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Globally, the bacterial genus Campylobacter is one of the leading causes of human gastroenteritis, with its primary route of infection being through poultry meat. The application of biosecurity measures is currently limited by a lack of understanding of the transmission dynamics within a flock. Our work is the first to undertake a mathematical modeling approach to Campylobacter population dynamics within a flock of broilers (chickens bred specifically for meat). A system of stochastic differential equations is used to model the routes of infection between co-housed birds. The presented model displays the strong correlation between housing density and Campylobacter prevalence, and shows how stochastic variation is the driving factor determining which strains of Campylobacter will emerge first within a flock. The model also shows how the system will rapidly select for phenotypic advantages, to quickly eliminate demographically-weaker strains. A global sensitivity analysis is performed, highlighting that the growth and death rate of other native bacterial species likely contributes the greatest to preventing flock outbreaks, presenting a promising approach to hypothesizing new methods of combatting disease transmission.

BackgroundEngland’s COVID-19 “roadmap out of lockdown” set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued. Here we assess the roadmap, the impact of the Delta variant, and potential future epidemic trajectories.MethodsWe extended a model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the Delta variant. We calibrated the model to English surveillance data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs.FindingsThe roadmap was successful in offsetting the increased transmission resulting from lifting NPIs with increasing population immunity through vaccination. However due to the emergence of Delta, with an estimated transmission advantage of 73% (95%CrI: 68-79) over Alpha, fully lifting NPIs on 21 June 2021 as originally planned may have led to 3,400 (95%CrI: 1,300-4,400) peak daily hospital admissions under our central parameter scenario. Delaying until 19 July reduced peak hospitalisations by three-fold to 1,400 (95%CrI: 700-1,500) per day. There was substantial uncertainty in the epidemic trajectory, with particular sensitivity to estimates of vaccine effectiveness and the intrinsic transmissibility of Delta.InterpretationOur findings show that the risk of a large wave of COVID hospitalisations resulting from lifting NPIs can be substantially mitigated if the timing of NPI relaxation is carefully balanced against vaccination coverage. However, with Delta, it may not be possible to fully lift NPIs without a third wave of hospitalisations and deaths, even if vaccination coverage is high. Variants of concern, their transmissibility, vaccine uptake, and vaccine effectiveness must be carefully monitored as countries relax pandemic control measures.FundingNational Institute for Health Research, UK Medical Research Council, Wellcome Trust, UK Foreign, Commonwealth & Development Office.Research in contextEvidence before this studyWe searched PubMed up to 23 July 2021 with no language restrictions using the search terms: (COVID-19 or SARS-CoV-2 or 2019-nCoV or “novel coronavirus”) AND (vaccine or vaccination) AND (“non pharmaceutical interventions” OR “non-pharmaceutical interventions) AND (model*). We found nine studies that analysed the relaxation of controls with vaccination roll-out. However, none explicitly analysed real-world evidence balancing lifting of interventions, vaccination, and emergence of the Delta variant.Added value of this studyOur data synthesis approach combines real-world evidence from multiple data sources to retrospectively evaluate how relaxation of COVID-19 measures have been balanced with vaccination roll-out. We explicitly capture the emergence of the Delta variant, its transmissibility over Alpha, and quantify its impact on the roadmap. We show the benefits of maintaining NPIs whilst vaccine coverage continues to increase and capture key uncertainties in the epidemic trajectory after NPIs are lifted.Implications of all the available evidenceOur study shows that lifting interventions must be balanced carefully and cautiously with vaccine roll-out. In the presence of a new, highly transmissible variant, vaccination alone may not be enough to control COVID-19. Careful monitoring of vaccine uptake, effectiveness, variants, and changes in contact patterns as restrictions are lifted will be critical in any exit strategy.

Despite continued efforts to improve biosecurity protocols, Campylobacter continues to be detected in the majority of commercial chicken flocks across Europe. Using an extensive data set of Campylobacter prevalence within a chicken breeder flock for over a year, multiple Bayesian models are presented to explore the dynamics of the spread of Campylobacter in response to seasonal variation, species-specificity, bird health, and total colonization prevalence. These models indicated that birds within the flock varied greatly in their response to bacterial challenge, and that this phenomenon had a large impact on the overall prevalence of different species of Campylobacter. Campylobacter jejuni appeared more frequently in the summer, while Campylobacter coli persisted for a longer duration, amplified by the most susceptible birds in the flock. Our study suggests that strains of Campylobacter that appear most frequently likely possess no demographic advantage, but are instead amplified due to the health of the birds that ingest it.

