Clinical Epidemiology of Pediatric COVID-19 and MIS-C

儿科 COVID-19 和 MIS-C 的临床流行病学

基本信息

批准号：
10633081
负责人：
Carlos Rafael Oliveira
金额：
$ 17.7万
依托单位：
YALE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-05-01 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10633081
关键词：
18 year old 2019-nCoV Accident and Emergency department Adult Affect Algorithms COVID-19 COVID-19 patient COVID-19 severity COVID-19 surveillance Caring Child Child Care Childhood Clinic Clinical Clinical Data Communicable Diseases Complement Country Critical Illness Cross-Sectional Studies Data Data Analyses Data Science Data Set Detection Deterioration Diagnosis Discipline Disease Educational workshop Electronic Health Record Emerging Communicable Diseases Emotional Enrollment Epidemiology Failure Frequencies Fright Functional disorder Funding Future Goals Health Care Costs Health system Hospitalization Hospitalized Child Hospitals Hour Infection Informatics Infrastructure International Intervention Investigation Laboratories Literature Long-Term Effects Longitudinal Studies Longitudinal cohort Longitudinal cohort study Machine Learning Manuals Medical center Mentored Patient-Oriented Research Career Development Award Mentors Mentorship Modeling Multisystem Inflammatory Syndrome in Children Names Natural Language Processing Organ Outcome Patient Self-Report Patient-Focused Outcomes Patients Pediatric epidemiology Phenotype Physicians Policy Maker Protocols documentation Quality of Life Assessment Recovery Registries Reporting Research Research Personnel Respiratory Disease Risk Risk Factors SARS-CoV-2 infection SARS-CoV-2 positive Science Scientist Severities Shock Site Societies Standardization State Hospitals Structure Symptoms Syndrome System Testing Therapeutic Intervention Training United States Ventilator Virus Work biomedical informatics body system clinical care clinical epidemiology clinical predictive model clinical predictors clinical risk cohort computer program computerized tools data access design economic cost experience follow-up future pandemic gradient boosting health related quality of life improved longitudinal analysis machine learning model mathematical model multidisciplinary novel novel coronavirus pandemic disease predictive modeling prevent preventive intervention programs public health relevance recruit severe COVID-19 skills structured data systemic inflammatory response tool unstructured data

项目摘要

PROJECT SUMMARY / ABSTRACT Although the novel Coronavirus (SARS-CoV-2) has accounted for significant health and economic costs throughout the world, relatively little is known about its effect on children. The first pediatric case of SARS- CoV-2 in the United States was reported on March 2, 2020, and within just three months, over 64,000 cases were confirmed. Even though children, as a group, have been relatively spared from the effects of the virus, there has been an increasing body of evidence to suggest that some may become critically ill. Since a number of children with SARS-CoV-2 infections manifest with severe systemic inflammation and multi-organ dysfunction, more research on determinants of disease and long-term outcomes of those affected is critical. Dr. Oliveira is a pediatric infectious disease clinician whose long-term goal is to become an independently funded physician-scientist, who integrates the disciplines of clinical epidemiology, data science, and biomedical informatics to detect and respond to emerging infectious diseases. The work described in this proposal builds on the scientific themes he developed throughout his prior training and aims to mechanistically understand the effects of SARS-CoV-2 in children by integrating three different scientific tools: natural language processing, machine learning, and clinical epidemiology. The first consideration for this K23 award period will be to use novel computational tools to build automated surveillance and data-extraction system that can facilitate the identification and tracking of incident cases of SARS-CoV-2 in children (Aim 1). Using this surveillance system, Dr. Oliveira will create a comprehensive registry and conduct a rigorous, model-based investigation to derive a state-of-the-art prediction model of clinical deterioration in children with SARS-CoV-2 (Aim 2). Last, he will recruit a longitudinal cohort of SARS-Cov-2 and determine the frequency of complications and long-term outcomes after recovery (Aim 3). This mentored research experience will furnish Dr. Oliveira with skills and expertise in various aspects of clinical epidemiology, including the establishment of surveillance systems, conducting longitudinal studies, computer programing, and executing sophisticated analyses of the longitudinal data. Workshops, semester- long courses will complement this practical experience, and one-on-one mentorship by a multidisciplinary team of established, independently funded, internationally respected investigators and pioneers in the fields of epidemiology, infectious diseases, biomedical informatics, and mathematical modeling. After this work, Dr. Oliveira will have produced important science that could improve the care of all the children affected by this pandemic. Furthermore, he will have gained a unique set of skills and built the necessary infrastructure that will allow him to establish a research program integrating the disciplines of clinical epidemiology, data science, and informatics to detect, prevent, and respond to future pandemics.

