Robot-Assisted Surgery and Racial and Ethnic Disparities in Post-Prostatectomy Outcomes Among Prostate Cancer Patients.

BACKGROUND: We sought to determine whether the differences in short-term outcomes between patients undergoing robot-assisted radical prostatectomy (RARP) and those treated with open radical prostatectomy (ORP) differ by race and ethnicity. METHODS: This observational study used New York State Cancer Registry data linked to discharge records and included patients undergoing radical prostatectomy for localized prostate cancer during 2008-2018. We used logistic regression to examine the association between race and ethnicity (non-Hispanic White [NHW], non-Hispanic Black [NHB], Hispanic), surgical approach (RARP, ORP), and postoperative outcomes (major events, prolonged length of stay [pLOS], 30-day re-admission). We tested interaction between race and ethnicity and surgical approach on multiplicative and additive scales. RESULTS: The analytical cohort included 18,926 patients (NHW 14,215 [75.1%], NHB 3195 [16.9%], Hispanic 1516 [8.0%]). The average age was 60.4 years (standard deviation 7.1). NHB and Hispanic patients had lower utilization of RARP and higher risks of postoperative adverse events than NHW patients. NHW, NHB, and Hispanic patients all had reduced risks of adverse events when undergoing RARP versus ORP. The absolute reductions in the risks of major events and pLOS following RARP versus ORP were larger among NHB {relative excess risk due to interaction (RERI): major events -0.32 [95% confidence interval (CI) -0.71 to -0.03]; pLOS -0.63 [95% CI -0.98 to -0.35]) and Hispanic (RERI major events -0.27 [95% CI -0.77 to 0.09]; pLOS -0.93 [95% CI -1.46 to -0.51]) patients than among NHW patients. The interaction was absent on the multiplicative scale. CONCLUSIONS: RARP use has not penetrated and benefited all racial and ethnic groups equally. Increasing utilization of RARP among NHB and Hispanic patients may help reduce disparities in patient outcomes after radical prostatectomy.

Wastewater surveillance provides 10-days forecasting of COVID-19 hospitalizations superior to cases and test positivity: A prediction study.

Background: The public health response to COVID-19 has shifted to reducing deaths and hospitalizations to prevent overwhelming health systems. The amount of SARS-CoV-2 RNA fragments in wastewater are known to correlate with clinical data including cases and hospital admissions for COVID-19. We developed and tested a predictive model for incident COVID-19 hospital admissions in New York State using wastewater data. Methods: Using county-level COVID-19 hospital admissions and wastewater surveillance covering 13.8 million people across 56 counties, we fit a generalized linear mixed model predicting new hospital admissions from wastewater concentrations of SARS-CoV-2 RNA from April 29, 2020 to June 30, 2022. We included covariates such as COVID-19 vaccine coverage in the county, comorbidities, demographic variables, and holiday gatherings. Findings: Wastewater concentrations of SARS-CoV-2 RNA correlated with new hospital admissions per 100,000 up to ten days prior to admission. Models that included wastewater had higher predictive power than models that included clinical cases only, increasing the accuracy of the model by 15%. Predicted hospital admissions correlated highly with observed admissions (r = 0.77) with an average difference of 0.013 hospitalizations per 100,000 (95% CI = [0.002, 0.025]). Interpretation: Using wastewater to predict future hospital admissions from COVID-19 is accurate and effective with superior results to using case data alone. The lead time of ten days could alert the public to take precautions and improve resource allocation for seasonal surges.

Spatial Variation in COVID-19 Mortality in New York City and Its Association with Neighborhood Race, Ethnicity, and Nativity Status.

We examined the association between variation in COVID-19 deaths and spatial differences in the racial, ethnic, and nativity-status composition of New York City neighborhoods, which has received little scholarly attention. Using COVID-19 mortality data (through 31 May 2021) and socioeconomic and demographic data from the American Community Survey at the Zip Code Tabulation Area level as well as United-Hospital-Fund-level neighborhood data from the Community Health Survey of the New York City Department of Health and Mental Hygiene, we employed multivariable Poisson generalized estimating equation models and assessed the association between COVID-19 mortality, racial/ethnic/nativity-status composition, and other ecological factors. Our results showed an association between neighborhood-level racial and ethnic composition and COVID-19 mortality rates that is contingent upon the neighborhood-level nativity-status composition. After multivariable adjustment, ZCTAs with large shares of native-born Blacks and foreign-born Hispanics and Asians were more likely to have higher COVID-19 mortality rates than areas with large shares of native-born Whites. Areas with more older adults and essential workers, higher levels of household crowding, and population with diabetes were also at high risk. Small-area analyses of COVID-19 mortality can inform health policy responses to neighborhood inequalities on the basis of race, ethnicity, and immigration status.

