Modeling the environmental suitability of anthrax in Ghana and estimating populations at risk: Implications for vaccination and control.
Modeling the environmental suitability of anthrax in Ghana and estimating populations at risk: Implications for vaccination and control.
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DOI：
10.1371/journal.pntd.0005885
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发表时间：
2017-10
影响因子：
3.8
通讯作者：
Blackburn JK
中科院分区：
文献类型：
--
作者：
Kracalik IT;Kenu E;Ayamdooh EN;Allegye-Cudjoe E;Polkuu PN;Frimpong JA;Nyarko KM;Bower WA;Traxler R;Blackburn JK
炭疽病在西非高度流行。尽管牲畜疫苗在控制炭疽方面有效，但报告不足、后勤和资源有限使疫苗接种活动难以实施。为了更好地了解炭疽的地理限制，阐明与其发生相关的环境因素，并确定处于风险中的人类和牲畜种群，我们开发了加纳炭疽环境适宜性的预测模型。我们从2005-2016年期间加纳的兽医和疫情应对记录中获得了关于牲畜炭疽的位置和日期的数据，以及牲畜疫苗接种登记和典型高风险群体的人口估计。为了预测炭疽的环境适应性，我们使用了一个随机森林（RF）模型的集合，该模型结合了气候和环境因素。从2005年到2016年前六个月，牲畜中发生了67起炭疽疫情（851例）;疫情在2月至4月期间出现季节性高峰，主要涉及牛。每年接种的疫苗剂量中位数为19，709剂[范围：0- 17.5万]。RF模型的结果表明，加纳北方与该国南部存在明显的生态分界线，将环境适宜的广大地区分隔开来。碱性土壤pH值的增加与炭疽发生的可能性较高。我们估计有220万（95% CI：2.0，2.5）万头牲畜和80.5万（95% CI：519，890）万低收入农村牲畜饲养者位于炭疽风险地区。根据我们的估计，加纳目前的炭疽疫苗接种工作覆盖了一小部分潜在风险的牲畜，因此控制工作应集中在提高高危人群的疫苗覆盖率。炭疽病是一种由土壤传播的人畜共患疾病，在世界各地都有发现。在西非国家加纳，炭疽疫情每年都会爆发，给牲畜饲养者及其动物带来沉重负担。为了控制人类和动物的炭疽病，建议在流行地区每年为牲畜接种疫苗。然而，在资源贫乏的地区，分发和管理疫苗是困难的，部分原因是报告不足，后勤问题，资源有限，以及对炭疽风险区的地理范围的认识不足。我们的目标是使用机器学习算法（随机森林）对在加纳收集的高空间分辨率炭疽疫情数据进行建模。为了实现这一目标，我们使用了气候和环境特征的组合来预测炭疽的潜在环境适应性，绘制其分布图，并确定处于风险中的牲畜和人群。结果表明，一个显着的生态分界线分离的广泛地区的环境适宜性在加纳北方从该国南部，这密切反映了从南部热带和落叶林过渡到北方苏丹和几内亚稀树草原的生态过渡带。根据我们的模型预测，我们估计有超过300万反刍家畜和低收入家畜饲养者位于炭疽风险区。这些发现表明，高风险群体中的年度牲畜疫苗接种覆盖率较低。因此，需要从兽医和人类卫生部门整合控制战略，以改善监测，增加疫苗的传播和加纳及周边地区农村牲畜饲养者的采用。
Anthrax is hyper-endemic in West Africa. Despite the effectiveness of livestock vaccines in controlling anthrax, underreporting, logistics, and limited resources makes implementing vaccination campaigns difficult. To better understand the geographic limits of anthrax, elucidate environmental factors related to its occurrence, and identify human and livestock populations at risk, we developed predictive models of the environmental suitability of anthrax in Ghana. We obtained data on the location and date of livestock anthrax from veterinary and outbreak response records in Ghana during 2005–2016, as well as livestock vaccination registers and population estimates of characteristically high-risk groups. To predict the environmental suitability of anthrax, we used an ensemble of random forest (RF) models built using a combination of climatic and environmental factors. From 2005 through the first six months of 2016, there were 67 anthrax outbreaks (851 cases) in livestock; outbreaks showed a seasonal peak during February through April and primarily involved cattle. There was a median of 19,709 vaccine doses [range: 0–175 thousand] administered annually. Results from the RF model suggest a marked ecological divide separating the broad areas of environmental suitability in northern Ghana from the southern part of the country. Increasing alkaline soil pH was associated with a higher probability of anthrax occurrence. We estimated 2.2 (95% CI: 2.0, 2.5) million livestock and 805 (95% CI: 519, 890) thousand low income rural livestock keepers were located in anthrax risk areas. Based on our estimates, the current anthrax vaccination efforts in Ghana cover a fraction of the livestock potentially at risk, thus control efforts should be focused on improving vaccine coverage among high risk groups. Anthrax is a soil-borne zoonotic disease found worldwide. In the West African nation of Ghana, anthrax outbreaks occur annually with a high burden to livestock keepers and their animals. To control anthrax in both humans and animals, annual livestock vaccination is recommended in endemic regions. However, in resource poor areas distributing and administering vaccine is difficult, in part, due to underreporting, logistical issues, limited resources, and an under appreciation of the geographic extent of anthrax risk zones. Our objective was to model high spatial resolution anthrax outbreak data, collected in Ghana, using a machine learning algorithm (random forest). To achieve this, we used a combination of climatic and environmental characteristics to predict the potential environmental suitability of anthrax, map its distribution, and identify livestock and human populations at risk. Results indicate a marked ecological divide separating the broad areas of environmental suitability in northern Ghana from the southern part of the country, which closely mirrors the ecotone transitions from southern tropical and deciduous forests to the northern Sudanian and Guinea Savanna. Based on our model prediction, we estimated >3 million combined ruminant livestock and low income livestock keepers are situated in anthrax risk zones. These findings suggest a low level of annual livestock vaccination coverage among high risk groups. Thus, integrating control strategies from both the veterinary and human health sectors are needed to improve surveillance and increase vaccine dissemination and adoption by rural livestock keepers in Ghana and the surrounding region.