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Background: In the event of a release of a pathogen such as smallpox, which is human-to-human transmissible and has high associated mortality, a key question is how best to deploy containment and control strategies. Given the general uncertainty surrounding this issue, mathematical modelling has played an important role in informing the likely optimal response, in particular defining the conditions under which mass-vaccination would be appropriate. In this paper, we consider two key questions currently unanswered in the literature: firstly, what is the optimal spatial scale for intervention; and secondly, how sensitive are results to the modelling assumptions made about the pattern of human contacts?Methods: Here we develop a novel mathematical model for smallpox that incorporates both information on individual contact structure (which is important if the effects of contact tracing are to be captured accurately) and large-scale patterns of movement across a range of spatial scales in Great Britain.Results: Analysis of this model confirms previous work suggesting that a locally targeted 'ring' vaccination strategy is optimal, and that this conclusion is actually quite robust for different socio-demographic and epidemiological assumptions.Conclusions: Our method allows for intuitive understanding of the reasons why national mass vaccination is typically predicted to be suboptimal. As such, we present a general framework for fast calculation of expected outcomes during the attempted control of diverse emerging infections; this is particularly important given that parameters would need to be interactively estimated and modelled in any release scenario. [ABSTRACT FROM AUTHOR]

Background: Lower Respiratory Tract Infections (LRTI) pose a serious threat to older adults but may be underdiagnosed due to atypical presentations. Here we assess LRTI symptom profiles and syndromic (symptom-based) case ascertainment in older (≥ 65y) as compared to younger adults (< 65y)., Methods: We included adults (≥ 18y) with confirmed LRTI admitted to two acute care Trusts in Bristol, UK from 1st August 2020- 31st July 2022. Logistic regression was used to assess whether age ≥ 65y reduced the probability of meeting syndromic LRTI case definitions, using patients' symptoms at admission. We also calculated relative symptom frequencies (log-odds ratios) and evaluated how symptoms were clustered across different age groups., Results: Of 17,620 clinically confirmed LRTI cases, 8,487 (48.1%) had symptoms meeting the case definition. Compared to those not meeting the definition these cases were younger, had less severe illness and were less likely to have received a SARS-CoV-2 vaccination or to have active SARS-CoV-2 infection. Prevalence of dementia/cognitive impairment and levels of comorbidity were lower in this group. After controlling for sex, dementia and comorbidities, age ≥ 65y significantly reduced the probability of meeting the case definition (aOR = 0.67, 95% CI:0.63-0.71). Cases aged ≥ 65y were less likely to present with fever and LRTI-specific symptoms (e.g., pleurisy, sputum) than younger cases, and those aged ≥ 85y were characterised by lack of cough but frequent confusion and falls., Conclusions: LRTI symptom profiles changed considerably with age in this hospitalised cohort. Standard screening protocols may fail to detect older and frailer cases of LRTI based on their symptoms., (© 2024. The Author(s).)

Background: Predicting the likely size of future SARS-CoV-2 waves is necessary for public health planning. In England, voluntary "plan B" mitigation measures were introduced in December 2021 including increased home working and face coverings in shops but stopped short of restrictions on social contacts. The impact of voluntary risk mitigation behaviours on future SARS-CoV-2 burden is unknown., Methods: We developed a rapid online survey of risk mitigation behaviours ahead of the winter 2021 festive period and deployed in two longitudinal cohort studies in the UK (Avon Longitudinal Study of Parents and Children (ALSPAC) and TwinsUK/COVID Symptom Study (CSS) Biobank) in December 2021. Using an individual-based, probabilistic model of COVID-19 transmission between social contacts with SARS-CoV-2 Omicron variant parameters and realistic vaccine coverage in England, we predicted the potential impact of the SARS-CoV-2 Omicron wave in England in terms of the effective reproduction number and cumulative infections, hospital admissions and deaths. Using survey results, we estimated in real-time the impact of voluntary risk mitigation behaviours on the Omicron wave in England, if implemented for the entire epidemic wave., Results: Over 95% of survey respondents (N ALSPAC  = 2686 and N Twins  = 6155) reported some risk mitigation behaviours, with vaccination and using home testing kits reported most frequently. Less than half of those respondents reported that their behaviour was due to "plan B". We estimate that without risk mitigation behaviours, the Omicron variant is consistent with an effective reproduction number between 2.5 and 3.5. Due to the reduced vaccine effectiveness against infection with the Omicron variant, our modelled estimates suggest that between 55% and 60% of the English population could be infected during the current wave, translating into between 12,000 and 46,000 cumulative deaths, depending on assumptions about severity and vaccine effectiveness. The actual number of deaths was 15,208 (26 November 2021-1 March 2022). We estimate that voluntary risk reduction measures could reduce the effective reproduction number to between 1.8 and 2.2 and reduce the cumulative number of deaths by up to 24%., Conclusions: Predicting future infection burden is affected by uncertainty in disease severity and vaccine effectiveness estimates. In addition to biological uncertainty, we show that voluntary measures substantially reduce the projected impact of the SARS-CoV-2 Omicron variant but that voluntary measures alone would be unlikely to completely control transmission., (© 2023. The Author(s).)

Background: During an influenza pandemic, a substantial proportion of transmission is thought to occur in households. We used data on influenza progression in individuals and their contacts collected by the City of Milwaukee Health Department (MHD) to study the transmission of pandemic influenza A/H1N1 virus in 362 households in Milwaukee, WI, and the effects of oseltamivir treatment and chemoprophylaxis., Methods: 135 households had chronological information on symptoms and oseltamivir usage for all household members. The effect of oseltamivir treatment and other factors on the household secondary attack rate was estimated using univariate and multivariate logistic regression with households as the unit of analysis. The effect of oseltamivir treatment and other factors on the individual secondary attack rate was estimated using univariate and multivariate logistic regression with individual household contacts as the unit of analysis, and a generalized estimating equations approach was used to fit the model to allow for clustering within households., Results: Oseltamivir index treatment on onset day or the following day (early treatment) was associated with a 42% reduction (OR: 0.58, 95% CI: 0.19, 1.73) in the odds of one or more secondary infections in a household and a 50% reduction (OR: 0.5, 95% CI: 0.17, 1.46) in the odds of a secondary infection in individual contacts. The confidence bounds are wide due to a small sample of households with early oseltamivir index usage - in 29 such households, 5 had a secondary attack. Younger household contacts were at higher risk of infection (OR: 2.79, 95% CI: 1.50-5.20)., Conclusions: Early oseltamivir treatment may be beneficial in preventing H1N1pdm influenza transmission; this may have relevance to future control measures for influenza pandemics. Larger randomized trials are needed to confirm this finding statistically.