Evidence map›Paper›PMID 33641677›Full record

ArticleBMC medicine2021

Optimizing antiviral treatment for seasonal influenza in the USA: a mathematical modeling analysis.

Matan Yechezkel, Martial L Ndeffo Mbah, Dan Yamin

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
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  7. Decreased Incidence of Influenza During the COVID-19 Pandemic.International journal of general medicine · 2022
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Matan Yechezkel *Department of Industrial Engineering, Tel Aviv University, 55 Haim Levanon St, Tel Aviv, Israel.
Martial L Ndeffo Mbah *Department of Veterinary Integrative Biosciences, College of Veterinary Medicine & Biomedical Sciences, Texas A&M University, College Station, Texas, 77843, USA. mndeffo@cvm.tamu.edu.ORCID 0000-0003-4158-7613
Dan Yamin *Department of Industrial Engineering, Tel Aviv University, 55 Haim Levanon St, Tel Aviv, Israel. dan.yamin@gmail.com.
Tel Aviv University · ILTexas A&M University · US

Funding

College of Veterinary Medicine and Biomedical Sciences, Texas A and M University Faculty StartupIsrael Science Foundation grant No. 3409/19
6 · The paper itself

Abstract

backgroundSeasonal influenza remains a major cause of morbidity and mortality in the USA. Despite the US Centers for Disease Control and Prevention recommendation promoting the early antiviral treatment of high-risk patients, treatment coverage remains low.

methodsTo evaluate the population-level impact of increasing antiviral treatment timeliness and coverage among high-risk patients in the USA, we developed an influenza transmission model that incorporates data on infectious viral load, social contact, and healthcare-seeking behavior. We modeled the reduction in transmissibility in treated individuals based on their reduced daily viral load. The reduction in hospitalizations following treatment was based on estimates from clinical trials. We calibrated the model to weekly influenza data from Texas, California, Connecticut, and Virginia between 2014 and 2019. We considered in the baseline scenario that 2.7-4.8% are treated within 48 h of symptom onset while an additional 7.3-12.8% are treated after 48 h of symptom onset. We evaluated the impact of improving the timeliness and uptake of antiviral treatment on influenza cases and hospitalizations.

resultsModel projections suggest that treating high-risk individuals as early as 48 h after symptom onset while maintaining the current treatment coverage level would avert 2.9-4.5% of all symptomatic cases and 5.5-7.1% of all hospitalizations. Geographic variability in the effectiveness of earlier treatment arises primarily from variabilities in vaccination coverage and population demographics. Regardless of these variabilities, we found that when 20% of the high-risk individuals were treated within 48 h, the reduction in hospitalizations doubled. We found that treatment of the elderly population (> 65 years old) had the highest impact on reducing hospitalizations, whereas treating high-risk individuals aged 5-19 years old had the highest impact on reducing transmission. Furthermore, the population-level benefit per treated individual is enhanced under conditions of high vaccination coverage and a low attack rate during an influenza season.

conclusionsIncreased timeliness and coverage of antiviral treatment among high-risk patients have the potential to substantially reduce the burden of seasonal influenza in the USA, regardless of influenza vaccination coverage and the severity of the influenza season.

Indexed as

AdolescentAdultAgedAntiviral AgentsChildChild, PreschoolFemaleHumansInfantInfant, NewbornInfluenza, HumanInfluenza VaccinesMaleMiddle AgedModels, TheoreticalUnited StatesAntiviral AgentsInfluenza VaccinesAntiviral treatmentMathematical modelingSeasonal influenzaVaccination

Identifiers

PMID33641677
PMCPMC7917004
OpenAlexW3134787549

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.