Epidemiology of infectious diarrhoea and the relationship with etiological and meteorological factors in Jiangsu Province, China

Combatting infectious diarrhea: innovations in treatment and vaccination strategies

INTRODUCTION

The escalating prevalence of infectious diseases is an important cause of concern in society. Particularly in several developing countries, infectious diarrhea poses a major problem, with a high fatality rate, especially among young children. The condition is divided into four classes, namely, acute diarrhea, invasive diarrhea, acute bloody diarrhea, and chronic diarrhea. Various pathogenic agents, such as bacteria, viruses, protozoans, and helminths, contribute to the onset of this condition.

AREAS COVERED

The review discusses the scenario of infectious diarrhea, the prevalent types, as well as approaches to management including preventive, therapeutic, and vaccination strategies. The vaccination techniques are extensively discussed including the available vaccines, their advantages as well as limitations.

EXPERT OPINION

There are several approaches available to develop new-improved vaccines. In addition, route of immunization is important and aerosols/nasal sprays, oral route, skin patches, powders, and liquid jets to minimize needles can be used. Plant-based vaccines, such as rice, might save packing and refrigeration costs by being long-lasting, non-refrigerable, and immunogenic. Future research should utilize predetermined PCR testing intervals and symptom monitoring to identify persistent pathogens after therapy and symptom remission.

Natural and socio-environmental factors contribute to the transmissibility of COVID-19: evidence from an improved SEIR model

COVID-19 has ravaged Brazil, and its spread showed spatial heterogeneity. Changes in the environment have been implicated as potential factors involved in COVID-19 transmission. However, considerable research efforts have not elucidated the risk of environmental factors on COVID-19 transmission from the perspective of infectious disease dynamics. The aim of this study is to model the influence of the environment on COVID-19 transmission and to analyze how the socio-ecological factors affecting the probability of virus transmission in 10 states dramatically shifted during the early stages of the epidemic in Brazil. First, this study used a Pearson correlation to analyze the interconnection between COVID-19 morbidity and socio-ecological factors and identified factors with significant correlations as the dominant factors affecting COVID-19 transmission. Then, the time-lag effect of dominant factors on the morbidity of COVID-19 was investigated by constructing a distributed lag nonlinear model and standard two-stage meta-analytic model, and the results were considered in the improved SEIR model. Lastly, a machine learning method was introduced to explore the nonlinear relationship between the environmental propagation probability and socio-ecological factors. By analyzing the impact of environmental factors on virus transmission, it can be found that population mobility directly caused by human activities had a greater impact on virus transmission than temperature and humidity. The heterogeneity of meteorological factors can be accounted for by the diverse climate patterns in Brazil. The improved SEIR model was adopted to explore the interconnection of COVID-19 transmission and the environment, which revealed a new strategy to probe the causal links between them.

Short-Term Effects of Climate Variability on Childhood Diarrhoea in Bangladesh: Multi-Site Time-Series Regression Analysis

The aim of this study was to estimate the effects of climate on childhood diarrhoea hospitalisations across six administrative divisions in Bangladesh and to provide scientific evidence for local health authorities for disease control and prevention. Fortnightly hospital admissions (August/2013-June/2017) for diarrhoea in children under five years of age, and fortnightly average maximum temperature, relative humidity and rainfall recordings for six administrative divisions were modelled using negative binomial regression with distributed lag linear terms. Flexible spline functions were used to adjust models for seasonality and long-term trends. During the study period, 25,385 diarrhoea cases were hospitalised. Overall, each 1 °C rise in maximum temperature increased diarrhoea hospitalisations by 4.6% (IRR = 1.046; 95% CI, 1.007-1.088) after adjusting for seasonality and long-term trends in the unlagged model. Using lagged effects of maximum temperature, and adjusting for relative humidity and rainfall for each of the six administrative divisions, the relationship between maximum temperature and diarrhoea hospitalisations varied between divisions, with positive and negative effect estimates. The temperature-diarrhoea association may be confounded by seasonality and long-term trends. Our findings are a reminder that the effects of climate change may be heterogeneous across regions, and that tailored diarrhoea prevention strategies need to consider region-specific recommendations rather than relying on generic guidelines.