Assessing the Effect of Precipitation on Asthma Emergency Department Visits in New York State From 2005 to 2014: A Case-Crossover Study.

The Earth's precipitation patterns are changing, and regional precipitation is expected to continue to increase in New York State (NYS). Heavy precipitation may negatively affect asthma prevalence through its effect on seasonally varying allergens. We employed a threshold analysis using a time-stratified semi-symmetric bi-directional case-crossover study design to assess the effect of increase in precipitation on asthma (ICD-9 code 493.xx, N = 970,903) emergency department (ED) visits between 2005 and 2014 during non-winter months in NYS. Spatially contiguous gridded meteorological data from North American Land Data Assimilation System (NLDAS) were utilized. We used conditional logistic regression models and stratified the analyses by seasons. During non-winter months, we found a small, statistically significant risk of asthma ED visits for precipitation levels above 50 mm, with differences by season. These results suggest that heavy precipitation may be related to an increased risk of asthma ED visits. Gridded meteorological estimates provide a means of addressing the gaps in exposure classification, and these findings provide opportunities for further research on interactions with aeroallergens and meteorological conditions in the context of climate and health.

Neighborhood Deprivation and Neural Tube Defects.

BACKGROUND: Individual measures of socioeconomic status (SES) have been associated with an increased risk of neural tube defects (NTDs); however, the association between neighborhood SES and NTD risk is unknown. Using data from the National Birth Defects Prevention Study (NBDPS) from 1997 to 2011, we investigated the association between measures of census tract SES and NTD risk. METHODS: The study population included 10,028 controls and 1829 NTD cases. We linked maternal addresses to census tract SES measures and used these measures to calculate the neighborhood deprivation index. We used generalized estimating equations to calculate adjusted odds ratios (aORs) and 95% confidence intervals (CIs) estimating the impact of quartiles of census tract deprivation on NTDs adjusting for maternal race-ethnicity, maternal education, and maternal age at delivery. RESULTS: Quartiles of higher neighborhood deprivation were associated with NTDs when compared with the least deprived quartile (Q2: aOR = 1.2; 95% CI = 1.0, 1.4; Q3: aOR = 1.3, 95% CI = 1.1, 1.5; Q4 (highest): aOR = 1.2; 95% CI = 1.0, 1.4). Results for spina bifida were similar; however, estimates for anencephaly and encephalocele were attenuated. Associations differed by maternal race-ethnicity. CONCLUSIONS: Our findings suggest that residing in a census tract with more socioeconomic deprivation is associated with an increased risk for NTDs, specifically spina bifida.

Is gastroschisis associated with county-level socio-environmental quality during pregnancy?

BACKGROUND: Gastroschisis prevalence more than doubled between 1995 and 2012. While there are individual-level risk factors (e.g., young maternal age, low body mass index), the impact of environmental exposures is not well understood. METHODS: We used the U.S. Environmental Protection Agency's Environmental Quality Index (EQI) as a county-level estimate of cumulative environmental exposures for five domains (air, water, land, sociodemographic, and built) and overall from 2006 to 2010. Adjusted odds ratios (aOR) and 95% confidence interval (CI) were estimated from logistic regression models between EQI tertiles (better environmental quality (reference); mid; poorer) and gastroschisis in the National Birth Defects Prevention Study from births delivered between 2006 and 2011. Our analysis included 594 cases with gastroschisis and 4105 infants without a birth defect (controls). RESULTS: Overall EQI was modestly associated with gastroschisis (aOR [95% CI]: 1.29 [0.98, 1.71]) for maternal residence in counties with poorer environmental quality, compared to the reference (better environmental quality). Within domain-specific indices, only the sociodemographic domain (aOR: 1.51 [0.99, 2.29]) was modestly associated with gastroschisis, when comparing poorer to better environmental quality. CONCLUSIONS: Future work could elucidate pathway(s) by which components of the sociodemographic domain or possibly related psychosocial factors like chronic stress potentially contribute to risk of gastroschisis.

