Tracking changes in SARS-CoV-2 transmission with a novel outpatient sentinel surveillance system in Chicago, USA.

Public health indicators typically used for COVID-19 surveillance can be biased or lag changing community transmission patterns. In this study, we investigate whether sentinel surveillance of recently symptomatic individuals receiving outpatient diagnostic testing for SARS-CoV-2 could accurately assess the instantaneous reproductive number R(t) and provide early warning of changes in transmission. We use data from community-based diagnostic testing sites in the United States city of Chicago. Patients tested at community-based diagnostic testing sites between September 2020 and June 2021, and reporting symptom onset within four days preceding their test, formed the sentinel population. R(t) calculated from sentinel cases agreed well with R(t) from other indicators. Retrospectively, trends in sentinel cases did not precede trends in COVID-19 hospital admissions by any identifiable lead time. In deployment, sentinel surveillance held an operational recency advantage of nine days over hospital admissions. The promising performance of opportunistic sentinel surveillance suggests that deliberately designed outpatient sentinel surveillance would provide robust early warning of increasing transmission.

Validation of a Machine Learning Model to Predict Childhood Lead Poisoning.

Importance: Childhood lead poisoning causes irreversible neurobehavioral deficits, but current practice is secondary prevention. Objective: To validate a machine learning (random forest) prediction model of elevated blood lead levels (EBLLs) by comparison with a parsimonious logistic regression. Design, Setting, and Participants: This prognostic study for temporal validation of multivariable prediction models used data from the Women, Infants, and Children (WIC) program of the Chicago Department of Public Health. Participants included a development cohort of children born from January 1, 2007, to December 31, 2012, and a validation WIC cohort born from January 1 to December 31, 2013. Blood lead levels were measured until December 31, 2018. Data were analyzed from January 1 to October 31, 2019. Exposures: Blood lead level test results; lead investigation findings; housing characteristics, permits, and violations; and demographic variables. Main Outcomes and Measures: Incident EBLL (≥6 µg/dL). Models were assessed using the area under the receiver operating characteristic curve (AUC) and confusion matrix metrics (positive predictive value, sensitivity, and specificity) at various thresholds. Results: Among 6812 children in the WIC validation cohort, 3451 (50.7%) were female, 3057 (44.9%) were Hispanic, 2804 (41.2%) were non-Hispanic Black, 458 (6.7%) were non-Hispanic White, and 442 (6.5%) were Asian (mean [SD] age, 5.5 [0.3] years). The median year of housing construction was 1919 (interquartile range, 1903-1948). Random forest AUC was 0.69 compared with 0.64 for logistic regression (difference, 0.05; 95% CI, 0.02-0.08). When predicting the 5% of children at highest risk to have EBLLs, random forest and logistic regression models had positive predictive values of 15.5% and 7.8%, respectively (difference, 7.7%; 95% CI, 3.7%-11.3%), sensitivity of 16.2% and 8.1%, respectively (difference, 8.1%; 95% CI, 3.9%-11.7%), and specificity of 95.5% and 95.1% (difference, 0.4%; 95% CI, 0.0%-0.7%). Conclusions and Relevance: The machine learning model outperformed regression in predicting childhood lead poisoning, especially in identifying children at highest risk. Such a model could be used to target the allocation of lead poisoning prevention resources to these children.

Household interventions for preventing domestic lead exposure in children.

