Introduction
Worldwide, 33 million years of healthy lives are lost each year to food-borne illness, which is underestimated [1]. Studies have shown that warmer climates and heat waves increase the incidence of Salmonellosis and Campylobacteriosis [Reference Akil, Ahmad and Reddy2, Reference Kuhn3]. However, different climate variables can affect each food-borne pathogen differently. The association between temperature rise and increased incidence of infection is more consistent with salmonellosis than with Listeria infection [Reference Semenza4]. A meta-analysis showed the pooled relative risk (RR) for each 1-degree rise in temperature for salmonellosis was 1.05 (95% confidence interval (C):1.04–1.07) [Reference Chua5]. For Vibrio infections, an increase in water (not air) temperature is associated with an increased incidence of infection [Reference Semenza4]. The intensity and rapidity of exposure to the climate variable also determine the risk of infection.
In addition to the number of infections, it is also important to study the severity of the disease. Are these infections limited to gastroenteritis, or is there a trend for more invasive infections like bacteraemia? The impact of bacteraemia compared to gastroenteritis is greater, with increased morbidity and mortality, hospitalization, and health services costs [Reference Israel6, Reference Aung7]. With climate change and more difficult conditions for environmental pathogens, bacteraemia may reflect increased virulence from these organisms. A 10-year analysis of passive surveillance data in Queensland, Australia, noted a rise in the incidence of invasive salmonellosis, particularly in the elderly [Reference Parisi8]. Ninety-two per cent of these invasive infections were diagnosed on blood culture [Reference Parisi8]. Salmonella Virchow was the most common species identified [Reference Parisi8]. The contributory factors for the increased invasiveness of these infections were unclear. It has been projected that compared to the years of life lost to disabilities (YLD) in 2000, salmonellosis would contribute to a 9–48% increase in YLD by 2030 due to temperature changes from climate change [Reference Zhang, Bi and Hiller9].
The relationship between climate change and food/waterborne disease is complex. There are temporal and regional variations across the world affected by behavioural changes in populations that increase the risk of these illnesses. While cholera, enteric fever, and bacillary dysentery predominate in the Indian subcontinent and Africa, non-cholera Vibrio species and non-typhoidal Salmonella and Campylobacter infections are prevalent in the temperate regions of the world. There is heterogeneity in the studies reporting an association between climate variables and enteric pathogens, with varied methodologies and modelling strategies.
Existing literature on the impact of climate variables on food-borne pathogens has been restricted to a particular variable [Reference Chua5] or pathogen [Reference Saad10]. We formulated the research question to determine the effect of ambient temperature (including heat waves) and precipitation (including floods) on the incidence of pathogen-specific infections – gastroenteritis and bacteraemia.
Methods
Search strategy
This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Searches for published literature in English on the impact of climate change on infections from Salmonella, Shigella, Campylobacter, Vibrio, and Listeria infections were conducted. MEDLINE (Ovid), Scopus, PubMed, and Web of Science electronic databases were searched without any restrictions on date range.
Inclusion and exclusion criteria
All published articles on the pathogens of interest and one or more climate variables were eligible for inclusion. No time frame was applied as the effect of climate variables on bacteria has not been a recent development. We excluded studies not in English and those not on selected pathogens or climate variables of interest and review articles. Conference abstracts and posters were not included.
Data extraction
One author (NM) screened the abstracts, shortlisted the studies for full-text assessment, and determined inclusion in the review upon examination of the full text. The final list of eligible studies for meta-analysis was checked by two authors (NM and OA). The studies were tabulated by the pathogen of study and data on publication year, study location, study time period, number of cases, population number, climate variable exposure, exposure lag, quantitative estimation of risk, modelling strategy, and key findings, and reported statistics of adjusted analyses were extracted into a purpose-built database. The risk estimates that the studies reported were the correlation coefficient (r), RR, odds ratio (OR), and incidence rate ratio (IRR).
