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Improving accuracy of identification of COVID-19-related deaths is essential to public health surveillance and research. The verbal autopsy, an established strategy involving an interview with a decedent's caregiver or witness using a semi-structured questionnaire, may improve accurate counting of COVID-19-related deaths.To develop and pilot-test the Verbal Autopsy Instrument for COVID-19 (VAIC) and a death adjudication protocol using it.We used a multi-step process to design the VAIC and a protocol for its use. We developed a preliminary version of a verbal autopsy instrument specifically for COVID. We then pilot-tested this instrument by interviewing respondents about the deaths of 15 adults aged ≥65 during the initial COVID-19 surge in New York City. We modified it after the first 5 interviews. We then reviewed the VAIC and clinical information for the 15 deaths and developed a death adjudication process/algorithm to determine whether the underlying cause of death was definitely (40% of these pilot cases), probably (33%), possibly (13%), or unlikely/definitely not (13%) COVID-19-related. We noted differences between the adjudicated cause of death and a death certificate.The VAIC and a death adjudication protocol using it may improve accuracy in identifying COVID-19-related deaths.
Adult, SARS-CoV-2, Cause of Death, Surveys and Questionnaires, COVID-19, Humans, Research and Reporting Methods, Autopsy
Adult, SARS-CoV-2, Cause of Death, Surveys and Questionnaires, COVID-19, Humans, Research and Reporting Methods, Autopsy
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |