<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">AJMB</journal-id><journal-title-group><journal-title>American Journal of Molecular Biology</journal-title></journal-title-group><issn pub-type="epub">2161-6620</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ajmb.2022.123010</article-id><article-id pub-id-type="publisher-id">AJMB-118170</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biomedical&amp;Life Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  A Retrospective Analysis of Wastewater Confirms Dominant Circulation of SARS-CoV-2 Delta Variant in Nairobi, Kenya, between April 2021 and August 2021
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Patson</surname><given-names>Sichamba</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Fred</surname><given-names>Wamunyokoli</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Peter</surname><given-names>Borus</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Rosemary</surname><given-names>Nzunza</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Opanda</surname><given-names>Silvanos</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Samwel</surname><given-names>Symekher</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Samoel</surname><given-names>Ashimosi Khamadi</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Janet</surname><given-names>Majanja</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Meshack</surname><given-names>Wadegu</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Esther</surname><given-names>Chitechi</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Benlick</surname><given-names>Mwangi</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Evans</surname><given-names>Komen</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Stephen</surname><given-names>Ombija</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wallace</surname><given-names>Dimbuson Bulimo</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya</addr-line></aff><aff id="aff3"><addr-line>Kenya Medical Research Institute Centre for Virus Research, Nairobi, Kenya</addr-line></aff><aff id="aff1"><addr-line>Pan African University Institute for Basic Sciences Technology and Innovation (PAUSTI), Nairobi, Kenya</addr-line></aff><pub-date pub-type="epub"><day>31</day><month>05</month><year>2022</year></pub-date><volume>12</volume><issue>03</issue><fpage>109</fpage><lpage>121</lpage><history><date date-type="received"><day>8,</day>	<month>May</month>	<year>2022</year></date><date date-type="rev-recd"><day>26,</day>	<month>June</month>	<year>2022</year>	</date><date date-type="accepted"><day>29,</day>	<month>June</month>	<year>2022</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Wastewater surveillance has been applied in various parts of the world to monitor the introduction and transmissions of SARS-CoV-2 variants in a population. The knowledge of SARS-CoV-2 variants circulating in a population is critical to COVID-19 management and timing of the application of public health countermeasures. Contrary to the routine clinical surveillance of SARS-CoV-2 where cases from asymptomatic patients are often underreported, wastewater surveillance offers an unbiased tool for monitoring the extent of SARS-CoV-2 transmissions in a community. The present study aimed to characterize SARS-CoV-2 variants that circulated in Nairobi County, Kenya, between April 2021 and August 2021 utilizing wastewater samples. Viral RNA was extracted from wastewater samples, followed by SARS-CoV-2 screening by real-time RT-qPCR before targeted sequencing of the Spike gene. Forty samples were analyzed, of which 50% (n = 20) tested positive for SARS-CoV-2 by real-time RT-qPCR. Of these, 45% (n = 9) were successfully amplified by RT-PCR and sequenced. The majority (78%, 7/9) of the viruses belonged to the Delta (B.1.617.2) lineage of SARS-CoV-2, while a minority (22%) belonged to the Alpha (B.1.1.7) and Alpha-Delta lineages. Phylogenetic analysis of the SARS-COV-2 delta lineage strains revealed scattered clustering of the Kenyan viruses among the global strains included in the analysis, suggesting different introductory routes into the country. On the whole, our results confirm previous clinical findings that SARS-CoV-2 variants belonging to the Alpha (B.1.1.7) and Delta (B.1.617.2) lineages circulated in Nairobi County, Kenya during the study period, with the latter predominating. This is the first study to describe the diversity of SARS-CoV-2 variants circulating in Kenya, through wastewater analysis.
 
