We report the complete genome sequences of nine double recombinant vaccine-derived novel oral poliovirus type 2 genomes from acute flaccid paralysis (AFP) cases (n = 3), AFP case contacts (n = 4), and environmental surveillance sampling (n = 2) in Nigeria.

CDC continues to track the evolution of SARS-CoV-2, including the Omicron variant and its descendants, using national genomic surveillance. This report summarizes U.S. trends in variant proportion estimates during May 2023-September 2024, a period when SARS-CoV-2 lineages primarily comprised descendants of Omicron variants XBB and JN.1. During summer and fall 2023, multiple descendants of XBB with immune escape substitutions emerged and reached >10% prevalence, including EG.5-like lineages by June 24, FL.1.5.1-like lineages by August 5, HV.1 lineage by September 30, and HK.3-like lineages by November 11. In winter 2023, the JN.1 variant emerged in the United States and rapidly attained predominance nationwide, representing a substantial genetic shift (>30 spike protein amino acid differences) from XBB lineages. Descendants of JN.1 subsequently circulated and reached >10% prevalence, including KQ.1-like and KP.2-like lineages by April 13, KP.3 and LB.1-like lineages by May 25, and KP.3.1.1 by July 20. Surges in COVID-19 cases occurred in winter 2024 during the shift to JN.1 predominance, as well as in summer 2023 and 2024 during circulation of multiple XBB and JN.1 descendants, respectively. The ongoing evolution of the Omicron variant highlights the importance of continued genomic surveillance to guide medical countermeasure development, including the selection of antigens for updated COVID-19 vaccines.

To reduce influenza-associated morbidity and mortality, countries in South America recommend annual influenza vaccination for persons at high risk for severe influenza illness, including young children, persons with preexisting health conditions, and older adults. Interim estimates of influenza vaccine effectiveness (VE) from Southern Hemisphere countries can provide early information about the protective effects of vaccination and help guide Northern Hemisphere countries in advance of their season. Using data from a multicountry network, investigators estimated interim VE against influenza-associated severe acute respiratory illness (SARI) hospitalization using a test-negative case-control design. During March 13-July 19, 2024, Argentina, Brazil, Chile, Paraguay, and Uruguay identified 11,751 influenza-associated SARI cases; on average, 21.3% of patients were vaccinated against influenza, and the adjusted VE against hospitalization was 34.5%. The adjusted VE against the predominating subtype A(H3N2) was 36.5% and against A(H1N1)pdm09 was 37.1%. These interim VE estimates suggest that although the proportion of hospitalized patients who were vaccinated was modest, vaccination with the Southern Hemisphere influenza vaccine significantly lowered the risk for hospitalization. Northern Hemisphere countries should, therefore, anticipate the need for robust influenza vaccination campaigns and early antiviral treatment to achieve optimal protection against influenza-associated complications.

BACKGROUND: Dengue fever remains a significant public health challenge in tropical and subtropical regions, with its transmission dynamics being influenced by both environmental factors and human mobility. The Dominican Republic, a biodiversity hotspot in the Caribbean, has experienced recurrent dengue outbreaks, yet detailed understanding of the virus's transmission pathways and the impact of climatic factors remains limited. This study aims to elucidate the recent transmission dynamics of the dengue virus (DENV) in the Dominican Republic, utilizing a combination of genomic sequencing and epidemiological data analysis, alongside an examination of historical climate patterns. METHODS: We conducted a comprehensive study involving the genomic sequencing of DENV samples collected from patients across different regions of the Dominican Republic over a two-year period. Phylogenetic analyses were performed to identify the circulation of DENV lineages and to trace transmission pathways. Epidemiological data were integrated to analyze trends in dengue incidence and distribution. Additionally, we integrated historical climate data spanning several decades to assess trends in temperature and their potential impact on DENV transmission potential. RESULTS: Our results highlight a previously unknown north-south transmission pathway within the country, with the co-circulation of multiple virus lineages. Additionally, we examine the historical climate data, revealing long-term trends towards higher theoretical potential for dengue transmission due to rising temperatures. CONCLUSION: This multidisciplinary study reveals intricate patterns of dengue virus transmission in the Dominican Republic, characterized by the co-circulation of multiple DENV lineages and a novel transmission pathway. The observed correlation between rising temperatures and increased dengue transmission potential emphasizes the need for integrated climate-informed strategies in dengue control efforts. Our findings offer critical insights for public health authorities in the Dominican Republic and similar settings, guiding resource allocation and the development of preparedness strategies to mitigate the impacts of climate change on dengue transmission.

