Viral variant-resolved wastewater surveillance of SARS-CoV-2 at national scale.
Journal
Nature biotechnology
ISSN: 1546-1696
Titre abrégé: Nat Biotechnol
Pays: United States
ID NLM: 9604648
Informations de publication
Date de publication:
12 2022
12 2022
Historique:
received:
02
12
2021
accepted:
07
06
2022
pubmed:
20
7
2022
medline:
17
12
2022
entrez:
19
7
2022
Statut:
ppublish
Résumé
SARS-CoV-2 surveillance by wastewater-based epidemiology is poised to provide a complementary approach to sequencing individual cases. However, robust quantification of variants and de novo detection of emerging variants remains challenging for existing strategies. We deep sequenced 3,413 wastewater samples representing 94 municipal catchments, covering >59% of the population of Austria, from December 2020 to February 2022. Our system of variant quantification in sewage pipeline designed for robustness (termed VaQuERo) enabled us to deduce the spatiotemporal abundance of predefined variants from complex wastewater samples. These results were validated against epidemiological records of >311,000 individual cases. Furthermore, we describe elevated viral genetic diversity during the Delta variant period, provide a framework to predict emerging variants and measure the reproductive advantage of variants of concern by calculating variant-specific reproduction numbers from wastewater. Together, this study demonstrates the power of national-scale WBE to support public health and promises particular value for countries without extensive individual monitoring.
Identifiants
pubmed: 35851376
doi: 10.1038/s41587-022-01387-y
pii: 10.1038/s41587-022-01387-y
doi:
Substances chimiques
Wastewater
0
RNA, Viral
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1814-1822Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.
Références
Nicola, M. et al. The socio-economic implications of the coronavirus pandemic (COVID-19): a review. Int. J. Surg. 78, 185–193 (2020).
doi: 10.1016/j.ijsu.2020.04.018
Josephson, A., Kilic, T. & Michler, J. D. Socioeconomic impacts of COVID-19 in low-income countries. Nat. Hum. Behav. 5, 557–565 (2021).
doi: 10.1038/s41562-021-01096-7
Harvey, W. T. et al. SARS-CoV-2 variants, spike mutations and immune escape. Nat. Rev. Microbiol. 19, 409–424 (2021).
doi: 10.1038/s41579-021-00573-0
Callaway, E. Heavily mutated coronavirus variant puts scientists on alert. Nature 21, 600 (2021).
Truong, T. T. et al. Increased viral variants in children and young adults with impaired humoral immunity and persistent SARS-CoV-2 infection: a consecutive case series. EBioMedicine 67, 103355 (2021).
doi: 10.1016/j.ebiom.2021.103355
Lucas, C. et al. Impact of circulating SARS-CoV-2 variants on mRNA vaccine-induced immunity. Nature 600, 523–529 (2021).
doi: 10.1038/s41586-021-04085-y
Chandler, J.C. et al. SARS-CoV-2 exposure in wild white-tailed deer (Odocoileus virginianus). Proc. Natl Acad. Sci. USA 118, e2114828118 (2021).
doi: 10.1073/pnas.2114828118
Plante, J. A. et al. The variant gambit: COVID-19’s next move. Cell Host Microbe 29, 508–515 (2021).
doi: 10.1016/j.chom.2021.02.020
Gardy, J. L. & Loman, N. J. Towards a genomics-informed, real-time, global pathogen surveillance system. Nat. Rev. Genet. 19, 9–20 (2018).
doi: 10.1038/nrg.2017.88
Grubaugh, N. D. et al. Tracking virus outbreaks in the twenty-first century. Nat Microbiol. 4, 10–19 (2019).
doi: 10.1038/s41564-018-0296-2
Smith, G. J. D. et al. Origins and evolutionary genomics of the 2009 swine-origin H1N1 influenza a epidemic. Nature 459, 1122–1125 (2009).
doi: 10.1038/nature08182
Inzaule, S. C., Tessema, S. K., Kebede, Y., Ogwell Ouma, A. E. & Nkengasong, J. N. Genomic-informed pathogen surveillance in Africa: opportunities and challenges. Lancet Infect. Dis. 21, e281–e289 (2021).
