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    "title": "Reading an Ebola Outbreak Through Genomes"
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    "exposureContext": "Sequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment."
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      "statement": "Combining viral sequences with dates, locations, and epidemiological information can support estimates of clustered transmission during an outbreak.",
      "qualifier": "The transmission history remains model-based and uncertain where cases are unobserved or metadata are incomplete; multiple histories can fit similar sequence data.",
      "evidenceKind": "primary_study",
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        "scope": "Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak sampling",
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      "qualifier": "Absence 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.",
      "evidenceKind": "primary_study",
      "context": {
        "scope": "Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak sampling",
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  "limitation": "These claims concern the sampled 2014 Sierra Leone outbreak genomes. Phylogenies and transmission models are inferences bounded by missing infections, metadata, sampling times, within-host diversity, and model assumptions.",
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    "caseStudy": {
      "slug": "ebola-outbreak-genomics",
      "title": "Reading an Ebola Outbreak Through Genomes",
      "area": "Viruses · Genomics · Epidemiology",
      "question": "What can viral genome differences tell us about an outbreak—and what can’t they tell us alone?",
      "overview": "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.",
      "mechanism": [
        "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.",
        "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.",
        "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.",
        "Dates, locations, case investigations, and contact histories provide independent constraints. Joint genomic and epidemiological analyses can support transmission clusters while retaining uncertainty.",
        "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.",
        "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."
      ],
      "evidence": "This case teaches genomic epidemiology as inference from sampled genomes plus temporal, geographic, and contact evidence. The published lineage reconstruction is bounded to the early 2014 dataset; a phylogeny is not a direct-contact map, and a sequence substitution alone does not establish a phenotype.",
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          "question": "Why compare viral genomes from multiple cases?",
          "answer": "Shared and different sequence changes help estimate how sampled viruses are related and can support reconstruction of outbreak history."
        },
        {
          "question": "Why are genomes not enough to prove direct transmission between two people?",
          "answer": "Closely related genomes can fit several transmission histories. Timing, location, contact, and sampling evidence are also needed."
        },
        {
          "question": "What does “no evidence of another zoonotic introduction” mean in the 2014 study?",
          "answer": "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."
        },
        {
          "question": "Does a new mutation show that the virus became more dangerous?",
          "answer": "No. Sequence surveillance finds changes; functional experiments or epidemiological analyses are needed to test effects on transmission, severity, or intervention response."
        }
      ]
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      "title": "Genomes help reconstruct an outbreak",
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      "note": "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.",
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          "context": {
            "scope": "Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak sampling",
            "organism": "Orthoebolavirus zairense (Ebola virus lineage in the outbreak dataset)",
            "taxonId": "3052462",
            "conditionId": "disease-ebola-virus-disease",
            "population": "99 viral genomes sampled from 78 patients in Sierra Leone in the Gire et al. study",
            "location": "Sierra Leone; lineage inference also considered Guinea",
            "timePeriod": "2014 outbreak; early epidemic weeks in the Gire et al. dataset",
            "exposureContext": "Sequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment."
          },
          "references": [
            {
              "referenceId": "ebola-genomic-surveillance",
              "relation": "supports",
              "sourceRecordId": "PMID:25214632",
              "sourceVersion": "Published 2014"
            }
          ]
        },
        {
          "id": "ebola-phylogeny-estimates-sampled-ancestry",
          "version": 1,
          "subjectId": "concept-genomics",
          "predicate": "CAN_ESTIMATE",
          "objectValue": "Evolutionary relationships among sampled viral genomes under a phylogenetic model",
          "statement": "Shared substitutions and genome-wide patterns can be used to estimate how sampled Ebola viruses are related and to evaluate outbreak-lineage hypotheses.",
          "qualifier": "A phylogeny describes inferred ancestry among sampled sequences; it is not a person-to-person contact map and does not establish direct transmission by itself.",
          "evidenceKind": "primary_study",
          "context": {
            "scope": "Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak sampling",
            "organism": "Orthoebolavirus zairense (Ebola virus lineage in the outbreak dataset)",
            "taxonId": "3052462",
            "conditionId": "disease-ebola-virus-disease",
            "population": "99 viral genomes sampled from 78 patients in Sierra Leone in the Gire et al. study",
            "location": "Sierra Leone; lineage inference also considered Guinea",
            "timePeriod": "2014 outbreak; early epidemic weeks in the Gire et al. dataset",
            "exposureContext": "Sequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment."
