Verbal Autopsy: Reimagining Data & Automated Cause Assignment (using ALPHA Network data)

口头尸检：重新想象数据

• 批准号: 10215570
• 负责人: SAMUEL J CLARK
• 金额: $ 45.76万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-20 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10215570
• 关键词: Accounting; Address; Affect; Africa; Algorithms; Autopsy; Brazil; Cause of Death; Cessation of life; China; Clinics and Hospitals; Communities; Computer software; Copper; Data; Death Certificates; Dependence; Diagnostic; Disease; Effectiveness; Epidemiology; Health Priorities; Health Resources; Hospital Records; India; Individual; Indonesia; Intervention; Interview; Language; Link; Malawi; Mathematics; Measurement; Measures; Methods; Modeling; Monitor; Mozambique; Outcome; Performance; Physicians; Population; Population Distributions; Population Group; Practice Guidelines; Procedures; Randomized; Reporting; Reproducibility; Research; Signs and Symptoms; Site; Source; Spottings; Standardization; Statistical Methods; Structure; Symptoms; System; Testing; Text; Time; Translations; Uncertainty; Variant; Vital Statistics; Zambia; automated analysis; base; comparative; design; effectiveness testing; exhaustion; experimental study; global health; handheld equipment; improved; innovation; instrument; language processing; low and middle-income countries; open source; population health; prevent; public health intervention; public health relevance; response; sociolinguistics; standardize guidelines; symptomatic improvement; therapy design

 DESCRIPTION (provided by applicant): Global health priorities are set and progress assessed by measuring how many lives are ended or affected by various diseases. Most low and middle income countries do not have adequate vital statistics, with the result that two-thirds of global deaths are not registered and have no cause. Verbal autopsy (VA) has the potential to become a feasible, affordable method for assessing cause of death when full autopsy and death certification are not possible. Existing VA methods do not yield reproducible, comparable cause of death assignments and can be unacceptably slow. This project aims to develop affordable, robust, calibrated methods to assign causes to individual deaths and characterize the distribution of deaths by cause by completing the following four activities: (1) develop a new standard, automated, statistical method to assign causes to deaths from VA data - InSilicoVA, (2) use additional facility-based data and debiased physician-assigned causes to create new, improved symptom-cause information modules used by InSilicoVA to inform the assignment of causes, (3) conduct an exhaustive, fair comparison of existing automated methods for assigning causes from VA data, including InSilicoVA, and (4) reduce measurement error in VA data by conducting fieldwork at multiple long-term field sites in Africa to understand and standardize the VA interview and then test the effectiveness of a new interview design and language processing procedures informed by that understanding. InSilicoVA will improve on existing methods by (1) being fully probabilistic, (2) keeping individual and population levels consistent (3) reporting consistent uncertainty at both levels, (4) utilizing information from the narrative section of the A interview, (5) accounting for measurement error, and (6) incorporating a hierarchical structure to allow aggregation and comparison across broad regions. At the end of this project, the community of VA users will have (1) full, open-source access to InSilicoVA, (2) valuable, new symptom-cause information modules for use in InSilicoVA and other methods, (3) urgently needed, objective information describing the performance of existing automated VA cause-assignment methods, and (4) an innovative new standardized VA interview design and standard operating procedures for handling language and VA data during and after the VA interview. The overall effect will be to increase the number of deaths with comparable causes determined using a reproducible method with quantifiable accuracy. This, in turn, will provide an opportunity to improve national, regional and global population health indicators in parts of the world without adequate vital statistics systems. With better and more timely information on population health, resources can be allocated and interventions targeted more efficiently and with greater effect. More lives will be improved and extended.

 描述（由申请人提供）：通过衡量有多少生命被各种疾病终结或影响，确定全球卫生优先事项并评估进展。大多数低收入和中等收入国家没有足够的生命统计数据，导致全球三分之二的死亡没有登记，也没有死因。口头尸检（VA）有可能成为一个可行的，负担得起的方法来评估死亡原因时，完全尸检和死亡证明是不可能的。现有的VA方法无法产生可重复的、可比较的死因分配，并且速度可能慢得令人无法接受。该项目旨在通过完成以下四项活动，制定负担得起的、稳健的、经过校准的方法，以确定个人死亡的原因，并按原因描述死亡的分布情况：（1）开发一种新的标准、自动化、统计方法，以根据VA数据- InSilicoVA分配死亡原因，（2）使用额外的基于机构的数据和去偏的医生分配的原因来创建新的，InSilicoVA用于通知原因分配的改进的非原因信息模块，（3）对用于从VA数据分配原因的现有自动化方法进行详尽、公平的比较，包括InSilicoVA，以及（4）通过在多个长-在非洲的长期实地考察点，了解VA面试并使之标准化，然后测试新面试设计和语言处理程序的有效性。InSilicoVA将通过以下方式改进现有方法：（1）完全概率性，（2）保持个体和群体水平一致，（3）报告两个水平的一致不确定性，（4）利用A访谈的叙述部分的信息，（5）解释测量误差，以及（6）纳入分层结构，以允许在广泛的区域进行汇总和比较。在该项目结束时，VA用户社区将拥有（1）完整的开源InSilicoVA访问权限，（2）用于InSilicoVA和其他方法的有价值的新原因信息模块，（3）描述现有自动VA原因分配方法性能的迫切需要的客观信息，以及（4）创新的新的标准化VA访谈设计和标准操作程序，用于在VA访谈期间和之后处理语言和VA数据。总体效应将是增加使用可重复方法确定的具有可比原因的死亡人数，该方法具有可量化的准确性。这反过来又将提供一个机会，在世界上没有人口保健的地区改善国家、区域和全球人口保健指标。 适当的人口动态统计系统。有了更好和更及时的人口健康信息，就可以更有效地分配资源，更有针对性地采取干预措施，取得更大的效果。更多的生命将得到改善和延长。

项目成果

Agreement between cause of death assignment by computer-coded verbal autopsy methods and physician coding of verbal autopsy interviews in South Africa.

• DOI: 10.1080/16549716.2023.2285105
• 发表时间: 2023-12-31
• 期刊: GLOBAL HEALTH ACTION
• 影响因子: 2.6
• 作者: Groenewald, Pam;Thomas, Jason;Clark, Samuel J.;Morof, Diane;Joubert, Jane D.;Kabudula, Chodziwadziwa;Li, Zehang;Bradshaw, Debbie
• 通讯作者: Bradshaw, Debbie

Health and demographic surveillance systems in low- and middle-income countries: history, state of the art and future prospects.

• DOI: 10.1080/16549716.2021.1974676
• 发表时间: 2021-10-26
• 期刊: Global health action
• 影响因子: 2.6
• 作者: Herbst K;Juvekar S;Jasseh M;Berhane Y;Chuc NTK;Seeley J;Sankoh O;Clark SJ;Collinson MA
• 通讯作者: Collinson MA

Estimating causes of death where there is no medical certification: evolution and state of the art of verbal autopsy.

• DOI: 10.1080/16549716.2021.1982486
• 发表时间: 2021-10-26
• 期刊: Global health action
• 影响因子: 2.6
• 作者: Chandramohan D;Fottrell E;Leitao J;Nichols E;Clark SJ;Alsokhn C;Cobos Munoz D;AbouZahr C;Di Pasquale A;Mswia R;Choi E;Baiden F;Thomas J;Lyatuu I;Li Z;Larbi-Debrah P;Chu Y;Cheburet S;Sankoh O;Mohamed Badr A;Fat DM;Setel P;Jakob R;de Savigny D
• 通讯作者: de Savigny D