项目摘要 /摘要尽管新颖的冠状病毒（SARS-COV-2）占了巨大的健康和经济成本在世界范围内，对其对儿童的影响知之甚少。 SARS的第一个小儿病例据报道，美国的COV-2于2020年3月2日报告，在短短三个月内，超过64,000例被确认。即使作为一个小组，儿童也被相对幸免于病毒的影响，但越来越多的证据表明，有些人可能患有重病。由于数字患有SARS-COV-2感染的儿童表现出严重的全身炎症和多器官功能障碍，对受影响者的疾病决定因素和长期结局的更多研究至关重要。奥利维拉（Oliveira）博士是一位儿科传染病临床医生，其长期目标是成为独立的资助的医师科学家，整合了临床流行病学，数据科学和生物医学学科信息学以检测和应对新兴的传染病。该提案中描述的工作是关于他在他先前培训的整个科学主题，并旨在机械理解 SARS-COV-2在儿童中的影响通过整合三种不同的科学工具：自然语言处理，机器学习和临床流行病学。这个K23奖励期的首次考虑是使用构建自动监视和数据算术系统的新型计算工具，可以促进儿童SARS-COV-2事件案例的识别和跟踪（AIM 1）。使用此监视系统， Oliveira博士将创建一个全面的注册表，并进行严格的基于模型的调查，以得出A SARS-COV-2儿童临床恶化的最新预测模型（AIM 2）。最后，他会的招募SARS-COV-2的纵向队列，并确定并发症的频率和长期恢复后的结果（AIM 3）。这项受过指导的研究经验将为Oliveira博士提供技能和专业知识临床流行病学，包括建立监视系统，进行纵向研究，计算机编程，并执行纵向数据的复杂分析。讲习班，学期 - 长课程将补充这种实用的经验，并由多学科团队进行一对一的指导在该领域的成熟，独立资助，国际尊重的调查员和开拓者流行病学，传染病，生物医学信息学和数学建模。在这项工作之后，奥利维拉博士将产生重要的科学，以改善所有孩子的照顾受这个大流行的影响。此外，他将获得一套独特的技能，并建立必要的技能基础设施将使他能够建立一项整合临床学科的研究计划流行病学，数据科学和信息学，以检测，预防和应对未来的大流行病。

项目成果

期刊论文数量（16）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Expedited Partner Therapy: A Multicomponent Initiative to Boost Provider Counseling.

加速合作伙伴治疗：促进提供者咨询的多组成部分举措。

DOI：
10.1097/olq.0000000000001894
发表时间：
2024
期刊：
Sexually transmitted diseases
影响因子：
3.1
作者：
Markowitz,MelissaA;Ackerman-Banks,ChristinaM;Oliveira,CarlosR;Fashina,Oluwatomini;Pathy,ShefaliR;Sheth,SanginiS
通讯作者：
Sheth,SanginiS

Routine saliva testing for SARS-CoV-2 in children: Methods for partnering with community childcare centers.

DOI：
10.3389/fpubh.2023.1003158
发表时间：
2023
期刊：
FRONTIERS IN PUBLIC HEALTH
影响因子：
5.2
作者：
Rayack, Erica J.;Askari, Hibah Mahwish;Zirinsky, Elissa;Lapidus, Sarah;Sheikha, Hassan;Peno, Chikondi;Kazemi, Yasaman;Yolda-Carr, Devyn;Liu, Chen;Grubaugh, Nathan D.;Ko, Albert I.;Wyllie, Anne L.;Spatz, Erica S.;Oliveira, Carlos R.;Bei, Amy K.
通讯作者：
Bei, Amy K.

Severe Acute Respiratory Syndrome Coronavirus 2 Testing in Children in a Large Regional US Health System During the Coronavirus Disease 2019 Pandemic.