Host population structure and rare dispersal events drive leptospirosis transmission patterns among Rattus norvegicus in Boston, Massachusetts, US.

Leptospirosis (caused by pathogenic bacteria in the genus Leptospira ) is prevalent worldwide but more common in tropical and subtropical regions. Transmission can occur following direct exposure to infected urine from reservoir hosts, such as rats, or a urine-contaminated environment, which then can serve as an infection source for additional rats and other mammals, including humans. The brown rat, Rattus norvegicus , is an important reservoir of leptospirosis in urban settings. We investigated leptospirosis among brown rats in Boston, Massachusetts and hypothesized that rat dispersal in this urban setting influences the movement, persistence, and diversity of Leptospira . We analyzed DNA from 328 rat kidney samples collected from 17 sites in Boston over a seven-year period (2016-2022); 59 rats representing 12 of 17 sites were positive for Leptospira . We used 21 neutral microsatellite loci to genotype 311 rats and utilized the resulting data to investigate genetic connectivity among sampling sites. We generated whole genome sequences for 28 Leptospira isolates obtained from frozen and fresh tissue from some of the 59 Leptospira -positive rat kidneys. When isolates were not obtained, we attempted Leptospira genomic DNA capture and enrichment, which yielded 14 additional Leptospira genomes from rats. We also generated an enriched Leptospira genome from a 2018 human case in Boston. We found evidence of high genetic structure and limited dispersal among rat populations that is likely influenced by major roads and/or other unknown dispersal barriers, resulting in distinct rat population groups within the city; at certain sites these groups persisted for multiple years. We identified multiple distinct phylogenetic clades of L. interrogans among rats, with specific clades tightly linked to distinct rat populations. This pattern suggests L. interrogans persists in local rat populations and movement of leptospirosis in this urban rat community is driven by rat dispersal. Finally, our genomic analyses of the 2018 human leptospirosis case in Boston suggests a link to rats as the source. These findings will be useful for guiding rat control and human leptospirosis mitigation efforts in this and other urban settings.

Association between Combined Sewer Overflow Events and Gastrointestinal Illness in Massachusetts Municipalities with and without River-Sourced Drinking Water, 2014-2019.

BACKGROUND: Combined sewer overflow (CSO) events release untreated wastewater into surface waterbodies during heavy precipitation and snowmelt. Combined sewer systems serve ∼40 million people in the United States, primarily in urban and suburban municipalities in the Midwest and Northeast. Predicted increases in heavy precipitation events driven by climate change underscore the importance of quantifying potential health risks associated with CSO events. OBJECTIVES: The aims of this study were to a) estimate the association between CSO events (2014-2019) and emergency department (ED) visits for acute gastrointestinal illness (AGI) among Massachusetts municipalities that border a CSO-impacted river, and b) determine whether associations differ by municipal drinking water source. METHODS: A case time-series design was used to estimate the association between daily cumulative upstream CSO discharge and ED visits for AGI over lag periods of 4, 7, and 14 days, adjusting for temporal trends, temperature, and precipitation. Associations between CSO events and AGI were also compared by municipal drinking water source (CSO-impacted river vs. other sources). RESULTS: Extreme upstream CSO discharge events (>95th percentile by cumulative volume) were associated with a cumulative risk ratio (CRR) of AGI of 1.22 [95% confidence interval (CI): 1.05, 1.42] over the next 4 days for all municipalities, and the association was robust after adjusting for precipitation [1.17 (95% CI: 0.98, 1.39)], although the CI includes the null. In municipalities with CSO-impacted drinking water sources, the adjusted association was somewhat less pronounced following 95th percentile CSO events [CRR= 1.05 (95% CI: 0.82, 1.33)]. The adjusted CRR of AGI was 1.62 in all municipalities following 99th percentile CSO events (95% CI: 1.04, 2.51) and not statistically different when stratified by drinking water source. DISCUSSION: In municipalities bordering a CSO-impacted river in Massachusetts, extreme CSO events are associated with higher risk of AGI within 4 days. The largest CSO events are associated with increased risk of AGI regardless of drinking water source. https://doi.org/10.1289/EHP14213.

Evaluating COVID-19 Risk to Essential Workers by Occupational Group: A Case Study in Massachusetts.