Quality appraisal
We used the ROBINS-E tool as a guide for assessing the risk of bias within the included studies [Reference Higgins, Morgan, Rooney, Taylor, Thayer, Silva, Lemeris, Akl, Arroyave, Bateson, Berkman, Demers, Forastiere, Glenn, Hróbjartsson, Kirrane, LaKind, Luben, Lunn, McAleenan, Mcguinness, Meerpohl, Mehta, Nachman, Obbagy, O’Connor, Radke, Savović, Schubauer-Berigan, Schwingl, Schunemann, Shea, Steenland, Stewart, Straif, Tilling, Verbeek, Vermeulen, Viswanathan, Zahm and Sterne11]. The tool is validated for use in non-randomized ecological studies. The tool consists of seven domains: bias confounding, exposure and outcome measurements, participation selection, post-exposure intervention, missing data, and reporting bias. Each domain is assessed through signalling questions to make judgements on the risk of bias in the domain, the predicted direction of bias, and whether the risk of bias threatens conclusions regarding the exposure having an effect on the outcome. If the risk of bias was considered ‘high enough to change the direction of the outcomes’, the domain was marked as high risk. If the bias was ‘very low’, the domain was marked as low risk. Studies were considered high quality if the overall judgement suggested a low risk of bias in at most one domain. If there were ‘some concerns of bias’ in at least two domains, they were considered moderate in quality, and if there were three or more domains with ‘high or very high risk of bias’, they were low in quality.
Meta-analysis
Studies that had included cases of bacteraemia were shortlisted for meta-analysis. We used random-effects models with inverse-variance weighting to pool the IRR estimates for each pathogen together with their 95% confidence interval (CI). The between-study heterogeneity was evaluated using I 2 statistics as the proportion of variability in effect estimates that is not attributed to sampling error. Following Higgins et al. 2019 [Reference Higgins and Thompson12], a threshold of p < 0.1 was used to indicate statistical significance, and I 2 values of 25%, 50%, and 75% were considered to represent low, moderate, and considerable heterogeneity, respectively. The statistical analysis was carried out in R version 4.2.2 [Reference Wolfgang13] package meta and metaphor [Reference Balduzzi, Rücker and Schwarzer14].
Results
Characteristics of included studies
A total of 3,402 studies were obtained from the databases, and after sorting duplicates, 3,204 abstracts were screened. Out of the 186 articles shortlisted for full-text reading and eligibility, 83 were included in the qualitative review, and three were chosen for meta-analysis (Figure 1). Publication years ranged from 2007 to 2019 (the year of data extraction), with the great majority of included articles (n = 69; 73%) published since 2015 (Figure 1). The grouping of studies by countries and pathogens is summarized in Table 1.
Figure 1. PRISMA flow chart showing the study selection process.
Table 1. Grouping of studies by regions of study, pathogens, and main findings with climate variable associations
All studies in the qualitative review are tabulated. Twenty studies for Campylobacter and twenty-six, nineteen, and eighteen studies for Salmonella, Shigella, and Vibrio species, respectively, were identified. The maximum lagged week was 52 weeks for Vibrio sp. and 9, 12, and 4 weeks for Campylobacter, Salmonella, and Shigella species, respectively. The majority of the articles were scored as having some concerns for bias in at least two domains and were categorized as moderate in quality in the overall judgement (Table S1 in the Supplementary Material).
Ten high-quality studies were identified for Campylobacter, and 11 were of moderate quality. Out of these, three had cases that included bacteraemia [Reference Kuhn15–Reference Weisent17]. Twelve studies on Salmonellosis were high quality. Four studies included patients with bacteraemia [Reference Saad10, Reference Jiang18–Reference Nili20]. With shigellosis, none of the studies specifically discussed bacteraemia and three studies were of high quality. With Vibrio sp., four studies were of high quality.
Overview of pathogens and effect of temperature and precipitation
Campylobacter species
The burden of Campylobacteriosis is high in the Americas and Europe, predominantly in the temperate regions (Figure 2), with the United States of America (USA) and United Kingdom (UK) reporting age-standardized disability-adjusted life year (DALY) of 7.55 and 9.4, respectively [21]. Studies on Campylobacteriosis were predominantly conducted in Europe, North America, and Oceania (Table 1). Campylobacteriosis had a positive association with ambient temperature, whether it was measured as a weekly maximum, monthly, or daily average and extreme heat (Table 2 and Figure 3a). This was true not only for gastroenteritis but also for bacteraemia. The rise in cases was mostly found in a temperature range between 10 and 25 ° C. Out of the 20 studies, 19 (95%) reported a positive association with temperature. With precipitation, six out of nine studies described a positive association (Figure 3a and Table 3).