Exploring the Association between Ambient Temperature and Daily Hospital Admissions for Diarrhea in Mopani District, Limpopo Province, South Africa

Diarrhea contributes significantly to global morbidity and mortality. There is evidence that diarrhea prevalence is associated with ambient temperature. This study aimed to determine if there was an association between ambient temperature and diarrhea at a rural site in South Africa. Daily diarrheal hospital admissions (2007 to 2016) at two large district hospitals in Mopani district, Limpopo province were compared to average daily temperature and apparent temperature (Tapp, 'real-feel' temperature that combined temperature, relative humidity, and wind speed). Linear regression and threshold regression, age-stratified to participants ≤5 years and >5 years old, considered changes in daily admissions by unit °C increase in Tapp. Daily ranges in ambient temperature and Tapp were 2-42 °C and -5-34 °C, respectively. For every 1 °C increase in average daily temperature, there was a 6% increase in hospital admissions for diarrhea for individuals of all ages (95% CI: 0.04-0.08; p < 0.001) and a 4% increase in admissions for individuals older than 5 years (95% CI: 0.02-0.05; p < 0.001). A positive linear relationship between average daily Tapp and all daily diarrheal admissions for children ≤5 years old was not statistically significant (95% CI: -0.00-0.03; p = 0.107). Diarrhea is common in children ≤5 years old, however, is more likely triggered by factors other than temperature/Tapp, while it is likely associated with increased temperature in individuals >5 years old. We are limited by lack of data on confounders and effect modifiers, thus, our findings are exploratory. To fully quantify how temperature affects hospital admission counts for diarrhea, future studies should include socio-economic-demographic factors as well as WASH-related data such as personal hygiene practices and access to clean water.

Effects of Ambient Temperature, Relative Humidity, and Precipitation on Diarrhea Incidence in Surabaya

BACKGROUND

Diarrhea remains a common infectious disease caused by various risk factors in developing countries. This study investigated the incidence rate and temporal associations between diarrhea and meteorological determinants in five regions of Surabaya, Indonesia.

METHOD

Monthly diarrhea records from local governmental health facilities in Surabaya and monthly means of weather variables, including average temperature, precipitation, and relative humidity from Meteorology, Climatology, and Geophysical Agency were collected from January 2018 to September 2020. The generalized additive model was employed to quantify the time lag association between diarrhea risk and extremely low (5th percentile) and high (95th percentile) monthly weather variations in the north, central, west, south, and east regions of Surabaya (lag of 0-2 months).

RESULT

The average incidence rate for diarrhea was 11.4 per 100,000 during the study period, with a higher incidence during rainy season (November to March) and in East Surabaya. This study showed that the weather condition with the lowest diarrhea risks varied with the region. The diarrhea risks were associated with extremely low and high temperatures, with the highest RR of 5.39 (95% CI 4.61, 6.17) in the east region, with 1 month of lag time following the extreme temperatures. Extremely low relative humidity increased the diarrhea risks in some regions of Surabaya, with the highest risk in the west region at lag 0 (RR = 2.13 (95% CI 1.79, 2.47)). Extremely high precipitation significantly affects the risk of diarrhea in the central region, at 0 months of lag time, with an RR of 3.05 (95% CI 2.09, 4.01).

CONCLUSION

This study identified a high incidence of diarrhea in the rainy season and in the deficient developed regions of Surabaya, providing evidence that weather magnifies the adverse effects of inadequate environmental sanitation. This study suggests the local environmental and health sectors codevelop a weather-based early warning system and improve local sanitation practices as prevention measures in response to increasing risks of infectious diseases.

Geographical variation in the effect of ambient temperature on infectious diarrhea among children under 5 years