The Global Specialized Polio Laboratory at CDC supports the Global Poliovirus Laboratory Network with environmental surveillance (ES) to detect the presence of vaccine strain polioviruses, vaccine-derived polioviruses, and wild polioviruses in high-risk countries. Environmental sampling provides valuable supplementary information, particularly in areas with gaps in surveillance of acute flaccid paralysis (AFP) mainly in children less than 15 years. In collaboration with Guatemala's National Health Laboratory (Laboratorio Nacional de Salud Guatemala), monthly sewage collections allowed screening enterovirus (EV) presence without incurring additional costs for sample collection, transport, or concentration. Murine recombinant fibroblast L-cells (L20B) and human rhabdomyosarcoma (RD) cells are used for the isolation of polioviruses following a standard detection algorithm. Though non-polio-Enteroviruses (NPEV) can be isolated, the algorithm is optimized for the detection of polioviruses. To explore if other EV's are present in sewage not found through standard methods, five additional cell lines were piloted in a small-scale experiment, and next-generation sequencing (NGS) was used for the identification of any EV types. Human lung fibroblast cells (HLF) were selected based on their ability to isolate EV-A genus. Sewage concentrates collected between 2020-2021 were isolated in HLF cells and any cytopathic effect positive isolates used for NGS. A large variety of EVs, including echoviruses 1, 3, 6, 7, 11, 13, 18, 19, 25, 29; coxsackievirus A13, B2, and B5, EV-C99, EVB, and polioviruses (Sabin 1 and 3) were identified through genomic typing in NGS. When the EV genotypes were compared by phylogenetic analysis, it showed many EV's were genomically like viruses previously isolated from ES collected in Haiti. Enterovirus occurrence did not follow a seasonality, but more diverse EV types were found in ES collection sites with lower populations. Using the additional cell line in the existing poliovirus ES algorithm may add value by providing data about EV circulation, without additional sample collection or processing. Next-generation sequencing closed gaps in knowledge providing molecular epidemiological information on multiple EV types and full genome sequences of EVs present in wastewater in Guatemala.

We report the complete genome sequences of six S19 poliovirus reference strains for all three poliovirus serotypes, including three Sabin vaccine-derived and three wild-type-derived strains. The S19 strains are extensively attenuated and genetically stable when compared to the reference poliovirus strains, while maintaining the same antigenicity and immunogenicity.

BACKGROUND: Recently, increasing focus on patient input into research and healthcare improvements has fostered expanded patient-centered advocacy efforts. This first pan-fungal disease summit, part of the MYCology Advocacy, Research, & Education effort, brought together patients, caregivers, and mycology experts to better document patient experiences with invasive fungal disease (IFD) and establish priorities for mycology education, advocacy, and research. METHODS: Patients who had suffered from IFD, their caregivers, clinicians, industry representatives, government officials, and patient advocacy professionals were invited. Patients and caregivers shared their stories and struggles with IFD. Breakout sessions separated mycology experts from patients and caregivers for further discussions to identify commonalities and perceived gaps and to formulate recommendations. The 2 groups then reconvened to develop consensus recommendations. RESULTS: IFD patients and their caregivers shared experiences reflecting the typically lengthy prediagnosis, acute treatment, long-term treatment, and posttreatment recovery stages of IFD. They reported substantial physical, psychological, and financial burdens associated with the IFD experience, particularly related to delayed diagnoses. They reaffirmed a need for coordinated patient-centered education, peer support, and advocacy to document the burden of serious fungal infections. Mycology experts discussed strategies to address gaps in the mycology field, such as insufficient training, inadequate workforce support, and a need to partner more with patient groups. CONCLUSIONS: A summit involving patients with IFD, family caregivers, and mycology experts identified a substantial nonclinical burden of disease associated with IFD. Patients and mycology experts prioritized several goals for education, advocacy, and research to raise awareness of IFD and improve outcomes.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

Associations between antenatal SARS-CoV-2 infection and pregnancy outcomes have been conflicting and the role of the immune system is currently unclear. This prospective cohort study investigated the interaction of antenatal SARS-CoV-2 infection, changes in cytokine and HS-CRP levels, birthweight and gestational age at birth. 2352 pregnant participants from New York City (2020-2022) were included. Plasma levels of interleukin (IL)-1β, IL-6, IL-17A and high-sensitivity C-reactive protein (HS-CRP) were quantified in blood specimens obtained across pregnancy. Quantile and linear regression models were conducted to 1) assess the impact of antenatal SARS-CoV-2 infection, overall and by timing of detection of SARS-CoV-2 positivity (< 20 weeks versus ≥ 20 weeks), on birthweight and gestational age at delivery; 2) examine the relationship between SARS-CoV-2 infection and maternal immune changes during pregnancy. All models were adjusted for maternal demographic and obstetric factors and pandemic timing. Birthweight models were additionally adjusted for gestational age at delivery and fetal sex. Immune marker models were also adjusted for gestational age at specimen collection and multiplex assay batch. 371 (15.8%) participants were infected with SARS-CoV-2 during pregnancy, of which 98 (26.4%) were infected at < 20 weeks gestation. Neither SARS-CoV-2 infection in general nor in early or late pregnancy was associated with lower birthweight nor earlier gestational age at delivery. Further, we did not observe cytokine or HS-CRP changes in response to SARS-CoV-2 infection and thus found no evidence to support a potential association between immune dysregulation and the diversity in pregnancy outcomes following infection.

