29 research outputs found
The reachability of contagion in temporal contact networks: how disease latency can exploit the rhythm of human behavior
The symptoms of many infectious diseases influence their host to withdraw
from social activity limiting their own potential to spread. Successful
transmission therefore requires the onset of infectiousness to coincide with a
time when its host is socially active. Since social activity and infectiousness
are both temporal phenomena, we hypothesize that diseases are most pervasive
when these two processes are synchronized. We consider disease dynamics that
incorporate a behavioral response that effectively shortens the infectious
period of the disease. We apply this model to data collected from face-to-face
social interactions and look specifically at how the duration of the latent
period effects the reachability of the disease. We then simulate the spread of
the model disease on the network to test the robustness of our results.
Diseases with latent periods that synchronize with the temporal social behavior
of people, i.e. latent periods of 24 hours or 7 days, correspond to peaks in
the number of individuals who are potentially at risk of becoming infected. The
effect of this synchronization is present for a range of disease models with
realistic parameters. The relationship between the latent period of an
infectious disease and its pervasiveness is non-linear and depends strongly on
the social context in which the disease is spreading.Comment: 9 Pages, 5 figure
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Structure and dynamics of evolving complex networks
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe analysis of large disordered complex networks has recently received enormous attention motivated by both academic and commercial interest. The most important results in this discipline have come from the analysis of stochastic models which mimic the growth and evolution of real networks as they change over time. The purpose of this thesis is to introduce various novel processes which dictate the development of a network on a small scale, and use techniques learned from statistical physics to derive the dynamical and structural properties of the network on the macroscopic scale. We introduce each model as a set of mechanisms determining how a network changes over a small period in time, from these rules we derive several topological
properties of the network after many iterations, most notably the degree distribution. 1. In the rst mechanism, nodes are introduced and linked to older nodes in the network in such a way as to create triangles and maintain a high level of clustering. The mechanism resembles the growth of a citation network and we demonstrate analytically that the mechanism introduced su ces to explain the power-law form commonly found in citation distributions. 2. The second mechanism involves edge rewiring processes - detaching one end of an edge and reattaching it, either to a random node anywhere in the network or to one selected locally. 3. We analyse a variety of processes based around a novel fragmentation mechanism. 4. The nal model concerns the problem of nding the electrical resistance across a network. The network grows as a random tree, as it grows the distribution of resistance converges towards a steady state solution. We nd an application of the relatively recent concept of a random Fibonacci sequence in deriving the rate of convergence of the mean.EPSR
Spontaneous divergence of disease status in an economic epidemiological game
We introduce a game inspired by the challenges of disease management in
livestock farming and the transmission of endemic disease through a trade
network. Success in this game comes from balancing the cost of buying new stock
with the risk that it will be carrying some disease. When players follow a
simple memory-based strategy we observe a spontaneous separation into two
groups corresponding to players with relatively high, or low, levels of
infection. By modelling the dynamics of both the disease and the formation and
breaking of trade relationships, we derive the conditions for which this
separation occurs as a function of the transmission rate and the threshold
level of acceptable disease for each player. When interactions in the game are
restricted to players that neighbour each other in a small-world network,
players tend to have similar levels of infection as their neighbours. We
conclude that success in economic-epidemiological systems can originate from
misfortune and geographical circumstances as well as by innate differences in
personal attitudes towards risk
A metapopulation model for preventing the reintroduction of bovine viral diarrhea virus to naïve herds: Scotland case study
BACKGROUND: Bovine viral diarrhea (BVD) virus is one of the most problematic infectious pathogens for cattle. Since 2013, a mandatory BVD eradication program has successfully reduced the number of infected cattle living on Scottish farms; however, England remains at high prevalence and presents a risk to Scotland through animal movement. METHODS: We analyze cattle movements in the UK from 2008 to 2017 and recorded incidence of BVD in Scotland from 2017 to 2020. To simulate BVD reintroduction into Scotland, we developed an epidemiological model that combines transmission between cattle and animal movements between farms. A total of four control strategies were implemented in the model: no intervention, import restriction, targeted vaccination, and combined strategy. RESULTS: During the course of the eradication scheme, movements into Scotland became increasingly distributed in regions close to the England–Scotland border. The prevalence of BVD in this region decreased at a slower rate than the rest of Scotland during the eradication scheme. Our model showed that the change in the prevalence is expected, given that the change in the patterns of movement and if vaccination is targeted to the border areas that decrease in the prevalence will be seen throughout the whole of Scotland. CONCLUSION: Scottish farms are susceptible to BVD virus reintroduction through animal imports from non-BVD-free nations with farms in border areas being the most vulnerable. Protecting the border regions provides direct and indirect protection to the rest of Scottish farms by interrupting chains of transmission