</p></abstract><kwd-group><kwd>Wastewater Surveillance</kwd><kwd> SARS-CoV-2</kwd><kwd> Delta Variants</kwd><kwd> Spike Gene</kwd><kwd> COVID-19</kwd><kwd> Kenya</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>The Coronavirus disease 2019 (COVID-19) is caused by a human coronavirus strain known as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) [<xref ref-type="bibr" rid="scirp.118170-ref1">1</xref>]. The Virus is transmitted through respiratory droplets and direct contact with both asymptomatic and symptomatic carriers [<xref ref-type="bibr" rid="scirp.118170-ref2">2</xref>]. The main symptoms of the disease include fever, coughing, sneezing, diarrhoea, dyspnoea, headache, sore throat, and rhinorrhoea [<xref ref-type="bibr" rid="scirp.118170-ref3">3</xref>]. COVID-19 was declared a global pandemic by the World Health Organization (WHO) on 11<sup>th</sup> March 2020 [<xref ref-type="bibr" rid="scirp.118170-ref4">4</xref>]. The first case of COVID-19 was confirmed in Kenya on 12<sup>th</sup> March 2020 [<xref ref-type="bibr" rid="scirp.118170-ref5">5</xref>], and as of December 31, 2021, more than 295,028 cases and 5378 deaths had been reported in the country [<xref ref-type="bibr" rid="scirp.118170-ref6">6</xref>].</p><p>Wastewater-based epidemiology is a surveillance tool for the collection, extraction, and detection of infectious agents present in a population using wastewater as a sample source [<xref ref-type="bibr" rid="scirp.118170-ref7">7</xref>]. The technique has been employed for the detection of illicit drugs [<xref ref-type="bibr" rid="scirp.118170-ref8">8</xref>], antimicrobial resistance (AMR) [<xref ref-type="bibr" rid="scirp.118170-ref9">9</xref>], viruses such as poliovirus [<xref ref-type="bibr" rid="scirp.118170-ref10">10</xref>], hepatitis A virus, norovirus outbreaks [<xref ref-type="bibr" rid="scirp.118170-ref11">11</xref>] and SARS-CoV-2 [<xref ref-type="bibr" rid="scirp.118170-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref13">13</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref14">14</xref>]. COVID-19-infected individuals usually shed the virus in the nasal, oropharyngeal, and gastrointestinal tract [<xref ref-type="bibr" rid="scirp.118170-ref15">15</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref16">16</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref17">17</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref18">18</xref>]. The reverse transcription-quantitative polymerase chain reaction (RT-qPCR) has shown that viral RNA shedding continues after symptoms have subsided, and that viruses shed into the wastewater environment can be detected for an extended period [<xref ref-type="bibr" rid="scirp.118170-ref19">19</xref>].</p><p>The major benefits of the wastewater-based epidemiology approach are that it is non-invasive, unbiased, in-expensive, and can serve as an early-warning system for SARS-CoV-2 emergence due to its inherent inclusiveness, and the ability to capture both asymptomatic and symptomatic cases [<xref ref-type="bibr" rid="scirp.118170-ref14">14</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref20">20</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref21">21</xref>]. Additionally, wastewater represents a pooled sample from a population for its ability to blend the viruses coming from different sources such as hand washing, sputum, feaces, and fomites contributed by both symptomatic and asymptomatic cases [<xref ref-type="bibr" rid="scirp.118170-ref22">22</xref>].</p><p>The SARS-CoV-2 nucleic RNA material has previously been detected in wastewater in various countries, globally [<xref ref-type="bibr" rid="scirp.118170-ref23">23</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref24">24</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref25">25</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref26">26</xref>]. Case in point, countries such as Australia, New Zealand, Brazil, the Netherlands, and the United States have adopted wastewater surveillance as a routine COVID-19 monitoring method [<xref ref-type="bibr" rid="scirp.118170-ref27">27</xref>]. Despite its convenience and the various advantages that come with it, data on SARS-CoV-2 from wastewater surveillance in Kenya is lacking.