Understanding the geographical distribution in the association of temperature with childhood diarrhea can assist in formulating effective localized diarrhea prevention practices. This study aimed to identify the geographical variation in terms of temperature thresholds, lag effects, and attributable fraction (AF) in the effects of ambient temperature on Class C Other Infectious Diarrhea (OID) among children <5 years in Jiangsu Province, China. Daily data of OID cases and meteorological variables from 2015 to 2019 were collected. City-specific minimum morbidity temperature (MMT), increasing risk temperature (IRT), maximum risk temperature (MRT), maximum risk lag day (MRD), and lag day duration (LDD) were identified as risk indicators for the temperature-OID relationship using distributed lag non-linear models. The AF of OID incidence due to temperature was evaluated. Multivariable regression was also applied to explore the underlying modifiers of the AF. The geographical distributions of MMT, IRT, and MRT generally decreased with the latitude increment varying between 22.3-34.7 °C, -2.9-18.1 °C, and -6.8-23.2 °C. Considerable variation was shown in the AF ranging from 0.2 to 8.5%, and the AF significantly increased with latitude (95% confidence interval (CI): -3.458, -0.987) and economic status decrement (95% CI: -0.161, -0.019). Our study demonstrated between-city variations in the association of temperature with OID, which should be considered in the localized clinical and public health practices to decrease the incidence of childhood diarrhea.

Evaluation of the transmissibility of norovirus and the effectiveness of prevention and control measures for schools in Jiangsu Province

OBJECTIVE

This study aims to estimate the transmissibility of norovirus outbreaks in schools by different transmission routes, and to evaluate the effects of isolation, school-closure and disinfection measures under different intervention intensities, finally, scientific prevention and control suggestions are proposed.

METHOD

23 outbreaks of norovirus infectious diarrhea occurring in Jiangsu Province's school from 2012-2018 were selected and fitted to the model. The data includes various types of school places and pathogen genotype. A 'SEIAQRW' model with two transmission routes was established. The transmissibility of each outbreak was assessed using effective reproduction number, the efficacy of different intervention measures and intensities were evaluated by calculating the total attack rate and peak incidence.

RESULTS

The mean effective reproduction number of noroviruses was estimated to be 8.92 for the human-to-human route of transmission and 2.19 for the water or food-to-human route of transmission. When all symptomatic cases were isolated, the median peak incidence for both transmission routes both being less than 1.8%. There was a smaller reduction in total attack rate compared to peak incidence, the median total attack rate for the two transmission routes decreased by 17.59% and 42.09%, respectively. When the effect of school-closure or disinfection is more than 90%, the total attack rate and peak incidence in the human-to-human route are reduced by more than 90% compared to no intervention, and the peak incidence in the water or food-to-human routes can be reduced to less than 1.4%, but the reduction in the total attack rate is only 50% or so.

CONCLUSION

Norovirus outbreaks have a high rate of transmission in schools. In the case of norovirus outbreaks, isolation should be complemented by other interventions, and the implementation of high-intensity school closures or disinfection of the external environment can be effective in reducing the spread of the virus.

Floods and diarrheal morbidity: Evidence on the relationship, effect modifiers, and attributable risk from Sichuan Province, China

Background

Although studies have provided the estimates of floods-diarrhoea associations, little is known about the lag effect, effect modification, and attributable risk. Based on Sichuan, China, an uneven socio-economic development province with plateau, basin, and mountain terrains spanning different climatic zones, we aimed to systematically examine the impacts of floods on diarrheal morbidity.

Methods

We retrieved information on daily diarrheal cases, floods, meteorological variables, and annual socio-economic characteristics for 21 cities in Sichuan from January 1, 2017 to December 31, 2019. We fitted time-series Poisson models to estimate the city-specific floods-diarrhoea relation over the lags of 0-14 days, and then pooled them using meta-analysis for cumulative and lag effects. We further employed meta-regression to explore potential effect modifiers and identify effect modification. We calculated the attributable diarrheal cases and fraction of attributable morbidity within the framework of the distributed lag model.

Results

Floods had a significant cumulative association with diarrhoea at the provincial level, but varied by regions and cities. The effects of the floods appeared on the second day after the floods and lasted for 5 days. Floods-diarrhoea relations were modified by three effect modifiers, with stronger flood effects on diarrhoea found in areas with higher air pressure, lower diurnal temperature range, or warmer temperature. Floods were responsible for advancing a fraction of diarrhoea, corresponding to 0.25% within the study period and 0.48% within the flood season.

Conclusions

The impacts imposed by floods were mainly distributed within the first week. The floods-diarrhoea relations varied by geographic and climatic conditions. The diarrheal burden attributable to floods is currently low in Sichuan, but this figure could increase with the exposure more intensive and the effect modifiers more detrimental in the future. Our findings are expected to provide evidence for the formulation of temporal- and spatial-specific strategies to reduce potential risks of flood-related diarrhoea.

