Unmatched spatially stratified controls: A simulation study examining efficiency and precision using spatially-diverse controls and generalized additive models.

Unmatched spatially stratified random sampling (SSRS) of non-cases selects geographically balanced controls by dividing the study area into spatial strata and randomly selecting controls from all non-cases within each stratum. The performance of SSRS control selection was evaluated in a case study spatial analysis of preterm birth in Massachusetts. In a simulation study, we fit generalized additive models using controls selected by SSRS or simple random sample (SRS) designs. We compared mean squared error (MSE), bias, relative efficiency (RE), and statistically significant map results to the model results with all non-cases. SSRS designs had lower average MSE (0.0042-0.0044) and higher RE (77-80%) compared to SRS designs (MSE: 0.0072-0.0073; RE across designs: 71%). SSRS map results were more consistent across simulations, reliably identifying statistically significant areas. SSRS designs improved efficiency by selecting controls that are geographically distributed, particularly from low population density areas, and may be more appropriate for spatial analyses.

Effect of socioeconomic factors during the early COVID-19 pandemic: a spatial analysis.

BACKGROUND: Spatial variability of COVID-19 cases may suggest geographic disparities of social determinants of health. Spatial analyses of population-level data may provide insight on factors that may contribute to COVID-19 transmission, hospitalization, and death. METHODS: Generalized additive models were used to map COVID-19 risk from March 2020 to February 2021 in Orange County (OC), California. We geocoded and analyzed 221,843 cases to OC census tracts within a Poisson framework while smoothing over census tract centroids. Location was randomly permuted 1000 times to test for randomness. We also separated the analyses temporally to observe if risk changed over time. COVID-19 cases, hospitalizations, and deaths were mapped across OC while adjusting for population-level demographic data in crude and adjusted models. RESULTS: Risk for COVID-19 cases, hospitalizations, and deaths were statistically significant in northern OC. Adjustment for demographic data substantially decreased spatial risk, but areas remained statistically significant. Inclusion of location within our models considerably decreased the magnitude of risk compared to univariate models. However, percent minority (adjusted RR: 1.06, 95%CI: 1.06, 1.07), average household size (aRR: 1.06, 95%CI: 1.05, 1.07), and percent service industry (aRR: 1.05, 95%CI: 1.04, 1.06) remained significantly associated with COVID-19 risk in adjusted spatial models. In addition, areas of risk did not change between surges and risk ratios were similar for hospitalizations and deaths. CONCLUSION: Significant risk factors and areas of increased risk were identified in OC in our adjusted models and suggests that social and environmental factors contribute to the spread of COVID-19 within communities. Areas in north OC remained significant despite adjustment, but risk substantially decreased. Additional investigation of risk factors may provide insight on how to protect vulnerable populations in future infectious disease outbreaks.

SARS-CoV-2 antibody seroprevalence among firefighters in Orange County, California.

OBJECTIVES: We conducted serological SARS-CoV-2 antibody testing from October to November 2020 to estimate the SARS-CoV-2 seroprevalence among firefighters/paramedics in Orange County (OC), California. METHODS: OC firefighters employed at the time of the surveillance activity were invited to participate in a voluntary survey that collected demographic, occupational and previous COVID-19 testing data, and a SARS-CoV-2 immunoglobulin (Ig)G antibody blood test. We collected venous blood samples using mobile phlebotomy teams that travelled to individual fire stations, in coordination with an annual tuberculosis testing campaign for firefighters employed by OC Fire Authority (OCFA), and independently for firefighters employed by cities. We estimated seroprevalence and assessed several potential predictors of seropositivity. RESULTS: The seroprevalence was 5.3% among 923 OCFA personnel tested, with 92.2% participating. Among firefighters self-reporting a previous positive COVID-19 antibody or PCR test result, twenty-one (37%) did not have positive IgG tests in the current serosurvey. There were no statistically significant differences in demographic characteristics between cases and non-cases. Work city was a significant predictor of case status (p=0.015). Seroprevalence (4.8%) was similar when aggregated across seven city fire departments (42%-65% participation). In total, 1486°C fire personnel were tested. CONCLUSION: Using a strong serosurvey design and large firefighter cohort, we observed a SARS-CoV-2 IgG seroprevalence of 5.3%. The seroprevalence among OC firefighters in October 2020 was lower than the general county population estimated seroprevalence (11.5%) in August. The difference may be due in part to safety measures taken by OC fire departments at the start of the pandemic, as well as differences in antibody test methods and/or duration of antibody response.

A spatial analysis of birth defects in Texas, 1999-2011.

BACKGROUND: The etiologies of major birth defects are still unclear and few spatial analyses have been conducted in the United States. Spatial analyses of individual-level data can help elucidate environmental and social risk factors. METHODS: We used generalized additive models to analyze 52,955 cases of neural tube defects, congenital heart defects (CHDs), gastroschisis, and orofacial cleft defects, and sampled from 642,399 controls born between 1999 and 2011 in Texas. The effect of geographic location was measured using a bivariable smooth term of geocoded birth address within a logistic regression framework. We calculated and mapped odds ratios (ORs) and 95% confidence intervals (CIs) for birth defects subtypes across Texas, and adjusted for maternal characteristics, environmental indicators, and community-level covariates. We also performed time-stratified spatiotemporal analyses for more prevalent birth defects. RESULTS: Location was significantly associated with crude odds of all birth defects except hypoplastic left heart syndrome. After adjusting for maternal characteristics, environmental indicators, and community-level factors, ORs in many geographic areas were no longer statistically significant for most defects, especially CHDs. However, areas of significant and insignificant elevated risk remained for defects in all groups in North and South Texas, with ORs for ventricular septal defects increasing over time. Low risk of birth defects was often present in the northern part of East Texas. CONCLUSION: Significant spatial patterns of birth defects were identified and varied depending on adjustment of different categories of covariates. Further investigation of areas with increased risks may aid in our understanding of birth defects.

