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

Assessing the importance of demographic risk factors across two waves of SARS-CoV-2 using fine-scale case data

For the long term control of an infectious disease such as COVID-19, it is crucial to identify the most likely individuals to become infected and the role that differences in demographic characteristics play in the observed patterns of infection. As high-volume surveillance winds down, testing data from earlier periods are invaluable for studying risk factors for infection in detail. Observed changes in time during these periods may then inform how stable thepattern will be in the long term.To this end we analyse the distribution of cases of COVID-19 across Scotland in 2021, where the location (census areas of order 500–1,000 residents) and reporting date of cases are known. We consider over 450,000 individually recorded cases, in two infection waves triggered by different lineages: B.1.1.529 (“Omicron”) and B.1.617.2 (“Delta”). We use random forests, informed by measures of geography, demography, testing and vaccination. We show that the distributions are only adequately explained when considering multiple explanatory variables, implying that case heterogeneity arose from a combination of individual behaviour, immunity, and testing frequency.Despite differences in virus lineage, time of year, and interventions in place, we find the risk factors remained broadly consistent between the two waves. Many of the observed smaller differences could be reasonably explained by changes in control measures

Assessing the potential impact of environmental land management schemes on emergent infection disease risks

Financial incentives are provided by governments to encourage the plantation of new woodland to increase habitat, biodiversity, carbon sequestration, and other economic benefits for landowners. Whilst these are largely positive effects, it is worth considering that greater biodiversity and presence of wildlife species in proximity to agricultural holdings may pose a risk of disease transmission between wildlife and livestock. Wildlife transmission and the provision of a reservoir for infectious disease is particularly important in the transmission dynamics of bovine tuberculosis. In this paper we develop an economic model for changing land use due to forestry subsidies. We use this asses the impact on wild deer populations in the newly created woodland areas and the emergent infectious disease risk arising from the proximity of new and existing wild deer populations and existing cattle holdings. We consider an area in the South-West of Scotland, having existing woodland, deer populations, and extensive and diverse cattle farm holdings. In this area we find that, with a varying level of subsidy and plausible new woodland creation, the contact risk between areas of wild deer and cattle increases between 26% and 35% over the contact risk present with zero subsidy. This model provides a foundation for extending to larger regions and for examining potential risk mitigation strategies, for example the targeting of subsidy in low risk areas or provisioning for buffer zones between woodland and agricultural holdings

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”

Epidemics on dynamic networks

In many populations, the patterns of potentially infectious contacts are transients that can be described as a network with dynamic links. The relative timescales of link and contagion dynamics and the characteristics that drive their tempos can lead to important differences to the static case. Here, we propose some essential nomenclature for their analysis, and then review the relevant literature. We describe recent advances in they apply to infection processes, considering all of the methods used to record, measure and analyse them, and their implications for disease transmission. Finally, we outline some key challenges and opportunities in the field. Keywords: Social network analysis, Disease models, Network metrics, Network dat

An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health

Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature

Atmospheric effects of the emerging mainland Chinese transportation system at and beyond the regional scale

Local surface travel needs in the People's Republic of China (mainland China) have traditionally been met largely by nonpolluting bicycles. A major automobile manufacturing/importing effort has begun in the country over the last decade, and planning documents indicate that the Chinese may strive to acquire more than 100 million vehicles early in the next century. By analogy with large automotive fleets already existing in the western world, both regional and global scale pollution effects are to be expected from the increase. The present work adopts the latest projections of Chinese automobile manufacture and performs some quantitative assessments of the extent of pollution generation. Focus for the investigation is placed upon the oxidant ozone. Emissions of the precursor species nitrogen oxides and volatile organics are constructed based on data for the current automotive sector in the eastern portion of the United States. Ozone production is first estimated from measured values for continental/oceanic scale yields relative to precursor oxidation. The estimates are then corroborated through idealized two dimensional modeling of the photochemistry taking place in springtime air flow off the Asian land mass and toward the Pacific Ocean. The projected fleet sizes could increase coastal and remote oceanic ozone concentrations by tens of parts per billion (ppb) in the lower troposphere. Influences on the tropospheric aerosol system and on the major greenhouse gas carbon dioxide are treated peripherally. Nitrogen oxides created during the vehicular internal combustion process will contribute to nitrate pollution levels measured in the open Pacific. The potential for soot and fugitive dust increases should be considered as the automotive infrastructure develops. Since the emerging Chinese automotive transportation system will represent a substantial addition to the global fleet and all the carbon in gasoline is eventually oxidized completely, a significant rise in global carbon dioxide inputs will ensue as well. Some policy issues are treated preliminary. The assumption is made that alterations to regional oxidant/aerosol systems and to terrestrial climate are conceivable. The likelihood that the Chinese can achieve the latest vehicle fleet goals is discussed, from the points of view of new production, positive pollution feedbacks from a growing automobile industry, and known petroleum reserves. Vehicular fuel and maintenance options lying before the Chinese are outlines and compared. To provide some perspective on the magnitude of the environmental changes associated with an Asian automotive buildup, recent estimates of the effects of future air traffic over the Pacific Rim are described

Estimates for local and movement-based transmission of bovine tuberculosis in British cattle

Both badgers and livestock movements have been implicated in contributing to the ongoing epidemic of bovine tuberculosis (BTB) in British cattle. However, the relative contributions of these and other causes are not well quantified. We used cattle movement data to construct an individual (premises)-based model of BTB spread within Great Britain, accounting for spread due to recorded cattle movements and other causes. Outbreak data for 2004 were best explained by a model attributing 16% of herd infections directly to cattle movements, and a further 9% unexplained, potentially including spread from unrecorded movements. The best-fit model assumed low levels of cattle-to-cattle transmission. The remaining 75% of infection was attributed to local effects within specific high-risk areas. Annual and biennial testing is mandatory for herds deemed at high risk of infection, as is pre-movement testing from such herds. The herds identified as high risk in 2004 by our model are in broad agreement with those officially designated as such at that time. However, border areas at the edges of high-risk regions are different, suggesting possible areas that should be targeted to prevent further geographical spread of disease. With these areas expanding rapidly over the last decade, their close surveillance is important to both identify infected herds quickly, and limit their further growth