Occupational exposure to SARS-CoV-2 varies by profession, but "essential workers" are often considered in aggregate in COVID-19 models. This aggregation complicates efforts to understand risks to specific types of workers or industries and target interventions, specifically towards non-healthcare workers. We used census tract-resolution American Community Survey data to develop novel essential worker categories among the occupations designated as COVID-19 Essential Services in Massachusetts. Census tract-resolution COVID-19 cases and deaths were provided by the Massachusetts Department of Public Health. We evaluated the association between essential worker categories and cases and deaths over two phases of the pandemic from March 2020 to February 2021 using adjusted mixed-effects negative binomial regression, controlling for other sociodemographic risk factors. We observed elevated COVID-19 case incidence in census tracts in the highest tertile of workers in construction/transportation/buildings maintenance (Phase 1: IRR 1.32 [95% CI 1.22, 1.42]; Phase 2: IRR: 1.19 [1.13, 1.25]), production (Phase 1: IRR: 1.23 [1.15, 1.33]; Phase 2: 1.18 [1.12, 1.24]), and public-facing sales and services occupations (Phase 1: IRR: 1.14 [1.07, 1.21]; Phase 2: IRR: 1.10 [1.06, 1.15]). We found reduced case incidence associated with greater percentage of essential workers able to work from home (Phase 1: IRR: 0.85 [0.78, 0.94]; Phase 2: IRR: 0.83 [0.77, 0.88]). Similar trends exist in the associations between essential worker categories and deaths, though attenuated. Estimating industry-specific risk for essential workers is important in targeting interventions for COVID-19 and other diseases and our categories provide a reproducible and straightforward way to support such efforts.

Heat stress and heat strain among outdoor workers in El Salvador and Nicaragua.

BACKGROUND: There is growing attention on occupational heat stress in Central America, as workers in this region are affected by a unique form of chronic kidney disease. Previous studies have examined wet bulb globe temperatures and estimated metabolic rates to assess heat stress, but there are limited data characterizing heat strain among these workers. OBJECTIVE: The aims were to characterize heat stress and heat strain and examine whether job task, break duration, hydration practices, and kidney function were associated with heat strain. METHODS: We used data from the MesoAmerican Nephropathy Occupational Study, a cohort of 569 outdoor workers in El Salvador and Nicaragua who underwent workplace exposure monitoring, including continuous measurement of core body temperature (Tc), heart rate (HR), physical activity, and wet bulb globe temperature (WBGT), over the course of three days in January 2018 - May 2018. Participants represented five industries: sugarcane, corn, plantain, brickmaking, and construction. RESULTS: Median WBGTs were relatively high (>27 °C) at most sites, particularly when work shifts spanned the afternoon hours (e.g., 29.2 °C among plantain workers). Sugarcane workers, especially cane cutters in both countries and Nicaraguan agrichemical applicators, had the highest estimated metabolic rates (medians: 299-318 kcal/hr). Most workers spent little time on break (<10% of the shift), as determined by physical activity data. Overall, sugarcane workers-particularly those in Nicaragua-experienced the highest Tc and HR values. However, a few workers in other industries reached high Tc (>39 °C) as well. Impaired kidney function (estimated glomerular filtration rate <90 mL/min/1.73 m2) was associated with higher Tc and HR values, even after adjustment. SIGNIFICANCE: This is the largest study to-date examining heat stress and strain among outdoor workers in Central America. Workers at sugar companies regularly experienced Tc > 38°C (76.9% of monitored person-days at Nicaraguan companies; 46.5% at Salvadoran companies). Workers with impaired kidney function had higher measures of Tc and HR. IMPACT STATEMENT: This study examined levels of occupational heat stress and heat strain experienced among outdoor workers in five industries in El Salvador and Nicaragua. We characterized heat stress using wet bulb globe temperatures and estimated metabolic rate and heat strain using core body temperature and heart rate. Sugarcane workers, particularly cane cutters and Nicaraguan agrichemical applicators, performed more strenuous work and experienced greater levels of heat strain. Impaired kidney function was associated with higher heart rates and core body temperatures.

Metabolic Features of Increased Gut Permeability, Inflammation, and Altered Energy Metabolism Distinguish Agricultural Workers at Risk for Mesoamerican Nephropathy.

