key: cord-0286579-rcjy5jep authors: Owuor, D. C.; Ngoi, J. M.; Nyasimi, F. M.; Murunga, N.; Nyiro, J. U.; Garten, R.; Barnes, J. R.; Chaves, S. S.; Nokes, D. J.; Agoti, C. N. title: Local patterns of spread of influenza A(H3N2) virus in coastal Kenya over a one-year period revealed through virus sequence data date: 2021-09-12 journal: nan DOI: 10.1101/2021.09.08.21263309 sha: 93cbdcf7f3429f512f8b88b42c6fd898ebc41ece doc_id: 286579 cord_uid: rcjy5jep The patterns of spread of influenza A viruses in local populations in tropical and sub-tropical regions are unclear due to sparsity of representative spatiotemporal sequence data. We sequenced and analyzed 58 influenza A(H3N2) virus genomes sampled between December 2015 and December 2016 from nine health facilities within the Kilifi Health and Demographic Surveillance System (KHDSS), a predominantly rural region, covering approximately 891 km2 along the Kenyan coastline. The genomes were compared with 1,571 contemporaneous global sequences from 75 countries. We observed at least five independent introductions of A(H3N2) viruses into the region during the one-year period, with the importations originating from Africa, Europe, and North America. We also inferred 23 virus location transition events between the nine facilities included in the study. International virus imports into the study area were captured at the facilities of Chasimba, Matsangoni, Mtondia, and Mavueni, while all four exports from the region were captured from the Chasimba facility, all occurring to Africa destinations. A strong spatial clustering of virus strains at all locations was observed associated with local evolution. Our study shows that influenza A(H3N2) virus epidemics in local populations appear to be characterized by limited introductions followed by significant local spread and evolution. Two subtypes of human influenza type A virus (IAV), A(H3N2) and A(H1N1)pdm09, and two 46 lineages of human influenza type B virus (IBV), Victoria and Yamagata, currently co-circulate 47 in human populations [1] causing annual seasonal epidemics globally [2] [3] [4] [5] [6] . These viruses 48 belong to the family Orthomyxoviridae, which are enveloped, negative-sense, single-stranded 49 RNA viruses with segmented genomes [7] . IAVs evolve rapidly and undergo immune driven 50 selection through accumulation of amino acid changes, especially at antigenic sites of 51 hemagglutinin (HA) glycoproteins [8] [9] [10] . These amino acid sequence drifts on HA are 52 observed more frequently in A(H3N2) virus than A(H1N1)pdm09 virus [11, 12] . Since 2009, 53 antigenic drift of A(H3N2) viruses has resulted in emergence of several genetic groups (i.e., 54 clades, subclades, and subgroups) globally, for example, clade 1 to 7 viruses [13] . Clade 3 55 viruses are the most genetically diverse and are divided into several genetic groups: subclades 56 3A, 3B, and 3C; and subgroups 3C.1, 3C.2, 3C.2a, 3C.3, and 3C.3a. We recently characterized 57 A(H3N2) viruses that circulated in coastal Kenya between 2009 and 2017 and revealed co-58 circulation of multiple A(H3N2) virus genetic groups among hospitalized patients and 59 outpatients [5] . 60 61 While the global spread of seasonal influenza viruses has been studied intensively using 62 phylogenetic and phylogeographic approaches [14] [15] [16] [17] [18] [19] [20] , their local patterns of spread remain 63 less clear [21] , especially at city-wide or town scale. Although it is important to understand 64 how diseases spread around the globe, local spread is most often the main driver of novel cases 65 of respiratory diseases such as COVID-19 or influenza [21] . Transmission patterns have been 66 recorded at different levels of human social clustering. Household studies have been performed 67 to investigate person-to-person influenza transmission [22] . Studies of college campuses using 68 phylogenetic methods have revealed extensive mixing of influenza virus strains among college 69 students [23] . City-wide and countrywide, transmission of influenza in a season is 70 characterized by majorly multiple virus introductions into cities [21] and countries [24] [25] [26] ; 71 viruses then spread from multiple geographical locations to multiple geographical destinations 72 following introduction [24] [25] [26] . However, there is a paucity of studies that describe the patterns 73 of spread of influenza on a local scale (city or town) due to sparsity of representative 74 spatiotemporal sequence data from defined sub-populations residing in the same geography 75 within a country [21, 27] . 