Seasonality and within-subject clustering of rotavirus infections in an eight-site birth cohort study

Clinical and nutritional correlates of bacterial diarrhoea aetiology in young children: a secondary cross-sectional analysis of the ABCD trial

OBJECTIVE

The objective was to assess the association between nutritional and clinical characteristics and quantitative PCR (qPCR)-diagnosis of bacterial diarrhoea in a multicentre cohort of children under 2 years of age with moderate to severe diarrhoea (MSD).

DESIGN

A secondary cross-sectional analysis of baseline data collected from the AntiBiotics for Children with Diarrhoea trial (NCT03130114).

PATIENTS

Children with MSD (defined as >3 loose stools within 24 hours and presenting with at least one of the following: some/severe dehydration, moderate acute malnutrition (MAM) or severe stunting) enrolled in the ABCD trial and collected stool sample.

STUDY PERIOD

June 2017-July 2019.

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

Likely bacterial aetiology of diarrhoea. Secondary outcomes included specific diarrhoea aetiology.

RESULTS

A total of 6692 children with MSD had qPCR results available and 28% had likely bacterial diarrhoea aetiology. Compared with children with severe stunting, children with MAM (adjusted OR (aOR) (95% CI) 1.56 (1.18 to 2.08)), some/severe dehydration (aOR (95% CI) 1.66 (1.25 to 2.22)) or both (aOR (95% CI) 2.21 (1.61 to 3.06)), had higher odds of having likely bacterial diarrhoea aetiology. Similar trends were noted for stable toxin-enterotoxigenic Escherichia coli aetiology. Clinical correlates including fever and prolonged duration of diarrhoea were not associated with likely bacterial aetiology; children with more than six stools in the previous 24 hours had higher odds of likely bacterial diarrhoea (aOR (95% CI) 1.20 (1.05 to 1.36)) compared with those with fewer stools.

CONCLUSION

The presence of MAM, dehydration or high stool frequency may be helpful in identifying children with MSD who might benefit from antibiotics.

Delineating the Seasonality of Varicella and Its Association With Climate in the Tropical Country of Colombia

BACKGROUND

Varicella causes a major health burden in many low- to middle-income countries located in tropical regions. Because of the lack of surveillance data, however, the epidemiology of varicella in these regions remains uncharacterized. In this study, based on an extensive dataset of weekly varicella incidence in children ≤10 during 2011-2014 in 25 municipalities, we aimed to delineate the seasonality of varicella across the diverse tropical climates of Colombia.

METHODS

We used generalized additive models to estimate varicella seasonality, and we used clustering and matrix correlation methods to assess its correlation with climate. Furthermore, we developed a mathematical model to examine whether including the effect of climate on varicella transmission could reproduce the observed spatiotemporal patterns.

RESULTS

Varicella seasonality was markedly bimodal, with latitudinal changes in the peaks' timing and amplitude. This spatial gradient strongly correlated with specific humidity (Mantel statistic = 0.412, P = .001) but not temperature (Mantel statistic = 0.077, P = .225). The mathematical model reproduced the observed patterns not only in Colombia but also México, and it predicted a latitudinal gradient in Central America.

CONCLUSIONS

These results demonstrate large variability in varicella seasonality across Colombia and suggest that spatiotemporal humidity fluctuations can explain the calendar of varicella epidemics in Colombia, México, and potentially in Central America.

Seasonal variation of diarrhoeal pathogens among Guinea-Bissauan children under five years of age

BACKGROUND

Diarrhoea remains a major cause of childhood morbidity and mortality in low-income countries (LICs). The frequency of diarrhoeal episodes may vary by season, yet few prospective cohort studies have examined seasonal variation among various diarrhoeal pathogens using multiplex qPCR to analyse bacterial, viral and parasitic pathogens.

METHODS

We combined our recent qPCR data of diarrhoeal pathogens (nine bacterial, five viral and four parasitic) among Guinea-Bissauan children under five years old with individual background data, dividing by season. The associations of season (dry winter and rainy summer) and the various pathogens were explored among infants (0-11 months) and young children (12-59 months) and those with and without diarrhoea.

RESULTS

Many bacterial pathogens, especially EAEC, ETEC and Campylobacter, and parasitic Cryptosporidium, prevailed in the rainy season, whereas many viruses, particularly the adenovirus, astrovirus and rotavirus proved common in the dry season. Noroviruses were found constantly throughout the year. Seasonal variation was observed in both age groups.

CONCLUSION

In childhood diarrhoea in a West African LIC, seasonal variation appears to favour EAEC, ETEC, and Cryptosporidium in the rainy and viral pathogens in the dry season.

