Economic analysis of disease and control of multi-field epidemics in agriculture
Epidemics of plant diseases are estimated to cause significant economic losses in crop production. Fungicide applications are widely used to control crop diseases but incur substantial indirect costs. One essential class of indirect costs arises due to the evolution of fungicide resistance. This indirect cost must be estimated reliably to design economic policy for more sustainable use of fungicides. Such estimation is difficult because the cost depends on economic parameters and the evo-epidemiological properties of crop pathogens. Even a conceptual framework for such estimation is missing. To address this problem, we combined a spatially implicit mathematical model of crop epidemics with an economic analysis at the landscape scale. We investigated how the net economic return from a landscape depends on the proportion of fungicide-treated fields. We discovered a pattern of accelerating (or decelerating) returns, contrary to expected diminishing returns. Next, we calculated the economic cost of the evolution of fungicide resistance as the difference between the optimal net return of the landscape in the absence and presence of resistance. We found that this cost depends strongly on the fungicide price, the degree of resistance, the pathogens basic reproduction number and the yield loss due to disease. Surprisingly, the cost declines with the fungicide price and exhibits a non-monotonic pattern as a function of the basic reproduction number. Hence, to calculate the cost, we must estimate these parameters robustly, incorporating variations in environmental conditions, crop varieties and the genetic composition of pathogen populations. Appropriate estimation of the cost of resistance evolution can inform economic policy and encourage more sustainable use of fungicides. Author SummaryFungicides protect crops from diseases and are essential for securing the global food supply, but they incur serious indirect costs to society and the environment. One such cost arises because of the evolution of fungicide resistance. Part of the pathogen population (fungicide-resistant) can gain protection from a fungicide via a genetic change. If fungicide applications continue, the fungicide-resistant subpopulation increases and dominates the population, leading to low efficacy. Resistance can lead to severe economic losses, but no conceptual framework exists for estimating them. We present a novel mathematical framework to estimate the economic costs of fungicide resistance at the landscape scale. We combined an epidemiological model describing disease spread with an economic cost-benefit analysis. Surprisingly, we found that the economic cost of resistance declines for more expensive fungicides. This cost also depends on the pathogens capacity to spread (invasiveness): the cost is highest for pathogens with intermediate invasiveness. Thus, the cost of resistance depends on economic parameters and the biological characteristics of plant diseases. Our findings can inform economic policies for sustainable fungicide use, such as taxes or subsidies. Our paper also contributes to the broader discourse on agricultural sustainability while ensuring global food security.