</p><p>In an attempt to bridge the gap, the present study aimed to describe the genetic diversity of SARS-CoV-2 variants that circulated in Nairobi County, Kenya between April 2021 and August 2021 through real-time RT-qPCR screening of the virus nucleic RNA in wastewater, coupled with nucleotide sequencing of the complete Spike protein-encoding gene. The SARS-CoV-2 spike protein (S) is the major surface virus antigenic protein, responsible for host Angiotensin-converting enzyme 2 (ACE2) receptor recognition and attachment [<xref ref-type="bibr" rid="scirp.118170-ref28">28</xref>]. Furthermore, the spike protein is a major determinant of SARS-CoV-2 variant designation [<xref ref-type="bibr" rid="scirp.118170-ref29">29</xref>] which is caused by genetic mutations in the gene that codes for this protein [<xref ref-type="bibr" rid="scirp.118170-ref30">30</xref>].</p></sec><sec id="s2"><title>2. Materials and Methods</title><sec id="s2_1"><title>2.1. Study Sites and Sampling</title><p>The study utilized grab samples (n = 40) that were previously collected as part of routine poliovirus environment surveillance (ES) by the Centre for virus research of Kenya Medical Research Institute (KEMRI). The sampling period was between April 2021 and August 2021. The samples were collected from eight sampling sites, namely, Kibera, Dandora treatment plant, Mukuru Kware river, Eastleigh A, Eastleigh B, Majengo river, Kaverera bridge, and Mathare within the Nairobi County, as previously mapped and validated by WHO (<xref ref-type="fig" rid="fig1">Figure 1</xref>).</p></sec><sec id="s2_2"><title>2.2. Viral RNA Extraction and Real-Time RT-qPCR Screening</title><p>Prior to viral RNA extraction, the wastewater samples were concentrated following the two-phase separation method of the World Health Organization [<xref ref-type="bibr" rid="scirp.118170-ref32">32</xref>] protocol for environmental surveillance of Poliovirus. Briefly, 500 ml wastewater was centrifuged, at 1500 g for 20 minutes. The pellet was stored at 4˚C for later use and the pH of the supernatant was adjusted to neutral (pH 7 - 7.5) using NaOH and HCl. The supernatant was mixed with defined amounts of dextran and polyethylene glycol (PEG). The Mixture was kept in constant agitation for 1 hour at room temperature using a magnetic stir plate then poured into the separating funnels which were left to stand overnight at 4˚C. The concentrate was harvested by collecting the lower layer and the interphase slowly drop-wise, and this concentrate was mixed with the pellet from the initial centrifugation. The viral RNA was extracted using the RADI PREP swab and stool DNA/RNA kit following the manufacturer’s instructions (KH Medical Co. Ltd. Republic of Korea). The RADI COVID-19 Detection kit was used to screen the extracted RNA for SARS-CoV-2 using a real-time RT-qPCR assay targeting the virus S and RdRp genes as directed by the manufacturer (KH Medical Co., ltd. Korea).</p></sec><sec id="s2_3"><title>2.3. Complementary DNA (cDNA) Synthesis and Conventional RT-PCR</title><p>The cDNA synthesis was performed using the Accuris qMax™ First Strand cDNA Synthesis Kit (USA), based on the manufacturer's instructions. PCR amplification of the SARS-CoV-2 surface spike protein-encoding gene was performed using a set of five pairs of primers described elsewhere [<xref ref-type="bibr" rid="scirp.118170-ref33">33</xref>]. The PCR master mix was prepared using the FIREPol<sup>&#174;</sup> Master Mix, based on the manufacturer’s specifications (Solis Biodyne, Tartu, Estonia).</p><p>The PCR amplicons generated were electrophoresed on a 1% agarose gel (Sigma-Aldrich Co, USA) stained in 2 &#181;g/ml ethidium bromide (Sigma-Aldrich Co, USA) solution and viewed using the E-box gel imaging system (Vilber Lourmat, France). The amplicons were next purified using Exonuclease I/Shrimp Alkaline Phosphatase (ExoSap-IT) enzyme (Affymetrix, USA), based on the manufacturer’s instructions. Subsequently, the purified products were sequenced on both strands on an automated 3500&#215;L Genetic Analyzer (Applied Biosystems, USA). Cycle sequencing was done using the Big Dye Terminator Cycle sequencing kit v3.1 (Applied Biosystems, USA), based on the manufacturer’s instructions. The SARS-CoV-2 Spike protein-encoding gene sequences reported in this work are available in GenBank under the accession numbers: ON063425 - ON063433.