The 2013–present Western African Ebola virus disease (EVD) outbreak is the largest ever recorded with >28,000 reported cases. Ebola virus (EBOV) genome sequencing has played an important role throughout this outbreak; however, relatively few sequences have been determined from patients in Liberia, the second worst-affected country. Here, we report 140 EBOV genome sequences from the second wave of the Liberian outbreak and analyze them in combination with 782 previously published sequences from throughout the Western African outbreak. While multiple early introductions of EBOV to Liberia are evident, the majority of Liberian EVD cases are consistent with a single introduction, followed by spread and diversification within the country. Movement of the virus within Liberia was widespread, and reintroductions from Liberia served as an important source for the continuation of the already ongoing EVD outbreak in Guinea. Overall, little evidence was found for incremental adaptation of EBOV to the human host.

Here, we report 140 EBOV genome sequences from the second wave of the Liberian outbreak; these sequences were generated as part of our ongoing surveillance efforts (). Combined with previously published data, these sequences cover 13 Liberian counties and enabled us to perform a longitudinal analysis spanning nearly an entire year of the outbreak. This analysis provides an in-depth look at the introduction and spread of EBOV in Liberia. We further analyzed all Liberian sequences in combination with 734 genomes from Guinea, Mali, and Sierra Leone to place the Liberian cases in the context of the entire Western African outbreak and to screen for patterns of EBOV adaptation to the human host.

Despite the multi-lateral sequencing efforts, the available genome sequences still represent <4% of the reported cases. Lacking in particular are sequences from cases in Liberia (deposited genomes represent <0.5% of reported cases). As of September 30, 2015, the second highest number of EVD cases among all affected countries (10,672, 37.5% of total) and the highest number of EVD-related deaths (4,808, 42.5% of total) were reported from Liberia. The Liberian portion of the outbreak is thought to have consisted of at least two distinct waves of EVD cases. The first began in March 2014 and is thought to have been relatively short in duration and scope (<20 reported cases), while the second wave, which likely started during May 2014, included the vast majority of cases (). Two additional, isolated EVD case clusters have occurred in Liberia, March 20–28 and June 28 to July 22, 2015. However, current data indicate that both likely represent reemergence of transmission chains from the major second wave of EVD cases () (unpublished data). Liberia was declared free of EBOV infections, for the second time, on September 3, 2015.

High-throughput EBOV genome sequencing has served an integral role in understanding and responding to the Western African EVD outbreak. As of September 30, 2015, almost 1,000 nearly full-length EBOV Makona genome sequences have been determined (). Early sequences from patients in Guinea and Sierra Leone demonstrated that the Western African outbreak resulted from a single EBOV introduction event followed by sustained human-to-human transmission (); real-time genomic surveillance in Liberia has provided evidence for sexual transmission of the virus, resulting in changes to public-health policy (); and continued genomic sequencing throughout the outbreak has provided a detailed view into the ongoing spread and diversification of EBOV, thus providing critical information for maintaining effective control strategies ().

Late in 2013, a novel variant of Ebola virus (EBOV Makona) () emerged in the human population of southeastern Guinea to start what would become the largest human Ebola virus disease (EVD) outbreak on record (). As of September 30, 2015, 28,424 EVD cases had been reported in association with this outbreak, including 11,311 deaths (39.8% case-fatality rate), and new EVD cases were still being reported in two of the three most heavily impacted countries: Guinea (3,805 cases, 13.4% of total) and Sierra Leone (13,911, 48.9%) (). The unprecedented scale of this outbreak resulted in sustained human-to-human transmission, the ramifications of which are still being explored.

Nomenclature- and database-compatible names for the two Ebola virus variants that emerged in Guinea and the Democratic Republic of the Congo in 2014.

