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Hospital-based transmission had a dominant role in Middle East respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus (SARS-CoV) epidemics1, 2, but large-scale studies of its role in the SARS-CoV-2 pandemic are lacking. Such transmission risks spreading the virus to the most vulnerable individuals and can have wider-scale impacts through hospital–community interactions. Using data from acute hospitals in England, we quantify within-hospital transmission, evaluate likely pathways of spread and factors associated with heightened transmission risk, and explore the wider dynamical consequences. We estimate that between June 2020 and March 2021 between 95,000 and 167,000 inpatients acquired SARS-CoV-2 in hospitals (1% to 2% of all hospital admissions in this period). Analysis of time series data provided evidence that patients who themselves acquired SARS-CoV-2 infection in hospital were the main sources of transmission to other patients. Increased transmission to inpatients was associated with hospitals having fewer single rooms and lower heated volume per bed. Moreover, we show that reducing hospital transmission could substantially enhance the efficiency of punctuated lockdown measures in suppressing community transmission. These findings reveal the previously unrecognized scale of hospital transmission, have direct implications for targeting of hospital control measures and highlight the need to design hospitals better equipped to limit the transmission of future high-consequence pathogens.

Many infection prevention and control (IPC) interventions have been adopted by hospitals to limit nosocomial transmission of SARS-CoV-2. The aim of this systematic review is to identify evidence on the effectiveness of these interventions. We conducted a literature search of five databases (OVID MEDLINE, Embase, CENTRAL, COVID-19 Portfolio (pre-print), Web of Science). SWIFT ActiveScreener software was used to screen English titles and abstracts published between 1st January 2020 and 6th April 2021. Intervention studies, defined by Cochrane Effective Practice and Organisation of Care, that evaluated IPC interventions with an outcome of SARS-CoV-2 infection in either patients or healthcare workers were included. Personal protective equipment (PPE) was excluded as this intervention had been previously reviewed. Risks of bias were assessed using the Cochrane tool for randomised trials (RoB2) and non-randomized studies of interventions (ROBINS-I). From 23,156 screened articles, we identified seven articles that met the inclusion criteria, all of which evaluated interventions to prevent infections in healthcare workers and the majority of which were focused on effectiveness of prophylaxes. Due to heterogeneity in interventions, we did not conduct a meta-analysis. All agents used for prophylaxes have little to no evidence of effectiveness against SARS-CoV-2 infections. We did not find any studies evaluating the effectiveness of interventions including but not limited to screening, isolation and improved ventilation. There is limited evidence from interventional studies, excluding PPE, evaluating IPC measures for SARS-CoV-2. This review calls for urgent action to implement such studies to inform policies to protect our most vulnerable populations and healthcare workers. © 2021 The Authors

Bacterial antibiotic resistance is an important global health threat and the interfaces of antibiotic resistance between humans, animals and the environment are complex. We aimed to determine the associations and overtime trends of antibiotic resistance between humans, animals and water sources from the same area and time and estimate attribution of the other sources to cases of human antibiotic resistance. A total of 125 children (aged 1–3 years old) had stool samples analysed for antibiotic-resistant bacteria at seven time points over two years, with simultaneous collection of samples of animal stools and water sources in a rural Indian community. Newey–West regression models were used to calculate temporal associations, the source with the most statistically significant relationships was household drinking water. This is supported by use of SourceR attribution modelling, that estimated the mean attribution of cases of antibiotic resistance in the children from animals, household drinking water and wastewater, at each time point and location, to be 12.6% (95% CI 4.4–20.9%), 12.1% (CI 3.4–20.7%) and 10.3% (CI 3.2–17.3%) respectively. This underlines the importance of the ‘one health’ concept and requires further research. Also, most of the significant trends over time were negative, suggesting a possible generalised improvement locally.