</p></sec><sec id="s2_4"><title>2.4. Sequence Analysis</title><p>The generated DNA nucleotide sequence fragments were assessed for quality and assembled into contig using finchTV v1.4.1 [<xref ref-type="bibr" rid="scirp.118170-ref34">34</xref>] and DNA Baser v4 [<xref ref-type="bibr" rid="scirp.118170-ref35">35</xref>] software respectively. Mutation calling and genetic lineage grouping were performed using Phylogenetic Assignment of Named Global Outbreak Lineages (PANGOLIN) [<xref ref-type="bibr" rid="scirp.118170-ref36">36</xref>] and NextStrain [<xref ref-type="bibr" rid="scirp.118170-ref37">37</xref>] online tools. The sequences were compared to NC_ 045512.2-Wuhan-Hu-1 as well as those obtained from other regions during the study period, which were drawn from the Global Initiative for Sharing All Influenza Data (GISAID) [<xref ref-type="bibr" rid="scirp.118170-ref38">38</xref>]. Multiple sequence alignment was performed using Muscle version v3.8 software [<xref ref-type="bibr" rid="scirp.118170-ref39">39</xref>]. A phylogenetic tree was generated using MrBayes software v3.2 [<xref ref-type="bibr" rid="scirp.118170-ref40">40</xref>] under the best fit TN93 + G substitution model as predicted by the jModelTest software [<xref ref-type="bibr" rid="scirp.118170-ref41">41</xref>]. The tree was visualized and annotated using Fig Tree v1.4.0 software [<xref ref-type="bibr" rid="scirp.118170-ref42">42</xref>].</p></sec></sec><sec id="s3"><title>3. Results</title><p>Overall, 20 (50%) of the extracted grab samples tested positive for SARS-CoV-2 by real-time RT-PCR, with Ct values ranging from 27.1 to 40 for both the target S and RdRp virus genes. The frequency of SARS-CoV-2 detections among the study sites is summarized in <xref ref-type="fig" rid="fig2">Figure 2</xref>.</p><p>Nine (45%) of the positives were successfully amplified and sequenced using conventional RT-PCR, and yielded usable sequences. Genetic analysis revealed that the majority (n = 7) of the sequences belonged to the SARS-CoV-2 Delta (B.1.617.2) lineage, while a minority (n = 2) belonged to the Alpha (B.1.1.7) and a recombinant (Alpha-Delta) lineages (<xref ref-type="table" rid="table1">Table 1</xref>). All the Kenya viruses exhibited various amino acid substitutions in the Spike protein relative to the prototype NC_045512.2-Wuhan-Hu-1 strain as summarized in <xref ref-type="table" rid="table1">Table 1</xref>.</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> SARS-CoV-2 lineage classification and amino acid variations in the spike protein of the Kenyan viruses relative to the prototype NC_045512.2-Wuhan-Hu-1 strain</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Sample ID</th><th align="center" valign="middle" >Date of collection</th><th align="center" valign="middle" >WHO Lineage</th><th align="center" valign="middle" >Spike protein mutation</th></tr></thead><tr><td align="center" valign="middle" >KENYA_104_19042021</td><td align="center" valign="middle" >6/4/21</td><td align="center" valign="middle" >Delta</td><td align="center" valign="middle" >T19R, P681R, D614G, L452R, F157del, R158del, D228H, E156G, G142D, T478K</td></tr><tr><td align="center" valign="middle" >KENYA_125_19052021</td><td align="center" valign="middle" >19/5/21</td><td align="center" valign="middle" >Delta</td><td align="center" valign="middle" >T19R, P681R, D614G, D950N, Q613H, T478K, L452R, F157del, R158del, E156G, G142D</td></tr><tr><td align="center" valign="middle" >KENYA_138_10062021</td><td align="center" valign="middle" >10/6/21</td><td align="center" valign="middle" >Delta</td><td align="center" valign="middle" >T19R, P681R, D614G, D950N, T478K, L452R, F157del, R158del, E156G, T95I, G142D</td></tr><tr><td align="center" valign="middle" >KENYA_139_10062021</td><td align="center" valign="middle" >10/6/21</td><td align="center" valign="middle" >Delta</td><td align="center" valign="middle" >P681R, D614G, L452R, F157del, R158del, E156G, T478K, D142D, D950N</td></tr><tr><td align="center" valign="middle" >KENYA_141_10062021</td><td align="center" valign="middle" >10/6/21</td><td align="center" valign="middle" >Delta</td><td align="center" valign="middle" >T19R, P681R, D614G, D950N, T478K, L452R, F157del, R158del, E156G, S112L, G142D</td></tr><tr><td align="center" valign="middle" >KENYA_143_10062021</td><td align="center" valign="middle" >10/6/21</td><td align="center" valign="middle" >(Alpha,V1)</td><td align="center" valign="middle" >A570D.S982A, P681H, D614G, T716I, Y144del, N501Y, D1118H, V70del, H69del</td></tr><tr><td