The effect of weather and simulated climate parameters on three gastro-intestinal infections in the Republic of Ireland

Latest IPCC projections (2022) suggest significantly  increased future incidence of infectious disease due to global warming and shifting climate patterns. Due to increasing global mean temperatures and extreme weather event frequency, assessing the potential impacts of climate change on infectious disease represents a critical challenge for public health authorities. This is particularly significant for environmentally-acquired infections which are directly or indirectly driven by local weather conditions. The current study sought to explore the relationship between antecedent weather and three gastrointestinal infections in the Republic of Ireland, namely cryptosporidiosis, Verotoxigenic E. Coli (VTEC) and campylobacteriosis.

Irreversibly anonymised cases of infection were acquired from the national Computerised Infectious Disease Reporting (CIDR) database. Overall, 4,509 cases of cryptosporidiosis (2007 - 2017), 2,755 cases of VTEC enteritis (2013 - 2017) and 20,274 cases of campylobacteriosis (2011 - 2018) were employed. Individual cases were geographically linked to a Census Small Area (SA).

Weekly seasonal adjustment of developed time series (trend & residuals of seasonally decomposed time-series) were undertaken for both climate and infection variables (incidence rate per 100k population). Climate variables were lagged from 1 to 20 weeks to account for likely delayed associations. A series of Spearman’s correlation matrices were subsequently developed. Infections hotspots were identified and used to construct space-time cluster frequency maps (Boudou et al., 2021, Cleary et al. 2021), with Monte-Carlo simulations used to simulate the effects of weekly mean temperature and rainfall changes on space-time cluster frequency. Analyses were delineated (restricted) based on season and settlement type (i.e., rural, urban, commuter areas).

Spearman’s correlation matrices confirmed the presence of ranked associations between rainfall, temperature and all three infections. Weekly VTEC and campylobacteriosis incidence were positively associated with the non-lagged mean temperature (Rho >0.6). Maximum positive associations were obtained between non-lagged rainfall (mm) for VTEC (Rho=0.68) and campylobacteriosis (Rho= 0.6), while a delayed positive association was found for cryptosporidiosis with a maximum Rho of 0.21 (Week 19). Findings from Monte-Carlo simulation provided strong insights on the direct impacts of temperature and rainfall changes on infection cluster frequency. An increase of 1^oC in weekly temperature was simulated to result in an 25% increase in the number of Small Areas reporting a space-time cluster of campylobacteriosis. Similarly, a 5mm increase in weekly rainfall was shown to increase the number of rural SAs reporting a space-time cluster of cryptosporidiosis by ≈4%.

Study findings leave little doubt as to the significance of climate patterns for all three infections, with all shown to increase (incidence rates and/or cluster occurrence) in concurrence with increasing temperatures and rainfall volumes. Accordingly, there is a pressing need for development of adapted health strategies within the context of predicted climate change (i.e., increased testing/surveillance and treatment capacity, improved risk communication during extreme weather events,…). This result points out the need to promote multidisciplinary researches by including meteorologists, hydrologists and engineer in public health planning strategies.