We examined the association between influenza vaccination policies at acute care hospitals and influenza vaccination coverage among healthcare personnel for the 2021-22 influenza season. Mandatory vaccination and masking for unvaccinated personnel were associated with increased odds of vaccination. Hospital employees had higher vaccination coverage than licensed independent practitioners.

In recent years, there has been increased attention on the importance of healthcare environmental cleaning, including the need to professionalize and support the workforce responsible for performing cleaning. Global agendas and strategies on infection prevention and control (IPC) and water, sanitation and hygiene highlight the need for improvements to this sector, particularly in resource-limited healthcare facilities in low- and middle-income countries. Correspondingly, several resources have been developed that aim to (1) improve professional training of cleaners and (2) improve implementation of best practices in resource-limited settings. This commentary seeks to provide insight into the barriers and facilitators to implementing these resources, drawing on the practical experience from two initiatives across four countries from 2018 through 2023. Several common barriers were identified across the diverse settings, including (1) low empowerment and status of the workforce, (2) low pay, inadequate staff time for the high workload needed to achieve best practices and high turnover of staff, and (3) a lack of connection and integration of environmental cleaning with IPC and patient safety efforts at the participating hospitals. Despite barriers, local teams identified effective mitigation measures. While considerable time and effort will be needed to truly overcome these barriers, there are opportunities to build upon attention and momentum on this topic and IPC initiatives in resource-limited settings in low- and middle-income countries. We propose several broader actions, all of which require local leadership and context-specific approaches.

During biological invasion process, species encounter new environments and partially escape some ecological constraints they faced in their native range, while they face new ones. The Asian tiger mosquito Aedes albopictus is one of the most iconic invasive species introduced in every inhabited continent due to international trade. It has also been shown to be infected by a prevalent yet disregarded microbial entomoparasite Ascogregarina taiwanensis. In this study, we aimed at deciphering the factors that shape the global dynamics of A. taiwanensis infection in natural A. albopictus populations. We showed that A. albopictus populations are highly colonized by several parasite genotypes but recently introduced ones are escaping it. We further performed experiments based on the invasion process to explain such pattern. To that end, we hypothesized that (i) mosquito passive dispersal (i.e. human-aided egg transportation) may affect the parasite infectiveness, (ii) founder effects (i.e. population establishment by a small number of mosquitoes) may influence the parasite dynamics, and (iii) unparasitized mosquitoes are more prompt to found new populations through active flight dispersal. The two first hypotheses were supported as we showed that parasite infection decreases over time when dry eggs are stored and that experimental increase in mosquitoes' density improves the parasite horizontal transmission to larvae. Surprisingly, parasitized mosquitoes tend to be more active than their unparasitized relatives. Finally, this study highlights the importance of global trade as a driver of biological invasion of the most invasive arthropod vector species.

AIMS: This study aimed to compare the heat inactivation kinetics of viable human norovirus with the surrogate, MS2 bacteriophage as well as assess the decay of the RNA signal. METHODS AND RESULTS: Human intestinal enteroids (HIEs) were used to analyze the heat inactivation kinetics of viable human norovirus compared to the surrogate MS2 bacteriophage, which was cultured using a plaque assay. Norovirus decay rates were 0.22 min-1, 0.68 min-1, and 1.11 min-1 for 50°C, 60°C, and 70°C, respectively, and MS2 bacteriophage decay rates were 0.0065 min-1, 0.045 min-1, and 0.16 min-1 for 50°C, 60°C, and 70°C, respectively. Norovirus had significantly higher decay rates than MS2 bacteriophage at all tested temperatures (P = 0.002-0.007). No decrease of RNA titers as measured by reverse transcription-PCR for both human norovirus and MS2 bacteriophage over time was observed, indicating molecular methods do not accurately depict viable human norovirus after heat inactivation and treatment efficiency is underestimated. CONCLUSIONS: Overall, our data demonstrates that MS2 bacteriophage is a conservative surrogate to measure heat inactivation and potentially overestimates the infectious risk of norovirus. Furthermore, this study corroborates that measuring viral RNA titers, as evaluated by PCR methods, does not correlate with the persistence of viable norovirus under heat inactivation.

