Livestock production losses attributable to brucellosis in northern and central Tanzania: Application of an epidemiological-economic modelling framework.

IF 3.4 2区 医学 Q1 PARASITOLOGY
PLoS Neglected Tropical Diseases Pub Date : 2025-02-14 eCollection Date: 2025-02-01 DOI:10.1371/journal.pntd.0012814
Ângelo J F Mendes, Daniel T Haydon, William A de Glanville, Rebecca F Bodenham, AbdulHamid S Lukambagire, Paul C D Johnson, Gabriel M Shirima, Sarah Cleaveland, Emma McIntosh, Nick Hanley, Jo E B Halliday
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引用次数: 0

Abstract

Livestock brucellosis is an endemic disease in many low-resource settings. Despite its widespread distribution, little is known about the scale of economic impacts caused by the disease. This study aimed to develop an integrated epidemiological-economic modelling framework to estimate production losses attributable to livestock brucellosis, using Tanzania as a case study. Data on livestock production and prevalence of exposure to Brucella spp. were obtained from surveys conducted in northern and central Tanzania between 2013 and 2019. A clustering algorithm was applied to classify households into pastoral and non-pastoral production systems. A Bayesian latent-class analysis model was applied to derive livestock brucellosis prevalence estimates. A herd-growth model was used to estimate production losses attributable to brucellosis. A total of 1,541 households (384 classified as pastoral and 1,157 as non-pastoral) contributed data on livestock production or prevalence of exposure to Brucella spp. The median (95% uncertainty interval, UI) individual-level brucellosis prevalence in cattle, sheep, and goats was 5.1% (3.4-6.9), 1.3% (0.1-3.0), and 2.5% (0.3-4.8) in the pastoral system, and 0.7% (0.1-1.6), 1.6% (0.2-3.8), and 2.5% (0.3-4.9) in the non-pastoral system, respectively. The median (95% UI) annual losses attributable to brucellosis in cattle, sheep, and goats, per infected animal, were 74.4 (26.2-211.7), 9.7 (3.4-23.1) and 10.6 (3.7-25.0) international dollars (int. $) in the pastoral system, and 62.3 (16.8-228.6), 6.3 (1.8-17.1) and 7.0 (2.2-17.9) int. $ in the non-pastoral system, respectively. Household-level losses were equivalent to 4.4% (2.1-8.8) and 0.6% (0.2-1.6) of the median (95% UI) livestock-derived income in the pastoral and non-pastoral systems, respectively. This study did not capture the system-wide impacts of brucellosis, including on human health. The estimated losses are only a part of the full societal economic impact of the disease. These results can be used to inform cost-benefit analyses of potential interventions and guide policy development for brucellosis control.

坦桑尼亚北部和中部因布鲁氏菌病造成的牲畜生产损失:流行病学-经济建模框架的应用。
牲畜布鲁氏菌病是许多资源匮乏地区的地方病。尽管该病分布广泛,但人们对该病造成的经济影响的规模知之甚少。这项研究的目的是建立一个综合流行病学-经济建模框架,以坦桑尼亚为案例研究,估计牲畜布鲁氏菌病造成的生产损失。从2013年至2019年在坦桑尼亚北部和中部进行的调查中获得了关于畜牧生产和布鲁氏菌感染流行率的数据。采用聚类算法将农户划分为牧区生产系统和非牧区生产系统。应用贝叶斯潜类分析模型来估计家畜布鲁氏菌病的流行情况。使用畜群生长模型来估计布鲁氏菌病造成的生产损失。共有1541户家庭(384户为牧区,1157户为非牧区)提供了有关畜牧生产或布鲁氏菌暴露流行率的数据。牛、绵羊和山羊的个体水平布鲁氏菌病流行率中位数(95%不确定区间,UI)在牧区系统中分别为5.1%(3.4-6.9)、1.3%(0.1-3.0)和2.5%(0.3-4.8),在非牧区系统中分别为0.7%(0.1-1.6)、1.6%(0.2-3.8)和2.5%(0.3-4.9)。每只感染牛、绵羊和山羊因布鲁氏菌病造成的年损失中位数(95% UI)分别为74.4(26.2-211.7)、9.7(3.4-23.1)和10.6(3.7-25.0)国际美元。$),以及62.3(16.8-228.6),6.3(1.8-17.1)和7.0 (2.2-17.9)int。$在非牧区系统中分别。在畜牧和非畜牧系统中,家庭层面的损失分别相当于牲畜收入中位数(95% UI)的4.4%(2.1-8.8)和0.6%(0.2-1.6)。这项研究没有捕捉到布鲁氏菌病的全系统影响,包括对人类健康的影响。估计的损失只是该疾病全部社会经济影响的一部分。这些结果可用于为潜在干预措施的成本效益分析提供信息,并指导布鲁氏菌病控制的政策制定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
PLoS Neglected Tropical Diseases
PLoS Neglected Tropical Diseases PARASITOLOGY-TROPICAL MEDICINE
自引率
10.50%
发文量
723
期刊介绍: PLOS Neglected Tropical Diseases publishes research devoted to the pathology, epidemiology, prevention, treatment and control of the neglected tropical diseases (NTDs), as well as relevant public policy. The NTDs are defined as a group of poverty-promoting chronic infectious diseases, which primarily occur in rural areas and poor urban areas of low-income and middle-income countries. Their impact on child health and development, pregnancy, and worker productivity, as well as their stigmatizing features limit economic stability. All aspects of these diseases are considered, including: Pathogenesis Clinical features Pharmacology and treatment Diagnosis Epidemiology Vector biology Vaccinology and prevention Demographic, ecological and social determinants Public health and policy aspects (including cost-effectiveness analyses).
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