Current sampling and sequencing biases of Lassa mammarenavirus limit inference from phylogeography and molecular epidemiology in Lassa Fever endemic regions

Page 1 of 18 1 Current sampling and sequencing biases of Lassa mammarenavirus limit 2 inference from phylogeography and molecular epidemiology in Lassa Fever 3 endemic regions. 4 5 Authors 6 Liã Bárbara Arruda1b#, Hayley Beth Free2a§, David Simons2§, Rashid Ansumana3, Linzy Elton1, 7 Najmul Haider 2c, Isobella Honeyborne 1, Danny Asogun 4, Timothy D McHugh 1, Francine 8 Ntoumi5,6, Alimuddin Zumla1,7, Richard Kock2 9 10 Affiliations 11 1 Centre for Clinical Microbiology, Division of Infection and Immunity, University College 12 London, London, UK 13 2 The Royal Veterinary College, University of London, Hatfield, UK. 14 3 School of Community Health Sciences, Njala University, Bo, Sierra Leone 15 4 Ekpoma and Irrua Specialist Teaching Hospital, Ambrose Alli University, Irrua, Nigeria. 16 5 Fondation Congolaise pour la Recherche Médicale (FCRM), Brazzaville, Republic of Congo 17 6 Institute for Tropical Medicine, University of Tübingen, Germany 18 7 NIHR Biomedical Research Centre, UCL Hospitals NHS Foundation Trust, London, UK 19 a Current affiliation Oxford Brookes University, Oxford, UK 20 b Current affiliation Wellcome Connecting Science, Hinxton, UK 21 c Current affiliation School of Life Sciences, Faculty of Natural Sciences, Keele University, 22 Staffordshire, United Kingdom 23 § Both authors contributed equality to this work 24 # Corresponding author 25 26 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. Page 2 of 18 27 Abstract 28 Lassa fever (LF) is a potentially lethal viral haemorrhagic infection of humans caused by Lassa 29 mammarenavirus (LASV). It is an important endemic zoonotic disease in West Africa with 30 growing evidence for increasing frequency and sizes of outbreaks. Phylogeographic and 31 molecular epidemiology methods have projected expansion of the Lassa fever endemic zone 32 in the context of future global change. The Natal multimammate mouse (Mastomys natalensis) 33 is the predominant LASV reservoir, with few studies investigating the role of other animal 34 species. To explore host sequencing biases, all LASV nucleotide sequences and associated 35 metadata available on GenBank (n = 2,298) were retrieved. Most data originated from Nigeria 36 (54%), Guinea (20%) and Sierra Leone (14%). Data from non-human hosts (n = 703) were 37 limited and only 69 sequences encompassed complete genes. We found a strong positive 38 correlation between the number of confirmed human cases and sequences at the country level 39 (r = 0.93 (95% Confidence Interval = 0.71 - 0.98), p < 0.001) but no correlation exists between 40 confirmed cases and the number of available rodent sequences (r = -0.019 (95% C.I. -0.71 - 41 0.69), p = 0.96). Spatial modelling of sequencing effort highlighted current biases in locations 42 of available sequences, with increased effort observed in Southern Guinea and Southern 43 Nigeria. Phylogenetic analyses showed geographic clustering of LASV lineages, suggestive 44 of isolated events of human-to-rodent transmission and the emergence of currently circulating 45 strains of LASV from the year 1498 in Nigeria. Overall, the current study highlights significant 46 geographic limitations in LASV surveillance, particularly, in non-human hosts. Further 47 investigation of the non-human reservoir of LASV, alongside expanded surveillance, are 48 required for precise characterisation of the emergence and dispersal of LASV. Accurate 49 surveillance of LASV circulation in non-human hosts is vital to guide early detection and 50 initiation of public health interventions for future Lassa fever outbreaks. 51 52 Key-words 53 Lassa mammarenavirus; Lassa Fever; Phylogeography; Metadata; Zoonoses; Surveillance 54 55 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 3 of 18 56 1 Introduction 57 58 Lassa fever (LF) is a lethal zoonotic viral haemorrhagic disease of humans, caused by Lassa 59 mammarenavirus (LASV). It causes an estimated 900,000 annual human infections and 60 several thousand deaths in West Africa annually (1,2). The WHO assigns LASV endemicity to 61 eight West African countries: Benin, Ghana, Guinea, Liberia, Mali, Sierra Leone, Togo and 62 Nigeria (S1 Fig) (3). LASV is a bisegmented ssRNA- virus of the family Arenaviridae (4,5). 