Modelling a Supplementary Vaccination Program of Rubella Using the 20122013 Epidemic Data in Japan

Taishi Kayano1,2, Hyojung Lee3,4, Hiroshi Nishiura5,6

  • 1Graduate School of Medicine, Hokkaido University, Kita 15-Jo Nishi 7-Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan. taishi.kaya@med.hokudai.ac.jp.

Insights

Japan

Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Public Health

Background:

  • Japan faced a significant rubella epidemic (2012-2013) with over 12,000 cases and 45 congenital rubella syndrome (CRS) cases.
  • Low vaccination rates in adult males may have contributed to the widespread rubella outbreak.

Purpose of the Study:

  • To inform a supplementary immunization program (SIP) by identifying target male age groups and vaccine quantities.
  • To enhance herd immunity and prevent future rubella epidemics in Japan.

Main Methods:

  • Utilized a mathematical model to analyze 2012-2013 epidemiological data.
  • Reconstructed age- and sex-dependent rubella transmission patterns.
  • Estimated the effective reproduction number (R0) during the epidemic's growth phase.

Main Results:

  • The effective reproduction number was estimated at 1.5 during the exponential growth phase in 2013.
  • Vaccinating males aged 20-49 years with at least 17 million doses is crucial for future epidemic prevention.
  • Even reduced vaccine doses in adult males can significantly decrease rubella and CRS incidence.

Conclusions:

  • A substantial risk of another major rubella epidemic (2018-2019) is predicted, potentially affecting males aged 25-54.
  • Targeted vaccination of adult males is essential for controlling rubella and preventing congenital rubella syndrome (CRS).

Related Concept Videos

Vaccinations01:51

Vaccinations

Overview
51.3K
Cancer Vaccines01:30

Cancer Vaccines

Cancer treatment vaccines are a rapidly evolving field that offers a promising approach to immunotherapy. Unlike traditional vaccines that prevent diseases, cancer treatment vaccines are designed to treat existing cancers by stimulating the immune system to recognize and attack cancer cells.
Cancer vaccines come in two categories: preventive (prophylactic) and treatment (active). Preventive vaccines, such as the Human Papillomavirus (HPV) vaccine, protect against viruses that cause certain...
990
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
253
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
544
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
247
One-Compartment Open Model: Urinary Excretion Data and Determination of k01:11

One-Compartment Open Model: Urinary Excretion Data and Determination of k

The one-compartment open model leverages urinary excretion data to estimate renal clearance, which gauges the kidney's capacity to expel a drug. This method offers several benefits, including directly measuring drug elimination and assessing the kidney's contribution to overall drug clearance. However, this approach has limitations. It assumes sole renal excretion of the drug, which is not true for all drugs. Accurate urinary excretion and plasma drug concentration measurement can also...
621