Dataset Information

Weather variables as important clinical predictors of bacterial diarrhoea among international travellers.

ABSTRACT:

Background

Clinicians and travellers often have limited tools to differentiate bacterial from non-bacterial causes of travellers' diarrhoea (TD). Development of a clinical prediction rule assessing the aetiology of TD may help identify episodes of bacterial diarrhoea and limit inappropriate antibiotic use. We aimed to identify predictors of bacterial diarrhoea among clinical, demographic and weather variables, as well as to develop and cross-validate a parsimonious predictive model.

Methods

We collected de-identified clinical data from 457 international travellers with acute diarrhoea presenting to two healthcare centres in Nepal and Thailand. We used conventional microbiologic and multiplex molecular methods to identify diarrheal aetiology from stool samples. We used random forest and logistic regression to determine predictors of bacterial diarrhoea.

Results

We identified 195 cases of bacterial aetiology, 63 viral, 125 mixed pathogens, 6 protozoal/parasite and 68 cases without a detected pathogen. Random forest regression indicated that the strongest predictors of bacterial over viral or non-detected aetiologies were average location-specific environmental temperature and red blood cell on stool microscopy. In 5-fold cross-validation, the parsimonious model with the highest discriminative performance had an area under the receiver operator curve of 0.73 using 3 variables with calibration intercept -0.01 (standard deviation, SD 0.31) and slope 0.95 (SD 0.36).

Conclusions

We identified environmental temperature, a location-specific parameter, as an important predictor of bacterial TD, among traditional patient-specific parameters predictive of aetiology. Future work includes further validation and the development of a clinical decision-support tool to inform appropriate use of antibiotics in TD.

SUBMITTER: Pender MA

PROVIDER: S-EPMC9282096 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Publications

Weather variables as important clinical predictors of bacterial diarrhoea among international travellers.

Pender Melissa A MA Smith Timothy T Brintz Ben J BJ Pandey Prativa P Shrestha Sanjaya K SK Anuras Sinn S Demons Samandra S Sornsakrin Siriporn S Bodhidatta Ladaporn L Platts-Mills James A JA Leung Daniel T DT

Journal of travel medicine 20220701 4

<h4>Background</h4>Clinicians and travellers often have limited tools to differentiate bacterial from non-bacterial causes of travellers' diarrhoea (TD). Development of a clinical prediction rule assessing the aetiology of TD may help identify episodes of bacterial diarrhoea and limit inappropriate antibiotic use. We aimed to identify predictors of bacterial diarrhoea among clinical, demographic and weather variables, as well as to develop and cross-validate a parsimonious predictive model.<h4>M ...[more]

PMID: 35134202

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Project description:IntroductionTravellers' diarrhoea (TD) continues to be the most common travel-related medical event in international travellers. Updated incidence and risk factor data will improve pre-travel medical advice for travellers from high-income countries (HICs), providing an opportunity for disease prevention and appropriate disease management.MethodsA systematic search for cohort studies of TD incidence published between 1 January 1997 and 2 March 2023 was performed using Ovid Medline, SCOPUS and Google Scholar databases. Study quality was assessed with a modified Newcastle-Ottawa Scale (NOS). We extracted incidence data for adults travelling less than 100 days from HIC and available risk factor data. The overall random-effects pooled incidence and the corresponding 95% confidence intervals (95% CI) were estimated. Heterogeneity was assessed using the I2 statistic, tau and the 95% prediction intervals. Subgroup analyses were conducted to identify the sources of heterogeneity. Risk factor studies were reviewed qualitatively and described.ResultsTen studies were included in the meta-analysis, containing 8478 participants. Two of the studies measured as high quality and eight as good quality as assessed by the modified NOS. The TD incidence was 36.1% (95% CI 24-41%; I2 94%), with a prediction interval ranging from 20.3 to 55.8%. The pooled incidence of mild, moderate and severe TD was 23.6, 8.1 and 2.9%, respectively. Subgroup analysis showed that the incidence increased with increasing average data collection period. Risk factors for TD in travellers from HIC identified include younger age, longer travel periods, low and middle-income destinations, travelling for tourism, backpacking travel styles and pre-travel health status.ConclusionIt is estimated that between 20 and 56% of international travellers can expect to develop TD in travel of under 100 days. While most cases are mild, ~3% of all travellers will experience a disease that prevents usual activities or requires medical attention.

