Analysis of environmental factors influencing endemic cholera risks in sub-Saharan Africa.

The recurring cholera outbreaks in sub-Saharan Africa are of growing concern, especially considering the potential acceleration in the global trend of larger and more lethal cholera outbreaks due to the impacts of climate change. However, there is a scarcity of evidence-based research addressing the environmental and infrastructure factors that sustain cholera recurrence in Africa. This study adopts a statistical approach to investigate over two decades of endemic cholera outbreaks and their relationship with five environmental factors: water provision, sanitation provision, raising temperatures, increased rainfall and GDP. The analysis covers thirteen of the forty-two countries in the mainland sub-Saharan region, collectively representing one-third of the region's territory and half of its population. This breadth enables the findings to be generalised at a regional level. Results from all analyses consistently associate water provision with cholera reduction. The stratified model links increased water provision with a reduction in cholera risk that ranged from 4.2 % to 84.1 % among eight countries (out of 13 countries) as well as a reduction of such risk that ranged from 9.8 % to 68.9 % when there is increased sanitation provision, which was observed in nine countries (out of 13). These results indicate that the population's limited access to water and sanitation, as well as the rise in temperatures, are critical infrastructure and environmental factors contributing to endemic cholera and the heightened risk of outbreaks across the sub-Saharan region. Therefore, these are key areas for targeted interventions and cross-border collaboration to enhance resilience to outbreaks and lead to the end of endemic cholera in the region. However, it is important to interpret the results of this study with caution; hence, further investigation is recommended to conduct a more detailed analysis of the impact of infrastructure and environmental factors on reducing cholera risk.

A mathematical, classical stratification modeling approach to disentangling the impact of weather on infectious diseases: A case study using spatio-temporally disaggregated Campylobacter surveillance data for England and Wales.

Disentangling the impact of the weather on transmission of infectious diseases is crucial for health protection, preparedness and prevention. Because weather factors are co-incidental and partly correlated, we have used geography to separate out the impact of individual weather parameters on other seasonal variables using campylobacteriosis as a case study. Campylobacter infections are found worldwide and are the most common bacterial food-borne disease in developed countries, where they exhibit consistent but country specific seasonality. We developed a novel conditional incidence method, based on classical stratification, exploiting the long term, high-resolution, linkage of approximately one-million campylobacteriosis cases over 20 years in England and Wales with local meteorological datasets from diagnostic laboratory locations. The predicted incidence of campylobacteriosis increased by 1 case per million people for every 5° (Celsius) increase in temperature within the range of 8°-15°. Limited association was observed outside that range. There were strong associations with day-length. Cases tended to increase with relative humidity in the region of 75-80%, while the associations with rainfall and wind-speed were weaker. The approach is able to examine multiple factors and model how complex trends arise, e.g. the consistent steep increase in campylobacteriosis in England and Wales in May-June and its spatial variability. This transparent and straightforward approach leads to accurate predictions without relying on regression models and/or postulating specific parameterisations. A key output of the analysis is a thoroughly phenomenological description of the incidence of the disease conditional on specific local weather factors. The study can be crucially important to infer the elusive mechanism of transmission of campylobacteriosis; for instance, by simulating the conditional incidence for a postulated mechanism and compare it with the phenomenological patterns as benchmark. The findings challenge the assumption, commonly made in statistical models, that the transformed mean rate of infection for diseases like campylobacteriosis is a mere additive and combination of the environmental variables.

Mechanisms of cholera transmission via environment in India and Bangladesh: state of the science review.

OBJECTIVES: Cholera has a long history in India and Bangladesh, the region where six out of the past seven global pandemics have been seeded. The changing climate and growing population have led to global cholera cases remaining high despite a consistent improvement in the access to clean water and sanitation. We aim to provide a holistic overview of variables influencing environmental cholera transmission within the context of India and Bangladesh, with a focus on the mechanisms by which they act. CONTENT: We identified 56 relevant texts (Bangladesh n = 40, India n = 7, Other n = 5). The results of the review found that cholera transmission is associated with several socio-economic and environmental factors, each associated variable is suggested to have at least one mediating mechanism. Increases in ambient temperature and coastal sea surface temperature support cholera transmission via increases in plankton and a preference of Vibrio cholerae for warmer waters. Increased rainfall can potentially support or reduce transmission via several mechanisms. SUMMARY AND OUTLOOK: Common issues in the literature are co-variance of seasonal factors, limited access to high quality cholera data, high research bias towards research in Dhaka and Matlab (Bangladesh). A specific and detailed understanding of the relationship between SST and cholera incidence remains unclear.

Mapping the evidence of the effects of environmental factors on the prevalence of antibiotic resistance in the non-built environment: Protocol for a systematic evidence map.

BACKGROUND: Human, animal, and environmental health are increasingly threatened by the emergence and spread of antibiotic resistance. Inappropriate use of antibiotic treatments commonly contributes to this threat, but it is also becoming apparent that multiple, interconnected environmental factors can play a significant role. Thus, a One Health approach is required for a comprehensive understanding of the environmental dimensions of antibiotic resistance and inform science-based decisions and actions. The broad and multidisciplinary nature of the problem poses several open questions drawing upon a wide heterogeneous range of studies. OBJECTIVE: This study seeks to collect and catalogue the evidence of the potential effects of environmental factors on the abundance or detection of antibiotic resistance determinants in the outdoor environment, i.e., antibiotic resistant bacteria and mobile genetic elements carrying antibiotic resistance genes, and the effect on those caused by local environmental conditions of either natural or anthropogenic origin. METHODS: Here, we describe the protocol for a systematic evidence map to address this, which will be performed in adherence to best practice guidelines. We will search the literature from 1990 to present, using the following electronic databases: MEDLINE, Embase, and the Web of Science Core Collection as well as the grey literature. We shall include full-text, scientific articles published in English. Reviewers will work in pairs to screen title, abstract and keywords first and then full-text documents. Data extraction will adhere to a code book purposely designed. Risk of bias assessment will not be conducted as part of this SEM. We will combine tables, graphs, and other suitable visualisation techniques to compile a database i) of studies investigating the factors associated with the prevalence of antibiotic resistance in the environment and ii) map the distribution, network, cross-disciplinarity, impact and trends in the literature.

Marine harmful algal blooms and human health: A systematic scoping review.

Exposure to harmful algal blooms (HABs) can lead to well recognised acute patterns of illness in humans. The objective of this scoping review was to use an established methodology and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting framework to map the evidence for associations between marine HABs and observed both acute and chronic human health effects. A systematic and reproducible search of publications from 1985 until May 2019 was conducted using diverse electronic databases. Following de-duplication, 5301 records were identified, of which 380 were included in the final qualitative synthesis. The majority of studies (220; 57.9%) related to Ciguatera Poisoning. Anecdotal and case reports made up the vast majority of study types (242; 63.7%), whereas there were fewer formal epidemiological studies (35; 9.2%). Only four studies related to chronic exposure to HABs. A low proportion of studies reported the use of human specimens for confirmation of the cause of illness (32; 8.4%). This study highlighted gaps in the evidence base including a lack of formal surveillance and epidemiological studies, limited use of toxin measurements in human samples, and a scarcity of studies of chronic exposure. Future research and policy should provide a baseline understanding of the burden of human disease to inform the evaluation of the current and future impacts of climate change and HABs on human health.

Seasonality and the effects of weather on Campylobacter infections.

BACKGROUND: Campylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood. METHODS: To investigate the impacts of temperature and rainfall on Campylobacter infections in England and Wales, cases of Campylobacter were linked to local temperature and rainfall at laboratory postcodes in the 30 days before the specimen date. Methods for investigation included a comparative conditional incidence, wavelet, clustering, and time series analyses. RESULTS: The increase of Campylobacter infections in the late spring was significantly linked to temperature two weeks before, with an increase in conditional incidence of 0.175 cases per 100,000 per week for weeks 17 to 24; the relationship to temperature was not linear. Generalized structural time series model revealed that changes in temperature accounted for 33.3% of the expected cases of Campylobacteriosis, with an indication of the direction and relevant temperature range. Wavelet analysis showed a strong annual cycle with additional harmonics at four and six months. Cluster analysis showed three clusters of seasonality with geographic similarities representing metropolitan, rural, and other areas. CONCLUSIONS: The association of Campylobacteriosis with temperature is likely to be indirect. High-resolution spatial temporal linkage of weather parameters and cases is important in improving weather associations with infectious diseases. The primary driver of Campylobacter incidence remains to be determined; other avenues, such as insect contamination of chicken flocks through poor biosecurity should be explored.

Pathogen seasonality and links with weather in England and Wales: a big data time series analysis.

