Incidence Of Infectious Diarrhea Research Articles

Association between hydrometeorological conditions and infectious diarrhea in mainland China: a spatiotemporal modeling study

Infectious diarrhea imposes substantial disease burden in China, with local climate identified as a key risk factor. In this study, we aimed to explore the association between hydrometeorological conditions and the incidence of infectious diarrhea, and investigate the modification effect of urbanization, which remained unclear previously. Monthly data were collected from 1 January 2021 to 31 December 2022 from each city of mainland China on cases of infectious diarrhea other than cholera, dysentery, typhoid and paratyphoid (i.e. other infectious diarrhea, OID), temperature and precipitation. We used Palmer drought severity index (PDSI) to represent local hydrometeorological conditions (dry and wet). A spatiotemporal Bayesian hierarchical model combined with distributed lag nonlinear model was specified to explore the association between PDSI and the relative risk of OID. The effect size of hydrometeorological conditions at different urbanization levels were quantified through a linear interaction term. A total of 1999 947 OID cases were included. There was a N-shaped cumulative association between PDSI and OID incidence over a maximum lag of 4 months. The effect of extreme dry conditions persisted over lag 1–3 months and peaked at the 2-month lag (RR = 2.67, 95%CI: 2.44–2.91). By contrast, the relative risk of OID increased immediately under extreme wet conditions (RR = 1.97, 95%CI: 1.68–2.32 at lag 0 month). Children and the older population were particularly susceptible to extreme dry and wet conditions, respectively. Areas with lower urbanization rate, healthcare resources and economic levels, and higher population density showed a higher risk of OID related to extreme dry conditions. While the modification effects of these urbanization characteristics were limited for extreme wet conditions. There was a nonlinear and lagged association between hydrometeorological conditions and the incidence of OID in mainland China, which may be modified in diverse patterns by urbanization indicators. Our findings will provide valuable reference for better prevention and control of OID.

Predicting the incidence of infectious diarrhea with symptom surveillance data using a stacking-based ensembled model

BackgroundInfectious diarrhea remains a major public health problem worldwide. This study used stacking ensemble to developed a predictive model for the incidence of infectious diarrhea, aiming to achieve better prediction performance.MethodsBased on the surveillance data of infectious diarrhea cases, relevant symptoms and meteorological factors of Guangzhou from 2016 to 2021, we developed four base prediction models using artificial neural networks (ANN), Long Short-Term Memory networks (LSTM), support vector regression (SVR) and extreme gradient boosting regression trees (XGBoost), which were then ensembled using stacking to obtain the final prediction model. All the models were evaluated with three metrics: mean absolute percentage error (MAPE), root mean square error (RMSE), and mean absolute error (MAE).ResultsBase models that incorporated symptom surveillance data and weekly number of infectious diarrhea cases were able to achieve lower RMSEs, MAEs, and MAPEs than models that added meteorological data and weekly number of infectious diarrhea cases. The LSTM had the best prediction performance among the four base models, and its RMSE, MAE, and MAPE were: 84.85, 57.50 and 15.92%, respectively. The stacking ensembled model outperformed the four base models, whose RMSE, MAE, and MAPE were 75.82, 55.93, and 15.70%, respectively.ConclusionsThe incorporation of symptom surveillance data could improve the predictive accuracy of infectious diarrhea prediction models, and symptom surveillance data was more effective than meteorological data in enhancing model performance. Using stacking to combine multiple prediction models were able to alleviate the difficulty in selecting the optimal model, and could obtain a model with better performance than base models.

Diagnostic performance of a multiplexed gastrointestinal PCR panel for identifying diarrheal pathogens in children undergoing hematopoietic stem cell transplant.

