BMC Infectious Diseases (Mar 2018)

Factors associated with human West Nile virus infection in Ontario: a generalized linear mixed modelling approach

  • Shruti Mallya,
  • Beate Sander,
  • Marie-Hélène Roy-Gagnon,
  • Monica Taljaard,
  • Ann Jolly,
  • Manisha A. Kulkarni

DOI
https://doi.org/10.1186/s12879-018-3052-6
Journal volume & issue
Vol. 18, no. 1
pp. 1 – 9

Abstract

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Abstract Background West Nile Virus (WNV) is a mosquito-borne pathogen that has become established in North America. Risk for human infection varies geographically in accordance with climate and population factors. Though often asymptomatic, human WNV infection can cause febrile illness or, rarely, neurologic disease. WNV has become a public health concern in Canada since its introduction in 2001. Methods To identify predictors of human WNV incidence at the public health unit (PHU) level in Ontario, Canada, we combined data on environmental and population characteristics of PHUs with historical mosquito and human surveillance records from 2002 to 2013. We examined the associations between annual WNV incidence and monthly climate indices (e.g. minimum and maximum temperature, average precipitation), land cover (e.g. deciduous forest, water), population structure (e.g. age and sex composition) and the annual percentage of WNV-positive mosquito pools from 2002 to 2013. We then developed a generalized linear mixed model with a Poisson distribution adjusting for spatial autocorrelation and repeat measures. Further to this, to examine potential ‘early season’ predictors of WNV incidence in a given year, we developed a model based on winter and spring monthly climate indices. Results Several climate indices, including mean minimum temperature (o C) in February (RR = 1.58, CI: [1.42, 1.75]), and the annual percentage of WNV-positive mosquito pools (RR = 1.07, CI: [1.04, 1.11]) were significantly associated with human WNV incidence at the PHU level. Higher winter minimum temperatures were also strongly associated with annual WNV incidence in the ‘early season’ model (e.g. February minimum temperature (RR = 1.91, CI: [1.73, 2.12]). Conclusions Our study demonstrates that early season temperature and precipitation indices, in addition to the percentage of WNV-positive mosquito pools in a given area, may assist in predicting the likelihood of a more severe human WNV season in southern regions of Ontario, where WNV epidemics occur sporadically.

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