Signals of significantly increased vaccine breakthrough, decreased hospitalization rates, and less severe disease in patients with COVID-19 caused by the Omicron variant of SARS-CoV-2 in Houston, Texas

42 Genetic variants of SARS-CoV-2 continue to dramatically alter the landscape of the 43 COVID-19 pandemic. The recently described variant of concern designated Omicron 44 (B.1.1.529) has rapidly spread worldwide and is now responsible for the majority of 45 COVID-19 cases in many countries. Because Omicron was recognized very recently, 46 many knowledge gaps exist about its epidemiology, clinical severity, and disease 47 course. A genome sequencing study of SARS-CoV-2 in the Houston Methodist 48 healthcare system identified 4,468 symptomatic patients with infections caused by 49 Omicron from late November 2021 through January 5, 2022. Omicron very rapidly 50 increased in only three weeks to cause 90% of all new COVID-19 cases, and at the end 51 of the study period caused 98% of new cases. Compared to patients infected with either 52 Alpha or Delta variants in our healthcare system, Omicron patients were significantly 53 younger, had significantly increased vaccine breakthrough rates, and were significantly 54 less likely to be hospitalized. Omicron patients required less intense respiratory support 55 and had a shorter length of hospital stay, consistent with on average decreased disease 56 severity. Two patients with Omicron “stealth” sublineage BA.2 also were identified. The 57 data document the unusually rapid spread and increased occurrence of COVID-19 58 caused by the Omicron variant in metropolitan Houston, and address the lack of 59 information about disease character among US patients. 60 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 4 [Introduction] 61 62 63 Over the last 14 months, the Alpha and Delta variants of concern (VOCs) of SARS-64 CoV-2 have caused two distinct COVID-19 disease surges in the United States, 65 Southeast Asia, Europe, and elsewhere (https://www.cdc.gov/coronavirus/2019-66 ncov/cases-updates/variant-surveillance/variant-info.html, last accessed December 30, 67 2021; https://www.gov.uk/government/collections/new-sars-cov-2-variant, last accessed 68 December 30, 2021), and remodeled the landscape of human behavior and many 69 societies. Delta replaced the Alpha variant as the cause of virtually all COVID-19 in 70 many countries (https://www.who.int/publications/m/item/weekly-epidemiological-71 update-on-covid-19---13-july-2021, last accessed August 18, 2021; 72 https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditions73 anddiseases/bulletins/coronaviruscovid19infectionsurveypilot/9july2021, last accessed 74 August 18, 2021). 75 At the start of the pandemic almost two years ago, the Houston Methodist 76 healthcare system instituted a comprehensive and integrated population genomics 77 project designed to sequence all SARS-CoV-2 samples causing COVID-19 in patients 78 cared for at our facilities, which include eight hospitals located throughout the 79 metroplex. The project was implemented when the initial Houston Methodist COVID-19 80 case was diagnosed at the end of February 2020, and has continued unabated1-7. This 81 project was facilitated by the existence of a single large diagnostic laboratory that 82 serves the entire system and is seamlessly integrated with a research institute with 83 extensive genomics expertise and capacity. A key goal was to comprehensively map 84 the population genomics, trajectory, and other features of the pandemic in metropolitan 85 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 5 Houston with a population size of approximately 7.2 million. Houston is the fourth 86 largest city in the United States, the most ethnically diverse metropolitan area in the 87 country, and is a major port of entry. To date, SARS-CoV-2 genomes have been 88 sequenced from greater than 70,000 patient samples. Many features of four distinct 89 SARS-CoV-2 waves in Houston have been described2-6. 90 The successes of rapid SARS-CoV-2 vaccine development and documented 91 efficacy, coupled with the significant downturn of the disease wave caused by Delta in 92 Houston and elsewhere in fall, 20216, suggested that the pandemic was abating. 93 However, the identification of a new VOC designated B.1.1.529 and known as Omicron 94 that has spread rapidly in South Africa and the UK has tempered this optimism8-10. 