We utilized a Bayesian, phylogeny-based approach to identify signatures of diversifying positive selection. This analysis highlighted 11 codons with significant support for positive selection (dN > dS posterior probability > 0.9) ( Figure 5 Table S6 ). One codon was identified within each of four ORFs: NP (codon 737), VP30 (codon 248), VP24 (codon 28), and L (codon 1,772); the other seven codons were located in the GPORF (codons 82, 455, 472, 479, 480, 493, and 638). Five codons each exhibited two distinct non-synonymous substitutions; the rest contained a single non-synonymous change. The frequency of the non-synonymous variants ranged from 0.11% to 91.7%. Eleven (68.8%) of the 16 non-synonymous substitutions at these codons were each only observed in the genome from one sample. Five of the significant GP codons and the one L codon are located within regions we identified to be intrinsically unstructured and to be hotspots for non-synonymous substitution. The most significant codon, GP-82 (dN > dS posterior probability = 0.995), includes a non-synonymous substitution (A82V) that arose early in the outbreak, during the transition between the GN1 and SL1 lineages. Codon 82 is located in the region of the GPthat contains the receptor binding domain (codons 54–201;). The substitutions at GP-638 (Q638R or Q638L) are also intriguing because they affect the glycoprotein’s tumor necrosis factor-alpha converting enzyme (TACE) cleavage site. The sheddase TACE cleaves the membrane-bound GP at the sequence L635-P-D↓-Q removing GPfrom the cell surface. TACE cleavage has been proposed as a mechanism of pathogenesis for filoviruses and sequence conservation among filoviral groups suggests that TACE-cleavage is important for fitness ().

The ongoing outbreak of EVD in Western Africa is substantially larger than all previously recorded outbreaks combined in terms of both the number of cases and the time span (a proxy for the length of transmission chains). Therefore, this outbreak has provided EBOV with unprecedented opportunity to evolve within the human host. The non-synonymous substitutions that have arisen during this outbreak are non-uniformly distributed across the EBOV genome ( Figure 5 A), with peaks in density at the C terminus of the NP gene, the region of the GP gene encoding the mucin-like domain, and toward the end of the L (RNA-dependent RNA polymerase) gene. Relative frequencies of non-synonymous substitutions across the EBOV genome within the human population are generally consistent with patterns of EBOV divergence within its unknown reservoir host, estimated using the earliest available genome sequence from each of nine distinct EVD outbreaks ( Figure 5 A; linear Rof 0.72). However, the rate of non-synonymous substitutions, relative to synonymous substitutions, is generally elevated across the genome within the Western African outbreak ( Figure 5 ), consistent with previous reports of incomplete purifying selection (). Peaks in non-synonymous divergence largely correspond to regions predicted to be intrinsically unstructured (). Therefore, these hotspots for non-synonymous substitution have likely resulted primarily from a lower level of functional constraint on encoded viral proteins.

(B and C) Distribution of dS (synonymous substitutions per synonymous site), dN (non-synonymous substitutions per non-synonymous site), and dN/dS. For each dataset, dS and dN were both normalized by the average dS per window. A sliding window of 999 nt (333 codons) was used with a step size of 249 nt (83 codons).

(A) Non-synonymous substitutions that have occurred within the Western African EVD outbreak (solid line) and between outbreaks caused by EBOV (dashed line). A sliding window of 1,000 nt was used with a step size of 250 nt. Each count was normalized by the average number of substitutions per window.

Ebolavirus is evolving but not changing: No evidence for functional change in EBOV from 1976 to the 2014 outbreak.

We estimated that viruses from LB1, LB4, and LB5 first entered Guinea in June–July 2014. The time to the most recent common ancestor (TMRCA) for all Guinean sequences in each of these sub-lineages was estimated to be July 22, July 9, and June 22 for LB1, LB4, and LB5, respectively ( Table S5 ). Circulation of LB1 viruses appears to have subsided around the same time in Liberia and Guinea, in late September 2014. LB4 and LB5 viruses, on the other hand, continued to circulate in Guinea into January 2015, beyond the last sampled genomes from those sub-lineages in Liberia ( Figure 3 B).

