Budgeting and portfolio allocation for biosecurity measures

Abstract

This paper presents a practical model for optimally allocating a budget across different biosecurity threats and measures (e.g. prevention or border quarantine, active surveillance for early detection, and containment and eradication measures) to ensure the highest rate of return. Our portfolio model differs from the common principle, which ranks alternative projects by their benefit cost ratios and picks the one that generates the highest average benefit cost ratio. The model we propose, instead, aims to allocate shares of the budget to the species where it is most cost‐effective, and consequently determine the optimal scale of the control program for each threat under varying budget constraints. The cost‐effectiveness of each block of budget spent on a threat is determined by minimising its expected total cost, including the damages it inflicts, and the control expenditures incurred in preventing or mitigating damages. As an illustration, the model is applied to the optimal allocation of a budget across four of Australia's most dangerous pests and diseases: red imported fire ants; foot‐and‐mouth disease; papaya fruit fly; and orange hawkweed. The model can readily be extended to consider more species and activities, and more complex settings including cases where detailed spatial and temporal information needs to be considered.

Quantifying the potential pathways and locations of Rift Valley fever virus entry into the United States

“…notoscriptus [Skuse]) underscores the challenge of biological invasion management (Peterson & Campbell, ; ProMed‐mail, ). When the consequence of disease establishment results in an annual threat to public and animal health and economic prosperity, investments towards the prevention of disease emergence far exceed the economic return of managing an established arbovirus (Fenichel et al., ; Kompas, ). Unfortunately, the complex nature of biological invasions and infectious disease dynamics make them difficult to forecast, but simplified modelling efforts can help clarify biological assumptions, identify feasible pathways of invasion, and identify gaps in knowledge, all essential to organizing response strategies that support the proactive mitigation of disease establishment (Fenichel et al., ; Hethcote, ; Kompas, ).…”

“…notoscriptus [Skuse]) underscores the challenge of biological invasion management (Peterson & Campbell, 2015;ProMed-mail, 2014). When the consequence of disease establishment results in an annual threat to public and animal health and economic prosperity, investments towards the prevention of disease emergence far exceed the economic return of managing an established arbovirus (Fenichel et al, 2010;Kompas, 2015).…”

“…Unfortunately, the complex nature of biological invasions and infectious disease dynamics make them difficult to forecast, but simplified modelling efforts can help clarify biological assumptions, identify feasible pathways of invasion, and identify gaps in knowledge, all essential to organizing response strategies that support the proactive mitigation of disease establishment (Fenichel et al, 2010;Hethcote, 2009;Kompas, 2015).…”

“…Should RVFV enter the USA, diagnosing the disease and controlling the spread of infected mosquitoes and vertebrates will pose a significant challenge to existing infrastructure (Britch & Linthicum, 2007). In the case of haemorrhagic diseases like RVFV, preventing viral emergence is significantly more efficient than dealing with the severe health and economic consequences associated with RVFV emergence or establishment (Basili & Belloc, 2015;Fenichel et al, 2010;Kompas, 2015).…”

“…Data from published resources on RVFV epidemiology, RVFV ecology and international movement were combined to (i) quantify pathways of RVFV entry into the USA, (ii) identify ports of entry, and (iii) distinguish which RVFV‐endemic regions are directly connected to the USA. This modelling effort is intended to help mitigate the ever‐increasing risk of RVFV invasion into the USA by postulating a priori estimates on pathways of viral entry that can help strategize cost‐effective surveillance and management plans (Bird & McElroy, ; Fenichel, Horan, & Hickling, ; Kompas, ; Lounibos, ; Tatem et al., ).…”