The Link Between Climate Change and Salmonella Incidence

By Dr. Chinta SidharthanReviewed by Lily Ramsey, LLMFeb 6 2025

Could the weather outside be influencing your chances of getting a foodborne illness? A recent study published in the Journal of Infection revealed that specific weather conditions had an impact on the spread of salmonellosis. This bacterial infection affects thousands of people every year.

By analyzing data from England, Wales, and the Netherlands, the researchers identified key weather factors, such as temperature, humidity, and precipitation, that are linked to an increase in reported salmonella cases.

​​​​​​​Study: Identifying Key Weather Factors Influencing Human Salmonellosis: A Conditional Incidence Analysis in England, Wales, and the Netherlands. Image Credit: faniadiana24/Shutterstock.com

Background

Salmonellosis, caused by the Salmonella bacteria, is one of the most common foodborne diseases worldwide, responsible for tens of thousands of cases in Europe each year. While it is well established that warm temperatures can promote bacterial growth, the relationship between climate conditions and disease transmission is complex.

Previous studies have shown that salmonellosis cases tend to rise during late summer in temperate regions, but many questions remain about the specific role of different weather factors.

For instance, humidity and precipitation can create conditions favorable for bacterial survival, while extreme heat may also influence food storage practices and human behaviors, increasing the risk of contamination.

Additionally, climate change is expected to bring more extreme weather events, potentially altering disease patterns in ways that are not yet fully understood. Understanding how weather influences the spread of food-borne bacteria is critical for improving public health strategies and predicting future outbreaks in a changing climate.

The Current Study

To investigate how weather influences the spread of salmonellosis, this team of European researchers analyzed 16 years of daily salmonella case data from England and Wales, along with four years of data from the Netherlands.

They also examined 14 different weather variables, including temperature, humidity, precipitation, and day length, using a novel statistical model to assess which factors had the strongest link to disease incidence.

The study relied on national surveillance data from public health agencies in both countries. Reported cases were carefully filtered to focus on foodborne Salmonella infections, and the researchers accounted for factors such as reporting delays and seasonal trends.

Furthermore, to determine how weather conditions affected the likelihood of infection, the team used a "conditional incidence" model, which estimates the probability of disease occurrence based on specific combinations of weather factors.

Key weather conditions were analyzed over different time frames, such as the seven days leading up to reported infections, to assess their impact. By comparing real-world salmonellosis cases with simulated case predictions, the researchers also aimed to validate their model’s accuracy.

They also tested whether their findings could be applied across different geographical regions by using weather data from the Netherlands to predict salmonella incidence there.

The study aimed to establish whether the relationship between weather and salmonellosis is location-specific or more universally applicable.

Major Findings

The study found that certain weather conditions significantly influence salmonellosis outbreaks. Specifically, higher air temperatures (above 10 °C) were strongly associated with increased infection rates. The risk was even higher when temperatures exceeded 15 °C during longer daylight hours (12–15 hours).

Additionally, dewpoint temperature (between 7 °C and 10 °C) and high relative humidity were also linked to greater salmonella incidence, suggesting that warm and moist conditions create an environment conducive to bacterial survival and transmission.

Interestingly, precipitation had a complex effect on the incidence of salmonellosis. While reduced rainfall was generally associated with more salmonellosis cases, extreme precipitation events in some regions were linked to increased risks, likely due to water contamination.

However, weather factors such as air pressure, wind speed, and sunshine duration did not show a strong influence on disease incidence.

The model developed in this study proved highly effective in predicting salmonellosis trends, accurately reflecting real-world case patterns in both England and the Netherlands. Even when applied to Dutch data, which involved different surveillance methods and reporting rates, the model successfully captured seasonal peaks of infection, indicating its potential for broader application.

However, the researchers also highlighted some of the limitations of the study. While weather conditions were seen to influence disease incidence, human behaviors, such as outdoor food consumption, hygiene practices, and food storage habits, are also crucial factors that could not be directly measured.

Conclusions

In conclusion, the research emphasized the need to consider weather as a critical factor in food-borne bacterial disease prediction and prevention. The findings also highlighted the potential for weather-based disease prediction models to aid in public health planning.

As climate change continues to drive shifts in weather patterns, understanding these relationships by refining these models and incorporating human behavioral factors will be vital for public health planning and food safety strategies. Furthermore, proactive strategies based on weather forecasts could help mitigate the risks of future foodborne illness outbreaks.