Estimated transmission dynamics of SARS-CoV-2 variants from wastewater are robust to differential shedding
Abstract The COVID-19 pandemic has accelerated the development and adoption of wastewater-based epidemiology. Wastewater samples can provide genomic information for detecting and assessing the spread of SARS-CoV-2 variants in communities and for estimating important epidemiological parameters such as the growth advantage of the variant. However, despite demonstrated successes, epidemiological data derived from wastewater suffers from potential biases. Of particular concern are differential shedding profiles that different variants of concern exhibit, because they can shift the relationship between viral loads in wastewater and prevalence estimates derived from clinical cases. Using mathematical modeling, simulations, and Swiss surveillance data, we demonstrate that this bias does not affect estimation of the growth advantage of the variant and has only a limited and transient impact on estimates of the effective reproduction number. Thus, population-level epidemiological parameters derived from wastewater maintain their advantages over traditional clinical-derived estimates, even in the presence of differential shedding among variants..
| Medienart: |
|
|---|
Preprint| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
bioRxiv.org - (2023) vom: 03. Nov. Zur Gesamtaufnahme - year:2023 |
|---|
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Dreifuss, David [VerfasserIn] |
|---|
| Links: |
Volltext [kostenfrei] |
|---|
| Themen: |
|---|
| doi: |
10.1101/2023.10.25.23297539 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
XBI041334000 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | XBI041334000 | ||
| 003 | DE-627 | ||
| 005 | 20231205143838.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231027s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1101/2023.10.25.23297539 |2 doi | |
| 035 | |a (DE-627)XBI041334000 | ||
| 035 | |a (biorXiv)10.1101/2023.10.25.23297539 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Dreifuss, David |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Estimated transmission dynamics of SARS-CoV-2 variants from wastewater are robust to differential shedding |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Abstract The COVID-19 pandemic has accelerated the development and adoption of wastewater-based epidemiology. Wastewater samples can provide genomic information for detecting and assessing the spread of SARS-CoV-2 variants in communities and for estimating important epidemiological parameters such as the growth advantage of the variant. However, despite demonstrated successes, epidemiological data derived from wastewater suffers from potential biases. Of particular concern are differential shedding profiles that different variants of concern exhibit, because they can shift the relationship between viral loads in wastewater and prevalence estimates derived from clinical cases. Using mathematical modeling, simulations, and Swiss surveillance data, we demonstrate that this bias does not affect estimation of the growth advantage of the variant and has only a limited and transient impact on estimates of the effective reproduction number. Thus, population-level epidemiological parameters derived from wastewater maintain their advantages over traditional clinical-derived estimates, even in the presence of differential shedding among variants. | ||
| 650 | 4 | |a Biology |7 (dpeaa)DE-84 | |
| 650 | 4 | |a 570 |7 (dpeaa)DE-84 | |
| 700 | 1 | |a Huisman, Jana S. |0 (orcid)0000-0002-1782-8109 |4 aut | |
| 700 | 1 | |a Rusch, Johannes C. |4 aut | |
| 700 | 1 | |a Caduff, Lea |4 aut | |
| 700 | 1 | |a Ganesanandamoorthy, Pravin |4 aut | |
| 700 | 1 | |a Devaux, Alexander J. |4 aut | |
| 700 | 1 | |a Gan, Charles |4 aut | |
| 700 | 1 | |a Stadler, Tanja |4 aut | |
| 700 | 1 | |a Kohn, Tamar |4 aut | |
| 700 | 1 | |a Ort, Christoph |4 aut | |
| 700 | 1 | |a Beerenwinkel, Niko |0 (orcid)0000-0002-0573-6119 |4 aut | |
| 700 | 1 | |a Julian, Timothy R. |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t bioRxiv.org |g (2023) vom: 03. Nov. |
| 773 | 1 | 8 | |g year:2023 |g day:03 |g month:11 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1101/2023.10.25.23297539 |z kostenfrei |3 Volltext |
| 912 | |a GBV_XBI | ||
| 951 | |a AR | ||
| 952 | |j 2023 |b 03 |c 11 | ||