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Non-pharmaceutical interventions minimize social contacts, hence the spread of respiratory pathogens such as influenza and SARS-CoV-2. Globally, there is a paucity of social contact data from the workforce. In this study, we quantified two-day contact patterns among USA employees. Contacts were defined as face-to-face conversations, involving physical touch or proximity to another individual and were collected using electronic self-kept diaries. Data were collected over 4 rounds from 2020 to 2021 during the COVID-19 pandemic. Mean (standard deviation) contacts reported by 1456 participants were 2.5 (2.5), 8.2 (7.1), 9.2 (7.1) and 10.1 (9.5) across round 1 (April-June 2020), 2 (November 2020-January 2021), 3 (June-August 2021), and 4 (November-December 2021), respectively. Between round 1 and 2, we report a 3-fold increase in the mean number of contacts reported per participant with no major increases from round 2-4. We then modeled SARS-CoV-2 transmission at home, work, and community settings. The model revealed reduced relative transmission in all settings in round 1. Subsequently, transmission increased at home and in the community but remained exceptionally low in work settings. To accurately parameterize models of infection transmission and control, we need empirical social contact data that capture human mixing behavior across time., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Norovirus is the most common cause of gastroenteritis outbreaks in long-term care facilities (LTCFs) in the United States, causing a high burden of disease in both residents and staff. Understanding how case symptoms and characteristics contribute to norovirus transmission can lead to more informed outbreak control measures in LTCFs. We examined line lists for 107 norovirus outbreaks that took place in LTCFs in five U.S. states from 2015 to 2019. We estimated the individual effective reproduction number, R i , to quantify individual case infectiousness and examined the contribution of vomiting, diarrhea, and being a resident (vs. staff) to case infectiousness. The associations between case characteristics and R i were estimated using a multivariable, log-linear mixed model with inverse variance weighting. We found that cases with vomiting infected 1.28 (95 % CI: 1.11, 1.48) times the number of secondary cases compared to cases without vomiting, and LTCF residents infected 1.31 (95 % CI: 1.15, 1.50) times the number of secondary cases compared to staff. There was no difference in infectiousness between cases with and without diarrhea (1.07; 95 % CI: 0.90, 1.29). This suggests that vomiting, particularly by LTCF residents, was a primary driver of norovirus transmission. These results support control measures that limit exposure to vomitus during norovirus outbreaks in LTCFs., Competing Interests: Declarations of interest BAL reports grants and personal fees from Takeda Pharmaceuticals and personal fees from the World Health Organization, outside the submitted work. YC, CA, and AK report no conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

The response to the COVID-19 pandemic in the U.S prompted abrupt and dramatic changes to social contact patterns. Monitoring changing social behavior is essential to provide reliable input data for mechanistic models of infectious disease, which have been increasingly used to support public health policy to mitigate the impacts of the pandemic. While some studies have reported on changing contact patterns throughout the pandemic, few have reported differences in contact patterns among key demographic groups and none have reported nationally representative estimates. We conducted a national probability survey of US households and collected information on social contact patterns during two time periods: August-December 2020 (before widespread vaccine availability) and March-April 2021 (during national vaccine rollout). Overall, contact rates in Spring 2021 were similar to those in Fall 2020, with most contacts reported at work. Persons identifying as non-White, non-Black, non-Asian, and non-Hispanic reported high numbers of contacts relative to other racial and ethnic groups. Contact rates were highest in those reporting occupations in retail, hospitality and food service, and transportation. Those testing positive for SARS-CoV-2 antibodies reported a higher number of daily contacts than those who were seronegative. Our findings provide evidence for differences in social behavior among demographic groups, highlighting the profound disparities that have become the hallmark of the COVID-19 pandemic., Competing Interests: Declarations of interest No conflicts to report., (Copyright © 2022. Published by Elsevier B.V.)