BACKGROUND: Fungal meningitis can be associated with epidural anesthesia procedures. Fusariosis is a rare infection typically affecting immunocompromised patients and rarely causes meningitis. During 2022-2023, public health officials responded to a large outbreak of Fusarium solani meningitis associated with epidural anesthesia in Durango, Mexico. METHODS: The public health response and epidemiological and clinical features of patients affected by this outbreak were described. Coordinated actions were addressed to identify the etiological agent, determine its drug susceptibility, develop diagnostic tests, and implement clinical and epidemiological protocols. Retrospective analyses of clinical variables and outcomes were performed to determine association with better patient survival. RESULTS: A total of 1801 persons exposed to epidural anesthesia were identified, of whom 80 developed meningitis. Fusarium solani was found in 3 brain biopsies and showed susceptibility to voriconazole and amphotericin B. After F solani polymerase chain reaction (PCR) implementation, 57 patients with meningitis were PCR-screened, and 31 (38.8%) had a positive result. Most patients were female (95%), and cesarean section was the most common surgical procedure (76.3%). The case fatality rate was 51.3% (41 patients) and the median hospitalization duration was 39.5 days (interquartile range, 18-86 days). Seventy-one patients (88.8%) received voriconazole/amphotericin B and 64 subjects (80%) additionally received steroids. Cox regression analysis showed an increased lethality risk in patients who received antifungal treatment after 5 days (hazard ratio, 2.1 [95% confidence interval, 1.01-4.48], P < .05). CONCLUSIONS: The F solani meningitis outbreak in Durango was an unprecedented medical challenge. Timely treatment and effective healthcare management were associated with better survival outcomes.

BACKGROUND: SARS-CoV-2 infection in pregnancy is associated with an increased risk of adverse birth outcomes such as preterm birth, stillbirth, and maternal and infant complications. Previous research suggests an increased risk of severe COVID-19 illness and stillbirth in pregnant people during delta variant predominance in 2021; however, those studies did not assess timing of infection during pregnancy, and few of them described COVID-19 vaccination status. OBJECTIVE: Using a large population-based cohort, this study compared pregnancy and infant outcomes and described demographic and clinical characteristics of pregnant people with SARS-CoV-2 infection prior to and during the delta variant period. STUDY DESIGN: This retrospective cohort analysis included persons with confirmed SARS-CoV-2 infection in pregnancy from 6 US jurisdictions reporting to the Surveillance for Emerging Threats to Pregnant People and Infants Network. Data were collected through case reports of polymerase chain reaction-positive pregnant persons and linkages to birth certificates, fetal death records, and immunization records. We described clinical characteristics and compared frequency of spontaneous abortion (<20 weeks of gestation), stillbirth (≥20 weeks), preterm birth (<37 weeks), small for gestational age, and term infant neonatal intensive care unit admission between the time periods of pre-delta and delta variant predominance. Study time periods were determined by when variants constituted more than 50% of sequences isolated according to regional SARS-CoV-2 genomic surveillance data, with time periods defined for pre-delta (March 3, 2020-June 25, 2021) and Delta (June 26, 2021-December 25, 2021). Adjusted prevalence ratios were estimated for each outcome measure using Poisson regression and were adjusted for continuous maternal age, race and ethnicity, and insurance status at delivery. RESULTS: Among 57,563 pregnancy outcomes, 57,188 (99.3%) were liveborn infants, 65 (0.1%) were spontaneous abortions, and 310 (0.5%) were stillbirths. Most pregnant persons were unvaccinated at the time of SARS-CoV-2 infection, with a higher proportion in pre-delta (99.4%) than in the delta period (78.4%). Of those with infections during delta and who were previously vaccinated, the timing from last vaccination to infection was a median of 183 days. Compared to pre-delta, infections during delta were associated with a higher frequency of stillbirths (0.7% vs 0.4%; adjusted prevalence ratio, 1.55; 95% confidence interval, 1.14-2.09) and preterm births (12.8% vs 11.9%; adjusted prevalence ratio, 1.14; 95% confidence interval, 1.07-1.20). The delta period was associated with a lower frequency of neonatal intensive care unit admission (adjusted prevalence ratio, 0.74; 95% confidence interval, 0.67-0.82) than in the pre-delta period. During the delta period, infection during the third trimester was associated with a higher frequency of preterm birth (adjusted prevalence ratio, 1.41; 95% confidence interval, 1.28-1.56) and neonatal intensive care unit admission (adjusted prevalence ratio, 1.21; 95% confidence interval, 1.01-1.45) compared to the first and second trimester combined. CONCLUSION: In this US-based cohort of persons with SARS-CoV-2 infection in pregnancy, the majority were unvaccinated, and frequencies of stillbirth and preterm birth were higher during the delta variant predominance period than in the pre-delta period. During the delta period, frequency of preterm birth and neonatal intensive care unit admission was higher among infections occurring in the third trimester vs those earlier in pregnancy. These findings demonstrate population-level increases of adverse fetal and infant outcomes, specifically in the presence of a COVID-19 variant with more severe presentation.