Background: Children are important in community-level influenza transmission. School-based monitoring may inform influenza surveillance. Methods: We used reported weekly confirmed influenza in Allegheny County during the 2007 and 2010-2015 influenza seasons using Pennsylvania's Allegheny County Health Department all-age influenza cases from health facilities, and all-cause and influenza-like illness (ILI)-specific absences from nine county school districts. Negative binomial regression predicted influenza cases using all-cause and illness-specific absence rates, calendar week, average weekly temperature, and relative humidity, using four cross-validations. Results: School districts reported 2 184 220 all-cause absences (2010-2015). Three one-season studies reported 19 577 all-cause and 3012 ILI-related absences (2007, 2012, 2015). Over seven seasons, 11 946 confirmed influenza cases were reported. Absences improved seasonal model fits and predictions. Multivariate models using elementary school absences outperformed middle and high school models (relative mean absolute error (relMAE) = 0.94, 0.98, 0.99). K-5 grade-specific absence models had lowest mean absolute errors (MAE) in cross-validations. ILI-specific absences performed marginally better than all-cause absences in two years, adjusting for other covariates, but markedly worse one year. Conclusions: Our findings suggest seasonal models including K-5th grade absences predict all-age-confirmed influenza and may serve as a useful surveillance tool.

Background: Mathematical models of respiratory syncytial virus (RSV) transmission can help describe seasonal epidemics and assess the impact of potential vaccines and immunoprophylaxis with monoclonal antibodies (mAb). Methods: We developed a deterministic, compartmental model for RSV transmission, which was fitted to population-based RSV hospital surveillance data from Auckland, New Zealand. The model simulated the introduction of either a maternal vaccine or a seasonal mAb among infants aged less than 6 months and estimated the reduction in RSV hospitalizations for a range of effectiveness and coverage values. Results: The model accurately reproduced the annual seasonality of RSV epidemics in Auckland. We found that a maternal vaccine with effectiveness of 30–40% in the first 90 days and 15–20% for the next 90 days could reduce RSV hospitalizations by 18–24% in children younger than 3 months, by 11–14% in children aged 3–5 months, and by 2–3% in children aged 6–23 months. A seasonal infant mAb with 40–60% effectiveness for 150 days could reduce RSV hospitalizations by 30–43%, 34–48% and by 14–21% in children aged 0–2 months, 3–5 months and 6–23 months, respectively. Conclusions: Our results suggest that either a maternal RSV vaccine or mAb would effectively reduce RSV hospitalization disease burden in New Zealand. Overall, a seasonal mAb resulted in a larger disease prevention impact than a maternal vaccine.

Many countries have banned groups and gatherings as part of their response to the pandemic caused by the coronavirus, SARS-CoV-2. Although there are outbreak reports involving mass gatherings, the contribution to overall transmission is unknown. We used data from a survey of social contact behaviour that specifically asked about contact with groups to estimate the population attributable fraction (PAF) due to groups as the relative change in the basic reproduction number when groups are prevented. Groups of 50+ individuals accounted for 0.5% of reported contact events, and we estimate that the PAF due to groups of 50+ people is 5.4% (95% confidence interval 1.4%, 11.5%). The PAF due to groups of 20+ people is 18.9% (12.7%, 25.7%) and the PAF due to groups of 10+ is 25.2% (19.4%, 31.4%). Under normal circumstances with pre-COVID-19 contact patterns, large groups of individuals have a relatively small epidemiological impact; small- and medium-sized groups between 10 and 50 people have a larger impact on an epidemic. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'. © 2021 The Authors.

Objective To establish whether there is any change in mortality from infection with a new variant of SARS-CoV-2, designated a variant of concern (VOC-202012/1) in December 2020, compared with circulating SARS-CoV-2 variants. Design Matched cohort study. Setting Community based (pillar 2) covid-19 testing centres in the UK using the TaqPath assay (a proxy measure of VOC-202012/1 infection). Participants 54 906 matched pairs of participants who tested positive for SARS-CoV-2 in pillar 2 between 1 October 2020 and 29 January 2021, followed-up until 12 February 2021. Participants were matched on age, sex, ethnicity, index of multiple deprivation, lower tier local authority region, and sample date of positive specimens, and differed only by detectability of the spike protein gene using the TaqPath assay. Main outcome measure Death within 28 days of the first positive SARS-CoV-2 test result. Results The mortality hazard ratio associated with infection with VOC-202012/1 compared with infection with previously circulating variants was 1.64 (95% confidence interval 1.32 to 2.04) in patients who tested positive for covid-19 in the community. In this comparatively low risk group, this represents an increase in deaths from 2.5 to 4.1 per 1000 detected cases. Conclusions The probability that the risk of mortality is increased by infection with VOC-202012/01 is high. If this finding is generalisable to other populations, infection with VOC-202012/1 has the potential to cause substantial additional mortality compared with previously circulating variants. Healthcare capacity planning and national and international control policies are all impacted by this finding, with increased mortality lending weight to the argument that further coordinated and stringent measures are justified to reduce deaths from SARS-CoV-2. ©