Figure 2. Global distribution of the burden of Campylobacter, cholera, non-typhoid Salmonella, and Shigella. Source: GBD Results tool: Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Results, Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2020.
Table 2. Studies on Campylobacter with temperature as the climate variable, stratified by type of temperature measurement
a r = correlation coefficient, B = beta coefficient, RR = relative risk, OR = odds ratio, IRR = incidence rate ratio, n/a = not available.
Table 3. Studies on Campylobacter with precipitation as the climate variable, stratified by type of precipitation measurement
a r = correlation coefficient, B = beta coefficient, RR = relative risk, OR = odds ratio, IRR = incidence rate ratio, n/a = not available, PR = precipitation range.
Figure 3. Graphs summarizing the estimated effects (r, beta, RR, IRR, and OR) of temperature and precipitation on specific pathogens. (a) Campylobacter, (b) Salmonella, (c) Shigella, and (d) Vibrio.
The studies by Bi et al. [Reference Bi22] in Australia and Carev et al. [Reference Carev, Tonkić and Boban23] in Croatia reported positive correlations. The studies used regression analyses and controlled for seasonality (using a categorical seasonal variable), lag effects, and long-term trends. Weekly maximum temperature had a positive impact on gastroenteritis in Brisbane but not in Adelaide in the Australian study [Reference Bi22]. Neither these studies nor another study in Denmark [Reference Kovats24] found any association between Campylobacter gastroenteritis and precipitation. A study by Kuhn et al. [Reference Higgins, Morgan, Rooney, Taylor, Thayer, Silva, Lemeris, Akl, Arroyave, Bateson, Berkman, Demers, Forastiere, Glenn, Hróbjartsson, Kirrane, LaKind, Luben, Lunn, McAleenan, Mcguinness, Meerpohl, Mehta, Nachman, Obbagy, O’Connor, Radke, Savović, Schubauer-Berigan, Schwingl, Schunemann, Shea, Steenland, Stewart, Straif, Tilling, Verbeek, Vermeulen, Viswanathan, Zahm and Sterne11] in Nordic countries that studied 64,034 cases over 15 years included cases of bacteraemia and reported a r of 0.09.
Two studies reported OR to show the positive association between the climate variables and gastroenteritis – an international study [Reference Kovats24] (weekly maximum temperature) and another case-crossover study on outbreaks in England (daily total rainfall) [Reference Nichols25] reported OR of 1.3 (95% CI: 1.08, 1.55) and 2.88 (95% CI: 0.29, 28.1), respectively. The time-series study by Fleury et al. [Reference Fleury26] in two provinces in Canada reported a 2.2% increase in gastroenteritis in Alberta and 4.5% in Newfoundland–Labrador, respectively, per degree rise in weekly mean temperature. A study in Maryland, USA [Reference Soneja16], analysed the association with extreme heat and precipitation and found an IRR of 1.04 (95% CI: 1.01, 1.08) and 1.03 (95% CI: 1.01, 1.05), respectively. Importantly, this study included cases of bacteraemia and found that higher La Niña periods have a greater impact on the incidence of infections compared to El Niño periods (IRR = 1.09).
Salmonella species
The majority of typhoid and non-typhoidal salmonella infections are found in Africa and Asia. Salmonellosis is the most common cause of bacteraemia in African children [Reference Teklemariam27]. This pathogen also contributes to significant DALY in developed countries (Figure 2) [Reference Teklemariam27]. Studies on Salmonellosis were conducted in North America, Asia, Europe, and Australia. All studies on Salmonella with increases in monthly, weekly, daily, and extreme temperatures showed an association with a rise in cases regardless of the outcome measure used (Tables 4 and 5, Figure 3b). However, precipitation had different effects in temperate and tropical regions of the world. Four out of the 16 studies (25%) did not find a positive association with precipitation. Both climate variables had a positive association with bacteraemia in the USA (Figure 4).