76 77 . CC-BY-NC 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.08.21263309 doi: medRxiv preprint The ML tree topology based on Kilifi is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.08.21263309 doi: medRxiv preprint Among the 97 IAV positive specimens that were available from the KHDSS, 72 (74.2%) that 204 passed pre-sequencing quality control checks were loaded onto the Illumina MiSeq. A total of 205 63 (87.5%) codon-complete genomes were successfully assembled following sequencing: 58 206 (92.1%) A(H3N2) virus and 5 (7.9%) A(H1N1)pdm09 virus sequences, respectively; only the 207 58 A(H3N2) virus genomes were included in the analysis. The 58 genomes comprised 4 genetic 208 groups: clade 3C.2A (n=34, 58.6%), subclade 3C.2A2 (n=3, 5.2%), subclade 3C.2A3 (n=1, 209 1.7%), and subgroup 3C.2A1b (n=20, 34.5%). The socio-demographic characteristics of the 210 patients whose samples were analyzed in this report are shown in Table 1 . is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted September 12, 2021. ; is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.08.21263309 doi: medRxiv preprint IAV was detected throughout the surveillance period in coastal Kenya (except in July, August, 232 and September 2016) with the number of observed cases fluctuating from month-to-month 233 (Figure 1, Panel B) . The proportion of samples from each health facility that were sequenced 234 roughly reflected the overall distribution of positives that were detected in the specific health 235 facilities (Figure 1, Panel B) We first assessed how the 58 A(H3N2) virus genomes from Kilifi compared to 1,571 genomes 253 sampled from around the world by inferring their phylogenies. The Kilifi genomes span the 254 existing global diversity (Figure 3) , which suggests exchange (most likely introductions into 255 Kilifi) of viruses with other areas around the globe. We then used ancestral location state 256 reconstruction of the dated phylogeny (Figure 3) to infer the number of viral imports and 257 exports. We inferred five importations originating from outside the region (two from Europe, 258 two from Africa, and one from North America), which represent five independent introductions 259 into Kilifi from areas outside the region (Figure 4) . We also inferred a total of 23 virus location 260 transition events between the nine health facilities, is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted September 12, 2021. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.08.21263309 doi: medRxiv preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted September 12, 2021. To determine the phylogeographic structure in the Kilifi sequence data using a statistical 283 approach, phylogeny-trait association tests were conducted to determine phylogenetic 284 association with sampling location (health facility), Table 2 is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.08.21263309 doi: medRxiv preprint confirmed a stronger spatial clustering of sequences at all locations (p<0.001), which is also 286 evident in the time-resolved tree of Kilifi sequences, Figure 5 . Additionally, the maximum 287 clade statistic was significant (p≤0.05) in most locations (6 out of 9 locations) reflecting 288 predominantly local evolution in most locations. The estimated differences in observed and 289 expected maximum clade values tentatively suggested that Pingilikani and Sokoke exhibited 290 the least spatial structure (i.e., most mixing; difference <0) while Matsangoni exhibited the 291 strongest spatial structure (difference of 4). 292 293 . CC-BY-NC 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.08.21263309 doi: medRxiv preprint We observed at least five independent introductions of A(H3N2) viruses into the region during 305 the one-year period, with the importations originating from Africa, Europe, and North America. 306 Additionally, we inferred 23 virus location transition events between the nine facilities 307 included in the study. International virus imports into the study area were captured at the 308 facilities of Chasimba, Matsangoni, Mtondia, and Mavueni, while all four exports from the 309 region were captured from the Chasimba facility, all occurring to Africa destinations. We also 310 observed a strong spatial clustering of virus strains at all locations, which was associated with 311 local evolution. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint In conclusion, although there is paucity of studies that describe the patterns of spread of 367 influenza on a local scale (city or town), our findings suggest that considerable influenza virus 368 diversity circulates within defined sub-populations residing in the same geography within a 369 country, including virus lineages that are unique to those locales, as reported for Kilifi. These 370 lineages may be capable of dissemination to other populations through virus location transition 371 events. Further knowledge of the viral lineages that circulate in specific locales is required to 372 understand the main drivers of novel cases of respiratory diseases and to inform vaccination 373 strategies within these populations. 374 375 . CC-BY-NC 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted September 12, 2021. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted September 12, 2021. ; World Health Organization. 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