align="center" valign="middle" >KENYA_164_15072021</td><td align="center" valign="middle" >15/7/21</td><td align="center" valign="middle" >recombinant (Delta and Alpha)</td><td align="center" valign="middle" >P681R, D614G, D950N, T478K, L452R, A520S</td></tr><tr><td align="center" valign="middle" >KENYA_203_12082021</td><td align="center" valign="middle" >12/8/21</td><td align="center" valign="middle" >Delta</td><td align="center" valign="middle" >T19R, P681R, D614G, L452R, F157del, R158del, D228H, E156G, D142D, T478K, D950N</td></tr><tr><td align="center" valign="middle" >KENYA_205_12082021</td><td align="center" valign="middle" >12/8/21</td><td align="center" valign="middle" >Delta</td><td align="center" valign="middle" >T19R, V90I, P681R, D614G, D950N, T478K, L452R, F157del, R158del, E156G, T95I, G142D</td></tr></tbody></table></table-wrap><p>These changes were however not unique to the Kenyan viruses as they were common among sequences of the global strains included in the analysis. Phylogenetic comparisons revealed general interspersion of the Kenyan SARS-CoV-2 Delta lineage viruses among the foreign reference strains included in the analysis (<xref ref-type="fig" rid="fig2">Figure 2</xref>). The Kenyan virus KENYA 205 12082021 clustered closely with the Indian and USA strains, KENYA 138 10062021 with Botswana and Australian strains, KENYA 139 10062021 with a strain from the United States of America, KENYA 203 12082021 and KENYA 104 19042021 with strains from Denmark and Cameroon, KENYA 125 19052021 with strains from Vietnam and India, KENYA 141 10062021 with strains from Tunisia &amp; Congo, and KENYA 164 15072021 with strains from southern Sudan and Japan (<xref ref-type="fig" rid="fig3">Figure 3</xref>).</p></sec><sec id="s4"><title>4. Discussion</title><p>Wastewater surveillance for SARS-CoV-2 offers an alternative approach for epidemiological tracking of the extend of virus spread in a community [<xref ref-type="bibr" rid="scirp.118170-ref43">43</xref>]. SARS-CoV-2 nucleic RNA has previously been detected in wastewaters [<xref ref-type="bibr" rid="scirp.118170-ref43">43</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref44">44</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref45">45</xref>]. This approach is mostly utilized in situations of low virus prevalence or during early periods of a pandemic [<xref ref-type="bibr" rid="scirp.118170-ref43">43</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref46">46</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref47">47</xref>]. Due to its low cost in comparison to clinical epidemiology, which requires individual patients to be swabbed, the approach may be used in low resource settings (where it will quickly indicate circulating strains in the general population) and may also be used routinely once the pandemic has established in the population [<xref ref-type="bibr" rid="scirp.118170-ref46">46</xref>]. The present study used real-time RT-qPCR assay coupled with targeted sequencing to detect and characterize the diversity of SARS-CoV-2 in Nairobi County, Kenya, between April 2021 and August 2021. Overall, nine SARS-CoV-2 variants were identified. The majority (78%, n = 7) of the variants belonged to the Delta SARS-CoV-2 lineage while a minority (22%) belonged to the Alpha (B.1.1.7) and Alpha-Delta recombinant lineages. This result is consistent with previous findings in Kenya using clinical epidemiologic approach [<xref ref-type="bibr" rid="scirp.118170-ref48">48</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref49">49</xref>] as well as related studies elsewhere, where increased cases of COVID-19 caused by the Delta SARS-CoV-2</p><p>variants were reported during the same period [<xref ref-type="bibr" rid="scirp.118170-ref50">50</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref51">51</xref>]. The increased global circulation of the Alpha (B.1.1.7) SARS-CoV-2 lineage was reported beginning in 2021, before being replaced by the Delta variant [<xref ref-type="bibr" rid="scirp.118170-ref51">51</xref>].