کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7495795 1485753 2018 21 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A Bayesian spatio-temporal framework to identify outbreaks and examine environmental and social risk factors for infectious diseases monitored by routine surveillance
ترجمه فارسی عنوان
یک چارچوب فضایی و زمانی بیزی برای شناسایی شیوع بیماری و بررسی عوامل خطر زیست محیطی و اجتماعی برای بیماری های عفونی تحت نظارت معمول
کلمات کلیدی
موضوعات مرتبط
علوم پزشکی و سلامت پزشکی و دندانپزشکی سیاست های بهداشت و سلامت عمومی
چکیده انگلیسی
Spatio-temporal disease patterns can provide clues to etiological pathways, but can be complex to model. Using a flexible Bayesian hierarchical framework, we identify previously undetected space-time clusters and environmental and socio-demographic risk factors for reported giardiasis and cryptosporidiosis at the New Zealand small area level. For giardiasis, there was no seasonal pattern in outbreak probability and an inverse association with density of dairy cattle (β^1 = −0.09, Incidence Risk Ratio (IRR) 0.90 (95% CI 0.84, 0.97) per 1 log increase in cattle/km2). In dairy farming areas, cryptosporidiosis outbreaks were observed in spring. Reported cryptosporidiosis was positively associated with dairy cattle density: β^1 = 0.12, IRR 1.13 (95% CI 1.05, 1.21) per 1 log increase in cattle/km2 and inversely associated with weekly average temperature: β^1 = −0.07, IRR 0.92 (95% CI 0.87, 0.98) per 4 °C increase. This framework can be generalized to determine the potential drivers of sporadic cases and latent outbreaks of infectious diseases of public health importance.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Spatial and Spatio-temporal Epidemiology - Volume 25, June 2018, Pages 39-48
نویسندگان
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