induced the strongest antibody responses specific to HA(s) of exposed strain/subtype viruses and closely related strains; they also induced cross-reactive antibodies to an unexposed influenza virus subtype(s), including novel viruses. Subsequent serum adsorption confirmed that the cross-reactive antibodies against novel subtype HAs were mainly induced by exposures to A(H1N1)/A(H3N2) influenza A viruses. In contrast, adults infected by influenza B viruses mounted antibody responses mostly specific to two influenza B virus lineage HAs. Median fluorescence intensities (MFIs) and seroconversion in MIADA had good correlations with the titers and seroconversion measured by hemagglutination inhibition and microneutralization assays. Our study demonstrated that antibody landscape analysis by the MIADA can be used for influenza vaccine evaluations and characterization of influenza virus infections.IMPORTANCE Repeated influenza vaccination and natural infections generate complex immune profiles in humans that require antibody landscape analysis to assess immunity and evaluate vaccines. However, antibody landscape analyses are difficult to perform using traditional assays. Here, we developed a high-throughput, serum-sparing, multiplex influenza antibody detection assay (MIADA) and analyzed the antibody landscapes following influenza vaccination and infection. We showed that adults had broader antibody landscapes than children. Influenza vaccination and infection not only induced the strongest antibody responses to the hemagglutinins of the viruses of exposure, but also induced cross-reactive antibodies to novel influenza viruses that can be removed by serum adsorption. There is a good correlation between the median fluorescence intensity (MFI) measured by MIADA and hemagglutination inhibition/microneutralization titers. Antibody landscape analysis by the MIADA can be used in influenza vaccine evaluations, including the development of universal influenza vaccines and the characterization of influenza virus infections.

BACKGROUND: COVID-19 has disproportionately affected older adults and certain racial and ethnic groups in the US. Data quantifying the disease burden, as well as describing clinical outcomes during hospitalization among these groups, is needed. OBJECTIVE: We aimed to describe interim COVID-19 hospitalization rates and severe clinical outcomes by age group and race and ethnicity among Veterans in a multi-site surveillance network. METHODS: We implemented a multisite COVID-19 surveillance platform in 5 Veterans Affairs Medical Centers (VAMCs: Atlanta, Bronx, Houston, Palo Alto, and Los Angeles), collectively serving >396,000 patients annually. From February 27- July 17 2020, we actively identified SARS-CoV-2 positive inpatient cases through screening of admitted patients and review of laboratory test results. We manually abstracted medical charts for demographics, underlying medical conditions, and clinical outcomes of COVID-19 hospitalized patients. We calculated hospitalization incidence and incidence rate ratios, and relative risk (RR) for invasive mechanical ventilation, intensive care unit (ICU) admission, and death after adjusting for age, race and ethnicity, and underlying medical conditions. RESULTS: We identified 621 laboratory-confirmed hospitalized COVID-19 cases. Median age was 70 years, 66% were aged ≥65 years, and 94% were male. Most COVID-19 diagnoses were among non-Hispanic Blacks (52%), followed by non-Hispanic Whites (25%) and Hispanic or Latinos (18%). Hospitalization rates were highest among Veterans aged ≥85 years, Hispanic or Latino, and non-Hispanic Black (430, 317 and 298 per 100,000, respectively); Veterans aged ≥85 years had a 14-fold increased rate of hospitalization compared with Veterans aged 18-29 years (95% CI: 5.7-34.6), while Hispanic or Latino and Black Veterans had a 4.6 and 4.2-fold increased rate of hospitalization compared with non-Hispanic White Veterans (95% CI: 3.6-5.9), respectively. Overall, 11.6% of patients required invasive mechanical ventilation, 26.6% were admitted to the intensive care unit (ICU), and 16.9% died in hospital. The adjusted RR for invasive mechanical ventilation and ICU admission did not differ by age group or race/ethnicity, but Veterans aged ≥65 had a 4.5-fold increased risk of death while hospitalized with COVID-19 compared with those aged <65 years (95% CI: 2.4-8.6). CONCLUSIONS: COVID-19 surveillance at 5 VAMCs across the US demonstrated higher hospitalization rates and severe outcomes in older Veterans, and higher hospitalization rates in Hispanic or Latino and non-Hispanic Black Veterans compared to non-Hispanic White Veterans. These data highlight the need for targeted prevention and timely treatment for Veterans, with special attention to increasing age, Hispanic or Latino and non-Hispanic Black Veterans.

