Validation of the gravity model in predicting the global spread of influenza

Int J Environ Res Public Health. 2011 Aug;8(8):3134-43. doi: 10.3390/ijerph8083134. Epub 2011 Jul 25.

Abstract

The gravity model is often used in predicting the spread of influenza. We use the data of influenza A (H1N1) to check the model's performance and validation, in order to determine the scope of its application. In this article, we proposed to model the pattern of global spread of the virus via a few important socio-economic indicators. We applied the epidemic gravity model for modelling the virus spread globally through the estimation of parameters of a generalized linear model. We compiled the daily confirmed cases of influenza A (H1N1) in each country as reported to the WHO and each state in the USA, and established the model to describe the relationship between the confirmed cases and socio-economic factors such as population size, per capita gross domestic production (GDP), and the distance between the countries/states and the country where the first confirmed case was reported (i.e., Mexico). The covariates we selected for the model were all statistically significantly associated with the global spread of influenza A (H1N1). However, within the USA, the distance and GDP were not significantly associated with the number of confirmed cases. The combination of the gravity model and generalized linear model provided a quick assessment of pandemic spread globally. The gravity model is valid if the spread period is long enough for estimating the model parameters. Meanwhile, the distance between donor and recipient communities has a good gradient. Besides, the spread should be at the early stage if a single source is taking into account.

Keywords: generalized linear model; gravity model; infectious disease; influenza A (H1N1); viral spread.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Computer Simulation
  • Humans
  • Influenza A Virus, H1N1 Subtype / physiology*
  • Influenza, Human / epidemiology*
  • Influenza, Human / transmission*
  • Influenza, Human / virology
  • Linear Models
  • Mexico / epidemiology
  • Models, Biological*
  • Pandemics*
  • Socioeconomic Factors
  • Time Factors
  • United States / epidemiology