Use and abuse of mathematical models: an illustration from the 2001 foot and mouth disease epidemic in the United Kingdom

Foot and mouth disease (FMD) is a major threat, not only to countries whose economies rely on agricultural exports, but also to industrialised countries that maintain a healthy domestic livestock industry by eliminating major infectious diseases from their livestock populations. Traditional methods of controlling diseases such as FMD require the rapid detection and slaughter of infected animals, and any susceptible animals with which they may have been in contact, either directly or indirectly. During the 2001 epidemic of FMD in the United Kingdom (UK), this approach was supplemented by a culling policy driven by unvalidated predictive models. The epidemic and its control resulted in the death of approximately ten million animals, public disgust with the magnitude of the slaughter, and political resolve to adopt alternative options, notably including vaccination, to control any future epidemics. The UK experience provides a salutary warning of how models can be abused in the interests of scientific opportunism.

Risk of foot and mouth disease associated with proximity in space and time to infected premises and the implications for control policy during the 2001 epidemic in Cumbria

An analysis was made that calculated the risk of disease for premises in the most heavily affected parts of the county of Cumbria during the foot-and-mouth disease epidemic in the UK in 2001. In over half the cases the occurrence of the disease was not directly attributable to a recently infected premises being located within 1.5 km. Premises more than 1.5 km from recently infected premises faced sufficiently high infection risks that culling within a 1.5 km radius of the infected premises alone could not have prevented the progress of the epidemic. A comparison of the final outcome in two areas of the county, south Penrith and north Cumbria, indicated that focusing on controlling the potential spread of the disease over short distances by culling premises contiguous to infected premises, while the disease continued to spread over longer distances, may have resulted in excessive numbers of premises being culled. Even though the contiguous cull in south Penrith appeared to have resulted in a smaller proportion of premises becoming infected, the overall proportion of premises culled was considerably greater than in north Cumbria, where, because of staff and resource limitations, a smaller proportion of premises contiguous to infected premises was culled

Disease-weather relationships for powdery mildew and yellow rust on winter wheat

Key weather factors determining the occurrence and severity of powdery mildew and yellow rust epidemics on winter wheat were identified. Empirical models were formulated to qualitatively predict a damaging epidemic (>5% severity) and quantitatively predict the disease severity given a damaging epidemic occurred. The disease data used was from field experiments at 12 locations in the UK covering the period from 1994 to 2002 with matching data from weather stations within a 5 km range. Wind in December to February was the most influential factor for a damaging epidemic of powdery mildew. Disease severity was best identified by a model with temperature, humidity, and rain in April to June. For yellow rust, the temperature in February to June was the most influential factor for a damaging epidemic as well as for disease severity. The qualitative models identified favorable circumstances for damaging epidemics, but damaging epidemics did not always occur in such circumstances, probably due to other factors such as the availability of initial inoculum and cultivar resistance.

Modelling disease spread and control in networks: implications for plant sciences

Networks are ubiquitous in natural, technological and social systems. They are of increasing relevance for improved understanding and control of infectious diseases of plants, animals and humans, given the interconnectedness of today's world. Recent modelling work on disease development in complex networks shows: the relative rapidity of pathogen spread in scale-free compared with random networks, unless there is high local clustering; the theoretical absence of an epidemic threshold in scale-free networks of infinite size, which implies that diseases with low infection rates can spread in them, but the emergence of a threshold when realistic features are added to networks (e.g. finite size, household structure or deactivation of links); and the influence on epidemic dynamics of asymmetrical interactions. Models suggest that control of pathogens spreading in scale-free networks should focus on highly connected individuals rather than on mass random immunization. A growing number of empirical applications of network theory in human medicine and animal disease ecology confirm the potential of the approach, and suggest that network thinking could also benefit plant epidemiology and forest pathology, particularly in human-modified pathosystems linked by commercial transport of plant and disease propagules. Potential consequences for the study and management of plant and tree diseases are discussed.

Epidemic multidrug-resistant (MDR-AmpC) Salmonella enterica serovar Newport strains contain three phage regions and a MDR resistance plasmid

Multidrug-resistant (MDR-AmpC) Salmonella enterica serovar Newport has caused serious disease in animals and humans in North America, whereas in the UK S. enterica serovar Newport is not associated with severe disease and usually sensitive to antibiotics; MDR S. Newport (not AmpC) strains have only been isolated from poultry. We found that UK poultry strains belonged to MLST type ST166 and were distinct from cattle isolates for being able to utilize D-tagotose and when compared by pulsed-field gel electrophoresis (PFGE), comparative genomic hybridization (CGH) and diversity arrays technology (DArT). Cattle strains belonged to the ST45 complex differing from ST166 at all seven loci. PFGE showed that 19 out of 27 cattle isolates were more than 85% similar to each other and some UK and US strains were indistinguishable. Both CGH and DArT identified genes (including phage-related ones) that were uniquely present in the US isolates and two such genes identified by DArT showed sequence similarities with the pertussis-like (artAB) toxin. This work demonstrates that MDR-AmpC S. Newport from the USA are genetically closely related to pan-susceptible strains from the UK, but contained three extra phage regions and a MDR plasmid.

Economic rationale for interventions to control livestock disease

Disease in farm animals has significant economic impacts on livestock production and incurs substantial costs for societies. Impacts affect not only livestock farms and the livestock industries but also sectors outside of farming. Important negative externalities of livestock disease include impacts on the health of other producers’ livestock, on human health, and on animal welfare. Good disease risk management/biosecurity and good animal welfare are public goods. Not taking account of these externality and public good aspects can lead to a misallocation of resources for livestock disease control. In such instances, there may be a strong case for government or other authority to intervene to ensure a better use of resources. There are a number of policy instruments that can be implemented for this purpose. One potential instrument is a Farm Animal Health and Welfare Stewardship Scheme funded under Pillar II of the CAP. A number of countries have public–private partnership cost-sharing schemes that aim to share appropriately both responsibilities and costs of epidemic livestock disease. There is a strong future agenda for appropriate intervention by governments in the management of livestock disease risks, including responsibility and cost sharing for livestock disease control, within the European Union and elsewhere.