Blood donation projections using hierarchical time series forecasting

The case of Zimbabwe’s national blood bank

Bibliographic Data

ID15362123
AuthorsCoster Chideme (0000-0002-0624-9136, University of the Free State, corresponding author), Delson Chikobvu (0000-0003-3979-658X, University of the Free State), Tendai Makoni (0000-0003-0853-7761, University of the Free State)
Year2024
Volume24
Issue1
Pages928-928
Publication date2024-03-31
Open AccessYes
TypeARTICLE
VenueBMC Public Health (JOURNAL)
Journal identifiersISSN: 1471-2458 • E-ISSN: 1471-2458
PublisherBioMed Central (PUBLISHER • GB)
DOI10.1186/s12889-024-18185-7
PMID38556866
OpenAlexW4393360092
LanguageEN
Citations received1
References cited33

The gradual decrease in future blood donations exhibited by the predictions calls for blood authorities in Zimbabwe to develop interventions that encourage blood donor retention and regular donations. The impact of the Covid-19 pandemic distorted the blood donation patterns such that the developed model did not capture the significant drop in blood donations during the pandemic period. Other shocks such as, a surge in global pandemics and other disasters, will inevitably affect the blood donation system. Thus, forecasting future blood collections with a high degree of accuracy requires robust mathematical models which factor in, the impact of various shocks to the system, on short notice

Autoregressive integrated moving average · Blood donations · Blood donor · Coronavirus disease 2019 (COVID-19 · Donation · Economics · Mean absolute percentage error · Operations management · Pandemic · Statistics · Time series · Blood donation and transfusion practices · Blood transfusion and management · Demography · Engineering · Mathematics · Medicine · Organ Donation and Transplantation · Immunology · Internal Medicine

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