other · Figshare · 2023
Exponential kernel smoothing R Function.
Kelly Hoffman (11336036), David Holcomb (10319240), Stacie Reckling (17199933), Thomas Clerkin (12937088), Denene Blackwood (6623078), Rachelle Beattie (17199936), Francis de los Reyes (17199939), Angela Harris (3831487), Helena Mitasova (3828700), Nadine Kotlarz (2616943), Jill Stewart (429683), Jacob Kazenelson (16624662), Lawrence Cahoon (17199942), Arthur Frampton (17199945), Mariya Munir (17199948), Allison Lee (4677154), Steven Berkowitz (2383336), Rachel Noble (584043), Virginia T. Guidry (6014533), Lawrence Engel (17199951), Marc Serre (1941109), Ariel Christensen (17199954)
Cited by 0Open access
Abstract
<div><p>Wastewater surveillance emerged during the COVID-19 pandemic as a novel strategy for tracking the burden of illness in communities. Previous work has shown that trends in wastewater SARS-CoV-2 viral loads correlate well with reported COVID-19 case trends over longer time periods (i.e., months). We used detrending time series to reveal shorter sub-trend patterns (i.e., weeks) to identify leads or lags in the temporal alignment of the wastewater/case relationship. Daily incident COVID-19 cases and twice-weekly wastewater SARS-CoV-2 viral loads measured at 20 North Carolina sewersheds in 2021 were detrended using smoothing ranges of ∞, 16, 8, 4 and 2 weeks, to produce detrended cases and wastewater viral loads at progressively finer time scales. For each sewershed and smoothing range, we calculated the Spearman correlation between the cases and the wastewater viral loads with offsets of -7 to +7 days. We identified a conclusive lead/lag relationship at 15 of 20 sewersheds, with detrended wastewater loads temporally leading detrended COVID-19 cases at 11 of these sites. For the 11 leading sites, the correlation between wastewater loads and cases was greatest for wastewater loads sampled at a median lead time of 6 days before the cases were reported. Distinct lead/lag relationships were the most pronounced after detrending with smoothing ranges of 4–8 weeks, suggesting that SARS-CoV-2 wastewater viral loads can track fluctuations in COVID-19 case incidence rates at fine time scales and may serve as a leading indicator in many settings. These results could help public health officials identify, and deploy timely responses in, areas where cases are increasing faster than the overall pandemic trend.</p></div>
Cite this paper
(11336036), K. H., (10319240), D. H., (17199933), S. R., (12937088), T. C., (6623078), D. B., (17199936), R. B., (17199939), F. D. L. R., (3831487), A. H., (3828700), H. M., (2616943), N. K., (429683), J. S., (16624662), J. K., (17199942), L. C., (17199945), A. F., (17199948), M. M., (4677154), A. L., (2383336), S. B., (584043), R. N., (6014533), V. T. G., . . . (17199954), A. C. (2023). Exponential kernel smoothing R Function. Figshare. https://doi.org/10.1371/journal.pwat.0000140.s026
(11336036), Kelly Hoffman, et al. “Exponential kernel smoothing R Function.” Figshare, 2023, https://doi.org/10.1371/journal.pwat.0000140.s026.
(11336036), Kelly Hoffman, David Holcomb (10319240), Stacie Reckling (17199933), Thomas Clerkin (12937088), Denene Blackwood (6623078), Rachelle Beattie (17199936), Francis de los Reyes (17199939), et al. 2023. “Exponential kernel smoothing R Function.” Figshare. https://doi.org/10.1371/journal.pwat.0000140.s026.
(11336036), K.H. et al. (2023) ‘Exponential kernel smoothing R Function’, Figshare. Available at: https://doi.org/10.1371/journal.pwat.0000140.s026.
@misc{113360362023exponential,
title = {{Exponential kernel smoothing R Function.}},
author = {(11336036), Kelly Hoffman and (10319240), David Holcomb and (17199933), Stacie Reckling and (12937088), Thomas Clerkin and (6623078), Denene Blackwood and (17199936), Rachelle Beattie and (17199939), Francis de los Reyes and (3831487), Angela Harris and (3828700), Helena Mitasova and (2616943), Nadine Kotlarz and (429683), Jill Stewart and (16624662), Jacob Kazenelson and (17199942), Lawrence Cahoon and (17199945), Arthur Frampton and (17199948), Mariya Munir and (4677154), Allison Lee and (2383336), Steven Berkowitz and (584043), Rachel Noble and (6014533), Virginia T. Guidry and (17199951), Lawrence Engel and (1941109), Marc Serre and (17199954), Ariel Christensen},
journal = {Figshare},
year = {2023},
doi = {10.1371/journal.pwat.0000140.s026}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.