Climate variability, weather and enteric disease incidence in New Zealand: Time series analysis

Aparna Lal, Takayoshi Ikeda, Nigel French, Michael G. Baker, Simon Hales

Research output: Contribution to journalArticlepeer-review

60 Citations (Scopus)

Abstract

Background: Evaluating the influence of climate variability on enteric disease incidence may improve our ability to predict how climate change may affect these diseases. Objectives: To examine the associations between regional climate variability and enteric disease incidence in New Zealand. Methods: Associations between monthly climate and enteric diseases (campylobacteriosis, salmonellosis, cryptosporidiosis, giardiasis) were investigated using Seasonal Auto Regressive Integrated Moving Average (SARIMA) models. Results: No climatic factors were significantly associated with campylobacteriosis and giardiasis, with similar predictive power for univariate and multivariate models. Cryptosporidiosis was positively associated with average temperature of the previous month (β= 0.130, SE = 0.060, p<0.01) and inversely related to the Southern Oscillation Index (SOI) two months previously (β = -0.008, SE = 0.004, p<0.05). By contrast, salmonellosis was positively associated with temperature (β = 0.110, SE = 0.020, p,0.001) of the current month and SOI of the current (β = 0.005, SE = 0.002, p<0.050) and previous month (β = 0.005, SE = 0.002, p<0.05). Forecasting accuracy of the multivariate models for cryptosporidiosis and salmonellosis were significantly higher. Conclusions: Although spatial heterogeneity in the observed patterns could not be assessed, these results suggest that temporally lagged relationships between climate variables and national communicable disease incidence data can contribute to disease prediction models and early warning systems.

Original languageEnglish
Article numbere83484
JournalPLoS ONE
Volume8
Issue number12
DOIs
Publication statusPublished - 23 Dec 2013
Externally publishedYes

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