Associations between long-term drought and diarrhea among children under five in low- and middle-income countries

Climate change is projected to intensify drought conditions, which may increase the risk of diarrheal diseases in children. We constructed log-binomial generalized linear mixed models to examine the association between diarrhea risk, ascertained from global-scale nationally representative Demographic and Health Surveys, and drought, represented by the standardized precipitation evapotranspiration index, among children under five in 51 low- and middle-income countries (LMICs). Exposure to 6-month mild or severe drought was associated with an increased diarrhea risk of 5% (95% confidence interval 3-7%) or 8% (5-11%), respectively. The association was stronger among children living in a household that needed longer time to collect water or had no access to water or soap/detergent for handwashing. The association for 24-month drought was strong in dry zones but weak or null in tropical or temperate zones, whereas that for 6-month drought was only observed in tropical or temperate zones. In this work we quantify the associations between exposure to long-term drought and elevated diarrhea risk among children under five in LMICs and suggest that the risk could be reduced through improved water, sanitation, and hygiene practices, made more urgent by the likely increase in drought due to climate change.

The effect and attributable risk of daily temperature on category C infectious diarrhea in Guangdong Province, China

Previous studies have explored the effect between ambient temperature and infectious diarrhea (ID) mostly using relative risk, which provides limited information in practical applications. Few studies have focused on the disease burden of ID caused by temperature, especially for different subgroups and cities in a multi-city setting. This study aims to estimate the effects and attributable risks of temperature on category C ID and explore potential modifiers among various cities in Guangdong. First, distributed lag non-linear models (DLNMs) were used to explore city-specific associations between daily mean temperature and category C ID from 2014 to 2016 in Guangdong and pooled by applying multivariate meta-analysis. Then, multivariate meta-regression was implemented to analyze the potential heterogeneity among various cities. Finally, we assessed the attributable burden of category C ID due to temperature, low (below the 5th percentile of temperature) and high temperature (above the 95th percentile of temperature) for each city and subgroup population. Compared with the 50th percentile of daily mean temperature, adverse effects on category C ID were found when the temperature was lower than 12.27 ℃ in Guangdong Province. Some city-specific factors (longitude, urbanization rate, population density, disposable income per capita, and the number of medical technicians and beds per thousand persons) could modify the relationship of temperature-category C ID. During the study period, there were 60,505 category C ID cases (17.14% of total cases) attributable to the exposure of temperature, with the attributable fraction (AF) of low temperature (4.23%, 95% empirical confidence interval (eCI): 1.79-5.71%) higher than high temperature (1.34%, 95% eCI: 0.86-1.64%). Males, people under 5 years, and workers appeared to be more vulnerable to temperature, with AFs of 29.40%, 19.25%, and 21.49%, respectively. The AF varied substantially at the city level, with the largest AF of low temperature occurring in Shaoguan (9.58%, 95% eCI: 8.36-10.09%), and that of high temperature occurring in Shenzhen (3.16%, 95% eCI: 2.70-3.51%). Low temperature was an important risk factor for category C ID in Guangdong Province, China. The exposure-response relationship could be modified by city-specific characteristics. Considering the whole population, the attributable risk of low temperature was much higher than that of high temperature, and males, people under 5 years, and workers were vulnerable populations.

Study of Risk Factors for Total Attack Rate and Transmission Dynamics of Norovirus Outbreaks, Jiangsu Province, China, From 2012 to 2018

Objective: To describe the epidemiological characteristics of norovirus outbreaks in Jiangsu Province, utilize the total attack rate (TAR) and transmissibility (R_unc) as the measurement indicators of the outbreak, and a statistical difference in risk factors associated with TAR and transmissibility was compared. Ultimately, this study aimed to provide scientific suggestions to develop the most appropriate prevention and control measures.

Method: We collected epidemiological data from investigation reports of all norovirus outbreaks in Jiangsu Province from 2012 to 2018 and performed epidemiological descriptions, sequenced the genes of the positive specimens collected that were eligible for sequencing, created a database and calculated the TAR, constructed SEIAR and SEIARW transmission dynamic models to calculate R_unc, and performed statistical analyses of risk factors associated with the TAR and R_unc.