Purpose: To examine whether declines in the crude U.S. COVID-19 case fatality ratio is due to improved clinical care and/or other factors., Methods: We used multivariable logistic regression, adjusted for age and other individual-level characteristics, to examine associations between report month and mortality among confirmed and probable COVID-19 cases and hospitalized cases in Georgia reported March 2, 2020 to March 31, 2021., Results: Compared to August 2020, mortality risk among cases was lowest in November 2020 (OR = 0.84; 95% CI: 0.78-0.91) and remained lower until March 2021 (OR = 0.86; 95% CI: 0.77-0.95). Among hospitalized cases, mortality risk increased in December 2020 (OR = 1.16, 95% CI: 1.07-1.27) and January 2021 (OR = 1.25; 95% CI: 1.14-1.36), before declining until March 2021 (OR = 0.90, 95% CI: 0.78-1.04)., Conclusions: After adjusting for other factors, including the shift to a younger age distribution of cases, we observed lower mortality risk from November 2020 to March 2021 compared to August 2020 among cases. This suggests that improved clinical management may have contributed to lower mortality risk. Among hospitalized cases, mortality risk increased again in December 2020 and January 2021, but then decreased to a risk similar to that among all cases by March 2021., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: Estimate incidence of and risks for SARS-CoV-2 infection among nursing home staff in the state of Georgia during the 2020-2021 Winter COVID-19 Surge in the United States., Design: Serial survey and serologic testing at 2 time points with 3-month interval exposure assessment., Setting and Participants: Fourteen nursing homes in the state of Georgia; 203 contracted or employed staff members from those 14 participating nursing homes who were seronegative at the first time point and provided a serology specimen at second time point, at which time they reported no COVID-19 vaccination or only very recent vaccination (≤4 weeks)., Methods: Interval infection was defined as seroconversion to antibody presence for both nucleocapsid protein and spike protein. We estimated adjusted odds ratios (aORs) and 95% CIs by job type, using multivariable logistic regression, accounting for community-based risks including interval community incidence and interval change in resident infections per bed., Results: Among 203 eligible staff, 72 (35.5%) had evidence of interval infection. In multivariable analysis among unvaccinated staff, staff SARS-CoV-2 infection-induced seroconversion was significantly higher among nurses and certified nursing assistants accounting for race and interval infection incidence in both the community and facility (aOR 5.3, 95% CI 1.0-28.4). This risk persisted but was attenuated when using the full study cohort including those with very recent vaccination., Conclusions and Implications: Midway through the first year of the pandemic, job type continues to be associated with increased risk for infection despite enhanced infection prevention efforts including routine screening of staff. These results suggest that mitigation strategies prior to vaccination did not eliminate occupational risk for infection and emphasize critical need to maximize vaccine utilization to eliminate excess risk among front-line providers., (Copyright © 2022 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.)

SARS-CoV-2 outbreaks have occurred on several nautical vessels, driven by the high-density contact networks on these ships. Optimal strategies for prevention and control that account for realistic contact networks are needed. We developed a network-based transmission model for SARS-CoV-2 on the Diamond Princess outbreak to characterize transmission dynamics and to estimate the epidemiological impact of outbreak control and prevention measures. This model represented the dynamic multi-layer network structure of passenger-passenger, passenger-crew, and crew-crew contacts, both before and after the large-scale network lockdown imposed on the ship in response to the disease outbreak. Model scenarios evaluated variations in the timing of the network lockdown, reduction in contact intensity within the sub-networks, and diagnosis-based case isolation on outbreak prevention. We found that only extreme restrictions in contact patterns during network lockdown and idealistic clinical response scenarios could avert a major COVID-19 outbreak. Contact network changes associated with adequate outbreak prevention were the restriction of passengers to their cabins, with limited passenger-crew contacts. Clinical response strategies required for outbreak prevention may be infeasible in many cruise settings: early mass screening with an ideal PCR test (100 % sensitivity) and immediate case isolation upon diagnosis. Personal protective equipment (e.g., facemasks) had limited impact in this environment because the majority of transmissions after the ship lockdown occurred between passengers in cabins where masks were not consistently used. Public health restrictions on optional leisure activities like these should be considered until longer-term effective solutions such as a COVID-19 vaccine become widely available., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Competing Interests: EL reports personal fees from Sanofi Pasteur for participation in a global influenza vaccination advisory board, outside the area of work commented on here. BAL and KN were supported by NIH/NIAID R01 AI143875 and NIH/NIGMS R01 GM124280.

In the effort to control SARS-CoV-2 transmission, public health agencies in the United States and globally are aiming to increase population immunity. Immunity through vaccination and acquired following recovery from natural infection are the two means to build up population immunity, with vaccination being the safe pathway. However, measuring the contribution to population immunity from vaccination or natural infection is non-trivial. Historical COVID-19 case counts and vaccine coverage are necessary information but are not sufficient to approximate population immunity. Here, we consider the nuances of measuring each and propose an analytical framework for integrating the necessary data on cumulative vaccinations and natural infections at the state and national level. To guide vaccine roll-out and other aspects of control over the coming months, we recommend analytics that combine vaccine coverage with local (e.g. county-level) history of case reports and adjustment for waning antibodies to establish local estimates of population immunity. To do so, the strategic use of minimally-biased serology surveys integrated with vaccine administration data can improve estimates of the aggregate level of immunity to guide data-driven decisions to re-open safely and prioritize vaccination efforts., (Copyright © 2021 Elsevier Inc. All rights reserved.)