The simultaneous circulation of seasonal influenza virus and SARS-CoV-2 variants will likely pose unique challenges to public health during the future influenza seasons. Persons who are undergoing treatment in healthcare facilities may be particularly at risk. It is important for healthcare personnel to protect themselves and patients by receiving vaccines. The purpose of this study is to assess coverage of the seasonal influenza vaccine and COVID-19 monovalent booster among healthcare personnel working at acute care hospitals in the United States during the 2021-22 influenza season and to examine the demographic and facility characteristics associated with coverage. A total of 3260 acute care hospitals with over 7 million healthcare personnel reported vaccination data to National Healthcare Safety Network (NHSN) during the 2021-22 influenza season. Two separate negative binomial mixed models were developed to explore the factors associated with seasonal influenza coverage and COVID-19 monovalent booster coverage. At the end of the 2021-2022 influenza season, the overall pooled mean seasonal influenza coverage was 80.3%, and the pooled mean COVID-19 booster coverage was 39.5%. Several demographic and facility-level factors, such as employee type, facility ownership, and geographic region, were significantly associated with vaccination against influenza and COVID-19 among healthcare personnel working in acute care hospitals. Our findings highlight the need to increase the uptake of vaccination among healthcare personnel, particularly non-employees, those working in for-profit and non-medical school-affiliated facilities, and those residing in the South.

The emergence and rapid worldwide spread of SARS-CoV-2 has accelerated research and development for controlling the pandemic. A multi-coronavirus protein microarray was created containing full-length proteins, overlapping protein fragments of varying lengths and peptide libraries from SARS-CoV-2 and four other human coronaviruses. Sera from confirmed COVID-19 patients as well as unexposed individuals were applied to multi-coronavirus arrays to identify specific antibody reactivity. High level IgG, IgM and IgA reactivity to structural proteins S, M and N, as well as accessory proteins, of SARS-CoV-2 were observed that was specific to COVID-19 patients. Overlapping 100, 50 and 30 amino acid fragments of SARS-CoV-2 proteins identified antigenic regions. Numerous proteins of SARS-CoV, MERS-CoV and the endemic human coronaviruses, HCoV-NL63 and HCoV-OC43 were also more reactive with IgG, IgM and IgA in COVID-19 patient sera than in unexposed control sera, providing further evidence of immunologic cross-reactivity between these viruses. The multi-coronavirus protein microarray is a useful tool for mapping antibody reactivity in COVID-19 patients.Competing Interest StatementDavid Camerini, Arlo Z. Randall, Amit Oberai, Christopher Hung, Joshua Edgar, Adam Shandling, Vu Huynh, Andy A. Teng, Gary Hermanson, Jozelyn V. Pablo, Xiaowu Liang, Angela Yee and Joseph J. Campo are employees of Antigen Discovery Inc. In addition, Xiaowu Liang and Angela Yee have an equity interest in Antigen Discovery Inc. The other authors declare non competing interests.Funding StatementNo external funding was used in this study.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:This study was approved by the Mayo Clinic Human Subjects Institutional Review Board and the Centers for Disease Control and Prevention Human Subjects Office.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.YesAll data are freely available.

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& 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. & Charlene Zalesky, and Claudia & 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 & 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, & 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

Human-aided invasion of alien species across the world sometimes leads to economic, health or environmental burdens. During invasion process, species encounter new environments and partially escape some ecological constrains they faced in their native range, while they face new ones. The Asian tiger mosquito Aedes albopictus is one of the most iconic invasive species that was introduced in every inhabited continent over a short period of time due to international trade. It has also been shown to be infected by a prevalent and yet disregarded gregarine entomoparasite Ascogregarina taiwanensis. In this study, we aimed at deciphering the global dynamics of As. taiwanensis infection in natural Ae. albopictus populations and we further explored factors shaping its distribution. We showed that Ae. albopictus populations are highly colonized by several As. taiwanesis genotypes but recently introduced ones are escaping the parasite. We further performed experiments to explain such pattern. First, we hypothesized that founder effects (i.e. population establishment by a small number of individuals) may influence the parasite dynamics. This was confirmed since experimental increase in mosquitoes' density improves the parasite horizontal transmission to larvae. Furthermore, Ae. albopictus larvae do not exhibit density dependent prophylaxis to control the parasite meaning that infection is not mitigated when larval density increases. Secondly, we hypothesized that unparasitized mosquitoes were more prompt to found new populations through active flight dispersal. This was, however, unlikely since parasitized mosquitoes tend to be more active than their unparasitized relatives. Finally, we hypothesized that mosquito passive dispersal (i.e. often mediated by human-aided transportation of dried eggs) affects the parasite infectiveness. Our results support this hypothesis since parasite infection decreases over time when dry eggs are stored. This study highlights the importance of global trade on parasitism escape in one of the most invasive vector species on earth. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

