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Capturing Low Probability of Disease Dynamics in Coupled Populations

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Title: Capturing Low Probability of Disease Dynamics in Coupled Populations
Authors: Burton, Jackson
Summary: Researchers using mathematical models have made significant contributions to the field of epidemiology in recent years. These models have both explanatory and predicative power to describe disease dynamics. More recent work has considered multi-population models and the effects vaccinations have on the population as a whole. One such example can be seen in the West African country of Cameroon, which has two distinct patterns of measles outbreaks. By considering Cameroon as two subpopulations, a deterministic model is developed that includes the effect of vaccinations. Stability analysis is then performed on the model over a range of coupling and vaccination rates to establish thresholds between disease absence and persistence. Stochastic methods are then used to capture low probability events near these thresholds. We identified significant differences in vaccination rates predicted deterministically for disease absence versus vaccination rates that are effective at inducing disease absence.
URL: https://digitalcommons.montclair.edu/etd/787
Database: OpenDissertations
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DbLabel: OpenDissertations
An: ddu.oai.digitalcommons.montclair.edu.etd.1788
AccessLevel: 6
PubType: Dissertation/ Thesis
PubTypeId: dissertation
PreciseRelevancyScore: 0
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  Data: Researchers using mathematical models have made significant contributions to the field of epidemiology in recent years. These models have both explanatory and predicative power to describe disease dynamics. More recent work has considered multi-population models and the effects vaccinations have on the population as a whole. One such example can be seen in the West African country of Cameroon, which has two distinct patterns of measles outbreaks. By considering Cameroon as two subpopulations, a deterministic model is developed that includes the effect of vaccinations. Stability analysis is then performed on the model over a range of coupling and vaccination rates to establish thresholds between disease absence and persistence. Stochastic methods are then used to capture low probability events near these thresholds. We identified significant differences in vaccination rates predicted deterministically for disease absence versus vaccination rates that are effective at inducing disease absence.
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RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Mathematics
        Type: general
      – SubjectFull: Communicable diseases--Epidemiology--Mathematical models, Communicable diseases--Cameroon
        Type: general
    Titles:
      – TitleFull: Capturing Low Probability of Disease Dynamics in Coupled Populations
        Type: main
  BibRelationships:
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      – PersonEntity:
          Name:
            NameFull: Burton, Jackson
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          Dates:
            – D: 01
              M: 05
              Type: published
              Y: 2011
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