Characterisation of influenza viruses in the southern hemisphere can guide local response and provide insights to northern hemisphere jurisdictions about their upcoming influenza season.1,2 Here, we present the information on 2023 end of influenza season in the southern hemisphere about influenza lineages, incidence of medically attended, laboratory-confirmed influenza cases, and influenza vaccine effectiveness (VE) against the antigen from surveillance clinics and a hospital in San Juan de Lurigancho and San Martin de Porres, the two most populated districts of Peru. | | From Jan 1 to Sept 30, 2023, surveillance nurses sought individuals with COVID-19-like illness (CLI) of any age seeking care at outpatient sentinel sites between Monday and Saturday. CLI was defined as presenting with at least two of the following symptoms or signs—fever, chills, rigors, myalgia, headache, or sore throat for not more than 7 days from illness onset.3 On March 7, 2023, the nurses expanded their search to CLI cases hospitalised for not more than 72 h at Cayetano Heredia National Hospital. | | Nurses obtained written consent to survey and swab CLI cases. Enrolled participants provided information on pre-existing conditions and influenza vaccination status. Individuals targeted for vaccination by Peru and vaccinated between Jan and Sept 2022, more than 14 days before enrolment, were considered vaccinated (appendix p 1).

Despite the 2009 World Health Organization recommendation that all countries introduce rotavirus vaccines (RVV) into their national immunization programs, just 81 countries had introduced RVV by the end of 2015, leaving millions of children at risk for rotavirus morbidity and mortality. In response, the Rotavirus Accelerated Vaccine Introduction Network (RAVIN) was established in 2016 to provide support to eight Gavi-eligible countries that had yet to make an RVV introduction decision and/or had requested technical assistance with RVV preparations: Afghanistan, Bangladesh, Benin, Cambodia, Democratic Republic of Congo, Lao People's Democratic Republic, Myanmar, and Nepal. During 2016-2020, RAVIN worked with country governments and partners to support evidence-based immunization decision-making, RVV introduction preparation and implementation, and multilateral coordination. By the September 2020 program close-out, five of the eight RAVIN focus countries successfully introduced RVV into their routine childhood immunization programs. We report on the RAVIN approach, describe how the project responded collectively to an evolving RVV product landscape, synthesize common characteristics of the RAVIN country experiences, highlight key lessons learned, and outline the unfinished agenda to inform future new vaccine introduction efforts by countries and global partners.

BACKGROUND: Healthcare workers (HCWs) have experienced high rates of coronavirus disease 2019 (COVID-19) morbidity and mortality. We estimated COVID-19 2-dose primary series and monovalent booster vaccine effectiveness (VE) against symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron (BA.1 and BA.2) infection among HCWs in 3 Albanian hospitals during January-May 2022. METHODS: Study participants completed weekly symptom questionnaires, underwent polymerase chain reaction (PCR) testing when symptomatic, and provided quarterly blood samples for serology. We estimated VE using Cox regression models (1 - hazard ratio), with vaccination status as the time-varying exposure and unvaccinated HCWs as the reference group, adjusting for potential confounders: age, sex, prior SARS-CoV-2 infection (detected by PCR, rapid antigen test, or serology), and household size. RESULTS: At the start of the analysis period, 76% of 1462 HCWs had received a primary series, 10% had received a booster dose, and 9% were unvaccinated; 1307 (89%) HCWs had evidence of prior infection. Overall, 86% of primary series and 98% of booster doses received were BNT162b2. The median time interval from the second dose and the booster dose to the start of the analysis period was 289 (interquartile range [IQR], 210-292) days and 30 (IQR, 22-46) days, respectively. VE against symptomatic PCR-confirmed infection was 34% (95% confidence interval [CI], -36% to 68%) for the primary series and 88% (95% CI, 39%-98%) for the booster. CONCLUSIONS: Among Albanian HCWs, most of whom had been previously infected, COVID-19 booster dose offered improved VE during a period of Omicron BA.1 and BA.2 circulation. Our findings support promoting booster dose uptake among Albanian HCWs, which, as of January 2023, was only 20%. Clinical Trials Registration. NCT04811391.

Malaria is a serious and potentially fatal disease transmitted through the bite of an infective | female anopheline mosquito; pregnant people are more susceptible to malaria infection than nonpregnant people, and are at risk of significant adverse consequences for both mother and infant.1 | | These include maternal anemia, fetal growth retardation, stillbirth, premature birth, and low | birthweight.2 | Rarely, malaria can be transmitted congenitally from mother to fetus or to the | neonate at birth. Globally, it is estimated that over 13 million pregnancies were affected by | malaria in 2021, leading to an estimated 505,000 infants born with low birth weight.3 While | malaria in pregnancy is rarely seen in the United States, it nonetheless occurs, with 19 cases | among pregnant women (both travelers and refugees/immigrants) reported in the US in 2018, | 4 27 | in 2019 (Mace, unpublished data), and 8 in 2020 (Mace, unpublished data), and needs to be | recognized and treated quickly to prevent adverse effects to the mother and infant.