Table 4. Studies on Salmonella sp. with temperature as the climate variable, stratified by type of temperature measurement
Note: TR: 0–35 °C.
a r = correlation coefficient, B = beta coefficient, RR = relative risk, OR = odds ratio, IRR = incidence rate ratio, n/a = not available, DLNM = distributed lag non-linear model, GAM = generalized additive model, CAR = conditional autoregressive model, GEE = generalized estimating equation.
Table 5. Studies on Salmonella sp. with precipitation as the climate variable, stratified by type of precipitation measurement
a r = correlation coefficient, B = beta coefficient, RR = relative risk, OR = odds ratio, IRR = incidence rate ratio, n/a = not available, DLNM = distributed lag non-linear model, GEE = generalized estimating equation, GAM = generalized additive model, PR = precipitation range.
Figure 4. Pooled studies including bacteraemia climate estimated risk IRR. Pooled IRR indicating the health impacts associated with one unit increase in exceedance days for extreme temperature threshold 95th percentile (ETT95) and extreme precipitation threshold 90th percentile (EPT90), with 95% CIs.
Four studies measured monthly average temperature and reported a positive correlation of Salmonella gastroenteritis with ambient temperature. Cherrie et al. [Reference Cherrie28] performed a time-series analysis in England reporting r = 0.37 for temperature. A surveillance study in Ontario, Canada, by Ravel et al. [Reference Ravel29] found monthly cases peaking in the summer months, while there was no association with precipitation. Similar seasonality was noted in a study in Macedonia [Reference Kendrovski, Karadzovski and Spasenovska30] with a rise of 5.2% incidence per month with maximum monthly mean temperature. Lastly, Wang et al. [Reference Wang31] found an r = 0.55 for monthly temperature and r = 0.48 for monthly precipitation in Guizhou, China. Studies by Akil et al. [Reference Akil, Ahmad and Reddy2] and Mun et al. [Reference Mun32] reported a positive correlation with an outbreak of infections. However, the association was tested with an actual number of infections in the study period in the former study.
Using RR as an outcome measure and weekly mean temperature for exposure, four studies reported a positive association with salmonella gastroenteritis. Three of these were time-series analyses. The first [Reference Fleury26] in Alberta, Canada, showed a log RR increase of 1.2%; the second [Reference Dewan33], in Dhaka, Bangladesh, reported an increase of 14.2% with a 1° rise in temperature for typhoid cases; and the third [Reference Robinson34] in Melbourne, Australia, estimated a twofold increase at 33 °C compared to average weekly temperature. Lastly, Lake et al. [Reference Lake35] reported a RR of 1.05 for S. typhimurium and S. enteritidis infections in England. In contrast to the temperate regions of the world, four studies in Asian countries reported a positive association with precipitation. Three of these reported a rise in typhoid cases with increased rainfall and floods [Reference Dewan33, Reference Iyer36, Reference Liu37]. The study by Wang et al. [Reference Wang, Goggins and Chan38] reported a rise in Salmonella hospitalizations in Hong Kong, along with a rise in daily precipitation.
For bacteraemia, two studies in the USA that included positive blood culture cases reported a positive association with extreme temperature and precipitation events. Firstly, the study by Morgado et al. [Reference Morgado19] reported an IRR of 1.06 (95% CI: 1.04, 1.09). Similarly, the study by Jiang et al. [Reference Jiang18] in Maryland, USA, reported an IRR of 1.041 (95% CI: 1.013, 1.069). Another study using IRR was a time-series analysis in Singapore [Reference Aik39] that examined weekly temperature (1 °C rise) and precipitation (10 mm rise) and reported a 4.3% increase and 0.8% increase in gastroenteritis, respectively. Lastly, Milazzo et al. [Reference Milazzo40] found an increased risk of Salmonella cases varies with serotypes in Adelaide, and Britton et al. reported an IRR of 1.15 (95% CI: 1.07, 1.24) in New Zealand with a rise in monthly average temperature.
Shigella species
Studies on Shigellosis [Reference Ai41–Reference Zhang48] were predominantly from China, and all nine studies on temperature showed a positive association (Figure 3c). Nine of ten studies (90%) on extreme precipitation events like floods showed a positive association (Tables 6 and 7). (Figure 3c). Most studies found a rise in the incidence of gastroenteritis between 10 and 30 ° C temperature range. All the included studies had gastroenteritis as the predominant clinical manifestation, and no studies specified bacteraemia as an outcome.