Countries around the world have observed reduced infections from the SARS-CoV-2 virus, that causes COVID-19 illness, primarily due to non-pharmaceutical interventions (NPIs) such as lockdowns and social distancing measures designed to limit physical proximity between people. However, economies and societal interactions require restarting, and so lockdowns cannot continue indefinitely. Therefore, much hope is placed in using newly developed vaccines as a route back to normality, but this raises key questions about how they are shared. There are also emerging questions regarding travel. For instance, international business and trade necessitates at least some in-person exchanges, alongside restarting travel also for tourist purposes. By utilising a Susceptible-Infected-Recovered-Vaccinated (SIRV) mathematical model, we simulate the populations of two nations in parallel, where the first nation produces a vaccine and decides the extent to which it is shared with the second. Overlaying our mathematical structure is the virus-related effects of travel between the two nations. We find that even with extensive travel, nation one minimises its total number of deaths by simply retaining vaccines, aiming for full inoculation as fast as possible, suggesting that the risks posed by travel can be mitigated by rapidly vaccinating its own population. If instead we consider the total deaths i.e., sum of deaths of both nations, then such a policy of not sharing by nation one until full vaccination is highly sub-optimal. A policy of low initial sharing causes many more deaths in nation two than lives saved in nation one, raising important ethical issues. This imbalance in the health impact of vaccination provision must be considered as some countries begin to approach the point of extensive vaccination, while others lack the resources to do so.

10Countries around the world are in a state of lockdown to help limit the spread of SARS-CoV-2. However, as the number of new daily confirmed cases begins to decrease, governments must decide how to release their populations from quarantine as efficiently as possible without overwhelming their health services. We applied an optimal control framework to an adapted Susceptible-Exposure-Infection-Recovery (SEIR) model framework to investigate the efficacy of two potential lockdown release strategies, focusing on the UK population as a test case. To limit recurrent spread, we find that ending quarantine for the entire population simultaneously is a high-risk strategy, and that a gradual re-integration approach would be more reliable.Furthermore, to increase the number of people that can be first released, lockdown should not be ended until the number of new daily confirmed cases reaches a sufficiently low threshold.We model a gradual release strategy by allowing different fractions of those in lockdown to re-enter the working non-quarantined population. Mathematical optimisation methods, combined with our adapted SEIR model, determine how to maximise those working while preventing the health service from being overwhelmed. The optimal strategy is broadly found to be to release approximately half the population two-to-four weeks from the end of an initial infection peak, then wait another three-to-four months to allow for a second peak before releasing everyone else. We also modelled an "on-off" strategy, of releasing everyone, but re-establishing lockdown if infections become too high. We conclude that the worst-case scenario of a gradual release is more manageable than the worst-case scenario of an on-off strategy, and caution against lockdown-release strategies based on a threshold-dependent on-off mechanism.The two quantities most critical in determining the optimal solution are transmission rate and the recovery rate, where the latter is defined as the fraction of infected people in any given day that then become classed as recovered. We suggest that the accurate identification of these values is of particular importance to the ongoing monitoring of the pandemic.

Globally, the bacterial genus Campylobacter is one of the leading causes of human gastroenteritis, with its primary route of infection being through poultry meat. Despite decades of study we appear to be no closer to preventing outbreaks within commercial chicken flocks, and the application of biosecurity measures is limited by a lack of understanding of the transmission dynamics within a flock. Our work is the first to undertake a mathematical modelling approach to Campylobacter population dynamics within a flock of broilers (chickens bred specifically for meat). A system of stochastic differential equations is used to investigate the diverse and fluctuating conditions within the gut of a broiler, and models the routes of infection between co-housed birds. The presented model provides mechanistic explanations for key infection dynamics that have been long-observed but very poorly understood. We highlight several driving mechanisms behind observed infection phenomena, simulate experimentally observed inter-strain competition, and present a promising approach to hypothesising new methods of preventing flock outbreaks.The bacteria Campylobacter is one of the most common causes of food poisoning globally. The most common route of infection is through raw chicken meat, as a result of many chicken farms across the world housing fully infected flocks. Despite the magnitude of this public health risk, little is understood of the specifics of how chickens become infected, and the ways that they then infect one another. Our work presents a mathematical model of Campylobacter transmission dynamics within a flock of chickens.We compare the results of the model to real world data sets, explore key dynamical behaviours, and present a sensitivity analysis to highlight the most important factors underpinning outbreaks.