Literature DB >> 25828414

Prediction, risk and control of anti-influenza drugs in the Yodo River Basin, Japan during seasonal and pandemic influenza using the transmission model for infectious disease.

Takashi Azuma1, Norihide Nakada2, Naoyuki Yamashita2, Hiroaki Tanaka2.   

Abstract

To reduce the risk of producing an anti-influenza drug-resistant virus from wildfowl, it is important to estimate the concentrations of anti-influenza drugs in river water during an influenza pandemic and to evaluate the concentrations that keep river basins safe. We first created a newly designed infectious disease transmission model based on the Susceptible-Infected-Recovered model. This model was then applied to replicate the transitional changes of three representative anti-influenza drugs, oseltamivir (OS), oseltamivir carboxylate (OC), and zanamivir (ZAN), in the urban area of the Yodo River system, which is one of the major basins in Japan with a population of 12 million; this region contains nearly 10% of the country's flu cases during the seasonal influenza outbreaks between 1999 and 2010. The results showed high correlations between the estimated number of influenza cases and the concentrations of the three investigated anti-influenza drugs with the reported values. We then extended the application of the model to estimate the concentration level of these anti-influenza drugs during the several influenza pandemics. The maximum estimated concentrations for OS, OC, and ZAN were known to be 260-450ng/L, 1500-2600ng/L and 40-70ng/L, respectively, at the peak of the influenza pandemic. These results suggest that it is possible that a drug-resistant influenza virus can originate from wild mallard when there is a large-scale influenza pandemic. However, ozonation before discharge at sewage treatment plants is known to significantly reduce the release of such drugs into the aquatic environment to reduce the risk of a drug-resistant virus outbreak. It was also suggested that further environmental risk could be reduced by decreasing these concentrations further in river water.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Drug-resistant influenza virus; Mathematical epidemic models; Ozonation; Relenza; River water environment; Sewage treatment plant; Tamiflu; Wildfowls

Mesh:

Substances:

Year:  2015        PMID: 25828414     DOI: 10.1016/j.scitotenv.2015.03.069

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  4 in total

1.  A chronicle of SARS-CoV-2: Seasonality, environmental fate, transport, inactivation, and antiviral drug resistance.

Authors:  Manish Kumar; Payal Mazumder; Sanjeeb Mohapatra; Alok Kumar Thakur; Kiran Dhangar; Kaling Taki; Santanu Mukherjee; Arbind Kumar Patel; Prosun Bhattacharya; Pranab Mohapatra; Jörg Rinklebe; Masaaki Kitajima; Faisal I Hai; Anwar Khursheed; Hiroaki Furumai; Christian Sonne; Keisuke Kuroda
Journal:  J Hazard Mater       Date:  2020-10-06       Impact factor: 10.588

2.  Changes in Sewage Sludge Chemical Signatures During a COVID-19 Community Lockdown, Part 2: Nontargeted Analysis of Sludge and Evaluation with COVID-19 Metrics.

Authors:  Sara L Nason; Elizabeth Lin; Krystal J Godri Pollitt; Jordan Peccia
Journal:  Environ Toxicol Chem       Date:  2021-11-02       Impact factor: 4.218

Review 3.  Changes in Sewage Sludge Chemical Signatures During a COVID-19 Community Lockdown, Part 1: Traffic, Drugs, Mental Health, and Disinfectants.

Authors:  Sara L Nason; Elizabeth Lin; Brian Eitzer; Jeremy Koelmel; Jordan Peccia
Journal:  Environ Toxicol Chem       Date:  2021-10-19       Impact factor: 4.218

4.  Environmental impact assessment of COVID-19 therapeutic solutions. A prospective analysis.

Authors:  José V Tarazona; Marta Martínez; María-Aránzazu Martínez; Arturo Anadón
Journal:  Sci Total Environ       Date:  2021-03-10       Impact factor: 7.963

  4 in total

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