Objectives: To compare the effectiveness of a primary COVID-19 vaccine series plus a booster dose with a primary series alone for the prevention of Omicron variant COVID-19 hospitalization. Design(s): Multicenter observational case-control study using the test-negative design to evaluate vaccine effectiveness (VE). Setting(s): Twenty-one hospitals in the United States (US). Participant(s): 3,181 adults hospitalized with an acute respiratory illness between December 26, 2021 and April 30, 2022, a period of SARS-CoV-2 Omicron variant (BA.1, BA.2) predominance. Participants included 1,572 (49%) case-patients with laboratory confirmed COVID-19 and 1,609 (51%) control patients who tested negative for SARS-CoV-2. Median age was 64 years, 48% were female, and 21% were immunocompromised; 798 (25%) were vaccinated with a primary series plus booster, 1,326 (42%) were vaccinated with a primary series alone, and 1,057 (33%) were unvaccinated. Main Outcome Measure(s): VE against COVID-19 hospitalization was calculated for a primary series plus a booster and a primary series alone by comparing the odds of being vaccinated with each of these regimens versus being unvaccinated among cases versus controls. VE analyses were stratified by immune status (immunocompetent; immunocompromised) because the recommended vaccine schedules are different for these groups. The primary analysis evaluated all COVID-19 vaccine types combined and secondary analyses evaluated specific vaccine products. Result(s): Among immunocompetent patients, VE against Omicron COVID-19 hospitalization for a primary series plus one booster of any vaccine product dose was 77% (95% CI: 71-82%), and for a primary series alone was 44% (95% CI: 31-54%) (p<0.001). VE was higher for a boosted regimen than a primary series alone for both mRNA vaccines used in the US (BNT162b2: primary series plus booster VE 80% (95% CI: 73-85%), primary series alone VE 46% (95% CI: 30-58%) [p<0.001]; mRNA-1273: primary series plus booster VE 77% (95% CI: 67-83%), primary series alone VE 47% (95% CI: 30-60%) [p<0.001]). Among immunocompromised patients, VE for a primary series of any vaccine product against Omicron COVID-19 hospitalization was 60% (95% CI: 41-73%). Insufficient sample size has accumulated to calculate effectiveness of boosted regimens for immunocompromised patients. Conclusion(s): Among immunocompetent people, a booster dose of COVID-19 vaccine provided additional benefit beyond a primary vaccine series alone for preventing COVID-19 hospitalization due to the Omicron variant. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.

BACKGROUND: Accurate determination of COVID-19 vaccination status is necessary to produce reliable COVID-19 vaccine effectiveness (VE) estimates. Data comparing differences in COVID-19 VE by vaccination sources (i.e., immunization information systems [IIS], electronic medical records [EMR], and self-report) are limited. We compared the number of mRNA COVID-19 vaccine doses identified by each of these sources to assess agreement as well as differences in VE estimates using vaccination data from each individual source and vaccination data adjudicated from all sources combined. METHODS: Adults aged ≥18 years who were hospitalized with COVID-like illness at 21 hospitals in 18 U.S. states participating in the IVY Network during February 1-August 31, 2022, were enrolled. Numbers of COVID-19 vaccine doses identified by IIS, EMR, and self-report were compared in kappa agreement analyses. Effectiveness of mRNA COVID-19 vaccines against COVID-19-associated hospitalization was estimated using multivariable logistic regression models to compare the odds of COVID-19 vaccination between SARS-CoV-2-positive case-patients and SARS-CoV-2-negative control-patients. VE was estimated using each source of vaccination data separately and all sources combined. RESULTS: A total of 4499 patients were included. Patients with ≥1 mRNA COVID-19 vaccine dose were identified most frequently by self-report (n = 3570, 79 %), followed by IIS (n = 3272, 73 %) and EMR (n = 3057, 68 %). Agreement was highest between IIS and self-report for 4 doses with a kappa of 0.77 (95 % CI = 0.73-0.81). VE point estimates of 3 doses against COVID-19 hospitalization were substantially lower when using vaccination data from EMR only (VE = 31 %, 95 % CI = 16 %-43 %) than when using all sources combined (VE = 53 %, 95 % CI = 41 %-62%). CONCLUSION: Vaccination data from EMR only may substantially underestimate COVID-19 VE.

