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Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational and spatial scales, which even within a single pathogen often span hours to months, cellular to ecosystem levels, and local to pandemic spread. Some pathogens are directly transmitted between individuals of a single species, while others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity, and dynamic human behavior, raise prevention and control from formerly national to international issues. In the face of this complexity, mathematical models offer essential tools for synthesizing information to understand epidemiological patterns, and for developing the quantitative evidence base for decision-making in global health.

Background The SARS-CoV-2 delta (B.1.617.2) variant was first detected in England in March, 2021. It has since rapidly become the predominant lineage, owing to high transmissibility. It is suspected that the delta variant is associated with more severe disease than the previously dominant alpha (B.1.1.7) variant. We aimed to characterise the severity of the delta variant compared with the alpha variant by determining the relative risk of hospital attendance outcomes. Methods This cohort study was done among all patients with COVID-19 in England between March 29 and May 23, 2021, who were identified as being infected with either the alpha or delta SARS-CoV-2 variant through whole-genome sequencing. Individual-level data on these patients were linked to routine health-care datasets on vaccination, emergency care attendance, hospital admission, and mortality (data from Public Health England's Second Generation Surveillance System and COVID-19-associated deaths dataset; the National Immunisation Management System; and NHS Digital Secondary Uses Services and Emergency Care Data Set). The risk for hospital admission and emergency care attendance were compared between patients with sequencing-confirmed delta and alpha variants for the whole cohort and by vaccination status subgroups. Stratified Cox regression was used to adjust for age, sex, ethnicity, deprivation, recent international travel, area of residence, calendar week, and vaccination status. Findings Individual-level data on 43 338 COVID-19-positive patients (8682 with the delta variant, 34 656 with the alpha variant; median age 31 years [IQR 17–43]) were included in our analysis. 196 (2·3%) patients with the delta variant versus 764 (2·2%) patients with the alpha variant were admitted to hospital within 14 days after the specimen was taken (adjusted hazard ratio [HR] 2·26 [95% CI 1·32–3·89]). 498 (5·7%) patients with the delta variant versus 1448 (4·2%) patients with the alpha variant were admitted to hospital or attended emergency care within 14 days (adjusted HR 1·45 [1·08–1·95]). Most patients were unvaccinated (32 078 [74·0%] across both groups). The HRs for vaccinated patients with the delta variant versus the alpha variant (adjusted HR for hospital admission 1·94 [95% CI 0·47–8·05] and for hospital admission or emergency care attendance 1·58 [0·69–3·61]) were similar to the HRs for unvaccinated patients (2·32 [1·29–4·16] and 1·43 [1·04–1·97]; p=0·82 for both) but the precision for the vaccinated subgroup was low. Interpretation This large national study found a higher hospital admission or emergency care attendance risk for patients with COVID-19 infected with the delta variant compared with the alpha variant. Results suggest that outbreaks of the delta variant in unvaccinated populations might lead to a greater burden on health-care services than the alpha variant. Funding Medical Research Council; UK Research and Innovati...

There is good evidence that uptake of opiate substitution therapy and high coverage of needle and syringe programmes can substantially reduce the risk of hepatitis C virus transmission among injecting drug users. Research is now required on whether the scaling-up of intervention exposure can reduce and limit hepatitis C virus prevalence in this population.

Although the major pathogen responsible for bronchiolitis remains RSV, the infection can also be caused by RV and hBoV. Demographic characteristics and clinical severity of the disease may depend on the number of viruses or on the specific virus detected.

The tracking and projection of emerging epidemics is hindered by the disconnect between apparent epidemic dynamics, discernible from noisy and incomplete surveillance data, and the underlying, imperfectly observed, system. Behavior changes compound this, altering both true dynamics and reporting patterns, particularly for diseases with nonspecific symptoms, such as influenza. We disentangle these effects to unravel the hidden dynamics of the 2009 influenza A/H1N1pdm pandemic in London, where surveillance suggests an unusual dominant peak in the summer. We embed an age-structured model into a Bayesian synthesis of multiple evidence sources to reveal substantial changes in contact patterns and health-seeking behavior throughout the epidemic, uncovering two similar infection waves, despite large differences in the reported levels of disease. We show how this approach, which allows for real-time learning about model parameters as the epidemic progresses, is also able to provide a sequence of nested projections that are capable of accurately reflecting the epidemic evolution.Bayesian statistics | real-time modeling | general practice consultation data | infectious disease | seroepidemiology A n emerging epidemic engenders an increased demand upon health services. Resolving the extent to which this is due to high levels of disease transmission as opposed to a heightened public sensitivity is essential for determining the appropriate public health response.This was especially crucial when estimating the course of the 2009 influenza A/H1N1pdm outbreak in England, where, unusually, the pandemic resulted in a summer peak in rates of consultation at general practices (GPs) for influenza-like illness (ILI). This is clearly demonstrated by data from the return service of the Royal College of General Practitioners (RCGP) in Fig. 1A where weekly GP consultation rates per 100,000 population over the 2009 pandemic are compared with rates from the three previous years. Also shown is the proportion of swabbed individuals whose swabs tested positive for the presence of any flu virus (SI Data). Note that the GP consultation rate for 2009 is much higher than the usual seasonal rate, whereas the corresponding positivity is comparable to that observed in the preceding winters. This suggests that a substantial proportion of the peak in consultations was not directly attributable to A/H1N1pdm. Conversely, serological studies (3) have shown a marked increase in the prevalence of influenza antibodies among the population. Therefore, the degree to which the increased demand upon GPs is due to high levels of disease transmission as opposed to heightened public sensitivity remains unclear (4). Fig. 1 B and C show GP consultation rates by region and age group: consultations in Greater London and the West Midlands exhibit rapid early exponential growth, but the peak in London is much higher; rates appear to decrease markedly with age. Importantly, a first peak occurs immediately prior to the summer school holiday and the launch of the National ...

Marc Lipsitch and colleagues use complementary data from two US cities, Milwaukee and New York City, to assess the severity of pandemic (H1N1) 2009 influenza in the United States.

The Medical Research Council grant G0801947.