Table 6. Studies on Shigella sp. with temperature as the climate variable, stratified by type of temperature measurement
a r = correlation coefficient, B = beta coefficient, RR = relative risk, OR = odds ratio, IRR = incidence rate ratio, n/a = not available, TR = temperature ranges.
Table 7. Studies on Shigella sp. with precipitation as the climate variable, stratified by type of precipitation measurement
a r = correlation coefficient, B = beta coefficient, RR = relative risk, OR = odds ratio, IRR = incidence rate ratio, n/a = not available.
Three studies reported a correlation (r). Lee et al. [Reference Lee44] reported r = 0.65 for monthly average temperature and r = 0.17 for monthly precipitation in their study in Kon Tum Province, Vietnam. Two other studies [Reference Xu49, Reference Liu50] found a rise in gastroenteritis cases in China after a lag of 2 weeks. Other Chinese studies [Reference Ai41, Reference Cheng43, Reference Li45, Reference Wen47, Reference Wang51, Reference Liu52] reported an RR rise in Shigellosis with a rise in daily temperature. Li et al. [Reference Li45] noted that each degree rise led to an increase of 1.6%, and children aged 0–5 years were largely affected. Wang et al. [Reference Wang51] noted that ambient temperature was the most important factor regardless of the climate zone studied. Also, temperate cities in China were more affected than subtropical cities. Further, studies in China [Reference Xu49, Reference Colston53–Reference Liu55] revealed a positive association between Shigellosis cases and floods, with an increased incidence for up to three weeks. The risk was increased with short-term and severe floods and reduced with flood duration.
Vibrio species – cholera and non-cholera strains
Cholera is a major public health burden in Africa and Asia (Figure 2), and a majority of the studies on cholera were conducted in these continents. All nine studies on temperature and seven out of eight studies on precipitation showed a positive association with gastroenteritis (Figure 3d). The temperature range of rise in cases was 15–40 ° C. The study by Ruiz-Moreno et al. [Reference Ruiz-Moreno56] extensively investigated the rainfall–cholera relationship in Madras and explained the dual peak in annual cases by the differential effects of rainfall in endemic and epidemic areas. Generally, a complex relationship between rainfall and ambient temperature and cholera varies across regions (Table 8 and Table 9). The study by Ali et al. in matrix laboratory (MATLAB), Bangladesh, found that for an increase in sea surface temperature by 1 °C, there was a 25% increase in cholera incidence in the current month and a 6% increase in incidence with per degree Celsius rise in ambient temperature [Reference Ali57]. Two other studies reported a correlation of 0.204 for daily temperature [Reference Asadgol58] and 0.42 for monthly precipitation [Reference Cash59]. Only two studies reported the relationship between Vibrio infections and precipitation using RR as the measure of effect: one for cholera [Reference Fernandez60] and the other for non-Vibrio cholera infections [Reference Na61]. The cholera study reported a RR of 1.05 (1.04, 1.06) at lag 6 weeks, and the study on Vibrio Vulnificus infections reported a RR of 5.06 (95% CI: 2.41, 10.64) at lag 2 weeks.
Table 8. Studies on Vibrio sp. with temperature as the climate variable, stratified by type of temperature measurement
a r = correlation coefficient, B = beta coefficient, RR = relative risk, OR = odds ratio, IRR = incidence rate ratio, n/a = not available, TR = temperature ranges.
Table 9. Studies on Vibrio sp. with precipitation as the climate variable, stratified by type of precipitation measurement
a r = correlation coefficient, B = beta coefficient, RR = relative risk, OR = odds ratio, IRR = incidence rate ratio, n/a = not available, PR = precipitation range.
Non-cholera strains are predominantly associated with wound infections and septicaemia. These infections rise with sea surface temperature (Table 6). A case–control analysis for V. parahaemolyticus infections in Washington, USA, reported an OR of 2.16 (95% CI: 1.15, 4.05) with yearly temperature [Reference Davis62], while a modelling study in Haiti showed an OR of 1.46 (95% CI: 1.32, 1.16) for daily precipitation [Reference Eisenberg63]. An observational German study by Brehm et al. [Reference Brehm64] noted an association between heat waves and increased Vibrio cases. Of 63 cases, 38 with wound infections and one with septicaemia were found in cases who had recreational exposure to the Baltic Sea or consumed shrimp from the sea after heatwave events.