The four sequences from Mali also fell within the LB5 sub-lineage. Their placement is consistent with previous genetic characterization and epidemiological reports (). These four sequences include representatives from two independent introductions of EBOV to Mali, both of which have been traced to the movement of infected individuals from Guinea (). Our genetic data additionally demonstrate that both of these introduction events fall within transmission chains that can be traced back to the Liberian portion of the outbreak.

Although we found little evidence for additional movement of EBOV into Liberia following the initial appearance of the SL2 lineage, we obtained evidence for several re-introductions of SL2-derived EBOV from Liberia into Guinea. Viruses belonging to four sub-lineages of the Liberian outbreak were also detected in Guinea (LB1, LB2, LB4, and LB5; Figure 3 ). The Guinean sequences belonging to LB1 and LB4 (GN3 in) each formed distinct clades (for defining SNPs see Table S3 ), suggesting single introductions of viruses of each sub-lineage followed by spread and diversification within Guinea. Viruses belonging to LB4 seem to have disappeared from Liberia shortly after spreading into Guinea, where they continued to circulate for ∼6 months ( Figure 3 B). Viruses belonging to LB2 included two divergent Guinean sequences, suggesting two independent introductions, each of which resulted in limited, if any, spread within Guinea. Viruses belonging to LB5 (GN4 inand GUI-2 in) were the most successful of the exports into Guinea both in terms of the number of EVD cases and geographic breadth. In total, 68 of the Guinean EBOV genomes belonged to LB5, including 23 from samples collected in western Guinea (Conakry, Dubréka, Coyah, and Forécariah). The other Liberian sub-lineages that were introduced to Guinea were restricted in our dataset to the eastern half of Guinea. The pattern of shared diversity between Guinea and Liberia within the LB5 sub-lineage suggests either multiple EBOV importations from Liberia into Guinea or movement back into Liberia from Guinea following the initial introduction.

The Liberian outbreak was characterized by a large amount of within-country movement of EBOV. In spite of missing metadata from 37% of the samples, all of the major sub-lineages were observed in ≥2 Liberian counties; on average, each sub-lineage was observed in 4.25 counties ( Figure 3 C). In total, we estimated ∼63 instances of between-county exchange of EBOV based on 182 Liberian sequences from samples with SL2 lineage viruses ( Figures 4 and S1 ). The heavily impacted counties near Liberia’s capital, Margibi and Montserrado, were the largest exporters of EBOV to the rest of the country followed by Lofa, which shares a border with both Guinea and Sierra Leone and is the nearest Liberian county to the putative index case of the Western African outbreak (Méliandou, Nzérékoré Region, Guinea) (). The high number of predicted Margibi-to-Montserrado movement events is partly due to the inference of Margibi as the most probable county of origin for the SL2 lineage in Liberia ( Figure 4 A). This inference should be interpreted cautiously given the limited sampling (relative to the full outbreak), and the large amount of missing metadata associated with early Liberian samples; only 31% (8/26) of the samples from June–July 2014 are associated with county-level metadata (all from Lofa).

(C) Well-supported (Bayes factor ≥ 3) asymmetric rates of viral migration between counties. Arrow color indicates magnitude. Counties are colored by cumulative number of cases reported by the WHO.

(A) Temporal maximum clade credibility tree from BEAST analysis. Circles at the nodes indicate inferred ancestral location of each lineage. Circles with black outlines at the branch tips represent samples with known county of origin; those with white outlines were inferred in the analysis as a latent variable over the course of the MCMC. Circle size is proportional to the posterior probability of the assigned county. The bar at the root indicates the 95% HPD for the estimated root date.