95 Inasmuch as Omicron was recognized very recently, and much is not known about its 96 epidemiology and clinical characteristics and course, we used our integrated 97 infrastructure in an effort to address the lack of information available for United States 98 Omicron patients. Genome sequencing identified 4,468 COVID-19 patients with 99 symptomatic disease caused by Omicron in the Houston Methodist healthcare system 100 beginning in late November 2021 and ending January 5, 2022. In three weeks Omicron 101 spread throughout the Houston metropolitan region to become the cause of 90% of new 102 COVID-19 cases, and at the end of the study period caused 98% of all new cases. 103 Compared to patients infected with either Alpha or Delta variants and cared for in our 104 system, significantly fewer Omicron patients were hospitalized, and those who were 105 hospitalized required significantly less intense respiratory support and had a shorter 106 length of stay. Our findings are consistent with decreased disease severity among 107 Houston Methodist Omicron patients. Many factors undoubtedly have contributed, 108 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 6 including but not limited to increased vaccination uptake, population immunity, and 109 patient demographics such as younger age. The extent to which our findings translate 110 to other cities and other patient populations, including children, is unknown. These data 111 expand on our initial Omicron work7 and address the lack of information about disease 112 character among US patients with COVID-19 caused by this VOC. 113 114

115 116 Patient Specimens 117 118 Specimens were obtained from patients registered at Houston Methodist facilities (e.g., 119 hospitals and urgent care centers), and institutions in the Houston metropolitan region 120 that use our laboratory services. The great majority of individuals had signs or 121 symptoms consistent with COVID-19 disease. For analyses focusing on patients with 122 COVID-19 caused by the Omicron variant, samples obtained from November 27, 2021 123 through January 5, 2022 were used. This time frame was chosen because it represents 124 the period during which an Omicron variant was first identified in our healthcare system 125 and the last date of specimen collection used to generate genome sequence data for 126 this manuscript. Note that the genome data were generated for two distinct sampling 127 periods. The first period included November 27, 2021 through December 23, 2021 and 128 the second period included samples obtained between December 30, 2021 through 129 January 5, 2022. This discontinuous sampling strategy was used in an effort to obtain 130 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 7 the most up-to-date data available for inclusion in this study. Because of the substantial 131 number of positive specimens obtained daily in the December 24, 2021 to December 132 29, 2021 period (sometimes exceeding 1,500) it wasn’t possible to sequence most of 133 the samples collected during this period for inclusion in the study. 134 For analyses comparing features of patients infected with the Omicron VOC and 135 Alpha and Delta VOCs, all patients documented to be infected with these variants in the 136 Houston Methodist system were studied. The study included 40,991 unique patients 137 identified in this time frame for whom we had SARS-CoV-2 genome sequences. The 138 work was approved by the Houston Methodist Research Institute Institutional Review 139 Board (IRB1010-0199). 140 141 SARS-CoV-2 Molecular Diagnostic Testing 142 143 Specimens obtained from symptomatic patients with a suspicion for COVID-19 disease 144 were tested in the Molecular Diagnostics Laboratory at Houston Methodist Hospital 145 using assays granted Emergency Use Authorization (EUA) from the FDA 146 (https://www.fda.gov/medical-devices/emergency-situations-medical-devices/faqs-147 diagnostic-testing-sars-cov-2#offeringtests, last accessed June 7, 2021). Multiple 148 molecular testing platforms were used, including the COVID-19 test or RP2.1 test with 149 BioFire Film Array instruments, the Xpert Xpress SARS-CoV-2 test using Cepheid 150 GeneXpert Infinity or Cepheid GeneXpert Xpress IV instruments, the Cobas SARS-151 CoV-2 & Influenza A/B Assay using the