We measured contact patterns using online diaries for 304 employees of 3 U.S. companies working remotely. The median number of daily contacts was 2 (IQR 1-4); majority were conversation (55 %), occurred at home (64 %) and lasted >4 h (38 %). These data are crucial for modeling outbreak control among the workforces., (Copyright © 2021. Published by Elsevier B.V.)

Disease surveillance data are important for monitoring disease burden and occurrence, and for informing a wide range of efforts to improve population health. Surveillance for infectious diseases may be conducted passively, relying on reports from healthcare facilities, or actively, involving surveys of the population at risk. Passive surveillance typically provides wide spatial coverage, but is subject to biases arising from differences in care-seeking behavior, diagnostic practices, and under-reporting. Active surveillance minimizes these biases, but is typically constrained to small areas and subpopulations due to resource limitations. Methods based on linkage of individual records between passive and active surveillance datasets provide a means to estimate and correct for the biases of each system, leveraging the size and coverage of passive surveillance and the quality of data in active surveillance. We develop a spatial Bayesian hierarchical model for bias-correcting data from both systems to yield an improved estimate of disease measures after adjusting for under-ascertainment. We apply the framework to data from a passive and an active surveillance system for pulmonary tuberculosis (PTB) in Sichuan, China, and estimate the average sensitivity of the active surveillance system at 70% (95% credible interval: 62%, 78%), and the passive system at 30% (95% CI: 24%, 35%). Passive surveillance sensitivity exhibited considerable spatial variability, and was positively associated with a site's gross domestic product per capita. Bias-corrected estimates of county-level PTB prevalence in the province in 2010 identified regions in the southeast with the highest PTB burden, yielding different geographic priorities than previous reports., (Copyright © 2020. Published by Elsevier Ltd.)

Background: To accurately assess micronutrient status, it is necessary to characterize the effects of inflammation and the acute-phase response on nutrient biomarkers., Objective: Within a norovirus human challenge study, we aimed to model the inflammatory response of C-reactive protein (CRP) and α-1-acid glycoprotein (AGP) by infection status, model kinetics of micronutrient biomarkers by inflammation status, and evaluate associations between inflammation and micronutrient biomarkers from 0 to 35 d post-norovirus exposure., Methods: Fifty-two healthy adults were enrolled into challenge studies in a hospital setting and followed longitudinally; all were exposed to norovirus, half were infected. Post hoc analysis of inflammatory and nutritional biomarkers was performed. Subjects were stratified by inflammation resulting from norovirus exposure. Smoothed regression models analyzed the kinetics of CRP and AGP by infection status, and nutritional biomarkers by inflammation. Linear mixed-effects models were used to analyze the independent relations between CRP, AGP, and biomarkers for iron, vitamin A, vitamin D, vitamin B-12, and folate from 0 to 35 d post-norovirus exposure., Results: Norovirus-infected subjects had median (IQR) peak concentrations for CRP [16.0 (7.9-29.5) mg/L] and AGP [0.9 (0.8-1.2) g/L] on day 3 and day 4 postexposure, respectively. Nutritional biomarkers that differed (P < 0.05) from baseline within the inflamed group were ferritin (elevated day 3), hepcidin (elevated days 2, 3), serum iron (depressed days 2-4), transferrin saturation (depressed days 2-4), and retinol (depressed days 3, 4, and 7). Nutritional biomarker concentrations did not differ over time within the uninflamed group. In mixed models, CRP was associated with ferritin (positive) and serum iron and retinol (negative, P < 0.05)., Conclusion: Using an experimental infectious challenge model in healthy adults, norovirus infection elicited a time-limited inflammatory response associated with altered serum concentrations of certain iron and vitamin A biomarkers, confirming the need to consider adjustments of these biomarkers to account for inflammation when assessing nutritional status. These trials were registered at clinicaltrials.gov as NCT00313404 and NCT00674336., (Copyright © American Society for Nutrition 2019.)