Mesoamerican nephropathy (MeN) is a form of chronic kidney disease found predominantly in young men in Mesoamerica. Strenuous agricultural labor is a consistent risk factor for MeN, but the pathophysiologic mechanism leading to disease is poorly understood. We compared the urine metabolome among men in Nicaragua engaged in sugarcane harvest and seed cutting (n = 117), a group at high risk for MeN, against three referents: Nicaraguans working less strenuous jobs at the same sugarcane plantations (n = 78); Nicaraguans performing non-agricultural work (n = 102); and agricultural workers in Spain (n = 78). Using proton nuclear magnetic resonance, we identified 136 metabolites among participants. Our non-hypothesis-based approach identified distinguishing urine metabolic features in the high-risk group, revealing increased levels of hippurate and other gut-derived metabolites and decreased metabolites related to central energy metabolism when compared to referent groups. Our complementary hypothesis-based approach, focused on nicotinamide adenine dinucleotide (NAD+) related metabolites, and revealed a higher kynurenate/tryptophan ratio in the high-risk group (p = 0.001), consistent with a heightened inflammatory state. Workers in high-risk occupations are distinguishable by urinary metabolic features that suggest increased gut permeability, inflammation, and altered energy metabolism. Further study is needed to explore the pathophysiologic implications of these findings.

Influence of geospatial resolution on sociodemographic predictors of COVID-19 in Massachusetts.

PURPOSE: When studying health risks across a large geographic region such as a state or province, researchers often assume that finer-resolution data on health outcomes and risk factors will improve inferences by avoiding ecological bias and other issues associated with geographic aggregation. However, coarser-resolution data (e.g., at the town or county-level) are more commonly publicly available and packaged for easier access, allowing for rapid analyses. The advantages and limitations of using finer-resolution data, which may improve precision at the cost of time spent gaining access and processing data, have not been considered in detail to date. METHODS: We systematically examine the implications of conducting town-level mixed-effect regression analyses versus census-tract-level analyses to study sociodemographic predictors of COVID-19 in Massachusetts. In a series of negative binomial regressions, we vary the spatial resolution of the outcome, the resolution of variable selection, and the resolution of the random effect to allow for more direct comparison across models. RESULTS: We find stability in some estimates across scenarios, changes in magnitude, direction, and significance in others, and tighter confidence intervals on the census-tract level. Conclusions regarding sociodemographic predictors are robust when regions of high concentration remain consistent across town and census-tract resolutions. CONCLUSIONS: Inferences about high-risk populations may be misleading if derived from town- or county-resolution data, especially for covariates that capture small subgroups (e.g., small racial minority populations) or are geographically concentrated or skewed (e.g., % college students). Our analysis can help inform more rapid and efficient use of public health data by identifying when finer-resolution data are truly most informative, or when coarser-resolution data may be misleading.

Long-term aircraft noise exposure and risk of hypertension in postmenopausal women.

BACKGROUND: Studies of the association between aircraft noise and hypertension are complicated by inadequate control for potential confounders and a lack of longitudinal assessments, and existing evidence is inconclusive. OBJECTIVES: We evaluated the association between long-term aircraft noise exposure and risk of hypertension among post-menopausal women in the Women's Health Initiative Clinical Trials, an ongoing prospective U.S. METHODS: Day-night average (DNL) and night equivalent sound levels (Lnight) were modeled for 90 U.S. airports from 1995 to 2010 in 5-year intervals using the Aviation Environmental Design Tool and linked to participant geocoded addresses from 1993 to 2010. Participants with modeled exposures ≥45 A-weighted decibels (dB [A]) were considered exposed, and those outside of 45 dB(A) who also did not live in close proximity to unmodeled airports were considered unexposed. Hypertension was defined as systolic/diastolic blood pressure ≥140/90 mmHg or inventoried/self-reported antihypertensive medication use. Using time-varying Cox proportional hazards models, we estimated hazard ratios (HRs) for incident hypertension when exposed to DNL or Lnight ≥45 versus <45 dB(A), controlling for sociodemographic, behavioral, and environmental/contextual factors. RESULTS/DISCUSSION: There were 18,783 participants with non-missing DNL exposure and 14,443 with non-missing Lnight exposure at risk of hypertension. In adjusted models, DNL and Lnight ≥45 db(A) were associated with HRs of 1.00 (95% confidence interval [CI]: 0.93, 1.08) and 1.06 (95%CI: 0.91, 1.24), respectively. There was no evidence supporting a positive exposure-response relationship, and findings were robust in sensitivity analyses. Indications of elevated risk were seen among certain subgroups, such as those living in areas with lower population density (HRinteraction: 0.84; 95%CI: 0.72, 0.98) or nitrogen dioxide concentrations (HRinteraction: 0.82; 95%CI: 0.71, 0.95), which may indicate lower ambient/road traffic noise. Our findings do not suggest a relationship between aircraft noise and incident hypertension among older women in the U.S., though associations in lower ambient noise settings merit further investigation.