Are individual-level risk factors for gastroschisis modified by neighborhood-level socioeconomic factors?

BACKGROUND: Two strong risk factors for gastroschisis are young maternal age (<20 years) and low/normal pre-pregnancy body mass index (BMI), yet the reasons remain unknown. We explored whether neighborhood-level socioeconomic position (nSEP) during pregnancy modified these associations. METHODS: We analyzed data from 1269 gastroschisis cases and 10,217 controls in the National Birth Defects Prevention Study (1997-2011). To characterize nSEP, we applied the neighborhood deprivation index and used generalized estimating equations to calculate odds ratios and relative excess risk due to interaction. RESULTS: Elevated odds of gastroschisis were consistently associated with young maternal age and low/normal BMI, regardless of nSEP. High-deprivation neighborhoods modified the association with young maternal age. Infants of young mothers in high-deprivation areas had lower odds of gastroschisis (adjusted odds ratio [aOR]: 3.1, 95% confidence interval [CI]: 2.6, 3.8) than young mothers in low-deprivation areas (aOR: 6.6; 95% CI: 4.6, 9.4). Mothers of low/normal BMI had approximately twice the odds of having an infant with gastroschisis compared to mothers with overweight/obese BMI, regardless of nSEP (aOR range: 1.5-2.3). CONCLUSION: Our findings suggest nSEP modified the association between gastroschisis and maternal age, but not BMI. Further research could clarify whether the modification is due to unidentified biologic and/or non-biologic factors.

Neighborhood-level Socioeconomic Position During Early Pregnancy and Risk of Gastroschisis.

BACKGROUND: Neighborhood-level socioeconomic position has been shown to influence birth outcomes, including selected birth defects. This study examines the un derstudied association between neighborhood-level socioeconomic position during early pregnancy and the risk of gastroschisis, an abdominal birth defect of increasing prevalence. METHODS: We conducted a case-control study of 1,269 gastroschisis cases and 10,217 controls using data from the National Birth Defects Prevention Study (1997-2011). To characterize neighborhood-level socioeconomic position, we conducted a principal component analysis to construct two indices-Neighborhood Deprivation Index (NDI) and Neighborhood Socioeconomic Position Index (nSEPI). We created neighborhood-level indices using census socioeconomic indicators corresponding to census tracts associated with addresses where mothers lived the longest during the periconceptional period. We used generalized estimating equations to estimate odds ratios (ORs) and 95% confidence intervals (CIs), with multiple imputations for missing data and adjustment for maternal race-ethnicity, household income, education, birth year, and duration of residence. RESULTS: Mothers residing in moderate (NDI Tertile 2 aOR = 1.23; 95% CI = 1.03, 1.48 and nSEPI Tertile 2 aOR = 1.24; 95% CI = 1.04, 1.49) or low socioeconomic neighborhoods (NDI Tertile 3 aOR = 1.28; 95% CI = 1.05, 1.55 and nSEPI Tertile 3 aOR = 1.32, 95% CI = 1.09, 1.61) were more likely to deliver an infant with gastroschisis compared with mothers residing in high socioeconomic neighborhoods. CONCLUSIONS: Our findings suggest that lower neighborhood-level socioeconomic position during early pregnancy is associated with elevated odds of gastroschisis. Additional epidemiologic studies may aid in confirming this finding and evaluating potential mechanisms linking neighborhood-level socioeconomic factors and gastroschisis.

Assessing associations between residential proximity to greenspace and birth defects in the National Birth Defects Prevention Study.

