Clustered transmission hypothesesThese remain estimates bounded by missing infections and incomplete metadata.
A phylogeny estimates relationships among sampled viral genomes under a model. It cannot by itself identify direct transmission or prove who infected whom: unsampled cases, timing, contact records, and uncertainty all matter.
Comparing viral genomes can help infer how sampled infections are related and how a virus changed over time. Genomic evidence becomes more useful when combined with dates, locations, contact histories, and testing information.
02 · FOLLOW THE MECHANISM
How the pieces connect
01
STEP 01
Investigators collect viral samples with patient, date, and location metadata. The 2014 Sierra Leone study sequenced 99 genomes from 78 patients; those samples were informative but not a complete outbreak census.
02
STEP 02
Comparing viral genomes identifies shared and different substitutions within and between hosts. A sequence change is a candidate observation, not proof of a change in virulence, transmissibility, or treatment response.
03
STEP 03
A phylogenetic model estimates ancestry among sampled genomes. It can help compare outbreak-lineage hypotheses, but it does not identify direct person-to-person contacts on its own.
04
STEP 04
Dates, locations, case investigations, and contact histories provide independent constraints. Joint genomic and epidemiological analyses can support transmission clusters while retaining uncertainty.
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STEP 05
In its early-outbreak sample, Gire and colleagues inferred a lineage crossing from Guinea into Sierra Leone and sustained human transmission, with no evidence of additional zoonotic introductions in the data they analyzed.
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STEP 06
That conclusion is bounded by sampling, missing infections, metadata, and model assumptions. An unsampled event cannot be ruled out merely because it is absent from the sequence set.
Each biological link has its own source trail and a qualification describing the context in which it applies.
Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak samplingOrthoebolavirus zairense (Ebola virus lineage in the outbreak dataset)99 viral genomes sampled from 78 patients in Sierra Leone in the Gire et al. studySierra Leone; lineage inference also considered Guinea2014 outbreak; early epidemic weeks in the Gire et al. datasetEbola DiseaseNCBI Taxonomy 3052462
Study scopeSequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment.
Sequence Data & VariationThe study sample and the variation actually observed in those genomes.2 claims
Genomicsused to characterize 99 Ebola virus genomes from 78 patients in Sierra Leone, sequenced to approximately 2,000× coverage
The 2014 genomic-surveillance study sequenced 99 Ebola virus genomes from 78 patients in Sierra Leone and analyzed variation within and between hosts.
Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak samplingOrthoebolavirus zairense (Ebola virus lineage in the outbreak dataset)99 viral genomes sampled from 78 patients in Sierra Leone in the Gire et al. studySierra Leone; lineage inference also considered Guinea2014 outbreak; early epidemic weeks in the Gire et al. datasetEbola DiseaseNCBI Taxonomy 3052462
Study scopeSequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment.
Context and qualificationThe sample is a subset of cases, not a complete census of infections. Sequencing depth does not remove biases caused by missing cases, collection timing, or which infections could be sampled.
Orthoebolavirus zairenseshowed Rapidly accumulating interhost and intrahost sequence variation in sampled 2014 outbreak genomes
The sampled genomes showed both between-host and within-host genetic variation during the early outbreak period.
Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak samplingOrthoebolavirus zairense (Ebola virus lineage in the outbreak dataset)99 viral genomes sampled from 78 patients in Sierra Leone in the Gire et al. studySierra Leone; lineage inference also considered Guinea2014 outbreak; early epidemic weeks in the Gire et al. datasetEbola DiseaseNCBI Taxonomy 3052462
Study scopeSequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment.
Context and qualificationA sequence difference is not automatically a functional change: effects on viral fitness, transmissibility, diagnostics, or disease severity require separate experimental or epidemiological evidence.
Phylogeny Meets EpidemiologyUse sequence, time, place, and contact evidence to evaluate outbreak histories.3 claims
Genomicscan estimate Evolutionary relationships among sampled viral genomes under a phylogenetic model
Shared substitutions and genome-wide patterns can be used to estimate how sampled Ebola viruses are related and to evaluate outbreak-lineage hypotheses.
Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak samplingOrthoebolavirus zairense (Ebola virus lineage in the outbreak dataset)99 viral genomes sampled from 78 patients in Sierra Leone in the Gire et al. studySierra Leone; lineage inference also considered Guinea2014 outbreak; early epidemic weeks in the Gire et al. datasetEbola DiseaseNCBI Taxonomy 3052462
Study scopeSequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment.
Context and qualificationA phylogeny describes inferred ancestry among sampled sequences; it is not a person-to-person contact map and does not establish direct transmission by itself.
Combining viral sequences with dates, locations, and epidemiological information can support estimates of clustered transmission during an outbreak.
Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak samplingOrthoebolavirus zairense (Ebola virus lineage in the outbreak dataset)99 viral genomes sampled from 78 patients in Sierra Leone in the Gire et al. studySierra Leone; lineage inference also considered Guinea2014 outbreak; early epidemic weeks in the Gire et al. datasetEbola DiseaseNCBI Taxonomy 3052462
Study scopeSequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment.
Context and qualificationThe transmission history remains model-based and uncertain where cases are unobserved or metadata are incomplete; multiple histories can fit similar sequence data.
Orthoebolavirus zairenseoutbreak origin inference limited by Sampling coverage, collection time, viral diversity, epidemiological metadata, and inference assumptions
The study inferred cross-border lineage movement and sustained transmission from the sampled genomes, while finding no evidence for additional zoonotic introductions in the analyzed early-outbreak dataset.
Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak samplingOrthoebolavirus zairense (Ebola virus lineage in the outbreak dataset)99 viral genomes sampled from 78 patients in Sierra Leone in the Gire et al. studySierra Leone; lineage inference also considered Guinea2014 outbreak; early epidemic weeks in the Gire et al. datasetEbola DiseaseNCBI Taxonomy 3052462
Study scopeSequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment.
Context and qualificationAbsence of evidence in the sampled dataset is not proof that an unsampled event never occurred. The published inference is bounded by the study period, geographic sampling, and available cases.
A newly observed viral sequence change alone does not show that the virus has become more transmissible, more severe, or more resistant to an intervention.
Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak samplingOrthoebolavirus zairense (Ebola virus lineage in the outbreak dataset)99 viral genomes sampled from 78 patients in Sierra Leone in the Gire et al. studySierra Leone; lineage inference also considered Guinea2014 outbreak; early epidemic weeks in the Gire et al. datasetEbola DiseaseNCBI Taxonomy 3052462
Study scopeSequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment.
Context and qualificationThose conclusions need functional studies and/or appropriately designed epidemiological evidence; sequence surveillance identifies candidates for follow-up, not effects by itself.
Shared and different sequence changes help estimate how sampled viruses are related and can support reconstruction of outbreak history.
2Why are genomes not enough to prove direct transmission between two people?
Closely related genomes can fit several transmission histories. Timing, location, contact, and sampling evidence are also needed.
3What does “no evidence of another zoonotic introduction” mean in the 2014 study?
The sampled genomes and study model did not support an additional introduction in the analyzed dataset. It is a bounded inference, not proof that an unsampled event was impossible.
4Does a new mutation show that the virus became more dangerous?
No. Sequence surveillance finds changes; functional experiments or epidemiological analyses are needed to test effects on transmission, severity, or intervention response.