Background: Information on the etiology and age-specific burden of respiratory viral infections among school-aged children remains limited. Though school aged children are often recognized as driving the transmission of influenza as well as other respiratory viruses, little detailed information is available on the distribution of respiratory infections among children of different ages within this group. Factors other than age including gender and time spent in school may also be important in determining risk of infection but have been little studied in this age group. Methods: We conducted a cohort study to determine the etiology of influenza like illness (ILI) among 2519 K–12 students during the 2012–13 influenza season. We obtained nasal swabs from students with ILI-related absences. Generalized linear mixed-effect regressions determined associations of outcomes, including ILI and laboratory-confirmed respiratory virus infection, with school grade and other covariates. Results: Overall, 459 swabs were obtained from 552 ILI–related absences. Respiratory viruses were found in 292 (63.6%) samples. Influenza was found in 189 (41.2%) samples. With influenza B found in 134 (70.9%). Rates of influenza B were significantly higher in grades 1 (10.1, 95% CI 6.8–14.4%), 2 (9.7, 6.6–13.6%), 3 (9.3, 6.3–13.2%), and 4 (9.9, 6.8–13.8%) than in kindergarteners (3.2, 1.5–6.0%). After accounting for grade, sex and self-reported vaccination status, influenza B infection risk was lower among kindergarteners in half-day programs compared to kindergarteners in full-day programs (OR = 0.19; 95% CI 0.08–0.45). Conclusions: ILI and influenza infection is concentrated in younger schoolchildren. Reduced infection by respiratory viruses is associated with a truncated school day for kindergarteners but this finding requires further investigation in other grades and populations.

For most pathogens, transmission is driven by interactions between the behaviours of infectious individuals, the behaviours of the wider population, the local environment, and immunity. Phylogeographic approaches are currently unable to disentangle the relative effects of these competing factors. We develop a spatiotemporally structured phylogenetic framework that addresses these limitations by considering individual transmission events, reconstructed across spatial scales. We apply it to geocoded dengue virus sequences from Thailand (N = 726 over 18 years). We find infected individuals spend 96% of their time in their home community compared to 76% for the susceptible population (mainly children) and 42% for adults. Dynamic pockets of local immunity make transmission more likely in places with high heterotypic immunity and less likely where high homotypic immunity exists. Age-dependent mixing of individuals and vector distributions are not important in determining spread. This approach provides previously unknown insights into one of the most complex disease systems known and will be applicable to other pathogens.

Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39-4.13), indicating that 58-76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6-7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090-33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

In the absence of a vaccine, severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) transmission has been controlled by preventing person-to-person interactions via social distancing measures. In order to re-open parts of society, policy-makers need to consider how combinations of measures will affect transmission and understand the trade-offs between them. We use age-specific social contact data, together with epidemiological data, to quantify the components of the COVID-19 reproduction number. We estimate the impact of social distancing policies on the reproduction number by turning contacts on and off based on context and age. We focus on the impact of re-opening schools against a background of wider social distancing measures. We demonstrate that pre-collected social contact data can be used to provide a time-varying estimate of the reproduction number (R). We find that following lockdown (when R = 0.7, 95% CI 0.6, 0.8), opening primary schools has a modest impact on transmission (R = 0.89, 95% CI 0.82-0.97) as long as other social interactions are not increased. Opening secondary and primary schools is predicted to have a larger impact (R = 1.22, 95% CI 1.02-1.53). Contact tracing and COVID security can be used to mitigate the impact of increased social mixing to some extent; however, social distancing measures are still required to control transmission. Our approach has been widely used by policy-makers to project the impact of social distancing measures and assess the trade-offs between them. Effective social distancing, contact tracing and COVID security are required if all age groups are to return to school while controlling transmission. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission. © 2021, The Author(s).