63 Based on the genomic analysis of the large (L) and small segments (S) LASV has been 64 classified into seven lineages which demonstrate spatial segregation across the endemic 65 range (6). The high nucleotide variability (25-32%) of these lineages introduces complexity 66 into assays to detect LASV infection. 67 68 Epidemiological data on LF is limited and constrained by current testing and reporting in the 69 endemic region, making accurate estimates of its true burden challenging (7). Many individuals 70 infected with LASV do not seek healthcare with up to 80% of infections assumed 71 asymptomatic or presenting as mild illness (8). Estimates based on longitudinal serological 72 surveys in Sierra Leone in the early 1980’s indicated that 100,000 to 300,000 infections of LF 73 occurred annually in West Africa, with more recent estimates being up to 900,000 infections 74 (2,8). Identification of symptomatic cases is further confounded by overlapping symptoms with 75 other diseases (e.g., malaria) and lack of available diagnostic methods (1,9–11). Access to 76 diagnostic tests varies spatially, increased availability at centers of excellence in LF treatment 77 and research such as the Irrua Specialist Teaching Hospital, Nigeria and Kenema General 78 Hospital, Sierra Leone results in a spatial bias of reported cases from these locations. 79 Phylogenetic analysis and molecular dating of sequence clinical and research samples 80 suggest a westward route of dispersal of LASV lineages, from the most recent common 81 ancestor in Nigeria. (12–18). These estimates have been used to project the potential for 82 Lassa Fever to extend beyond the current endemic zone (19). 83 84 The Natal multimammate mouse (Mastomys natalensis) is the primary reservoir of LASV, 85 however, 11 other rodent species have been found to be acutely infected or have seropositivity 86 to LASV including; Mastomys erythroleucus, Hylomyscus pamfi, Mus baoulei and Rattus 87 rattus (15,20–24). Humans become infected with LASV upon contact with or inhalation of 88 excretions from the rodent species (12,25). Although human-to-human transmission has been 89 reported – typically associated with nosocomial outbreaks – these are rare events when 90 compared with spillover from rodent hosts (26). We performed a study of LASV nucleotide 91 sequences available from the National Centre for Biotechnology Information (NCBI) GenBank, 92 using associated metadata to spatially model sequencing effort, adjusted for the number of . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 4 of 18 93 suspected and confirmed human LF cases to determine potential biases in locations of 94 available sequences or significant geographic limitations in LASV surveillance, particularly, in 95 non-human hosts. 96 97 98 2 Methods 99 100 2.1 Data Collection and Processing 101 102 LASV nucleotide and protein sequences were obtained from the NCBI GenBank (27). The 103 search query run on 24 Sep 2021 was for “Lassa mammarenavirus” in the organism field of 104 the NCBI nucleotide dataset. Data were obtained using the NCBI Entrez API with analysis 105 conducted using the “genbankr” package within the R statistical programming language (27– 106 29). Associated citations were manually retrieved to identify missing metadata for sequences 107 including hosts and geographic location of samples. Sequences with large portions (10% 108 missing compared to reference sequences, NC_004296.1 and NC_004297.1 for S and L 109 segments respectively) of missing nucleotide data on the L- or S-segment or lacking 110 associated metadata (collection year, host species, country, and geographical region of 111 sampling) were excluded from phylogenetic analysis. Nucleotide sequences were aligned 112 using the ‘map to reference’ tool on Geneious Prime 20201.2. Alignment, visual inspection 113 and manual editing were performed, and entries that contained >100 continuous ambiguous 114 nucleotide calls were excluded (S1 Data). 115 116 2.2 Sequencing Bias 117 118 First, we compared the number of cases reported from countries between 2008-2023 with the 119 number of samples contained in GenBank to summarise the correlation between reported 120 human cases and availability of sequences. We then compared the proportion of human to 121 non-human derived sequences within countries. 