Roche Liat system, the SARS-CoV-2 Assay 152 using the Hologic Panther instrument, the Aptima SARS-CoV-2 Assay using the Hologic 153 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 8 Panther Fusion system, the Cobas SARS-CoV-2 test using the Roche 6800 system, 154 and the SARS-CoV-2 assay using Abbott Alinity m instruments. Virtually all tests were 155 performed on material obtained from nasopharyngeal swabs immersed in universal 156 transport media (UTM); oropharyngeal or nasal swabs, bronchoalveolar lavage fluid, or 157 sputum treated with dithiothreitol (DTT) were sometimes used. Standardized specimen 158 collection methods were used (https://vimeo.com/396996468/2228335d56, last 159 accessed June 7, 2021). 160 161 SARS-CoV-2 Genome Sequencing, Genome Analysis, and Identification of 162 Variants 163 164 We sequenced the SARS-CoV-2 genome of >90% of all positive cases in the Houston 165 Methodist healthcare system during the two sampling periods studied. Libraries for 166 whole SARS-CoV-2 genome sequencing were prepared according to version 4 167 (https://community.artic.network/t/sars-cov-2-version-4-scheme-release/312, last 168 accessed August 19, 2021) of the ARTIC nCoV-2019 sequencing protocol. The semi-169 automated workflow used has been described previously2-6. Sequence reads were 170 generated with an Illumina NovaSeq 6000 instrument. 171 Viral genomes were assembled with the BV-BRC SARS-Cov2 assembly service 172 (https://www.bv-brc.org/app/ComprehensiveSARS2Analysis, last accessed June 7, 173 2021, requires registration). The pipeline currently uses seqtk version 1.3-r117 for 174 sequence trimming (https://github.com/lh3/seqtk.git, last accessed December 30, 2021) 175 and minimap version 2.17 for aligning reads against the Wuhan-Hu-1 (NC_045512.2) 176 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 9

genome. Samtools version 1.11 was used for sequence and file manipulation, 177 where maximum depth and minimum depth parameters in mpileup were set to 8,000 178 and 3, respectively. iVar version 1.3.1 was used for primer trimming and variant calling. 179 Genetic lineages, VOCs, and variants of interest (VOIs) were identified based on 180 genome sequence data and designated by Pangolin v. 3.1.17 with pangoLEARN 181 module 2021-12-06 (https://cov-lineages.org/resources/pangolin.html, last accessed 182 December 12, 2021). Genome data used in this study have been deposited to 183 GISAID www.gisaid.org. 184 185 S-Gene Target-Failure Assay 186 187 An S-gene target-failure (SGTF) assay (TaqPath COVID-19 Combo Kit Thermo Fisher, 188 Inc.), was used as a surrogate marker for the Omicron VOC for some specimens 189 collected between December 18, 2021 and January 5, 2022. From November 1, 2021 190 onward, only Delta and Omicron were documented to be circulating in metropolitan 191 Houston, based on whole-genome sequence data. Patient samples were first tested in 192 the clinical Molecular Diagnostics Laboratory using a RT-PCR assay with an 193 Emergency Use Authorization as described above. The SARS-CoV-2 positive samples 194 were then tested with the SGTF assay according to the manufacturer’s instructions to 195 infer an Omicron or not-Omicron lineage. That is, the SGTF assay was only performed 196 on samples known to be positive for SARS-CoV-2. Samples yielding amplification of the 197 S-gene were classified as a Delta variant. The SGTF data were validated based on 198 comparing the results with our extensive genome sequence data. 199 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 10 200 201 Patient Metadata and Geospatial Analysis 202 203 Patient metadata were acquired from the electronic medical record by standard 204 informatics methods. Figures showing geospatial distribution of spread for Omicron 205 were generated with Tableau version 2021.2.7 (Tableau Software, LLC, Seattle, WA) 206 using patient home address zip codes. A vaccination breakthrough case was defined as 207 a PCR-positive sample from a patient obtained greater than 14 days after full 208 vaccination (e.g., both doses of the Pfizer or Moderna mRNA vaccines) was completed. 209 A booster vaccination breakthrough case was defined as a PCR-positive sample from a 210 patient obtained greater than 14 days after receiving a third vaccine dose. For some 211 cases, manual chart review was conducted to resolve discrepancies or clarify 212 ambiguities. 213 214 215