doi: 10.1016/S1473-3099(20)30939-7
Woolhouse, M. E. J., Rambaut, A. & Kellam, P. Lessons from Ebola: improving infectious disease surveillance to inform outbreak management. Sci. Transl. Med. 7, 307rv5 (2015).
doi: 10.1126/scitranslmed.aab0191
Furuse, Y. Genomic sequencing effort for SARS-CoV-2 by country during the pandemic. Int. J. Infect. Dis. 103, 305–307 (2021).
doi: 10.1016/j.ijid.2020.12.034
The COVID-19 Genomics UK (COG-UK) consortium. An integrated national scale SARS-CoV-2 genomic surveillance network. Lancet Microbe 1, e99–e100 (2020).
doi: 10.1016/S2666-5247(20)30054-9
Treibel, T. A. et al. COVID-19: PCR screening of asymptomatic health-care workers at London hospital. Lancet 395, 1608–1610 (2020).
doi: 10.1016/S0140-6736(20)31100-4
Brito, A. F. et al. Global disparities in SARS-CoV-2 genomic surveillance. Preprint at medRxiv https://doi.org/10.1101/2021.08.21.21262393 (2021)..
Belman, S., Saha, S. & Beale, M. A. SARS-CoV-2 genomics as a springboard for future disease mitigation in LMICs. Nat. Rev. Microbiol. https://doi.org/10.1038/s41579-021-00664-y (2021).
doi: 10.1038/s41579-021-00664-y
Majid, F., Omer, S. B. & Khwaja, A. I. Optimising SARS-CoV-2 pooled testing for low-resource settings. Lancet Microbe 1, e101–e102 (2020).
doi: 10.1016/S2666-5247(20)30056-2
Larsen, D. A., Green, H., Collins, M. B. & Kmush, B. L. Wastewater monitoring, surveillance and epidemiology: a review of terminology for a common understanding. FEMS Microbes 2, xtab011 (2021).
doi: 10.1093/femsmc/xtab011
Cavany, S. et al. Inferring SARS-CoV-2 RNA shedding into wastewater relative to the time of infection. Epidemiol Infect. 150, e21 (2022).
doi: 10.1017/S0950268821002752
Bonanno Ferraro, G. et al. A state-of-the-art scoping review on SARS-CoV-2 in sewage focusing on the potential of wastewater surveillance for the monitoring of the COVID-19 pandemic. Food Environ. Virol. https://doi.org/10.1007/s12560-021-09498-6 (2021).
Hassard, F., Lundy, L., Singer, A. C., Grimsley, J. & di Cesare, M. Innovation in wastewater near-source tracking for rapid identification of COVID-19 in schools. Lancet Microbe 2, e4–e5 (2021).
doi: 10.1016/S2666-5247(20)30193-2
la Rosa, G. et al. SARS-CoV-2 has been circulating in northern Italy since December 2019: evidence from environmental monitoring. Sci. Total Environ. 750, 141711 (2021).
doi: 10.1016/j.scitotenv.2020.141711
Martin, J. et al. Tracking SARS-CoV-2 in sewage: evidence of changes in virus variant predominance during COVID-19 pandemic. Viruses 12, 1144 (2020).
doi: 10.3390/v12101144
Nemudryi, A. et al. Temporal Detection and Phylogenetic Assessment of SARS-CoV-2 in Municipal Wastewater. Cell Rep. Med. 1, 100098 (2020).
doi: 10.1016/j.xcrm.2020.100098
Wurtzer, S. et al. Monitoring the propagation of SARS CoV2 variants by tracking identified mutation in wastewater using specific RT–qPCR. Preprint at medRxiv https://doi.org/10.1101/2021.03.10.21253291 (2021).