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.

Human norovirus (HuNoV) is an important cause of acute gastroenteritis and can be transmitted by water exposures, but its persistence in water is not well understood. Loss of HuNoV infectivity in surface water was compared with persistence of intact HuNoV capsids and genome segments. Surface water from a freshwater creek was filter-sterilized, inoculated with HuNoV (GII.4) purified from stool, and incubated at 15 or 20 °C. We measured HuNoV infectivity via the human intestinal enteroid system and HuNoV persistence via reverse transcription-quantitative polymerase chain reaction assays without (genome segment persistence) or with (intact viral capsid persistence) enzymatic pretreatment to digest naked RNA. For infectious HuNoV, results ranged from no significant decay to a decay rate constant ("k") of 2.2 day(-1). In one creek water sample, genome damage was likely a dominant inactivation mechanism. In other samples from the same creek, loss of HuNoV infectivity could not be attributed to genome damage or capsid cleavage. The range in k and the difference in the inactivation mechanism observed in water from the same site could not be explained, but variable constituents in the environmental matrix could have contributed. Thus, a single k may be insufficient for modeling virus inactivation in surface waters.

As authorities braced for the arrival of the Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), infrastructure investments and government directives prompted action in central Viet Nam to establish capacity for genomic surveillance sequencing. From 17 November 2021 to 7 January 2022, the Pasteur Institute in Nha Trang sequenced 162 specimens from 98 150 confirmed SARS-CoV-2 cases in the region collected from 8 November to 31 December 2021. Of these, all 127 domestic cases were identified as the B.1.617.2 (Delta) variant, whereas 92% (32/35) of imported cases were identified as the B.1.1.529 (Omicron) variant, all among international flight passengers. Patients were successfully isolated, enabling health-care workers to prepare for additional cases. Most (78%) of the 32 Omicron cases were fully vaccinated, suggesting continued importance of public health and social measures to control the spread of new variants.

Human noroviruses are one of the leading causes of acute gastroenteritis worldwide. Based on quantitative microbial risk assessments, norovirus contributes the greatest infectious risk of any pathogen from exposure to sewage-contaminated water; however, these estimates have been based upon molecular (i.e., RNA-based) data as human norovirus has remained largely unculturable in the laboratory. Current approaches to assess the environmental fate of noroviruses rely on the use of culturable surrogate viruses and molecular methods. Human intestinal enteroids (HIEs) are an emerging cell culture system capable of amplifying viable norovirus. Here, we applied the HIE assay to assess both viable norovirus and norovirus RNA persistence in surface, tap, and deionized water microcosms. Viable norovirus decreased to below the detection limit in tap and deionized water microcosms and was measured in a single replicate in the surface water microcosm at study conclusion (28 days). Conversely, the norovirus RNA signal remained constant over the duration of the study, even when viable norovirus was below the limit of detection. Our findings demonstrate the disconnect between current environmental norovirus detection via molecular methods and viability as assessed through the HIE assay. These results imply that molecular norovirus monitoring is not inherently representative of infectious norovirus. © 2022 American Chemical Society.

SignificanceThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.