Diarrhea is a common complication of hematopoietic stem cell transplantation (HSCT) and is associated with substantial morbidity, but its etiology is often unknown. Etiologies of diarrhea in this population include infectious causes, chemotherapy- or medication-induced mucosal injury and graft-versus-host disease (GVHD). Distinguishing these potential causes of diarrhea is challenging since diarrheal symptoms are often multifactorial, and the etiologies often overlap in transplant patients. The objectives of this study were to evaluate whether the FilmArray gastrointestinal (GI) panel would increase diagnostic yield and the degree to which pre-transplantation colonization predicts post-transplantation infection. From November 2019 to February 2021, a total of 158 patients undergoing HSCT were prospectively included in the study. Stool specimens were obtained from all HSCT recipients prior to conditioning therapy, 28 ± 7days after transplantation and at any new episode of diarrhea. All stool samples were tested by the FilmArray GI panel and other clinical microbiological assays. The primary cause of post-transplantation diarrhea was infection (57/84, 67.86%), followed by medication (38/84, 45.24%) and GVHD (21/84, 25.00%). Ninety-five of 158 patients were colonized with at least one gastrointestinal pathogen before conditioning therapy, and the incidence of infectious diarrhea was significantly higher in colonized patients (47/95, 49.47%) than in non-colonized patients (10/63, 15.87%) (P < 0.001). Fourteen of 19 (73.68%) patients who were initially colonized with norovirus pre-transplantation developed a post-transplantation norovirus infection. Twenty-four of 62 (38.71%) patients colonized with Clostridium difficile developed a diarrheal infection. In addition, FilmArray GI panel testing improved the diagnostic yield by almost twofold in our study (55/92, 59.78% vs. 30/92, 32.61%). Our data show that more than half of pediatric patients who were admitted for HSCT were colonized with various gastrointestinal pathogens, and more than one-third of these pathogens were associated with post-transplantation diarrhea. In addition, the FilmArray GI panel can increase the detection rate of diarrheal pathogens in pediatric HSCT patients, but the panel needs to be optimized for pathogen species, and further studies assessing its clinical impact and cost-effectiveness in this specific patient population are also needed.

Infectious Diarrhea Risks as a Public Health Emergency in Floods; a Systematic Review and Meta-Analysis.

Infectious diarrhea, a significant global health challenge, is exacerbated by flooding, a consequence of climate change and environmental disruption. This comprehensive study aims to quantify the association between flooding events and the incidence of infectious diarrhea, considering diverse demographic, environmental, and pathogen-specific factors. In this systematic review and meta-analysis, adhering to PROSPERO protocol (CRD42024498899), we evaluated observational studies from January 2000 to December 2023. The analysis incorporated global data from PubMed, Scopus, Embase, Web of Science, and ProQuest, focusing on the relative risk (RR) of diarrhea post-flooding. The study encompassed diverse variables like age, sex, pathogen type, environmental context, and statistical modeling approaches. The meta-analysis, involving 42 high-quality studies, revealed a substantial increase (RR = 1.40, 95% CI [1.29-1.52]) in the incidence of diarrhea following floods. Notably, bacterial and parasitic diarrheas demonstrated higher RRs (1.82 and 1.35, respectively) compared to viral etiologies (RR = 1.15). A significant sex disparity was observed, with women exhibiting a higher susceptibility (RR = 1.55) than men (RR = 1.35). Adults (over 15 years) faced a greater risk than younger individuals, highlighting age-dependent vulnerability. This extensive analysis confirms a significant correlation between flood events and increased infectious diarrhea risk, varying across pathogens and demographic groups. The findings highlight an urgent need for tailored public health interventions in flood-prone areas, focusing on enhanced sanitation, disease surveillance, and targeted education to mitigate this elevated risk. Our study underscores the critical importance of integrating flood-related health risks into global public health planning and climate change adaptation strategies.

Infectious diarrhea after allogeneic hematopoietic cell transplantation assessed by a multiplex polymerase chain reaction assay

ObjectivesTo determine the incidence of infectious diarrhea after allogeneic hematopoietic cell transplantation (HCT) using a multiplex polymerase chain reaction assay and assess risk factors for developing infectious diarrhea. MethodsThis was a single-center retrospective study of 140 consecutive allogeneic HCT recipients. Infectious diarrhea was assessed using a laboratory-developed multiplex polymerase chain reaction the first year after transplantation. ResultsThe incidence rate of infectious diarrhea episodes was 47 per 100 person-years, with the highest rate observed in the pre-engraftment phase. Most episodes were seen as nosocomial infections (38%) and most affected patients (82%) had only one episode of infectious diarrhea. The cumulative incidence of at least one episode of infectious diarrhea was 32% after 1 year. Nonrelapse mortality was higher in transplant recipients with at least one episode of infectious diarrhea (hazard ratio (HR) 2.02, 95% CI = 1.07-3.80). The most frequently observed pathogens were Clostridium difficile, adenovirus, Enteropathogenic Escherichia coli, and Campylobacter jejuni. Patients with acute lower gastrointestinal graft-vs-host disease stage 3 or 4 (HR 3.68, 95% CI = 1.57-8.63) conferred a higher risk for a first infectious diarrhea episode. ConclusionInfectious diarrhea after allogeneic HCT was seen in about one-third of the patients, mostly as nosocomial infection in the pre-engraftment phase.

