BACKGROUND: Oral pre-exposure prophylaxis (PrEP) with emtricitabine/tenofovir disoproxil fumarate (F/TDF) has high efficacy against HIV-1 acquisition. Seventy-two prospective studies of daily oral F/TDF PrEP were conducted to evaluate HIV-1 incidence, drug resistance, adherence, and bone and renal safety in diverse settings. METHODS: HIV-1 incidence was calculated from incident HIV-1 diagnoses after PrEP initiation and within 60 days of discontinuation. Tenofovir concentrations in dried blood spots (DBS), drug resistance, and bone/renal safety indicators were evaluated in a subset of studies. RESULTS: Among 17 274 participants, there were 101 cases with new HIV-1 diagnosis (.77 per 100 person-years; 95% confidence interval [CI]: .63-.94). In 78 cases with resistance data, 18 (23%) had M184I or V, 1 (1.3%) had K65R, and 3 (3.8%) had both mutations. In 54 cases with tenofovir concentration data from DBS, 45 (83.3%), 2 (3.7%), 6 (11.1%), and 1 (1.9%) had average adherence of <2, 2-3, 4-6, and ≥7 doses/wk, respectively, and the corresponding incidence was 3.9 (95% CI: 2.9-5.3), .24 (.060-.95), .27 (.12-.60), and .054 (.008-.38) per 100 person-years. Adherence was low in younger participants, Hispanic/Latinx and Black participants, cisgender women, and transgender women. Bone and renal adverse event incidence rates were 0.69 and 11.8 per 100 person-years, respectively, consistent with previous reports. CONCLUSIONS: Leveraging the largest pooled analysis of global PrEP studies to date, we demonstrate that F/TDF is safe and highly effective, even with less than daily dosing, in diverse clinical settings, geographies, populations, and routes of HIV-1 exposure.

BACKGROUND: On 20 September 2022, the Ugandan Ministry of Health declared an outbreak of Ebola disease caused by Sudan ebolavirus. METHODS: From 6 October 2022 to 10 January 2023, Centers for Disease Control and Prevention (CDC) staff conducted public health assessments at five US ports of entry for travellers identified as having been in Uganda in the past 21 days. CDC also recommended that state, local and territorial health departments ('health departments') conduct post-arrival monitoring of these travellers. CDC provided traveller contact information, daily to 58 health departments, and collected health department data regarding monitoring outcomes. RESULTS: Among 11 583 travellers screened, 132 (1%) required additional assessment due to potential exposures or symptoms of concern. Fifty-three (91%) health departments reported receiving traveller data from CDC for 10 114 (87%) travellers, of whom 8499 (84%) were contacted for monitoring, 1547 (15%) could not be contacted and 68 (1%) had no reported outcomes. No travellers with high-risk exposures or Ebola disease were identified. CONCLUSION: Entry risk assessment and post-arrival monitoring of travellers are resource-intensive activities that had low demonstrated yield during this and previous outbreaks. The efficiency of future responses could be improved by incorporating an assessment of risk of importation of disease, accounting for individual travellers' potential for exposure, and expanded use of methods that reduce burden to federal agencies, health departments, and travellers.

Respiratory syncytial virus (RSV) is a leading cause of hospitalization among young children. Historically, American Indian and Alaska Native (AI/AN) children have experienced high rates of RSV-associated hospitalization. In August 2023, a preventive monoclonal antibody (nirsevimab) was recommended for all infants aged <8 months (born during or entering their first RSV season) and for children aged 8-19 months (entering their second RSV season) who have increased risk for severe RSV illness, including all AI/AN children. This evaluation in Alaska's Yukon-Kuskokwim Delta region estimated nirsevimab effectiveness among AI/AN children in their first or second RSV seasons during 2023-2024. Among 472 children with medically attended acute respiratory illness (ARI), 48% overall had received nirsevimab ≥7 days earlier (median = 91 days before the ARI-related visit). For children in their first RSV season (292), nirsevimab effectiveness was 76% (95% CI = 42%-90%) against medically attended RSV illness and 89% (95% CI = 32%-98%) against RSV hospitalization. For children in their second RSV season (180), effectiveness against medically attended RSV illness was 88% (95% CI = 48%-97%). Nirsevimab is effective for preventing severe RSV illness among infants entering their first RSV season and children entering their second season with increased risk for severe RSV, including all AI/AN children.

During responses to outbreaks, the collection and analysis of data on employed case patients' industry and occupation are necessary to better understand the relationship between work and health outcomes. The occurrence of mpox by occupation and industry has not previously been assessed in the context of the 2022 outbreak. We analyzed employment data from 2548 mpox cases reported to the U.S. Centers for Disease Control and Prevention from surveillance systems in seven U.S. jurisdictions and population-based reference data on employment patterns from the U.S. Bureau of Labor Statistics to describe the differential proportionate distribution of cases across occupation and industry groups using the proportionate morbidity ratio. In gender-specific analyses, we found that men employed in certain occupations and industries had a higher relative risk of mpox than others. While occupational transmission cannot be ruled out, it is more likely that individuals with personal and behavioral risk factors for mpox were more likely to work in these occupations and industries. This analysis provides an example of collecting and analyzing occupation and industry data in case reports to understand possible differences in risk by occupation and industry in infectious disease outbreak investigation and help inform resource allocation, messaging, and response.