Listeria species
Only one study by Chersich et al. [Reference Chersich65] addressed the possibility of climate factors and Listeriosis. This discussed an outbreak of invasive Listeriosis in South Africa that resulted in 180 deaths. The source was traced to a food production facility that processed ‘ready-to-eat’ meat products. The risks identified were the impacts of temperature augmenting replication cycles of the bacterium, hot climate leading to breakdown in the food cooling chain, and the increased use of contaminated surface water.
Pooled estimates for bacteraemia
Four studies reported IRR for cases that included bacteraemia with ambient temperature and precipitation as climate variables [Reference Soneja16, Reference Jiang18–Reference Nili20]. Our meta-analysis combined three of these studies as they included extreme heat and precipitation as exposure variables (Figure 4). These studies used extreme temperature threshold 95% percentile (ETT95) and extreme precipitation threshold (EPT90) and showed a pooled IRR of 1.05 (95% CI: 1.03, 1.06) associated with a unit increase in ETT95 exceedance days and 1.09 (95% CI: 0.99, 1.19) associated with a unit increase in EPT90 exceedance days (Figure 4).
Discussion
In this systematic review and meta-analysis, we conducted a comprehensive synthesis of the impact of ambient temperature and precipitation on five food-borne pathogens based on published data between 2001 and 2021. In Europe, Australia, and North America, where Campylobacteriosis is predominant, a positive association was found with a rise in ambient temperature. Similarly, Salmonellosis incidence rose worldwide with temperature, with all studies showing a positive association. In contrast, the association with precipitation for both pathogens was less evident in temperate regions of the world. Shigellosis and Vibrio infections, more predominant in Africa and Asia, had a positive association with both temperature and excess precipitation. The positive association between these climate variables and illness was also consistent among studies where bacteraemia cases were included.
The findings of our review and meta-analysis are consistent with prior reviews on ambient temperature rise and infections from Campylobacter, Salmonella, and Shigella species [Reference Aarnisalo66, Reference Cousins67]. The majority of the studies for Campylobacter and Salmonella were either of high or moderate quality, which increased the reliability of the outcome measures, particularly for the two pathogens. This is the first review to demonstrate a positive association for studies including bacteraemia from Campylobacter and Salmonella species as an outcome.
The variable effect of climate variables on bacterial food pathogens in different regions of the world needs an understanding of not only the pathogen’s multiplication risks but also the modes of transmission and human behavioural factors. Campylobacter studies mostly found a lag period of 4–5 weeks, suggesting food contamination as the likely reason for the rise in incidence. The increase in cases in summer, particularly in Europe, seems to be related to the changes in behaviour among the people, for example, having more barbecues, outdoor parties, and contact with infected animals. The rise in temperature also increases the risk of infection in broiler flocks, and any errors in the cold chain of food transport can increase the risk in humans [Reference Semenza4]. With projected rises in ambient temperature, Campylobacter infection seasonality will be longer and not restricted just to summer months. This could translate to an increase of infections by 200% in the Nordic countries by the end of the century [Reference Kuhn3]. Although Campylobacter sp. replicates in humid conditions, a positive association with precipitation has not been consistently found. Possible explanations are, firstly, a paucity of studies and, secondly, heterogeneity in using the time of exposure of precipitation. A significant impact may not be found when daily total precipitation is averaged out to weekly estimates. Studies using excessive precipitation in a day showed a significant association [Reference Soneja16, Reference Nichols25]. Although the studies on Campylobacter bacteraemia do not mention the incidence of bacteraemia separately, the proportion of bacteraemia would also be expected to rise with current climate trends.