Despite multiple early introductions, the vast majority of Liberian EBOV sequences are consistent with a single introduction, most likely of an SL2 virus. The SL2 lineage includes Liberian sequences from as early as June 20, 2014 and all sequences sampled after July 3, 2014. Following the initial introduction of an SL2 EBOV into Liberia, the viral population rapidly diversified within that country, consistent with the exponential increase in EVD cases recorded through August 2014 ( Figure 1 ). The second wave of the Liberian outbreak was dominated by eight sub-lineages of SL2 referred to here as LB1–LB8 ( Figure 3 ). Together, these eight sub-lineages contained ∼92% (167/182) of the Liberian samples stemming from the SL2-type virus introduction. Each Liberian sub-lineage can be distinguished from the basal SL2 haplotype by one to two substitution events ( Table S3 ), and mean posterior estimates for the origin of each of these sub-lineages ranged from May 31, 2014 for LB3 (95% HPD: May 9–June 19) to July 21, 2014 for LB7 (95% HPD: June 27–August 5) ( Table S4 ). Sample testing dates were used to obtain minimum estimates for the duration of each sub-lineage in Liberia. On average, each sub-lineage circulated for at least 130 days. LB4 viruses exhibited the shortest duration within Liberia, only 46 days, while viruses of three different sub-lineages (LB2, LB3, and LB7) each circulated for >180 days. Several of these sub-lineages are defined by non-synonymous substitutions ( Table S3 ); targeted examinations of these changes will be required to determine whether any led to functional changes.

(A) Median-joining haplotype network based on a full genome alignment of 158 sequences from Liberia (SL2 only and with ≥ 98% genome coverage) and 95 sequences from Guinea and Mali that clustered within Liberian sub-lineages.

One limitation of the current dataset is the lack of sequences from Lofa County after August 22, 2014. Based on epidemiological data and proximity to the epicenter of the outbreak, Lofa County was one of the most likely entrance points into Liberia for EBOV lineages originating in neighboring countries (). Although the number of reported EVD cases in Lofa dropped rapidly starting in September 2014, cases were reported as late as mid-November 2014 (). Additional introductions into Liberia may have occurred during this period with limited transmission and spread outside of Lofa County.

Phylogenetic analysis revealed the presence of at least three distinct lineages of EBOV in Liberia ( Figure 2 ). The earliest Liberian EBOV genome sequence (April 1, 2014), and the only sequence from the first wave of Liberian EVD cases, was placed within the GN1 lineage () (referred to as GUI-1 in), otherwise exclusively containing sequences from Guinea. The other two EBOV lineages observed in Liberia were both associated with samples collected as early as June 2014, during the second wave of the Liberian outbreak. Four samples (June 20–July 3, 2014) fell within lineage SL1 (), which includes EBOV sequences from Guinea and Sierra Leone. The remaining 183 Liberian sequences, including all of the sequences obtained during this study, fell within lineage SL2 (). While SL2 also includes EBOV sequences from both Sierra Leone and Guinea, the basal haplotype within this lineage has previously only been sampled from Sierra Leone; this same haplotype was detected in two of our Liberian sequences (LIBR10089 and LIBR10237). Through phylogenetic rooting, it has been demonstrated that the SL2 lineage was derived from an SL1 virus (). Four nucleotide substitutions differentiate SL1 and SL2 sequences, and thus far no intermediate haplotypes have been uncovered, making it difficult to pinpoint the location of the SL1-SL2 transition. However, the presence of the basal haplotypes from both SL1 and SL2 during May in Sierra Leone suggests that this transition occurred in Sierra Leone, in which case the Liberian SL1 and SL2 sequences represent at least two distinct EBOV introductions into Liberia.

(A) Phylogenetic and temporal placement of 188 Liberian EBOV genomes relative to 734 EBOV sequences from Guinea, Mali, and Sierra Leone. Three distinct lineages are represented in the Liberian samples: GN1, SL1, and SL2.