A global outbreak of clade II mpox associated with sexual contact, disproportionately affecting gay, bisexual, and other men who have sex with men (MSM), has been ongoing since May 2022. Information on types of contact most associated with transmission is limited. This report used data from a multijurisdictional vaccine effectiveness case-control study of sexually active persons aged 18-49 years who identified as MSM or transgender, collected during August 2022-July 2023. Odds of mpox associated with selected types of intimate and nonintimate close contact with a person with mpox were estimated. Among 457 case-patients and 1,030 control patients who met minimum data requirements, 150 (32.8%) case-patients and 57 (5.5%) control patients reported close contact with a person with mpox and were included in this analysis. Adjusted odds of mpox were 5.4 times as high among those who reported having condomless receptive anal sex with a person with mpox, compared with participants who reported close contact with a person with mpox and no condomless receptive anal sex with that person (OR = 5.4; p = 0.031). Although the mpox vaccine is highly effective, vaccination coverage remains low; a multifaceted approach to prevention remains important and should include vaccination promotion, safer sex practices, and increasing awareness that mpox continues to circulate.

Isolation of symptomatic infectious persons can reduce influenza transmission. However, virus shedding that occurs without symptoms will be unaffected by such measures. Identifying effective isolation strategies for influenza requires understanding the interplay between individual virus shedding and symptom presentation. From 2017 to 2020, we conducted a case-ascertained household transmission study using influenza real-time RT-qPCR testing of nasal swabs and daily symptom diary reporting for up to 7 days after enrolment (≤14 days after index onset). We assumed real-time RT-qPCR cycle threshold (Ct) values were indicators of quantitative virus shedding and used symptom diaries to create a score that tracked influenza-like illness (ILI) symptoms (fever, cough, or sore throat). We fit phenomenological nonlinear mixed-effects models stratified by age and vaccination status and estimated two quantities influencing isolation effectiveness: shedding before symptom onset and shedding that might occur once isolation ends. We considered different isolation end points (including 24 h after fever resolution or 5 days after symptom onset) and assumptions about the infectiousness of Ct shedding trajectories. Of the 116 household contacts with ≥2 positive tests for longitudinal analyses, 105 (91%) experienced ≥1 ILI symptom. On average, children <5 years experienced greater peak shedding, longer durations of shedding, and elevated ILI symptom scores compared with other age groups. Most individuals (63/105) shed <10% of their total shed virus before symptom onset, and shedding after isolation varied substantially across individuals, isolation end points, and infectiousness assumptions. Our results can inform strategies to reduce transmission from symptomatic individuals infected with influenza.

The World Health Organization, in response to the growing burden of fungal disease, established a process to develop a fungal pathogen priority list. This systematic review aimed to evaluate the epidemiology and impact of infections caused by Talaromyces marneffei, Coccidioides species, and Paracoccidioides species. PubMed and Web of Sciences databases were searched to identify studies published between 1 January 2011 and 23 February 2021 reporting on mortality, complications and sequelae, antifungal susceptibility, preventability, annual incidence, and trends. Overall, 25, 17, and 6 articles were included for T. marneffei, Coccidioides spp. and Paracoccidioides spp., respectively. Mortality rates were high in those with invasive talaromycosis and paracoccidioidomycosis (up to 21% and 22.7%, respectively). Hospitalization was frequent in those with coccidioidomycosis (up to 84%), and while the duration was short (mean/median 3-7 days), readmission was common (38%). Reduced susceptibility to fluconazole and echinocandins was observed for T. marneffei and Coccidioides spp., whereas >88% of T. marneffei isolates had minimum inhibitory concentration values ≤0.015 μg/ml for itraconazole, posaconazole, and voriconazole. Risk factors for mortality in those with talaromycosis included low CD4 counts (odds ratio 2.90 when CD4 count <200 cells/μl compared with 24.26 when CD4 count <50 cells/μl). Outbreaks of coccidioidomycosis and paracoccidioidomycosis were associated with construction work (relative risk 4.4-210.6 and 5.7-times increase, respectively). In the United States of America, cases of coccidioidomycosis increased between 2014 and 2017 (from 8232 to 14 364/year). National and global surveillance as well as more detailed studies to better define sequelae, risk factors, outcomes, global distribution, and trends are required.

Recognizing the growing global burden of fungal infections, the World Health Organization established a process to develop a priority list of fungal pathogens (FPPL). In this systematic review, we aimed to evaluate the epidemiology and impact of infections caused by Fusarium spp., Scedosporium spp., and Lomentospora prolificans to inform the first FPPL. PubMed and Web of Sciences databases were searched to identify studies published between January 1, 2011 and February 23, 2021, reporting on mortality, complications and sequelae, antifungal susceptibility, preventability, annual incidence, and trends. Overall, 20, 11, and 9 articles were included for Fusarium spp., Scedosporium spp., and L. prolificans, respectively. Mortality rates were high in those with invasive fusariosis, scedosporiosis, and lomentosporiosis (42.9%-66.7%, 42.4%-46.9%, and 50.0%-71.4%, respectively). Antifungal susceptibility data, based on small isolate numbers, showed high minimum inhibitory concentrations (MIC)/minimum effective concentrations for most currently available antifungal agents. The median/mode MIC for itraconazole and isavuconazole were ≥16 mg/l for all three pathogens. Based on limited data, these fungi are emerging. Invasive fusariosis increased from 0.08 cases/100 000 admissions to 0.22 cases/100 000 admissions over the time periods of 2000-2009 and 2010-2015, respectively, and in lung transplant recipients, Scedosporium spp. and L. prolificans were only detected from 2014 onwards. Global surveillance to better delineate antifungal susceptibility, risk factors, sequelae, and outcomes is required.