          },
          "references": [
            {
              "referenceId": "ebola-genomic-surveillance",
              "relation": "supports",
              "sourceRecordId": "PMID:25214632",
              "sourceVersion": "Published 2014"
            },
            {
              "referenceId": "ebola-genomic-epidemiology",
              "relation": "qualifies",
              "sourceRecordId": "PMID:25516185",
              "sourceVersion": "Published 2015"
            }
          ]
        },
        {
          "id": "ebola-genomics-and-epidemiology-reconstruct-clusters",
          "version": 1,
          "subjectId": "concept-epidemiology",
          "predicate": "CAN_INTERPRET_WITH",
          "objectId": "concept-genomics",
          "statement": "Combining viral sequences with dates, locations, and epidemiological information can support estimates of clustered transmission during an outbreak.",
          "qualifier": "The transmission history remains model-based and uncertain where cases are unobserved or metadata are incomplete; multiple histories can fit similar sequence data.",
          "evidenceKind": "primary_study",
          "context": {
            "scope": "Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak sampling",
            "organism": "Orthoebolavirus zairense (Ebola virus lineage in the outbreak dataset)",
            "taxonId": "3052462",
            "conditionId": "disease-ebola-virus-disease",
            "population": "99 viral genomes sampled from 78 patients in Sierra Leone in the Gire et al. study",
            "location": "Sierra Leone; lineage inference also considered Guinea",
            "timePeriod": "2014 outbreak; early epidemic weeks in the Gire et al. dataset",
            "exposureContext": "Sequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment."
          },
          "references": [
            {
              "referenceId": "ebola-genomic-epidemiology",
              "relation": "supports",
              "sourceRecordId": "PMID:25516185; PMCID:PMC4375398",
              "sourceVersion": "Published 2015; Sierra Leone 2014 data"
            }
          ]
        },
        {
          "id": "ebola-lineage-inference-is-sample-bounded",
          "version": 1,
          "subjectId": "taxon-orthoebolavirus-zairense",
          "predicate": "OUTBREAK_ORIGIN_INFERENCE_LIMITED_BY",
          "objectValue": "Sampling coverage, collection time, viral diversity, epidemiological metadata, and inference assumptions",
          "statement": "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.",
          "qualifier": "Absence 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.",
          "evidenceKind": "primary_study",
          "context": {
            "scope": "Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak sampling",
            "organism": "Orthoebolavirus zairense (Ebola virus lineage in the outbreak dataset)",
            "taxonId": "3052462",
            "conditionId": "disease-ebola-virus-disease",
            "population": "99 viral genomes sampled from 78 patients in Sierra Leone in the Gire et al. study",
            "location": "Sierra Leone; lineage inference also considered Guinea",
            "timePeriod": "2014 outbreak; early epidemic weeks in the Gire et al. dataset",
            "exposureContext": "Sequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment."
          },
          "references": [
            {
              "referenceId": "ebola-genomic-surveillance",
              "relation": "supports",
              "sourceRecordId": "PMID:25214632",
              "sourceVersion": "Published 2014"
            },
            {
              "referenceId": "ebola-genomic-epidemiology",
              "relation": "qualifies",
              "sourceRecordId": "PMID:25516185",
              "sourceVersion": "Published 2015"
            }
          ]
        },
        {
          "id": "ebola-sequence-change-does-not-prove-phenotype",
          "version": 1,
          "subjectId": "concept-genomics",
          "predicate": "DOES_NOT_ALONE_ESTABLISH",
          "objectId": "disease-ebola-virus-disease",
          "statement": "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.",
          "qualifier": "Those conclusions need functional studies and/or appropriately designed epidemiological evidence; sequence surveillance identifies candidates for follow-up, not effects by itself.",
          "evidenceKind": "mechanistic_review",
          "context": {
            "scope": "Orthoebolavirus zairense genomic epidemiology; Sierra Leone, early 2014 outbreak sampling",
            "organism": "Orthoebolavirus zairense (Ebola virus lineage in the outbreak dataset)",
            "taxonId": "3052462",
            "conditionId": "disease-ebola-virus-disease",
            "population": "99 viral genomes sampled from 78 patients in Sierra Leone in the Gire et al. study",
            "location": "Sierra Leone; lineage inference also considered Guinea",
            "timePeriod": "2014 outbreak; early epidemic weeks in the Gire et al. dataset",
            "exposureContext": "Sequence inference is limited to sampled infections and must be integrated with dates, locations, contact records, and case ascertainment."
          },
          "references": [
            {
              "referenceId": "ebola-genomic-surveillance",
              "relation": "qualifies",
              "sourceRecordId": "PMID:25214632",
              "sourceVersion": "Published 2014"
            },
            {
              "referenceId": "cdc-ebola",
              "relation": "context",
              "sourceRecordId": "CDC: Ebola Disease Basics",
              "sourceVersion": "Page version not recorded in this snapshot"
            }
          ]
        }
      ],
      "limitation": "These claims concern the sampled 2014 Sierra Leone outbreak genomes. Phylogenies and transmission models are inferences bounded by missing infections, metadata, sampling times, within-host diversity, and model assumptions."
    }
  }
}