To place these Liberian sequences within the broader context of the Western African EVD outbreak, we compared them to 734 published sequences from Guinea, Mali, and Sierra Leone ( Table S2 ), which together spanned March 17, 2014 to January 31, 2015 (). Combined, these 922 samples contained 1,474 SNPs, 546 (37%) of which were parsimony-informative and 13 insertions/deletions (indels), 8 (61.5%) of which were parsimony-informative. All of the indels were located within non-coding regions. Of the SNPs, 960 were located within coding regions, 403 were non-synonymous within at least one open reading frame (ORF), 555 were synonymous, and two were nonsense mutations. In total, three mutations were predicted to result in premature stop codons within at least one ORF (one each in the nucleoprotein [NP], the glycoprotein [GP] and the viral protein 30 [VP30] genes) and one in the loss of the stop codon at the end of the ORF encoding the small soluble glycoprotein [ssGP] in the GP gene. However, with the exception of the previously reported nonsense mutation in VP30 that was present in 29 genomes in our analysis (position 9,354 relative to Ebola virus/H.sapiens-wt/GIN/2014/Makona-C15, Genbank KJ660346.2 ) (), all of these mutations were only observed in a single sample obtained from a public repository; therefore, we were unable to verify these putative ORF disruptions.

Using high-throughput sequencing technologies, we assembled an additional 140 EBOV genomes from 139 Liberian EVD patients. Two different samples were sequenced from one patient; these had identical consensus sequences. We also improved genome coverage for most of the 25 Liberian EBOV sequences we reported previously (additional 11% on average) (). Together, these 165 genomes spanned June 23, 2014 to February 14, 2015. Genome coverage ranged between 67.6%–99.7% with a mean coverage of 98.5% ( Table S1 ); 115 genomes are coding-complete, and the remainder are standard drafts according to the nomenclature laid out in. In combination with 22 sequences reported from the European Mobile laboratory (April 1–August 22, 2014) () and one sequence reported from the Centers for Disease Control and Prevention (August 3, 2014) (), we analyzed a total of 188 Liberian EBOV genomes. Together, these samples represent ∼1.8% of the reported EVD cases in Liberia (as of September 30, 2015) (). They temporally span nearly one year of the epidemic, including the period during which 99% of the confirmed and probable cases were reported in Liberia ( Figure 1 ). County of origin was reported for 119 (63%) samples. Together, they covered 13 of the 15 Liberian counties with sample sizes per county roughly proportional to the number of reported cases.

(C) Relative genetic diversity calculated with BEAST for the SL2 lineage in Liberia (SkyGrid reconstruction). The solid line represents the median estimate from the posterior probability, and the dashed lines represent the upper and lower estimates of the 95% credible interval.

Discussion

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et al. Evolution of ebola virus disease from exotic infection to global health priority, Liberia, mid-2014. UNICEF, 2014 UNICEF (2014). UNICEF-Liberia Ebola Virus Outbreak SitReps. www.unicef.org/appeals/files/UNICEF_Liberia_SitRep11_Ebola_Virus_Outbreak_7April2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep19_Ebola_Viral_Disease_23Apr2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep_22_Ebola_Viral_Disease_2_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep23_Ebola_Viral_Disease_13_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep24_Ebola_Viral_Disease_17_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep_Ebola_Viral_Disease_9July2014.pdf. The first appearance of EBOV in Liberia involved a GN1 lineage virus. GN1 sequences were commonly found in eastern Guinea during March–May 2014 (), consistent with a Guinean source for the first wave of Liberian EVD cases, which began in mid-March 2014 and ended in early-April 2014 (). This initial wave of cases is thought to have been locally contained, and our analysis is consistent with this speculation as no second wave Liberian sequences clustered within the GN1 lineage. Unfortunately, county-level information was not associated with the only first wave Liberian sample included in our analysis (KR817194). However, given the timing, it is likely that this sample was part of the transmission chain that began with a woman who died in mid- to late-March 2014 in Lofa County, which is situated in northwestern Liberia and shares borders with both Sierra Leone and Guinea. Six cases from this transmission chain were confirmed to be EBOV positive, including four samples from Lofa and two from Margibi ().