Accurate and timely mortality surveillance is crucial for elucidating risk factors, particularly for emerging diseases. We compared use of COVID-19 keywords on death certificates alone to identify COVID-19 deaths in Minnesota, USA, during 2020-2022, with use of a standardized mortality definition incorporating additional clinical data. For analyses, we used likelihood ratio χ(2) and median 1-way tests. Death certificates alone identified 96% of COVID-19 deaths confirmed by the standardized definition and an additional 3% of deaths that had been classified as non-COVID-19 deaths by the standardized definition. Agreement between methods was >90% for most groups except children, although agreement among adults varied by demographics and location at death. Overall median time from death to filing of death certificate was 3 days; decedent characteristics and whether autopsy was performed varied. Death certificates are an efficient and timely source of COVID-19 mortality data when paired with SARS-CoV-2 testing data.

BACKGROUND: Novel influenza viruses pose a potential pandemic risk, and rapid detection of infections in humans is critical to characterizing the virus and facilitating the implementation of public health response measures. METHODS: We use a probabilistic framework to estimate the likelihood that novel influenza virus cases would be detected through testing in different community and healthcare settings (urgent care, emergency department, hospital, and intensive care unit [ICU]) while at low frequencies in the United States. Parameters were informed by data on seasonal influenza virus activity and existing testing practices. RESULTS: In a baseline scenario reflecting the presence of 100 novel virus infections with similar severity to seasonal influenza viruses, the median probability of detecting at least one infection per month was highest in urgent care settings (72%) and when community testing was conducted at random among the general population (77%). However, urgent care testing was over 15 times more efficient (estimated as the number of cases detected per 100,000 tests) due to the larger number of tests required for community testing. In scenarios that assumed increased clinical severity of novel virus infection, median detection probabilities increased across all healthcare settings, particularly in hospitals and ICUs (up to 100%) where testing also became more efficient. CONCLUSIONS: Our results suggest that novel influenza virus circulation is likely to be detected through existing healthcare surveillance, with the most efficient testing setting impacted by the disease severity profile. These analyses can help inform future testing strategies to maximize the likelihood of novel influenza detection.

Streptococcus dysgalactiae subsp. equisimilis (SDSE) is an emerging cause of human infection with invasive disease incidence and clinical manifestations comparable to the closely related species, Streptococcus pyogenes. Through systematic genomic analyses of 501 disseminated SDSE strains, we demonstrate extensive overlap between the genomes of SDSE and S. pyogenes. More than 75% of core genes are shared between the two species with one third demonstrating evidence of cross-species recombination. Twenty-five percent of mobile genetic element (MGE) clusters and 16 of 55 SDSE MGE insertion regions were shared across species. Assessing potential cross-protection from leading S. pyogenes vaccine candidates on SDSE, 12/34 preclinical vaccine antigen genes were shown to be present in >99% of isolates of both species. Relevant to possible vaccine evasion, six vaccine candidate genes demonstrated evidence of inter-species recombination. These findings demonstrate previously unappreciated levels of genomic overlap between these closely related pathogens with implications for streptococcal pathobiology, disease surveillance and prevention.

Transgender women experience discrimination in many settings, including in employment. Because employment and health insurance are intertwined in the United States, employment discrimination might be related to lower health insurance coverage and health care use, including gender-affirming care. This analysis used data from transgender women (N = 1,608) in seven urban areas in the United States collected during 2019-2020 to present the prevalence of six discrimination types (employment, housing, bathroom, businesses, health care, and abuse) and to measure the association between employment discrimination (defined as trouble getting a job or fired due to being transgender) and sociodemographic characteristics, health care access, and health care use. Log-linked Poisson regression models were conducted to estimate adjusted prevalence ratios and 95% CIs. Seven in 10 transgender women experienced at least one type of discrimination during the past 12 months. During the same period, 9.9% of transgender women were fired and 32.4% had trouble getting a job because of being transgender. Employment discrimination was associated with younger age and lower socioeconomic status. Having trouble getting a job was associated with health care access and health care use factors, including having no health insurance or having Medicaid only, having an unmet medical need because of cost, never having transgender-specific care, and having an unmet need for gender-affirming procedures. These findings suggest that employment discrimination contributes to transgender women's economic marginalization and their ability to obtain adequate health insurance coverage and achieve their transition goals. These findings might help guide efforts that protect transgender women's right to pursue their work, health, and life goals without discrimination.

Transgender women, especially transgender women of color, are disproportionately affected by HIV. However, no surveillance system collects data on HIV risk factors among this population. To address this gap, CDC developed a surveillance system entitled National HIV Behavioral Surveillance Among Transgender Women (NHBS-Trans) to assess behavioral and contextual data through systematic biobehavioral surveillance to monitor behavioral risk factors, prevention usage, and HIV prevalence among transgender women. NHBS-Trans used respondent-driven sampling in seven urban areas in the United States. Trained interviewers used a standardized, anonymous questionnaire to collect information on HIV-related behavioral risk factors, HIV testing, and use of prevention services. Each of the seven participating project areas recruited approximately 200 eligible transgender women and offered anonymous HIV testing. Overall, in the seven project areas, 1,757 participants completed the eligibility screener for NHBS-Trans during 2019-2020; of these, 6.6% were seeds (i.e., a limited number of initial participants who were chosen by referrals from persons and community-based organizations who knew or were part of the local population of transgender women). A total of 1,637 (93.2%) participants were eligible, consented, and completed the interview. Of these, 1,624 (99.2%) agreed to HIV testing. Of the total 1,637 participants, 29 participants did not report identity of woman or transgender woman, resulting in a final sample of 1,608 transgender women. NHBS-Trans project area staff members (n = 14) reported that the survey was timely and addressed a critical need for HIV surveillance in a population that is often overlooked. The MMWR supplement includes this overview report on NHBS-Trans, which describes the methods (history, participant eligibility criteria, questionnaire, data collection, and HIV testing) as well as evaluation of project implementation and the performance of the questionnaire content, specifically the acceptability for transgender women. The other NHBS-Trans reports in the supplement include information on pre-exposure prophylaxis use, psychosocial syndemic conditions and condomless anal intercourse, nonprescription hormone use, homelessness, discrimination and the association between employment discrimination and health care access and use, and social support and the association between certain types of violence and harassment (gender-based verbal and physical abuse or harassment, physical intimate partner abuse or harassment, and sexual violence) and suicidal ideation. NHBS-Trans provides important data related to the goals of the Ending the HIV Epidemic in the U.S. initiative. Findings from NHBS-Trans can help guide community leaders, clinicians, and public health officials in improving access to and use of HIV prevention and treatment services by transgender women.