Peccia, J. et al. Measurement of SARS-CoV-2 RNA in wastewater tracks community infection dynamics. Nat. Biotechnol. 38, 1164–1167 (2020).
doi: 10.1038/s41587-020-0684-z
Agrawal, S., Orschler, L. & Lackner, S. Long-term monitoring of SARS-CoV-2 RNA in wastewater of the Frankfurt metropolitan area in Southern Germany. Sci Rep. 11, 5372 (2021).
doi: 10.1038/s41598-021-84914-2
Daleiden, B. et al. Wastewater surveillance of SARS-CoV-2 in Austria: development, implementation, and operation of the Tyrolean wastewater monitoring program. J. Water Health 20, 314–328 (2022).
doi: 10.2166/wh.2022.218
Radu, E. et al. Emergence of SARS-CoV-2 Alpha lineage and its correlation with quantitative wastewater-based epidemiology data. Water Res. 215, 118257 (2022).
doi: 10.1016/j.watres.2022.118257
Markt, R. et al. Detection and abundance of SARS-CoV-2 in wastewater in Liechtenstein, and the estimation of prevalence and impact of the B.1.1.7 variant. J. Water Health 20, 114–125 (2021).
doi: 10.2166/wh.2021.180
Karthikeyan, S. et al. High-throughput wastewater SARS-CoV-2 detection enables forecasting of community infection dynamics in San Diego County. mSystems 6, e00045-21 (2021).
doi: 10.1128/mSystems.00045-21
Crits-Christoph, A. et al. Genome sequencing of sewage detects regionally prevalent SARS-CoV-2 variants. mBio 12, 02703-20 (2021).
doi: 10.1128/mBio.02703-20
Izquierdo-Lara, R. et al. Monitoring SARS-CoV-2 circulation and diversity through community wastewater sequencing, the Netherlands and Belgium. Emerg. Infect. Dis. 27, 1405–1415 (2021).
doi: 10.3201/eid2705.204410
Agrawal, S. et al. A pan-European study of SARS-CoV-2 variants in wastewater 2 under the EU Sewage Sentinel System. Preprint at medRxiv https://doi.org/10.1101/2021.06.11.21258756 (2021).
Bar-Or, I. et al. Detection of SARS-CoV-2 variants by genomic analysis of wastewater samples in Israel. Sci. Total Environ. 789, 148002 (2021).
doi: 10.1016/j.scitotenv.2021.148002
Fontenele, S. et al. High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants. Water Res. 205, 117710 (2021).
doi: 10.1016/j.watres.2021.117710
Fuqua, J. L. et al. The rapid assessment of aggregated wastewater samples for genomic surveillance of SARS-CoV-2 on a city-wide scale. Pathogens 10, 1271 (2021).
doi: 10.3390/pathogens10101271
Jahn, K. et al. Detection of SARS-CoV-2 variants in Switzerland by genomic analysis of wastewater samples. Preprint at medRxiv https://doi.org/10.1101/2021.01.08.21249379 (2021).
Pechlivanis, N. et al. Detecting SARS-CoV-2 lineages and mutational load in municipal wastewater and a use-case in the metropolitan area of Thessaloniki, Greece. Sci. Rep. 12, 2659 (2021).
doi: 10.1038/s41598-022-06625-6
Smyth, D.S., Trujillo, M., Gregory, D.A. et al. Tracking cryptic SARS-CoV-2 lineages detected in NYC wastewater. Nat Commun 13, 635 (2022). https://doi.org/10.1038/s41467-022-28246-3
la Rosa, G. et al. Rapid screening for SARS-CoV-2 variants of concern in clinical and environmental samples using nested RT-PCR assays targeting key mutations of the spike protein. Water Res. 197, 117104 (2021).
doi: 10.1016/j.watres.2021.117104
Prado, T. et al. Wastewater-based epidemiology as a useful tool to track SARS-CoV-2 and support public health policies at municipal level in Brazil. Water Res. 191, 116810 (2021).
doi: 10.1016/j.watres.2021.116810
Rimoldi, S. G. et al. Presence and infectivity of SARS-CoV-2 virus in wastewaters and rivers. Sci. Total Environ. 744, 140911 (2020).
doi: 10.1016/j.scitotenv.2020.140911
Agrawal, S., Orschler, L. & Lackner, S. Metatranscriptomic analysis reveals SARS-CoV-2 mutations in wastewater of the Frankfurt metropolitan area in Southern Germany. Microbiol. Resour. Announc. 10, e00280-21 (2021).
doi: 10.1128/MRA.00280-21
Huisman, J. S. et al. Wastewater-based estimation of the effective reproductive number of SARS-CoV-2. Environ. Health Perspect. 130, 057011 (2022).
doi: 10.1289/EHP10050
Jahn, K. et al. Detection and surveillance of SARS-CoV-2 genomic variants in wastewater. Preprint at medRxiv https://doi.org/10.1101/2021.01.08.21249379 (2021)..