BACKGROUND: Uncertainty about risk of illness and the value of influenza vaccines negatively affects vaccine uptake among persons targeted for influenza vaccination. METHODS: During 2016-2019, we followed a cohort of healthcare personnel (HCP) targeted for free-of-charge influenza vaccination in five Lima hospitals to quantify risk of influenza, workplace presenteeism (coming to work despite illness), and absenteeism (taking time off from work because of illness). The HCP who developed acute respiratory illnesses (ARI) (≥1 of acute cough, runny nose, body aches, or feverishness) were tested for influenza using reverse-transcription polymerase chain reaction (rt-PCR). FINDINGS: The cohort (2968 HCP) contributed 950,888 person-days. Only 36 (6%) of 605 HCP who participated every year were vaccinated. The HCP had 5750 ARI and 147 rt-PCR-confirmed influenza illnesses. The weighted incidence of laboratory-confirmed influenza was 10.0/100 person-years; 37% used antibiotics, and 0.7% used antivirals to treat these illnesses. The HCP with laboratory-confirmed influenza were present at work while ill for a cumulative 1187 hours. INTERPRETATION: HCP were frequently ill and often worked rather than stayed at home while ill. Our findings suggest the need for continuing medical education about the risk of influenza and benefits of vaccination and stay-at-home-while-ill policies.

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

Viruses have high mutation rates and generally exist as a mixture of variants in biological samples. Next-generation sequencing (NGS) approach has surpassed Sanger for generating long viral sequences, yet how variants affect NGS de novo assembly remains largely unexplored. Our results from &gt;15,000 simulated experiments showed that presence of variants can turn an assembly of one genome into tens to thousands of contigs. This “variant interference” (VI) is highly consistent and reproducible by ten most used de novo assemblers, and occurs independent of genome length, read length, and GC content. The main driver of VI is pairwise identities between viral variants. These findings were further supported by in silico simulations, where selective removal of minor variant reads from clinical datasets allow the “rescue” of full viral genomes from fragmented contigs. These results call for careful interpretation of contigs and contig numbers from de novo assembly in viral deep sequencing.

Next-generation sequencing is a powerful tool for virological surveillance. While Illumina® and Ion Torrent® sequencing platforms are used extensively for generating viral RNA genome sequences, there is limited data comparing different platforms. We evaluated the Illumina MiSeq, Ion Torrent PGM and Ion Torrent S5 platforms using a panel of sixteen specimens containing picornaviruses and human caliciviruses (noroviruses and sapoviruses). The specimens were processed, using combinations of three library preparation and five sequencing kits, to assess the quality and completeness of assembled viral genomes, and an estimation of cost per sample to generate the data was calculated. The choice of library preparation kit and sequencing platform was found to impact the breadth of genome coverage and accuracy of consensus viral genomes. The Ion Torrent S5 outperformed the older Ion Torrent PGM platform in data quality and cost, and generated the highest proportion of reads for enterovirus D68 samples. However, indels at homopolymer regions impacted the accuracy of consensus genome sequences. For lower throughput sequencing runs (i.e., Ion Torrent 510 or Illumina MiSeq Nano V2), the cost per sample was lower on the MiSeq platform, whereas with higher throughput runs (Ion Torrent 530 or Illumina MiSeq V2) the cost per sample was comparable. These findings suggest that the Ion Torrent S5 and Illumina MiSeq platforms are both viable options for genomic sequencing of RNA viruses, each with specific advantages and tradeoffs.

Background Healthcare workers (HCWs) have experienced high rates of COVID-19 morbidity and mortality. We estimated COVID-19 two-dose primary series and monovalent booster vaccine effectiveness (VE) against symptomatic SARS-CoV-2 Omicron (BA.1 and BA.2) infection among HCWs in three Albanian hospitals during January-May 2022. Methods Study participants completed weekly symptom questionnaires, underwent PCR testing when symptomatic, and provided quarterly blood samples for serology. We estimated VE using Cox regression models (1-hazard ratio), with vaccination status as the time-varying exposure and unvaccinated HCWs as the reference group, adjusting for potential confounders: age, sex, prior SARS-CoV-2 infection (detected by PCR, rapid-antigen test or serology), and household size. Results At the start of the analysis period, 76% of 1,462 HCWs had received a primary series, 10% had received a booster dose, and 9% were unvaccinated; 1,307 (89%) HCWs had evidence of prior infection. Overall, 86% of primary series and 98% of booster doses received were BNT162b2. The median time interval from the second dose and the booster dose to the start of the analysis period was 289 days (IQR:210-292) and 30 days (IQR:22-46), respectively. VE against symptomatic PCR-confirmed infection was 34% (95%CI: -36;68) for the primary series and 88% (95%CI: 38;98) for the booster. Conclusions Among Albanian HCWs, most of whom had been previously infected, COVID-19 booster dose offered improved VE during a period of Omicron BA.1 and BA.2 circulation. Our findings support promoting booster dose uptake among Albanian HCWs, which, as of January 2023, was only 20%. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