CDC recommends pre-exposure prophylaxis (PrEP) for transgender women who have sex with men and who report sexual behaviors that place them at substantial ongoing risk for HIV exposure, including those who engage in nonsterile syringe sharing. Providing transgender women with access to PrEP is a critical strategy for reducing HIV acquisition and ending the HIV epidemic. Survey results from the National HIV Behavioral Surveillance Among Transgender Women were used to assess characteristics associated with past-year discussions of PrEP with a health care provider and PrEP use. Bivariate analyses were conducted to assess the association between covariates (sociodemographic, HIV-associated characteristics, and gender-affirming care) and each outcome, accounting for sampling design. All covariates that were statistically significant at p<0.05 in the bivariate analyses were included in multivariate models, and manual backward elimination was used to obtain final models that retained statistically significant covariates. Among 902 transgender women from seven urban areas in the United States without HIV infection in the analyses, 57% had recently discussed PrEP with a health care provider, and 32% recently had used PrEP. In the final multivariate model, the following subgroups of transgender women were more likely to report recent PrEP use: those who identified as Black or African American or Hispanic or Latina, had two or more sex partners in the past 12 months, had condomless sex in the past 12 months, reported their last sex partner was infected with HIV, had condomless sex with their last sex partner whose HIV status was positive or unknown, ever had transgender-specific health care, and currently had transgender-specific health insurance coverage. Participants who were less likely to have recently used PrEP were those who wanted to but were not currently taking hormones and those aged <40 years. Providing increased access to gender-affirming care and training health care providers who serve transgender women to incorporate PrEP into existing services might increase PrEP use among transgender women.

BACKGROUND: Diarrheal diseases continue to contribute significantly to morbidity and mortality in infants and young children in developing countries. There is an urgent need to better understand the contributions of novel, potentially uncultured, diarrheal pathogens to severe diarrheal disease, as well as distortions in normal gut microbiota composition that might facilitate severe disease. RESULTS: We use high throughput 16S rRNA gene sequencing to compare fecal microbiota composition in children under five years of age who have been diagnosed with moderate to severe diarrhea (MSD) with the microbiota from diarrhea-free controls. Our study includes 992 children from four low-income countries in West and East Africa, and Southeast Asia. Known pathogens, as well as bacteria currently not considered as important diarrhea-causing pathogens, are positively associated with MSD, and these include Escherichia/Shigella, and Granulicatella species, and Streptococcus mitis/pneumoniae groups. In both cases and controls, there tend to be distinct negative correlations between facultative anaerobic lineages and obligate anaerobic lineages. Overall genus-level microbiota composition exhibit a shift in controls from low to high levels of Prevotella and in MSD cases from high to low levels of Escherichia/Shigella in younger versus older children; however, there was significant variation among many genera by both site and age. CONCLUSIONS: Our findings expand the current understanding of microbiota-associated diarrhea pathogenicity in young children from developing countries. Our findings are necessarily based on correlative analyses and must be further validated through epidemiological and molecular techniques.

During July 7-11, 2023, CDC received reports of two patients in different states with a tuberculosis (TB) diagnosis following spinal surgical procedures that used bone allografts containing live cells from the same deceased donor. An outbreak associated with a similar product manufactured by the same tissue establishment (i.e., manufacturer) occurred in 2021. Because of concern that these cases represented a second outbreak, CDC and the Food and Drug Administration worked with the tissue establishment to determine that this product was obtained from a donor different from the one implicated in the 2021 outbreak and learned that the bone allograft product was distributed to 13 health care facilities in seven states. Notifications to all seven states occurred on July 12. As of December 20, 2023, five of 36 surgical bone allograft recipients received laboratory-confirmed TB disease diagnoses; two patients died of TB. Whole-genome sequencing demonstrated close genetic relatedness between positive Mycobacterium tuberculosis cultures from surgical recipients and unused product. Although the bone product had tested negative by nucleic acid amplification testing before distribution, M. tuberculosis culture of unused product was not performed until after the outbreak was recognized. The public health response prevented up to 53 additional surgical procedures using allografts from that donor; additional measures to protect patients from tissue-transmitted M. tuberculosis are urgently needed.

Before the COVID-19 pandemic, the role of asymptomatic influenza virus infections in influenza transmission was uncertain. However, the importance of asymptomatic infection with SARS-CoV-2 for onward transmission of COVID-19 has led experts to question whether the role of asymptomatic influenza virus infections in transmission had been underappreciated. We discuss the existing evidence on the frequency of asymptomatic influenza virus infections, the extent to which they contribute to infection transmission, and remaining knowledge gaps. We propose priority areas for further evaluation, study designs, and case definitions to address existing knowledge gaps.