Spatiotemporal impact of non-pharmaceutical interventions against COVID-19 on the incidence of infectious diarrhea in Xi'an, China.

Non-pharmaceutical interventions (NPIs) against COVID-19 may prevent the spread of other infectious diseases. Our purpose was to assess the effects of NPIs against COVID-19 on infectious diarrhea in Xi'an, China. Based on the surveillance data of infectious diarrhea, and the different periods of emergence responses for COVID-19 in Xi'an from 2011 to 2021, we applied Bayesian structural time series model and interrupted time series model to evaluate the effects of NPIs against COVID-19 on the epidemiological characteristics and the causative pathogens of infectious diarrhea. A total of 102,051 cases of infectious diarrhea were reported in Xi'an from 2011 to 2021. The Bayesian structural time series model results demonstrated that the cases of infectious diarrhea during the emergency response period was 40.38% lower than predicted, corresponding to 3,211 fewer cases, during the COVID-19 epidemic period of 2020-2021. The reduction exhibited significant variations in the demography, temporal and geographical distribution. The decline in incidence was especially evident in children under 5-years-old, with decreases of 34.09% in 2020 and 33.99% in 2021, relative to the 2017-2019 average. Meanwhile, the incidence decreased more significantly in industrial areas. NPIs against COVID-19 were associated with short- and long-term reductions in the incidence of infectious diarrhea, and this effect exhibited significant variations in epidemiological characteristics.

Efeito de um composto de leveduras na incidência de diarreia em bezerras criadas em diferentes sistemas de alojamento

O objetivo do presente estudo foi avaliar o efeito da suplementação de um produto composto de cultura de levedura e levedura enzimaticamente hidrolisada na incidência de diarreia e no desenvolvimento corporal de bezerras leiteiras submetidas à diferentes sistemas de alojamento. Foram usadas cento e dezenove bezerras mantidas em dois sistemas de alojamento e divididas aleatoriamente em dois grupos: grupo levedura (n = 62, 36 ao ar livre e 26 no curral) e grupo controle (n = 57, 30 ao ar livre e 27 no curral). O grupo levedura foi tratado com 8 ml de cultura de levedura / animal, que foi administrada oralmente uma vez por dia durante 42 dias. As medidas zootécnicas foram analisadas e a incidência de diarreia infecciosa foi monitorada, também foram realizadas coletas de sangue e fezes. Os dados foram submetidos à análise de variância por medidas repetidas do Software SAS, Tukey’s HSD e Teste Qui quadrado, sendo considerado diferença estatística (p≤0,05). Os animais do grupo controle criados ao ar livre apresentaram maior incidência de diarreia (80,00%) quando comparado aos animais do grupo tratamento (55,55%) (p=0,03). O período de maior incidência de diarreia (96,92%) foi nos primeiros 15 dias de vida (p

Forecasting incidence of infectious diarrhea using random forest in Jiangsu Province, China

BackgroundInfectious diarrhea can lead to a considerable global disease burden. Thus, the accurate prediction of an infectious diarrhea epidemic is crucial for public health authorities. This study was aimed at developing an optimal random forest (RF) model, considering meteorological factors used to predict an incidence of infectious diarrhea in Jiangsu Province, China.MethodsAn RF model was developed and compared with classical autoregressive integrated moving average (ARIMA)/X models. Morbidity and meteorological data from 2012 to 2016 were used to construct the models and the data from 2017 were used for testing.ResultsThe RF model considered atmospheric pressure, precipitation, relative humidity, and their lagged terms, as well as 1–4 week lag morbidity and time variable as the predictors. Meanwhile, a univariate model ARIMA (1,0,1)(1,0,0)52 (AIC = − 575.92, BIC = − 558.14) and a multivariable model ARIMAX (1,0,1)(1,0,0)52 with 0–1 week lag precipitation (AIC = − 578.58, BIC = − 578.13) were developed as benchmarks. The RF model outperformed the ARIMA/X models with a mean absolute percentage error (MAPE) of approximately 20%. The performance of the ARIMAX model was comparable to that of the ARIMA model with a MAPE reaching approximately 30%.ConclusionsThe RF model fitted the dynamic nature of an infectious diarrhea epidemic well and delivered an ideal prediction accuracy. It comprehensively combined the synchronous and lagged effects of meteorological factors; it also integrated the autocorrelation and seasonality of the morbidity. The RF model can be used to predict the epidemic level and has a high potential for practical implementation.

