Vaccine Supply Forecasting and Optimization using Deterministic and Probabilistic Approaches
2nd International Conference for Innovation in Technology, INOCON 2023
; 2023.
Article
in English
| Scopus | ID: covidwho-2321851
ABSTRACT
When the pandemic was at its peak, it was a quite difficult task for the government to schedule vaccine supply in various districts of a state. This task became further difficult when vaccines were required to be supplied to various Covid Vaccination Centers (CVCs) at a granular level. This is because there was no data regarding the trend being acquired at each CVC and the population distribution is non-uniform across the district. This led to the arousal of an ambiguous situation for a certain period and hence mismanagement. Now that we have sufficient data across each CVC, we can work on a time series analysis of vaccine requirements in which we can essentially forecast the number of administered doses and optimize the wastage at all atomic CVC levels. © 2023 IEEE.
ARIMA; Holt-Winter's Method; supply optimization; Time-series analysis; Vaccine dosage forecasting; Diseases; Harmonic analysis; Population statistics; Time series analysis; Vaccines; Deterministic and probabilistic approaches; Granular levels; Holt-Winters method; Non-uniform; Optimisations; Vaccine supplies; Forecasting
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
Topics:
Vaccines
Language:
English
Journal:
2nd International Conference for Innovation in Technology, INOCON 2023
Year:
2023
Document Type:
Article
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