Grower and regulator conflict in management of the citrus disease Huanglongbing in Brazil: A modelling study

Abstract

In managing plant diseases, there is often tension between a regulator seeking to destroy infected plants to prevent further infection on a national scale and growers seeking to retain infected plants to continue obtaining yield. A high‐profile example is Huanglongbing (HLB) or citrus greening, a bacterial disease that threatens Brazil's citrus industry. To prevent the spread of HLB, especially from abandoned infected groves, the government regulated that if 28% of a plantation unit (grove) is found to be symptomatic, then the whole plantation unit must be destroyed. This decision used the best evidence available in 2008, which suggested that a 28% detectable prevalence corresponded with 100% actual prevalence, the disparity being due to asymptomatic infected trees and imperfect detection methods. Using a mathematical model with parameters estimated from field data, we evaluate the assumptions underlying the 28% threshold. We investigate the effects of spraying insecticide and removing diseased plants on the infectious pressure and potential loss of yield from an infected grove. We find that the relationship between detectable and actual prevalence is much wider than allowed for in the regulations. There is a high probability that groves with detectable levels of symptomatic plants substantially below 28% have a >90% prevalence of infected plants. Paradoxically, in a well‐managed orchard, the threshold of 28% may not be reached at 100% prevalence. Infectious pressure from an infected grove is substantially reduced when growers control disease. Individual growers failing to manage disease, therefore, threaten the wider grower community. Control is likely to increase yield and prolong grove productivity, but in some groves may reduce yield. Policy implications. Current disease thresholds aimed at restricting the spread of the citrus disease, Huanglongbing (HLB), in Brazil allow heavily infected groves to remain in the landscape, but lower thresholds would disadvantage growers who are already controlling disease. There is probably no threshold that is optimal for individual growers and regulators but roguing and spraying is beneficial to both parties. Regulations should focus less on prevalence thresholds, and instead encourage early detection and co‐ordinated spraying among growers to control Huanglongbing on a regional level.

Using models to provide rapid programme support for California's efforts to suppress Huanglongbing disease of citrus

“…B 374: 20180281 these general features in strategic epidemiological models, for the benefit of future decision-makers facing the same challenges. Good progress in this kind of integrative work has already been made [21,24,[36][37][38][39][40]. A significant challenge faced by epidemiology is to integrate the valuable insights these analyses provide with close programme support work of the type described here.…”

Ongoing surveillance protects tanoak whilst conserving biodiversity: applying optimal control theory to a spatial simulation model of sudden oak death

“…Poorly designed disease management strategies can 180 lead to expensive failures of control, as was the case for control of Dutch elm disease in the UK [33] and citrus 181 canker in Florida [34]. Although detailed simulation models have been used to optimise management strategies for 182 a number of plant pathogens [3,32,[35][36][37][38][39][40][41], computational constraints mean that strategies under test are typically 183 restricted to one from a small set of possibilities in which the amount of control remains constant over time. Here we 184 have shown how frameworks for using optimal control theory [9] can be applied to realistic simulation models to 185 understand a practical disease management question, and identify effective management strategies.…”

“…Management of the isolated outbreak in Oregon has been effective at slowing the spread, containing 38 the disease within Curry county [4]. In some locations, control in Oregon has shown that local eradication, whilst 39 difficult, is possible [5]. Mathematical models however, have had little to say about how this local control should be 40 optimised.…”

Applying optimal control theory to complex epidemiological models to inform real-world disease management

“…These simulation models accurately capture the dynamics of the real system and so have become important tools for assessing policy decisions relating to real-time management responses as well as to increased preparedness for future threats. Examples include vaccination policies for human papillomavirus in the UK [5,6], livestock culling policies [7,8] and vaccination optimization [9,10] for footand-mouth disease, and optimal host removal strategies for tree diseases of citrus [11][12][13][14] and sudden oak death [15].…”