BACKGROUND: Antiviral chemoprophylaxis is recommended for use during influenza outbreaks in nursing homes to prevent transmission and severe disease among non-ill residents. Centers for Disease Control and Prevention (CDC) guidance recommends prophylaxis be initiated for all non-ill residents once an influenza outbreak is detected and be continued for at least 14 days and until seven days after the last laboratory-confirmed influenza case is identified. However, not all facilities strictly adhere to this guidance and the impact of such partial adherence is not fully understood. METHODS: We developed a stochastic compartmental framework to model influenza transmission within an average-sized U.S. nursing home. We compared the number of symptomatic illnesses and hospitalizations under varying prophylaxis implementation strategies, in addition to different levels of prophylaxis uptake and adherence by residents and healthcare personnel (HCP). RESULTS: Prophylaxis implemented according to current guidance reduced total symptomatic illnesses and hospitalizations among residents by an average of 12% and 36%, respectively, compared with no prophylaxis. We did not find evidence that alternative implementations of prophylaxis were more effective: compared to full adoption of current guidance, partial adoption resulted in increased symptomatic illnesses and/or hospitalizations, and longer or earlier adoption offered no additional improvements. In addition, increasing uptake and adherence among nursing home residents was effective in reducing resident illnesses and hospitalizations, but increasing HCP uptake had minimal indirect impacts for residents. CONCLUSIONS: The greatest benefits of influenza prophylaxis during nursing home outbreaks will likely be achieved through increasing uptake and adherence among residents and following current CDC guidance.

BACKGROUND: To assist clinicians with identifying children at risk of severe outcomes, we assessed the association between laboratory findings and severe outcomes among severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected children and determined if SARS-CoV-2 test result status modified the associations. METHODS: We conducted a cross-sectional analysis of participants tested for SARS-CoV-2 infection in 41 pediatric emergency departments in 10 countries. Participants were hospitalized, had laboratory testing performed, and completed 14-day follow-up. The primary objective was to assess the associations between laboratory findings and severe outcomes. The secondary objective was to determine if the SARS-CoV-2 test result modified the associations. RESULTS: We included 1817 participants; 522 (28.7%) SARS-CoV-2 test-positive and 1295 (71.3%) test-negative. Seventy-five (14.4%) test-positive and 174 (13.4%) test-negative children experienced severe outcomes. In regression analysis, we found that among SARS-CoV-2-positive children, procalcitonin ≥0.5 ng/mL (adjusted odds ratio [aOR], 9.14; 95% CI, 2.90-28.80), ferritin >500 ng/mL (aOR, 7.95; 95% CI, 1.89-33.44), D-dimer ≥1500 ng/mL (aOR, 4.57; 95% CI, 1.12-18.68), serum glucose ≥120 mg/dL (aOR, 2.01; 95% CI, 1.06-3.81), lymphocyte count <1.0 × 10(9)/L (aOR, 3.21; 95% CI, 1.34-7.69), and platelet count <150 × 10(9)/L (aOR, 2.82; 95% CI, 1.31-6.07) were associated with severe outcomes. Evaluation of the interaction term revealed that a positive SARS-CoV-2 result increased the associations with severe outcomes for elevated procalcitonin, C-reactive protein (CRP), D-dimer, and for reduced lymphocyte and platelet counts. CONCLUSIONS: Specific laboratory parameters are associated with severe outcomes in SARS-CoV-2-infected children, and elevated serum procalcitonin, CRP, and D-dimer and low absolute lymphocyte and platelet counts were more strongly associated with severe outcomes in children testing positive compared with those testing negative.

We report 2 cases of pharyngeal monkeypox virus and group A Streptococcus co-infection in the United States. No rash was observed when pharyngitis symptoms began. One patient required intubation before mpox was diagnosed. Healthcare providers should be aware of oropharyngeal mpox manifestations and possible co-infections; early treatment might prevent serious complications.

BACKGROUND: SARS-CoV-2 Omicron variants have the potential to impact vaccine effectiveness and duration of vaccine-derived immunity. We analyzed U.S. multi-jurisdictional COVID-19 vaccine breakthrough surveillance data to examine potential waning of protection against SARS-CoV-2 infection for the Pfizer-BioNTech (BNT162b) primary vaccination series by age. METHODS: Weekly numbers of SARS-CoV-2 infections during January 16, 2022-May 28, 2022 were analyzed by age group from 22 U.S. jurisdictions that routinely linked COVID-19 case surveillance and immunization data. A life table approach incorporating line-listed and aggregated COVID-19 case datasets with vaccine administration and U.S. Census data was used to estimate hazard rates of SARS-CoV-2 infections, hazard rate ratios (HRR) and percent reductions in hazard rate comparing unvaccinated people to people vaccinated with a Pfizer-BioNTech primary series only, by age group and time since vaccination. RESULTS: The percent reduction in hazard rates for persons 2 weeks after vaccination with a Pfizer-BioNTech primary series compared with unvaccinated persons was lowest among children aged 5-11 years at 35.5% (95% CI: 33.3%, 37.6%) compared to the older age groups, which ranged from 68.7%-89.6%. By 19 weeks after vaccination, all age groups showed decreases in the percent reduction in the hazard rates compared with unvaccinated people; with the largest declines observed among those aged 5-11 and 12-17 years and more modest declines observed among those 18 years and older. CONCLUSIONS: The decline in vaccine protection against SARS-CoV-2 infection observed in this study is consistent with other studies and demonstrates that national case surveillance data were useful for assessing early signals in age-specific waning of vaccine protection during the initial period of SARS-CoV-2 Omicron variant predominance. The potential for waning immunity during the Omicron period emphasizes the importance of continued monitoring and consideration of optimal timing and provision of booster doses in the future.