Background: Noroviruses are the leading cause of acute gastroenteritis and foodborne diarrheal disease in the United States. Norovirus vaccine development has progressed in recent years, but critical questions remain regarding which age groups should be vaccinated to maximize population impact., Methods: We developed a deterministic, age-structured compartmental model of norovirus transmission and immunity in the U.S., Population: The model was fit to age-specific monthly U.S. hospitalizations between 1996 and 2007. We simulated mass immunization of both pediatric and elderly populations assuming realistic coverages of 90% and 65%, respectively. We considered two mechanism of vaccine action, resulting in lower vaccine efficacy (lVE) between 22% and 43% and higher VE (hVE) of 50%., Results: Pediatric vaccination was predicted to avert 33% (95% CI: 27%, 40%) and 60% (95% CI: 49%, 71%) of norovirus episodes among children under five years for lVE and hVE, respectively. Vaccinating the elderly averted 17% (95% CI: 12%, 20%) and 38% (95% CI: 34%, 42%) of cases in 65+ year olds for lVE and hVE, respectively. At a population level, pediatric vaccination was predicted to avert 18-21 times more cases and twice as many deaths per vaccinee compared to elderly vaccination., Conclusions: The potential benefits are likely greater for a pediatric program, both via direct protection of vaccinated children and indirect protection of unvaccinated individuals, including adults and the elderly. These findings argue for a clinical development plan that will deliver a vaccine with a safety and efficacy profile suitable for use in children., Competing Interests: none, (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)

Human norovirus (NoV) is now recognized as one of the most important causative agents of gastroenteritis in all age groups worldwide. During the course of NoV infection, symptoms are usually mild and disappear within 48 h after onset. The incidence of NoV infection is high, with hundreds of cases per 10 000 of the population, although the number of infections is still underestimated. Epidemiological surveys conducted in Europe and North America have shown that NoV infections constitute a major disease burden, especially for young children and the elderly, in whom NoV infection leads to high rates of hospitalization and mortality. NoV infections are also of concern in hospitals, where viral infections can be persistent in immunocompromised patients. Although the cost of NoV infection in the hospital community has not yet been clearly established, it appears that NoV infections could cost hundreds of thousands of euros in terms of unit closure, and NoV-related sickness in patients and health workers. Besides their clinical burden, NoVs, as foodborne pathogens, also cause to millions of dollars of losses for the healthcare system and the food industry. Recent estimates in the USA showed that, annually, NoV illness cost $2 billion and led to a loss of approximately 5000 quality-adjusted life-years, making NoV one of the top five pathogens causing enteric illnesses. The highest cost among 14 foodborne pathogens is also attributed to human NoV in The Netherlands. This accumulation of evidence underlines the enormous impact of NoV on populations., (© 2014 The Authors Clinical Microbiology and Infection © 2014 European Society of Clinical Microbiology and Infectious Diseases.)

Infectious disease often occurs in small, independent outbreaks in populations with varying characteristics. Each outbreak by itself may provide too little information for accurate estimation of epidemic model parameters. Here we show that using standard stochastic epidemic models for each outbreak and allowing parameters to vary between outbreaks according to a linear predictor leads to a generalized linear model that accurately estimates parameters from many small and diverse outbreaks. By estimating initial growth rates in addition to transmission rates, we are able to characterize variation in numbers of initially susceptible individuals or contact patterns between outbreaks. With simulation, we find that the estimates are fairly robust to the data being collected at discrete intervals and imputation of about half of all infectious periods. We apply the method by fitting data from 75 norovirus outbreaks in health-care settings. Our baseline regression estimates are 0.0037 transmissions per infective-susceptible day, an initial growth rate of 0.27 transmissions per infective day, and a symptomatic period of 3.35 days. Outbreaks in long-term-care facilities had significantly higher transmission and initial growth rates than outbreaks in hospitals., (Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.)

Rotavirus causes one-third to one-half of severe diarrheal disease in children under the age of five years worldwide. In 2006 two rotavirus vaccines became available and, in the intervening years, approximately thirty countries have introduced them into their immunization programs, primarily in high-income and middle-income settings. Major reductions in rotavirus hospitalizations have been observed in a number of these locations, and in select countries, there have been impacts on gastroenteritis mortality associated with rotavirus vaccine introduction. In addition to these direct health benefits, reduced gastroenteritis risk has been documented in unvaccinated groups, including older children and adults, suggesting indirect benefits (i.e. herd immunity). In this paper, we summarize what has been learned from programs studying post-licensure vaccine effectiveness, impact on health-care utilization and death, safety issues (namely, intussception and the detection of adventitious viruses) and the potential selective pressure of vaccination on the diversity of rotavirus genotypes., (Published by Elsevier B.V.)