Genetic characterization of Staphylococcus aureus isolated from Norway rats in Boston, Massachusetts.

BACKGROUND: Despite the importance of domesticated animals in the generation and transmission of antibiotic-resistant Staphylococcus aureus, the role of wild animals, specifically rodents, in the ecology of S. aureus remains unclear. We recovered and genotyped S. aureus isolates from wild Norway rats (Rattus norvegicus) in Boston, Massachusetts to examine genetic relationships between common human and animal S. aureus isolates in a large US metropolitan area. METHODS: We collected and necropsied 63 rats from June 2016 to June 2017. Nasal, foot pad, fur, and fecal swabs were collected. Staphylococcus aureus was isolated using culture-based methods and polymerase chain reaction confirmation. S. aureus isolates were spa typed, tested for antibiotic susceptibility, and whole genome sequenced. Assembled sequences were uploaded to the Comprehensive Antibiotic Resistance Database to identify antibiotic resistance elements. A phylogenetic tree was constructed using the neighbor-joining method with the maximum composite likelihood distance in MEGA7. RESULTS: We recovered 164 Gram-positive bacterial isolates from Norway rats. Nineteen isolates from eight individual rats were confirmed as S. aureus (prevalence: 12.9% (8/63)). All S. aureus isolates were methicillin-susceptible S. aureus (MSSA), pvl-negative, and resistant to penicillin. Two isolates displayed resistance to erythromycin. Four different S. aureus spa types were detected (t933, t10751, t18202, and t189). Thirteen unique antibiotic resistance elements were identified, and all isolates shared genes mepR, mgrA, arlR, and S. aureus norA. Phylogenetic analysis if the 19 S. aureus isolates revealed they were genetically similar to four clades of S. aureus with similar resistance gene profiles isolated from both human- and animal-derived S. aureus, as well as formed a distinct phylogenetic cluster composed only of rat isolates. CONCLUSIONS: Wild rodents may serve as a reservoir or vector of antibiotic resistance genes in the urban environment with relevance for human and animal health.

Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts.

Infectious disease surveillance frequently lacks complete information on race and ethnicity, making it difficult to identify health inequities. Greater awareness of this issue has occurred due to the COVID-19 pandemic, during which inequities in cases, hospitalizations, and deaths were reported but with evidence of substantial missing demographic details. Although the problem of missing race and ethnicity data in COVID-19 cases has been well documented, neither its spatiotemporal variation nor its particular drivers have been characterized. Using individual-level data on confirmed COVID-19 cases in Massachusetts from March 2020 to February 2021, we show how missing race and ethnicity data: (1) varied over time, appearing to increase sharply during two different periods of rapid case growth; (2) differed substantially between towns, indicating a nonrandom distribution; and (3) was associated significantly with several individual- and town-level characteristics in a mixed-effects regression model, suggesting a combination of personal and infrastructural drivers of missing data that persisted despite state and federal data-collection mandates. We discuss how a variety of factors may contribute to persistent missing data but could potentially be mitigated in future contexts.

Influenza D virus exposure among US cattle workers: A call for surveillance.

Although cattle are a reservoir for influenza D virus (IDV), little is known about human exposure to IDV. We assessed IDV exposure and associated health effects among United States dairy workers, a population at heightened risk of cattle zoonoses. In prospective, cross-shift sampling of 31 workers employed at five large-herd dairy operations in two states, we found evidence of IDV in the nasal washes of 67% of participants at least once during the 5-day study period. IDV exposure was not associated with respiratory symptoms in these workers. These findings suggest that IDV is present in dairy cattle environments and can result in worker exposure.

COVID-19 and CKD: Employment, Food Security and Healthcare in El Salvador.