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident hospitalizations, incident cases, incident deaths, and cumulative deaths due to COVID-19 at national, state, and county levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work. Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below: AIpert-pwllnod: Natural Sciences and Engineering Research Council of Canada; Caltech-CS156: Gary Clinard Innovation Fund; CEID-Walk: University of Georgia; CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook; COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health; Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information &amp; Data Science Pilot Project; Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation; CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation; DDS-NBDS: NSF III-1812699; epiforecasts-ensemble1: Wellcome Trust (210758/Z/18/Z) FDANIHASU: supported by the Intramural Research Program of the NIH/NIDDK; GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowment, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. &amp; Charlene Zalesky, and Claudia &amp; Paul Raines, CDC MInD-Healthcare U01CK000531-Supplement; IHME: This work was supported by the Bill &amp; Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096); Imperial-ensemble1: SB acknowledges funding from the Wellcome Trust (219415); Institute of Business Forecasting: IBF; IowaStateLW-STEM: NSF DMS-1916204, Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics; IUPUI CIS: NSF; JHU_CSSE-DECOM: JHU CSSE: National Science Foundation (NSF) RAPID Real-time Forecasting of COVID-19 risk in the USA. 2021-2022. Award ID: 2108526. National Science Foundation (NSF) RAPID Development of an interactive web-based dashboard to track COVID-19 in real-time. 2020. Award ID: 2028604; JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers for Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, &amp; Infectious Disease Initiative (26798 Seed Grant); JHU_UNC_GAS-StatMechP ol: NIH NIGMS: R01GM140564; JHUAPL-Bucky: US Dept of Health and Human Services; KITmetricslab-select_ensemble: Daniel Wolffram gratefully acknowledges support by the Klaus Tschira Foundation; LANL-GrowthRate: LANL LDRD 20200700ER; MIT-Cassandra: MIT Quest for Intelligence; MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01; CA NU38OT000297 from the Council of State and Territorial Epidemiologists (CSTE); NotreDame-FRED: NSF RAPID DEB 2027718; NotreDame-mobility: NSF RAPID DEB 2027718; PSI-DRAFT: NSF RAPID Grant # 2031536; QJHong-Encounter: NSF DMR-2001411 and DMR-1835939; SDSC_ISG-TrendModel: The development of the dashboard was partly funded by the Fondation Privee des Hopitaux Universitaires de Geneve; UA-EpiCovDA: NSF RAPID Grant # 2028401; UChicagoCHATTOPADHYAY-UnIT: Defense Advanced Research Projects Agency (DARPA) #HR00111890043/P00004 (I. Chattopadhyay, University of Chicago); UCSB-ACTS: NSF RAPID IIS 2029626; UCSD_NEU-DeepGLEAM: Google Faculty Award, W31P4Q-21-C-0014; UMass-MechBayes: NIGMS #R35GM119582, NSF #1749854, NIGMS #R35GM119582; UMich-RidgeTfReg: This project is funded by the University of Michigan Physics Department and the University of Michigan Office of Research; UVA-Ensemble: National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and Virginia Dept of Health Grant VDH-21-501-0141; Wadnwani_AI-BayesOpt: This study is made possible by the generous support of the American People through the United States Agency for International Development (USAID). The work described in this article was implemented under the TRACETB Project, managed by WIAI under the terms of Cooperative Agreement Number 72038620CA00006. The contents of this manuscript are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government; WalmartLabsML-LogForecasting: Team acknowledges Walmart to support this study Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data produced are available online at https://github.com/reichlab/covid19-forecast-hub https://github.com/reichlab/covid19-forecast-hub

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naïve baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work.Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below. CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook. CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation. COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health. Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information&amp; Data Science Pilot Project. Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation. DDS-NBDS: NSF III-1812699. EPIFORECASTS-ENSEMBLE1: Wellcome Trust (210758/Z/18/Z) GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowments, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. &amp; Charlene Zalesky, and Claudia &amp; Paul Raines GT-DeepCOVID: CDC MInD-Healthcare U01CK000531-Supplement. NSF (Expeditions CCF-1918770, CAREER IIS-2028586, RAPID IIS-2027862, Medium IIS-1955883, NRT DGE-1545362), CDC MInD program, ORNL and funds/computing resources from Georgia Tech and GTRI. IHME: This work was supported by the Bill &amp; Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096). IowaStateLW-STEM: Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1916204, NSF CCF-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics. JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, US Office of Foreign Disaster Assistance, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers fo Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, &amp; Infectious Disease Initiative (26798 Seed Grant). LANL-GrowthRate: LANL LDRD 20200700ER. MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01. NotreDame-mobility and NotreDame-FRED: NSF RAPID DEB 2027718 UA-EpiCovDA: NSF RAPID Grant # 2028401. UCSB-ACTS: NSF RAPID IIS 2029626. UCSD-NEU: Google Faculty Award, DARPA W31P4Q-21-C-0014, COVID Supplement CDC-HHS-6U01IP001137-01. UMass-MechBayes: NIGMS R35GM119582, NSF 1749854. UMich-RidgeTfReg: The University of Michigan Physics Department and the University of Michigan Office of Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:UMass-Amherst IRBAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data and code referred to in the manuscript are publicly available. https://github.com/reichlab/covid19-forecast-hub/ https://github.com/reichlab/covidEnsembles https://zoltardata.com/project/44