Outcomes and costs of coronavirus disease (COVID-19) contact tracing are limited. During March-May 2020, we constructed transmission chains from 184 index cases and 1,499 contacts in Salt Lake County, Utah, USA, to assess outcomes and estimate staff time and salaries. We estimated 1,102 staff hours and $29,234 spent investigating index cases and contacts. Among contacts, 374 (25%) had COVID-19; secondary case detection rate was ≈31% among first-generation contacts, ≈16% among second- and third-generation contacts, and ≈12% among fourth-, fifth-, and sixth-generation contacts. At initial interview, 51% (187/370) of contacts were COVID-19-positive; 35% (98/277) became positive during 14-day quarantine. Median time from symptom onset to investigation was 7 days for index cases and 4 days for first-generation contacts. Contact tracing reduced the number of cases between contact generations and time between symptom onset and investigation but required substantial resources. Our findings can help jurisdictions allocate resources for contact tracing.

OBJECTIVE: To determine whether environmental surface contamination with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurred at a provincial hospital in Viet Nam that admitted patients with novel coronavirus disease 2019 (COVID-19) and at the regional reference laboratory responsible for confirmatory testing for SARS-CoV-2 in 2020. METHODS: Environmental samples were collected from patient and staff areas at the hospital and various operational and staff areas at the laboratory. Specimens from frequently touched surfaces in all rooms were collected using a moistened swab rubbed over a 25 cm(2) area for each surface. The swabs were immediately transported to the laboratory for testing by real-time reverse transcription polymerase chain reaction (RT-PCR). Throat specimens were collected from staff at both locations and were also tested for SARS-CoV-2 using real-time RT-PCR. RESULTS: During the sampling period, the laboratory tested 6607 respiratory specimens for SARS-CoV-2 from patients within the region, and the hospital admitted 9 COVID-19 cases. Regular cleaning was conducted at both sites in accordance with infection prevention and control (IPC) practices. All 750 environmental samples (300 laboratory and 450 hospital) and 30 staff specimens were negative for SARS-CoV-2. DISCUSSION: IPC measures at the facilities may have contributed to the negative results from the environmental samples. Other possible explanations include sampling late in a patient's hospital stay when virus load was lower, having insufficient contact time with a surface or using insufficiently moist collection swabs. Further environmental sampling studies of SARS-CoV-2 should consider including testing for the environmental presence of viruses within laboratory settings, targeting the collection of samples to early in the course of a patient's illness and including sampling of confirmed positive control surfaces, while maintaining appropriate biosafety measures.

The rapid worldwide spread of SARS-CoV-2 has accelerated research and development for controlling the COVID-19 pandemic. A multi-coronavirus protein microarray was created containing full-length proteins, overlapping protein fragments of various lengths, and peptide libraries from SARS-CoV-2 and four other human coronaviruses. Sera from confirmed COVID-19 patients as well as unexposed individuals were applied to multicoronavirus arrays to identify specific antibody reactivity. High-level IgG, IgM, and IgA reactivity to structural proteins S, M, and N of SARS-CoV-2, as well as accessory proteins such as ORF3a and ORF7a, were observed that were specific to COVID-19 patients. Antibody reactivity against overlapping 100-, 50-, and 30-amino acid fragments of SARS-CoV-2 proteins was used to identify antigenic regions. Numerous proteins of SARS-CoV, Middle East respiratory syndrome coronavirus (MERS-CoV), and the endemic human coronaviruses HCoV-NL63 and HCoV-OC43 were also more reactive with IgG, IgM, and IgA in COVID-19 patient sera than in unexposed control sera, providing further evidence of immunologic cross-reactivity between these viruses. Whereas unexposed individuals had minimal reactivity against SARS-CoV-2 proteins that poorly correlated with reactivity against HCoV-NL63 and HCoV-OC43 S2 and N proteins, COVID-19 patient sera had higher correlation between SARS-CoV-2 and HCoV responses, suggesting that de novo antibodies against SARS-CoV-2 cross-react with HCoV epitopes. Array responses were compared with validated spike protein-specific IgG enzyme-linked immunosorbent assays (ELISAs), showing agreement between orthologous methods. SARS-CoV-2 microneutralization titers were low in the COVID-19 patient sera but correlated with array responses against S and N proteins. The multi-coronavirus protein microarray is a useful tool for mapping antibody reactivity in COVID-19 patients. IMPORTANCE With novel mutant SARS-CoV-2 variants of concern on the rise, knowledge of immune specificities against SARS-CoV-2 proteins is increasingly important for understanding the impact of structural changes in antibody-reactive protein epitopes on naturally acquired and vaccine-induced immunity, as well as broader topics of cross-reactivity and viral evolution. A multi-coronavirus protein microarray used to map the binding of COVID-19 patient antibodies to SARS-CoV-2 proteins and protein fragments as well as to the proteins of four other coronaviruses that infect humans has shown specific regions of SARS-CoV-2 proteins that are highly reactive with patient antibodies and revealed cross-reactivity of these antibodies with other human coronaviruses. These data and the multi-coronavirus protein microarray tool will help guide further studies of the antibody response to COVID-19 and to vaccination against this worldwide pandemic.