O’Toole, Á. et al. Assignment of epidemiological lineages in an emerging pandemic using the pangolin tool. Virus Evol. 7, veab064 (2021).
doi: 10.1093/ve/veab064
Özkan, E. et al. High-throughput mutational surveillance of the SARS-CoV-2 spike gene. Preprint at medRxiv https://doi.org/10.1101/2021.07.22.21259587 (2021).
Paetzold, J. et al. Impacts of rapid mass vaccination against SARS-CoV2 in an early variant of concern hotspot. Nat. Commun. 13, 612 (2022).
doi: 10.1038/s41467-022-28233-8
Hasell, J. et al. A cross-country database of COVID-19 testing. Sci. Data 7, 345 (2020).
doi: 10.1038/s41597-020-00688-8
Progress on household drinking water, sanitation and hygiene 2000-2020: five years into the SDGs. (WHO and UNICEF, 2021).
Popa, A. et al. Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2. Sci. Transl. Med. 12, eabe2555 (2020).
doi: 10.1126/scitranslmed.abe2555
Elbe, S. & Buckland-Merrett, G. Data, disease and diplomacy: GISAID’s innovative contribution to global health. Global Challenges 1, 33–46 (2017).
doi: 10.1002/gch2.1018
Shu, Y. & McCauley, J. GISAID: global initiative on sharing all influenza data—from vision to reality. Eurosurveillance 22, 30494 (2017).
doi: 10.2807/1560-7917.ES.2017.22.13.30494
Cragg, J. G. Some statistical models for limited dependent variables with application to the demand for durable goods. Econometrica 39, 829–844 (1971).
doi: 10.2307/1909582
van Poelvoorde, L. A. et al. Strategy and performance evaluation of low-frequency variant calling for SARS-CoV-2 using targeted deep Illumina sequencing. Front. Microbiol. 12, 747458 (2021).
doi: 10.3389/fmicb.2021.747458
Itokawa, K., Sekizuka, T., Hashino, M., Tanaka, R. & Kuroda, M. Disentangling primer interactions improves SARS-CoV-2 genome sequencing by multiplex tiling PCR. PLoS One 15, e0239403 (2020).
doi: 10.1371/journal.pone.0239403
Nei, M. & Li, W.-H. Mathematical model for studying genetic variation in terms of restriction endonucleases (molecular evolution/mitochondrial DNA/nucleotide diversity). Genetics 76, 5269–5273 (1979).
Been, F. et al. Population normalization with ammonium in wastewater-based epidemiology: application to illicit drug monitoring. Environ. Sci. Technol. 48, 8162–8169 (2014).
doi: 10.1021/es5008388
Cori, A., Ferguson, N. M., Fraser, C. & Cauchemez, S. A new framework and software to estimate time-varying reproduction numbers during epidemics. Am. J. Epidemiology 178, 1505–1512 (2013).
doi: 10.1093/aje/kwt133
Campbell, F. et al. Increased transmissibility and global spread of SARSCoV- 2 variants of concern as at June 2021. Eurosurveillance 26, 1–6 (2021).
doi: 10.2807/1560-7917.ES.2021.26.24.2100509
Davies, N. G. et al. Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England. Science 372, eabg3055 (2021).
doi: 10.1126/science.abg3055
Washington, N. L. et al. Emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States. Cell 184, 2587–2594.e7 (2021).
doi: 10.1016/j.cell.2021.03.052
Ito, K., Piantham, C. & Nishiura, H. Relative instantaneous reproduction number of Omicron SARS-CoV-2 variant with respect to the Delta variant in Denmark. J. Med. Virol. 94, 2265–2268 (2021).
doi: 10.1002/jmv.27560
Baaijens, J. A. et al. Variant abundance estimation for SARS-CoV-2 in 1 wastewater using RNA-Seq quantification 2. Preprint at medRxiv https://doi.org/10.1101/2021.08.31.21262938 (2021).
Pipes, L., Chen, Z., Afanaseva, S. & Nielsen, R. Estimating the relative proportions of SARS-CoV-2 strains from 2 wastewater samples. Preprint at medRxiv https://doi.org/10.1101/2022.01.13.22269236 (2021).