BACKGROUND: Residential proximity to greenspace is associated with various health outcomes. OBJECTIVES: We estimated associations between maternal residential proximity to greenspace (based on an index of vegetation) and selected structural birth defects, including effect modification by neighborhood-level factors. METHODS: Data were from the National Birth Defects Prevention Study (1997-2011) and included 19,065 infants with at least one eligible birth defect (cases) and 8925 without birth defects (controls) from eight Centers throughout the United States. Maternal participants reported their addresses throughout pregnancy. Each address was systematically geocoded and residences around conception were linked to greenspace, US Census, and US Department of Agriculture data. Greenspace was estimated using the normalized difference vegetation index (NDVI); average maximum NDVI was estimated within 100 m and 500 m concentric buffers surrounding geocoded addresses to estimate residential NDVI. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals comparing those in the highest and lowest quartiles of residential NDVI and stratifying by rural/urban residence and neighborhood median income. RESULTS: After multivariable adjustment, for the 500 m buffer, inverse associations were observed for tetralogy of Fallot, secundum atrial septal defects, anencephaly, anotia/microtia, cleft lip ± cleft palate, transverse limb deficiency, and omphalocele, (aORs: 0.54-0.86). Results were similar for 100 m buffer analyses and similar patterns were observed for other defects, though results were not significant. Significant heterogeneity was observed after stratification by rural/urban for hypoplastic left heart, coarctation of the aorta, and cleft palate, with inverse associations only among participants residing in rural areas. Stratification by median income showed heterogeneity for atrioventricular and secundum atrial septal defects, anencephaly, and anorectal atresia, with inverse associations only among participants residing in a high-income neighborhood (aORs: 0.45-0.81). DISCUSSION: Our results suggest that perinatal residential proximity to more greenspace may contribute to a reduced risk of certain birth defects, especially among those living in rural or high-income neighborhoods.

Using LexisNexis to Improve Social Security Number Information in the New York State Cancer Registry.

Background: Social Security numbers (SSNs) collected by cancer surveillance registries in the United States are used for patient matching, deduplication, follow-up, and linkage studies. However, due to various reasons, a small proportion of patient records have missing or inaccurate SSNs. Recently, New York State Cancer Registry (NYSCR) data have been linked to LexisNexis data to obtain patient demographic information, including SSNs. The current study evaluated the feasibility of using LexisNexis to improve SSN information in the NYSCR. Materials and Methods: Patients diagnosed during the years 2005-2016, aged 21 or older, in the NYSCR were linked to LexisNexis data. For the matched patients, LexisNexis returned demographic information, including SSNs as available. Percentages of patients without LexisNexis matches or without LexisNexis SSNs were examined by demographic characteristics. We used multivariate logistic regression analyses to further evaluate how patient demographic characteristics affected the likelihood of no LexisNexis matches or of no SSNs returned. For patients with SSNs returned, LexisNexis SSNs were compared with registry SSNs. If patients had prior missing registry SSNs or if LexisNexis SSNs were inconsistent with registry SSNs, we used Match*Pro to review and verify match status. Registry SSNs were updated for those confirmed to be true matches. Improvement of SSNs was assessed based on percentage reduction of missingness. Results: Of 1,396,078 patient records submitted for LexisNexis linkage, 1.6% were not matched. Among those matched, 1.5% did not have SSNs returned. Multivariate logistic regression analyses indicated that patients who were female, Black, Asian Pacific Islander (API), Hispanic, born outside the United States, deceased, or living in poorer census tracts were more likely to not have LexisNexis matches, or to not have SSNs returned. Among 47,271 patients with missing registry SSNs (3.4%), 26,895 had SSNs returned from LexisNexis, and 24,919 were confirmed to be true matches. After registry SSNs updates, the percentage of SSN missingness was reduced to 1.7%, with a larger absolute reduction observed among those who were younger than 60 years, API, or alive. For 33,057 patients with inconsistent SSNs, 11,474 were due to incorrect consolidations of SSNs in the registry, and those SSNs were subsequently fixed. Conclusions: LexisNexis is a valuable resource for improving the quality of SSN information in registries. Our results showed that the overall percentage of patients with missing SSNs was reduced from 3.4% to 1.7% after LexisNexis link-age, and SSNs that were initially incorrectly consolidated for some patients were also identified and subsequently fixed. However, the magnitude of SSN improvement varied by patient demographic characteristics. Data quality improvements often require resources, and this evaluation can assist registries with decisions related to similar efforts.

Identifying Risk Factors for Hospitalization with Behavioral Health Disorders and Concurrent Temperature-Related Illness in New York State.