216 217 Omicron Epidemiologic Wave 218 219 The first Houston Methodist patient infected with an Omicron variant was identified at 220 the end of November 2021, a time when the Delta VOC was responsible for all COVID-221 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 11 19 cases in metropolitan Houston6. During this period, the metropolitan area was 222 experiencing a steady decrease in total number of new COVID-19 cases (Figure 1, 223 Figure 2). 224 Omicron increased in frequency unusually rapidly over a three-week period in 225 December (Figure 1, Figure 2). By December 23, the genome sequence data showed 226 that Omicron accounted for >90% of all new COVID-19 cases in our healthcare system 227 (Figure 2). The estimated case doubling time during this three-week period was 228 approximately 1.8 days (Figure 2), which means that Omicron increased in relative 229 frequency approximately three times faster than Delta had increased in our area6, an 230 unprecedented trajectory for SARS-COV-2 infections. By January 5, 2022, the Omicron 231 variant caused 98% of all new COVID-19 cases diagnosed in our healthcare system 232 (Figure 2). This represents the fifth wave of COVID-19 cases in metropolitan Houston 233 (Figure 1). 234 Consistent with extensive infections caused by Omicron in southern Africa and 235 elsewhere (https://www.cdc.gov/coronavirus/2019-ncov/variants/variant-236 classifications.html, last accessed December 28, 2021; 237 https://www.gov.uk/government/collections/new-sars-cov-2-variant, last accessed 238 December 28, 2021), several patients had very recent travel histories to countries with a 239 high prevalence of this VOC, suggesting acquisition of virus by some cases from abroad 240 and importation into Houston. However, the vast majority of Omicron patients had no 241 documented travel outside the US and undoubtedly acquired the infection domestically, 242 either in Houston or elsewhere. 243 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 12 To understand the geospatial distribution of Omicron in metropolitan Houston, 244 patient metadata were acquired from the electronic medical record by standard 245 informatics methods, and home address zip codes were used to visualize virus spread 246 (Figure 2). The 4,468 Houston Methodist patients infected with Omicron during this 247 period were distributed widely throughout metropolitan Houston, with 259 different zip 248 codes represented (Figure 2). The widespread distribution of Omicron in the Houston 249 metroplex in an extremely short period of time reflects the ability of this variant to spread 250 unusually rapidly and effectively between individuals, and cause symptomatic disease. 251 252 Comparison of Omicron, Alpha, and Delta COVID-19 Cases 253 254 There is a considerable lack of detailed information about patients with COVID-19 255 caused by the Omicron VOC, and data are especially lacking for US patients. We 256 compared available metadata for all Houston Methodist patients infected with Omicron, 257 Alpha, and Delta VOCs (Table 1, Table 2). The populations differed significantly in 258 many characteristics, including median age, hospital admission rates, maximum 259 respiratory support, rate of vaccine breakthrough, and median length of stay (Table 1, 260 Table 2). 261 Patients infected with Omicron were significantly younger than Alpha and Delta 262 patients (Table 1, Table 2). Importantly, Omicron patients were hospitalized significantly 263 less frequently than patients infected with either the Alpha or Delta variants, and had a 264 significantly shorter median hospital length of stay (Table 1, Table 2). 265 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 13 We next analyzed Omicron vaccine breakthrough cases (Table 1, Table 2). We 266 found 2,497 of the 4,468 total Omicron patients (55.9%) for whom we have whole 267 genome sequence data met the CDC definition of vaccine breakthrough cases (Table 1, 268 Table 2). There was no simple relationship between the time elapsed since 269 administration of the second vaccination dose and the date of vaccination breakthrough. 