122 123 To understand the bias of sequenced samples at a sub-national level the origin of a sequenced 124 sample was geocoded using the Google Geocoding API using the “ggmap” package (30). 125 Sequence locations were associated with level-1 administrative regions and data were 126 separated into human and rodent sources of samples to visualise the spatial heterogeneity of 127 sampling. To measure sampling effort bias, the number of samples obtained within a level-1 128 administrative region was associated with the centroid of the region. The number of confirmed 129 LF clinical cases reported from these regions in the previous 15 years was obtained (S2 Data). . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 5 of 18 130 The number of cases within a region was divided by the human population count to produce 131 the number of confirmed cases per 100,000 individuals. The number of sequences was used 132 as the response variable in a spatial Generalised Additive Model, with geographic coordinates 133 and cases per 100,000 individuals used as covariates. This model was constructed using the 134 “mgcv” package (31). 135 136 2.3 Phylogenetic Analysis 137 138 Phylogenetic analysis was undertaken through Bayesian Markov Chain Monte Carlo (MCMC) 139 method using BEAST.v1.10.4 (32). In BEAUTi, the parameters were a substitution model as 140 a generalised time reversible plus gamma site heterogeneity, with codon partition positions 1, 141 2, 3. A strict clock and a coalescent tree prior with a constant size population was used. Each 142 analysis consisted of 20 million MCMC steps and trees were sampled every 20,000 143 generations. Sample collection dates from the metadata were used as tip dates to fit to a 144 molecular clock, and country of sample collection was incorporated as a discrete state (16,33). 145 To assess the log files of the output TRACER.v.1.7.1 was used. Maximum-clade credibility 146 trees were generated through TreeAnnotator v1.8.4 and visualised in FigTree.v1.4.4 (34). 147 148 3 Results 149 150 3.1 Compiled Dataset 151 152 The initial dataset comprised 2,298 records (from samples obtained 1969-2019), including 153 nucleotide sequences and associated metadata. Incomplete gene sequences and sequences 154 lacking metadata information (n = 1,045) were removed from phylogenetic analyses. 155 Therefore, 680 sequences of complete S segment and 573 sequences of partial L segment (L 156 protein only) were used. Accession numbers of included and excluded sequences are 157 available in S1 Data. 158 159 3.2 Descriptive Analysis 160 161 Year of collection was available for 2,108 records, with the oldest sequence dating from 1969 162 and latest from 2019. Among these records, most sequences (n = 1,936, 92%) have been 163 obtained since 2008. Human-derived LASV sequences comprised most of the available 164 records (67%), other host species include Mastomys natalensis (29%) and Mastomys spp. 165 (3%), while Mastomys erythroleucus (n = 18), Mus baoulei (n = 9) and Hylomyscus pamfi (n = 166 10) represent < 1% each. The species sampled was not documented in 107 records. Country . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 6 of 18 167 of collection was available for 2,238 records. Most sequences were produced from samples 168 collected in Nigeria (54%), followed by Guinea (20%), Sierra Leone (14%), Liberia (4%) and 169 Cote d’Ivoire (3%) with the remainder obtained from, Benin, Ghana, Mali and Togo (Fig 1). 170 171 Sequences for human derived samples with regional location data (n = 1328, 63%) were 172 clustered in Edo State, Nigeria (n = 519, 39%), Ondo State, Nigeria (n = 220, 17%) and 173 Eastern Province, Sierra Leone (n = 159, 12%) with 430 samples from the remaining endemic 174 regions. Sequences from rodent samples with regional location data (n = 527, 25%) were most 175 commonly obtained from Faranah, Guinea (n = 210, 39%) and Eastern Province, Sierra Leone 176 (n = 107, 20%) with 210 samples from the regions. 