Next Article in Journal
The Effects of Forest Therapy on Coping with Chronic Widespread Pain: Physiological and Psychological Differences between Participants in a Forest Therapy Program and a Control Group
Previous Article in Journal
The Use of Carbonaceous Particle Exposure Metrics in Health Impact Calculations
Article Menu

Export Article

Open AccessArticle
Int. J. Environ. Res. Public Health 2016, 13(3), 253; doi:10.3390/ijerph13030253

Modeling Heterogeneity in Direct Infectious Disease Transmission in a Compartmental Model

1
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2
University of the Chinese Academy of Sciences, Beijing 100049, China
3
Key Laboratory of Surveillance and Early-Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China
4
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
5
University Corporation for Atmospheric Research/Visiting Scientist Programs, 3090 Center Green Drive, Boulder, CO 80301, USA
6
State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Science, Beijing 100190, China
*
Author to whom correspondence should be addressed.
Academic Editors: Igor Burstyn and Gheorghe Luta
Received: 7 June 2015 / Revised: 13 February 2016 / Accepted: 16 February 2016 / Published: 24 February 2016
View Full-Text   |   Download PDF [1036 KB, uploaded 24 February 2016]   |  

Abstract

Mathematical models have been used to understand the transmission dynamics of infectious diseases and to assess the impact of intervention strategies. Traditional mathematical models usually assume a homogeneous mixing in the population, which is rarely the case in reality. Here, we construct a new transmission function by using as the probability density function a negative binomial distribution, and we develop a compartmental model using it to model the heterogeneity of contact rates in the population. We explore the transmission dynamics of the developed model using numerical simulations with different parameter settings, which characterize different levels of heterogeneity. The results show that when the reproductive number, R0, is larger than one, a low level of heterogeneity results in dynamics similar to those predicted by the homogeneous mixing model. As the level of heterogeneity increases, the dynamics become more different. As a test case, we calibrated the model with the case incidence data for severe acute respiratory syndrome (SARS) in Beijing in 2003, and the estimated parameters demonstrated the effectiveness of the control measures taken during that period. View Full-Text
Keywords: infectious diseases; mathematical models; homogeneous mixing; heterogeneity; negative binomial distribution infectious diseases; mathematical models; homogeneous mixing; heterogeneity; negative binomial distribution
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Kong, L.; Wang, J.; Han, W.; Cao, Z. Modeling Heterogeneity in Direct Infectious Disease Transmission in a Compartmental Model. Int. J. Environ. Res. Public Health 2016, 13, 253.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Int. J. Environ. Res. Public Health EISSN 1660-4601 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top