Efficiency and Simulation of Thailand's Chiang Mai University Model for COVID-19 Mass Vaccination Hub (CMU-MVH Model).

IF 3.8 3区医学 Q2 INFECTIOUS DISEASES

American journal of infection control Pub Date : 2024-10-17 DOI:10.1016/j.ajic.2024.10.005

Amornphat Kitro, Danuphon Tippong, Wachiranun Sirikul, Natthanaphop Isaradech, Apiradee Kosai, Pimprapas Saengoa, Jiraporn Thammasarot, Penprapa Siviroj, Chaiy Rungsiyakull, Kriengkrai Srithanaviboonchai

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引用次数: 0

Abstract

Background: Mass vaccination is crucial for achieving herd immunity and controlling pandemics. Simulation models predict vaccination outcomes. This study evaluates efficiency and designs a tailored vaccination plan for Thailand.

Methods: Data was derived from a COVID-19 Mass Vaccination Hub (MVH) in Chiang Mai, Thailand. It was taken between June 2021 and December 2021. The discreet event simulation model is developed in Arena Simulation Enterprise Suite version 14.0.

Results: The operational efficiency of Chiang Mai University Mass Vaccination Hub (CMU-MVH) was 1,073 vaccinations per 8 hours with 38 service staff. The average processing times (APT) were 2.5 minutes for the registration station, 12.2 minutes for the assessment station, 8.3 minutes for vaccination, and 28.2 minutes for observation. With 100% staff availability and staff utilization ranging from 0.5 to 0.7, the CMU-MVH could handle 180 to 230 vaccinees per hour or 1,227 to 1,527 vaccinees per day. Reduced staff availability leads to an increase in average processing time, especially when staff availability is lower or equal to 60%.

Conclusions: The CMU-MVH could handle approximately a thousand vaccinations within 8 working hours. This capability could assist policymakers in developing more effective strategies and planning for future mass vaccinations.

Data availability statement: The data that support the findings of this study are available from the corresponding author, upon reasonable request.

查看原文本刊更多论文

泰国清迈大学 COVID-19 大规模疫苗接种中心模型（CMU-MVH 模型）的效率与模拟。

背景：大规模疫苗接种对于实现群体免疫和控制流行病至关重要。模拟模型可预测疫苗接种的结果。本研究评估了效率，并为泰国设计了量身定制的疫苗接种计划：数据来自泰国清迈的 COVID-19 大规模疫苗接种中心（MVH）。数据采集时间为 2021 年 6 月至 2021 年 12 月。离散事件仿真模型由 Arena Simulation Enterprise Suite 14.0 版开发：清迈大学大规模疫苗接种中心（CMU-MVH）的运行效率为每 8 小时接种 1,073 支疫苗，服务人员为 38 人。平均处理时间（APT）为：登记站 2.5 分钟，评估站 12.2 分钟，接种 8.3 分钟，观察 28.2 分钟。在人员可用率为 100%、人员利用率为 0.5 至 0.7 的情况下，CMU-MVH 每小时可处理 180 至 230 名接种者，每天可处理 1,227 至 1,527 名接种者。工作人员可用率降低会导致平均处理时间增加，尤其是当工作人员可用率低于或等于 60% 时：CMU-MVH可在8个工作小时内处理约一千例疫苗接种。这一能力可帮助决策者为未来的大规模疫苗接种制定更有效的战略和规划：支持本研究结果的数据可向相应作者索取。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

American journal of infection control 医学-传染病学

CiteScore

7.40

自引率

4.10%

发文量

479

审稿时长

24 days

期刊介绍： AJIC covers key topics and issues in infection control and epidemiology. Infection control professionals, including physicians, nurses, and epidemiologists, rely on AJIC for peer-reviewed articles covering clinical topics as well as original research. As the official publication of the Association for Professionals in Infection Control and Epidemiology (APIC)