Hosack Geoffrey R, Rossignol Philippe A, van den Driessche P
Department of Fisheries and Wildlife, Oregon State University, 104 Nash Hall, Corvallis, OR 97331-3803, USA.
J Theor Biol. 2008 Nov 7;255(1):16-25. doi: 10.1016/j.jtbi.2008.07.033. Epub 2008 Jul 30.
The theoretical underpinning of our struggle with vector-borne disease, and still our strongest tool, remains the basic reproduction number, R(0), the measure of long term endemicity. Despite its widespread application, R(0) does not address the dynamics of epidemics in a model that has an endemic equilibrium. We use the concept of reactivity to derive a threshold index for epidemicity, E(0), which gives the maximum number of new infections produced by an infective individual at a disease free equilibrium. This index describes the transitory behavior of disease following a temporary perturbation in prevalence. We demonstrate that if the threshold for epidemicity is surpassed, then an epidemic peak can occur, that is, prevalence can increase further, even when the disease is not endemic and so dies out. The relative influence of parameters on E(0) and R(0) may differ and lead to different strategies for control. We apply this new threshold index for epidemicity to models of vector-borne disease because these models have a long history of mathematical analysis and application. We find that both the transmission efficiency from hosts to vectors and the vector-host ratio may have a stronger effect on epidemicity than endemicity. The duration of the extrinsic incubation period required by the pathogen to transform an infected vector to an infectious vector, however, may have a stronger effect on endemicity than epidemicity. We use the index E(0) to examine how vector behavior affects epidemicity. We find that parasite modified behavior, feeding bias by vectors for infected hosts, and heterogeneous host attractiveness contribute significantly to transitory epidemics. We anticipate that the epidemicity index will lead to a reevaluation of control strategies for vector-borne disease and be applicable to other disease transmission models.
我们与媒介传播疾病作斗争的理论基础,也是我们目前最有力的工具,仍然是基本再生数R(0),即长期地方性流行程度的衡量指标。尽管R(0)得到了广泛应用,但在具有地方病平衡点的模型中,它并未涉及流行病的动态变化。我们利用反应性的概念推导出一个流行病阈值指数E(0),该指数表示在无病平衡点上,一个感染个体所能产生的新感染的最大数量。这个指数描述了患病率受到暂时扰动后疾病的短暂行为。我们证明,如果超过了流行病阈值,那么就可能出现疫情高峰,也就是说,即使该疾病并非地方性流行且最终会消失,患病率仍可能进一步上升。参数对E(0)和R(0)的相对影响可能不同,从而导致不同的控制策略。我们将这个新的流行病阈值指数应用于媒介传播疾病模型,因为这些模型有着悠久的数学分析和应用历史。我们发现,从宿主到媒介的传播效率以及媒介与宿主的比例对流行病的影响可能比对地方性流行的影响更强。然而,病原体将受感染媒介转变为感染性媒介所需的外在潜伏期的持续时间,对地方性流行的影响可能比对流行病的影响更强。我们利用指数E(0)来研究媒介行为如何影响流行病。我们发现,寄生虫改变的行为、媒介对受感染宿主的摄食偏好以及宿主的异质性吸引力对短暂性流行病有显著影响。我们预计,这个流行病指数将促使人们重新评估媒介传播疾病的控制策略,并适用于其他疾病传播模型。