Burden, clinical characteristics, risk factors, and seasonality of adenovirus 40/41 diarrhea in children in eight low-resource settings

Background

The application of molecular diagnostics has identified enteric group adenovirus serotypes 40 and 41 as important causes of diarrhea in children. However, many aspects of the epidemiology of adenovirus 40/41 diarrhea have not been described.

Methods

We used data from the 8-site Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development Project birth cohort study to describe site- and age-specific incidence, risk factors, clinical characteristics, and seasonality.

Results

The incidence of adenovirus 40/41 diarrhea was substantially higher by quantitative polymerase chain reaction than enzyme immunoassay and peaked at ∼30 episodes per 100 child-years in children aged 7–15 months, with substantial variation in incidence between sites. A significant burden was also seen in children 0–6 months of age, higher than other viral etiologies with the exception of rotavirus. Children with adenovirus 40/41 diarrhea were more likely to have a fever than children with norovirus, sapovirus, and astrovirus (adjusted odds ratio [aOR], 1.62; 95% CI, 1.16–2.26) but less likely than children with rotavirus (aOR, 0.66; 95% CI, 0.49–0.91). Exclusive breastfeeding was strongly protective against adenovirus 40/41 diarrhea (hazard ratio, 0.64; 95% CI, 0.48–0.85), but no other risk factors were identified. The seasonality of adenovirus 40/41 diarrhea varied substantially between sites and did not have clear associations with seasonal variations in temperature or rainfall.

Conclusions

This study supports the situation of adenovirus 40/41 as a pathogen of substantial importance, especially in infants. Fever was a distinguishing characteristic in comparison to other nonrotavirus viral etiologies, and promotion of exclusive breastfeeding may reduce the high observed burden in the first 6 months of life.

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.

Prevalence of diarrhoeal pathogens among children under five years of age with and without diarrhoea in Guinea-Bissau

BACKGROUND

Childhood diarrhoea, a major cause of morbidity and mortality in low-income regions, remains scarcely studied in many countries, such as Guinea-Bissau. Stool sample drying enables later qPCR analyses of pathogens without concern about electricity shortages.

METHODS

Dried stool samples of children under five years treated at the Bandim Health Centre in Bissau, Guinea-Bissau were screened by qPCR for nine enteric bacteria, five viruses, and four parasites. The findings of children having and not having diarrhoea were compared in age groups 0-11 and 12-59 months.

RESULTS

Of the 429 children- 228 with and 201 without diarrhoea- 96.9% and 93.5% had bacterial, 62.7% and 44.3% viral, and 52.6% and 48.3% parasitic pathogen findings, respectively. Enteroaggregarive Escherichia coli (EAEC; 60.5% versus 66.7%), enteropathogenic E. coli (EPEC; 61.4% versus 62.7%), Campylobacter (53.2% versus 51.8%), and enterotoxigenic E. coli (ETEC; 54.4% versus 44.3%) were the most common bacterial pathogens. Diarrhoea was associated with enteroinvasive E. coli (EIEC)/Shigella (63.3%), ETEC (54.4%), astrovirus (75.0%), norovirus GII (72.6%) and Cryptosporidium (71.2%). The only pathogen associated with severe diarrhoea was EIEC/Shigella (p<0.001). EAEC was found more frequent among the infants, and EIEC/Shigella, Giardia duodenalis and Dientamoeba fragilis among the older children.

CONCLUSIONS

Stool pathogens proved common among all the children regardless of them having diarrhoea or not.

Etiology and Incidence of Moderate-to-Severe Diarrhea in Young Children in Niger

BACKGROUND

High-resolution data on the etiology of childhood diarrhea in countries with the highest burden and mortality remain sparse and are needed to inform burden estimates and prioritize interventions.

METHODS

We tested stool specimens collected between October 2014 and December 2017 from children under 2 years of age from the per-protocol population of a placebo-controlled clinical trial of a bovine rotavirus pentavalent vaccine (Rotasiil) in Niger. We tested 1729 episodes of moderate-to-severe diarrhea (Vesikari score ≥ 7) using quantitative PCR and estimated pathogen-specific burdens by age, season, severity, and trial intervention arm.