Results: We collected a total of 206 reported outbreaks, of which 145 could be used to calculate transmissibility. The mean TAR in was 2.6% and the mean R_unc was 12.2. The epidemiological characteristics of norovirus outbreaks showed an overall increasing trend in the number of norovirus outbreaks from 2012 to 2018; more outbreaks in southern Jiangsu than northern Jiangsu; more outbreaks in urban areas than in rural areas; outbreaks occurred mostly in autumn and winter. Most of the sites where outbreaks occurred were schools, especially primary schools. Interpersonal transmission accounted for the majority. Analysis of the genotypes of noroviruses revealed that the major genotypes of the viruses changed every 3 years, with the GII.2 [P16] type of norovirus dominating from 2016 to 2018. Statistical analysis of TAR associated with risk factors found statistical differences in all risk factors, including time (year, month, season), location (geographic location, type of settlement, type of premises), population (total number of susceptible people at the outbreak site), transmission route, and genotype (P < 0.05). Statistical analysis of transmissibility associated with risk factors revealed that only transmissibility was statistically different between sites.

Conclusions: The number of norovirus outbreaks in Jiangsu Province continues to increase during the follow-up period. Our findings highlight the impact of different factors on norovirus outbreaks and identify the key points of prevention and control in Jiangsu Province.

Associations Between Eight Earth Observation-Derived Climate Variables and Enteropathogen Infection: An Independent Participant Data Meta-Analysis of Surveillance Studies With Broad Spectrum Nucleic Acid Diagnostics

Diarrheal disease, still a major cause of childhood illness, is caused by numerous, diverse infectious microorganisms, which are differentially sensitive to environmental conditions. Enteropathogen-specific impacts of climate remain underexplored. Results from 15 studies that diagnosed enteropathogens in 64,788 stool samples from 20,760 children in 19 countries were combined. Infection status for 10 common enteropathogens-adenovirus, astrovirus, norovirus, rotavirus, sapovirus, Campylobacter, ETEC, Shigella, Cryptosporidium and Giardia-was matched by date with hydrometeorological variables from a global Earth observation dataset-precipitation and runoff volume, humidity, soil moisture, solar radiation, air pressure, temperature, and wind speed. Models were fitted for each pathogen, accounting for lags, nonlinearity, confounders, and threshold effects. Different variables showed complex, non-linear associations with infection risk varying in magnitude and direction depending on pathogen species. Rotavirus infection decreased markedly following increasing 7-day average temperatures-a relative risk of 0.76 (95% confidence interval: 0.69-0.85) above 28°C-while ETEC risk increased by almost half, 1.43 (1.36-1.50), in the 20-35°C range. Risk for all pathogens was highest following soil moistures in the upper range. Humidity was associated with increases in bacterial infections and decreases in most viral infections. Several virus species' risk increased following lower-than-average rainfall, while rotavirus and ETEC increased with heavier runoff. Temperature, soil moisture, and humidity are particularly influential parameters across all enteropathogens, likely impacting pathogen survival outside the host. Precipitation and runoff have divergent associations with different enteric viruses. These effects may engender shifts in the relative burden of diarrhea-causing agents as the global climate changes.

Viral infection among children under the age of 5 with diarrhea in Shenyang from 2018 to 2020: A hospital-based study

Diarrhea is one of the leading causes of death among children, especially in the age under 5, but few studies are available on viral diarrhea in Shenyang. To understand the infection status and the relevant epidemiological characteristics of viral diarrhea and to fill gaps of the distribution of viruses across Shenyang in children under the age of 5 with diarrhea, from 2018 to 2020, stool specimens of children with diarrhea aged 0-59 months and surveillance data were collected in Sentinel Hospital of Shenyang. Specimens were then tested to determine the type of viruses, the seasonal and spatial patterns for major viruses were determined. Viruses were identified in 47.9% of the 897 samples from children with diarrhea. The main viruses of stool samples were rotavirus (16.9%, predominant type G9P[8]), calicivirus (14.7%), adenovirus (11.8%), and astrovirus (4.5%). Viral infections were mainly detected in the age of 0-12 months. In the area of Shenyang, Huanggu had the most cases (198, 22.1%), followed by Dadong (137, 15.3%) and Hunnan (135, 15.1%). The positive rate of viruses varied among patients of different ages, seasons, and regions. Public health entities and the government should develop corresponding measures for different age groups, seasons, and regions.