270 These 2,497 patients received either two doses of the Pfizer-BioNTech BNT162b2 (n = 271 1828, 73%) or Moderna mRNA-1273 (n = 553, 22%), or one dose of J&J/Janssen JNJ-272 78436735 (n = 115, 5%) vaccine; vaccine type was not specified for one individual. This 273 distribution reflects the majority use of BNT162b2 vaccination doses in our health 274 system. Compared to either Alpha or Delta patients, a significantly greater percentage 275 of patients with breakthrough cases was caused by the Omicron VOC (55.9% compared 276 to 3.2% and 24.3% for Alpha and Delta VOCs, respectively) (Table 1, Table 2). We 277 next analyzed individuals with breakthrough cases after receiving a third (booster) dose 278 of either the Pfizer-BioNTech BNT162b2 or Moderna mRNA-1273 vaccine. We found 279 that 711 (15.9%) of the 4,468 Omicron patients met this criteria. Consistent with 280 Omicron causing a significantly increased number of vaccine breakthrough cases, many 281 studies have reported that this variant has reduced sensitivity to antibody neutralization 282 in vitro, likely in large part due to the extensive number of amino acid and other 283 structural changes occurring in Omicron spike protein11-34. 284 285 Spike-Gene Target-Failure Assay 286 287 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 14 To estimate Omicron variant frequency in patient samples not yet sequenced, we 288 performed the TaqPath COVID-19 Combo Kit assay (ThermoFisher) on 1,216 samples 289 collected from symptomatic patients between December 18, 2021 and January 5, 2022 290 In total, 1,093 (90%) of patient samples yielded an RT-PCR result with S-gene target-291 failure indicative of the Omicron variant. These data are consistent with the increasing 292 frequency of new cases of COVID-19 caused by Omicron in our population (Figure 2). 293 294 Discovery of Omicron “Stealth” Sublineage BA.2 in Houston 295 296 The Omicron sublineage BA.2 was first identified in November 2021 in Australia in a 297 patient who had traveled to South Africa (https://github.com/cov-lineages/pango-298 designation/issues/359; last accessed December 30, 2021). This sublineage does not 299 have the full set of polymorphisms characteristic of BA.1 (B.1.1.529) and also has 300 additional mutations unique to it (https://github.com/cov-lineages/pango-301 designation/issues/361; last accessed December 30, 2021). One important difference is 302 that sublineage BA.2 lacks the spike gene deletion in the region encoding amino acid 303 69/70 which means that it will not be detected by the SGTF assay. As a consequence, it 304 is sometimes referred to as the Omicron “stealth” variant. We inspected all full genome 305 sequences present in our large database, including specimens obtained from 306 symptomatic patients and asymptomatic individuals, and discovered only two members 307 of the BA.2 sublineage in Houston COVID-19 patients. 308 309 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 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310 311 This work was conducted to address the relative lack of information about disease 312 character among US patients with COVID-19 caused by the Omicron VOC, and to 313 compare our findings with data available for patients in the Houston Methodist system 314 who had disease caused by the Alpha and Delta VOCs. We describe information 315 relevant to the massive Omicron wave in metropolitan Houston. In three weeks 316 (December 1, 2021 through December 23, 2021), Omicron was first identified in our 317 population and rapidly increased to cause 90% of all new COVID-19 cases, with an 318 unusually fast case doubling time of 1.8 days. Analysis of samples obtained from 319 December 30, 2021 to January 5, 2022 found that at the end of the sampling period 320 Omicron caused 98% of all new COVID-19 cases in our healthcare system. 321 The study was based on genome sequence analysis of 4,468 Omicron samples 322 taken from socioeconomically, geographically, and ethnically diverse symptomatic 323 patients. Several key findings were made, including (i) the Omicron VOC rapidly 324 increased as a cause of COVID-19 and spread throughout the metroplex in an 325 unusually short period of time, far faster than any other SARS-CoV-2 variant; (ii) 326 Omicron caused significantly more vaccine breakthrough cases than the Alpha or Delta 327 VOCs; (iii) Omicron patients were significantly younger than Alpha or Delta patients; (iv) 328 significantly fewer Omicron patients required hospitalization compared to Alpha and 329 Delta patients; (v) the median