BACKGROUND: Noroviruses are the major cause of acute gastroenteritis (AGE) in people of all ages globally. Standardized genotyping is key for outbreak investigations and surveillance networks. OBJECTIVE: Here we describe the validation of a one-step conventional RT-PCR assay for sequence-based dual typing of GI and GII noroviruses. This polymerase (P) and capsid (C) dual typing assay uses a combination of previously published oligonucleotide primers amplifying a genomic region spanning the 3'-end of ORF1 and 5'end of ORF2 resulting in a 579 bp product for GI and 570 bp product for GII viruses. RESULTS: The limit of detection of the assay ranged from 5 to 50 copies of viral RNA per reaction for GI and GII. To validate the assay, we tested 2,663 noroviruspositive stool samples from outbreaks and sporadic cases of AGE in Bangladesh, Guatemala, Peru, and USA collected between 2010-2019, of which 2,392 (90 %) were genotyped successfully. Most of the known genotypes infecting humans (GI (n = 9) and GII (n = 23)) and P types (GI (n = 15), GII, (n = 20)) could be detected. The remaining 270 samples had low viral load (Ct > 30) by real-time RT-PCR. A panel of 166 samples positive for other enteric viruses (rotavirus, astrovirus, sapovirus, adenovirus type 40/41) tested negative. CONCLUSION: The use of broadly reactive genotyping assays greatly strengthens exchange of standardized genotype data globally to monitor trends in genotype diversity which is important for both the development of vaccines and to measure their impact.

OBJECTIVES: Cause-of-death information, reported by frontline clinicians after a patient's death, is an irreplaceable source of public health data. However, systematic bias in cause-of-death reporting can lead to over- or underestimation of deaths attributable to different causes. New York City consistently reports higher rates of deaths attributable to pneumonia and influenza than many other US cities and the country. We investigated systematic erroneous reporting as a possible explanation for this phenomenon. METHODS: We reviewed all deaths from 2 New York City hospitals during 2013-2014 in which pneumonia or influenza was reported as the underlying cause of death (n = 188), and we examined the association between erroneous reporting and multiple extrinsic factors that may influence cause-of-death reporting (patient demographic characteristics and medical comorbidities, time and hospital location of death, type of medical provider reporting the death, and availability of certain diagnostic information). RESULTS: Pneumonia was erroneously reported as the underlying cause of death in 163 (86.7%) reports. We identified heart disease and dementia as the more likely underlying cause of death in 21% and 17% of erroneously reported deaths attributable to pneumonia, respectively. We found no significant association between erroneous reporting and the multiple extrinsic factors examined. CONCLUSIONS: Our results underscore how erroneous reporting of 1 condition can lead to underreporting of other causes of death. Misapplication or misunderstanding of procedures by medical providers, rather than extrinsic factors influencing the reporting process, are key drivers of erroneous cause-of-death reporting.

Sudden sensorineuronal hearing loss (SNHL) is reported in approximately one-third of survivors of Lassa fever (LF) and remains the most prominent cause of Lassa virus- (LASV) associated morbidity in convalescence. Using a guinea pig model of LF, and incorporating animals from LASV vaccine trials, we investigated viral antigen distribution and histopathology in the ear of infected animals to elucidate the pathogenesis of hearing loss associated with LASV infection. Antigen was detected only in animals that succumbed to disease and was found within structures of the inner ear that are intimately associated with neural detection and/or translation of auditory stimuli and in adjacent vasculature. No inflammation or viral cytopathic changes were observed in the inner ear or surrounding structures in these animals. In contrast, no viral antigen was detected in the ear of surviving animals. However, all survivors that exhibited clinical signs of disease during the course of infection developed perivascular mononuclear inflammation within and adjacent to the ear, indicating an ongoing inflammatory response in these animals that may contribute to hearing loss. These data contribute to the knowledge of LASV pathogenesis in the auditory system, support an immune-mediated process resulting in LASV-associated hearing loss, and demonstrate that vaccination protecting animals from clinical disease can also prevent infection-associated auditory pathology.