BACKGROUND: Lead poisoning is associated with physical, cognitive and neurobehavioural impairment in children and trials have tested many household interventions to prevent lead exposure. This is an update of the original review by the same authors first published in 2008. OBJECTIVES: To determine the effectiveness of household interventions in preventing or reducing lead exposure in children as measured by reductions in blood lead levels and/or improvements in cognitive development. SEARCH METHODS: We identified trials through electronic searches of CENTRAL (2012, Issue 1), MEDLINE (1948 to January Week 1 2012), EMBASE (1980 to Week 2 2012), CINAHL (1937 to January 2012), PsycINFO (1887 to January Week 2 2012), ERIC (1966 to January 2012), Sociological Abstracts (1952 to January 2012), Science Citation Index (1970 to 20 January 2012), ZETOC (20 January 2012), LILACS (20 January 2012), Dissertation Abstracts (late 1960s to January 2012), ClinicalTrials.gov (19 January 2012), Current Controlled Trials (19 January 2012), Australian New Zealand Clinical Trials Registry (19 January 2012) and the National Research Register Archive. We also contacted experts to find unpublished studies. SELECTION CRITERIA: Randomised and quasi-randomised controlled trials of household educational or environmental interventions to prevent lead exposure in children where at least one standardised outcome measure was reported. DATA COLLECTION AND ANALYSIS: Two authors independently reviewed all eligible studies for inclusion, assessed risk of bias and extracted data. We contacted trialists to obtain missing information. MAIN RESULTS: We included 14 studies (involving 2656 children). All studies reported blood lead level outcomes and none reported on cognitive or neurobehavioural outcomes. We put studies into subgroups according to their intervention type. We performed meta-analysis of both continuous and dichotomous data for subgroups where appropriate. Educational interventions were not effective in reducing blood lead levels (continuous: mean difference (MD) 0.02, 95% confidence interval (CI) -0.09 to 0.12, I(2) = 0 (log transformed); dichotomous ≥ 10µg/dL (≥ 0.48 µmol/L): relative risk (RR) 1.02, 95% CI 0.79 to 1.30, I(2)=0; dichotomous ≥ 15µg/dL (≥ 0.72 µmol/L): RR 0.60, 95% CI 0.33 to 1.09, I(2) = 0). Meta-analysis for the dust control subgroup also found no evidence of effectiveness (continuous: MD -0.15, 95% CI -0.42 to 0.11, I(2) = 0.9 (log transformed); dichotomous ≥ 10µg/dL (≥ 0.48 µmol/L): RR 0.93, 95% CI 0.73 to 1.18, I(2) =0; dichotomous ≥ 15µg/dL (≥ 0.72 µmol/L): RR 0.86, 95% CI 0.35 to 2.07, I(2) = 0.56). When meta-analysis for the dust control subgroup was adjusted for clustering, no statistical significant benefit was incurred. The studies using soil abatement (removal and replacement) and combination intervention groups were not able to be meta-analysed due to substantial differences between studies. AUTHORS' CONCLUSIONS: Based on current knowledge, household educational or dust control interventions are ineffective in reducing blood lead levels in children as a population health measure. There is currently insufficient evidence to draw conclusions about the effectiveness of soil abatement or combination interventions.Further trials are required to establish the most effective intervention for prevention of lead exposure. Key elements of these trials should include strategies to reduce multiple sources of lead exposure simultaneously using empirical dust clearance levels. It is also necessary for trials to be carried out in developing countries and in differing socioeconomic groups in developed countries.

An English/Spanish safety climate scale for construction workers.

BACKGROUND: Workers in the construction trades experience high rates of traumatic injury. An increasing number of workers in this industry speak only Spanish, including members of construction trade unions. This brief communication reports a dual language safety climate scale developed during a larger training intervention study. METHODS: Construction workers in two unions self-completed a previously validated 6-item safety climate scale modified for the construction trades. A seventh item was developed midway through the study and incorporated into the version completed by half of the respondents. For one union with a sizeable number of Spanish-speaking members, a dual-language (Spanish/English) version was administered. Follow-up telephone interviews conducted 3 months after the self-completed survey also included the safety climate scale. RESULTS: Cronbach's coefficient alpha was 0.85 for the 6-item scale and 0.85 for the 7-item scale. Similar coefficient alpha scores were found for the subgroup of Spanish-speakers on the 6- and 7-item scales. Spanish speakers with low education were less likely to respond to the scale when self-completing but not when it was administered by telephone in Spanish. CONCLUSION: This safety climate scale elicits consistent and reliable response from unionized construction workers when administered in English or in Spanish. Spanish literacy may be a consideration for the use of this scale among foreign-born Hispanic workers.