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Monitoring of Ebola Virus Makona Evolution through Establishment of Advanced Genomic Capability in Liberia. UNICEF, 2014 UNICEF (2014). UNICEF-Liberia Ebola Virus Outbreak SitReps. www.unicef.org/appeals/files/UNICEF_Liberia_SitRep11_Ebola_Virus_Outbreak_7April2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep19_Ebola_Viral_Disease_23Apr2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep_22_Ebola_Viral_Disease_2_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep23_Ebola_Viral_Disease_13_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep24_Ebola_Viral_Disease_17_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep_Ebola_Viral_Disease_9July2014.pdf. Sack et al., 2014 Sack, K., Fink, S., Belluck, P., and Nossiter, A. (2014). How Ebola Roared Back: Missed Chances. New York Times, http://www.nytimes.com/2014/12/30/health/how-ebola-roared-back.html?_r=1. Sack et al., 2014 Sack, K., Fink, S., Belluck, P., and Nossiter, A. (2014). How Ebola Roared Back: Missed Chances. New York Times, http://www.nytimes.com/2014/12/30/health/how-ebola-roared-back.html?_r=1. Contact tracing has revealed at least three potential introductions of EBOV to Liberia from Sierra Leone in late-May to early-June 2014. The timing of these events is consistent with the start of the second wave of Liberian EVD cases, and both lineages we observed in this second wave (SL1 and SL2) were present in Sierra Leone at this time (). This time period is also consistent with our previous estimate for the TMRCA of all Liberian SL2 viruses (). The earliest documented introduction involved a patient who traveled to Lofa from Sierra Leone on May 23, 2014; she died in Lofa on May 25, and her body was returned to Sierra Leone for burial (). This patient has been linked to additional EVD cases in Sierra Leone and Liberia, including cases in Monrovia (). However, our analysis indicated that this introduction involved an SL1 virus, which means that it is unlikely to have led to the majority of Liberia’s EVD cases. Two of the sequences analyzed here came from samples that can be linked to this transmission chain (KR817231 and KR817233) (S. Fink, personal communication), and both belong to the SL1 lineage. A second introduction from Sierra Leone to Lofa occurred in early-June 2014 (); it is unclear what lineage of virus was introduced in this instance or whether this case resulted in further transmission in Liberia.

UNICEF, 2014 UNICEF (2014). UNICEF-Liberia Ebola Virus Outbreak SitReps. www.unicef.org/appeals/files/UNICEF_Liberia_SitRep11_Ebola_Virus_Outbreak_7April2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep19_Ebola_Viral_Disease_23Apr2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep_22_Ebola_Viral_Disease_2_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep23_Ebola_Viral_Disease_13_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep24_Ebola_Viral_Disease_17_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep_Ebola_Viral_Disease_9July2014.pdf. UNICEF, 2014 UNICEF (2014). UNICEF-Liberia Ebola Virus Outbreak SitReps. www.unicef.org/appeals/files/UNICEF_Liberia_SitRep11_Ebola_Virus_Outbreak_7April2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep19_Ebola_Viral_Disease_23Apr2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep_22_Ebola_Viral_Disease_2_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep23_Ebola_Viral_Disease_13_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep24_Ebola_Viral_Disease_17_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep_Ebola_Viral_Disease_9July2014.pdf. The third documented introduction is reported to have occurred in late-May or early-June 2014 when a woman traveled from Sierra Leone to the New Kru Town community in Monrovia, Montserrado County. This patient has been linked to several other EVD cases in Monrovia, including health care workers at Redemption Hospital (). We don’t know the lineage of EBOV involved in this introduction, but this is a good candidate for the SL2 introduction that appears to have led to the majority of Liberian EVD cases. Our analysis indicated that the success of SL2 lineage viruses in Liberia was likely due in part to the establishment of this lineage in high-density neighborhoods around Monrovia (Montserrado and Margibi Counties). Approximately 70% of Liberia’s reported cases occurred in this region, and it served as an important source of infections in other parts of the country. Additionally, New Kru Town was one of two primary epicenters of EVD cases (in addition to Foya, Lofa County) during June to early-July 2014, at the beginning of the second wave of Liberian EVD cases ().