Background The E484K and L452R amino acid substitutions on the spike protein of SARS-CoV-2 are associated with reduced neutralization by antibodies from acquired immunity. This study examines the respective association of these mutations with infection in persons who had previously received a COVID-19 vaccine.Methods Genetic sequences from SARS-CoV-2 specimens collected from Maryland residents and reported to Maryland Department of Health were linked to vaccination history. The prevalence of infections in fully vaccinated persons -- defined as being at least two weeks past receiving the final scheduled dose of a COVID-19 vaccine series -- was compared between infections caused by viruses carrying E484K to those not carrying E484K, and between infections caused by viruses carrying L452R to those not carrying L452R, using logistic regression to adjust for confounding.Results Of 9,048 sequenced SARS-CoV-2 specimens examined, 265 (2.9%) were collected from fully vaccinated persons. In adjusted analysis, the E484K substitution was associated with an increase in the odds of the sequenced specimen being collected from a fully vaccinated person (OR 1.96, 95% CI, 1.36 to 2.83). The L452R mutation was not significantly associated with infections in vaccinated persons (OR 1.07, 95% CI, 0.69 to 1.68).Conclusion Though more than 97% of SARS-CoV-2 infections were in persons who were not fully vaccinated, the E484K mutation was associated with increased odds of SARS-CoV-2 infection in vaccinated persons. Linking vaccination and sequencing data can help identify and estimate the impact SARS-CoV-2 mutations may have on vaccine effectiveness.Summary In viruses sequenced for Maryland’s routine SARS-CoV-2 genomic surveillance, the spike protein amino acid substitution E484K was more prevalent in viruses that infected vaccinated people than in viruses that infected people who were not vaccinated.Competing Interest StatementThe authors have declared no competing interest.Funding StatementNo external funding to report.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Case investigation, data collection, and analysis were conducted for public health purposes. This project was reviewed by the Division of Scientific Education and Professional Development within the Center for Surveillance, Epidemiology, and Laboratory Services at the Centers for Disease Control and Prevention (CDC). The project was determined to meet the requirements of public health surveillance covered by the U.S. Department of Health and Human Services Policy for the Protection of Human Research Subjects as defined in 45 C.F.R. part 46.102(l)(2), 21 C.F.R. part 56; 42 U.S.C. Sec.241(d); 5 U.S.C. Sec.552a; 44 U.S.C. Sec.3501 et seq. In., and the decision was made that this project was nonresearch and did not require ethical review by the CDC Human Research Protection Office. Ethical approval was waived and informed consent was not required.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesData are the property of the U.S. state of Maryland and are collected for public health surveillance purposes. They are not available to the ublic.

Little is known about enteropathogen seroepidemiology among children in low-resource settings. We measured serological IgG responses to eight enteropathogens (Giardia intestinalis, Cryptosporidium parvum, Entamoeba histolytica, Salmonella enterica, enterotoxigenic Escherichia coli, Vibrio cholerae, Campylobacter jejuni, norovirus) in cohorts from Haiti, Kenya, and Tanzania. We studied antibody dynamics and force of infection across pathogens and cohorts. Enteropathogens shared common seroepidemiologic features that enabled between-pathogen comparisons of transmission. Overall, exposure was intense: for most pathogens the window of primary infection was &lt;3 years old; for highest transmission pathogens primary infection occurred within the first year. Longitudinal profiles revealed significant IgG boosting and waning above seropositivity cutoffs, underscoring the value of longitudinal designs to estimate force of infection. Seroprevalence and force of infection were rank-preserving across pathogens, illustrating the measures provide similar information about transmission heterogeneity. Our findings suggest multiplex antibody assays are a promising approach to measure population-level enteropathogen transmission in serologic surveillance.

In July 2021, the Sonoma County Health Department was alerted to three cases of COVID-19 among residents of a homeless shelter in Santa Rosa, California. Among 153 shelter residents, 83 (54%) were fully vaccinated; 71 (86%) vaccinated residents had received the Janssen COVID-19 vaccine and 12 (14%) received an mRNA (Pfizer BioNTech or Moderna) COVID-19 vaccine. Within 1 month, 116 shelter residents (76%) received positive SARS-CoV-2 test results, including 66 fully vaccinated residents and 50 not fully vaccinated. 9 fully vaccinated and 1 unvaccinated were hospitalized for COVID-19. All hospitalized cases had at least one underlying medical condition. Two deaths occurred, one in a vaccinated resident and one in a non-vaccinated resident. Specimens from 52 residents underwent whole genome sequencing; all were identified as SARS-CoV-2, Delta Variant AY.13 lineage. Additional mitigation measures are needed in medically vulnerable congregate setting where limited resources make individual quarantine and isolation not feasible. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

Age-related cognitive decline, a common component of the brain aging process, is associated with significant impairment in daily functioning and quality of life among geriatric adults. While the complexity of mechanisms underlying cognitive aging are still being elucidated, microbial exposure and the multifactorial inflammatory cascades associated with systemic infections is emerging as a potential driver of neurological senescence. The negative cognitive and neurobiological consequences of a single pathogen-associated inflammatory experience, such as that modeled through treatment with lipopolysaccharide (LPS), are well documented. Yet, the brain aging impacts of repeated, intermittent inflammatory challenges are less well studied. To extend the emerging literature assessing the impact of infection burden on cognitive function among normally aging mice, here, we repeatedly exposed adult mice to intermittent LPS challenges during the aging period. Male 10-month-old C57BL6 mice were systemically administered escalating doses of LPS once every two weeks for 2.5 months. We evaluated cognitive consequences using the non-spatial step-through inhibitory avoidance task and both spatial working and reference memory versions of the Morris water maze. We also probed several potential mechanisms, including cortical and hippocampal cytokine/chemokine gene expression as well as hippocampal neuronal function via extracellular field potential recordings. Though there was limited evidence for an ongoing inflammatory state in cortex and hippocampus, we observed impaired learning and memory and a disruption of hippocampal long-term potentiation. These data suggest that a history of intermittent exposure to LPS-induced inflammation is associated with a subtle but significantly accelerated trajectory of cognitive decline. The broader impact of these findings may have important implications for standard of care involving infections in aging individuals or populations at-risk for dementia. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.

