Cost-effectiveness analysis of COVID-19 variants effects in an age-structured model

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

This study analyzes the impact of COVID-19 variants on cost-effectiveness across age groups, considering vaccination efforts and nonpharmaceutical interventions in Republic of Korea. We aim to assess the costs needed to reduce COVID-19 cases and deaths using age-structured model. The proposed age-structured model analyzes COVID-19 transmission dynamics, evaluates vaccination effectiveness, and assesses the impact of the Delta and Omicron variants. The model is fitted using data from the Republic of Korea between February 2021 and November 2022. The cost-effectiveness of interventions, medical costs, and the cost of death for different age groups are evaluated through analysis. The impact of different variants on cases and deaths is also analyzed, with the Omicron variant increasing transmission rates and decreasing case-fatality rates compared to the Delta variant. The cost of interventions and deaths is higher for older age groups during both outbreaks, with the Omicron outbreak resulting in a higher overall cost due to increased medical costs and interventions. This analysis shows that the daily cost per person for both the Delta and Omicron variants falls within a similar range of approximately $10–$35. This highlights the importance of conducting cost-effect analyses when evaluating the impact of COVID-19 variants.

Related collections

Most cited references 34

Record: found
Abstract: found
Article: not found

The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study

Kiesha Prem, Yang Liu, Timothy Russell … (2020)

Summary Background In December, 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus, emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures in response to the outbreak, including extended school and workplace closures. We aimed to estimate the effects of physical distancing measures on the progression of the COVID-19 epidemic, hoping to provide some insights for the rest of the world. Methods To examine how changes in population mixing have affected outbreak progression in Wuhan, we used synthetic location-specific contact patterns in Wuhan and adapted these in the presence of school closures, extended workplace closures, and a reduction in mixing in the general community. Using these matrices and the latest estimates of the epidemiological parameters of the Wuhan outbreak, we simulated the ongoing trajectory of an outbreak in Wuhan using an age-structured susceptible-exposed-infected-removed (SEIR) model for several physical distancing measures. We fitted the latest estimates of epidemic parameters from a transmission model to data on local and internationally exported cases from Wuhan in an age-structured epidemic framework and investigated the age distribution of cases. We also simulated lifting of the control measures by allowing people to return to work in a phased-in way and looked at the effects of returning to work at different stages of the underlying outbreak (at the beginning of March or April). Findings Our projections show that physical distancing measures were most effective if the staggered return to work was at the beginning of April; this reduced the median number of infections by more than 92% (IQR 66–97) and 24% (13–90) in mid-2020 and end-2020, respectively. There are benefits to sustaining these measures until April in terms of delaying and reducing the height of the peak, median epidemic size at end-2020, and affording health-care systems more time to expand and respond. However, the modelled effects of physical distancing measures vary by the duration of infectiousness and the role school children have in the epidemic. Interpretation Restrictions on activities in Wuhan, if maintained until April, would probably help to delay the epidemic peak. Our projections suggest that premature and sudden lifting of interventions could lead to an earlier secondary peak, which could be flattened by relaxing the interventions gradually. However, there are limitations to our analysis, including large uncertainties around estimates of R 0 and the duration of infectiousness. Funding Bill & Melinda Gates Foundation, National Institute for Health Research, Wellcome Trust, and Health Data Research UK.

0 comments Cited 854 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Effectiveness of mRNA BNT162b2 COVID-19 vaccine up to 6 months in a large integrated health system in the USA: a retrospective cohort study

Sara Tartof, Jeff M Slezak, Heidi Fischer … (2021)

Background Vaccine effectiveness studies have not differentiated the effect of the delta (B.1.617.2) variant and potential waning immunity in observed reductions in effectiveness against SARS-CoV-2 infections. We aimed to evaluate overall and variant-specific effectiveness of BNT162b2 (tozinameran, Pfizer–BioNTech) against SARS-CoV-2 infections and COVID-19-related hospital admissions by time since vaccination among members of a large US health-care system. Methods In this retrospective cohort study, we analysed electronic health records of individuals (≥12 years) who were members of the health-care organisation Kaiser Permanente Southern California (CA, USA), to assess BNT162b2 vaccine effectiveness against SARS-CoV-2 infections and COVID-19-related hospital admissions for up to 6 months. Participants were required to have 1 year or more previous membership of the organisation. Outcomes comprised SARS-CoV-2 PCR-positive tests and COVID-19-related hospital admissions. Effectiveness calculations were based on hazard ratios from adjusted Cox models. This study was registered with ClinicalTrials.gov , NCT04848584. Findings Between Dec 14, 2020, and Aug 8, 2021, of 4 920 549 individuals assessed for eligibility, we included 3 436 957 (median age 45 years [IQR 29–61]; 1 799 395 [52·4%] female and 1 637 394 [47·6%] male). For fully vaccinated individuals, effectiveness against SARS-CoV-2 infections was 73% (95% CI 72–74) and against COVID-19-related hospital admissions was 90% (89–92). Effectiveness against infections declined from 88% (95% CI 86–89) during the first month after full vaccination to 47% (43–51) after 5 months. Among sequenced infections, vaccine effectiveness against infections of the delta variant was high during the first month after full vaccination (93% [95% CI 85–97]) but declined to 53% [39–65] after 4 months. Effectiveness against other (non-delta) variants the first month after full vaccination was also high at 97% (95% CI 95–99), but waned to 67% (45–80) at 4–5 months. Vaccine effectiveness against hospital admissions for infections with the delta variant for all ages was high overall (93% [95% CI 84–96]) up to 6 months. Interpretation Our results provide support for high effectiveness of BNT162b2 against hospital admissions up until around 6 months after being fully vaccinated, even in the face of widespread dissemination of the delta variant. Reduction in vaccine effectiveness against SARS-CoV-2 infections over time is probably primarily due to waning immunity with time rather than the delta variant escaping vaccine protection. Funding Pfizer.