Salmonella replication is enhanced with the rise in temperature, which explains the cyclical rise in cases in late summer in temperate regions of the world. The variation in temperature in equatorial regions is less pronounced, which could explain the lesser impact of temperature in these areas [Reference Saad10]. However, seasonal monsoons in these regions lead to a rise in enteric fever every year, as flooding is a risk for transmission of enteric fever [Reference Saad10]. This can explain the positive association with lagged effects in Asian countries. In contrast, only excessive daily precipitation positively affected temperate regions of the world. The review by Saad [Reference Saad10] includes 16 datasets with Salmonella bacteraemia and showed a positive association with temperature and rainfall. An increase in ambient temperature over the coming years would significantly impact the incidence of salmonellosis worldwide, particularly in the non-equatorial regions, which would also translate to an increase in hospitalizations.
Bacillary dysentery cases from Shigella species also rise with temperature as the bacterium replicates more and food-borne transmission rises. The difference compared to the other bacterial food pathogens is the short lag period, as the incubation period is short. With precipitation, the most consistent association is with floods. This is more obvious in low socio-economic areas in China, where poor access to clean drinking water during floods increases the risk of transmission [Reference Wang51]. Given that most cases are diagnosed with stool specimens, our review found no studies specific to bacteraemia. Only three studies were of high quality, as most other studies had biases with confounding and exposure.
Ambient temperature promotes Vibrio species growth, and increases in algal blooms contribute as well [Reference Thickman and Gobler68]. For non-cholera species, water temperature and salinity are the two most important risk factors for growth. With the warming of the oceans, coastal regions will face increased sepsis cases from these species [Reference Baker-Austin69]. Heat waves have helped spread Vibrio sp. to higher latitudes, and a mini-review predicted that infections might quadruple in the coming years [Reference Froelich and Daines70]. Cholera cases in Africa and India have a complex relationship with climate variables. In the dry season, the rise in cases is chiefly due to increased ambient temperature. During the monsoon, the dilutional effect of rainfall on water salinity leads to a reduction in the number of cases. After a lag period, due to increased contact with contaminated water, there is another peak of cases [Reference Ruiz-Moreno56]. A study by Koelle et al. [Reference Koelle71] in MATLAB, Bangladesh, demonstrated an association of outbreaks with monsoons and a lag period as long as eight months. The authors also noted that if herd immunity is high after a recent outbreak, climate variables had a limited impact on cholera transmission. Four studies were of high quality, while the rest had confounding and selection biases. In the future, the prediction is that Vibrio infections will rise and expand geographically with current climate trends [Reference Baker-Austin69]. This would include cases of bacteraemia and lead to high mortality.
We acknowledge the following limitations in this review and meta-analysis. First, some studies conducted in non-English languages were excluded. Second, the absence of data on the proportion of cases of bacteraemia in the studies prevented an accurate prediction of the genuine impact of climate on this severe outcome. Thirdly, only one author did the screening, and only MEDLINE was updated in March 2023 to capture any missing recent studies. The maximum number of publications was obtained from the databases, and the potential for missed publications, although possible, is low. Many studies reported outcomes for multiple pathogens but reported outcome measures separately, reducing the chance of any reporting bias. Lastly, although we developed our study protocol a priori (available on request from the corresponding author upon request), time constraints prevented us from registration or publication before this was completed. Despite these acknowledged limitations, the findings in this study are important and valid.
In summary, this is the first review that provides a comprehensive overview of the complex interactions between the intensity and timing of climate variable exposure and the incidence of pathogen-specific infections. Studies that included cases of Campylobacter and Salmonella bacteraemia reported a rise in incidence with ambient temperature and precipitation. Further research is needed to study the impact of a surge in food pathogen bacteraemia with current trends in climate change.
Supplementary material
The supplementary material for this article can be found at http://doi.org/10.1017/S0950268824000839.
Data availability statement
All relevant data are presented in the manuscript.
Author contribution
N.M. conceived the study, conducted the systematic search, extracted the data, analysed the data, interpreted the results, and wrote the first draft of the paper; M.Y.K. assisted with interpreting the results and the first draft of the paper; MEC assisted with interpreting the results and the first draft of the paper; P.L. assisted with interpreting the results and the first draft of the paper; and O.A. assisted with data extraction, data analysis, interpretation of the results, and the first draft of the paper. All authors contributed to drafting and revising the manuscript.
Competing interest
The authors declare no competing interests.
Open access