177 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 7 of 18 178 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 8 of 18 179 Figure 1 – The number of sequences, shown on a log 10 scale, retrieved from NCBI GenBank 180 with associated regional sampling location and host for human samples (top, n = 1,328) and 181 rodent samples (bottom, n = 527). Grey regions represent level-1 administrative areas with no 182 sequences within countries that have at least one available sequence. White countries are 183 West African countries with no available LASV sequences. See S1 Fig for country names. 184 Shapefiles for basemap layer obtained from GADM 4.0.2 (35) 185 186 187 3.3 Sequencing bias 188 189 We observed a strong positive correlation between the number of confirmed human cases 190 between 2008-2023 and the number of GenBank deposited sequences at country level 191 (r(degrees of freedom = 7) = 0.93 (95% Confidence Interval = 0.71-0.98), p < 0.001). When 192 analysed by species source no correlation was observed with the number of confirmed cases 193 and the number of available rodent sequences was observed (r(6) = -0.019 (95% C.I. -0.71- 194 0.69), p = 0.96). 195 196 When combining both human and rodent-derived samples at the regional level to explore 197 spatial sampling biases, we found that sequencing effort is greatest in Southwest Nigeria, 198 centred over Edo State and the Faranah and Nzérékoré regions of Guinea, Eastern Province 199 of Sierra Leone and Nimba district of Liberia (Fig 2). There was a positive, non-linear 200 association between the rate of confirmed human cases with the number of available rodent 201 and human derived LASV sequences at regional level (deviance explained = 14%, estimated 202 degrees of freedom = 2.29, p < 0.001). 203 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 9 of 18 204 205 Figure 2 – Modelled relative sequencing effort derived from both human and rodent samples. 206 Greatest sequencing effort coincides with areas where sampling in humans (Edo, Nigeria and 207 Kenema, Sierra Leone) and rodents (Faranah, Guinea) have historically been focussed. 208 Shapefiles for basemap layer obtained from GADM 4.0.2 (35) 209 210 3.4 Phylogenetic Analysis 211 212 Sequences for each segment of LASV showed clustering according to previously documented 213 lineages I-VII alongside geographical clustering with lineages I-III and VI present in Nigeria, 214 lV in Liberia, Guinea and Sierra Leone, V in Mali and VII in Togo (S2 Fig). In this analysis only 215 L segment sequences of lineage V from Cote d’Ivoire were included due to quality control 216 exclusion criteria. The phylogeny of the L segment indicates an older emergence of LASV in 217 the human population, with the most recent common ancestor (MRCA) predicted in the year 218 828 in Nigeria, inference based on the S segment indicates the emergence in the year 1350 219 (Table 1). 220 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 10 of 18 221 Table 1 - The most recent common ancestor (MRCA) stratified by host and country of 222 collection of Lassa mammarenavirus (LASV) S and L segments. Samples were collected 223 between 1969-2018. Host species Country S segment MRCA L segment MRCA Benin 1995 1989 Guinea 1895 1871 Liberia 1895 1627 Nigeria 1681 1498 Sierra Leone 1901 1874 Homo sapiens (n=1181) Togo 2016 2014 Hylomyscus pamfi (n=2) Nigeria 1681 1498 Guinea 1975 2010Mastomys erythroleucus (n=18) Nigeria 2008 2006 Guinea 1938 1997 Mali 1951 2007 Mastomys natalensis (n=36) Sierra Leone 1909 1979 224 225 There was a lack of sequence information from lineage I and VI, however, phylogeny suggests 226 these lineages are basal to others in Nigeria (S2 Fig). Lineage VII in Togo is most closely 227 related to Nigerian isolates and potentially diverged between 500-900 years ago. The 228 divergence of lineage III and IV is predicted to have occurred between the years 1332-1551. 229 Introduction to countries west of Nigeria appears to be by dispersal initially to Liberia, followed 230 by Guinea in the 1700s, followed by Sierra Leone and Mali approximately 100 years later. A 231 lack of full segment sequences from lineage V limits calculation of divergence from the most 232 recent common ancestor from lineage IV (approximately 200 years). 