A Closer Look at Indirect Causes of Death After Hurricane Maria Using a Semiparametric Model.

communicable diseases education public health professional hurricane mortality

Journal

Disaster medicine and public health preparedness
ISSN: 1938-744X
Titre abrégé: Disaster Med Public Health Prep
Pays: United States
ID NLM: 101297401

Informations de publication

Date de publication:
16 Nov 2023
Historique:
medline: 20 11 2023
pubmed: 17 11 2023
entrez: 16 11 2023
Statut: epublish

Résumé

The coronavirus disease 2019 (COVID-19) pandemic as well as other recent natural emergencies have put the spotlight on emergency planning. One important aspect is that natural disasters or emergencies often lead to indirect deaths, and studying the behavior of indirect deaths during emergencies can guide emergency planning. While many studies have suggested many indirect deaths in Puerto Rico due to Hurricane Maria; the specific causes of these deaths have not been carefully studied. In this study, we use a semiparametric model and mortality data to evaluate cause of death trends. Our model adjusts for cause of death effect potentially varying over time while also inferring on how long excess deaths occurred. From September 2017 to March 2018, after adjusting for intra-annual variability and population displacement, we find evidence of significant excess deaths due to Alzheimer's/Parkinson, heart disease, sepsis, diabetes, renal failure, and pneumonia and influenza. In contrast, for the same time period we find no evidence of significant excess deaths due to cancer, hypertension, respiratory diseases, cerebrovascular disease, suicide, homicide, falling accidents, and traffic accidents.

Identifiants

pubmed: 37970871
pii: S1935789323001659
doi: 10.1017/dmp.2023.165
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e528

Auteurs

Oscar Lugo (O)

Department of Mathematical Sciences, University of Puerto Rico, Mayaguez, Puerto Rico.

Roberto Rivera (R)

Department of Mathematical Sciences, University of Puerto Rico, Mayaguez, Puerto Rico.

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Classifications MeSH