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建立与尼日利亚阿布贾犬咬伤自我报告受害者狂犬病死亡概率相关的可改变因素模型。

Modelling modifiable factors associated with the probability of human rabies deaths among self-reported victims of dog bites in Abuja, Nigeria.

机构信息

School of Veterinary Science, The University of Queensland, Gatton, Australia.

Department of Veterinary Medicine, Faculty of Veterinary Medicine, University of Abuja, Abuja, Nigeria.

出版信息

PLoS Negl Trop Dis. 2023 Feb 21;17(2):e0011147. doi: 10.1371/journal.pntd.0011147. eCollection 2023 Feb.

Abstract

Canine-mediated rabies kills tens of thousands of people annually in lesser-developed communities of Asia, Africa, and the Americas, primarily through bites from infected dogs. Multiple rabies outbreaks have been associated with human deaths in Nigeria. However, the lack of quality data on human rabies hinders advocacy and resource allocation for effective prevention and control. We obtained 20 years of dog bite surveillance data across 19 major hospitals in Abuja, incorporating modifiable and environmental covariates. To overcome the challenge of missing information, we used a Bayesian approach with expert-solicited prior information to jointly model missing covariate data and the additive effects of the covariates on the predicted probability of human death after rabies virus exposure. Only 1155 cases of dog bites were recorded throughout the study period, out of which 4.2% (N = 49) died of rabies. The odds for risk of human death were predicted to decrease among individuals who were bitten by owned dogs compared to those bitten by free-roaming dogs. Similarly, there was a predicted decrease in the probability of human death among victims bitten by vaccinated dogs compared to those bitten by unvaccinated dogs. The odds for the risk of human death after bitten individuals received rabies prophylaxis were predicted to decrease compared to no prophylaxis. We demonstrate the practical application of a regularised Bayesian approach to model sparse dog bite surveillance data to uncover risk factors for human rabies, with broader applications in other endemic rabies settings with similar profiles. The low reporting observed in this study underscores the need for community engagement and investment in surveillance to increase data availability. Better data on bite cases will help to estimate the burden of rabies in Nigeria and would be important to plan effective prevention and control of this disease.

摘要

在亚洲、非洲和美洲的欠发达社区,犬类传播的狂犬病每年导致数万人死亡,主要是通过感染狂犬病的狗咬伤。在尼日利亚,多次狂犬病疫情都与人类死亡有关。然而,由于缺乏关于人类狂犬病的高质量数据,阻碍了为有效预防和控制狂犬病而进行的宣传和资源分配。我们获得了阿布贾 19 家主要医院 20 年的犬咬伤监测数据,其中包含可修改和环境协变量。为了克服信息缺失的挑战,我们使用了贝叶斯方法,利用专家征求的先验信息,共同对缺失的协变量数据和协变量对狂犬病病毒暴露后人类死亡的预测概率的附加效应进行建模。在整个研究期间,仅记录了 1155 例犬咬伤病例,其中 4.2%(N=49)死于狂犬病。与被流浪狗咬伤的个体相比,被自己饲养的狗咬伤的个体死亡风险的几率预计会降低。同样,与未接种疫苗的狗相比,接种疫苗的狗咬伤的受害者死亡的概率预计会降低。与未接受狂犬病预防的个体相比,接受狂犬病预防的个体的死亡风险几率预计会降低。我们展示了正则化贝叶斯方法在稀疏犬咬伤监测数据建模中的实际应用,以揭示人类狂犬病的风险因素,在其他具有类似特征的狂犬病流行地区也有更广泛的应用。本研究中观察到的低报告率强调了社区参与和对监测的投资的必要性,以增加数据的可获得性。更好的咬伤病例数据将有助于估计尼日利亚的狂犬病负担,并对规划这种疾病的有效预防和控制非常重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2c7/9983858/1098099385b9/pntd.0011147.g001.jpg

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