Project description:Backgroundtravellers' diarrhoea (TD) is frequently reported with incidence up to 40% in high-risk destinations. Previous studies showed that the number of loose stools alone is inadequate to holistically predict the severity of TD. To improve the prediction of prognosis and to optimize treatments, a simple risk-based clinical severity classification has been developed.Methodspooled baseline data of signs and symptoms and number of loose stools from 1098 subjects enrolled in two double-blind Phase 3 trials of rifamycin-SV were analyzed with correlation, multiple correspondence analyses, prognostic factor criteria, and Contal and O'Quigley method to generate a TD severity classification (mild, moderate and severe). The relative importance of this classification on resolution of TD was assessed by Cox proportional model hazard model on the time to last unformed stool (TLUS).Resultsthe analysis showed that TLUS were longer for the severe [hazard ratio (HR) 0.24; P < 0.001; n = 173] and moderate (HR 0.54; P = 0.0272; n = 912) vs mild. Additionally, when the treatment assigned in the studies was investigated in the severity classification, the results yielded that rifamycin-SV significantly shortened TLUS vs placebo for all subjects (HR 1.9; P = 0.0006), severe (HR 5.9; P = 0.0232) and moderate (HR 1.7; P = 0.0078) groups and was as equally efficacious as ciprofloxacin for all subjects, moderate and severe groups (HRs: 0.962, 0.9, 1.2; all P = NS, respectively). When reassessed by this classification, rifamycin-SV showed consistent efficacy with the Phase 3 studies.Conclusionsthis newly developed TD clinical severity classification demonstrated strong prognostic value and clinical utility by combining patients' multiple signs and symptoms of enteric infection and number of loose stools to provide a holistic assessment of TD. By expanding on the current classification by incorporating patient reported outcomes in addition to TLUS, a classification like the one developed, may help optimize patient selection for future clinical studies.

Project description:BackgroundAcute gastroenteritis (AGE) is a major medical condition for travellers worldwide, particularly travellers to low- and middle-income countries. Norovirus (NoV) is the most common cause of viral AGE in older children and adults, but data on prevalence and impact amongst travellers is limited.MethodsProspective, multi-site, observational cohort study conducted 2015-2017, amongst adult international travellers from the US and Europe to areas of moderate to high risk of travel-acquired AGE. Participants provided self-collected pre-travel stool samples and self-reported AGE symptoms whilst travelling. Post-travel stool samples were requested from symptomatic subjects and a sample of asymptomatic travellers within 14 days of return. Samples were tested for NoV by RT-qPCR, genotyped if positive and tested for other common enteric pathogens by Luminex xTAG GPP.ResultsOf the 1109 participants included, 437 (39.4%) developed AGE symptoms resulting in an overall AGE incidence of 24.7 per 100 person-weeks [95% confidence interval (CI): 22.4; 27.1]. In total, 20 NoV-positive AGE cases (5.2% of those tested) were identified at an incidence of 1.1 per 100 person-weeks (95% CI: 0.7; 1.7). NoV-positive samples belonged mostly to genogroup GII (18, 85.7%); None of the 13 samples sequenced belonged to genotype GII.4. Clinical severity of AGE was higher for NoV-positive than for NoV-negative cases (mean modified Vesikari Score 6.8 vs 4.9) with more cases classified as severe or moderate (25% vs 6.8%). In total, 80% of NoV-positive participants (vs 38.9% in NoV-negative) reported at least moderate impact on travel plans.ConclusionsAGE is a prevalent disease amongst travellers with a small proportion associated with NoV. Post-travel stool sample collection timing might have influenced the low number of NoV cases detected; however, NoV infections resulted in high clinical severity and impact on travel plans. These results may contribute to targeted vaccine development and the design of future studies on NoV epidemiology.

Project description:Coccidioidomycosis (Valley fever) is a disease caused by the fungal pathogens Coccidioides immitis and Coccidioides posadasii that are endemic to the southwestern United States and parts of Mexico and South America. Throughout the range where the pathogens are endemic, there are seasonal patterns of infection rates that are associated with certain climatic variables. Previous studies that looked at annual and monthly relationships of coccidioidomycosis and climate suggest that infection numbers are linked with precipitation and temperature fluctuations; however, these analytic methods may miss important nonlinear, nonmonotonic seasonal relationships between the response (Valley fever cases) and explanatory variables (climate) influencing disease outbreaks. To improve our current knowledge and to retest relationships, we used case data from three counties of high endemicity in southern Arizona paired with climate data to construct a generalized additive statistical model that explores which meteorological parameters are most useful in predicting Valley fever incidence throughout the year. We then use our model to forecast the pattern of Valley fever cases by month. Our model shows that maximum monthly temperature, average PM10, and total precipitation 1 month prior to reported cases (lagged model) were all significant in predicting Valley fever cases. Our model fits Valley fever case data in the region of endemicity of southern Arizona and captures the seasonal relationships that predict when the public is at higher risk of being infected. This study builds on and retests relationships described by previous studies regarding climate variables that are important for predicting risk of infection and understanding this fungal pathogen. IMPORTANCE The inhalation of environmental infectious propagules from the fungal pathogens Coccidioides immitis and Coccidioides posadasii by susceptible mammals can result in coccidioidomycosis (Valley fever). Arizona is known to be a region where the pathogen is hyperendemic, and reported cases are increasing throughout the western United States. Coccidioides spp. are naturally occurring fungi in arid soils. Little is known about ecological factors that influence the growth of these fungi, and a higher environmental burden may result in increases in human exposure and therefore case rates. By examining case and climate data from Arizona and using generalized additive statistical models, we were able to examine the relationship between disease outbreaks and climatic variables and predict seasonal time points of increased infection risk.

