Why COVID-19 modelling of progression and prevention fails to translate to the real-world

Heneghan, Carl; Jefferson, Tom

doi:10.1016/j.jbior.2022.100914

Cited by 6 publications

(6 citation statements)

References 24 publications

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“…We intentionally concentrated on articles which were calibrated on data for an at least partially vaccinated population, as subsequent studies found that early COVID-19 pandemic prognostic models, when retrospectively analyzed, tended to have serious deficiencies. These deficiencies included overestimating the number of hospitalisations and deaths ( 25 ), as well as underestimating the impact of voluntary behavioral changes if the number of cases increased ( 26 ), or taking mutually exclusive assumptions concerning the reproduction number ( 27 ).…”

Section: Discussionmentioning

confidence: 99%

To vaccinate or to isolate? Establishing which intervention leads to measurable mortality reduction during the COVID-19 Delta wave in Poland

Walkowiak,

Walkowiak

2023

Front. Public Health

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BackgroundDuring the Delta variant COVID-19 wave in Poland there were serious regional differences in vaccination rates and discrepancies in the enforcement of pandemic preventive measures, which allowed us to assess the relative effectiveness of the policies implemented.MethodsCreating a model that would predict mortality based on vaccination rates among the most vulnerable groups and the timing of the wave peak enabled us to calculate to what extent flattening the curve reduced mortality. Subsequently, a model was created to assess which preventive measures delayed the peak of infection waves. Combining those two models allowed us to estimate the relative effectiveness of those measures.ResultsFlattening the infection curve worked: according to our model, each week of postponing the peak of the wave reduced excess deaths by 1.79%. Saving a single life during the Delta wave required one of the following: either the vaccination of 57 high-risk people, or 1,258 low-risk people to build herd immunity, or the isolation of 334 infected individuals for a cumulative period of 10.1 years, or finally quarantining 782 contacts for a cumulative period of 19.3 years.ConclusionsExcept for the most disciplined societies, vaccination of high-risk individuals followed by vaccinating low-risk groups should have been the top priority instead of relying on isolation and quarantine measures which can incur disproportionately higher social costs. Our study demonstrates that even in a country with uniform policies, implementation outcomes varied, highlighting the importance of fine-tuning policies to regional specificity.

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Section: Discussionmentioning

confidence: 99%

To vaccinate or to isolate? Establishing which intervention leads to measurable mortality reduction during the COVID-19 Delta wave in Poland

Walkowiak,

Walkowiak

2023

Front. Public Health

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“…Collecting comprehensive and accurate statistical data was already a difficult task, but during the COVID-19 pandemic, this problem has worsened and the primitiveness of monitoring and forecasting mechanisms has become apparent [2].…”

Section: Introductionmentioning

confidence: 99%

Artificial Populations in Agent-Based Modeling

Glushchenko,

Manolov,

Kozlov

et al. 2023

Preprint

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In the field of modeling social systems, the use of agent-based models (AM) has become a powerful tool for understanding processes occurring in society, in particular, for studying the spread of infections among the population. The agent model is based on a synthetic population consisting of agents, their interactions and sometimes the territory in which the interaction occurs. The choice of an appropriate method for creating such artificial populations and the selection of parameters becomes a key issue affecting the realism of the model and its ability to reflect real-world scenarios. This article delves into the interplay between agent-based modeling, synthetic population construction, and parameter selection, offering our insight into the complex process of modeling infectious disease dynamics. The review concludes with an exploration of extending the Covasim model [1] to experiments in computational epidemiology. Covasim, a dynamic transmission modeling tool, is known for its ability to adapt to different scenarios and offers predictive information critical for managing epidemiological situations. The Covasim model could include improvements to better simulate real-world epidemic conditions, including a revised transmission strategy to account for accumulation through daily contacts. In addition, we propose to add a module for intercity travel and a visualization package that will significantly expand the functionality of Covasim. These improvements make Covasim a more versatile and efficient tool for modeling and analyzing epidemic processes.

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“…‘In the aftermath of the COVID-19 pandemic, Box’s wisdom regarding models seems as prescient as ever. Much of the more dubious modeling performed during this period has generated substantial criticism ( 1 ). Modeling complex systems involving human beings, incapable of reliably living up to the role of rational actor, is particularly fraught with danger ( 2 ).…”

mentioning

confidence: 99%