RESULTS

The 4 pathogens with the highest attributable incidence of diarrhea were Shigella (7.2 attributable episodes per 100 child-years; 95% confidence interval: 5.2, 9.7), Cryptosporidium (6.5; 5.8, 7.2), rotavirus (6.4; 5.9, 6.7), and heat-stabile toxin-producing enterotoxigenic Escherichia coli (ST-ETEC) (6.2; 3.1, 7.7). Cryptosporidium was the leading etiology of severe diarrhea (Vesikari score ≥ 11) and diarrhea requiring hospitalization. Shigella was the leading etiology of diarrhea in children 12-23 months of age but also had a substantial burden in the first year of life, with 60.5% of episodes of severe shigellosis occurring in infants. Shigella, Cryptosporidium, and ST-ETEC incidence peaked during the warmer and wetter period and coincided with peak all-cause diarrhea incidence.

CONCLUSIONS

In this high-burden setting, the leading diarrheal pathogens were Shigella, Cryptosporidium, rotavirus, and ST-ETEC, and each was disproportionately seen in infants. Vaccine development should target these pathogens, and the impact of vaccine schedule on diarrhea burden in the youngest children will need to be considered.

Pathogen-Specific Impacts of the 2011-2012 La Niña-Associated Floods on Enteric Infections in the MAL-ED Peru Cohort: A Comparative Interrupted Time Series Analysis

Extreme floods pose multiple direct and indirect health risks. These risks include contamination of water, food, and the environment, often causing outbreaks of diarrheal disease. Evidence regarding the effects of flooding on individual diarrhea-causing pathogens is limited, but is urgently needed in order to plan and implement interventions and prioritize resources before climate-related disasters strike. This study applied a causal inference approach to data from a multisite study that deployed broadly inclusive diagnostics for numerous high-burden common enteropathogens. Relative risks (RRs) of infection with each pathogen during a flooding disaster that occurred at one of the sites-Loreto, Peru-were calculated from generalized linear models using a comparative interrupted time series framework with the other sites as a comparison group and adjusting for background seasonality. During the early period of the flood, increased risk of heat-stable enterotoxigenic E. coli (ST-ETEC) was identified (RR = 1.73 [1.10, 2.71]) along with a decreased risk of enteric adenovirus (RR = 0.36 [0.23, 0.58]). During the later period of the flood, sharp increases in the risk of rotavirus (RR = 5.30 [2.70, 10.40]) and sapovirus (RR = 2.47 [1.79, 3.41]) were observed, in addition to increases in transmission of Shigella spp. (RR = 2.86 [1.81, 4.52]) and Campylobacter spp. (RR = 1.41 (1.01, 1.07). Genotype-specific exploratory analysis reveals that the rise in rotavirus transmission during the flood was likely due to the introduction of a locally atypical, non-vaccine (G2P[4]) strain of the virus. Policy-makers should target interventions towards these pathogens-including vaccines as they become available-in settings where vulnerability to flooding is high as part of disaster preparedness strategies, while investments in radical, transformative, community-wide, and locally-tailored water and sanitation interventions are also needed.

Rotavirus Seasonality: An Application of Singular Spectrum Analysis and Polyharmonic Modeling

The dynamics of many viral infections, including rotaviral infections (RIs), are known to have a complex non-linear, non-stationary structure with strong seasonality indicative of virus and host sensitivity to environmental conditions. However, analytical tools suitable for the identification of seasonal peaks are limited. We introduced a two-step procedure to determine seasonal patterns in RI and examined the relationship between daily rates of rotaviral infection and ambient temperature in cold climates in three Russian cities: Chelyabinsk, Yekaterinburg, and Barnaul from 2005 to 2011. We described the structure of temporal variations using a new class of singular spectral analysis (SSA) models based on the "Caterpillar" algorithm. We then fitted Poisson polyharmonic regression (PPHR) models and examined the relationship between daily RI rates and ambient temperature. In SSA models, RI rates reached their seasonal peaks around 24 February, 5 March, and 12 March (i.e., the 55.17 ± 3.21, 64.17 ± 5.12, and 71.11 ± 7.48 day of the year) in Chelyabinsk, Yekaterinburg, and Barnaul, respectively. Yet, in all three cities, the minimum temperature was observed, on average, to be on 15 January, which translates to a lag between the peak in disease incidence and time of temperature minimum of 38-40 days for Chelyabinsk, 45-49 days in Yekaterinburg, and 56-59 days in Barnaul. The proposed approach takes advantage of an accurate description of the time series data offered by the SSA-model coupled with a straightforward interpretation of the PPHR model. By better tailoring analytical methodology to estimate seasonal features and understand the relationships between infection and environmental conditions, regional and global disease forecasting can be further improved.

Consultations for gastroenteritis in general practice and out-of-hours services in Norway 2006-15

BACKGROUND

Most of the patients with gastroenteritis seeking health care services are managed in primary care; yet, little is known about these consultations. Syndromic-based surveillance of gastrointestinal infections is used in several countries, including Norway.

