Transoceanic pathogen transfer in the age of sail and steam
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View abstract on PubMed
Summary
This summary is machine-generated.Mathematical modeling quantifies historical risks of shipborne pathogen introduction. Factors like journey time, ship size, and increased travel with steamships and large populations significantly amplified global disease spread.
Area Of Science
- Historical epidemiology
- Mathematical modeling of disease transmission
- Global health history
Background
- Transoceanic travel following 1492 facilitated unprecedented global pathogen circulation.
- Understanding the dynamics of historical disease spread is crucial for public health.
Purpose Of The Study
- To quantify the historical risk of shipborne pathogen introduction using mathematical modeling.
- To identify key factors influencing the spread of diseases during transoceanic voyages.
- To estimate introduction risks across various historical journey times and ship sizes.
Main Methods
- Utilized mathematical modeling to assess pathogen introduction risk.
- Incorporated variables such as journey duration, ship size, population susceptibility, transmission intensity, density dependence, and pathogen characteristics.
- Contextualized findings with historical port arrival data (San Francisco, 1850-1852) and significant voyages (1492-1918).
Main Results
- Provided numerical estimates for pathogen introduction risk based on historical journey times and ship populations.
- Demonstrated that steam travel significantly increased the risk of transoceanic pathogen circulation.
- Showed that frequent, large-scale population movements via shipping substantially elevated disease transmission risks.
Conclusions
- Historical travel, particularly with advancements like steamships and increased shipping volumes, dramatically heightened the risk of global pathogen circulation.
- Mathematical modeling offers valuable insights into quantifying historical disease introduction pathways.
- Findings underscore the impact of transportation technology and human mobility on infectious disease dynamics.
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