Since February 12, 2020, approximately 6.5 million cases of SARS-CoV-2 infection, the cause of coronavirus disease 2019 (COVID-19), and 190,000 SARS-CoV-2-associated deaths have been reported in the United States (1,2). Symptoms associated with SARS-CoV-2 infection are milder in children compared with adults (3). Persons aged <21 years constitute 26% of the U.S. population (4), and this report describes characteristics of U.S. persons in that population who died in association with SARS-CoV-2 infection, as reported by public health jurisdictions. Among 121 SARS-CoV-2-associated deaths reported to CDC among persons aged <21 years in the United States during February 12-July 31, 2020, 63% occurred in males, 10% of decedents were aged <1 year, 20% were aged 1-9 years, 70% were aged 10-20 years, 45% were Hispanic persons, 29% were non-Hispanic Black (Black) persons, and 4% were non-Hispanic American Indian or Alaska Native (AI/AN) persons. Among these 121 decedents, 91 (75%) had an underlying medical condition,* 79 (65%) died after admission to a hospital, and 39 (32%) died at home or in the emergency department (ED).(†) These data show that nearly three quarters of SARS-CoV-2-associated deaths among infants, children, adolescents, and young adults have occurred in persons aged 10-20 years, with a disproportionate percentage among young adults aged 18-20 years and among Hispanics, Blacks, AI/ANs, and persons with underlying medical conditions. Careful monitoring of SARS-CoV-2 infections, deaths, and other severe outcomes among persons aged <21 years remains particularly important as schools reopen in the United States. Ongoing evaluation of effectiveness of prevention and control strategies will also be important to inform public health guidance for schools and parents and other caregivers.

BACKGROUND: In fall 2017, 3 solid organ transplant (SOT) recipients from a common donor developed encephalitis within 1 week of transplantation, prompting suspicion of transplant-transmitted infection. Eastern equine encephalitis virus (EEEV) infection was identified during testing of endomyocardial tissue from the heart recipient. METHODS: We reviewed medical records of the organ donor and transplant recipients and tested serum, whole blood, cerebrospinal fluid, and tissue from the donor and recipients for evidence of EEEV infection by multiple assays. We investigated blood transfusion as a possible source of organ donor infection by testing remaining components and serum specimens from blood donors. We reviewed data from the pretransplant organ donor evaluation and local EEEV surveillance. RESULTS: We found laboratory evidence of recent EEEV infection in all organ recipients and the common donor. Serum collected from the organ donor upon hospital admission tested negative, but subsequent samples obtained prior to organ recovery were positive for EEEV RNA. There was no evidence of EEEV infection among donors of the 8 blood products transfused into the organ donor or in products derived from these donations. Veterinary and mosquito surveillance showed recent EEEV activity in counties nearby the organ donor's county of residence. Neuroinvasive EEEV infection directly contributed to the death of 1 organ recipient and likely contributed to death in another. CONCLUSIONS: Our investigation demonstrated EEEV transmission through SOT. Mosquito-borne transmission of EEEV to the organ donor was the likely source of infection. Clinicians should be aware of EEEV as a cause of transplant-associated encephalitis.

