Optimising the surveillance and control of communicable diseases: the effects of population heterogeneity on transmission dynamics

植物种群中传染病的爆发造成了毁灭性的经济和环境后果。在许多情况下，在病原体首次入侵后不久在人群中检测感染对控制方法的成功至关重要。因此，设计有效的监测策略以早期发现入侵植物病原体是全球生物安全的一个关键挑战。不幸的是，监测规划常常与无症状感染期相混淆，在此期间，植物没有表现出明显的症状。然而，有可能使用“哨兵”植物，它们可以更快地显示症状，作为早期预警信标。在这个项目中，我将应用数学和计算技术来确定在哪些情况下，基于哨兵的监测策略将提供一种具有成本效益的方法来早期检测监测，将现实生活中的植物病原体作为案例研究。

Outbreaks of infectious diseases in plant populations are responsible for devastating economic and environmental consequences. In many cases, detecting infection in a population soon after a pathogen has first invaded is crucial to the success of control methods. The design of effective surveillance strategies for the early detection of invasive plant pathogens is consequently a key challenge for global biosecurity. Unfortunately, monitoring programmes are often confounded by periods of asymptomatic infection, during which plants do not display visible symptoms. However, there is the potential to use 'sentinel' plants which display symptoms more quickly as early warning beacons. In this project, I will apply mathematical and computational techniques to determine scenarios under which sentinel-based surveillance strategies will provide a cost-effective approach to early detection monitoring, considering real-life plant pathogens as case studies.