Ascertainment rate of SARS-CoV-2 infections from healthcare and community testing in the UK
The proportion of SARS-CoV-2 infections ascertained through healthcare and community testing is generally unknown and expected to vary depending on natural factors and changes in test-seeking behaviour. Here we use population surveillance data and reported daily case numbers in the United Kingdom to estimate the rate of case ascertainment. We mathematically describe the relationship between the ascertainment rate, the daily number of reported cases, population prevalence, and the sensitivity of PCR and Lateral Flow tests as a function time since exposure. Applying this model to the data, we estimate that 20%–40% of SARS-CoV-2 infections in the UK were ascertained with a positive test with results varying by time and region. Cases of the Alpha variant were ascertained at a higher rate than the wild type variants circulating in the early pandemic, and higher again for the Delta variant and Omicron BA.1 sub-lineage, but lower for the BA.2 sub-lineage. Case ascertainment was higher in adults than in children. We further estimate the daily number of infections and compare this to mortality data to estimate that the infection fatality rate increased by a factor of 3 during the period dominated by the Alpha variant, and declined in line with the distribution of vaccines. This manuscript was submitted as part of a theme issue on “Modelling COVID-19 and Preparedness for Future Pandemics”
Social fluidity mobilizes contagion in human and animal populations
International audienceHumans and other group-living animals tend to distribute their social effort disproportionately. Individuals predominantly interact with a small number of close companions while maintaining weaker social bonds with less familiar group members. By incorporating this behavior into a mathematical model, we find that a single parameter, which we refer to as social fluidity, controls the rate of social mixing within the group. Large values of social fluidity correspond to gregarious behavior, whereas small values signify the existence of persistent bonds between individuals. We compare the social fluidity of 13 species by applying the model to empirical human and animal social interaction data. To investigate how social behavior influences the likelihood of an epidemic outbreak, we derive an analytical expression of the relationship between social fluidity and the basic reproductive number of an infectious disease. For species that form more stable social bonds, the model describes frequency-dependent transmission that is sensitive to changes in social fluidity. As social fluidity increases, animal-disease systems become increasingly density-dependent. Finally, we demonstrate that social fluidity is a stronger predictor of disease outcomes than both group size and connectivity, and it provides an integrated framework for both density-dependent and frequency-dependent transmission
Modelling plausible scenarios for the Omicron SARS-CoV-2 variant from early-stage surveillance
In this paper we used an adapted version of an existing simulation model of
SARS-CoV-2 transmission in Scotland to investigate the rise of the Omicron
variant of concern, in order to evaluate plausible scenarios for transmission
advantage and vaccine immune escape relative to the Delta variant. We also
explored possible outcomes of different levels of imposed non-pharmaceutical
intervention. The initial results of these scenarios were used to inform the
Scottish Government in the early outbreak stages of the Omicron variant.
We use an explicitly spatial agent-based simulation model combined with
spatially fine-grained COVID-19 observation data from Public Health Scotland.
Using the model with parameters fit over the Delta variant epidemic, some
initial assumptions about Omicron transmission advantage and vaccine escape,
and a simple growth rate fitting procedure, we were able to capture the initial
outbreak dynamics for Omicron. We also find the modelled dynamics hold up to
retrospective scrutiny.
We found that the modelled imposition of extra non-pharmaceutical
interventions planned by the Scottish Government at the time would likely have
little effect in light of the transmission advantage held by the Omicron
variant and the fact that the planned interventions would have occurred too
late in the outbreak's trajectory. Finally, we found that any assumptions made
about the projected distribution of vaccines in the model population had little
bearing on the outcome, in terms of outbreak size and timing, rather that the
detailed landscape of immunity prior to the outbreak was of far greater
importance
A Metapopulation Model for Preventing the Reintroduction of Bovine Viral Diarrhea Virus to Naïve Herds: Scotland Case Study
BackgroundBovine viral diarrhea (BVD) virus is one of the most problematic infectious pathogens for cattle. Since 2013, a mandatory BVD eradication program has successfully reduced the number of infected cattle living on Scottish farms; however, England remains at high prevalence and presents a risk to Scotland through animal movement.MethodsWe analyze cattle movements in the UK from 2008 to 2017 and recorded incidence of BVD in Scotland from 2017 to 2020. To simulate BVD reintroduction into Scotland, we developed an epidemiological model that combines transmission between cattle and animal movements between farms. A total of four control strategies were implemented in the model: no intervention, import restriction, targeted vaccination, and combined strategy.ResultsDuring the course of the eradication scheme, movements into Scotland became increasingly distributed in regions close to the England–Scotland border. The prevalence of BVD in this region decreased at a slower rate than the rest of Scotland during the eradication scheme. Our model showed that the change in the prevalence is expected, given that the change in the patterns of movement and if vaccination is targeted to the border areas that decrease in the prevalence will be seen throughout the whole of Scotland.ConclusionScottish farms are susceptible to BVD virus reintroduction through animal imports from non-BVD-free nations with farms in border areas being the most vulnerable. Protecting the border regions provides direct and indirect protection to the rest of Scottish farms by interrupting chains of transmission