Meteorological and social conditions contribute to infectious diarrhea in China

Infectious diarrhea in China showed a significant pattern. Many researchers have tried to reveal the drivers, yet usually only meteorological factors were taken into consideration. Furthermore, the diarrheal data they analyzed were incomplete and the algorithms they exploited were inefficient of adapting realistic relationships. Here, we investigate the impacts of meteorological and social factors on the number of infectious diarrhea cases in China. A machine learning algorithm called the Random Forest is utilized. Our results demonstrate that nearly half of infectious diarrhea occurred among children under 5 years old. Generally speaking, increasing temperature or relative humidity leads to increased cases of infectious diarrhea in China. Nevertheless, people from different age groups or different regions own different sensitivities to meteorological factors. The weight of feces that are harmfully treated could be a possible reason for infectious diarrhea of the elderly as well as children under 5 years old. These findings indicate that infectious diarrhea prevention for children under 5 years old remains a primary task in China. Personalized prevention countermeasures ought to be provided to different age groups and different regions. It is essential to bring the weight of feces that are harmfully treated to the forefront when considering infectious diarrhea prevention.

Time series analysis of foodborne diseases during 2012–2018 in Shenzhen, China

The present study aimed to use the autoregressive integrated moving average (ARIMA) model to forecast foodborne disease incidence in Shenzhen city and help guide efforts to prevent foodborne disease. The data of foodborne diseases in Shenzhen comes from the infectious diarrhea surveillance network, community foodborne disease surveillance network, and student foodborne disease surveillance network. The incidence data from January 2012 to December 2017 was used for the model-constructing, while the data from January 2018 to December 2018 was used for the model-validating. The mean absolute percentage error (MAPE) was used to assess the performance of the model. The monthly foodborne disease incidence from January 2012 to December 2017 in Shenzhen was between 954 and 32,863 with an incidence rate between 4.77 and 164.32/100,000 inhabitants. The ARIMA (1,1,0) was an adequate model for the change in monthly foodborne disease incidence series, yielding a MAPE of 5.34%. The mathematical formula of the ARIMA (1,1,0) model was (1 − B) × log(incidencet) = 0.04338 + εt/(1 + 0.51106B). The predicted foodborne disease incidences in the next three years were 635,751, 1,069,993, 1,800,838, respectively. Monthly foodborne disease incidence in Shenzhen were shown to follow the ARIMA (1,1,0) model. This model can be considered adequate for predicting future foodborne disease incidence in Shenzhen and can aid in the decision-making processes.

Enteric adenovirus epidemiology from historical fecal samples in Brazil (1998-2005): Pre-rotavirus vaccine era

Human adenovirus (HAdV) is recognized as frequent cause of acute gastroenteritis and enteric viruses can be preserved in frozen stored feces for long periods of times. The purpose of the present study was to investigate enteric HAdV genotypic diversity in archival fecal specimens stored from 1998 to 2005 in order to understand the natural history of HAdV in diarrheal patients in Brazil before rotavirus vaccine introduction. A total of 3346 specimens were tested for HAdV using conventional PCR. Genotypes were identified by sequencing. HAdV was detected in 6.8% (228/3346). Positivity was higher in children ≤ 5 years and males (p < 0.05). HAdV was most frequently observed during winter and spring seasons (p < 0.05). HAdV-F41 was the most prevalent genotype (59.2%;135/228), followed by HAdV-F40 (16.2%;37/228), HAdV-C1 (5.2%;12/228), HAdV-C2 (5.2%;12/228), HAdV-C5 (3.1%;7/228), HAdV-A12 (1.3%;3/228), HAdV-E4 (0.9%;2/228), HAdV-B3 (0.9%;2/228) and HAdV-B21 (0.4%;1/228). In 7.6% (17/228) only species D could be defined. HAdV-E4 strains were phylogenetic analyzed and classified as lineage (a)-like PG II. HAdV prevalence remained stable in Brazilian population, regardless rotavirus vaccine introduction. The predominant HAdV genotypes detected did not change over time, highlighting a high diversity of circulating strains in the country throughout decades. Due to the historical lack of HAdV genotyping surveillance in Brazil, HAdV-E4 epidemiology is virtually unknown in the country. The present study contributed significantly to the understanding of the natural history of HAdV in diarrheal patients in Brazil. The acquired data are important for clinical diagnosis, particularly for studies investigating enteric viruses' prevalence and molecular epidemiology of archival clinical specimens.