Extreme temperature events are linked to increased emergency department visits, hospitalizations, and mortality for individuals with behavioral health disorders (BHD). This study aims to characterize risk factors for concurrent temperature-related illness among BHD hospitalizations in New York State. Using data from the NYS Statewide and Planning Research and Cooperative System between 2005-2019, multivariate log binomial regression models were used in a population of BHD hospitalizations to estimate risk ratios (RR) for a concurrent heat-related (HRI) or cold-related illness (CRI). Dementia (RR 1.65; 95% CI:1.49, 1.83) and schizophrenia (RR 1.38; 95% CI:1.19, 1.60) were associated with an increased risk for HRI among BHD hospitalizations, while alcohol dependence (RR 2.10; 95% CI:1.99, 2.22), dementia (RR 1.52; 95% CI:1.44, 1.60), schizophrenia (RR 1.41; 95% CI:1.31, 1.52), and non-dependent drug/alcohol use (RR 1.20; 95% CI:1.15, 1.26) were associated with an increased risk of CRI among BHD hospitalizations. Risk factors for concurrent HRI among BHD hospitalizations include increasing age, male gender, non-Hispanic Black race, and medium hospital size. Risk factors for concurrent CRI among BHD hospitalizations include increasing age, male gender, non-Hispanic Black race, insurance payor, the presence of respiratory disease, and rural hospital location. This study adds to the literature by identifying dementia, schizophrenia, substance-use disorders, including alcohol dependence and non-dependent substance-use, and other sociodemographic factors as risk factors for a concurrent CRI in BHD hospitalizations.

Public Health Response to a Case of Paralytic Poliomyelitis in an Unvaccinated Person and Detection of Poliovirus in Wastewater - New York, June-August 2022.

On July 18, 2022, the New York State Department of Health (NYSDOH) notified CDC of detection of poliovirus type 2 in stool specimens from an unvaccinated immunocompetent young adult from Rockland County, New York, who was experiencing acute flaccid weakness. The patient initially experienced fever, neck stiffness, gastrointestinal symptoms, and limb weakness. The patient was hospitalized with possible acute flaccid myelitis (AFM). Vaccine-derived poliovirus type 2 (VDPV2) was detected in stool specimens obtained on days 11 and 12 after initial symptom onset. To date, related Sabin-like type 2 polioviruses have been detected in wastewater* in the patient's county of residence and in neighboring Orange County up to 25 days before (from samples originally collected for SARS-CoV-2 wastewater monitoring) and 41 days after the patient's symptom onset. The last U.S. case of polio caused by wild poliovirus occurred in 1979, and the World Health Organization Region of the Americas was declared polio-free in 1994. This report describes the second identification of community transmission of poliovirus in the United States since 1979; the previous instance, in 2005, was a type 1 VDPV (1). The occurrence of this case, combined with the identification of poliovirus in wastewater in neighboring Orange County, underscores the importance of maintaining high vaccination coverage to prevent paralytic polio in persons of all ages.

Road traffic density and recurrent asthma emergency department visits among Medicaid enrollees in New York State 2005-2015.

BACKGROUND: Environmental exposures such as traffic may contribute to asthma morbidity including recurrent emergency department (ED) visits. However, these associations are often confounded by socioeconomic status and health care access. OBJECTIVE: This study aims to assess the association between traffic density and recurrence of asthma ED visits in the primarily low income Medicaid population in New York State (NYS) between 2005 and 2015. METHODS: The primary outcome of interest was a recurrent asthma ED visit within 1-year of index visit. Traffic densities (weighted for truck traffic) were spatially linked based on home addresses. Bivariate and multivariate logistic regression analyses were conducted to identify factors predicting recurrent asthma ED visits. RESULTS: In a multivariate model, Medicaid recipients living within 300-m of a high traffic density area were at a statistically significant risk of a recurrent asthma ED visit compared to those in a low traffic density area (OR = 1.31; 95% CI:1.24,1.38). Additionally, we evaluated effect measure modification for risk of recurrent asthma visits associated with traffic exposure by socio-demographic factors. The highest risk was found for those exposed to high traffic and being male (OR = 1.87; 95% CI:1.46,2.39), receiving cash assistance (OR = 2.11; 95% CI:1.65,2.72), receiving supplemental security income (OR = 2.21; 95% CI:1.66,2.96) and being in the 18.44 age group (OR = 1.59;95% CI 1.48,1.70) was associated with the highest risk of recurrent asthma ED visit. Black non-Hispanics (OR = 2.35; 95% CI:1.70,3.24), Hispanics (OR = 2.13; 95% CI:1.49,3.04) and those with race listed as "Other" (OR = 1.89 95% CI:1.13,3.16) in high traffic areas had higher risk of recurrent asthma ED visits as compared to White non-Hispanics in low traffic areas. CONCLUSION: We observed significant persistent disparities in asthma morbidity related to traffic exposure and race/ethnicity in a low-income population. Our findings suggest that even within a primarily low-income study population, socioeconomic differences persist. These differences in susceptibility in the extremely low-income group may not be apparent in health studies that use Medicaid enrollment as a proxy for low SES.