length of stay for hospitalized Omicron patients was 330 significantly shorter than for Alpha and Delta patients, and consistent with this 331 observation, on average the maximum respiratory support required for Omicron patients 332 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 16 was significantly less than for Alpha or Delta patients. Our findings are largely 333 consistent with many aspects of Omicron data reported from the UK, South Africa, and 334 Canada8-10, 35-38, and are consistent with experimental animal infection data suggesting 335 that Omicron causes less severe disease in mice and hamsters39-43. This study was 336 facilitated by a comprehensive and integrated population genomics and epidemiology 337 project2-6 implemented at the end of February 2020, when the initial COVID-19 case 338 was diagnosed in the Houston Methodist healthcare system. 339 Several questions arise from our findings, namely the underlying causes for the 340 differences we observe in Omicron compared to Alpha and Delta patients. We believe 341 the data from the extensive studies examining serologic and structural differences in 342 Omicron relative to Alpha and Delta likely contribute to the increased vaccine 343 breakthrough cases observed. It is also possible that waning of immunity is a 344 contributing factor as well. We do not currently have serologic or other data that could 345 address this possibility in our patients. As noted above, ample in vitro and animal 346 infection model data have accumulated suggesting that Omicron is less virulent than 347 Delta or Alpha VOC. We speculate that the lower age of Omicron patients may be 348 attributable to a disproportionately greater likelihood of risky behaviors in the younger 349 population, for example less mask wearing and less social distancing. Regardless, 350 additional studies are required to gain more information about factors contributing to the 351 differences between Alpha, Delta, and Omicron patients that we identified in this study. 352 Because we sequence the genome of approximately 90% of SARS-CoV-2 353 causing COVID-19 in our diverse Houston Methodist patient population, and have done 354 so for almost two years, we are continuously monitoring the composition of this virus in 355 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 17 a major US metroplex. This affords us the opportunity to rapidly assess changes in 356 SARS-CoV-2 population genomic structure in the fourth largest city in the US. However, 357 our study has several limitations. Although we sequenced the genomes of SARS-CoV-2 358 causing 90% of all Houston Methodist COVID-19 cases in the study period, this sample 359 represents only approximately 5% of cases reported in the metropolitan region. Our 360 patient population will underrepresent some demographic groups, for example 361 homeless individuals and pediatric patients. The samples sequenced in this study were 362 obtained from symptomatic individuals, which means that it is possible that we failed to 363 identify Omicron subvariants or features preferentially represented in asymptomatic 364 individuals. It is likely that our study included some patients where Omicron was 365 detected on hospital admission but was incidental to the primary cause of admission. 366 The identification of two asymptomatic individuals with the Omicron “stealth” 367 sublineage BA.2 is potentially concerning and stresses the importance of using whole-368 genome sequencing to study patient samples. This sublineage lacks the spike gene 369 deletion corresponding to amino acids 69 and 70 and is not detected by some 370 commonly used assays. Sublineage BA.2 now accounts for approximately 5% of 371 COVID-19 in the UK, which means that it has the ability to successfully transmit and 372 cause disease44. It will be important to determine if this SARS-CoV-2 genotype 373 increases in frequency in metropolitan Houston as additional genome sequencing is 374 conducted on samples from our patient population. 