Impacts of Meteorological Factors on the Incidence of Infectious Diarrhea in Urban Shanghai, China

Impacts of Meteorological Factors on the Incidence of Infectious Diarrhea in Urban Shanghai, China

Effectiveness of probiotics in reducing the incidence of Clostridium difficile-associated diarrhea in elderly patients: a systematic review.

Clostridium difficile bacteria are a leading cause of infectious diarrhea. This is an anaerobic, gram-positive and spore-forming rod responsible for significant morbidity and mortality, especially among elderly hospitalized patients. Standard management of C. difficile-associated diarrhea (CDAD) consists of discontinuing a causative antibiotic, correcting fluid-electrolytes imbalance and initiating an antibiotic treatment for CDAD. Alternative approaches for prevention of CDAD include probiotics. This systematic review will provide a comprehensive, unbiased summary of the available research on the effectiveness of probiotics in decreasing the incidence of infectious diarrhea in elderly hospitalized patients. To conduct a systematic review to determine the best available evidence related to the effectiveness of probiotics in the prevention of CDAD in elderly hospitalized patients. The review question was: are probiotics effective in decreasing the incidence of CDAD in elderly hospitalized patients? The current review included studies of participants who were aged 60 years and more and who were residents of acute- and post-acute care facilities undergoing or planning to undergo antibiotic treatment for the management of any infectious conditions, except CDAD. The current review included studies that evaluated the effectiveness of probiotics for prevention of CDAD in elderly hospitalized patients in acute- and post-acute care settings compared to usual care. The current review included studies examining the following outcome measures: incidence or relapse of CDAD. Cases of CDAD were defined by presence of diarrhea and verified by positive results for stool enzyme immunoassay for toxins A and B. The current review included only experimental study designs including randomized controlled trials. The search strategy included studies published in English between 1978, when the first case of CDAD was reported, and 2015. Papers selected for retrieval were assessed by two independent reviewers for methodological quality prior to inclusion in the review using standardized critical appraisal instruments from the Joanna Briggs Institute (JBI). Data were extracted from papers included in the review using the standardized data extraction tool from the JBI Meta-Analysis of Statistics Assessment and Review Instrument. The data extracted included specific details about the interventions, populations, study methods and outcomes of significance to the review question and specific objectives. Quantitative data were pooled using statistical meta-analysis. Effect sizes were expressed as odds ratios, and their 95% confidence intervals were calculated to determine if probiotic treatment was superior to placebo in reducing CDAD incidence. Heterogeneity was assessed using the standard I statistic. Five studies were included in the review. The individual study results were conflicting, including non-significant results for four studies and statistically significant results in one that demonstrated fewer cases of CDAD among patients receiving probiotics compared to placebo. The meta-analysis finding indicated that there was no statistically significant difference in CDAD incidence in elderly hospitalized patients taking probiotics when compared to a placebo. Probiotics were not found to be more effective than placebo for reducing CDAD incidence in elderly hospitalized patients. However, studies that demonstrate improved outcomes must be examined to determine future needs for research. Studies varied with regard to the dose, frequency, method of administration (probiotic drinks versus capsule), length of administration and the number of strains of bacteria administered. Further studies are needed to evaluate the effectiveness of probiotics for CDAD prevention in this population. Clinical trials with evidence-based administration methods and meta-analyses that pool the results of studies with congruent methodologies are needed to enable conclusions to be drawn on the effectiveness of probiotic administration for CDAD prevention.