BACKGROUND: Transmission of respiratory viruses between staff and residents of pediatric long-term care facilities (pLTCFs) can occur. We assessed the feasibility of using text or email messages to perform surveillance for acute respiratory infections (ARIs) among staff. METHODS: From December 7, 2016 to May 7, 2017, 50 staff participants from 2 pLTCFs received weekly text or email requests to report the presence or absence of ARI symptoms. Those who fulfilled the ARI case definition (≥2 symptoms) had respiratory specimens collected to detect viruses by reverse transcriptase polymerase chain reaction assays. Pre- and postsurveillance respiratory specimens were collected to assess subclinical viral shedding. RESULTS: The response rate to weekly electronic messages was 93%. Twenty-one ARIs reported from 20 (40%) participants fulfilled the case definition. Respiratory viruses were detected in 29% (5/17) of specimens collected at symptom onset (influenza B, respiratory syncytial virus, coronavirus [CoV] 229E, rhinovirus [RV], and dual detection of CoV OC43 and bocavirus). Four participants had positive presurveillance (4 RV), and 6 had positive postsurveillance specimens (3 RV, 2 CoV NL63, and 1 adenovirus). CONCLUSIONS: Electronic messaging to conduct ARI surveillance among pLTCF staff was feasible.

Using a coronavirus disease 2019 (COVID-19)-associated hospitalization surveillance network, we found that 42.5% of hospitalized COVID-19 cases with available data from March 1-June 30, 2020, received ≥1 COVID-19 investigational treatment. Hydroxychloroquine, azithromycin, and remdesivir were used frequently; however, hydroxychloroquine and azithromycin use declined over time, while use of remdesivir increased.

Among 513 adults aged 18-49 years without underlying medical conditions hospitalized with COVID-19 during March-August 2020, 22% were admitted to intensive care unit; 10% required mechanical ventilation; and three patients died (0.6%). These data demonstrate that healthy younger adults can develop severe COVID-19.

BACKGROUND: In the United States, laboratory confirmed coronavirus disease 2019 (COVID-19) is nationally notifiable. However, reported case counts are recognized to be less than the true number of cases because detection and reporting are incomplete and can vary by disease severity, geography, and over time. METHODS: To estimate the cumulative incidence SARS-CoV-2 infections, symptomatic illnesses, and hospitalizations, we adapted a simple probabilistic multiplier model. Laboratory-confirmed case counts that were reported nationally were adjusted for sources of under-detection based on testing practices in inpatient and outpatient settings and assay sensitivity. RESULTS: We estimated that through the end of September, 1 of every 2.5 (95% Uncertainty Interval (UI): 2.0-3.1) hospitalized infections and 1 of every 7.1 (95% UI: 5.8-9.0) non-hospitalized illnesses may have been nationally reported. Applying these multipliers to reported SARS-CoV-2 cases along with data on the prevalence of asymptomatic infection from published systematic reviews, we estimate that 2.4 million hospitalizations, 44.8 million symptomatic illnesses, and 52.9 million total infections may have occurred in the U.S. population from February 27-September 30, 2020. CONCLUSIONS: These preliminary estimates help demonstrate the societal and healthcare burdens of the COVID-19 pandemic and can help inform resource allocation and mitigation planning.

Health care personnel (HCP) can be exposed to SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), both within and outside the workplace, increasing their risk for infection. Among 6,760 adults hospitalized during March 1-May 31, 2020, for whom HCP status was determined by the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), 5.9% were HCP. Nursing-related occupations (36.3%) represented the largest proportion of HCP hospitalized with COVID-19. Median age of hospitalized HCP was 49 years, and 89.8% had at least one underlying medical condition, of which obesity was most commonly reported (72.5%). A substantial proportion of HCP with COVID-19 had indicators of severe disease: 27.5% were admitted to an intensive care unit (ICU), 15.8% required invasive mechanical ventilation, and 4.2% died during hospitalization. HCP can have severe COVID-19-associated illness, highlighting the need for continued infection prevention and control in health care settings as well as community mitigation efforts to reduce transmission.

Pregnant women might be at increased risk for severe coronavirus disease 2019 (COVID-19) (1,2). The COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) (3) collects data on hospitalized pregnant women with laboratory-confirmed SARS-CoV-2, the virus that causes COVID-19; to date, such data have been limited. During March 1-August 22, 2020, approximately one in four hospitalized women aged 15-49 years with COVID-19 was pregnant. Among 598 hospitalized pregnant women with COVID-19, 54.5% were asymptomatic at admission. Among 272 pregnant women with COVID-19 who were symptomatic at hospital admission, 16.2% were admitted to an intensive care unit (ICU), and 8.5% required invasive mechanical ventilation. During COVID-19-associated hospitalizations, 448 of 458 (97.8%) completed pregnancies resulted in a live birth and 10 (2.2%) resulted in a pregnancy loss. Testing policies based on the presence of symptoms might miss COVID-19 infections during pregnancy. Surveillance of pregnant women with COVID-19, including those with asymptomatic infections, is important to understand the short- and long-term consequences of COVID-19 for mothers and newborns. Identifying COVID-19 in women during birth hospitalizations is important to guide preventive measures to protect pregnant women, parents, newborns, other patients, and hospital personnel. Pregnant women and health care providers should be made aware of the potential risks for severe COVID-19 illness, adverse pregnancy outcomes, and ways to prevent infection.