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Galvani A.P. Strategies for containing Ebola in West Africa. As a result of demographic transition and internal conflict, Western Africa has become a region characterized by high rates of migration (), and this movement is reflected in the spread of EBOV within Liberia. In the 2008 Liberian census, 54% of the population over the age of 14 reported being internally displaced (), and 22% of the Liberian-born population was enumerated in a county different from that of birth (). This high rate of migration has resulted in the establishment of strong social ties across geographic regions, and the relatively small size of the country (∼111,000 km) makes regular travel between many regions feasible. Reflective of this aspect of Liberian society, we saw widespread movement of EBOV within Liberia, which is likely to have played an important role in the magnitude and longevity of the Liberian portion of the EVD outbreak. Regular migration of infected individuals complicates surveillance and isolation efforts, which are critical for controlling EVD outbreaks ().

Kateh et al., 2015 Kateh F.

Nagbe T.

Kieta A.

Barskey A.

Gasasira A.N.

Driscoll A.

Tucker A.

Christie A.

Karmo B.

Scott C.

et al. Centers for Disease Control and Prevention (CDC)

Rapid response to Ebola outbreaks in remote areas - Liberia, July-November 2014. UNICEF, 2014 UNICEF (2014). UNICEF-Liberia Ebola Virus Outbreak SitReps. www.unicef.org/appeals/files/UNICEF_Liberia_SitRep11_Ebola_Virus_Outbreak_7April2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep19_Ebola_Viral_Disease_23Apr2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep_22_Ebola_Viral_Disease_2_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep23_Ebola_Viral_Disease_13_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep24_Ebola_Viral_Disease_17_June_2014.pdf; www.unicef.org/appeals/files/UNICEF_Liberia_SitRep_Ebola_Viral_Disease_9July2014.pdf. The dominant pathways of EBOV spread within Liberia are broadly consistent with expectations based on the distribution of EVD cases and available data on contact tracing. Our analysis identified two neighboring counties, Montserrado and Margibi, as the primary sources for the spread of EBOV to other Liberian counties. This finding is consistent with epidemiological investigations into EVD clusters in remote Liberian villages. Together, these two counties were identified as the sources for 90% (9/10) of the EVD case clusters for which an index case was successfully identified (). Montserrado and Margibi were also the two worst-affected Liberian counties, respectively, in terms of the number of reported EVD cases. Similarly, Lofa was identified as the third most important source of EBOV within Liberia, which is consistent with Lofa being the third worst-affected county and a major epicenter early in the second wave of Liberian EVD cases (). However, based on our current dataset, Lofa’s contribution as an EBOV source is substantially lower than that of Montserrado and Margibi. This pattern is probably reflective of Lofa’s remote location. Lofa is a likely entry point for EBOV to Liberia due to its proximity to the putative origin of the Western African EVD outbreak and shared borders with Guinea and Sierra Leone. However, Lofa is largely isolated from the highly populated regions of Liberia due to poor connecting roads. Therefore, the contribution of human movement to and from Lofa was likely overshadowed by more frequently traveled routes once EBOV became established in the more densely populated counties of Montserrado and Margibi. Our genomic analysis also identified several connections between counties that are consistent with documented but relatively uncommon movement events ( Figure S1 ), thus illustrating the utility of genomic sequencing to identify and confirm chains of transmission in the absence of good epidemiological data.

Park et al., 2015 Park D.J.

Dudas G.

Wohl S.