Background: In Central America, the COVID-19 pandemic coexists with a devastating epidemic of chronic kidney disease of unknown origin. The consequences of these overlapping health crises remain largely unknown. Methods: We assessed vulnerability to and impact of the first wave of COVID-19 on participants in a cohort study of chronic kidney disease (CKD) in El Salvador (n = 229). Participants were contacted by phone during August and September 2020. We queried changes to employment, healthcare access, household income and food security due to the pandemic (from March 2020 until the time of the interview) and COVID-19-associated symptoms during that time. Findings: We reached 94% of the cohort (n = 215). Nearly 40% of participants reported an unexpected change in employment or work activities and 8.8% reported new unemployment due to the pandemic. Participants with CKD (n = 27) had higher odds of reporting new income insecurity, food insecurity, and reductions in medical care access due to the pandemic. COVID-19-associated symptoms (an approximation of disease) were reported in 7.0% (n = 15). Participants with CKD were more likely to report COVID-19-associated symptoms compared to those without CKD, although these differences were not statistically significant. Conclusions: Overall, participants with CKD suffered greater economic consequences as a result of the pandemic and may have experienced higher incidence of COVID-19 disease, although laboratory diagnostics would be required to draw this conclusion. Longitudinal analyses are required to comprehensively evaluate the implications of the pandemic for individuals with CKD in Central America.

High prevalence of chronic kidney disease of unknown etiology among workers in the Mesoamerican Nephropathy Occupational Study.

BACKGROUND: Mortality from chronic kidney disease of unknown etiology (CKDu) is extremely high along the Pacific coast of Central America, particularly among sugarcane workers. The Mesoamerican Nephropathy Occupational Study (MANOS) is a prospective cohort study of CKDu among agricultural and non-agricultural workers in El Salvador and Nicaragua. The objective of this manuscript is to describe the MANOS cohort recruitment, baseline data collection, and CKDu prevalence after two rounds. METHODS: Workers with no known diabetes, hypertension, or CKD were recruited from sugarcane, corn, plantain, brickmaking, and road construction industries (n = 569). Investigators administered questionnaires, collected biological samples, and observed workers for three consecutive workdays at the worksite. Serum specimens were analyzed for kidney function parameters, and used to calculate estimated glomerular filtration rate (eGFR). At six months, serum was collected again prior to the work shift. CKD at baseline is defined as eGFR ≤ 60 ml/min/1.73m2 at both timepoints. Age-standardized prevalence was calculated by industry, country, and demographic measures. Kidney function parameters were compared by CKD status. RESULTS: Prevalence of CKD at baseline was 7.4% (n = 42). Age-standardized prevalence was highest in Salvadoran sugarcane (14.1%), followed by Salvadoran corn (11.6%), and Nicaraguan brickmaking (8.1%). Nicaraguan sugarcane had the lowest prevalence, likely due to kidney function screenings prior to employment. CONCLUSION: Despite efforts to enroll participants without CKD, our identification of prevalent CKD among agricultural and non-agricultural workers in the MANOS cohort indicates notable kidney disease in the region, particularly among sugarcane workers.

Community predictors of COVID-19 cases and deaths in Massachusetts: Evaluating changes over time using geospatially refined data.

BACKGROUND: The COVID-19 pandemic has highlighted the need for targeted local interventions given substantial heterogeneity within cities and counties. Publicly available case data are typically aggregated to the city or county level to protect patient privacy, but more granular data are necessary to identify and act upon community-level risk factors that can change over time. METHODS: Individual COVID-19 case and mortality data from Massachusetts were geocoded to residential addresses and aggregated into two time periods: "Phase 1" (March-June 2020) and "Phase 2" (September 2020 to February 2021). Institutional cases associated with long-term care facilities, prisons, or homeless shelters were identified using address data and modeled separately. Census tract sociodemographic and occupational predictors were drawn from the 2015-2019 American Community Survey. We used mixed-effects negative binomial regression to estimate incidence rate ratios (IRRs), accounting for town-level spatial autocorrelation. RESULTS: Case incidence was elevated in census tracts with higher proportions of Black and Latinx residents, with larger associations in Phase 1 than Phase 2. Case incidence associated with proportion of essential workers was similarly elevated in both Phases. Mortality IRRs had differing patterns from case IRRs, decreasing less substantially between Phases for Black and Latinx populations and increasing between Phases for proportion of essential workers. Mortality models excluding institutional cases yielded stronger associations for age, race/ethnicity, and essential worker status. CONCLUSIONS: Geocoded home address data can allow for nuanced analyses of community disease patterns, identification of high-risk subgroups, and exclusion of institutional cases to comprehensively reflect community risk.

Time-varying associations between COVID-19 case incidence and community-level sociodemographic, occupational, environmental, and mobility risk factors in Massachusetts.