Coupling freedom from disease principles and early warning from wastewater surveillance to improve health security.

Infectious disease surveillance is vitally important to maintaining health security, but these efforts are challenged by the pace at which new pathogens emerge. Wastewater surveillance can rapidly obtain population-level estimates of disease transmission, and we leverage freedom from disease principles to make use of nondetection of SARS-CoV-2 in wastewater to estimate the probability that a community is free from SARS-CoV-2 transmission. From wastewater surveillance of 24 treatment plants across upstate New York from May through December of 2020, trends in the intensity of SARS-CoV-2 in wastewater correlate with trends in COVID-19 incidence and test positivity (⍴ > 0.5), with the greatest correlation observed for active cases and a 3-day lead time between wastewater sample date and clinical test date. No COVID-19 cases were reported 35% of the time the week of a nondetection of SARS-CoV-2 in wastewater. Compared to the United States Centers for Disease Control and Prevention levels of transmission risk, transmission risk was low (no community spared) 50% of the time following nondetection, and transmission risk was moderate or lower (low community spread) 92% of the time following nondetection. Wastewater surveillance can demonstrate the geographic extent of the transmission of emerging pathogens, confirming that transmission risk is either absent or low and alerting of an increase in transmission. If a statewide wastewater surveillance platform had been in place prior to the onset of the COVID-19 pandemic, policymakers would have been able to complement the representative nature of wastewater samples to individual testing, likely resulting in more precise public health interventions and policies.

Short-term PM2.5 and cardiovascular admissions in NY State: assessing sensitivity to exposure model choice.

BACKGROUND: Air pollution health studies have been increasingly using prediction models for exposure assessment even in areas without monitoring stations. To date, most studies have assumed that a single exposure model is correct, but estimated effects may be sensitive to the choice of exposure model. METHODS: We obtained county-level daily cardiovascular (CVD) admissions from the New York (NY) Statewide Planning and Resources Cooperative System (SPARCS) and four sets of fine particulate matter (PM2.5) spatio-temporal predictions (2002-2012). We employed overdispersed Poisson models to investigate the relationship between daily PM2.5 and CVD, adjusting for potential confounders, separately for each state-wide PM2.5 dataset. RESULTS: For all PM2.5 datasets, we observed positive associations between PM2.5 and CVD. Across the modeled exposure estimates, effect estimates ranged from 0.23% (95%CI: -0.06, 0.53%) to 0.88% (95%CI: 0.68, 1.08%) per 10 µg/m3 increase in daily PM2.5. We observed the highest estimates using monitored concentrations 0.96% (95%CI: 0.62, 1.30%) for the subset of counties where these data were available. CONCLUSIONS: Effect estimates varied by a factor of almost four across methods to model exposures, likely due to varying degrees of exposure measurement error. Nonetheless, we observed a consistently harmful association between PM2.5 and CVD admissions, regardless of model choice.

Using social security number to identify sub-populations vulnerable to the health impacts from extreme heat in Florida, U.S.