BACKGROUND: Data on risk factors for COVID-19-associated hospitalization are needed to guide prevention efforts and clinical care. We sought to identify factors independently associated with COVID-19-associated hospitalizations. METHODS: U.S. community-dwelling adults (≥18 years) hospitalized with laboratory-confirmed COVID-19 during March 1-June 23, 2020 were identified from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), a multi-state surveillance system. To calculate hospitalization rates by age, sex, and race/ethnicity strata, COVID-NET data served as the numerator and Behavioral Risk Factor Surveillance System estimates served as the population denominator for characteristics of interest. Underlying medical conditions examined included hypertension, coronary artery disease, history of stroke, diabetes, obesity [BMI ≥30 kg/m 2], severe obesity [BMI≥40 kg/m 2], chronic kidney disease, asthma, and chronic obstructive pulmonary disease. Generalized Poisson regression models were used to calculate adjusted rate ratios (aRR) for hospitalization. RESULTS: Among 5,416 adults, hospitalization rates were higher among those with ≥3 underlying conditions (versus without)(aRR: 5.0; 95%CI: 3.9, 6.3), severe obesity (aRR:4.4; 95%CI: 3.4, 5.7), chronic kidney disease (aRR:4.0; 95%CI: 3.0, 5.2), diabetes (aRR:3.2; 95%CI: 2.5, 4.1), obesity (aRR:2.9; 95%CI: 2.3, 3.5), hypertension (aRR:2.8; 95%CI: 2.3, 3.4), and asthma (aRR:1.4; 95%CI: 1.1, 1.7), after adjusting for age, sex, and race/ethnicity. Adjusting for the presence of an individual underlying medical condition, higher hospitalization rates were observed for adults aged ≥65, 45-64 (versus 18-44 years), males (versus females), and non-Hispanic black and other race/ethnicities (versus non-Hispanic whites). CONCLUSION: Our findings elucidate groups with higher hospitalization risk that may benefit from targeted preventive and therapeutic interventions.

Most reported cases of coronavirus disease 2019 (COVID-19) in children aged <18 years appear to be asymptomatic or mild (1). Less is known about severe COVID-19 illness requiring hospitalization in children. During March 1-July 25, 2020, 576 pediatric COVID-19 cases were reported to the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), a population-based surveillance system that collects data on laboratory-confirmed COVID-19-associated hospitalizations in 14 states (2,3). Based on these data, the cumulative COVID-19-associated hospitalization rate among children aged <18 years during March 1-July 25, 2020, was 8.0 per 100,000 population, with the highest rate among children aged <2 years (24.8). During March 21-July 25, weekly hospitalization rates steadily increased among children (from 0.1 to 0.4 per 100,000, with a weekly high of 0.7 per 100,000). Overall, Hispanic or Latino (Hispanic) and non-Hispanic black (black) children had higher cumulative rates of COVID-19-associated hospitalizations (16.4 and 10.5 per 100,000, respectively) than did non-Hispanic white (white) children (2.1). Among 208 (36.1%) hospitalized children with complete medical chart reviews, 69 (33.2%) were admitted to an intensive care unit (ICU); 12 of 207 (5.8%) required invasive mechanical ventilation, and one patient died during hospitalization. Although the cumulative rate of pediatric COVID-19-associated hospitalization remains low (8.0 per 100,000 population) compared with that among adults (164.5),* weekly rates increased during the surveillance period, and one in three hospitalized children were admitted to the ICU, similar to the proportion among adults. Continued tracking of SARS-CoV-2 infections among children is important to characterize morbidity and mortality. Reinforcement of prevention efforts is essential in congregate settings that serve children, including childcare centers and schools.

