Development of risk prediction models for preterm delivery in a rural setting in Ethiopia.

Background: Preterm birth complications are the leading causes of death among children under five years. However, the inability to accurately identify pregnancies at high risk of preterm delivery is a key practical challenge, especially in resource-constrained settings with limited availability of biomarkers assessment. Methods: We evaluated whether risk of preterm delivery can be predicted using available data from a pregnancy and birth cohort in Amhara region, Ethiopia. All participants were enrolled in the cohort between December 2018 and March 2020. The study outcome was preterm delivery, defined as any delivery occurring before week 37 of gestation regardless of vital status of the foetus or neonate. A range of sociodemographic, clinical, environmental, and pregnancy-related factors were considered as potential inputs. We used Cox and accelerated failure time models, alongside decision tree ensembles to predict risk of preterm delivery. We estimated model discrimination using the area-under-the-curve (AUC) and simulated the conditional distributions of cervical length (CL) and foetal fibronectin (FFN) to ascertain whether they could improve model performance. Results: We included 2493 pregnancies; among them, 138 women were censored due to loss-to-follow-up before delivery. Overall, predictive performance of models was poor. The AUC was highest for the tree ensemble classifier (0.60, 95% confidence interval = 0.57-0.63). When models were calibrated so that 90% of women who experienced a preterm delivery were classified as high risk, at least 75% of those classified as high risk did not experience the outcome. The simulation of CL and FFN distributions did not significantly improve models' performance. Conclusions: Prediction of preterm delivery remains a major challenge. In resource-limited settings, predicting high-risk deliveries would not only save lives, but also inform resource allocation. It may not be possible to accurately predict risk of preterm delivery without investing in novel technologies to identify genetic factors, immunological biomarkers, or the expression of specific proteins.

Effect of in-line drinking water chlorination at the point of collection on child diarrhoea in urban Bangladesh: a double-blind, cluster-randomised controlled trial.

BACKGROUND: Previous blinded trials of household water treatment interventions in low-income settings have failed to detect a reduction in child diarrhoea. Technological advances have enabled the development of automated in-line chlorine dosers that can disinfect drinking water without electricity, while also allowing users to continue their typical water collection practices. We aimed to evaluate the effect of installing novel passive chlorination devices at shared water points on child diarrhoea prevalence in low-income, densely populated communities in urban Bangladesh. METHODS: In this double-blind cluster-randomised controlled trial, 100 shared water points (clusters) in two low-income urban communities in Bangladesh were randomly assigned (1:1) to have their drinking water automatically chlorinated at the point of collection by a solid tablet chlorine doser (intervention group) or to be treated by a visually identical doser that supplied vitamin C (active control group). The trial followed an open cohort design; all children younger than 5 years residing in households accessing enrolled water points were measured every 2-3 months during a 14-month follow-up period (children could migrate into or out of the cluster). The primary outcome was caregiver-reported child diarrhoea (≥3 loose or watery stools in a 24-h period [WHO criteria]) with a 1-week recall, including all available childhood observations in the analyses. This trial is registered with ClinicalTrials.gov, number NCT02606981, and is completed. FINDINGS: Between July 5, 2015, and Nov 11, 2015, 100 water points with 920 eligible households were enrolled into the study and randomly assigned to the treatment (50 water points; 517 children at baseline; 2073 child observations included in the primary analysis) or control groups (50; 519; 2154). Children in the treatment group had less WHO-defined diarrhoea than did children in the control group (control 216 [10·0%] of 2154; treatment 156 [7·5%] of 2073; prevalence ratio 0·77, 95% CI 0·65-0·91). Drinking water at the point of collection at treatment taps had detectable free chlorine residual 83% (mean 0·37 ppm) of the time compared with 0% at control taps (0·00 ppm). INTERPRETATION: Passive chlorination at the point of collection could be an effective and scalable strategy in low-income urban settings for reducing child diarrhoea and for achieving global progress towards Sustainable Development Goal 6.1 to attain universal access to safe and affordable drinking water. Targeting a low chlorine residual (<0·5 ppm) in treated water can increase taste acceptability of chlorinated drinking water while still reducing the risk of diarrhoea. FUNDING: The World Bank.