[How Did the Dengue Fever Outbreak Progress in Yoyogi Park, Tokyo, in 2014?-Evaluation Based on a Mathematical Model]

Nihon Eiseigaku Zasshi. 2017;72(1):55-65. doi: 10.1265/jjh.72.55.
[Article in Japanese]

Abstract

Objectives: In the summer of 2014, an outbreak of autochthonous dengue fever occurred in Yoyogi Park and its vicinity, Tokyo, Japan. In this study, we investigated how the dengue fever outbreak progressed in Yoyogi Park using a mathematical model.

Methods: This study was limited to the transmission of the dengue virus in Yoyogi Park and its vicinity. We estimated the distributions of the intrinsic incubation period and infection dates on the basis of epidemiological information on the dengue outbreak in 2014. We searched for an assumption that satisfactorily explains the outbreak in 2014 using rough estimates of secondary and tertiary infection cases. We constructed a mathematical model for the transmission of the dengue virus between humans and Aedes albopictus.

Results: We carried out 1,000-trial stochastic simulations for all combinations of three kinds of assumption about Ae. albopictus and asymptomatic infection with each of three levels. Simulation results showed that the scale of the outbreak was markedly affected by the daily survival rate of Ae. albopictus. The outbreak involved a small number of secondary infection cases, reached a peak at tertiary infection, and transformed to termination at the fourth infection. Under some assumptions, the daily progress of onset cases was within a range between the 1st-3rd quartiles of 1,000 trials for 87% of dates and within a range between the minimum and maximum for all dates.

Conclusions: It is important to execute plans to detect asymptomatic cases and reduce the survival rate of Ae. albopictus to prevent the spread of tertiary infections unless an outbreak is suppressed at the secondary infection stage.

MeSH terms

  • Aedes / virology*
  • Animals
  • Dengue / epidemiology*
  • Dengue / transmission*
  • Dengue / virology
  • Dengue Virus* / physiology
  • Disease Outbreaks*
  • Humans
  • Models, Theoretical*
  • Time Factors
  • Tokyo / epidemiology
  • Virus Latency