Artificial neural networks for infectious diarrhea prediction using meteorological factors in Shanghai (China)

Infectious diarrhea is an important public health problem around the world. Meteorological factors have been strongly linked to the incidence of infectious diarrhea. Therefore, accurately forecast the number of infectious diarrhea under the effect of meteorological factors is critical to control efforts. In recent decades, development of artificial neural network (ANN) models, as predictors for infectious diseases, have created a great change in infectious disease predictions. In this paper, a three layered feed-forward back-propagation ANN (BPNN) model trained by Levenberg–Marquardt algorithm was developed to predict the weekly number of infectious diarrhea by using meteorological factors as input variable. The meteorological factors were chosen based on the strongly relativity with infectious diarrhea. Also, as a comparison study, the support vector regression (SVR), random forests regression (RFR) and multivariate linear regression (MLR) also were applied as prediction models using the same dataset in addition to BPNN model. The 5-fold cross validation technique was used to avoid the problem of overfitting in models training period. Further, since one of the drawbacks of ANN models is the interpretation of the final model in terms of the relative importance of input variables, a sensitivity analysis is performed to determine the parametric influence on the model outputs. The simulation results obtained from the BPNN confirms the feasibility of this model in terms of applicability and shows better agreement with the actual data, compared to those from the SVR, RFR and MLR models. The BPNN model, described in this paper, is an efficient quantitative tool to evaluate and predict the infectious diarrhea using meteorological factors.

HIV-related diarrhea is multifactorial and fat malabsorption is commonly present, independent of HAART

OBJECTIVE: Highly active antiretroviral therapy (HAART) has significantly decreased the incidence of infectious diarrhea affecting HIV-infected patients. Still, diarrhea remains a common symptom in HIV. We sought to determine the incidence of fat malabsorption as a cause of diarrhea in HIV patients receiving non-HAART (nucleoside analog only) and HAART (protease inhibitor-containing) antiretroviral regimens. METHODS: From June, 1995, to April, 1999, 88 HIV-infected patients underwent evaluation for diarrhea, which included endoscopy. We examined the incidence of fat malabsorption with a 24-h stool collection for fecal fat in a cohort of these patients (N = 33). Patients were divided into two groups, those receiving protease inhibitor-containing HAART and those receiving less intensive, nucleoside analog-only, non-HAART regimens. RESULTS: Thirty of 33 patients (90.9%) had fat malabsorption. Twenty of 21 patients not receiving HAART (95.2%) had fat malabsorption with a mean of 34 ± 38 g of stool fat and a mean stool weight of 797 ± 454 g. Ten of 12 patients receiving HAART (83.3%) had fat malabsorption with a mean of 46 ± 86 g of stool fat and a mean stool weight of 800 ± 647 g. Stool weight correlated with the degree of fat malabsorption ( R = 0.77). CONCLUSION: Fat malabsorption represents a commonly undiagnosed entity in HIV-infected patients with diarrhea, whether or not they are receiving HAART therapy. Fecal fat determination should be considered a routine part of the diagnostic workup of HIV-infected patients experiencing diarrhea.

REDUCTION OF DIARRHEAL ILLNESS FOLLOWING ADMINISTRATION OFLACTOBACILLUS PLANTARUM 299V IN A DAYCARE FACILITY

102 Rationale:Lactobacillus plantarum 299v is one of several recently described probiotic bacteria. These organisms by definition result in specific health benefits such as disease prevention or amelioration. This particular probiotic has been shown to adhere to mucosal epithelial cells and competitively inhibit the attachment of pathogenic organisms such asE. coli in cell culture systems. It also reduces gut inflammation in a variety of animal models. Hypothesis: We hypothesized that this organism might be useful in preventing the spread of diarrheal disease in a daycare setting. Methods: We administered 1010 colony-forming units per day in fermented oatmeal powder to 71 children attending day care in a region of Brazil with a high incidence of infectious diarrhea. Seventy-two children were given non-fermented oatmeal powder as a control. Number of diarrheal days was measured in both groups. Diarrhea was defined as more than 3 loose watery stools in 24 hours. All children were monitored for signs and symptoms of infection by research staff present on a daily basis. After the first month, the dose was decreased to every other day, and was given weekly the third month. All children were between the ages of six months and three years and all meals were consumed in the day care. There were no differences in age or sex between active and control groups. Results: While there were no differences in diarrheal days between treatment and control groups, 42 diarrheal days occurred during the first month and only 5 the second month in the entire group. The incidence of respiratory infections also decreased from 123 days the first month to 34 cases the second month. These differences were highly unusual, could not be explained by seasonal variation, and were contrary to the experiences of prior years. Data on the third month is presently being collected. Conclusion: We speculate that colonization with the probioticLactobacillus plantarum 299v in half the children in this daycare setting reduced the dissemination of infectious diarrhea in this highly susceptible population.