233 234 235 4 Discussion 236 237 There are several important aspects of our study and findings. First, we studied a 238 comprehensive dataset of publicly available full-segment LASV sequences, spanning West 239 Africa and host species, to inform our understanding of the phylogeny of LASV dispersal. 240 Second, we identified substantial variability in the origin of available sequences and 241 completeness of records. Third, we showed strong geographic clustering among lineages 242 supporting prior hypotheses of radiation from both Nigeria and a subsequent introduction into 243 Liberia (19). Fourth, the synthesis of available metadata highlights important gaps in currently . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 11 of 18 244 available data, including spatial bias in the sequencing of samples and suggests this should 245 be used to inform the design of epidemiological programmes going forward. 246 247 Our analyses of 2,298 LASV sequences obtained from GenBank highlights the spatial biases 248 in the availability of sequence data that may limit our understanding of the current and historic 249 dispersal of LASV lineages in West Africa. First, sequence data was typically obtained from 250 three of the eight endemic countries: Nigeria, Guinea and Sierra Leone. We found a strong 251 associated between the number of reported human cases and number of available sequences. 252 When stratifying by host species this trend did not remain with rodent derived samples 253 showing no association with the number of human cases indicating important under-sampling 254 in high human cases regions and relatively high sampling in locations with low numbers of 255 human cases. This is potentially an important source of bias when attempting to infer 256 phylogeography within the reservoir host of this zoonotic pathogen. Sequence data from other 257 countries, and more regions within them, across West Africa are required to increase 258 confidence in the timelines of the currently inferred westward expansion. Greater focus needs 259 to be placed on acquiring sequences from the rodent host to understand viral genetic diversity 260 within the primary reservoir species. Comparing rodent derived sequences with those 261 acquired from spillover into human populations may also allow identification of genetic drivers 262 of transmission (36). 263 264 The overrepresentation of data from these three countries has been mapped as relative 265 sequencing effort to identify regions where increased LASV sequencing are required to 266 counteract current sequencing biases. Second, geographic clustering of LASV lineages, 267 suggest isolated events of human-to-rodent transmission and the emergence of LASV dating 268 from 1498 in Nigeria. Similarly, Olayemi et al. report evidence of earlier emergence of the virus 269 in humans than in rodents in Nigeria (16). Comparatively limited data from non-human hosts 270 with limited genome coverage, (69/703 sequences encompassed complete genes) produce 271 important uncertainty around the observation of human-to-rodent transmission. Taken 272 together, this data highlight limited surveillance among animal species, necessitating further 273 investments in data acquisition and sharing to accurately define the spatiotemporal expansion 274 of LASV in West Africa. 275 276 The phylogenetic analysis of LASV stratified by host species supports spatial evolution, in 277 addition to intra-host viral evolution (S2 Fig). For instance, LASV sequences from M. 278 erytholeucus sampled in Nigeria and Guinea clustered within lineages III and IV, respectively. 279 Interestingly, these isolates appear to occur after the emergence of the most recent common 280 ancestor virus circulating among humans and M. natalensis in these countries (Table 1), . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 12 of 18 281 suggesting introduction of LASV into M. erythroleucus populations was a consequence of 282 pathogen circulation in human and M. natalensis populations. Sequences from M. natalensis 283 in Sierra Leone exhibit minimal clustering, and were interspersed with sequences from 284 humans, potentially representing isolated events of pathogen introduction into human 285 populations with spillback into commensal rodent populations (i.e., reverse zoonosis). The 286 most recent common ancestor of LASV sequences from M. natalensis in Sierra Leone suggest 287 a later emergence of the virus in this country. Our findings corroborate those of Olayemi et al., 288 that within Sierra Leone LASV appears to have emerged in human hosts before rodents (16). 