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–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.

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The campylobacteriosis conundrum – examining the incidence of infection with Campylobacter sp. in Australia, 1998–2013

Epidemiology and Infection ◽

10.1017/s0950268816002909 ◽

2016 ◽

Vol 145 (4) ◽

pp. 839-847 ◽

Cited By ~ 11

Author(s):

C. R. M. MOFFATT ◽

K. GLASS ◽

R. STAFFORD ◽

C. D'ESTE ◽

M. D. KIRK

Keyword(s):

Incidence Rate ◽

Negative Binomial ◽

Age Groups ◽

Negative Binomial Regression ◽

Incidence Rates ◽

Age Group ◽

Disease Notification ◽

Significant Public Health ◽

Rate Ratios ◽

Over Time

SUMMARYCampylobacter sp. are a globally significant cause of gastroenteritis. Although rates of infection in Australia are among the highest in the industrialized world, studies describing campylobacteriosis incidence in Australia are lacking. Using national disease notification data between 1998 and 2013 we examined Campylobacter infections by gender, age group, season and state and territory. Negative binomial regression was used to estimate incidence rate ratios (IRRs), including trends by age group over time, with post-estimation commands used to obtain adjusted incidence rates. The incidence rate for males was significantly higher than for females [IRR 1·20, 95% confidence interval (CI) 1·18–1·21], while a distinct seasonality was demonstrated with higher rates in both spring (IRR 1·18, 95% CI 1·16–1·20) and summer (IRR 1·17, 95% CI 1·16–1·19). Examination of trends in age-specific incidence over time showed declines in incidence in those aged <40 years combined with contemporaneous increases in older age groups, notably those aged 70–79 years (IRR 1998–2013: 1·75, 95% CI 1·63–1·88). While crude rates continue to be highest in children, our findings suggest the age structure for campylobacteriosis in Australia is changing, carrying significant public health implications for older Australians.

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Increased Use of Computed Tomography Does Not Harm Patients with Acute Appendicitis

The American Surgeon ◽

10.1177/000313480607200410 ◽

2006 ◽

Vol 72 (4) ◽

pp. 326-329 ◽

Cited By ~ 2

Author(s):

Tehillah S. Menes ◽

Arthur H. Aufses ◽

Mary Rojas ◽

Nina A. Bickell

Keyword(s):

Computed Tomography ◽

Acute Appendicitis ◽

Median Time ◽

Phase 1 ◽

False Negative ◽

Phase 2 ◽

Time To Surgery ◽

Group Time ◽

Use Efficiency ◽

Over Time

The increased use of computed tomography (CT) in patients with appendicitis may cause a delay in surgery and, therefore, higher perforation rates. We examined the use of CT, delay in time to surgery, and perforation rates in appendicitis patients operated on in two periods: Phase 1, 1996 through 1998 and Phase 2, 2001 through 2002. CT was performed in 18 per cent of the Phase 1 group compared with 62 per cent in the Phase 2 group. In the Phase 1 group, patients undergoing CT had a delay to surgery compared with those without CT (18.6 hours vs 7 hours; P < 0.0001). In the Phase 2 group, time to surgery was reduced (median time = 12 hours with CT vs 6 hours without CT; P < 0.001). CT was more accurate in the later group; there were less false-negative and equivocal studies. There was no difference in perforation rates between the Phase 1 and 2 groups. Over time, the increased use, efficiency, and accuracy of CT in patients with acute appendicitis were associated with reduced delays to surgery. The use of CT did not harm patients, but did not translate to better overall outcomes in this group of patients.