Goba A.

Whitmer S.L.

Andersen K.G.

Sealfon R.S.

Ladner J.T.

Kugelman J.R.

Matranga C.B.

et al. Ebola Virus Epidemiology, Transmission, and Evolution during Seven Months in Sierra Leone. Simon-Loriere et al., 2015 Simon-Loriere E.

Faye O.

Faye O.

Koivogui L.

Magassouba N.

Keita S.

Thiberge J.M.

Diancourt L.

Bouchier C.

Vandenbogaert M.

et al. Distinct lineages of Ebola virus in Guinea during the 2014 West African epidemic. WHO, 2015 WHO (2015). Ebola Situation Reports. http://apps.who.int/ebola/ebola-situation-reports. Hoenen et al., 2014 Hoenen T.

Groseth A.

Feldmann F.

Marzi A.

Ebihara H.

Kobinger G.

Günther S.

Feldmann H. Complete genome sequences of three ebola virus isolates from the 2014 outbreak in west Africa. Figure 6 Liberian Sub-Lineages of EBOV Contributed Substantially to the Largest Peak in Guinean EVD Cases Show full caption (A) The number of Guinean EBOV sequences through time colored based on the geographic origin of the evolutionary lineages to which each sequence belongs. WHO, 2015 WHO (2015). Ebola Situation Reports. http://apps.who.int/ebola/ebola-situation-reports. (B) Confirmed and probable EVD cases in Guinea through time, according to the WHO’s patient database (). The EBOV transmission pattern we deduced for Liberia, driven primarily by within-country spread and diversification, is very similar to that described for eastern Sierra Leone during May 2014–January 2015 (), but distinct from the developing picture of the Guinean portion of the outbreak, which appears to have included multiple re-introductions of EBOV from both Liberia and Sierra Leone (). This difference in transmission dynamics may partly explain differences between countries in the distribution of EVD cases over time. The portions of the outbreak in Liberia and Sierra Leone both exhibited a single primary peak in cases, whereas the Guinean portion of the outbreak has been characterized by several distinct peaks of similar magnitude (). Our combined analysis of genomic data from samples collected in four Western African countries demonstrated that occasional importation of EBOV from Liberia likely played a role in the continuation of the Guinean outbreak and the spread of EBOV to Mali. Starting in August 2014, 70% (69/99) of sequences from the eastern half of Guinea and 30% of sequences from the western half of Guinea (23/76) belonged to evolutionary sub-lineages that originated in Liberia ( Figure 6 ). At least five distinct transmission events from Liberia into Guinea are supported by our analysis, and at least three of these led to sustained EBOV transmission within Guinea. One of these imported sub-lineages, LB5, was further transmitted, on two separate occasions, from Guinea to Mali (). We were able to place the ancestors of the three most successful imported lineages within June–July 2014, which is before the official border closings and just before the largest of the peaks in Guinean EVD cases ( Figure 6 ).

Lindblade et al., 2015 Lindblade K.A.

Kateh F.

Nagbe T.K.

Neatherlin J.C.

Pillai S.K.

Attfield K.R.

Dweh E.

Barradas D.T.

Williams S.G.

Blackley D.J.

et al. Decreased Ebola Transmission after Rapid Response to Outbreaks in Remote Areas, Liberia, 2014. It is important to note that international movement of EBOV is only visible in our analysis when this movement resulted in further transmission of the virus. Therefore, we are unable to determine whether the unidirectionality of the international exchange we detected is the result of differences in rates of human movement into/out of Liberia or whether this reflects discrepancies in detecting and controlling newly introduced EBOV transmission chains. The rapid establishment of treatment and isolation facilities was shown to have been effective for interrupting EBOV transmission in several isolated portions of the Liberian outbreak (). A detailed investigation of EBOV control measures throughout Western Africa, in light of the movement patterns highlighted in our analysis, will be illustrative regarding the effectiveness of different management approaches.