BACKGROUND: The diagnosis of SARS-CoV-2-associated multisystem inflammatory syndrome in adults (MIS-A) requires distinguishing it from acute COVID-19 and may impact clinical management. METHODS: In this retrospective cohort study, we applied the U.S. Centers for Disease Control and Prevention case definition to identify adults hospitalized with MIS-A at six academic medical centers during March 1, 2020-December 31, 2021. MIS-A patients were matched on age group, sex, site, and admission date at a 1:2 ratio to patients hospitalized with acute symptomatic COVID-19. Conditional logistic regression was used to compare demographics, presenting symptoms, laboratory and imaging results, treatments administered, and outcomes between cohorts. RESULTS: Through medical record review of 10,223 patients hospitalized with SARS-CoV-2-associated illness, we identified 53 MIS-A cases. Compared with 106 matched COVID-19 patients, MIS-A patients were more likely to be non-Hispanic Black and less likely to be non-Hispanic White. MIS-A patients more likely had laboratory-confirmed COVID-19 ≥ 14 days prior to hospitalization, more likely had positive in-hospital SARS-CoV-2 serologic testing, and more often presented with gastrointestinal symptoms and chest pain. They were less likely to have underlying medical conditions and to present with cough and dyspnea. On admission, MIS-A patients had higher neutrophil-to-lymphocyte ratio, C-reactive protein, ferritin, procalcitonin and D-dimer, compared with COVID-19 patients. MIS-A patients had longer hospitalization and more likely required intensive care admission, invasive mechanical ventilation, and vasopressors. Mortality was 6% in both cohorts. CONCLUSIONS: Compared with patients with acute symptomatic COVID-19, adults with MIS-A more often manifest certain symptoms and laboratory findings early during hospitalization. These features may facilitate diagnosis and management.

Although reinfections with SARS-CoV-2 have occurred in the United States with increasing frequency, U.S. epidemiologic trends in reinfections and associated severe outcomes have not been characterized. Weekly counts of SARS-CoV-2 reinfections, total infections, and associated hospitalizations and deaths reported by 18 U.S. jurisdictions during September 5, 2021-December 31, 2022, were analyzed overall, by age group, and by five periods of SARS-CoV-2 variant predominance (Delta and Omicron [BA.1, BA.2, BA.4/BA.5, and BQ.1/BQ.1.1]). Among reported reinfections, weekly trends in the median intervals between infections and frequencies of predominant variants during previous infections were calculated. As a percentage of all infections, reinfections increased substantially from the Delta (2.7%) to the Omicron BQ.1/BQ.1.1 (28.8%) periods; during the same periods, increases in the percentages of reinfections among COVID-19-associated hospitalizations (from 1.9% [Delta] to 17.0% [Omicron BQ.1/BQ.1.1]) and deaths (from 1.2% [Delta] to 12.3% [Omicron BQ.1/BQ.1.1]) were also substantial. Percentages of all COVID-19 cases, hospitalizations, and deaths that were reinfections were consistently higher across variant periods among adults aged 18-49 years compared with those among adults aged ≥50 years. The median interval between infections ranged from 269 to 411 days by week, with a steep decline at the start of the BA.4/BA.5 period, when >50% of reinfections occurred among persons previously infected during the Alpha variant period or later. To prevent severe COVID-19 outcomes, including those following reinfection, CDC recommends staying up to date with COVID-19 vaccination and receiving timely antiviral treatments, when eligible.

Updated (bivalent) COVID-19 vaccines were first recommended by CDC on September 1, 2022.* An analysis of case and death rates by vaccination status shortly after authorization of bivalent COVID-19 vaccines showed that receipt of a bivalent booster dose provided additional protection against SARS-CoV-2 infection and associated death (1). In this follow-up report on the durability of bivalent booster protection against death among adults aged ≥65 years, mortality rate ratios (RRs) were estimated among unvaccinated persons and those who received a bivalent booster dose by time since vaccination during three periods of Omicron lineage predominance (BA.5 [September 18–November 5, 2022], BQ.1/BQ.1.1 [November 6, 2022–January 21, 2023], and XBB.1.5 [January 22–April 1, 2023]).† | | During September 18, 2022–April 1, 2023, weekly counts of COVID-19–associated deaths§ among unvaccinated persons and those who received a bivalent booster dose¶ were reported from 20 U.S. jurisdictions** that routinely link case surveillance data to immunization registries and vital registration databases (1). Vaccinated persons who did not receive a bivalent COVID-19 booster dose were excluded. Rate denominators were calculated from vaccine administration data and 2019 U.S. intercensal population estimates,†† with numbers of unvaccinated persons estimated by subtracting numbers of vaccinated persons from the 2019 intercensal population estimates, as previously described§§ (1). Average weekly mortality rates were estimated based on date of specimen collection¶¶ during each variant period by vaccination status and time since bivalent booster dose receipt. RRs were calculated by dividing rates among unvaccinated persons by rates among bivalent booster dose recipients; after detrending the underlying linear changes in weekly rates, 95% CIs were estimated from the remaining variation in rates observed*** (1). SAS (version 9.4; SAS Institute) and R (version 4.1.2; R Foundation) software were used to conduct all analyses. This activity was reviewed by CDC and was conducted consistent with applicable federal law and CDC policy.†††