Parameterisation of a bluetongue virus mathematical model using a systematic literature review

IF 2.2 2区 农林科学 Q1 VETERINARY SCIENCES
Joanna de Klerk , Michael Tildesley , Adam Robbins , Erin Gorsich
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引用次数: 0

Abstract

Bluetongue virus (BT) is a vector-borne virus that causes a disease, called bluetongue, which results in significant economic loss and morbidity in sheep, cattle, goats and wild ungulates across all continents of the world except Antarctica. Despite the geographical breadth of its impact, most BT epidemiological models are informed by parameters derived from the 2006–2009 BTV-8 European outbreak. The aim of this study was to develop a highly adaptable model for BT which could be used elsewhere in the world, as well as to identify the parameters which most influence outbreak dynamics, so that policy makers can be properly informed with the most current information to aid in disease planning.

To provide a framework for future outbreak modelling and an updated parameterisation that reflects natural variation in infections, a newly developed and parameterised two-host, two-vector species ordinary differential equation model was formulated and analysed. The model was designed to be adaptable to be implemented in any region of the world and able to model both epidemic and endemic scenarios. It was parameterised using a systematic literature review of host-to-vector and vector-to-host transmission rates, host latent periods, host infectious periods, and vaccine protection factors. The model was demonstrated using the updated parameters, with South Africa as a setting based on the Western Cape’s known cattle and sheep populations, local environmental parameters, and Culicoides spp. presence data.

The sensitivity analysis identified that the duration of the infectious period for sheep and cows had the greatest impact on the outbreak length and number of animals infected at the peak of the outbreak. Transmission rates from cows and sheep to C. imicola midges greatly influenced the day on which the peak of the outbreak occurred, along with the duration of incubation period, and infectious period for cows. Finally, the protection factor of the vaccine had the greatest influence on the total number of animals infected. This knowledge could aid in the development of control measures.

Due to gradual climate and anthropological change resulting in alterations in vector habitat suitability, BT outbreaks are likely to continue to increase in range and frequency. Therefore, this research provides an updated BT modelling framework for future outbreaks around the world to explore transmission, outbreak dynamics and control measures.

利用系统文献综述为蓝舌病病毒数学模型设定参数
蓝舌病病毒(BT)是一种通过病媒传播的病毒,可导致一种名为蓝舌病的疾病,给除南极洲以外的世界各大洲的绵羊、牛、山羊和野生动物造成重大经济损失和发病率。尽管蓝舌病影响的地域范围很广,但大多数蓝舌病流行病学模型都是根据 2006-2009 年 BTV-8 欧洲疫情得出的参数建立的。为了给未来的疫情建模提供一个框架,并更新参数以反映感染的自然变化,我们制定并分析了一个新开发的、参数化的双宿主、双载体物种常微分方程模型。设计该模型的目的是使其能够在世界任何地区实施,并能够模拟流行病和地方病的情况。通过对宿主到病媒和病媒到宿主的传播率、宿主潜伏期、宿主感染期和疫苗保护因子进行系统的文献综述,对模型进行了参数化。根据西开普省已知的牛羊种群、当地环境参数和库利科德虫属的存在数据,以南非为背景,使用更新后的参数对模型进行了演示。奶牛和绵羊向伊米柯拉蠓的传播率以及潜伏期和奶牛感染期的长短在很大程度上影响了疫情高峰出现的日期。最后,疫苗的保护因子对感染动物的总数影响最大。由于气候和人类活动的逐渐变化导致病媒栖息地适宜性的改变,BT 爆发的范围和频率可能会继续增加。因此,这项研究为未来世界各地爆发的 BT 提供了一个最新的建模框架,以探索传播、爆发动态和控制措施。
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来源期刊
Preventive veterinary medicine
Preventive veterinary medicine 农林科学-兽医学
CiteScore
5.60
自引率
7.70%
发文量
184
审稿时长
3 months
期刊介绍: Preventive Veterinary Medicine is one of the leading international resources for scientific reports on animal health programs and preventive veterinary medicine. The journal follows the guidelines for standardizing and strengthening the reporting of biomedical research which are available from the CONSORT, MOOSE, PRISMA, REFLECT, STARD, and STROBE statements. The journal focuses on: Epidemiology of health events relevant to domestic and wild animals; Economic impacts of epidemic and endemic animal and zoonotic diseases; Latest methods and approaches in veterinary epidemiology; Disease and infection control or eradication measures; The "One Health" concept and the relationships between veterinary medicine, human health, animal-production systems, and the environment; Development of new techniques in surveillance systems and diagnosis; Evaluation and control of diseases in animal populations.
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