Sapoval, N. et al. Enhanced Detection of Recently Emerged SARS-CoV-2 Variants of Concern in Wastewater. Preprint at medRxiv https://doi.org/10.1101/2021.09.08.21263279 (2021).
Wade, M. J. et al. Understanding and managing uncertainty and variability for wastewater monitoring beyond the pandemic: lessons learned from the United Kingdom national COVID-19 surveillance programmes. J. Hazard. Mater. 424, 127456 (2022).
doi: 10.1016/j.jhazmat.2021.127456
Karthikeyan, S. et al. Rapid, large-scale wastewater surveillance and automated reporting system enable early detection of nearly 85% of COVID-19 cases on a university campus. mSystems 6, 793–814 (2021).
doi: 10.1128/mSystems.00793-21
Calderón-Franco, D., Orschler, L., Lackner, S., Agrawal, S. & Weissbrodt, D. G. Monitoring SARS-CoV-2 in sewage: toward sentinels with analytical accuracy. Sci. Total Environ. 804, 150244 (2022).
doi: 10.1016/j.scitotenv.2021.150244
Shrestha, S. et al. Wastewater-based epidemiology for cost-effective mass surveillance of covid-19 in low-and middle-income countries: challenges and opportunities. Water 13, 2897 (2021).
doi: 10.3390/w13202897
Hong, P. Y. et al. Estimating the minimum number of SARS-CoV-2 infected cases needed to detect viral RNA in wastewater: to what extent of the outbreak can surveillance of wastewater tell us? Environ. Res. 195, 110748 (2021).
doi: 10.1016/j.envres.2021.110748
Basu, P. et al. Surveillance of SARS-CoV-2 RNA in open-water sewage canals contaminated with untreated wastewater in resource-constrained regions. Access Microbiol. 4, 000318 (2022).
doi: 10.1099/acmi.0.000318
Chan, M. C. W. et al. Seasonal influenza a virus in feces of hospitalized adults. Emerg. Infect. Dis. 17, 2038–2042 (2011).
doi: 10.3201/eid1711.110205
Pogka, V. et al. Laboratory surveillance of polio and other enteroviruses in high-risk populations and environmental samples. Appl. Environ. Microbiol. 83, e02872-16 (2017).
doi: 10.1128/AEM.02872-16
Wolfe, M. K. et al. Wastewater-based detection of an influenza outbreak. Preprint at medRxiv https://doi.org/10.1101/2022.02.15.22271027 (2022).
Lynch, M., Bost, D., Wilson, S., Maruki, T. & Harrison, S. Population-genetic inference from pooled-sequencing data. Genome Biol. Evol. 6, 1210–1218 (2014).
doi: 10.1093/gbe/evu085
Suratekar, R. et al. High diversity in Delta variant across countries revealed by genome‐wide analysis of SARS‐CoV‐2 beyond the Spike protein. Mol. Syst. Biol. 18, e10673 (2022).
doi: 10.15252/msb.202110673
Stern, A. et al. The unique evolutionary dynamics of the SARS-CoV-2 Delta variant-2 sequencing. Preprint at medRxiv https://doi.org/10.1101/2021.08.05.21261642 (2021).
Yuan, S. et al. Pathogenicity, transmissibility, and fitness of SARS-CoV-2 Omicron in Syrian hamsters. Science. 0, eabn8939. 10.1126/science.abn8939 (2022).
Safford, H. R., Shapiro, K. & Bischel, H. N. Wastewater analysis can be a powerful public health tool—if it’s done sensibly. Proc. Natl Acad. Sci. USA 119, e2119600119 (2022).
doi: 10.1073/pnas.2119600119
Water quality—determination of the chemical oxygen demand index (ST-COD)—small-scale sealed-tube method. DS/ISO 15705:2002(E) (International Standards Organisation, 2002).
Water quality—determination of nitrogen—part 1: method using oxidative digestion with peroxodisulfate. ISO 11905-1:1997 (International Standards Organisation, 1997).
Water quality—determination of ammonium nitrogen—method by flow analysis (CFA and FIA) and spectrometric detection. ISO 11732:2005. (International Standards Organisation, 2005).
