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Summary Background Enteropathogen infections in early childhood not only cause diarrhoea but contribute to poor growth. We used molecular diagnostics to assess whether particular enteropathogens were associated with linear growth across seven low-resource settings. Methods We used quantitative PCR to detect 29 enteropathogens in diarrhoeal and non-diarrhoeal stools collected from children in the first 2 years of life obtained during the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) multisite cohort study. Length was measured monthly. We estimated associations between aetiology-specific diarrhoea and subclinical enteropathogen infection and quantity and attained length in 3 month intervals, at age 2 and 5 years, and used a longitudinal model to account for temporality and time-dependent confounding. Findings Among 1469 children who completed 2 year follow-up, 35 622 stool samples were tested and yielded valid results. Diarrhoeal episodes attributed to bacteria and parasites, but not viruses, were associated with small decreases in length after 3 months and at age 2 years. Substantial decrements in length at 2 years were associated with subclinical, non-diarrhoeal, infection with Shigella (length-for-age Z score [LAZ] reduction −0·14, 95% CI −0·27 to −0·01), enteroaggregative Escherichia coli (−0·21, −0·37 to −0·05), Campylobacter (−0·17, −0·32 to −0·01), and Giardia (−0·17, −0·30 to −0·05). Norovirus, Cryptosporidium, typical enteropathogenic E coli, and Enterocytozoon bieneusi were also associated with small decrements in LAZ. Shigella and E bieneusi were associated with the largest decreases in LAZ per log increase in quantity per g of stool (−0·13 LAZ, 95% CI −0·22 to −0·03 for Shigella; −0·14, −0·26 to −0·02 for E bieneusi). Based on these models, interventions that successfully decrease exposure to Shigella, enteroaggregative E coli, Campylobacter, and Giardia could increase mean length of children by 0·12–0·37 LAZ (0·4–1·2 cm) at the MAL-ED sites. Interpretation Subclinical infection and quantity of pathogens, particularly Shigella, enteroaggregative E coli, Campylobacter, and Giardia, had a substantial negative association with linear growth, which was sustained during the first 2 years of life, and in some cases, to 5 years. Successfully reducing exposure to certain pathogens might reduce global stunting. Funding Bill & Melinda Gates Foundation.

Optimum management of childhood diarrhoea in low-resource settings has been hampered by insufficient data on aetiology, burden, and associated clinical characteristics. We used quantitative diagnostic methods to reassess and refine estimates of diarrhoea aetiology from the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) cohort study.We re-analysed stool specimens from the multisite MAL-ED cohort study of children aged 0-2 years done at eight locations (Dhaka, Bangladesh; Vellore, India; Bhaktapur, Nepal; Naushero Feroze, Pakistan; Venda, South Africa; Haydom, Tanzania; Fortaleza, Brazil; and Loreto, Peru), which included active surveillance for diarrhoea and routine non-diarrhoeal stool collection. We used quantitative PCR to test for 29 enteropathogens, calculated population-level pathogen-specific attributable burdens, derived stringent quantitative cutoffs to identify aetiology for individual episodes, and created aetiology prediction scores using clinical characteristics.We analysed 6625 diarrhoeal and 30 968 non-diarrhoeal surveillance stools from 1715 children. Overall, 64·9% of diarrhoea episodes (95% CI 62·6-71·2) could be attributed to an aetiology by quantitative PCR compared with 32·8% (30·8-38·7) using the original study microbiology. Viral diarrhoea (36·4% of overall incidence, 95% CI 33·6-39·5) was more common than bacterial (25·0%, 23·4-28·4) and parasitic diarrhoea (3·5%, 3·0-5·2). Ten pathogens accounted for 95·7% of attributable diarrhoea: Shigella (26·1 attributable episodes per 100 child-years, 95% CI 23·8-29·9), sapovirus (22·8, 18·9-27·5), rotavirus (20·7, 18·8-23·0), adenovirus 40/41 (19·0, 16·8-23·0), enterotoxigenic Escherichia coli (18·8, 16·5-23·8), norovirus (15·4, 13·5-20·1), astrovirus (15·0, 12·0-19·5), Campylobacter jejuni or C coli (12·1, 8·5-17·2), Cryptosporidium (5·8, 4·3-8·3), and typical enteropathogenic E coli (5·4, 2·8-9·3). 86·2% of the attributable incidence for Shigella was non-dysenteric. A prediction score for shigellosis was more accurate (sensitivity 50·4% [95% CI 46·7-54·1], specificity 84·0% [83·0-84·9]) than current guidelines, which recommend treatment only of bloody diarrhoea to cover Shigella (sensitivity 14·5% [95% CI 12·1-17·3], specificity 96·5% [96·0-97·0]).Quantitative molecular diagnostics improved estimates of pathogen-specific burdens of childhood diarrhoea in the community setting. Viral causes predominated, including a substantial burden of sapovirus; however, Shigella had the highest overall burden with a high incidence in the second year of life. These data could improve the management of diarrhoea in these low-resource settings.BillMelinda Gates Foundation.

Enterotoxigenic Escherichia coli (ETEC) is a leading cause of childhood diarrhea in low income countries and in travelers to those areas. Inactivated enterotoxins and colonization factors (CFs) are leading vaccine candidates, therefore it is important to determine the prevailing CF types in different geographic locations and populations. Here we developed real time PCR (qPCR) assays for 14 colonization factors, including the common vaccine targets. These assays, along with three enterotoxin targets (STh, STp, and LT) were formulated into three 5-plex qPCR panels, and validated on 120 ETEC isolates and 74 E. coli colony pools. The overall sensitivity and specificity was 99% (199/202) and 99% (2497/2514), respectively, compared to the CF results obtained with conventional PCR. Amplicon sequencing of discrepant samples revealed that the qPCR was 100% accurate. qPCR panels were also performed on nucleic acid extracted from stool and compared to the results of the ETEC isolates or E. coli colony pools cultured from them. 95% (105/110) of the CF detections in the cultures were confirmed in the stool. Additionally, direct testing of stool yielded 30 more CF detections. Among 74 randomly selected E. coli colony pools with paired stool, at least one CF was detected in 63% (32/51) of the colony pools while at least one CF was detected in 78% (47/60) of the stool samples (P = NS). We conclude that these ETEC CF assays can be used on both cultures and stool samples to facilitate better understanding of CF distribution for ETEC epidemiology and vaccine development.

Summary We describe the substantial impact of rotavirus vaccine introduction on all-cause and rotavirus diarrhea admissions to a rural Tanzanian referral hospital. Despite this impact, rotavirus remained the leading etiology of diarrhea requiring hospitalization in the third year after vaccine introduction., Background No data are available on the etiology of diarrhea requiring hospitalization after rotavirus vaccine introduction in Africa. The monovalent rotavirus vaccine was introduced in Tanzania on 1 January 2013. We performed a vaccine impact and effectiveness study as well as a quantitative polymerase chain reaction (qPCR)–based etiology study at a rural Tanzanian hospital. Methods We obtained data on admissions among children

Detection and quantification of enteropathogens in stool specimens is useful for diagnosing the cause of diarrhea but is technically challenging. Here we evaluate several important determinants of quantification: specimen collection, nucleic acid extraction, and extraction and amplification efficiency. First, we evaluate the molecular detection and quantification of pathogens in rectal swabs versus stool, using paired flocked rectal swabs and whole stool collected from 129 children hospitalized with diarrhea in Tanzania. Swabs generally yielded a higher quantification cycle (Cq) (average 29.7, standard deviation 3.5 vs. 25.3 ± 2.9 from stool, P