BACKGROUND: Associations between community-level risk factors and COVID-19 incidence have been used to identify vulnerable subpopulations and target interventions, but the variability of these associations over time remains largely unknown. We evaluated variability in the associations between community-level predictors and COVID-19 case incidence in 351 cities and towns in Massachusetts from March to October 2020. METHODS: Using publicly available sociodemographic, occupational, environmental, and mobility datasets, we developed mixed-effect, adjusted Poisson regression models to depict associations between these variables and town-level COVID-19 case incidence data across five distinct time periods from March to October 2020. We examined town-level demographic variables, including population proportions by race, ethnicity, and age, as well as factors related to occupation, housing density, economic vulnerability, air pollution (PM2.5), and institutional facilities. We calculated incidence rate ratios (IRR) associated with these predictors and compared these values across the multiple time periods to assess variability in the observed associations over time. RESULTS: Associations between key predictor variables and town-level incidence varied across the five time periods. We observed reductions over time in the association with percentage of Black residents (IRR = 1.12 [95%CI: 1.12-1.13]) in early spring, IRR = 1.01 [95%CI: 1.00-1.01] in early fall) and COVID-19 incidence. The association with number of long-term care facility beds per capita also decreased over time (IRR = 1.28 [95%CI: 1.26-1.31] in spring, IRR = 1.07 [95%CI: 1.05-1.09] in fall). Controlling for other factors, towns with higher percentages of essential workers experienced elevated incidences of COVID-19 throughout the pandemic (e.g., IRR = 1.30 [95%CI: 1.27-1.33] in spring, IRR = 1.20 [95%CI: 1.17-1.22] in fall). Towns with higher proportions of Latinx residents also had sustained elevated incidence over time (IRR = 1.19 [95%CI: 1.18-1.21] in spring, IRR = 1.14 [95%CI: 1.13-1.15] in fall). CONCLUSIONS: Town-level COVID-19 risk factors varied with time in this study. In Massachusetts, racial (but not ethnic) disparities in COVID-19 incidence may have decreased across the first 8 months of the pandemic, perhaps indicating greater success in risk mitigation in selected communities. Our approach can be used to evaluate effectiveness of public health interventions and target specific mitigation efforts on the community level.

Time-varying associations between COVID-19 case incidence and community-level sociodemographic, occupational, environmental, and mobility risk factors in Massachusetts.

BACKGROUND: Associations between community-level risk factors and COVID-19 incidence are used to identify vulnerable subpopulations and target interventions, but the variability of these associations over time remains largely unknown. We evaluated variability in the associations between community-level predictors and COVID-19 case incidence in 351 cities and towns in Massachusetts from March to October 2020. METHODS: Using publicly available sociodemographic, occupational, environmental, and mobility datasets, we developed mixed-effect, adjusted Poisson regression models to depict associations between these variables and town-level COVID-19 case incidence data across five distinct time periods. We examined town-level demographic variables, including z-scores of percent Black, Latinx, over 80 years and undergraduate students, as well as factors related to occupation, housing density, economic vulnerability, air pollution (PM 2.5 ), and institutional facilities. RESULTS: Associations between key predictor variables and town-level incidence varied across the five time periods. We observed reductions over time in the association with percentage Black residents (IRR=1.12 CI=(1.12-1.13) in spring, IRR=1.01 CI=(1.00-1.01) in fall). The association with number of long-term care facility beds per capita also decreased over time (IRR=1.28 CI=(1.26-1.31) in spring, IRR=1.07 CI=(1.05-1.09)in fall). Controlling for other factors, towns with higher percentages of essential workers experienced elevated incidence of COVID-19 throughout the pandemic (e.g., IRR=1.30 CI=(1.27-1.33) in spring, IRR=1.20, CI=(1.17-1.22) in fall). Towns with higher percentages of Latinx residents also had sustained elevated incidence over time (e.g., IRR=1.19 CI=(1.18-1.21) in spring, IRR=1.14 CI=(1.13-1.15) in fall). CONCLUSIONS: Town-level COVID-19 risk factors vary with time. In Massachusetts, racial (but not ethnic) disparities in COVID-19 incidence have decreased over time, perhaps indicating greater success in risk mitigation in selected communities. Our approach can be used to evaluate effectiveness of public health interventions and target specific mitigation efforts on the community level.

Biomarkers of kidney injury among children in a high-risk region for chronic kidney disease of uncertain etiology.