Birth defects and unconventional natural gas developments in Texas, 1999-2011.

Unconventional natural gas developments (UNGD) may release air and water pollutants into the environment, potentially increasing the risk of birth defects. We conducted a case-control study evaluating 52,955 cases with birth defects and 642,399 controls born between 1999 and 2011 to investigate the relationship between UNGD exposure and the risk of gastroschisis, congenital heart defects (CHD), neural tube defects (NTDs), and orofacial clefts in Texas. We calculated UNGD densities (number of UNGDs per area) within 1, 3, and 7.5 km of maternal address at birth and categorized exposure by density tertiles. For CHD subtypes with large case numbers, we also performed time-stratified analyses to examine temporal trends. We calculated adjusted odds ratios (aOR) and 95% confidence intervals (CI) for the association with UNGD exposure, accounting for maternal characteristics and neighborhood factors. We also included a bivariable smooth of geocoded maternal location in an additive model to account for unmeasured spatially varying risk factors. Positive associations were observed between the highest tertile of UNGD density within 1 km of maternal address and risk of anencephaly (aOR: 2.44, 95% CI: 1.55, 3.86), spina bifida (aOR: 2.09, 95% CI: 1.47, 2.99), gastroschisis among older mothers (aOR: 3.19, 95% CI: 1.77, 5.73), aortic valve stenosis (aOR: 1.90, 95% CI: 1.33, 2.71), hypoplastic left heart syndrome (aOR: 2.00, 95% CI: 1.39, 2.86), and pulmonary valve atresia or stenosis (aOR: 1.36, 95% CI: 1.10, 1.66). For CHD subtypes, results did not differ substantially by distance from maternal address or when residual confounding was considered, except for atrial septal defects. We did not observe associations with orofacial clefts. Our results suggest that UNGDs were associated with some CHDs and possibly NTDs. In addition, we identified temporal trends and observed presence of spatial residual confounding for some CHDs.

Spatiotemporal analysis of human exposure to halogenated flame retardant chemicals.

Human exposure to flame retardants occurs in microenvironments due to their ubiquitous presence in consumer products and building materials. Recent research suggests higher levels of exposure through elevated surface dust (ESD) compared to floor dust (FD). However, it is unclear whether this pattern is consistent in different microenvironments beyond the home. We hypothesized that time spent in various microenvironments will significantly modify the pattern of human exposure to flame retardant chemicals in ESD and FD. We tested this hypothesis by collecting time activity diaries from 43 participants; and by estimating human exposure to 10 polybrominated diphenyl ether and 8 non-polybrominated diphenyl ether flame retardant chemicals, based on chemical concentrations measured in different microenvironments visited by the participants. The results of paired t-tests show that, with some notable exceptions, estimates of human exposure to most chemicals through ESD are statistically significantly higher for ∑PBDE (p=0.00) and ∑non-PBDEs (p=0.00) than through FD. This study reinforces the need to integrate temporal, locational, and elevation dimensions in assessing human exposure to potentially toxic flame retardant chemicals.

Potential human exposure to halogenated flame-retardants in elevated surface dust and floor dust in an academic environment.

Most households and workplaces all over the world possess furnishings and electronics, all of which contain potentially toxic flame retardant chemicals to prevent fire hazards. Indoor dust is a recognized repository of these types of chemicals including polybrominated diphenyl ethers (PBDEs) and non-polybrominated diphenyl ethers (non-PBDEs). However, no previous U.S. studies have differentiated concentrations from elevated surface dust (ESD) and floor dust (FD) within and across microenvironments. We address this information gap by measuring twenty-two flame-retardant chemicals in dust on elevated surfaces (ESD; n=10) and floors (FD; n=10) from rooms on a California campus that contain various concentrations of electronic products. We hypothesized a difference in chemical concentrations in ESD and FD. Secondarily, we examined whether or not this difference persisted: (a) across the studied microenvironments and (b) in rooms with various concentrations of electronics. A Wilcoxon signed-rank test demonstrated that the ESD was statistically significantly higher than FD for BDE-47 (p=0.01), BDE-99 (p=0.01), BDE-100 (p=0.01), BDE-153 (p=0.02), BDE-154 (p=0.02), and 3 non-PBDEs including EH-TBB (p=0.02), BEH-TEBP (p=0.05), and TDCIPP (p=0.03). These results suggest different levels and kinds of exposures to flame-retardant chemicals for individuals spending time in the sampled locations depending on the position of accumulated dust. Therefore, further research is needed to estimate human exposure to flame retardant chemicals based on how much time and where in the room individuals spend their time. Such sub-location estimates will likely differ from assessments that assume continuous unidimensional exposure, with implications for improved understanding of potential health impacts of flame retardant chemicals.