BACKGROUND: Many infectious diseases of public health importance display annual seasonal patterns in their incidence. We aimed to systematically document the seasonality of several human infectious disease pathogens in England and Wales, highlighting those organisms that appear weather-sensitive and therefore may be influenced by climate change in the future. METHODS: Data on infections in England and Wales from 1989 to 2014 were extracted from the Public Health England (PHE) SGSS surveillance database. We conducted a weekly, monthly and quarterly time series analysis of 277 pathogen serotypes. Each organism's time series was forecasted using the TBATS package in R, with seasonality detected using model fit statistics. Meteorological data hosted on the MEDMI Platform were extracted at a monthly resolution for 2001-2011. The organisms were then clustered by K-means into two groups based on cross correlation coefficients with the weather variables. RESULTS: Examination of 12.9 million infection episodes found seasonal components in 91/277 (33%) organism serotypes. Salmonella showed seasonal and non-seasonal serotypes. These results were visualised in an online Rshiny application. Seasonal organisms were then clustered into two groups based on their correlations with weather. Group 1 had positive correlations with temperature (max, mean and min), sunshine and vapour pressure and inverse correlations with mean wind speed, relative humidity, ground frost and air frost. Group 2 had the opposite but also slight positive correlations with rainfall (mm, > 1 mm, > 10 mm). CONCLUSIONS: The detection of seasonality in pathogen time series data and the identification of relevant weather predictors can improve forecasting and public health planning. Big data analytics and online visualisation allow the relationship between pathogen incidence and weather patterns to be clarified.

A comparison of weather variables linked to infectious disease patterns using laboratory addresses and patient residence addresses.

BACKGROUND: To understand the impact of weather on infectious diseases, information on weather parameters at patient locations is needed, but this is not always accessible due to confidentiality or data availability. Weather parameters at nearby locations are often used as a proxy, but the accuracy of this practice is not known. METHODS: Daily Campylobacter and Cryptosporidium cases across England and Wales were linked to local temperature and rainfall at the residence postcodes of the patients and at the corresponding postcodes of the laboratory where the patient's specimen was tested. The paired values of daily rainfall and temperature for the laboratory versus residence postcodes were interpolated from weather station data, and the results were analysed for agreement using linear regression. We also assessed potential dependency of the findings on the relative geographic distance between the patient's residence and the laboratory. RESULTS: There was significant and strong agreement between the daily values of rainfall and temperature at diagnostic laboratories with the values at the patient residence postcodes for samples containing the pathogens Campylobacter or Cryptosporidium. For rainfall, the R-squared was 0.96 for the former and 0.97 for the latter, and for maximum daily temperature, the R-squared was 0.99 for both. The overall mean distance between the patient residence and the laboratory was 11.9 km; however, the distribution of these distances exhibited a heavy tail, with some rare situations where the distance between the patient residence and the laboratory was larger than 500 km. These large distances impact the distributions of the weather variable discrepancies (i.e. the differences between weather parameters estimated at patient residence postcodes and those at laboratory postcodes), with discrepancies up to ±10 °C for the minimum and maximum temperature and 20 mm for rainfall. Nevertheless, the distributions of discrepancies (estimated separately for minimum and maximum temperature and rainfall), based on the cases where the distance between the patient residence and the laboratory was within 20 km, still exhibited tails somewhat longer than the corresponding exponential fits suggesting modest small scale variations in temperature and rainfall. CONCLUSION: The findings confirm that, for the purposes of studying the relationships between meteorological variables and infectious diseases using data based on laboratory postcodes, the weather results are sufficiently similar to justify the use of laboratory postcode as a surrogate for domestic postcode. Exclusion of the small percentage of cases where there is a large distance between the residence and the laboratory could increase the precision of estimates, but there are generally strong associations between daily weather parameters at residence and laboratory.

Environmental Suitability of Vibrio Infections in a Warming Climate: An Early Warning System.