The Short-term Effects of Temperature on Infectious Diarrhea among Children under 5 Years Old in Jiangsu, China: A Time-series Study (2015-2019)

The association between meteorological factors and infectious diarrhea has been widely studied in many countries. However, investigation among children under 5 years old in Jiangsu, China remains quite limited. Data including infectious diarrhea cases among children under five years old and daily meteorological indexes in Jiangsu, China from 2015 to 2019 were collected. The lag-effects up to 21 days of daily maximum temperature (Tmax) on infectious diarrhea were explored using a quasi-Poisson regression with a distributed lag non-linear model (DLNM) approach. The cases number of infectious diarrhea was significantly associated with seasonal variation of meteorological factors, and the burden of disease mainly occurred among children aged 0–2 years old. Moreover, when the reference value was set at 16.7°C, Tmax had a significant lag-effect on cases of infectious diarrhea among children under 5 years old in Jiangsu Province, which was increased remarkably in cold weather with the highest risk at 8°C. The results of DLNM analysis implicated that the lag-effect of Tmax varied among the 13 cities in Jiangsu and had significant differences in 8 cities. The highest risk of Tmax was presented at 5 lag days in Huaian with a maximum RR of 1.18 (95% CI: 1.09, 1.29). Suzhou which had the highest number of diarrhea cases (15830 cases), had a maximum RR of 1.04 (95% CI:1.03, 1.05) on lag 15 days. Tmax is a considerable indicator to predict the epidemic of infectious diarrhea among 13 cities in Jiangsu, which reminds us that in cold seasons, more preventive strategies and measures should be done to prevent infectious diarrhea.

Effect of ambient temperatures on category C notifiable infectious diarrhea in China: An analysis of national surveillance data

BACKGROUND

Many studies have explored the association between meteorological factors and infectious diarrhea (ID) transmission but with inconsistent results, in particular the roles from temperatures. We aimed to explore the effects of temperatures on the transmission of category C ID, to identify its potential heterogeneity in different climate zones of China, and to provide scientific evidence to health authorities and local communities for necessary public health actions.

METHODS

Daily category C ID counts and meteorological variables were collected from 270 cities in China over the period of 2014-16. Distributed lag non-linear models (DLNMs) were applied in each city to obtain the city-specific temperature-disease associations, then a multivariate meta-analysis was implemented to pool the city-specific effects. Multivariate meta-regression was conducted to explore the potential effect modifiers. Attributable fraction was calculated for both low and high temperatures, defined as temperatures below the 5th percentile of temperature or above the 95th percentile of temperature.

RESULTS

A total of 2,715,544 category C ID cases were reported during the study period. Overall, a M-shaped curve relationship was observed between temperature and category C ID, with a peak at the 81st percentile of temperatures (RR = 1.723, 95% CI: 1.579-1.881) compared to 50th percentile of temperatures. The pooled associations were generally stronger at high temperatures compared to low ambient temperatures, and the attributable fraction due to heat was higher than cold. Latitude was identified as a possible effect modifier.

CONCLUSIONS

The overall positive pooled associations between temperature and category C ID in China suggest the increasing temperature could bring about more category C infectious diarrhea cases, which warrants further public health measurements.

