Applying Association Mining and Group Based Trajectory Analyses to Characterize Spatial Temporal Trends of Community-Onset Antibiotic Resistant Staphylococcus aureus Infections in Children

应用关联挖掘和基于群体的轨迹分析来表征儿童社区发病的抗生素耐药性金黄色葡萄球菌感染的时空趋势

• 批准号: 10800503
• 负责人: Lilly Hsi-Chih Immergluck
• 金额: $ 31.48万
• 依托单位: MOREHOUSE SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-07-07 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10800503
• 关键词: Address; African American; African American population; Antibiotic Resistance; Antibiotics; Area; Bacterial Antibiotic Resistance; Black Populations; Black race; Center for Translational Science Activities; Cessation of life; Child; Childhood; Chronic; Clindamycin; Clinical stratification; Communities; Coupled; Disparity; Economic Burden; Elderly; Enrollment; Epidemic; Epitopes; Genotype; Geographic Locations; Germ; Hospitals; Human; Human Microbiome; Indigenous; Infection; Influenza; Knowledge; Lactams; Link; Longevity; Maps; Mediating; Methicillin; Methicillin Resistance; Methods; Mining; Modeling; Molecular; Molecular Profiling; Monobactams; Multi-Drug Resistance; Multiple Bacterial Drug Resistance; Nature; Neighborhoods; Outpatients; Patients; Pattern; Persons; Phenotype; Predisposition; Process; Public Health; Recurrence; Recurrent disease; Research; Resistance; Risk; Risk Factors; Skin; Skin Tissue; Soft Tissue Infections; Source; Specificity; Staphylococcal Vaccines; Staphylococcus aureus; Staphylococcus aureus infection; Statistical Models; Time; Time trend; Virulent; Work; antibiotic resistant infections; antimicrobial; antimicrobial drug; bacterial resistance; beta-Lactam Resistance; beta-Lactams; commensal bacteria; community burden; community setting; experience; foodborne illness; health disparity; human microbiota; infection management; methicillin resistant Staphylococcus aureus; metropolitan; microbiome; pathogen; pressure; prevent; prospective; rate of change; recurrent infection; transmission process; trend; trend analysis; vaccine candidate

Abstract Staphylococcus aureus (S. aureus) remains a leading cause of infections, especially in the outpatient setting where it is the primary cause of skin and soft tissue infections (SSTI). S. aureus also is a commensal bacterium, known to colonize 25-40% of humans and is therefore, part of the human microbiome. In the late 1990s, a new clonal lineage emerged making S. aureus the source of epidemic proportions of community associated infections across the lifespan, with an increased risk among African American and indigenous children and older adults. Over time, the landscape of the antibiotic resistance changed, likely due to multifactorial processes, including the overprescribing of non β-lactam antibiotics (resistance to β-lactam class is the hall mark of methicillin resistant S. aureus (MRSA)).Two decades later, both non β-lactam S. aureus (methicillin sensitive or MSSA) and MRSA have gained additional resistance to other antibiotic classes, making S. aureus a multi drug resistant (MDR) bacteria and one of the top antibiotic resistant germs causing severe illnesses nationally and worldwide. While it has been well known that health disparities exist for MRSA, the disparities seen with community originated forms of MDR S. aureus (and risk factors associated with this strain) are different than those MDR S. aureus which originated from hospital settings. Socioecological conditions play a role in the risks seen with community-based infections. Our study proposes to use association mining of antibiotic resistant phenotypes seen with S. aureus with spatial trend analyses to detect transmission patterns over time and areas. Applying multi-level spatially relevant group- based trajectory modeling will allow us to detect ‘subtle’ changes in MDR patterns that occur over time, and delineate geographic areas associated with MDR patterns. Results generated by this research will contribute to current the knowledge on community-based S. aureus strains (the genotype and its associated phenotypes) which cause SSTI and additionally, address the gap of identifying the factors contributing to recurrence of these SSTI. Understanding strain specificity will serve as the basis to prevent the spread of antibiotic resistant S. aureus infections in community settings and help identify S. aureus antigenic determinants which potentially can serve as staphylococcal vaccine candidates. This study has the potential to curb the upward trajectory and increasing public health threat posed by this multi-drug resistant bacteria.

抽象的 金黄色葡萄球菌（金黄色葡萄球菌）仍然是感染的主要原因，尤其是在 皮肤和软组织感染的主要原因的门诊环境 （SSTI）。 人类，是从1990年代后期的人类微波经的一部分 谱系出现了，使金黄色葡萄球菌成为社区流行比例的来源 整个生命周期的相关感染，非洲风险增加 随着时间的流逝，美国和土著儿童和老年人。 抗生素抗性发生了变化，可能是由于多因素过程所致 大厅标记是大厅 甲氧西林的金黄色葡萄球菌（MRSA）。 金黄色葡萄球菌（甲氧西林敏感或MSSA）和MRSA已获得对 其他抗生素类别，使金黄色葡萄球菌成为多药耐药（MDR）细菌和 最高的抗生素耐药菌之一，导致严重的Ilnessessess sessesses s 在全球范围内。 MDR S.金黄色葡萄酒的社区起源形式（和风险因素） 与theis菌株相关的）不同于那些起源的金黄色葡萄球菌 从医院环境中 基于社区的感染。 具有空间趋势分析的金黄色葡萄球菌观察到的抗性表型可检测 随着时间和区域的传输模式。 基于基于的轨迹建模将我们检测MDR模式的“微妙”变化 随着时间的流逝发生，并描绘了与MDR模式相关的地理区域。 这项研究产生的结果有助于当前有关 基于社区的金黄色葡萄球菌菌株（基因型及其相关表型） 这是导致SSTI的，另外，解决了识别因素的差距 有助于理解应变特异性的复发。 防止抗生素抗生素链球菌感染在社区中传播的基础 设置并有助于识别金黄色葡萄球菌抗原药，可能会服务 随着葡萄球菌疫苗的候选物。 这种多药抗性的vactteria构成的轨迹和增加的公共卫生线程威胁。