BACKGROUND: Some Vibrio spp. are pathogenic and ubiquitous in marine waters with low to moderate salinity and thrive with elevated sea surface temperature (SST). OBJECTIVES: Our objective was to monitor and project the suitability of marine conditions for Vibrio infections under climate change scenarios. METHODS: The European Centre for Disease Prevention and Control (ECDC) developed a platform (the ECDC Vibrio Map Viewer) to monitor the environmental suitability of coastal waters for Vibrio spp. using remotely sensed SST and salinity. A case-crossover study of Swedish cases was conducted to ascertain the relationship between SST and Vibrio infection through a conditional logistic regression. Climate change projections for Vibrio infections were developed for Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. RESULTS: The ECDC Vibrio Map Viewer detected environmentally suitable areas for Vibrio spp. in the Baltic Sea in July 2014 that were accompanied by a spike in cases and one death in Sweden. The estimated exposure-response relationship for Vibrio infections at a threshold of 16°C revealed a relative risk (RR)=1.14 (95% CI: 1.02, 1.27; p=0.024) for a lag of 2 wk; the estimated risk increased successively beyond this SST threshold. Climate change projections for SST under the RCP 4.5 and RCP 8.5 scenarios indicate a marked upward trend during the summer months and an increase in the relative risk of these infections in the coming decades. CONCLUSIONS: This platform can serve as an early warning system as the risk of further Vibrio infections increases in the 21st century due to climate change. https://doi.org/10.1289/EHP2198.

Challenges in developing methods for quantifying the effects of weather and climate on water-associated diseases: A systematic review.

Infectious diseases attributable to unsafe water supply, sanitation and hygiene (e.g. Cholera, Leptospirosis, Giardiasis) remain an important cause of morbidity and mortality, especially in low-income countries. Climate and weather factors are known to affect the transmission and distribution of infectious diseases and statistical and mathematical modelling are continuously developing to investigate the impact of weather and climate on water-associated diseases. There have been little critical analyses of the methodological approaches. Our objective is to review and summarize statistical and modelling methods used to investigate the effects of weather and climate on infectious diseases associated with water, in order to identify limitations and knowledge gaps in developing of new methods. We conducted a systematic review of English-language papers published from 2000 to 2015. Search terms included concepts related to water-associated diseases, weather and climate, statistical, epidemiological and modelling methods. We found 102 full text papers that met our criteria and were included in the analysis. The most commonly used methods were grouped in two clusters: process-based models (PBM) and time series and spatial epidemiology (TS-SE). In general, PBM methods were employed when the bio-physical mechanism of the pathogen under study was relatively well known (e.g. Vibrio cholerae); TS-SE tended to be used when the specific environmental mechanisms were unclear (e.g. Campylobacter). Important data and methodological challenges emerged, with implications for surveillance and control of water-associated infections. The most common limitations comprised: non-inclusion of key factors (e.g. biological mechanism, demographic heterogeneity, human behavior), reporting bias, poor data quality, and collinearity in exposures. Furthermore, the methods often did not distinguish among the multiple sources of time-lags (e.g. patient physiology, reporting bias, healthcare access) between environmental drivers/exposures and disease detection. Key areas of future research include: disentangling the complex effects of weather/climate on each exposure-health outcome pathway (e.g. person-to-person vs environment-to-person), and linking weather data to individual cases longitudinally.

Association between heavy precipitation events and waterborne outbreaks in four Nordic countries, 1992-2012.

We conducted a matched case-control study to examine the association between heavy precipitation events and waterborne outbreaks (WBOs) by linking epidemiological registries and meteorological data between 1992 and 2012 in four Nordic countries. Heavy precipitation events were defined by above average (exceedance) daily rainfall during the preceding weeks using local references. We performed conditional logistic regression using the four previous years as the controls. Among WBOs with known onset date (n = 89), exceedance rainfall on two or more days was associated with occurrence of outbreak, OR = 3.06 (95% CI 1.38-6.78), compared to zero exceedance days. Stratified analyses revealed a significant association with single household water supplies, ground water as source and for outbreaks occurring during spring and summer. These findings were reproduced in analyses including all WBOs with known outbreak month (n = 186). The vulnerability of single households to WBOs associated with heavy precipitation events should be communicated to homeowners and implemented into future policy planning to reduce the risk of waterborne illness.

A Unified Framework for the Infection Dynamics of Zoonotic Spillover and Spread.

A considerable amount of disease is transmitted from animals to humans and many of these zoonoses are neglected tropical diseases. As outbreaks of SARS, avian influenza and Ebola have demonstrated, however, zoonotic diseases are serious threats to global public health and are not just problems confined to remote regions. There are two fundamental, and poorly studied, stages of zoonotic disease emergence: 'spillover', i.e. transmission of pathogens from animals to humans, and 'stuttering transmission', i.e. when limited human-to-human infections occur, leading to self-limiting chains of transmission. We developed a transparent, theoretical framework, based on a generalization of Poisson processes with memory of past human infections, that unifies these stages. Once we have quantified pathogen dynamics in the reservoir, with some knowledge of the mechanism of contact, the approach provides a tool to estimate the likelihood of spillover events. Comparisons with independent agent-based models demonstrates the ability of the framework to correctly estimate the relative contributions of human-to-human vs animal transmission. As an illustrative example, we applied our model to Lassa fever, a rodent-borne, viral haemorrhagic disease common in West Africa, for which data on human outbreaks were available. The approach developed here is general and applicable to a range of zoonoses. This kind of methodology is of crucial importance for the scientific, medical and public health communities working at the interface between animal and human diseases to assess the risk associated with the disease and to plan intervention and appropriate control measures. The Lassa case study revealed important knowledge gaps, and opportunities, arising from limited knowledge of the temporal patterns in reporting, abundance of and infection prevalence in, the host reservoir.

Cyclospora infection linked to travel to Mexico, June to September 2015.

Cyclospora cayetanensis was identified in 176 returned travellers from the Riviera Maya region of Mexico between 1 June and 22 September 2015; 79 in the United Kingdom (UK) and 97 in Canada. UK cases completed a food exposure questionnaire. This increase in reported Cyclospora cases highlights risks of gastrointestinal infections through travelling, limitations in Cyclospora surveillance and the need for improved hygiene in the production of food consumed in holiday resorts.

An Outbreak of Cryptosporidium parvum across England & Scotland Associated with Consumption of Fresh Pre-Cut Salad Leaves, May 2012.

BACKGROUND: We report a widespread foodborne outbreak of Cryptosporidium parvum in England and Scotland in May 2012. Cases were more common in female adults, and had no history of foreign travel. Over 300 excess cases were identified during the period of the outbreak. Speciation and microbiological typing revealed the outbreak strain to be C. parvum gp60 subtype IIaA15G2R1. METHODS: Hypothesis generation questionnaires were administered and an unmatched case control study was undertaken to test the hypotheses raised. Cases and controls were interviewed by telephone. Controls were selected using sequential digit dialling. Information was gathered on demographics, foods consumed and retailers where foods were purchased. RESULTS: Seventy-four laboratory confirmed cases and 74 controls were included in analyses. Infection was found to be strongly associated with the consumption of pre-cut mixed salad leaves sold by a single retailer. This is the largest documented outbreak of cryptosporidiosis attributed to a food vehicle.

Analytical studies assessing the association between extreme precipitation or temperature and drinking water-related waterborne infections: a review.

Determining the role of weather in waterborne infections is a priority public health research issue as climate change is predicted to increase the frequency of extreme precipitation and temperature events. To document the current knowledge on this topic, we performed a literature review of analytical research studies that have combined epidemiological and meteorological data in order to analyze associations between extreme precipitation or temperature and waterborne disease.A search of the databases Ovid MEDLINE, EMBASE, SCOPUS and Web of Science was conducted, using search terms related to waterborne infections and precipitation or temperature. Results were limited to studies published in English between January 2001 and December 2013.Twenty-four articles were included in this review, predominantly from Asia and North-America. Four articles used waterborne outbreaks as study units, while the remaining articles used number of cases of waterborne infections. Results presented in the different articles were heterogeneous. Although most of the studies identified a positive association between increased precipitation or temperature and infection, there were several in which this association was not evidenced. A number of articles also identified an association between decreased precipitation and infections. This highlights the complex relationship between precipitation or temperature driven transmission and waterborne disease. We encourage researchers to conduct studies examining potential effect modifiers, such as the specific type of microorganism, geographical region, season, type of water supply, water source or water treatment, in order to assess how they modulate the relationship between heavy rain events or temperature and waterborne disease. Addressing these gaps is of primary importance in order to identify the areas where action is needed to minimize negative impact of climate change on health in the future.

European monitoring systems and data for assessing environmental and climate impacts on human infectious diseases.

Surveillance is critical to understanding the epidemiology and control of infectious diseases. The growing concern over climate and other drivers that may increase infectious disease threats to future generations has stimulated a review of the surveillance systems and environmental data sources that might be used to assess future health impacts from climate change in Europe. We present an overview of organizations, agencies and institutions that are responsible for infectious disease surveillance in Europe. We describe the surveillance systems, tracking tools, communication channels, information exchange and outputs in light of environmental and climatic drivers of infectious diseases. We discuss environmental and climatic data sets that lend themselves to epidemiological analysis. Many of the environmental data sets have a relatively uniform quality across EU Member States because they are based on satellite measurements or EU funded FP6 or FP7 projects with full EU coverage. Case-reporting systems for surveillance of infectious diseases should include clear and consistent case definitions and reporting formats that are geo-located at an appropriate resolution. This will allow linkage to environmental, social and climatic sources that will enable risk assessments, future threat evaluations, outbreak management and interventions to reduce disease burden.