Background: Influenza infection is often measured by a fourfold antibody titer increase over an influenza season (ie seroconversion). However, this approach may fail when influenza seasons are less distinct as it does not account for transient effects from recent infections. Here, we present a method to determine seroconversion for non-paired sera, adjusting for changes in individuals’ antibody titers to influenza due to the transient impact of recent exposures, varied sampling times, and laboratory processes. Methods: We applied our method using data for five H3N2 strains collected from 942 individuals, aged 2-90 years, during the first two study visits of the Fluscape cohort study (2009-2012) in Guangzhou, China. Results: After adjustment, apparent seroconversion rates for non-circulating strains decreased while we observed a 20% increase in seroconversion rates to recently circulating strains. When examining seroconversion to the most recently circulating strain (A/Brisbane/20/2007) in our study, participants aged under 18, and over 64 had the highest seroconversion rates compared to other age groups. Conclusions: Our results highlight the need for improved methods when using antibody titers as an endpoint in settings where there is no clear influenza “off” season. Methods, like those presented here, that use titers from circulating and non-circulating strains may be key.

Some directly transmitted human pathogens, such as influenza and measles, generate sustained exponential growth in incidence and have a high peak incidence consistent with the rapid depletion of susceptible individuals. Many do not. While a prolonged exponential phase typically arises in traditional disease-dynamic models, current quantitative descriptions of nonstandard epidemic profiles are either abstract, phenomenological, or rely on highly skewed offspring distributions in network models. Here, we create large socio-spatial networks to represent contact behavior using human population-density data, a previously developed fitting algorithm, and gravity-like mobility kernels. We define a basic reproductive number [Formula: see text] for this system, analogous to that used for compartmental models. Controlling for [Formula: see text], we then explore networks with a household-workplace structure in which between-household contacts can be formed with varying degrees of spatial correlation, determined by a single parameter from the gravity-like kernel. By varying this single parameter and simulating epidemic spread, we are able to identify how more frequent local movement can lead to strong spatial correlation and, thus, induce subexponential outbreak dynamics with lower, later epidemic peaks. Also, the ratio of peak height to final size was much smaller when movement was highly spatially correlated. We investigate the topological properties of our networks via a generalized clustering coefficient that extends beyond immediate neighborhoods, identifying very strong correlations between fourth-order clustering and nonstandard epidemic dynamics. Our results motivate the observation of both incidence and socio-spatial human behavior during epidemics that exhibit nonstandard incidence patterns.

Objective To characterise the clinical features of patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United Kingdom during the growth phase of the first wave of this outbreak who were enrolled in the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study, and to explore risk factors associated with mortality in hospital. Design Prospective observational cohort study with rapid data gathering and near real time analysis. Setting 208 acute care hospitals in England, Wales, and Scotland between 6 February and 19 April 2020. A case report form developed by ISARIC and WHO was used to collect clinical data. A minimal follow-up time of two weeks (to 3 May 2020) allowed most patients to complete their hospital admission. Participants 20 133 hospital inpatients with covid-19. Main outcome measures Admission to critical care (high dependency unit or intensive care unit) and mortality in hospital. Results The median age of patients admitted to hospital with covid-19, or with a diagnosis of covid-19 made in hospital, was 73 years (interquartile range 58-82, range 0-104). More men were admitted than women (men 60%, n=12 068; women 40%, n=8065). The median duration of symptoms before admission was 4 days (interquartile range 1-8). The commonest comorbidities were chronic cardiac disease (31%, 5469/17 702), uncomplicated diabetes (21%, 3650/17 599), non-asthmatic chronic pulmonary disease (18%, 3128/17 634), and chronic kidney disease (16%, 2830/17 506); 23% (4161/18 525) had no reported major comorbidity. Overall, 41% (8199/20 133) of patients were discharged alive, 26% (5165/20 133) died, and 34% (6769/20 133) continued to receive care at the reporting date. 17% (3001/18 183) required admission to high dependency or intensive care units; of these, 28% (826/3001) were discharged alive, 32% (958/3001) died, and 41% (1217/3001) continued to re

Introduction: The incidence of severe childhood diarrhoea has fallen substantially following the introduction of rotavirus vaccine in the UK in July 2013. Since children with rotavirus infection may experience febrile and afebrile seizures, we evaluated the impact of rotavirus vaccination on seizure hospitalisations in children in England. Methods: Using data from Hospital Episode Statistics, we employed interrupted time-series analyses to assess changes in monthly hospital admissions for seizures among children aged