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Total Excess Mortality Surveillance for Real-Time Decision-Making in Disasters and Crises.
Santos-Burgoa, Carlos; Garcia-Meza, Alejandra; Talayero, Maria Jose; Kuenster, Nolan; Goldman Hawes, Ann S; Andrade, Elizabeth.
  • Santos-Burgoa C; The George Washington University.
  • Garcia-Meza A; Independent Consultant.
  • Talayero MJ; The George Washington University.
  • Kuenster N; The George Washington University.
  • Goldman Hawes AS; The George Washington University.
  • Andrade E; The George Washington University.
Disaster Med Public Health Prep ; 17: e350, 2023 03 13.
Article in English | MEDLINE | ID: covidwho-2279775
ABSTRACT
Crises such as Hurricane Maria and the coronavirus disease 2019 (COVID-19) pandemic have revealed that untimely reporting of the death toll results in inadequate interventions, impacts communication, and fuels distrust on response agencies. Delays in establishing mortality are due to the contested definition of deaths attributable to a disaster and lack of rapid collection of vital statistics data from inadequate health system infrastructure. Readily available death counts, combined with geographic, demographic, and socioeconomic data, can serve as a baseline to build a continuous mortality surveillance system. In an emergency setting, real-time Total, All-cause, Excess Mortality (TEM) can be a critical tool, granting authorities timely information ensuring a targeted response and reduce disaster impact. TEM measurement can identify spikes in mortality, including geographic disparities and disproportionate deaths in vulnerable populations. This study recommends that measuring total, all-cause, excess mortality as a first line of response should become the global standard for measuring disaster impact.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Disasters / Cyclonic Storms / COVID-19 Type of study: Prognostic study / Screening_studies Limits: Humans Language: English Journal: Disaster Med Public Health Prep Journal subject: Public Health Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Disasters / Cyclonic Storms / COVID-19 Type of study: Prognostic study / Screening_studies Limits: Humans Language: English Journal: Disaster Med Public Health Prep Journal subject: Public Health Year: 2023 Document Type: Article