Project description:ObjectivesThis report estimates the risk of COVID-19 importation and secondary transmission associated with a modified quarantine programme in Canada.Design and participantsProspective analysis of international asymptomatic travellers entering Alberta, Canada.InterventionsAll participants were required to receive a PCR COVID-19 test on arrival. If negative, participants could leave quarantine but were required to have a second test 6 or 7 days after arrival. If the arrival test was positive, participants were required to remain in quarantine for 14 days.Main outcome measuresProportion and rate of participants testing positive for COVID-19; number of cases of secondary transmission.ResultsThe analysis included 9535 international travellers entering Alberta by air (N=8398) or land (N=1137) that voluntarily enrolled in the Alberta Border Testing Pilot Programme (a subset of all travellers); most (83.1%) were Canadian citizens. Among the 9310 participants who received at least one test, 200 (21.5 per 1000, 95% CI 18.6 to 24.6) tested positive. Sixty-nine per cent (138/200) of positive tests were detected on arrival (14.8 per 1000 travellers, 95% CI 12.5 to 17.5). 62 cases (6.7 per 1000 travellers, 95% CI 5.1 to 8.5; 31.0% of positive cases) were identified among participants that had been released from quarantine following a negative test result on arrival. Of 192 participants who developed symptoms, 51 (26.6%) tested positive after arrival. Among participants with positive tests, four (2.0%) were hospitalised for COVID-19; none required critical care or died. Contact tracing among participants who tested positive identified 200 contacts; of 88 contacts tested, 22 were cases of secondary transmission (14 from those testing positive on arrival and 8 from those testing positive thereafter). SARS-CoV-2 B.1.1.7 lineage was not detected in any of the 200 positive cases.Conclusions21.5 per 1000 international travellers tested positive for COVID-19. Most (69%) tested positive on arrival and 31% tested positive during follow-up. These findings suggest the need for ongoing vigilance in travellers testing negative on arrival and highlight the value of follow-up testing and contact tracing to monitor and limit secondary transmission where possible.

Project description:BackgroundThe wellbeing and safety of international tourists is a paramount concern for governments and stakeholders. Mortality among travellers and the causes of death serve as a significant metric of destination safety. We describe the epidemiology and causes of death among international travellers in Peru.MethodsData retrieved from the Peruvian government's deaths certificates registry included all non-residents who died between January 2017 and December 2021. We analysed the national incidence and causes of death among international travellers in Peru. Causes of death were classified into non-communicable diseases (NCD), communicable diseases and injuries. We classified fatalities according to the existence of preventive measures that could be provided during the travel medicine consultation to decrease the risk.ResultsWe obtained records from 1514 deaths among international travellers (973 males, 64%). The incidence increased from 0.2 deaths per 10 000 travellers in 2017 to 9.9 in 2021. NCDs were the most common causes of death (n = 560, 37%), followed by communicable diseases (n = 487, 32%), and injuries (n = 321, 21%). Causes of death were unknown in 9.7% of the records. The leading causes of death in these categories were cancer, cardiovascular disease, COVID-19 and trauma. We found similar sex distribution of NCDs in travellers aged >50 years and higher rates of communicable diseases among males across all ages. Injury-associated deaths were significantly higher among males aged 18-29 years (P < 0.001) compared with other sex-age groups. We estimated that for 57.7% of deaths risk could have been decreased through pre-travel advice.ConclusionRates of deaths among travellers to Peru increased over time. Most deaths were due to NCDs, followed by communicable diseases and injuries. Pre-travel medical optimization and effective advice focused on age-sex and destination specific risks could reduce risk among travellers. Increased awareness among travel medicine practitioners and improvement of emergency medical response systems in Peru could decrease mortality.

Dataset Information

Weather variables as important clinical predictors of bacterial diarrhoea among international travellers.

Background

Methods

Results

Conclusions

Publications

Weather variables as important clinical predictors of bacterial diarrhoea among international travellers.

Similar Datasets

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