Air pollution and age-dependent changes in emotional behavior across early adolescence in the U.S.

Recent studies have linked air pollution to increased risk for behavioral problems during development, albeit with inconsistent findings. Additional longitudinal studies are needed that consider how emotional behaviors may be affected when exposure coincides with the transition to adolescence - a vulnerable time for developing mental health difficulties. This study investigates if annual average PM2.5 and NO2 exposure at ages 9-10 years moderates age-related changes in internalizing and externalizing behaviors over a 2-year follow-up period in a large, nationwide U.S. sample of participants from the Adolescent Brain Cognitive Development (ABCD) Study®. Air pollution exposure was estimated based on the residential address of each participant using an ensemble-based modeling approach. Caregivers answered questions from the Child Behavior Checklist (CBCL) at the baseline, 1-year follow-up, and 2-year follow-up visits, for a total of 3 waves of data; from the CBCL we obtained scores on internalizing and externalizing problems plus 5 syndrome scales (anxious/depressed, withdrawn/depressed, rule-breaking behavior, aggressive behavior, and attention problems). Zero-inflated negative binomial models were used to examine both the main effect of age as well as the interaction of age with each pollutant on behavior while adjusting for various socioeconomic and demographic characteristics. Against our hypothesis, there was no evidence that greater air pollution exposure was related to more behavioral problems with age over time.

Development of a computational model to inform environmental surveillance sampling plans for Salmonella enterica serovar Typhi in wastewater.

Typhoid fever-an acute febrile disease caused by infection with the bacterium Salmonella enterica serotype Typhi (S. Typhi)-continues to be a leading cause of global morbidity and mortality, particularly in developing countries with limited access to safe drinking water and adequate sanitation. Environmental surveillance, the process of detecting and enumerating disease-causing agents in wastewater, is a useful tool to monitor the circulation of typhoid fever in endemic regions. The design of environmental surveillance sampling plans and the interpretation of sampling results is complicated by a high degree of uncertainty and variability in factors that affect the final measured pathogens in wastewater samples, such as pathogen travel time through a wastewater network, pathogen dilution, decay and degradation, and laboratory processing methods. Computational models can, to an extent, assist in the design of sampling plans and aid in the evaluation of how different contributing factors affect sampling results. This study presents a computational model combining dynamic and probabilistic modeling techniques to estimate-on a spatial and temporal scale-the approximate probability of detecting S. Typhi within a wastewater system. This model may be utilized to inform environmental surveillance sampling plans and may provide useful insight into selecting appropriate sampling locations and times and interpreting results. A simulated applied modeling scenario is presented to demonstrate the model's functionality for aiding an environmental surveillance study in a typhoid-endemic community.

Development, confirmation, and application of a seeded Escherichia coli process control organism to validate Salmonella enterica serovar Typhi environmental surveillance methods.

Salmonella enterica serovar Typhi (S. Typhi) is the causative agent of Typhoid fever. Blood culture is the gold standard for clinical diagnosis, but this is often difficult to employ in resource limited settings. Environmental surveillance of waste-impacted waters is a promising supplement to clinical surveillance, however validating methods is challenging in regions where S. Typhi concentrations are low. To evaluate existing S. Typhi environmental surveillance methods, a novel process control organism (PCO) was created as a biosafe surrogate. Using a previous described qPCR assay, a modified PCR amplicon for the staG gene was cloned into E. coli. We developed a target region that was recognized by the Typhoid primers in addition to a non-coding internal probe sequence. A multiplex qPCR reaction was developed that differentiates between the typhoid and control targets, with no cross-reactivity or inhibition of the two probes. The PCO was shown to mimic S. Typhi in lab-based experiments with concentration methods using primary wastewater: filter cartridge, recirculating Moore swabs, membrane filtration, and differential centrifugation. Across all methods, the PCO seeded at 10 CFU/mL and 100 CFU/mL was detected in 100% of replicates. The PCO is detected at similar quantification cycle (Cq) values across all methods at 10 CFU/mL (Average = 32.4, STDEV = 1.62). The PCO was also seeded into wastewater at collection sites in Vellore (India) and Blantyre (Malawi) where S. Typhi is endemic. All methods tested in both countries were positive for the seeded PCO. The PCO is an effective way to validate performance of environmental surveillance methods targeting S. Typhi in surface water.