289 However, this data must be caveated by the limited information from rodent species in these 290 locations. 291 292 There is a lower coverage of rodent-derived LASV sequences, with those from the primary 293 reservoir M. natalensis forming fewer than one-third of all sequences (n = 642, 28%), with 294 substantially lower sampling of other possible rodent hosts, including other Mastomys species. 295 Rodent sampling has not increased at the same rate as human samples despite increased 296 sampling effort since 2008 (15,22,37). There is substantial heterogeneity in the locations in 297 which rodent and human samples are available. For example, a relatively high number of 298 rodent samples (n = 429) have been obtained from Guinea while few human sequences (n = 299 20) are available from these locations. The inverse is true of Nigeria where most human 300 derived sequences are obtained (n = 1,147) but only 85 rodent sequences are available, and 301 all of these from a single state (Edo, Nigeria). The number of suspected and reported cases 302 was found to be positively but non-linearly associated with the number of available sequences. 303 This is suggestive of a consolidation of research and focus of sampling in areas historically 304 with high numbers of human cases but has led to a paucity of sequences from elsewhere in 305 the endemic region. The limited number of full segment sequences from rodents, from few 306 geographic locations, limits our understanding of viral radiation in rodent hosts, particularly 307 from species which are not considered the primary reservoir, e.g., H. pamfi. The most recent 308 common ancestor for the viral sequence obtained from H. pamfi is estimated to be in the late 309 1600s, it is therefore possible lineage VI and/or H. pamfi as a reservoir of LASV has gone 310 undetected due to lack of sufficient sampling (15). 311 312 Interpreting available LASV sequences is challenging for several reasons. A large proportion 313 of available sequences (70%) have been obtained within Lassa fever research programs, 314 representing spatial ascertainment bias (38–40). In addition to these spatial biases’ temporal 315 biases are apparent. Since 2016 there has been a substantial increase in the number of LASV 316 sequences available in NCBI GenBank, reflecting increasing research effort, availability of 317 sequencing platforms and increased data collection during Lassa fever epidemics, such as in . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 13 of 18 318 the 2018 Nigeria Lassa fever outbreak (41–43). There are notably fewer recorded sequences 319 of LASV from Benin, Togo, and Ghana, suggesting a potential a gap in surveillance and 320 research capacity in these locations or a lack of circulating LASV, despite several reported 321 outbreaks (44–46). Phylogenetic analysis on 60% of our initial dataset, following removal of 322 sequences due to incompleteness or missing geographic and year of collection information (n 323 = 1,045) demonstrated geographic clustering of LASV lineages, supporting prior analyses 324 (14–16,33,44,47–49). Increased data availability from Nigeria following increased LASV 325 surveillance allowed regional analysis of phylogeny for lineages II and III supporting previous 326 findings of expansion of these lineages from North-East Nigeria to the South-West of the 327 country (13,50,51). 328 329 A substantial number (n = 869) of the sequences retrieved corresponded to short fragments 330 (< 1 Kb) probably derived from PCR products used for diagnostic purposes rather than for 331 viral genomic surveillance. LASV is a segmented virus, and it was not possible to identify 332 complete genome sequences since both S and L segments are reported separately on the 333 sequence’s repository. The molecular clock analyses from L protein indicated an earlier 334 emergence of LASV when compared to S segment analysis (828 and 1350 respectively), 335 potentially because the viral RNA polymerase (L protein) is less affected by selective 336 pressure than the S segment (12,47,52). 