BACKGROUND: Healthcare workers have experienced high rates of morbidity and mortality from coronavirus disease 2019 (COVID-19). METHODS: A prospective cohort study was conducted in three Albanian hospitals between 19 February and 14 December 2021. All participants underwent polymerase chain reaction (PCR) and serological testing at enrolment, regular serology throughout, and PCR testing when symptomatic.Vaccine effectiveness (VE) against COVID-19 and against all severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infections (symptomatic or asymptomatic) was estimated. VE was estimated using a Cox regression model, with vaccination status as a time-varying variable. FINDINGS: In total, 1504 HCWs were enrolled in this study; 70% had evidence of prior SARS-CoV-2 infection. VE was 65.1% [95% confidence interval (CI) 37.7-80.5] against COVID-19, 58.2% (95% CI 15.7-79.3) among participants without prior SARS-CoV-2 infection, and 73.6% (95% CI 24.3-90.8) among participants with prior SARS-CoV-2 infection. For BNT162b2 alone, VE was 69.5% (95% CI 44.5-83.2). During the period when the Delta variant was predominant, VE was 67.1% (95% CI 38.3-82.5). VE against SARS-CoV-2 infection for the full study period was 36.9% (95% CI 15.8-52.7). INTERPRETATION: This study found moderate primary series VE against COVID-19 among healthcare workers in Albania. These results support the continued promotion of COVID-19 vaccination in Albania, and highlight the benefits of vaccination in populations with high levels of prior infection.

Introduction: Despite a government-subsidized vaccination program, healthcare personnel (HCP) influenza vaccination uptake remains low in Peru. Using three years of cross-sectional surveys and an additional five years of prior vaccination history of HCP in Peru, we explored HCP knowledge, attitudes, and practices (KAP) of influenza illness and its impact on vaccination frequency. Methods: In 2016, the Estudio Vacuna de Influenza Peru (VIP) cohort was initiated in Lima, Peru, which collected information about HCP KAP and influenza vaccination history from 20112018. HCP were classified by their 8-year influenza vaccination history as never (0 years), infrequently (14 years), or frequently (58 years) vaccinated. Logistic regression models were used to describe KAP associated with frequent compared to infrequent influenza vaccination, adjusted for each HCP's healthcare workplace, age, sex, preexisting medical conditions, occupation, and length of time providing direct patient care. Results: From 20162018, 5131 HCP were recruited and 3120 fully enrolled in VIP; 2782 consistently reported influenza vaccination status and became our analytic sample. From 20112018, 14.3% of HCP never, 61.4% infrequently, and 24.4% frequently received influenza vaccines. Compared to HCP who were infrequently vaccinated, frequently vaccinated HCP were more likely to believe they were susceptible to influenza (adjusted odds ratio [aOR]:1.49, 95% confidence interval [CI]:1.221.82), perceived vaccination to be effective (aOR:1.92, 95%CI:1.592.32), were knowledgeable about influenza and vaccination (aOR:1.37, 95%CI:1.061.77), and believed vaccination had emotional benefits like reduced regret or anger if they became ill with influenza (aOR:1.96, 95%CI:1.602.42). HCP who reported vaccination barriers like not having time or a convenient place to receive vaccines had reduced odds of frequent vaccination (aOR:0.74, 95%CI:0.610.89) compared to those without reported barriers. Conclusion: Few HCP frequently received influenza vaccines during an eight-year period. To increase HCP influenza vaccination in middle-income settings like Peru, campaigns could strengthen influenza risk perception, vaccine knowledge, and accessibility. 2023

Introduction: Despite a government-subsidized vaccination program, healthcare personnel (HCP) influenza vaccination uptake remains low in Peru. Using three years of cross-sectional surveys and an additional five years of prior vaccination history of HCP in Peru, we explored HCP knowledge, attitudes, and practices (KAP) of influenza illness and its impact on vaccination frequency. Methods: In 2016, the Estudio Vacuna de Influenza Peru (VIP) cohort was initiated in Lima, Peru, which collected information about HCP KAP and influenza vaccination history from 2011─2018. HCP were classified by their 8-year influenza vaccination history as never (0 years), infrequently (1─4 years), or frequently (5─8 years) vaccinated. Logistic regression models were used to describe KAP associated with frequent compared to infrequent influenza vaccination, adjusted for each HCP's healthcare workplace, age, sex, preexisting medical conditions, occupation, and length of time providing direct patient care. Results: From 2016─2018, 5131 HCP were recruited and 3120 fully enrolled in VIP; 2782 consistently reported influenza vaccination status and became our analytic sample. From 2011─2018, 14.3% of HCP never, 61.4% infrequently, and 24.4% frequently received influenza vaccines. Compared to HCP who were infrequently vaccinated, frequently vaccinated HCP were more likely to believe they were susceptible to influenza (adjusted odds ratio [aOR]:1.49, 95% confidence interval [CI]:1.22─1.82), perceived vaccination to be effective (aOR:1.92, 95%CI:1.59─2.32), were knowledgeable about influenza and vaccination (aOR:1.37, 95%CI:1.06─1.77), and believed vaccination had emotional benefits like reduced regret or anger if they became ill with influenza (aOR:1.96, 95%CI:1.60─2.42). HCP who reported vaccination barriers like not having time or a convenient place to receive vaccines had reduced odds of frequent vaccination (aOR:0.74, 95%CI:0.61─0.89) compared to those without reported barriers. Conclusion: Few HCP frequently received influenza vaccines during an eight-year period. To increase HCP influenza vaccination in middle-income settings like Peru, campaigns could strengthen influenza risk perception, vaccine knowledge, and accessibility. © 2023

SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), was first identified in December 2019 in Wuhan, China, and has since spread worldwide. On March 11, 2020, the World Health Organization declared COVID-19 a pandemic (1). That same day, the first confirmed COVID-19-associated fatality occurred in New York City (NYC). To identify confirmed COVID-19-associated deaths, defined as those occurring in persons with laboratory-confirmed SARS-CoV-2 infection, on March 13, 2020, the New York City Department of Health and Mental Hygiene (DOHMH) initiated a daily match between all deaths reported to the DOHMH electronic vital registry system (eVital) (2) and laboratory-confirmed cases of COVID-19. Deaths for which COVID-19, SARS-CoV-2, or an equivalent term is listed on the death certificate as an immediate, underlying, or contributing cause of death, but that do not have laboratory-confirmation of COVID-19 are classified as probable COVID-19-associated deaths. As of May 2, a total of 13,831 laboratory-confirmed COVID-19-associated deaths, and 5,048 probable COVID-19-associated deaths were recorded in NYC (3). Counting only confirmed or probable COVID-19-associated deaths, however, likely underestimates the number of deaths attributable to the pandemic. The counting of confirmed and probable COVID-19-associated deaths might not include deaths among persons with SARS-CoV-2 infection who did not access diagnostic testing, tested falsely negative, or became infected after testing negative, died outside of a health care setting, or for whom COVID-19 was not suspected by a health care provider as a cause of death. The counting of confirmed and probable COVID-19-associated deaths also does not include deaths that are not directly associated with SARS-CoV-2 infection. The objective of this report is to provide an estimate of all-cause excess deaths that have occurred in NYC in the setting of widespread community transmission of SARS-CoV-2. Excess deaths refer to the number of deaths above expected seasonal baseline levels, regardless of the reported cause of death. Estimation of all-cause excess deaths is used as a nonspecific measure of the severity or impact of pandemics (4) and public health emergencies (5). Reporting of excess deaths might provide a more accurate measure of the impact of the pandemic.

BACKGROUND: Many children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies so far have been small and localised, with limited generalisability. We aimed to evaluate the performance of currently used diagnostic algorithms and to use prediction modelling to develop evidence-based algorithms to assist in tuberculosis treatment decision making for children presenting to primary health-care centres. METHODS: For this meta-analysis, we identified individual participant data from a WHO public call for data on the management of tuberculosis in children and adolescents and referral from childhood tuberculosis experts. We included studies that prospectively recruited consecutive participants younger than 10 years attending health-care centres in countries with a high tuberculosis incidence for clinical evaluation of pulmonary tuberculosis. We collated individual participant data including clinical, bacteriological, and radiological information and a standardised reference classification of pulmonary tuberculosis. Using this dataset, we first retrospectively evaluated the performance of several existing treatment-decision algorithms. We then used the data to develop two multivariable prediction models that included features used in clinical evaluation of pulmonary tuberculosis-one with chest x-ray features and one without-and we investigated each model's generalisability using internal-external cross-validation. The parameter coefficient estimates of the two models were scaled into two scoring systems to classify tuberculosis with a prespecified sensitivity target. The two scoring systems were used to develop two pragmatic, treatment-decision algorithms for use in primary health-care settings. FINDINGS: Of 4718 children from 13 studies from 12 countries, 1811 (38·4%) were classified as having pulmonary tuberculosis: 541 (29·9%) bacteriologically confirmed and 1270 (70·1%) unconfirmed. Existing treatment-decision algorithms had highly variable diagnostic performance. The scoring system derived from the prediction model that included clinical features and features from chest x-ray had a combined sensitivity of 0·86 [95% CI 0·68-0·94] and specificity of 0·37 [0·15-0·66] against a composite reference standard. The scoring system derived from the model that included only clinical features had a combined sensitivity of 0·84 [95% CI 0·66-0·93] and specificity of 0·30 [0·13-0·56] against a composite reference standard. The scoring system from each model was placed after triage steps, including assessment of illness acuity and risk of poor tuberculosis-related outcomes, to develop treatment-decision algorithms. INTERPRETATION: We adopted an evidence-based approach to develop pragmatic algorithms to guide tuberculosis treatment decisions in children, irrespective of the resources locally available. This approach will empower health workers in primary health-care settings with high tuberculosis incidence and limited resources to initiate tuberculosis treatment in children to improve access to care and reduce tuberculosis-related mortality. These algorithms have been included in the operational handbook accompanying the latest WHO guidelines on the management of tuberculosis in children and adolescents. Future prospective evaluation of algorithms, including those developed in this work, is necessary to investigate clinical performance. FUNDING: WHO, US National Institutes of Health.