Hemolysin-Producing Strains among Diarrheagenic Escherichia coli Isolated from Children under 2 Years Old with Diarrheal Disease

Even if serotyping based on O antigens is still routinely used by most laboratories for the detection of diarrheagenic Escherichia coli, this method can provide false-positive reactions, due to the high diversity of O antigens. Molecular methods represent a valuable tool that clarifies these situations. In the Bacteriology Laboratory of Mureș County Hospital, between May 2016 and July 2019, 160 diarrheagenic E. coli strains were isolated from children under 2 years old with diarrheic disease. The strains were identified as Shiga toxin-producing E. coli (STEC)/enteropathogenic Escherichia coli (EPEC) via agglutination with polyvalent sera. STEC strains were serotyped using monovalent sera for serogroup O157. Simplex PCR was performed on the strains to determine the presence of the hlyA gene, and, for the positive ones, the hemolytic activity was tested. Antibiotic susceptibility of the identified diarrheagenic E. coli strains was also investigated. STEC strains were the most frequently identified (49.1%), followed by EPEC (40.2%). The hlyA gene was identified in 12 cases, representing 18.2% of the STEC strains. Even if the extended-spectrum β-lactamase (ESBL)-producing strains represented only 10%, a relevant percentage of multidrug-resistant (MDR) strains (24%) was identified.

Understanding the Impact of Rainfall on Diarrhea: Testing the Concentration-Dilution Hypothesis Using a Systematic Review and Meta-Analysis

BACKGROUND

Projected increases in extreme weather may change relationships between rain-related climate exposures and diarrheal disease. Whether rainfall increases or decreases diarrhea rates is unclear based on prior literature. The concentration-dilution hypothesis suggests that these conflicting results are explained by the background level of rain: Rainfall following dry periods can flush pathogens into surface water, increasing diarrhea incidence, whereas rainfall following wet periods can dilute pathogen concentrations in surface water, thereby decreasing diarrhea incidence.

OBJECTIVES

In this analysis, we explored the extent to which the concentration-dilution hypothesis is supported by published literature.

METHODS

To this end, we conducted a systematic search for articles assessing the relationship between rain, extreme rain, flood, drought, and season (rainy vs. dry) and diarrheal illness.

RESULTS

A total of 111 articles met our inclusion criteria. Overall, the literature largely supports the concentration-dilution hypothesis. In particular, extreme rain was associated with increased diarrhea when it followed a dry period [incidence rate ratio ( IRR ) = 1.26 ; 95% confidence interval (CI): 1.05, 1.51], with a tendency toward an inverse association for extreme rain following wet periods, albeit nonsignificant, with one of four relevant studies showing a significant inverse association (IRR = 0.911 ; 95% CI: 0.771, 1.08). Incidences of bacterial and parasitic diarrhea were more common during rainy seasons, providing pathogen-specific support for a concentration mechanism, but rotavirus diarrhea showed the opposite association. Information on timing of cases within the rainy season (e.g., early vs. late) was lacking, limiting further analysis. We did not find a linear association between nonextreme rain exposures and diarrheal disease, but several studies found a nonlinear association with low and high rain both being associated with diarrhea.

DISCUSSION

Our meta-analysis suggests that the effect of rainfall depends on the antecedent conditions. Future studies should use standard, clearly defined exposure variables to strengthen understanding of the relationship between rainfall and diarrheal illness. https://doi.org/10.1289/EHP6181.

The Effect of Ambient Temperature on Infectious Diarrhea and Diarrhea-like Illness in Wuxi, China

Background:

The disease burden of infectious diarrhea cannot be underestimated. Its seasonal patterns indicate that weather patterns may play an important role and have an important effect on it. The objective of this study was to clarify the relationship between temperature and infectious diarrhea, and diarrhea-like illness.

Methods:

Distributed lag non-linear model, which was based on the definition of a cross-basis, was used to examine the effect.

Results:

Viral diarrhea usually had high incidence in autumn-winter and spring with a peak at -6°C; Norovirus circulated throughout the year with an insignificant peak at 8°C, while related bacteria usually tested positive in summer and peaked at 22°C. The lag-response curve of the proportion of diarrhea-like cases in outpatient and emergency cases revealed that at -6°C, with the lag days increasing, the proportion increased. Similar phenomena were observed at the beginning of the curves of virus and bacterial positive rate, showing that the risk increased as the lag days increased, peaking on days 16 and 9, respectively. The shape of lag-response curve of norovirus positive rate was different from others, presenting m-type, with 2 peaks on day 3 and day 18.

Conclusion:

Weather patterns should be taken into account when developing surveillance programs and formulating relevant public health intervention strategies.