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Student-inflicted injuries to staff in schools: comparing risk between educators and non-educators

Injury Prevention ◽

10.1136/injuryprev-2017-042472 ◽

2017 ◽

Vol 25 (2) ◽

pp. 116-122 ◽

Cited By ~ 1

Author(s):

Katherine E Schofield ◽

Andrew D Ryan ◽

Craig Stroinski

Keyword(s):

Risk Factors ◽

General Education ◽

Injury Risk ◽

Negative Binomial ◽

Negative Binomial Regression ◽

Acting Out ◽

Increased Risk ◽

Educational Assistants ◽

Reduction Methods ◽

Rate Ratios

ObjectiveStudent-inflicted injury to staff in the educational services sector is a growing concern. Studies on violence have focused on teachers as victims, but less is known about injuries to other employee groups, particularly educational assistants. Inequities may be present, as educational assistants and non-educators may not have the same wage, benefits, training and employment protections available to them as professional educators. We identified risk factors for student-related injury and their characteristics among employees in school districts.MethodsWorkers’ compensation data were used to identify incidence and severity of student-related injury. Rates were calculated using negative binomial regression; risk factors were identified using multivariate models to calculate rate ratios (RR) and 95% CIs.ResultsOver 26% of all injuries were student-related; 8% resulted in lost work time. Special and general education assistants experienced significantly increased risk of injury (RR=6.0, CI 5.05 to 7.15; RR=2.07, CI 1.40 to 3.07) as compared with educators. Risk differed by age, gender and school district type. Text analyses categorised student-related injury. It revealed injury from students acting out occurred most frequently (45.4%), whereas injuries involving play with students resulted in the highest percentage of lost-time injuries (17.7%) compared with all interaction categories.ConclusionStudent-inflicted injury to staff occurs frequently and can be severe. Special education and general assistants bear the largest burden of injury compared with educators. A variety of prevention techniques to reduce injury risk and severity, including policy or environmental modifications, may be appropriate. Equal access to risk reduction methods for all staff should be prioritised.

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Prevalence of SARS-CoV-2 infection among people experiencing homelessness in Toronto during the first wave of the COVID-19 pandemic

10.1101/2021.09.21.21263713 ◽

2021 ◽

Author(s):

Linh Luong ◽

Michaela Beder ◽

Rosane Nisenbaum ◽

Aaron Orkin ◽

Jonathan Wong ◽

...

Keyword(s):

Negative Binomial ◽

Negative Binomial Regression ◽

Infection Rates ◽

Individual Site ◽

Site Characteristics ◽

Increased Risk ◽

Binomial Regression ◽

Great Heterogeneity ◽

The Relationship ◽

Over Time

Background: People experiencing homelessness are at increased risk of SARS-CoV-2 infection. This study reports the point prevalence of SARS-CoV-2 infection during testing conducted at sites serving people experiencing homelessness in Toronto during the first wave of the COVID-19 pandemic. We also explored the association between site characteristics and prevalence rates. Methods: The study included individuals who were staying at shelters, encampments, COVID-19 physical distancing sites, and drop-in and respite sites and completed outreach-based testing for SARS-CoV-2 during the period April 17 to July 31, 2020. We examined test positivity rates over time and compared them to rates in the general population of Toronto. Negative binomial regression was used to examine the relationship between each shelter-level characteristic and SARS-CoV-2 positivity rates. We also compared the rates across 3 time periods (T1: April 17-April 25; T2: April 26-May 23; T3: May 24-June 25). Results: The overall prevalence of SARS-CoV-2 infection was 8.5% (394/4657). Site-specific rates showed great heterogeneity with infection rates ranging from 0% to 70.6%. Compared to T1, positivity rates were 0.21 times lower (95% CI: 0.06, 0.75) during T2 and 0.14 times lower (95% CI: 0.043, 0.44) during T3. Most cases were detected during outbreak testing (384/394 [97.5%]) rather than active case finding. Interpretation: During the first wave of the pandemic, rates of SARS-CoV-2 infection at sites for people experiencing homelessness in Toronto varied significantly over time. The observation of lower rates at certain sites may be attributable to overall time trends, expansion of outreach-based testing to include sites without known outbreaks and/or individual site characteristics.

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Assessing Differential Impacts of COVID-19 on Black Communities

10.1101/2020.05.04.20090274 ◽

2020 ◽

Cited By ~ 3

Author(s):

Gregorio A. Millett ◽

Austin T. Jones ◽

David Benkeser ◽

Stefan Baral ◽

Laina Mercer ◽

...

