An agent-based model to assess large-scale COVID-19 vaccination campaigns for the Italian territory: The case study of Lombardy region

Cattaneo, Andrea; Mazzoleni, Mirko; Previdi, Fabio

doi:10.1016/j.cmpb.2022.107029

Cited by 13 publications

(8 citation statements)

References 38 publications

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“…This form is well-suited for post-hoc analyses, in which the number of vaccinations that were conducted per unit time (e.g., day or week) is known, see e.g. Islam et al (2021); Gozzi et al (2022); Luebben et al (2023); Kekíc et al (2023); Aruffo et al (2022); Ziarelli et al (2023); Ferreira et al (2022); Cattaneo et al (2022). Mathematically, this form requires careful attention when solving the ODE numerically, to ensure X ( t ) remains non-negative at all time.…”

Section: Key Implementation Details In Vaccine Prioritization Modelsmentioning

confidence: 99%

“…In Cattaneo et al (2022), the Covasim model is used to determine the number of infections and deaths prevented by vaccines in the Italian region Lombardy, and to retrospectively evaluate vaccine allocation strategies. Prioritization of the elderly and at-risk categories, as used in Italy, was validated as the most effective in reducing deaths, however only as long as the vaccine roll-out happens fast enough.…”

Section: Summary Of Selected Modeling Studiesmentioning

confidence: 99%

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Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models

Gonzalez-Parra,

Mahmud,

Kadelka

2024

Preprint

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As the world becomes ever more connected, the chance of pandemics increases as well. The recent COVID-19 pandemic and the concurrent global mass vaccine roll-out provides an ideal setting to learn from and refine our understanding of infectious disease models for better future preparedness. In this review, we systematically analyze and categorize mathematical models that have been developed to design optimal vaccine prioritization strategies of an initially limited vaccine. As older individuals are disproportionately affected by COVID-19, the focus is on models that take age explicitly into account. The lower mobility and activity level of older individuals gives rise to non-trivial trade-offs. Secondary research questions concern the optimal time interval between vaccine doses and spatial vaccine distribution. This review showcases the effect of various modeling assumptions on model outcomes. A solid understanding of these relationships yields better infectious disease models and thus public health decisions during the next pandemic.

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Section: Key Implementation Details In Vaccine Prioritization Modelsmentioning

confidence: 99%

Section: Summary Of Selected Modeling Studiesmentioning

confidence: 99%

Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models

Gonzalez-Parra,

Mahmud,

Kadelka

2024

Preprint

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“…Out of the 47 included studies, there were 40 unique models; five models were used in more than one paper. 31,35,38,40,42,46,47,50,55,59,61,63 Key characteris cs of the included models are shown in table 2 and the complete data extrac on table is available in supplementary file 2.…”

Section: Study Selec Onmentioning

confidence: 99%

Mathematical models of COVID-19 vaccination in high-income countries: A systematic review

Burch,

Khan,

Stone

et al. 2024

Preprint

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Objectives Since COVID–19 first emerged in 2019, mathematical models have been developed to predict transmission and provide insight into disease control strategies. A key research need now is for models to inform long–term vaccination policy. We aimed to review the variety of existing modelling methods, in order to identify gaps in the literature and highlight areas for future model development. Study design This study was a systematic review. Methods We searched PubMed, Embase and Scopus from 1 January 2019 to 6 February 2023 for peer-reviewed, English-language articles describing age–structured, dynamic, mathematical models of COVID–19 transmission and vaccination in high–income countries that include waning immunity or reinfection. We extracted details of the structure, features and approach of each model and combined them in a narrative synthesis. Results Of the 1109 articles screened, 47 were included. Most studies used deterministic, compartmental models set in Europe or North America that simulated a time horizon of 3.5 years or less. Common outcomes included cases, hospital utilisation and deaths. Only nine models included long COVID, costs, life–years or quality of life–related measures. Two studies explored the potential impact of new variants beyond Omicron. Conclusions This review demonstrates a need for long–term models that focus on outcome measures such as quality–adjusted life years, the population–level effects of long COVID and the cost–effectiveness of future policies — all of which are essential considerations in the planning of long–term vaccination strategies.

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“…The objective of the proposed ABM is to simulate the dynamics of COVID-19 in closed indoor settings. Given the variability of the transmission parameters of COVID-19 across various strains [45], we need to evaluate the parameters under different simulation scenarios.…”

Section: Purpose and Patternsmentioning

confidence: 99%

Modeling COVID-19 Transmission in Closed Indoor Settings: An Agent-Based Approach with Comprehensive Sensitivity Analysis

Ebrahimi,

Alesheikh,

Hooshangi

et al. 2024

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Computational simulation models have been widely used to study the dynamics of COVID-19. Among those, bottom-up approaches such as agent-based models (ABMs) can account for population heterogeneity. While many studies have addressed COVID-19 spread at various scales, insufficient studies have investigated the spread of COVID-19 within closed indoor settings. This study aims to develop an ABM to simulate the spread of COVID-19 in a closed indoor setting using three transmission sub-models. Moreover, a comprehensive sensitivity analysis encompassing 4374 scenarios is performed. The model is calibrated using data from Calabria, Italy. The results indicated a decent consistency between the observed and predicted number of infected people (MAPE = 27.94%, RMSE = 0.87 and χ2(1,N=34)=(44.11,p=0.11)). Notably, the transmission distance was identified as the most influential parameter in this model. In nearly all scenarios, this parameter had a significant impact on the outbreak dynamics (total cases and epidemic peak). Also, the calibration process showed that the movement of agents and the number of initial asymptomatic agents are vital model parameters to simulate COVID-19 spread accurately. The developed model may provide useful insights to investigate different scenarios and dynamics of other similar infectious diseases in closed indoor settings.

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An agent-based model to assess large-scale COVID-19 vaccination campaigns for the Italian territory: The case study of Lombardy region

Cited by 13 publications

References 38 publications

Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models

Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models

Mathematical models of COVID-19 vaccination in high-income countries: A systematic review

Modeling COVID-19 Transmission in Closed Indoor Settings: An Agent-Based Approach with Comprehensive Sensitivity Analysis

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