Quantitative microbial risk assessment of outdoor aerosolized pathogens in cities with poor sanitation
Quantitative microbial risk assessment of outdoor aerosolized pathogens in cities with poor sanitation
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DOI：
10.1016/j.scitotenv.2022.154233
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发表时间：
2022-03-10
影响因子：
9.8
通讯作者：
Deshusses，Marc A.
中科院分区：
文献类型：
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作者：
Rocha-Melogno，Lucas;Crank，Katherine C.;Deshusses，Marc A.
在卫生服务不安全的地方，肠道病原体的空气微生物传播途径知之甚少。为了部分填补这一知识空白，我们使用定量微生物风险评估(QMRA)评估了开放废旧运河(OWCs)附近生物气溶胶对公众健康的潜在影响。我们使用在玻利维亚拉巴斯获得的数据来表征气雾化肠道病原体可能通过食物、代谢物和吸入(所有这些都随后是摄入)构成的疾病风险。选择了三种参考病原菌进行评估：肠毒素大肠杆菌(ETEC)、福氏志贺氏菌和空肠弯曲杆菌。与受污染的食物(如5×10−6和2×10−7)相比，吸入后再摄入的感染风险中位数最高，为3×10−5(每100,000次接触3例感染)。雏菊感染。我们的敏感性分析表明，空气中的细菌通量是对风险影响最大的因素。我们的结果表明，在拉巴斯，来自OWCs的粪便细菌气溶胶存在不可忽视的感染风险，C。比环保局的饮用水标准(1×10−4)高出18倍(食物)和100倍(吸入)。我们在为不同环境中的用户指定应用程序开发的新型Web应用程序中包含了此处提供的两个QMRA模型。
The aeromicrobiological transmission pathway of enteric pathogens in places with unsafe sanitation services is poorly understood. In an attempt to partly fill this knowledge gap, we assessed the potential public health impact of bioaerosols near open waste canals (OWCs) using Quantitative Microbial Risk Assessment (QMRA). We used data acquired in La Paz, Bolivia to characterize the risk of disease that aerosolized enteric pathogens may pose through food, fomites and inhalation (all followed by ingestion). Three reference pathogens were selected to conduct the assessment: enterotoxigenicEscherichia coli(ETEC),Shigella flexneri,andCampylobacter jejuni. Inhalation followed by ingestion had the highest median infection risk per event i.e. 3 × 10−5(3 infections for every 100,000 exposures),compared to contaminated food e.g. 5 × 10−6and fomites e.g. 2 × 10−7, all forC. jejuniinfections. Our sensitivity analysis showed that bacterial fluxes from the air were the most influential factor on risk. Our results suggest that fecal bacterial aerosols from OWCs present non-negligible risks of infection in La Paz, with median annual infection risks byC. jejunibeing 18 (food), and 100 (inhalation) times greater than the EPA's standard for drinking water (1 × 10−4). We included two of the QMRA models presented here in a novel web application we developed for user-specified application in different contexts.