Keyword(s):

Black People ◽

Negative Binomial ◽

Negative Binomial Regression ◽

Black Communities ◽

Negative Binomial Regression Model ◽

County Level ◽

Structural Racism ◽

Black Residents ◽

Us Counties ◽

Rate Ratios

AbstractPurposeGiven incomplete data reporting by race, we used data on COVID-19 cases and deaths in US counties to describe racial disparities in COVID-19 disease and death and associated determinants.MethodsUsing publicly available data (accessed April 13, 2020), predictors of COVID-19 cases and deaths were compared between disproportionately (≥13%) black and all other (<13% black) counties. Rate ratios were calculated and population attributable fractions (PAF) were estimated using COVID-19 cases and deaths via zero-inflated negative binomial regression model. National maps with county-level data and an interactive scatterplot of COVID-19 cases were generated.ResultsNearly ninety-seven percent of disproportionately black counties (656/677) reported a case and 49% (330/677) reported a death versus 81% (1987/2,465) and 28% (684/ 2465), respectively, for all other counties. Counties with higher proportions of black people have higher prevalence of comorbidities and greater air pollution. Counties with higher proportions of black residents had more COVID-19 diagnoses (RR 1.24, 95% CI 1.17-1.33) and deaths (RR 1.18, 95% CI 1.00-1.40), after adjusting for county-level characteristics such as age, poverty, comorbidities, and epidemic duration. COVID-19 deaths were higher in disproportionally black rural and small metro counties. The PAF of COVID-19 diagnosis due to lack of health insurance was 3.3% for counties with <13% black residents and 4.2% for counties with ≥13% black residents.ConclusionsNearly twenty-two percent of US counties are disproportionately black and they accounted for 52% of COVID-19 diagnoses and 58% of COVID-19 deaths nationally. County-level comparisons can both inform COVID-19 responses and identify epidemic hot spots. Social conditions, structural racism, and other factors elevate risk for COVID-19 diagnoses and deaths in black communities.

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Education-related inequalities in cause-specific mortality: First estimates for Australia using individual-level linked census and mortality data

10.1101/2020.09.21.20193516 ◽

2020 ◽

Author(s):

Jennifer Welsh ◽

Grace Joshy ◽

Lauren Morgan ◽

Kay Soga ◽

Hsei-Di Law ◽

...

Keyword(s):

High Education ◽

Causes Of Death ◽

Negative Binomial ◽

International Comparisons ◽

Negative Binomial Regression ◽

Medical Intervention ◽

Mortality Data ◽

Individual Level ◽

Specific Mortality ◽

Inequalities In Mortality

Background: Socioeconomic inequalities in mortality are evident in all high-income countries and ongoing monitoring is recommended using linked census-mortality data. Using such data, we provide first estimates of education-related inequalities in cause-specific mortality in Australia, suitable for international comparisons. Methods: Using Australian Census (2016) linked to 13-months of Death Registrations data (2016-17), we estimated relative rates (RR) and rate differences (RD, per100 000 person-years), comparing rates in low (no qualifications) and intermediate (secondary school) with high education (tertiary), for individual causes of death (among those 25-84y) and grouped according to preventability (25-74y), separately by sex and age group, adjusting for age, using negative binomial regression. Results: Among 13.9M people contributing 14 452 732 person-years, 84 743 deaths occurred. We observed inequalities in most causes of death for each age-sex group. Among men aged 25-44y, absolute and relative inequalities (low versus high education) were largest for injuries, e.g. transport accidents (RR=10.1 [95%CI: 5.4-18.7], RD=21.1 [15.9-26.3]). Among those aged 45-64y, inequalities were greatest for chronic diseases, e.g. lung cancer (men RR=6.6 [4.9-8.9], RD=55.6 [51.1-60.1]) and ischaemic heart disease (women RR=5.8 [3.7-9.1], RD=19.2 [17.0-21.5]), with similar patterns for people aged 65-84y. When grouped according to preventability, inequalities were large for causes amenable to behaviour change and medical intervention for all ages and causes amenable to injury prevention among young men. Conclusions: Australian education-related inequalities in mortality are substantial, generally higher than international estimates, and related to preventability. Findings highlight opportunities to reduce them and the potential to improve the health of the population.

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Measuring the effectiveness of COVID-19 containment policies in Italian regions: are we doing enough?

