Cargando…

Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants

(MOTIVATION): Wastewater-based epidemiology (WBE) has emerged as a promising approach for monitoring the COVID-19 pandemic, since the measurement process is cost-effective and is exposed to fewer potential errors compared to other indicators like hospitalization data or the number of detected cases....

Descripción completa

Detalles Bibliográficos
Autores principales: Polcz, Péter, Tornai, Kálmán, Juhász, János, Cserey, György, Surján, György, Pándics, Tamás, Róka, Eszter, Vargha, Márta, Reguly, István Z., Csikász-Nagy, Attila, Pongor, Sándor, Szederkényi, Gábor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier Ltd. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265948/
https://www.ncbi.nlm.nih.gov/pubmed/37295226
http://dx.doi.org/10.1016/j.watres.2023.120098
_version_ 1785058639142191104
author Polcz, Péter
Tornai, Kálmán
Juhász, János
Cserey, György
Surján, György
Pándics, Tamás
Róka, Eszter
Vargha, Márta
Reguly, István Z.
Csikász-Nagy, Attila
Pongor, Sándor
Szederkényi, Gábor
author_facet Polcz, Péter
Tornai, Kálmán
Juhász, János
Cserey, György
Surján, György
Pándics, Tamás
Róka, Eszter
Vargha, Márta
Reguly, István Z.
Csikász-Nagy, Attila
Pongor, Sándor
Szederkényi, Gábor
author_sort Polcz, Péter
collection PubMed
description (MOTIVATION): Wastewater-based epidemiology (WBE) has emerged as a promising approach for monitoring the COVID-19 pandemic, since the measurement process is cost-effective and is exposed to fewer potential errors compared to other indicators like hospitalization data or the number of detected cases. Consequently, WBE was gradually becoming a key tool for epidemic surveillance and often the most reliable data source, as the intensity of clinical testing for COVID-19 drastically decreased by the third year of the pandemic. Recent results suggests that the model-based fusion of wastewater measurements with clinical data and other indicators is essential in future epidemic surveillance. (METHOD): In this work, we developed a wastewater-based compartmental epidemic model with a two-phase vaccination dynamics and immune evasion. We proposed a multi-step optimization-based data assimilation method for epidemic state reconstruction, parameter estimation, and prediction. The computations make use of the measured viral load in wastewater, the available clinical data (hospital occupancy, delivered vaccine doses, and deaths), the stringency index of the official social distancing rules, and other measures. The current state assessment and the estimation of the current transmission rate and immunity loss allow a plausible prediction of the future progression of the pandemic. (RESULTS): Qualitative and quantitative evaluations revealed that the contribution of wastewater data in our computational epidemiological framework makes predictions more reliable. Predictions suggest that at least half of the Hungarian population has lost immunity during the epidemic outbreak caused by the BA.1 and BA.2 subvariants of Omicron in the first half of 2022. We obtained a similar result for the outbreaks caused by the subvariant BA.5 in the second half of 2022. (APPLICABILITY): The proposed approach has been used to support COVID management in Hungary and could be customized for other countries as well.
format Online
Article
Text
id pubmed-10265948
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher The Author(s). Published by Elsevier Ltd.
record_format MEDLINE/PubMed
spelling pubmed-102659482023-06-14 Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants Polcz, Péter Tornai, Kálmán Juhász, János Cserey, György Surján, György Pándics, Tamás Róka, Eszter Vargha, Márta Reguly, István Z. Csikász-Nagy, Attila Pongor, Sándor Szederkényi, Gábor Water Res Article (MOTIVATION): Wastewater-based epidemiology (WBE) has emerged as a promising approach for monitoring the COVID-19 pandemic, since the measurement process is cost-effective and is exposed to fewer potential errors compared to other indicators like hospitalization data or the number of detected cases. Consequently, WBE was gradually becoming a key tool for epidemic surveillance and often the most reliable data source, as the intensity of clinical