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Estimating Dengue Transmission Intensity in China Using Catalytic Models Based on Serological Data.

Ning LiHaidong LiZhengji ChenHuan XiongZhibo LiTao WeiWei LiuXu-Sheng Zhang
Published in: Tropical medicine and infectious disease (2023)
In recent decades, the global incidence of dengue has risen sharply, with more than 75% of infected people showing mild or no symptoms. Since the year 2000, dengue in China has spread quickly. At this stage, there is an urgent need to fully understand its transmission intensity and spread in China. Serological data provide reliable evidence for symptomatic and recessive infections. Through a literature search, we included 23 studies that collected age-specific serological dengue data released from 1980 to 2021 in China. Fitting four catalytic models to these data, we distinguished the transmission mechanisms by deviation information criterion and estimated force of infection and basic reproduction number ( R 0 ), important parameters for quantifying transmission intensity. We found that transmission intensity varies over age in most of the study populations, and attenuation of antibody protection is identified in some study populations; the R 0 of dengue in China is between 1.04-2.33. Due to the scarceness of the data, the temporal trend cannot be identified, but data shows that transmission intensity weakened from coastal to inland areas and from southern to northern areas in China if assuming it remained temporally steady during the study period. The results should be useful for the effective control of dengue in China.
Keyphrases
  • zika virus
  • dengue virus
  • electronic health record
  • aedes aegypti
  • big data
  • systematic review
  • healthcare
  • heavy metals
  • machine learning
  • autism spectrum disorder
  • social media
  • single molecule
  • human health