375 In the aggregate, our data add critical new information to features of Omicron 376 genomic epidemiology and patient characteristics in the US. Further, the present study 377 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 18 highlights the importance of analyzing SARS-CoV-2 genome data integrated with 378 patient metadata and stresses the need to continue to do this in near-real time as the 379 Omicron surge continues, the virus evolves, and new variants with potentially altered 380 fitness and biomedically relevant phenotypes are generated. Analyses of this type are 381 also important in the context of vaccine formulation and long COVID, an increasing 382 health and economic problem globally. Finally, the strategy we have used in this and 383 previous studies2-6 are readily applicable to future infectious diseases problems that 384 warrant special attention. 385 386 Acknowledgments 387 388 We thank Drs. Marc Boom and Dirk Sostman for their ongoing support, and Dr. Sasha 389 M. Pejerrey for editorial contributions. The research was supported by the Houston 390 Methodist Academic Institute Infectious Diseases Fund and many generous Houston 391 philanthropists. The funders had no role in the design and conduct of the study; 392 collection, management, analysis, and interpretation of the data; preparation, review, or 393 approval of the manuscript; and decision to submit the manuscript for publication. 394 395 We declare that we have no conflict of interest. 396 397 Author Contributions 398 399 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 19 P.A.C., R.J.O., S.W.L., and J.M.M. had full access to all study data and take 400 responsibility for the integrity of the data and the accuracy of the data analysis; concept 401 and design by J.M.M., P.A.C., R.J.O., and S.W.L; data acquisition, analysis, or 402 interpretation by all authors; drafting of the manuscript by all authors; statistical analysis 403 by P.A.C.; funding obtained by J.M.M. and J.J.D.; and overall supervision by J.M.M. 404 P.A.C., R.J.O., and S.W.L. contributed equally and are co-first authors. 405 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 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January 14, 2022. 610 611 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 2 9 612 Figure 1 Epidemiologic curve showing five COVID-19 disease waves in Houston 613 Methodist patients. Number of new COVID-19 cases (y-axis) totals are shown as a +/- 614 three-day moving average. Each of the five waves is shown in a different color. The first 615 and second waves were composed of a heterogenous array of SARS-CoV-2 genotypes.616 The Alpha VOC shown in the third wave, the Delta VOC shown in the fourth, and the 617 Omicron VOC shown in the fifth wave indicate their numeric prominence in those 618 waves. The figure should not be interpreted to mean that all cases in the third, fourth, 619 and fifth waves were caused by Alpha, Delta, and Omicron VOCs, respectively. Rather, 620 they are the dominant single VOCs causing disease in Houston Methodist system 621 patients in those waves. The fifth wave shown includes data through January 5, 2022. 622 The figure was generated with Tableau version 2021.2.7 (Tableau Software, LLC, 623 Seattle, WA), and is a modified version of one presented recently6. The curve is 624 essentially superimposable on COVID-19 activity in all metropolitan Houston, Texas. 625 9 st s. r, All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 30 626 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 31 Figure 2 Increase in Omicron frequency over time and distribution in metropolitan 627 Houston. The study time frame was November 27, 2021 through January 5, 2022. A: 628 Omicron logistic growth model. The estimated case doubling time is 1.8 days. B: 629 Cumulative increase in Omicron during the study period; y-axis is the cumulative 630 number of new COVID-19 Omicron cases. At the end of the study period, Omicron 631 caused 98% of all COVID-19 cases. The plateau between December 24, 2021 and 632 December 30, 2021 exists because we did not sequence samples obtained during this 633 period due to the massive number of daily positive specimens, as described in the 634