AIM

To investigate the extent of, and explore characteristics associated with, consultations for gastroenteritis in primary care and to compare consultations in daytime general practice and out-of-hours (OOH) services in Norway.

DESIGN AND SETTING

Registry-based study using reimbursement claims data from all consultations in general practice and OOH services in Norway over the 10-year period, 2006-15.

METHODS

The main outcome variable was whether the consultation took place in general practice or OOH services. Possible associations with patient age and sex, time and use of point-of-care C-reactive protein (CRP) testing and sickness certificate issuing were investigated.

RESULTS

Gastroenteritis consultations (n = 1 281 048) represented 0.9% of all consultations in primary care (n = 140 199 637), of which 84.4% were conducted in general practice and 15.6% in OOH services. Young children and young adults dominated among the patients. Point-of-care CRP testing was used in 36.1% of the consultations. Sickness certificates were issued in 43.6% of consultations with patients in working age. Age-specific time variations in consultation frequencies peaking in winter months were observed.

CONCLUSIONS

The proportion of gastroenteritis consultations was higher in the OOH services when compared with daytime general practice. Young children and young adults dominated among the patients. The seasonal variation in consultation frequency is similar to that shown for gastroenteritis caused by norovirus.

The seasonality of diarrheal pathogens: A retrospective study of seven sites over three years

BACKGROUND

Pediatric diarrhea can be caused by a wide variety of pathogens, from bacteria to viruses to protozoa. Pathogen prevalence is often described as seasonal, peaking annually and associated with specific weather conditions. Although many studies have described the seasonality of diarrheal disease, these studies have occurred predominantly in temperate regions. In tropical and resource-constrained settings, where nearly all diarrhea-associated mortality occurs, the seasonality of many diarrheal pathogens has not been well characterized. As a retrospective study, we analyze the seasonal prevalence of diarrheal pathogens among children with moderate-to-severe diarrhea (MSD) over three years from the seven sites of the Global Enteric Multicenter Study (GEMS), a case-control study. Using data from this expansive study on diarrheal disease, we characterize the seasonality of different pathogens, their association with site-specific weather patterns, and consistency across study sites.

METHODOLOGY/PRINCIPAL FINDINGS

Using traditional methodologies from signal processing, we found that certain pathogens peaked at the same time every year, but not at all sites. We also found associations between pathogen prevalence and weather or "seasons," which are defined by applying modern machine-learning methodologies to site-specific weather data. In general, rotavirus was most prevalent during the drier "winter" months and out of phase with bacterial pathogens, which peaked during hotter and rainier times of year corresponding to "monsoon," "rainy," or "summer" seasons.

CONCLUSIONS/SIGNIFICANCE

Identifying the seasonally-dependent prevalence for diarrheal pathogens helps characterize the local epidemiology and inform the clinical diagnosis of symptomatic children. Our multi-site, multi-continent study indicates a complex epidemiology of pathogens that does not reveal an easy generalization that is consistent across all sites. Instead, our study indicates the necessity of local data to characterizing the epidemiology of diarrheal disease. Recognition of the local associations between weather conditions and pathogen prevalence suggests transmission pathways and could inform control strategies in these settings.

Use of earth observation-derived hydrometeorological variables to model and predict rotavirus infection (MAL-ED): a multisite cohort study

BACKGROUND

Climate change threatens to undermine recent progress in reducing global deaths from diarrhoeal disease in children. However, the scarcity of evidence about how individual environmental factors affect transmission of specific pathogens makes prediction of trends under different climate scenarios challenging. We aimed to model associations between daily estimates of a suite of hydrometeorological variables and rotavirus infection status ascertained through community-based surveillance.

METHODS

For this analysis of multisite cohort data, rotavirus infection status was ascertained through community-based surveillance of infants in the eight-site MAL-ED cohort study, and matched by date with earth observation estimates of nine hydrometeorological variables from the Global Land Data Assimilation System: daily total precipitation volume (mm), daily total surface runoff (mm), surface pressure (mbar), wind speed (m/s), relative humidity (%), soil moisture (%), solar radiation (W/m2), specific humidity (kg/kg), and average daily temperatures (°C). Lag relationships, independent effects, and interactions were characterised by use of modified Poisson models and compared with and without adjustment for seasonality and between-site variation. Final models were created with stepwise selection of main effects and interactions and their validity assessed by excluding each site in turn and calculating Tjur's Coefficients of Determination.

