Modeling the spread and control of foot-and-mouth disease in Pennsylvania following its discovery and options for control

Abstract

In this paper, we simulate outbreaks of foot-and-mouth disease in the Commonwealth of Pennsylvania, USA – after the introduction of a state-wide movement ban – as they might unfold in the presence of mitigation strategies. We have adapted a model previously used to investigate FMD control policies in the UK to examine the potential for disease spread given an infection seeded in each county in Pennsylvania. The results are highly dependent upon the county of introduction and the spatial scale of transmission. Should the transmission kernel be identical to that for the UK, the epidemic impact is limited to fewer than 20 premises, regardless of the county of introduction. However, for wider kernels where infection can spread further, outbreaks seeded in or near the county with highest density of premises and animals result in large epidemics (>150 premises). Ring culling and vaccination reduce epidemic size, with the optimal radius of the rings being dependent upon the county of introduction. Should the kernel width exceed a given county-dependent threshold, ring culling is unable to control the epidemic. We find that a vaccinate-to-live policy is generally preferred to ring culling (in terms of reducing the overall number of premises culled), indicating that well-targeted control can dramatically reduce the risk of large scale outbreaks of foot-and-mouth disease occurring in Pennsylvania.

Models of highly pathogenic avian influenza epidemics in commercial poultry flocks in Nigeria and Ghana

“…The results of adding ring culling or countrywide vaccination to the baseline culling strategy were similar to those reported in models of foot-and-mouth disease (Tildesley et al 2006, 2011). Reactive countrywide vaccination strategies where the order in which premises are vaccinated is determined by known risk factors for infection (in our case, flock size and proximity to an infected flock) are more effective in reducing the final size of the epidemic and the epidemic impact than vaccinating at random.…”

“…Furthermore, the epidemic impact changed in a complicated manner as the radius of the high-risk zone was increased. This result has been noted by others (e.g., Tildesley et al 2011) and serves to emphasize that there is no straightforward way of deciding in advance on an optimum preemptive ring culling strategy. For example, in our simulations of major outbreaks in Ogun, culling within a 4-mi radius high-risk zone resulted in the lowest attack rate (number of infected farms, 39.37 farms), but the epidemic impact (the total number of farms culled, 119.28 farms) was greater than resulted from the less onerous default strategy (100.97 farms, Table 2).…”

“…However, it should be emphasized that this outcome could not have been predicted in advance. Given different values for the transmission kernel parameters δ and ρ, quite different results could have been obtained (e.g., Tildesley et al 2011). …”

Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California

“…However, the metric could readily be extended to a range of objective functions with different weightings for the individual components depending on perceived costs and benefits by different stakeholders (7,34). Treatment radii can also be adjusted to allow for different degrees of risk aversion (35), for example, selecting the radius that corresponds to the 5th percentile (high risk aversion) through to the 95th percentile (low risk aversion) (compare Fig. 4).…”

Vaccination against Foot-And-Mouth Disease: Do Initial Conditions Affect Its Benefit?

“…As seen above, delaying the implementation of vaccination reduces the benefit of a reactive vaccination strategy. As argued elsewhere [33], it is therefore important that qualitative rules should be generated to inform policy within the early stages of an epidemic until sufficient data are collected to enable full quantitative assessment of the transmission kernel function.…”