337 338 Despite these challenges, this study has synthesised currently available data on LASV 339 sequences to investigate the location and period of sampling to reconstruct the dispersal of 340 viral lineages across the endemic region. Despite the regionalisation of LF being driven by 341 rodent-to-human transmission, there remains scarce LASV genomic data from non-human 342 hosts. We have mapped the locations of relative under sampling to guide targeted efforts to 343 counteract biases in currently available data for both rodent and human derived sequences. 344 Expanded sampling of LASV from animal species within the endemic region will improve our 345 current understanding of LASV evolution and ecology and improve confidence in current 346 estimates of westward expansion of Lassa fever in humans. Further understanding of the 347 viral evolution dynamics of LASV and spatial expansion of current lineages will be vital to 348 ensure adequate diagnostic tools are available to respond to the expected sporadic 349 outbreaks of Lassa Fever across the region. 350 351 Supplementary material 352 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 14 of 18 353 S1 Data. GenBank accession number of analysed sequences. This dataset includes 354 available data about host, country, region, year, sequence length, genome segment (L or S) 355 and predicted MRCA. 356 357 S2 Data. Dataset on confirmed Lassa fever cases. This presents the number of confirmed 358 cases of Lassa fever reported from countries between 2008 and 2023 at a subnational level 359 that were used to calculate the number of cases per 100,000 people. References for the 360 reports used to produce this dataset are included. 361 362 S1 Figure. Map of West Africa. displays a map of West Africa with country names for 363 reference with Fig 1 and Fig 2. Shapefiles for mapping obtained from GADM 4.0.2 (35) 364 365 S2 Figure. Time-calibrated phylogeny for both the small segment (S) and large segment 366 (L) from included LASV sequences. 367 368 Author contributions 369 Conceptualisation: DS and LBA; Methodology: HF, DS, DA and LBA; Formal Analyses: HF, 370 DS and LBA; Investigation: HF, DS and LBA; Supervision: LBA; Data Curation: HF and DS; 371 Writing – original draft preparation: HF, DS, LBA; Writing – Review and Editing: IH, LE, NH, 372 RA, RK, FN, DA, AZ and TMcH; Funding acquisition: AZ and FN. 373 374 Data availability and reproducibility 375 All data used in these analyses are publicly available from GenBank. The accession numbers 376 of records used are available as supplementary material. Code to reproduce the metadata 377 analyses are available as an archived Git release on Zenodo 378 (https://doi.org/10.5281/zenodo.6340162) 379 380 Conflict of interests 381 The authors declare no conflict of interests 382 383 Acknowledgements: 384 Linzy Elton, Timothy D McHugh, Francine Ntoumi, and Alimuddin Zumla acknowledge support 385 from EDCTP-Central Africa and East African Clinical Research Networks (CANTAM-3, 386 EACCR-3). Sir Zumla is an NIHR Senior Investigator, a Mahathir Science Award, Sir Patrick 387 Manson Medal and EU-EDCTP Pascoal Mocumbi Prize laureate. Liã Bárbara Arruda, David 388 Simons, Rashid Ansumana, Linzy Elton, Najmul Haider, Isobella Honeyborne, Danny Asogun, 389 Timothy D McHugh, Francine Ntoumi, Alimuddin Zumla and Richard Kock acknowledge . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted June 22, 2023. ; https://doi.org/10.1101/2023.06.20.23291686doi: medRxiv preprint Page 15 of 18 390 support from the Pan-African Network for Rapid Research, Response and Preparedness for 391 Infectious Diseases Epidemics – PANDORA-ID-NET, funded through the European and 392 Developing Countries Clinical Trials Partnership (EDCTP) (grant number RIA2016E-1609). 393 David Simons is supported by a PhD studentship from the UK Biotechnology and Biological 394 Sciences Research Council (BB/M009513/1). 395 396 References 397 1. Asogun DA, Gunther S, Akpede GO, Ihekweazu C, Zumla A. Lassa Fever: Epidemiology, Clinical 398 Features, Diagnosis, Management and Prevention. [Review]. Infectious Disease Clinics of North 399 America. 2019;33(4):933–51. 400 2. Basinski AJ, Fichet-Calvet E, Sjodin AR, Varrelman TJ, Remien CH, Layman NC, et al. 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