0 comments Cited 571 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Projecting social contact matrices in 152 countries using contact surveys and demographic data

Kiesha Prem, Alex Cook, Mark Jit (2017)

Heterogeneities in contact networks have a major effect in determining whether a pathogen can become epidemic or persist at endemic levels. Epidemic models that determine which interventions can successfully prevent an outbreak need to account for social structure and mixing patterns. Contact patterns vary across age and locations (e.g. home, work, and school), and including them as predictors in transmission dynamic models of pathogens that spread socially will improve the models’ realism. Data from population-based contact diaries in eight European countries from the POLYMOD study were projected to 144 other countries using a Bayesian hierarchical model that estimated the proclivity of age-and-location-specific contact patterns for the countries, using Markov chain Monte Carlo simulation. Household level data from the Demographic and Health Surveys for nine lower-income countries and socio-demographic factors from several on-line databases for 152 countries were used to quantify similarity of countries to estimate contact patterns in the home, work, school and other locations for countries for which no contact data are available, accounting for demographic structure, household structure where known, and a variety of metrics including workforce participation and school enrolment. Contacts are highly assortative with age across all countries considered, but pronounced regional differences in the age-specific contacts at home were noticeable, with more inter-generational contacts in Asian countries than in other settings. Moreover, there were variations in contact patterns by location, with work-place contacts being least assortative. These variations led to differences in the effect of social distancing measures in an age structured epidemic model. Contacts have an important role in transmission dynamic models that use contact rates to characterize the spread of contact-transmissible diseases. This study provides estimates of mixing patterns for societies for which contact data such as POLYMOD are not yet available.

0 comments Cited 321 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Hyojung Lee: hjlee@knu.ac.kr

Journal

Journal ID (nlm-ta): Sci Rep

Journal ID (iso-abbrev): Sci Rep

Title: Scientific Reports

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2045-2322

Publication date (Electronic): 22 September 2023

Publication date PMC-release: 22 September 2023

Publication date Collection: 2023

Volume: 13

Electronic Location Identifier: 15844

Affiliations

[1 ]Department of Artificial Intelligence and Software, Kangwon National University, ( https://ror.org/01mh5ph17) Chuncheon, Gangwon 25913 Republic of Korea

[2 ]GRID grid.249964.4, ISNI 0000 0001 0523 5253, Division of Data Analysis, Center for Global R&D Data Analysis, , Korea Institute of Science and Technology Information (KISTI), ; Seoul, 02456 Republic of Korea

[3 ]National Institute for Mathematical Sciences, ( https://ror.org/04n7py080) Daejeon, 34047 Republic of Korea

[4 ]Nonlinear Dynamics and Mathematical Application Center, Kyungpook National University, ( https://ror.org/040c17130) Daegu, 41566 Republic of Korea

[5 ]Department of Statistics, Kyungpook National University, ( https://ror.org/040c17130) Daegu, 41566 Republic of Korea

Article

Publisher ID: 41876

DOI: 10.1038/s41598-023-41876-x

PMC ID: 10516971

PubMed ID: 37739967

SO-VID: 7c1abeb9-aad1-4470-99e2-fb1befffe9fd

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 29 April 2023

Date accepted : 1 September 2023

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100003725, National Research Foundation of Korea;

Award ID: 2020R1C1C1A01012557

Award ID: 2022R1A2C3011711

Award Recipient : Giphil Cho Geunsoo Jang Hyojung Lee

Custom metadata

ScienceOpen disciplines: Uncategorized

Keywords: viral infection,computational models

Data availability:

ScienceOpen disciplines: Uncategorized

Keywords: viral infection, computational models

Cost-effectiveness analysis of COVID-19 variants effects in an age-structured model

Read this article at

Abstract

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 34

The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study

Effectiveness of mRNA BNT162b2 COVID-19 vaccine up to 6 months in a large integrated health system in the USA: a retrospective cohort study

Projecting social contact matrices in 152 countries using contact surveys and demographic data

Author and article information

Contributors

Journal

Affiliations

Article

History

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 193

Most referenced authors 411