</p><p>Notably, only 45% (9/20) of the SARS-CoV-2 viral RNA positive samples were detected by real-time RT-qPCR subsequently amplified by conventional RT-PCR prior to sequencing. The failure of 55% of the samples to amplify by conventional RT-PCR may be attributed to low copy numbers of template SARS-CoV-2 RNA (high Ct value samples) in the samples. Real-time PCR has statistically higher sensitivity compared to conventional RT-PCR [<xref ref-type="bibr" rid="scirp.118170-ref52">52</xref>] [<xref ref-type="bibr" rid="scirp.118170-ref53">53</xref>]. Cumulatively, the Eastleigh (Eastleigh A/B) and Kibera sampling sites had the highest detection levels, accounting for nearly 60% of the total extractions. This could be attributed to the high population density in these two slum areas, as well as the proximity of the sampling sites to very fresh and raw stool, implying that the viruses had not been exposed to the environment for too long since they were shed in the stool. The observed differences in SARS-CoV-2 detection levels by real-time RT-qPCR could be attributed to varying degrees of virus damage in the wastewaters. Findings from a previous study have shown that the period for the survival of SARS-CoV-2 RNA in wastewater is hinged on various factors including the presence of other microorganisms and physicochemical properties such as pH, solids, and disinfectant compounds, known to destroy viruses and their nucleic acids, rendering viral detection cumbersome [<xref ref-type="bibr" rid="scirp.118170-ref54">54</xref>]. Furthermore, the higher SARS-CoV-2 concentrations in in sewage of the two sites could be attributed to a failure to comply with government COVID-19 public health countermeasures such as masking and social distancing, resulting in increased community transmissions and concomitant increased virus shedding in stool.</p><p>Phylogenetic analysis of the SARS-CoV-2 Delta (B.1.617.2) lineage strains based on the complete surface glycoprotein spike gene sequence data revealed interspersion of the Kenyan viruses among the global strains included in the analysis. This result suggests seeding of the Delta SARS-CoV-2 variant strains into Kenya from different source countries.</p></sec><sec id="s5"><title>5. Conclusion</title><p>This study had some pitfalls. The limited number of wastewater samples analyzed may not provide a true representation of the frequency of SARS-CoV-2 variants that circulated in Nairobi County, Kenya, during the studied period, thus introducing bias in the reported data. Secondly, the targeted sequencing of solely the virus Spike gene is limiting as evolutionary patterns exhibited by the other genes comprising the SARS-CoV-2 genome are missed. Despite the limitations, we have demonstrated that SARS-CoV-2 variants belonging to the Alpha (B.1.1.7) and Delta (B.1.617.2) lineages circulated in Nairobi County, Kenya between April 2021 and August 2021, with the latter predominating. This is the first study to describe the diversity of SARS-CoV-2 variants circulating in Kenya, through wastewater analysis.</p></sec><sec id="s6"><title>Acknowledgments</title><p>We thank the Kenya Medical Research Institute (KEMRI), Centre for Virus Research (CVR), for unwavering support during the implementation of this study. We also thank the Pan African University Institute for Basic Sciences, Technology, and Innovation (PAUSTI) for finding the project.</p></sec><sec id="s7"><title>Ethical Approval</title><p>The KEMRI Scientific and Ethics Review Unit (SERU) approved this study under protocol approval number SERU4323.</p></sec><sec id="s8"><title>Authors’ Contributions</title><p>Conceptualization: Bulimo Dimbuson Wallace, Nzunza Rosemary, Wamunyokoli Fred.</p><p>Data curation: Sichamba Patson, Opanda Silvanos, Bulimo Dimbuson Wallace.</p><p>Formal analysis: Sichamba Patson, Opanda Silvanos, Symekher Samwel, Bulimo Dimbuson Wallace.</p><p>Investigation: Sichamba Patson.</p><p>Methodology: Sichamba Patson, Nzunza Rosemary, Symekher Samwel, Majanja Janet, Wadegu Meshack, Wanguche Esther, Mwangi Benlick, Ombija Stephen, Borus Peter, Evans Komen.</p><p>Supervision: Bulimo Dimbuson Wallace, Wamunyokoli Fred, Borus Peter, Nzunza Rosemary.</p><p>Writing—original draft: Sichamba Patson, Nzunza Rosemary, Symekher Samwel, Majanja Janet, Wadegu Meshack, Wanguche Esther, Ombija Stephen.</p><p>Writing—review &amp; editing: Bulimo Dimbuson Wallace, Opanda Silvanos, Samoel Ashimosi Khamadi, Wamunyokoli Fred.</p></sec><sec id="s9"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s10"><title>Cite this paper</title><p>Sichamba, P., Wamunyokoli, F., Borus, P., Nzunza, R., Silvanos, O., Symekher, S., Khamadi, S.A., Majanja, J., Wadegu, M., Chitechi, E., Mwangi, B., Komen, E., Ombija, S. and Bulimo, W.D. 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