FINDINGS

All nine hydrometeorological variables were significantly associated with rotavirus infection after adjusting for seasonality and between-site variation over multiple consecutive or non-consecutive lags, showing complex, often non-linear associations that differed by symptom status and showed considerable mutual interaction. The final models explained 5·9% to 6·2% of the variability in rotavirus infection in the pooled data and their predictions explained between 0·0% and 14·1% of the variability at individual study sites.

INTERPRETATION

These results suggest that the effect of climate on rotavirus transmission was mediated by four independent mechanisms: waterborne dispersal, airborne dispersal, virus survival on soil and surfaces, and host factors. Earth observation data products available at a global scale and at subdaily resolution can be combined with longitudinal surveillance data to test hypotheses about routes and drivers of transmission but showed little potential for making predictions in this setting.

FUNDING

Bill & Melinda Gates Foundation; Foundation for the National Institutes of Health, National Institutes of Health, Fogarty International Center; Sherrilyn and Ken Fisher Center for Environmental Infectious Diseases, Johns Hopkins School of Medicine; and NASA's Group on Earth Observations Work Programme.

Rates of hospitalization and death for all-cause and rotavirus acute gastroenteritis before rotavirus vaccine introduction in Kenya, 2010-2013

Background

Rotavirus vaccine was introduced in Kenya immunization program in July 2014. Pre-vaccine disease burden estimates are important for assessing vaccine impact.

Methods

Children with acute gastroenteritis (AGE) (≥3 loose stools and/or ≥ 1 episode of unexplained vomiting followed by loose stool within a 24-h period), hospitalized in Siaya County Referral Hospital (SCRH) from January 2010 through December 2013 were enrolled. Stool specimens were tested for rotavirus (RV) using an enzyme immunoassay (EIA). Hospitalization rates were calculated using person-years of observation (PYO) from the Health Demographic Surveillance System (HDSS) as a denominator, while adjusting for healthcare utilization at household level and proportion of stool specimen collected from patients who met the case definition at the surveillance hospital. Mortality rates were calculated using PYO as the denominator and number of deaths estimated using total deaths in the HDSS, proportion of deaths attributed to diarrhoea by verbal autopsy (VA) and percent positive for rotavirus AGE (RVAGE) hospitalizations.

Results

Of 7760 all-cause hospitalizations among children < 5 years of age, 3793 (49%) were included in the analysis. Of these, 21% (805) had AGE; RV was detected in 143 (26%) of 541 stools tested. Among children < 5 years, the estimated hospitalization rates per 100,000 PYO for AGE and RVAGE were 2413 and 429, respectively. Mortality rate associated with AGE and RVAGE were 176 and 45 per 100,000 PYO, respectively.

Conclusion

AGE and RVAGE caused substantial health care burden (hospitalizations and deaths) before rotavirus vaccine introduction in Kenya.

Evaluating meteorological data from weather stations, and from satellites and global models for a multi-site epidemiological study

BACKGROUND

Longitudinal and time series analyses are needed to characterize the associations between hydrometeorological parameters and health outcomes. Earth Observation (EO) climate data products derived from satellites and global model-based reanalysis have the potential to be used as surrogates in situations and locations where weather-station based observations are inadequate or incomplete. However, these products often lack direct evaluation at specific sites of epidemiological interest.

METHODS

Standard evaluation metrics of correlation, agreement, bias and error were applied to a set of ten hydrometeorological variables extracted from two quasi-global, commonly used climate data products - the Global Land Data Assimilation System (GLDAS) and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) - to evaluate their performance relative to weather-station derived estimates at the specific geographic locations of the eight sites in a multi-site cohort study. These metrics were calculated for both daily estimates and 7-day averages and for a rotavirus-peak-season subset. Then the variables from the two sources were each used as predictors in longitudinal regression models to test their association with rotavirus infection in the cohort after adjusting for covariates.

RESULTS

The availability and completeness of station-based validation data varied depending on the variable and study site. The performance of the two gridded climate models varied considerably within the same location and for the same variable across locations, according to different evaluation criteria and for the peak-season compared to the full dataset in ways that showed no obvious pattern. They also differed in the statistical significance of their association with the rotavirus outcome. For some variables, the station-based records showed a strong association while the EO-derived estimates showed none, while for others, the opposite was true.

CONCLUSION

Researchers wishing to utilize publicly available climate data - whether EO-derived or station based - are advised to recognize their specific limitations both in the analysis and the interpretation of the results. Epidemiologists engaged in prospective research into environmentally driven diseases should install their own weather monitoring stations at their study sites whenever possible, in order to circumvent the constraints of choosing between distant or incomplete station data or unverified EO estimates.