BACKGROUND: Currently, the United States has the largest number of reported coronavirus disease 2019 (COVID-19) cases and deaths globally. Using a geographically diverse surveillance network, we describe risk factors for severe outcomes among adults hospitalized with COVID-19. METHODS: We analyzed data from 2,491 adults hospitalized with laboratory-confirmed COVID-19 during March 1-May 2, 2020 identified through the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network comprising 154 acute care hospitals in 74 counties in 13 states. We used multivariable analyses to assess associations between age, sex, race and ethnicity, and underlying conditions with intensive care unit (ICU) admission and in-hospital mortality. RESULTS: Ninety-two percent of patients had >/=1 underlying condition; 32% required ICU admission; 19% invasive mechanical ventilation; and 17% died. Independent factors associated with ICU admission included ages 50-64, 65-74, 75-84 and >/=85 years versus 18-39 years (adjusted risk ratio (aRR) 1.53, 1.65, 1.84 and 1.43, respectively); male sex (aRR 1.34); obesity (aRR 1.31); immunosuppression (aRR 1.29); and diabetes (aRR 1.13). Independent factors associated with in-hospital mortality included ages 50-64, 65-74, 75-84 and >/=85 years versus 18-39 years (aRR 3.11, 5.77, 7.67 and 10.98, respectively); male sex (aRR 1.30); immunosuppression (aRR 1.39); renal disease (aRR 1.33); chronic lung disease (aRR 1.31); cardiovascular disease (aRR 1.28); neurologic disorders (aRR 1.25); and diabetes (aRR 1.19). CONCLUSION: In-hospital mortality increased markedly with increasing age. Aggressive implementation of prevention strategies, including social distancing and rigorous hand hygiene, may benefit the population as a whole, as well as those at highest risk for COVID-19-related complications.

Since SARS-CoV-2, the novel coronavirus that causes coronavirus disease 2019 (COVID-19), was first detected in December 2019 (1), approximately 1.3 million cases have been reported worldwide (2), including approximately 330,000 in the United States (3). To conduct population-based surveillance for laboratory-confirmed COVID-19-associated hospitalizations in the United States, the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) was created using the existing infrastructure of the Influenza Hospitalization Surveillance Network (FluSurv-NET) (4) and the Respiratory Syncytial Virus Hospitalization Surveillance Network (RSV-NET). This report presents age-stratified COVID-19-associated hospitalization rates for patients admitted during March 1-28, 2020, and clinical data on patients admitted during March 1-30, 2020, the first month of U.S. surveillance. Among 1,482 patients hospitalized with COVID-19, 74.5% were aged >/=50 years, and 54.4% were male. The hospitalization rate among patients identified through COVID-NET during this 4-week period was 4.6 per 100,000 population. Rates were highest (13.8) among adults aged >/=65 years. Among 178 (12%) adult patients with data on underlying conditions as of March 30, 2020, 89.3% had one or more underlying conditions; the most common were hypertension (49.7%), obesity (48.3%), chronic lung disease (34.6%), diabetes mellitus (28.3%), and cardiovascular disease (27.8%). These findings suggest that older adults have elevated rates of COVID-19-associated hospitalization and the majority of persons hospitalized with COVID-19 have underlying medical conditions. These findings underscore the importance of preventive measures (e.g., social distancing, respiratory hygiene, and wearing face coverings in public settings where social distancing measures are difficult to maintain)(dagger) to protect older adults and persons with underlying medical conditions, as well as the general public. In addition, older adults and persons with serious underlying medical conditions should avoid contact with persons who are ill and immediately contact their health care provider(s) if they have symptoms consistent with COVID-19 (https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html) (5). Ongoing monitoring of hospitalization rates, clinical characteristics, and outcomes of hospitalized patients will be important to better understand the evolving epidemiology of COVID-19 in the United States and the clinical spectrum of disease, and to help guide planning and prioritization of health care system resources.

An outbreak of novel coronavirus (2019-nCoV) that began in Wuhan, China, has spread rapidly, with cases now confirmed in multiple countries. We report the first case of 2019-nCoV infection confirmed in the United States and describe the identification, diagnosis, clinical course, and management of the case, including the patient's initial mild symptoms at presentation with progression to pneumonia on day 9 of illness. This case highlights the importance of close coordination between clinicians and public health authorities at the local, state, and federal levels, as well as the need for rapid dissemination of clinical information related to the care of patients with this emerging infection.

Respiratory syncytial virus (RSV) often causes respiratory illness in adults. Over 40 RSV vaccine and monoclonal antibody products are currently in preclinical development or clinical trials. Because RSV diagnostic practices may impact disease burden estimates, we investigated infectious disease physicians' RSV diagnostic practices among their adult patients.

