Validating the InterVA-5 Cause of Death Analytical Tool: Using Mortality Data From the Comprehensive Health and Epidemiological Surveillance System in Papua New Guinea [PDF]
Objective InterVA-5 is a new version of an analytical tool for cause of death (COD) analysis at the population level. This study validates the InterVA-5 against the medical review method, using mortality data in Papua New Guinea (PNG).Design and setting ...
Bang Nguyen Pham +2 more
exaly +4 more sources
Agreement between cause of death assignment by computer-coded verbal autopsy methods and physician coding of verbal autopsy interviews in South Africa [PDF]
Background The South African national cause of death validation (NCODV 2017/18) project collected a national sample of verbal autopsies (VA) with cause of death (COD) assignment by physician-coded VA (PCVA) and computer-coded VA (CCVA).
Pam Groenewald +7 more
doaj +2 more sources
Strengthening Standardised Interpretation of Verbal Autopsy Data: The New InterVA-4 Tool. [PDF]
Background: Verbal autopsy (VA) is the only available approach for determining the cause of many deaths, where routine certification is not in place. Therefore, it is important to use standards and methods for VA that maximise efficiency, consistency and
Samuel J Clark +2 more
exaly +2 more sources
Applying the InterVA-4 Model to Determine Causes of Death in Rural Ethiopia [PDF]
Background: In Ethiopia, most deaths take place at home and routine certification of cause of death by physicians is lacking. As a result, reliable cause of death (CoD) data are often not available.
Geert Jan Dinant +2 more
exaly +2 more sources
Probabilistic Methods for Verbal Autopsy Interpretation: InterVA Robustness in Relation to Variations in a Priori Probabilities [PDF]
InterVA is a probabilistic method for interpreting verbal autopsy (VA) data. It uses a priori approximations of probabilities relating to diseases and symptoms to calculate the probability of specific causes of death given reported symptoms recorded in a
Peter Byass +2 more
exaly +2 more sources
A comparison of verbal autopsy assignment methods to obtain adult cause-specific mortality in two longitudinal studies in Rakai and Kalungu districts of South Central, Uganda. [PDF]
Verbal Autopsy (VA) data determines cause of death (CoD) in settings where certification is lacking, using structured interviews on symptoms and circumstances before death.
Dorean Nabukalu +8 more
doaj +2 more sources
Childhood Cause-Specific Mortality in Rural Western Kenya: Application of the InterVA-4 Model [PDF]
Background: Assessing the progress in achieving the United Nation's Millennium Development Goals in terms of population health requires consistent and reliable information on cause-specific mortality, which is often rare in resource-constrained countries.
John Vulule +2 more
exaly +2 more sources
Computer assisted verbal autopsy: comparing large language models to physicians for assigning causes to 6939 deaths in Sierra Leone from 2019–2022 [PDF]
Background Verbal autopsies (VAs) collect information on deaths in low and middle-income countries occurring outside healthcare facilities to estimate causes of death (CODs) for use in epidemiological or planning studies.
Richard Wen +10 more
doaj +2 more sources
Comparison of verbal autopsy using a large language model to biologically confirmed causes of death for malaria and other communicable diseases among children in six sub-Saharan African countries [PDF]
Background Malaria, a preventable parasitic disease, causes most child deaths in sub-Saharan Africa (SSA). Reliable cause-of-death data are essential to evaluate progress toward the national and global malaria control goals.
Ronald Carshon-Marsh +7 more
doaj +2 more sources
Cause of Death During 2009–2012, Using a Probabilistic Model (InterVA-4): An Experience From Ballabgarh Health and Demographic Surveillance System in India [PDF]
Objectives: The present study aimed to estimate the age and cause-specific mortality in Ballabgarh Health and Demographic Surveillance System (HDSS) site for the years 2009 to 2012, using a probabilistic model (InterVA-4).
Puneet Misra +2 more
exaly +2 more sources

