The impact of temperature on non-typhoidal Salmonella and Campylobacter infections: an updated systematic review and meta-analysis of epidemiological evidence

Abstract

Background: As temperatures rise, the transmission and incidence of enteric infections such as those caused by Salmonella and Campylobacter increase. This study aimed to review and synthesise the available evidence on the effects of exposure to ambient temperatures on non-typhoidal Salmonella and Campylobacter infections.

Methods: A systematic search was conducted for peer-reviewed epidemiological studies published between January 1990 and March 2024, in PubMed, Scopus, Embase, and Web of Science databases. Original observational studies using ecological time-series, case-crossover or case-series study designs reporting the association between ambient temperature and non-typhoidal Salmonella and Campylobacter infections in the general population were included. A random-effects meta-analysis was performed to pool the relative risks (RRs) per 1 °C temperature increase, and further meta regression, and subgroup analyses by climate zone, temperature metrics, temporal resolution, lag period, and continent were conducted. The Navigation Guide systematic review methodology framework was used to assess the quality and strength of evidence. The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO).

Findings: Out of 3472 results, 44 studies were included in this systematic review encompassing over one million cases each of Salmonella and Campylobacter infections. Geographically, the 44 studies covered 27 countries across five continents and most of the studies were from high income countries. The meta-analysis incorporated 23 Salmonella studies (65 effect estimates) and 15 Campylobacter studies (24 effect estimates). For each 1 °C rise in temperature, the risk of non-typhoidal Salmonella and Campylobacter infections increased by 5% (RR: 1.05, 95% CI: 1.04-1.06), and 5% (RR: 1.05, 95% CI: 1.04-1.07%), respectively, with varying risks across different climate zones. The overall evidence was evaluated as being of "high" quality, and the strength of the evidence was determined to be "sufficient" for both infections.

Interpretation: These findings emphasise the relationship between temperature and the incidence of Salmonella and Campylobacter infections. It is crucial to exercise caution when generalising these findings, given the limited number of studies conducted in low and middle-income countries. Nevertheless, the results demonstrate the importance of implementing focused interventions and adaptive measures, such as the establishment of localised early warning systems and preventive strategies that account for climatic fluctuations. Furthermore, our research emphasises the ongoing need for surveillance and research efforts to monitor and understand the changing dynamics of temperature-related enteric infections in the context of climate change.

Funding: Australian Research Council Discovery Projects grant (ARC DP200102571) Program.

Keywords: Campylobacter; Climate change; Enteric infections; Meta-analysis; Salmonella; Temperature.

Fig. 1

PRISMA flow diagram for literature search and study selection process of the systematic review and meta-analysis.

Fig. 2

Location of studies based on Köppen-Geiger climate zone classification across continents. Details for Köppen-Geiger climate zone abbreviations are described in the Supplementary material (SM-pp. 23).

Fig. 3

Percentage distribution of overall risk of bias ratings within each bias domain for all included studies. (a) non-typhoidal Salmonella infection studies (n = 29), (b) Campylobacter infection studies (n = 22). The plots were created using the Risk of Bias Visualization Tool (ROBVIS).

Fig. 4

Random-effects meta-analysis findings for Salmonella infection studies by subgroup showing change in RR and 95% CIs per 1 °C increase in temperature (k = number of effect estimates).

Fig. 5

Random-effects meta-analysis findings for Campylobacter infection studies by subgroup showing change in RR and 95% CIs per 1 °C increase in temperature (k = number of effect estimates).