The Camp Fire, California's deadliest wildfire, began November 8, 2018, and was extinguished November 25 (1). Approximately 1,100 evacuees from the fire sought emergency shelter. On November 10, acute gastroenteritis (AGE) was reported in two evacuation shelters; norovirus illness was suspected, because it is commonly detected in shelter-associated AGE outbreaks. Norovirus is highly contagious and resistant to several disinfectants. Butte County Public Health Department (BCPHD), assisted by the California Department of Public Health (CDPH), initiated active surveillance to identify cases, confirm the etiology, and assess shelter infection prevention and control (IPC) practices to guide recommendations. During November 8-30, a total of 292 patients with AGE were identified among nine evacuation shelters; norovirus was detected in 16 of 17 unique patient stool specimens. Shelter IPC assessments revealed gaps in illness surveillance, isolation practices, cleaning, disinfection, and handwashing. CDPH and BCPHD collaborated with partner agencies to implement AGE screening, institute isolation protocols and 24-hour cleaning services, and promote proper hand hygiene. During disasters with limited resources, damaged infrastructure, and involvement of multiple organizations, establishing shelter disease surveillance and IPC is difficult. However, prioritizing effective surveillance and IPC at shelter activation is necessary to prevent, identify, and contain outbreaks.

We report herein a fatal case of acute human orthopneumovirus (formerly respiratory syncytial virus) infection in a captive white-handed gibbon (Hylobates lar). Other members of the housing group had mild respiratory signs. Gross examination revealed bilateral pulmonary congestion and froth in the bronchi. Microscopically, the lungs had lymphocytic, neutrophilic infiltration of the interstitium and alveolar walls. There was necrosis of terminal bronchiolar epithelium and terminal bronchioles, and surrounding alveoli contained necrotic and exfoliated epithelial cells admixed with histiocytes and syncytial cells. Additional lesions included nonsuppurative meningoencephalitis, and epidermal hyperkeratosis and hyperplasia with syncytial cell formation. PCR screening for 12 human respiratory viruses was positive for orthopneumovirus in multiple tissues, including lung, and immunohistochemical staining for human orthopneumovirus detected viral antigen within bronchial epithelial cells. IHC and PCR for measles virus on preserved sections were negative. White-handed gibbons have not been previously reported as hosts for human orthopneumovirus, an important respiratory pathogen of both primates and humans.

Diagnosis and treatment of culture negative endocarditis remains a challenge. This report describes a rare cause of endocarditis in humans, Bartonella vinsonii, identified through next generation sequencing of plasma microbial cell-free DNA with confirmation of cardiac valve tissue infection through immunohistochemical staining and polymerase chain reaction.

BACKGROUND: Infectious disease forecasting aims to predict characteristics of both seasonal epidemics and future pandemics. Accurate and timely infectious disease forecasts could aid public health responses by informing key preparation and mitigation efforts. MAIN BODY: For forecasts to be fully integrated into public health decision-making, federal, state, and local officials must understand how forecasts were made, how to interpret forecasts, and how well the forecasts have performed in the past. Since the 2013-14 influenza season, the Influenza Division at the Centers for Disease Control and Prevention (CDC) has hosted collaborative challenges to forecast the timing, intensity, and short-term trajectory of influenza-like illness in the United States. Additional efforts to advance forecasting science have included influenza initiatives focused on state-level and hospitalization forecasts, as well as other infectious diseases. Using CDC influenza forecasting challenges as an example, this paper provides an overview of infectious disease forecasting; applications of forecasting to public health; and current work to develop best practices for forecast methodology, applications, and communication. CONCLUSIONS: These efforts, along with other infectious disease forecasting initiatives, can foster the continued advancement of forecasting science.

We report the nearly complete genome sequence of a human enterovirus, a strain of echovirus 30, obtained from a cerebrospinal fluid specimen from a teenaged patient with aseptic meningitis in September 2017.

As influenza viruses continue to jump species barriers to cause human infection, assessments of disease severity and viral replication kinetics in vivo provide crucial information for public health professionals. The ferret model is a valuable resource for evaluating influenza virus pathogenicity; thus, understanding the most effective sample collection and usage techniques, as well as the full spectrum of attainable data following experimental inoculation in this species, is paramount. This is especially true for scheduled necropsy of virus-infected ferrets, a standard component in evaluation of influenza virus pathogenicity, as necropsy findings can provide important information regarding disease severity and pathogenicity that is not otherwise available from the live animal. In this review, we describe the range of influenza viruses assessed in ferrets, the measures of experimental disease severity in this model, and optimal sample collection during necropsy of virus-infected ferrets. Collectively, this information is critical for assessing systemic involvement following influenza virus infection in mammals.