section. C – F: Geospatial distribution of Omicron based on 635 home address zip code for each patient. C: November 27 – December 6; D: November 636 27 – December 16; E: November 27 – December 26; F: November 27 – January 5. 637 Note differences in heat map scale for each panel. Figures were generated using 638 Tableau version 2021.2.7. (Tableau Software, LLC, Seattle, WA). 639 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 32 Table 1. Summary of pertinent patient metadata for 7,617 unique patients infected 640 with Omicron or Alpha variants. 641 Omicron Variant Alpha Variant Total Statistical Analysis No. (%) with data 4468 (58.7%) 3149 (41.3%) 7617 Patient Characteristics Median Age (Years) 44.3 50.0 47.2 P<0.0001 Mann-Whitney Female 2584 (57.8%) 1617 (51.3%) 4201 (55.2%) P<0.0001 Fisher’s exact test Male 1884 (42.2%) 1532 (48.7%) 3416 (44.8%) Ethnicity Caucasian 1627 (36.4%) 1240 (39.4%) 2867 (37.6%) P<0.0001 Chi-square Hispanic or Latino 992 (22.2%) 942 (29.9%) 1934 (25.4%) Black 1376 (30.8%) 729 (23.2%) 2105 (27.6%) Asian 203 (4.5%) 122 (3.9%) 325 (4.3%) Other 29 (0.6%) 32 (1.0%) 61 (0.8%) Unavailable 241 (5.4%) 84 (2.7%) 325 (4.3%) BMI Median BMI 29.0 30.5 29.6 P<0.0001 Mann-Whitney Admission Data Admitted 884 (19.8%) 1719 (54.6%) 2603 (34.2%) P<0.0001 Fisher’s exact test Odds Ratio: 0.205 (95% CI 0.185- 0.227) Not Admitted 3584 (80.2%) 1430 (45.4%) 5014 (65.8%) Median LOS (Days) (Discharged patients only) 3.2 5.1 4.7 P<0.0001 Mann-Whitney Max Respiratory Support ECMO 1 (0.1%) 7 (0.4%) 8 (0.3%) P<0.0001 Chi-square Mechanical Ventilation 49 (5.5%) 144 (8.4%) 193 (7.4%) All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 33 Non-Invasive Ventilation 63 (7.1%) 163 (9.5%) 226 (8.7%) High Flow Oxygen 72 (8.1%) 364 (21.2%) 436 (16.7%) Low Flow Oxygen 314 (35.5%) 722 (42.0%) 1036 (39.8%) Room Air 385 (43.6%) 319 (18.6%) 704 (27.0%) Mortality Alive 4430 (99.1%) 2979 (94.6%) 7409 (97.3%) P<0.0001 Fisher’s exact test Odds Ratio: 0.150 (95% CI 0.105- 0.214) Deceased 38 (0.9%) 170 (5.4%) 208 (2.7%) Median PCR Cycle Threshold Abbott Alinity 20.8 n=1961 22.4 n=1049 n=3010 P=0.0001 Mann-Whitney Hologic Panther 22.7 n=476 24.2 n=355 n=831 P=0.0745 Mann-Whitney Vaccine Not Fully Vaccinated 1971 (44.1%) 3048 (96.8%) 5019 (65.9%) P<0.0001 Fisher’s exact test Odds Ratio: 38.232 (95% CI 31.088- 47.017) Fully Vaccinated 2497 (55.9%) 101 (3.2%) 2598 (34.1%) BMI: body mass index; CI: confidence interval; ECMO: extracorporeal membrane oxygenation; LOS: length of stay 642 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 34 Table 2. Summary of pertinent patient metadata for 20,196 unique patients 643 infected with Omicron or Delta variants. 644 Omicron Variant Delta Variant Total Statistical Analysis No. (%) with data 4468 (22.1%) 15728 (77.9%) 20196 Patient Characteristics Median Age (Years) 44.3 48.3 47.6 P<0.0001 Mann-Whitney Female 2584 (57.8%) 8123 (51.6%) 10707 (53.0%) P<0.0001 Fisher’s exact test Male 1884 (42.2%) 7605 (48.4%) 9489 (47.0%) Ethnicity Caucasian 1627 (36.4%) 6903 (43.9%) 8530 (42.2%) P<0.0001 Chi-square Hispanic or Latino 992 (22.2%) 4179 (26.6%) 5171 (25.6%) Black 1376 (30.8%) 3450 (21.9%) 4826 (23.9%) Asian 203 (4.5%) 531 (3.4%) 734 (3.6%) Other 29 (0.6%) 112 (0.7%) 141 (0.7%) Unavailable 241 (5.4%) 553 (3.5%) 794 (3.9%) BMI Median BMI 29.0 29.6 29.4 P<0.0001 Mann-Whitney Admission Data Admitted 884 (19.8%) 6779 (43.1%) 7663 (37.9%) P<0.0001 Fisher’s exact test Odds Ratio: 0.326 (95% CI 0.301- 0.353) Not Admitted 3584 (80.2%) 8949 (56.9%) 12533 (62.1%) Median LOS (Days) (Discharged patients only) 3.2 5.4 5.2 P<0.0001 Mann-Whitney Max Respiratory Support ECMO 1 (0.1%) 19 (0.3%) 20 (0.3%) P<0.0001 Chi-square Mechanical Ventilation 49 (5.5%) 727 (10.7%) 776 (10.1%) All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint 35 Non-Invasive Ventilation 63 (7.1%) 641 (9.5%) 704 (9.2%) High Flow Oxygen 72 (8.1%) 1796 (26.5%) 1868 (24.4%) Low Flow Oxygen 314 (35.5%) 2290 (33.8%) 2604 (34.0%) Room Air 385 (43.6%) 1306 (19.3%) 1691 (22.1%) Mortality Alive 4430 (99.1%) 14889 (94.7%) 19319 (95.7%) P<0.0001 Fisher’s exact test Odds Ratio: 0.152 (95% CI 0.110- 0.211) Deceased 38 (0.9%) 839 (5.3%) 877 (4.3%) Median PCR Cycle Threshold Abbott Alinity 20.8 n=1961 21.5 n=5122 n=7083 P<0.0001 Mann-Whitney Hologic Panther 22.7 n=476 22.6 n=1298 n=1774 P=0.1606 Mann-Whitney Vaccine No vaccine 1815 (40.6%) 11415 (72.6%) 13230 (65.5%) P7 days past 1st Vaccine 156 (3.5%) 494 (3.1%) 650 (3.2%) >14 days past 2nd Vaccine 1786 (40.0%) 3679 (23.4%) 5465 (27.1%) >14 days past 3rd Vaccine 711 (15.9%) 140 (0.9%) 851 (4.2%) BMI: body mass index; CI: confidence interval; ECMO: extracorporeal membrane oxygenation; LOS: length of stay 645 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprintthis version posted January 19, 2022. ; https://doi.org/10.1101/2021.12.30.21268560doi: medRxiv preprint