title: Forecasting high-priority infectious disease surveillance regions: a socioeconomic model.
abstract: BACKGROUND
  Few researchers have assessed the relationships between socioeconomic inequality and infectious disease outbreaks at the population level globally. We use a socioeconomic model to forecast national annual rates of infectious disease outbreaks.
  
  
  METHODS
  We constructed a multivariate mixed-effects Poisson model of the number of times a given country was the origin of an outbreak in a given year. The dataset included 389 outbreaks of international concern reported in the World Health Organization's Disease Outbreak News from 1996 to 2008. The initial full model included 9 socioeconomic variables related to education, poverty, population health, urbanization, health infrastructure, gender equality, communication, transportation, and democracy, and 1 composite index. Population, latitude, and elevation were included as potential confounders. The initial model was pared down to a final model by a backwards elimination procedure. The dependent and independent variables were lagged by 2 years to allow for forecasting future rates.
  
  
  RESULTS
  Among the socioeconomic variables tested, the final model included child measles immunization rate and telephone line density. The Democratic Republic of Congo, China, and Brazil were predicted to be at the highest risk for outbreaks in 2010, and Colombia and Indonesia were predicted to have the highest percentage of increase in their risk compared to their average over 1996-2008.
  
  
  CONCLUSIONS
  Understanding socioeconomic factors could help improve the understanding of outbreak risk. The inclusion of the measles immunization variable suggests that there is a fundamental basis in ensuring adequate public health capacity. Increased vigilance and expanding public health capacity should be prioritized in the projected high-risk regions.
authors.affiliation: Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology, Boston, USA.
authors.forename: Emily H
authors.initials: EH
authors.lastname: Chan
authors.forename: David A
authors.initials: DA
authors.lastname: Scales
authors.forename: Timothy F
authors.initials: TF
authors.lastname: Brewer
authors.forename: Lawrence C
authors.initials: LC
authors.lastname: Madoff
authors.forename: Marjorie P
authors.initials: MP
authors.lastname: Pollack
authors.forename: Anne G
authors.initials: AG
authors.lastname: Hoen
authors.forename: Tenzin
authors.initials: T
authors.lastname: Choden
authors.forename: John S
authors.initials: JS
authors.lastname: Brownstein
mesh_terms: D003141:Communicable Diseases / Q000453:epidemiology*; D004196:Disease Outbreaks / Q000517:prevention & control / Q000706:statistics & numerical data*; D004522:Educational Status; D062665:Epidemiological Monitoring; D005260:Female; D005544:Forecasting; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D011203:Poverty; D012959:Socioeconomic Factors