Chigozie Louisa J Ugwu, Ali Asgary, Jianhong Wu, Jude Dzevela Kong, Nicola Luigi Bragazzi, James Orbinski, Woldegebriel Assefa Woldegerima
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引用次数: 0
Abstract
Background: Ontario, being one of Canada's largest provinces, has been central to the high incidence of human Mpox. Research is scarce on how socio-environmental factors influence Mpox incidences. This study seeks to explore potential geographical correlations and the relationship between indicators of social marginalization and Mpox incidence rate in Ontario.
Methodology: We used surveillance data on confirmed human Mpox cases from May 1, 2022, to March 31, 2024, extracted from the Public Health Ontario website for this study. Spatial autocorrelation of Mpox incidence was investigated using spatial methods including Moran's Index, Getis-Ord Gi*statistic, and spatial Poisson scan statistic. Following this, we adopted a generalized Poisson regression (GPR) model to estimate the incidence rate ratios (IRRs) based on the association between Ontario PHU-level marginalization and Mpox incidence, while adjusting for age and sex. The goodness-of-fit of the models was assessed using the Log Likelihood (LL), Akaike Information Criterion (AIC), Akaike's Information Criterion corrected (AICc), and the Bayesian Information Criterion (BIC).
Results: Our analysis revealed significant localized spatial heterogeneity in Mpox incidence across Ontario. Statistically significant local clusters of Mpox cases were identified in Toronto ([Formula: see text] ), Ottawa ([Formula: see text]), and a secondary cluster, overlapping Hamilton PHU with nine local districts ([Formula: see text]), all with [Formula: see text]. The incidence rate of Mpox was statistically significantly associated with a higher proportion of ethnic concentration (racialized groups, migrants, or visible minorities) [Formula: see text], gender [Formula: see text] and higher residential instability [Formula: see text].
Conclusion: We identified major Mpox hotspots in Toronto. According to our model results, the high incidence rate may be influenced by the greater population of internal migrants and younger individuals. Based on these insights, we recommend targeted interventions in the high-risk neighborhoods. Efforts to improve Mpox diagnosis and promote health equity among socioeconomically vulnerable populations, including racial and ethnic minorities, should be implemented.
背景:安大略省是加拿大最大的省份之一,也是人类麻疹高发地区的中心。关于社会环境因素如何影响麻疹发病率的研究很少。本研究旨在探讨安大略省社会边缘化指标与Mpox发病率之间的潜在地理相关性和关系。方法:我们使用从安大略省公共卫生部网站提取的2022年5月1日至2024年3月31日确认的人痘病例的监测数据进行本研究。采用Moran's指数、Getis-Ord Gi*统计量和泊松扫描统计量等空间方法研究Mpox发病率的空间自相关性。在此基础上,我们采用广义泊松回归(GPR)模型,在调整年龄和性别的基础上,基于安大略省phu水平边缘化与Mpox发病率之间的关系来估计发病率比(IRRs)。采用对数似然(Log Likelihood, LL)、赤池信息准则(Akaike Information Criterion, AIC)、赤池信息准则修正(Akaike’s Information Criterion, AICc)和贝叶斯信息准则(Bayesian Information Criterion, BIC)对模型的拟合优度进行评估。结果:我们的分析显示安大略省m痘发病率存在显著的局部空间异质性。在多伦多([公式:见文本])、渥太华([公式:见文本])和汉密尔顿PHU与9个地方地区重叠的二级聚集性([公式:见文本])发现了具有统计意义的地方痘病例聚集性,所有这些地区都有[公式:见文本]。Mpox的发病率在统计上与较高比例的种族集中(种族化群体、移民或少数族裔)、性别(公式:见文本)和较高的居住不稳定性(公式:见文本)显著相关。结论:我们确定了多伦多主要的Mpox热点地区。根据我们的模型结果,高发病率可能受到更多的内部流动人口和年轻个体的影响。基于这些见解,我们建议在高危社区进行有针对性的干预。应努力改善Mpox诊断并促进社会经济弱势群体(包括种族和族裔少数群体)的卫生公平。
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