10.36253/978-88-5518-461-8.15 ◽

2021 ◽

pp. 75-80

Author(s):

Demetrio Panarello ◽

Giorgio Tassinari

Keyword(s):

Negative Binomial ◽

Negative Binomial Regression ◽

Current Phase ◽

Mobility Limitations ◽

Italian Regions ◽

Binomial Regression ◽

Stringency Level ◽

Restrictive Measures ◽

Second Wave ◽

Over Time

A successful fight against COVID-19 greatly depends on citizens’ adherence to the restrictive measures, which may not suffice alone. Making use of a containment index, data on sanctions, and Google’s movement trends across Italian regions, complemented by other sources, we investigate the extent to which compliance with the mobility limitations has affected the number of deaths over time in the period from the 24th of February 2020 to the 9th of November 2020, by using panel data for Italian regions, analysed through a negative binomial regression method. We also differentiated the study period, estimating two distinct models on two subsamples: until the 13th of September and since the 14th of September. In so doing, we show how the pandemic dynamics have changed between the first and the second wave of the emergency. Our results highlight that the importance of the restrictive measures and of citizens’ accord on their abidance has greatly increased since the end of the summer, also because the stringency level of the adopted measures has critically declined. Informing citizens about the effects and purposes of the restrictive measures is of paramount importance, especially in the current phase of the pandemic.

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Individual- and City-Level Socioeconomic Factors and Tooth Loss among Elderly People: A Cross-Level Multilevel Analysis

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17072345 ◽

2020 ◽

Vol 17 (7) ◽

pp. 2345 ◽

Cited By ~ 1

Author(s):

Mario Vianna Vettore ◽

Janete M. Rebelo Vieira ◽

José F. F. Gomes ◽

Nara M. O. Martins ◽

Yan N. L. Freitas ◽

...

Keyword(s):

Elderly People ◽

Tooth Loss ◽

Family Income ◽

Negative Binomial ◽

Negative Binomial Regression ◽

Federal District ◽

Level Data ◽

Education Gaps ◽

Individual Variables ◽

Rate Ratios

This study aimed to test the association of contextual and individual socioeconomic status with tooth loss among Brazilian elderly people aged 65–74 years. Data from 5435 elderly participants from the Brazilian National Oral Health Survey (2010) were linked to city-level data for 27 state capitals and the Federal District. Tooth loss was clinically assessed according to the number of missing natural teeth. Contextual social variables included Human Development Index income (HDI-income) and HDI-education. Individual socioeconomic measures were monthly family income and years of schooling. Covariates included sex, skin colour, number of residents per room and number of goods. Multilevel Negative Binomial regression models were used to estimate rate ratios (RR) and 95% confidence intervals between contextual and individual variables and tooth loss. Contextual and individual income and education measures were consistently associated with tooth loss. Elderly people living in cities with low HDI-income and low HDI-education were respectively 21% and 33% more likely to present tooth loss. Cross-level interaction suggested that the relationship of lower income and lower schooling with tooth loss is different across levels of city-level income and city-level education inequality, respectively. Public policies aiming to reduce the income and education gaps and preventive dental interventions are imperative to tackle tooth loss among elderly people.

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368 Durability of Tx Response to Zolpidem using a Partial Reinforcement Regimen: Does this strategy require contingent reinforcement?

SLEEP ◽

10.1093/sleep/zsab072.367 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A146-A147

Author(s):

Michael Perlis ◽

Knashawn Morales ◽

Ivan Vargas ◽

Alexandria Muench ◽

Mark Seewald ◽

...

Keyword(s):