testing for COVID-19 drastically decreased by the third year of the pandemic. Recent results suggests that the model-based fusion of wastewater measurements with clinical data and other indicators is essential in future epidemic surveillance. (METHOD): In this work, we developed a wastewater-based compartmental epidemic model with a two-phase vaccination dynamics and immune evasion. We proposed a multi-step optimization-based data assimilation method for epidemic state reconstruction, parameter estimation, and prediction. The computations make use of the measured viral load in wastewater, the available clinical data (hospital occupancy, delivered vaccine doses, and deaths), the stringency index of the official social distancing rules, and other measures. The current state assessment and the estimation of the current transmission rate and immunity loss allow a plausible prediction of the future progression of the pandemic. (RESULTS): Qualitative and quantitative evaluations revealed that the contribution of wastewater data in our computational epidemiological framework makes predictions more reliable. Predictions suggest that at least half of the Hungarian population has lost immunity during the epidemic outbreak caused by the BA.1 and BA.2 subvariants of Omicron in the first half of 2022. We obtained a similar result for the outbreaks caused by the subvariant BA.5 in the second half of 2022. (APPLICABILITY): The proposed approach has been used to support COVID management in Hungary and could be customized for other countries as well. The Author(s). Published by Elsevier Ltd. 2023-08-01 2023-05-25 /pmc/articles/PMC10265948/ /pubmed/37295226 http://dx.doi.org/10.1016/j.watres.2023.120098 Text en © 2023 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Polcz, Péter
Tornai, Kálmán
Juhász, János
Cserey, György
Surján, György
Pándics, Tamás
Róka, Eszter
Vargha, Márta
Reguly, István Z.
Csikász-Nagy, Attila
Pongor, Sándor
Szederkényi, Gábor
Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants
title Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants
title_full Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants
title_fullStr Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants
title_full_unstemmed Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants
title_short Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants
title_sort wastewater-based modeling, reconstruction, and prediction for covid-19 outbreaks in hungary caused by highly immune evasive variants
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265948/
https://www.ncbi.nlm.nih.gov/pubmed/37295226
http://dx.doi.org/10.1016/j.watres.2023.120098
work_keys_str_mv AT polczpeter wastewaterbasedmodelingreconstructionandpredictionforcovid19outbreaksinhungarycausedbyhighlyimmuneevasivevariants
AT tornaikalman wastewaterbasedmodelingreconstructionandpredictionforcovid19outbreaksinhungarycausedbyhighlyimmuneevasivevariants
AT juhaszjanos wastewaterbasedmodelingreconstructionandpredictionforcovid19outbreaksinhungarycausedbyhighlyimmuneevasivevariants
AT csereygyorgy wastewaterbasedmodelingreconstructionandpredictionforcovid19outbreaksinhungarycausedbyhighlyimmuneevasivevariants
AT surjangyorgy wastewaterbasedmodelingreconstructionandpredictionforcovid19outbreaksinhungarycausedbyhighlyimmuneevasivevariants
AT pandicstamas wastewaterbasedmodelingreconstructionandpredictionforcovid19outbreaksinhungarycausedbyhighlyimmuneevasivevariants
AT rokaeszter wastewaterbasedmodelingreconstructionandpredictionforcovid19outbreaksinhungarycausedbyhighlyimmuneevasivevariants
AT varghamarta wastewaterbasedmodelingreconstructionandpredictionforcovid19outbreaksinhungarycausedbyhighlyimmuneevasivevariants
AT regulyistvanz wastewaterbasedmodelingreconstructionandpredictionforcovid19outbreaksinhungarycausedbyhighlyimmuneevasivevariants
AT csikasznagyattila wastewaterbasedmodelingreconstructionandpredictionforcovid19outbreaksinhungarycausedbyhighlyimmuneevasivevariants
AT pongorsandor wastewaterbasedmodelingreconstructionandpredictionforcovid19outbreaksinhungarycausedbyhighlyimmuneevasivevariants
AT szederkenyigabor wastewaterbasedmodelingreconstructionandpredictionforcovid19outbreaksinhungarycausedbyhighlyimmuneevasivevariants