BACKGROUND: Mesoamerican Nephropathy (MeN), a form of chronic kidney disease of uncertain etiology, is a leading cause of death in Central America. The disease often presents in young adult male agricultural workers and progresses rapidly. Given the young age at presentation, we hypothesized that children in Central America experience subclinical kidney injury prior to working life. METHODS: We assessed specimens from a cross-sectional study of youth, aged 7-17 years, predominantly residing in a high-risk region of Nicaragua (n = 210). We evaluated urinary concentrations and risk factors for kidney injury biomarkers neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), interleukin-18 (IL-18), monocyte chemoattractant protein 1 (MCP-1), and chitinase-3-like protein 1 (YKL-40). We evaluated the association between biomarkers and contemporaneous eGFR and compared biomarker concentrations with reference values from healthy children in other countries. RESULTS: Median uNGAL, uIL-18, and uKIM-1 concentrations exceeded healthy reference values. A one-year increase in age was associated with 40% increase in odds of being in the highest quartile of uNGAL (OR 1.4; (95%CI 1.2, 1.5); p < 0.0001). Youth who reported ever experiencing dysuria had 2.5 times the odds of having uNGAL concentrations in the top quartile (OR 2.5; (95%CI 1.4, 4.6); p = 0.003). Girls had significantly higher concentrations of all biomarkers than boys. Nine percent of children demonstrated low eGFR (≤ 100 ml/min/1.73 m2), while 29% showed evidence of hyperfiltration (eGFR ≥ 160 ml/min/1.73 m2), both potentially indicative of renal dysfunction. CONCLUSIONS: Children residing in regions of Nicaragua at high risk for MeN may experience subclinical kidney injury prior to occupational exposures.

Developing and evaluating a pediatric asthma severity computable phenotype derived from electronic health records.

BACKGROUND: Extensive data available in electronic health records (EHRs) have the potential to improve asthma care and understanding of factors influencing asthma outcomes. However, this work can be accomplished only when the EHR data allow for accurate measures of severity, which at present are complex and inconsistent. OBJECTIVE: Our aims were to create and evaluate a standardized pediatric asthma severity phenotype based in clinical asthma guidelines for use in EHR-based health initiatives and studies and also to examine the presence and absence of these data in relation to patient characteristics. METHODS: We developed an asthma severity computable phenotype and compared the concordance of different severity components contributing to the phenotype to trends in the literature. We used multivariable logistic regression to assess the presence of EHR data relevant to asthma severity. RESULTS: The asthma severity computable phenotype performs as expected in comparison with national statistics and the literature. Severity classification for a child is maximized when based on the long-term medication regimen component and minimized when based only on the symptom data component. Use of the severity phenotype results in better, clinically grounded classification. Children for whom severity could be ascertained from these EHR data were more likely to be seen for asthma in the outpatient setting and less likely to be older or Hispanic. Black children were less likely to have lung function testing data present. CONCLUSION: We developed a pragmatic computable phenotype for pediatric asthma severity that is transportable to other EHRs.

Comment on Sarathkumara et al.: Exposure to Hantavirus is a Risk Factor Associated with Kidney Diseases in Sri Lanka: A Cross Sectional Study.

In a recent paper, Sarathkumara et al [...].

Recent Research on Occupational Animal Exposures and Health Risks: A Narrative Review.

PURPOSE OF REVIEW: In the last year, an increasing number of studies have reported on methicillin-resistant Staphylococcus aureus (MRSA) transmission in Africa and Asia and in migrant workers. We reviewed original research on occupational health and safety of animal workers published from January 1, 2018, through June 30, 2019, with a targeted focus on infectious disease studies published in these populations. RECENT FINDINGS: Studies focused on occupational exposures to infectious agents, dust and allergens, pesticides, and occupational injury. Research on zoonotic MRSA used whole genome-sequencing technologies to evaluate transmission in Africa and Asia. Swine worker exposure to porcine coronavirus and emerging influenza A viruses was documented in China. 16s RNA amplicon sequencing identified distinct microbiota compositions in households with active animal farmers. Multiple bioaerosol exposures were assessed for industrial dairy workers. Occupational injury studies highlighted the struggles of Latino animal workers in the USA. These studies highlighted the global expansion of zoonotic antibiotic resistance and identified novel occupational zoonoses of concern. The integration of microbiome assessment and compound mixtures into the evaluation of dust and endotoxin exposures for animal workers marks a new direction for this work.