BACKGROUND: Some socioeconomically vulnerable groups may experience disproportionately higher risk of extreme heat illness than other groups, but no study has utilized the presence/absence of a social security number (SSN) as a proxy for vulnerable sub-populations. METHODS: This study focused on the warm season from 2008 to 2012 in Florida, U.S. With a total number of 8,256,171 individual level health outcomes, we devised separate case-crossover models for five heat-sensitive health outcomes (cardiovascular disease, dehydration, heat-related illness, renal disease, and respiratory disease), type of health care visit (emergency department (ED) and hospitalization), and patients reporting/not reporting an SSN. Each stratified model also considered potential effect modification by sex, age, or race/ethnicity. RESULTS: Mean temperature raised the odds of five heat-sensitive health outcomes with the highest odds ratios (ORs) for heat-related illness. Sex significantly modified heat exposure effects for dehydration ED visits (Males: 1.145, 95 % CI: 1.137-1.153; Females: 1.110, 95 % CI: 1.103-1.117) and hospitalization (Males: 1.116, 95 % CI: 1.110-1.121; Females: 1.100, 95 % CI: 1.095-1.105). Patients not reporting an SSN between 25 and 44 years (1.264, 95 % CI: 1.192-1.340) exhibited significantly higher dehydration ED ORs than those reporting an SSN (1.146, 95 % CI: 1.136-1.157). We also observed significantly higher ORs for cardiovascular disease hospitalization from the no SSN group (SSN: 1.089, 95 % CI: 1.088-1.090; no SSN: 1.100, 95 % CI: 1.091-1.110). CONCLUSIONS: This paper partially supports the idea that individuals without an SSN could experience higher risks of dehydration (for those 25-45 years), renal disease, and cardiovascular disease than those with an SSN.

Co-quantification of crAssphage increases confidence in wastewater-based epidemiology for SARS-CoV-2 in low prevalence areas.

Wastewater surveillance of SARS-CoV-2 RNA is increasingly being incorporated into public health efforts to respond to the COVID-19 pandemic. In order to obtain the maximum benefit from these efforts, approaches to wastewater monitoring need to be rapid, sensitive, and relatable to relevant epidemiological parameters. In this study, we present an ultracentrifugation-based method for the concentration of SARS-CoV-2 wastewater RNA and use crAssphage, a bacteriophage specific to the human gut, to help account for RNA loss during transit in the wastewater system and sample processing. With these methods, we were able to detect, and sometimes quantify, SARS-CoV-2 RNA from 20 mL wastewater samples within as little as 4.5 hours. Using known concentrations of bovine coronavirus RNA and deactivated SARS-CoV-2, we estimate recovery rates of approximately 7-12% of viral RNA using our method. Results from 24 sewersheds across Upstate New York during the spring and summer of 2020 suggested that stronger signals of SARS-CoV-2 RNA from wastewater may be indicative of greater COVID-19 incidence in the represented service area approximately one week in advance. SARS-CoV-2 wastewater RNA was quantifiable in some service areas with daily positives tests of less than 1 per 10,000 people or when weekly positive test rates within a sewershed were as low as 1.7%. crAssphage DNA concentrations were significantly lower during periods of high flow in almost all areas studied. After accounting for flow rate and population served, crAssphage levels per capita were estimated to be about 1.35 × 1011 and 2.42 × 108 genome copies per day for DNA and RNA, respectively. A negative relationship between per capita crAssphage RNA and service area size was also observed likely reflecting degradation of RNA over long transit times. Our results reinforce the potential for wastewater surveillance to be used as a tool to supplement understanding of infectious disease transmission obtained by traditional testing and highlight the potential for crAssphage co-detection to improve interpretations of wastewater surveillance data.

Access to cardiac surgery centers for cardiac and non-cardiac hospitalizations in adolescents and adults with congenital heart defects- a descriptive case series study.

BACKGROUND: Individuals with congenital heart defects (CHDs) are recommended to receive all inpatient cardiac and noncardiac care at facilities that can offer specialized care. We describe geographic accessibility to such centers in New York State and determine several factors associated with receiving care there. METHODS: We used inpatient hospitalization data from the Statewide Planning and Research Cooperative System (SPARCS) in New York State 2008-2013. In the absence of specific adult CHD care center designations during our study period, we identified pediatric/adult and adult-only cardiac surgery centers through the Cardiac Surgery Reporting System to estimate age-based specialized care. We calculated one-way drive and public transit time (in minutes) from residential address to centers using R gmapsdistance package and the Google Maps Distance Application Programming Interface (API). We calculated prevalence ratios using modified Poisson regression with model-based standard errors, fit with generalized estimating equations clustered at the hospital level and subclustered at the individual level. RESULTS: Individuals with CHDs were more likely to seek care at pediatric/adult or adult-only cardiac surgery centers if they had severe CHDs, private health insurance, higher severity of illness at encounter, a surgical procedure, cardiac encounter, and shorter drive time. These findings can be used to increase care receipt (especially for noncardiac care) at pediatric/adult or adult-only cardiac surgery centers, identify areas with limited access, and reduce disparities in access to specialized care among this high-risk population.