Ye, Y., Ellenberg, R. M., Graham, K. E. & Wigginton, K. R. Survivability, partitioning, and recovery of enveloped viruses in untreated municipal wastewater. Environ. Sci. Technol. 50, 5077–5085 (2016).
doi: 10.1021/acs.est.6b00876
Wu, F. et al. SARS-CoV-2 titers in wastewater are higher than expected from clinically confirmed cases. mSystems 5, e00614-20 (2020).
doi: 10.1128/mSystems.00614-20
Bushnell, B., Rood, J. & Singer, E. BBMerge – Accurate paired shotgun read merging via overlap. PLoS One 12, e0185056 (2017).
doi: 10.1371/journal.pone.0185056
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
doi: 10.1093/bioinformatics/btp324
Grubaugh, N. D. et al. An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar. Genome Biol. 20, 8 (2019).
doi: 10.1186/s13059-018-1618-7
Wilm, A. et al. LoFreq: a sequence-quality aware, ultra-sensitive variant caller for uncovering cell-population heterogeneity from high-throughput sequencing datasets. Nucleic Acids Res. 40, 11189–11201 (2012).
doi: 10.1093/nar/gks918
Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993 (2011).
doi: 10.1093/bioinformatics/btr509
Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin) 6, 80–92 (2012).
doi: 10.4161/fly.19695
Cingolani, P. et al. Using Drosophila melanogaster as a model for genotoxic chemical mutational studies with a new program, SnpSift. Front. Genet. 3, 35 (2012).
doi: 10.3389/fgene.2012.00035
Smithson, M. & Verkuilen, J. A better lemon squeezer? Maximum-likelihood regression with beta-distributed dependent variables. Psychol. Methods 11, 54–71 (2006).
doi: 10.1037/1082-989X.11.1.54
Rigby, R. A. & Stasinopoulos, D. M. Generalized additive models for location, scale and shape. J. R. Stat. Soc. C Appl. Stat. 54, 507–554 (2005).
doi: 10.1111/j.1467-9876.2005.00510.x
Barndorff-Nielsen, E. & Jorgensen, B. Some Parametric Models on the Simplex. J.Multivar. Anal. 39, 106–116 (1991).
doi: 10.1016/0047-259X(91)90008-P
Lee, S., Wolberg, G. & Shin, S. Y. Scattered data interpolation with multilevel B-splines. IEEE Trans. Vis. Comput. Graph. 3, 228–244 (1997).
doi: 10.1109/2945.620490
Thompson, R. N. et al. Improved inference of time-varying reproduction numbers during infectious disease outbreaks. Epidemics 29, 100356 (2019).
doi: 10.1016/j.epidem.2019.100356
Hart, W. et al. Inference of the SARS-CoV-2 generation time using UK household data. eLife 11, e70767 (2022).
doi: 10.7554/eLife.70767
Hart, W. S. et al. Generation time of the alpha and delta SARS-CoV-2 variants: an epidemiological analysis. Lancet Infect. Dis. 22, 603–610 (2022).
doi: 10.1016/S1473-3099(22)00001-9
Abbott, S., Sherratt, K., Moritz, G. & Funk, S. Estimation of the test to test distribution as a proxy for generation interval distribution for the Omicron variant in England. Preprint at medRxiv https://doi.org/10.1101/2022.01.08.22268920 (2022).
Rousseeuw, P. J. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53–65 (1987).
doi: 10.1016/0377-0427(87)90125-7
Nelson, C. W., Moncla, L. H. & Hughes, A. L. SNPGenie: estimating evolutionary parameters to detect natural selection using pooled next-generation sequencing data. Bioinformatics 31, 3709–3711 (2015).
Heiler, G. et al. Country-wide mobility changes observed using mobile phone data during COVID-19 pandemic. In 2020 IEEE International Conference on Big Data (Big Data) 3123–3132 (IEEE, 2020).
Triska, P., Amman, F., Endler, L. & Bergthaler, A. WAVES (Web-based tool for Analysis and Visualization of Environmental Samples) – a web application for visualization of wastewater pathogen sequencing results. Preprint at medRxiv https://doi.org/10.1101/2022.05.31.22275831 (2022).