Research suggest prenatal vaccination against coronavirus disease-19 (COVID-19) is safe. However, previous studies utilized retrospectively collected data or examined late pregnancy vaccinations. We investigated the associations of COVID-19 vaccination throughout pregnancy with delivery and neonatal outcomes. We included 1,794 mother-neonate dyads enrolled in the Generation C Study with known prenatal COVID-19 vaccination status and complete covariate and outcome data. We used multivariable quantile regressions to estimate the effect of prenatal COVID-19 vaccination on birthweight, delivery gestational age, and blood loss at delivery; and Poisson generalized linear models for Caesarean delivery (CD) and Neonatal Intensive Care Unit (NICU) admission. Using the above methods, we estimated effects of trimester of vaccine initiation on these outcomes. In our sample, 13.7% (n = 250) received at least one prenatal dose of any COVID-19 vaccine. Vaccination was not associated with birthweight (β = 12.42 g [-90.5, 114.8]), gestational age (β = 0.2 days [-1.1, 1.5]), blood loss (β = -50.6 ml [-107.0, 5.8]), the risks of CD (RR = 0.8; [0.6, 1.1]) or NICU admission (RR = 0.9 [0.5, 1.7]). Trimester of vaccine initiation was also not associated with these outcomes. Our findings suggest that there is no associated risk between prenatal COVID-19 vaccination and adverse delivery and neonatal outcomes in a cohort sample from NYC.

We sequenced 109 type 2 Sabin-like poliovirus isolates that had been collected from acute flaccid paralysis patients or healthy children in Nigeria. Understanding the genetic makeup of these viruses may contribute to polio eradication efforts.

While risk of fomite transmission of SARS-CoV-2 is considered low, there is limited environmental data within households. This January-April 2021 investigation describes frequency and types of surfaces positive for SARS-CoV-2 by real-time reverse transcription polymerase chain reaction (RT-PCR) among residences with ≥1 SARS-CoV-2 infection, and associations of household characteristics with surface RT-PCR and viable virus positivity. Of 1232 samples from 124 households, 27.8% (n = 342) were RT-PCR positive with nightstands (44.1%) and pillows (40.9%) most frequently positive. SARS-CoV-2 lineage, documented household transmission, greater number of infected persons, shorter interval between illness onset and sampling, total household symptoms, proportion of infected persons ≤12 years old, and persons exhibiting upper respiratory symptoms or diarrhea were associated with more positive surfaces. Viable virus was isolated from 0.2% (n = 3 samples from one household) of all samples. This investigation suggests that while SARS-CoV-2 on surfaces is common, fomite transmission risk in households is low.

BACKGROUND: Households are common places for spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We investigated factors associated with household transmission and acquisition of SARS-CoV-2. METHODS: Households with children age <18 years were enrolled into prospective, longitudinal cohorts and followed from August 2020 to August 2021 in Utah, September 2020 to August 2021 in New York City, and November 2020 to October 2021 in Maryland. Participants self-collected nasal swabs weekly and with onset of acute illness. Swabs were tested for SARS-CoV-2 using reverse transcription polymerase chain reaction. We assessed factors associated with SARS-CoV-2 acquisition using a multilevel logistic regression adjusted for household size and clustering and SARS-CoV-2 transmission using a logistic regression adjusted for household size. RESULTS: Among 2053 people (513 households) enrolled, 180 people (8.8%; in 76 households) tested positive for SARS-CoV-2. Compared with children age <12 years, the odds of acquiring infection were lower for adults age ≥18 years (adjusted odds ratio [aOR], 0.34; 95% CI, 0.14-0.87); however, this may reflect vaccination status, which protected against SARS-CoV-2 acquisition (aOR, 0.17; 95% CI, 0.03-0.91). The odds of onward transmission were similar between symptomatic and asymptomatic primary cases (aOR, 1.00; 95% CI, 0.35-2.93) and did not differ by age (12-17 years vs <12 years: aOR, 1.08; 95% CI, 0.20-5.62; ≥18 years vs <12 years: aOR, 1.70; 95% CI, 0.52-5.83). CONCLUSIONS: Adults had lower odds of acquiring SARS-CoV-2 compared with children, but this association might be influenced by coronavirus disease 2019 (COVID-19) vaccination, which was primarily available for adults and protective against infection. In contrast, all ages, regardless of symptoms and COVID-19 vaccination, had similar odds of transmitting SARS-CoV-2. Our findings underscore the importance of SARS-CoV-2 mitigation measures for persons of all ages.

Enteroviruses can cause human infectious disease. We report 16 near-complete genome sequences of enteroviruses that were isolated through environmental surveillance of wastewater in Guatemala.