The first recorded outbreak of cryptosporidiosis due to Cryptosporidium cuniculus (formerly rabbit genotype), following a water quality incident.

We report the first identified outbreak of cryptosporidiosis with Cryptosporidium cuniculus following a water quality incident in Northamptonshire, UK. A standardised, enhanced Cryptosporidium exposure questionnaire was administered to all cases of cryptosporidiosis after the incident. Stool samples, water testing, microscopy slides and rabbit gut contents positive for Cryptosporidium were typed at the Cryptosporidium Reference Unit, Singleton Hospital, Swansea. Twenty-three people were microbiologically linked to the incident although other evidence suggests an excess of 422 cases of cryptosporidiosis above baseline. Most were adult females; unusually for cryptosporidiosis there were no affected children identified under the age of 5 years. Water consumption was possibly higher than in national drinking water consumption patterns. Diarrhoea duration was negatively correlated to distance from the water treatment works where the contamination occurred. Oocyst counts were highest in water storage facilities. This outbreak is the first caused by C. cuniculus infection to have been noted and it has conclusively demonstrated that this species can be a human pathogen. Although symptomatically similar to cryptosporidiosis from C. parvum or C. hominis, this outbreak has revealed some differences, in particular no children under 5 were identified and females were over-represented. These dissimilarities are unexplained although we postulate possible explanations.

Opportunities and limitations of molecular methods for quantifying microbial compliance parameters in EU bathing waters.

The debate over the suitability of molecular biological methods for the enumeration of regulatory microbial parameters (e.g. Faecal Indicator Organisms [FIOs]) in bathing waters versus the use of traditional culture-based methods is of current interest to regulators and the science community. Culture-based methods require a 24-48hour turn-around time from receipt at the laboratory to reporting, whilst quantitative molecular tools provide a more rapid assay (approximately 2-3h). Traditional culturing methods are therefore often viewed as slow and 'out-dated', although they still deliver an internationally 'accepted' evidence-base. In contrast, molecular tools have the potential for rapid analysis and their operational utility and associated limitations and uncertainties should be assessed in light of their use for regulatory monitoring. Here we report on the recommendations from a series of international workshops, chaired by a UK Working Group (WG) comprised of scientists, regulators, policy makers and other stakeholders, which explored and interrogated both molecular (principally quantitative polymerase chain reaction [qPCR]) and culture-based tools for FIO monitoring under the European Bathing Water Directive. Through detailed analysis of policy implications, regulatory barriers, stakeholder engagement, and the needs of the end-user, the WG identified a series of key concerns that require critical appraisal before a potential shift from culture-based approaches to the employment of molecular biological methods for bathing water regulation could be justified.

Self-reported stomach upset in travellers on cruise-based and land-based package holidays.

BACKGROUND: International travellers are at a risk of infectious diseases not seen in their home country. Stomach upsets are common in travellers, including on cruise ships. This study compares the incidence of stomach upsets on land- and cruise-based holidays. METHODS: A major British tour operator has administered a Customer Satisfaction Questionnaire (CSQ) to UK resident travellers aged 16 or more on return flights from their holiday abroad over many years. Data extracted from the CSQ was used to measure self-reported stomach upset in returning travellers. RESULTS: From summer 2000 through winter 2008, 6,863,092 questionnaires were completed; 6.6% were from cruise passengers. A higher percentage of land-based holiday-makers (7.2%) reported stomach upset in comparison to 4.8% of cruise passengers (RR = 1.5, p<0.0005). Reported stomach upset on cruises declined over the study period (7.1% in 2000 to 3.1% in 2008, p<0.0005). Over 25% of travellers on land-based holidays to Egypt and the Dominican Republic reported stomach upset. In comparison, the highest proportion of stomach upset in cruise ship travellers were reported following cruises departing from Egypt (14.8%) and Turkey (8.8%). CONCLUSIONS: In this large study of self-reported illness both demographic and holiday choice factors were shown to play a part in determining the likelihood of developing stomach upset while abroad. There is a lower cumulative incidence and declining rates of stomach upset in cruise passengers which suggest that the cruise industry has adopted operations (e.g. hygiene standards) that have reduced illness over recent years.