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（由适用提供）：通过衡量各种疾病结束或影响多少生命来确定和进度进行全球健康优先级。大多数低收入国家和中等收入国家没有足够的重要统计数据，结果是三分之二的全球死亡未注册，没有原因。口头尸检（VA）有可能成为一种可行的，负担得起的方法，用于评估死亡原因，当时无法进行全面尸检和死亡认证。现有的VA方法不会产生可重复的，可比较的死亡分配原因，并且可能会缓慢。该项目旨在开发负担得起，健壮，校准的方法来分配导致个人死亡，并通过完成以下四项活动来表征由于原因的分配，以开发一种新的标准，自动化的，自动化的，统计的方法，将原因分配给VA数据的死亡原因 - va数据 - Insilicova，Insilicova，（2）通过基于设施和辩论性的症状来提出额外的症状，并将其用于INSIL，以置于新的症状，并改善症状，并改善症状，并改善症状，以置于INSIOM，并符合症状，并将其用于症状，并将其用于症状，并符合新的症状，并将其置于范围内的症状。原因的分配，（3）对包括Insilicova在内的VA数据分配原因的现有自动化方法进行了详尽的公平比较，以及（4）（4）通过在非洲多个长期现场站点进行现场工作来减少VA数据中的测量误差，以了解和标准化VA访谈，然后对新的访谈设计和语言处理的有效性来理解该访谈的有效性。 Insilicova将通过（1）完全概率地改善现有方法，（2）保持个人和人口水平一致（3）在这两个级别上报告一致的不确定性，（（4）利用访谈的叙事部分中的信息，（5）核算测量误差的核算，以及（6）在整个范围内构建层次结构，可以在整个范围内进行跨区域和比较。在该项目结束时，VA用户的社区将拥有（1）全面的，开源的访问iNilicova，（2）有价值的，新的症状原因信息模块用于Insilicova和其他方法，（3）急需的客观信息，描述现有自动化的VA Cavie-Assissign and（4）在Innsive and Innrave and Innrave va va va va and（4）的标准数据的性能，以及（4）的范围内，以及（4）在Innsive and Innrave and Innrand Standard andive va va va va va va va and（4）在VA采访之后。总体效果将是使用具有可量化精度的可重复方法确定的可比原因来增加死亡人数。反过来，这将为改善世界各地的国家，地区和全球人口健康指标提供机会 足够的重要统计系统。有了更好，更及时的人口健康信息，可以将资源分配和干预措施更有效，更有效。更多的生活将得到改善和延长。

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