Streptococcus pneumoniae inflicts a huge disease burden as the leading cause of community-acquired pneumonia and meningitis. Soon after mainstream antibiotic usage, multiresistant pneumococcal clones emerged and disseminated worldwide. Resistant clones are generated through adaptation to antibiotic pressures imposed while naturally residing within the human upper respiratory tract. Here, a huge array of related commensal streptococcal strains transfers core genomic and accessory resistance determinants to the highly transformable pneumococcus. beta-Lactam resistance is the hallmark of pneumococcal adaptability, requiring multiple independent recombination events that are traceable to nonpneumococcal origins and stably perpetuated in multiresistant clonal complexes. Pneumococcal strains with elevated MICs of beta-lactams are most often resistant to additional antibiotics. Basic underlying mechanisms of most pneumococcal resistances have been identified, although new insights that increase our understanding are continually provided. Although all pneumococcal infections can be successfully treated with antibiotics, the available choices are limited for some strains. Invasive pneumococcal disease data compiled during 1998 to 2013 through the population-based Active Bacterial Core surveillance program (U.S. population base of 30,600,000) demonstrate that targeting prevalent capsular serotypes with conjugate vaccines (7-valent and 13-valent vaccines implemented in 2000 and 2010, respectively) is extremely effective in reducing resistant infections. Nonetheless, resistant non-vaccine-serotype clones continue to emerge and expand.

BACKGROUND: From January-July 2014, >46,000 unaccompanied children (UC) from Central America crossed the U.S.-Mexico border. In June-July, UC aged 9-17 years in four shelters and a processing center in four U.S. states were hospitalized with acute respiratory illness. We conducted a multistate investigation to interrupt disease transmission. METHODS: Medical charts were abstracted for hospitalized UC. Non-hospitalized UC with influenza-like illness were interviewed, and nasopharyngeal and oropharyngeal swabs for PCR-based detection of respiratory pathogens were collected. Nasopharyngeal swabs were used to assess pneumococcal colonization in symptomatic and asymptomatic UC. Pneumococcal blood isolates from hospitalized UC and nasopharyngeal isolates were characterized by serotyping (Quellung) and whole-genome sequencing. RESULTS: Among the 15 hospitalized UC, 4 (44%) of 9 tested positive for influenza viruses, and 6 (43%) of 14 with blood cultures grew pneumococcus, all serotype 5. Among 48 non-hospitalized children with influenza-like illness, >1 respiratory pathogen was identified in 46 (96%). Among 774 non-hospitalized UC, 185 (24%) yielded pneumococcus, and 70 (38%) were serotype 5. UC who transferred through the processing center were more likely than others to be colonized with serotype 5 (OR 3.8; 95% CI, 2.1-6.9). Analysis of the core pneumococcal genomes detected two related, yet independent, clusters. No pneumococcus cases were reported after pneumococcal and influenza immunization campaigns were implemented. CONCLUSIONS: This outbreak of respiratory disease was due to multiple pathogens, including Streptococcus pneumoniae serotype 5 and influenza viruses. Pneumococcal and influenza vaccinations prevented further transmission. Future efforts to prevent similar outbreaks will benefit from use of both vaccines.

The effect of second generation pneumococcal conjugate vaccines on invasive pneumococcal disease (IPD) strain distributions have not yet been well described. We analyzed IPD isolates recovered from children <5 years of age through Active Bacterial Core surveillance before (2008-2009; n=828) and after (2011-2013; n=600) 13-valent vaccine (PCV13) implementation. We employed conventional testing, PCR/electrospray ionization mass spectrometry, and whole genome sequence (WGS) analysis to identify serotypes, resistance features, genotypes, and pilus types. PCV13, licensed in February of 2010, effectively targeted all major 19A and 7F genotypes and decreased antimicrobial resistance primarily due to removal of the 19A/ST320 complex. The strain complex contributing most to remaining beta-lactam resistance during 2011-2013 was 35B/ST558. Significant emergence of non-vaccine clonal complexes was not evident. Due to the removal of vaccine serotype strains, positivity for one or both pilus types (PI-1 and PI-2) decreased in the post PCV13 years 2011-2013 relative to 2008-2009 (decreases of 32-55% for PI-1, > 95% for PI-2 and combined PI-1 + PI-2). beta-lactam susceptibility phenotypes correlated consistently with transpeptidase region sequence combinations of the three major penicillin binding proteins (PBPs) determined through WGS. Other major resistance features were predictable by DNA signatures from WGS. Multilocus sequence data combined with PBP combinations identified progeny, serotype donors, and recipient strains in serotype switch events. PCV13 decreased all PCV13 serotype clones and concurrently decreased strain subsets with resistance and/or adherence features conducive for successful carriage. Our results serve as a reference describing key features of current pediatric IPD strains in the United States after PCV13 implementation.