Treatment Response ◽

Phase 1 ◽

Partial Reinforcement ◽

Continuous Treatment ◽

Phase 2 ◽

Sleep Continuity ◽

Average Improvement ◽

Average Change ◽

Treatment Responses ◽

Over Time

Abstract Introduction In 2015, partial reinforcement (PR) was assessed as an alternative approach to maintenance therapy with zolpidem. The method being: once a treatment response is obtained over the course of 1-month’s Tx with QHS dosing (Phase-1), Tx response can maintained over time with a PR regimen (Phase-2 [nightly pill/capsule use with 50% of capsules having medication and 50% having only inert filler]). In that study, it was assumed that Phase1 QHS dosing was required 1) to maximize treatment responding and 2) for the conditioning of pharmacologic responses to the medication vehicle (capsule). In the present study, these assumptions were tested by including both QHS and PR arms into Phase-1. Methods In Phase-1 (1 month), subjects were randomized to the QHS or PRS conditions (2QHS:1PRS). In Phase-2 (3 months), the PRS group continued forward without a change in the treatment regimen (variable dose [VD-VD]) and the QHS group was re-randomized to either continued QHS Tx (full dose [FD-FD]) or to PRS Tx [FD-VD]). Both study phases were evaluated for treatment responses rates and for average change in TWT (SL+WASO+EMA). Results 55 subjects (age 61.2+/-8.1, 64% female, & 73% white) were enrolled into Phase-1; 39 were randomized to the QHS condition and 16 to the PRS condition. In Phase-1, 77% (QHS) and 50% (PRS) exhibited treatment responses (p=0.09) where the average change in TWT was similar by group (QHS was -43min [CI -76,-9] and PRS was -76min [CI -138,-14];p=0.35). In Phase-2, 73% (FD-FD), 57% (FD-VD), and 88% (VD-VD) exhibited continued treatment responses (p=0.22) where the average improvement of TWT continued with FD-FD and remained stable for FD-VD and VD-VD (p<0.01). Conclusion These data, while preliminary, suggest that QHS (vs. PRS) dosing produces more treatment responders and similar initial effects on sleep continuity during Phase-1, comparable maintenance of treatment response over time, and continued improvement on sleep continuity during Phase-2. These results suggest that partial reinforcement can maintain effects but cannot allow for the additional clinical gains afforded by continuous treatment. Given this, it may be the case that the partial reinforcement technique could be improved upon by extending phase from 1 to 2–4 months. Support (if any):

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Evolving epidemiology of reported cryptosporidiosis cases in the United States, 1995–2012

Epidemiology and Infection ◽

10.1017/s0950268815003131 ◽

2015 ◽

Vol 144 (8) ◽

pp. 1792-1802 ◽

Cited By ~ 11

Author(s):

J. E. PAINTER ◽

J. W. GARGANO ◽

J. S. YODER ◽

S. A. COLLIER ◽

M. C. HLAVSA

Keyword(s):

United States ◽

Risk Factors ◽

Race And Ethnicity ◽

Negative Binomial ◽

Disease Outbreaks ◽

Negative Binomial Regression ◽

The United States ◽

Case Status ◽

Estimate Rate ◽

Rate Ratios

SUMMARYCryptosporidiumis the leading aetiology of waterborne disease outbreaks in the United States. This report briefly describes the temporal and geographical distribution of US cryptosporidiosis cases and presents analyses of cryptosporidiosis case data reported in the United States for 1995–2012. The Cochran–Armitage test was used to assess changes in the proportions of cases by case status (confirmedvs.non-confirmed), sex, race, and ethnicity over the study period. Negative binomial regression models were used to estimate rate ratios (RR) and 95% confidence intervals (CI) for comparing rates across three time periods (1995–2004, 2005–2008, 2009–2012). The proportion of confirmed cases significantly decreased (P< 0·0001), and a crossover from male to female predominance in case-patients occurred (P< 0·0001). Overall, compared to 1995–2004, rates were higher in 2005–2008 (RR 2·92, 95% CI 2·08–4·09) and 2009–2012 (RR 2·66, 95% CI 1·90–3·73). However, rate changes from 2005–2008 to 2009–2012 varied by age group (Pinteraction< 0·0001): 0–14 years (RR 0·55, 95% CI 0·42–0·71), 15–44 years (RR 0·99, 95% CI 0·82–1·19), 45–64 years (RR 1·47, 95% CI 1·21–1·79) and ⩾65 years (RR 2·18, 95% CI 1·46–3·25). The evolving epidemiology of cryptosporidiosis necessitates further identification of risk factors in population subgroups. Adding systematic molecular typing ofCryptosporidiumspecimens to US national cryptosporidiosis surveillance would help further identify risk factors and markedly expand understanding of cryptosporidiosis epidemiology in the United States.

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