Spatial and temporal variation in the association between temperature and salmonellosis in NZ

Abstract

Abstract Objective: Modelling the relationship between weather, climate and infectious diseases can help identify high‐risk periods and provide understanding of the determinants of longer‐term trends. We provide a detailed examination of the non‐linear and delayed association between temperature and salmonellosis in three New Zealand cities (Auckland, Wellington and Christchurch). Methods: Salmonella notifications were geocoded to the city of residence for the reported case. City‐specific associations between weekly maximum temperature and the onset date for reported salmonella infections (1997–2007) were modelled using non‐linear distributed lag models, while controlling for season and long‐term trends. Results: Relatively high temperatures were positively associated with infection risk in Auckland (n=3,073) and Christchurch (n=880), although the former showed evidence of a more immediate relationship with exposure to high temperatures. There was no significant association between temperature and salmonellosis risk in Wellington. Conclusions: Projected increases in temperature with climate change may have localised health impacts, suggesting that preventative measures will need to be region‐specific. This evidence contributes to the increasing concern over the public health impacts of climate change.

Keywords

• temperature
• salomonellosis
• non‐linear
• lagged