Individual and Neighborhood Vulnerability to the Spanish Flu

个人和社区对西班牙流感的脆弱性

• 批准号: 10644538
• 负责人: John R Logan
• 金额: $ 23.93万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10644538
• 关键词: 1918 influenza pandemic; Address; Affect; Age; Area; Attention; Birth Place; COVID-19; COVID-19 pandemic; Cause of Death; Censuses; Cessation of life; Characteristics; Cities; Communities; Community Health; Coronavirus; Country; Data; Data Set; Death Certificates; Death Rate; Death Records; Dimensions; Ethnic Origin; Event; Fatality rate; Gender; Genetic Transcription; Glean; Health; Household; Individual; Inequality; Influenza; Knowledge; Link; Location; Measurement; Measures; Names; Neighborhoods; New York; New York City; Occupations; Outcome; Parents; Pattern; Persons; Philadelphia; Pneumonia; Public Health; Race; Records; Research; Risk; Risk Factors; Sampling; Severities; Social Class; Societies; Spanish flu; Standardization; Surveys; Survivors; System; Time; Variant; behavior measurement; comparative; contagion; experience; falls; flexibility; flu; future pandemic; health disparity; innovation; mortality; mortality risk; multilevel analysis; outcome disparities; pandemic disease; predictive modeling; previous pandemic; response; social group; spatial relationship; urban area

PROJECT SUMMARY/ABSTRACT This is a study of mortality risk in the deadliest pandemic in the 20th Century, the Spanish flu of 1918, in two of the U.S. cities with the highest number of fatalities, New York and Philadelphia. It has four main aims. Aim 1 is to examine mortality from the Spanish flu at the neighborhood scale in these cities. Aim 2 is to extend the ecological analysis with multilevel models including individual-level predictors. Aim 3 is to compare the patterns of influenza/pneumonia mortality during the pandemic with mortality in the same period in the previous year, and Aim 4 is to compare patterns between cities. Few studies of pandemics have gone beyond analyzing mortality data at the level of whole cities to consider spatial variation within cities, and there have been none that examined risk of mortality in a pandemic using multilevel models. In this project, drawing on individual death records, attention can be directed to specific neighborhoods and mortality risk of their residents. The study will show how personal characteristics such as age, gender, race, nativity, and social class affect risk of mortality in a multilevel model that includes similar characteristics measured at a neighborhood scale and also incorporates spatial relationships among neighborhoods. These aims will be addressed through analysis of a new data set with several innovative components. 1) Transcription of all death certificates during fall 1917 and fall 1918 in New York and Philadelphia including the person’s name, age, race, gender, address, cause of death, date of death, occupation, and parents’ names and place of birth. 2) Geocoding of addresses in a historically accurate GIS system, so that persons can be linked to their neighborhoods. 3) Use of 100% census microdata from 1920 to create measures of neighborhood characteristics, construct a comparison sample of flu survivors, and glean information about the households of those who died. These data will allow the project to probe the independent effects of various individual risk factors while also examining neighborhood differences and spatial patterns in mortality.

项目摘要/摘要 这是一项研究20世纪最致命的大流行的死亡风险，1918年的西班牙流感 纽约和费城死亡人数最多的美国城市。它有四个主要目标。目标1是 在这些城市的邻里范围内检查西班牙流感的死亡率。目标2是扩展 具有多级模型的生态分析，包括个人级预测指标。目标3是比较 在同一时期的大流行期间，影响扎/肺炎死亡率的模式 一年和目标4是比较城市之间的模式。很少有关于大流行的研究超出分析 在整个城市层面上考虑城市内空间变化的死亡率数据，没有 使用多级模型检查了大流行中死亡率的风险。在这个项目中，利用个人 死亡记录，可以关注特定社区和居民的死亡风险。 研究将表明年龄，性别，种族，诞生和社会阶层等个人特征如何影响 多层次模型中的死亡率包括在邻里规模上测得的相似特征，也包括 结合了社区之间的空间关系。 这些目标将通过分析具有几个创新组件的新数据集来解决。 1） 1917年秋季和1918年秋季在纽约和费城的所有死亡证书的转录 人的名字，年龄，种族，性别，地址，死亡原因，死亡日期，占领和父母的名字 和出生地。 2）在历史上准确的GIS系统中的地址地理编码，以便人们可以 链接到他们的社区。 3）从1920年开始使用100％人口普查微型数据来创建测量 邻里特征，构建流感表面的比较样本，并收集有关 死者的家庭。这些数据将使项目能够探究各种的独立效果 个体风险因素，同时还检查死亡率的邻里差异和空间模式。