Giardiasis in the United States – an epidemiologic and geospatial analysis of county-level drinking water and sanitation data, 1993–2010

Giardiasis is the most commonly reported intestinal parasitic infection in the United States. Outbreak investigations have implicated poorly maintained private wells, and hypothesized a role for wastewater systems in giardiasis transmission. Surveillance data consistently show geographic variability in reported giardiasis incidence. We explored county-level associations between giardiasis cases, household water and sanitation (1990 census), and US Census division. Using 368,847 reported giardiasis cases (1993–2010), we mapped county-level giardiasis incidence rates, private well reliance, and septic system reliance, and assessed spatiotemporal clustering of giardiasis. We used negative binomial regression to evaluate county-level associations between giardiasis rates, region, and well and septic reliance, adjusted for demographics. Adjusted giardiasis incidence rate ratios (aIRRs) were highest (aIRR 1.3; 95% confidence interval 1.2–1.5) in counties with higher private well reliance. There was no significant association between giardiasis and septic system reliance in adjusted models. Consistent with visual geographic distributions, the aIRR of giardiasis was highest in New England (aIRR 3.3; 95% CI 2.9–3.9; reference West South Central region). Our results suggest that, in the USA, private wells are relevant to giardiasis transmission; giardiasis risk factors might vary regionally; and up-to-date, location-specific national data on water sources and sanitation methods are needed.

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1164. County-Level Geographic Distribution of Extended-Spectrum Cephalosporin-Resistant Enterobacteriaceae Across Outpatient Settings of the Veterans Health Administration, 2000–2017

Open Forum Infectious Diseases ◽

10.1093/ofid/ofy210.997 ◽

2018 ◽

Vol 5 (suppl_1) ◽

pp. S350-S351

Author(s):

Michihiko Goto ◽

Rajeshwari Nair ◽

Daniel Livorsi ◽

Marin Schweizer ◽

Michael Ohl ◽

...

Keyword(s):

United States ◽

Veterans Health Administration ◽

The United States ◽

Incidence Rates ◽

County Level ◽

Veterans Health ◽

Health Administration ◽

Geographic Variability ◽

Extended Spectrum ◽

Outpatient Settings

Abstract Background Extended-spectrum cephalosporin resistance (ESCR) among Enterobacteriaceae has emerged globally over the last two decades, with increased prevalence in the community. Data from European countries and healthcare-associated isolates in the United States have demonstrated substantial geographic variability in the prevalence of ESCR, but community-onset isolates in the United States have been less studied. We aimed to describe geographic distribution and spread of ESCR among outpatient settings across the Veterans Health Administration (VHA) over 18 years. Methods We analyzed a retrospective cohort of all patients who had any positive clinical culture specimen for ESCR Enterobacteriaceae collected in an outpatient setting; ESCR was defined by phenotypic nonsusceptibility to at least one extended-spectrum cephalosporin agent or detection of an extended-spectrum β-lactamase. Patient-level data were grouped by county of residence, and the total number of unique patients who received care within VHA for each county was used as a denominator. We aggregated data by time terciles (2000–2005, 2006–2011, and 2012–2017), and overall and county-level incidence rates were calculated as the number of unique patients in each year with ESCR Enterobacteriaceae per person-year. Results During the study period, there were 1,980,095 positive cultures for Enterobacteriaceae from 870,797 unique patients across outpatient settings of VHA, from a total of 107,404,504 person-years. Among those, 136,185 cultures (6.9%) from 75,500 unique patients (8.7%) were ESCR. The overall incidence rate was 9.0 cases per 10,000 person-years, which increased from 6.3 per 10,000 person-years in 2000 to 14.6 per 10,000 person-years in 2017. County-level incidence rates ranged widely but increased overall (interquartile range [IQR] in 2000–2005: 0–6.7; 2006–2011: 0–9.1; 2012–2017: 3.1–14.3 per 10,000 person-years), with some geographic clustering (figure). Conclusion This study demonstrates that there has been geographic variation both in incidence rates and trends of ESCR Enterobacteriaceae in outpatient settings of VHA, which suggests the importance of tailoring local antibiotic-prescribing guidelines incorporating geographic variability in epidemiology. Disclosures M. Ohl, Gilead Sciences, Inc.: Grant Investigator, Research grant.

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Trends in heart failure-related cardiovascular mortality in rural versus urban United States counties, 2011–2018: A cross-sectional study

PLoS ONE ◽

10.1371/journal.pone.0246813 ◽

2021 ◽

Vol 16 (3) ◽

pp. e0246813

Author(s):

Jacob B. Pierce ◽

Nilay S. Shah ◽

Lucia C. Petito ◽

Lindsay Pool ◽

Donald M. Lloyd-Jones ◽

...

Keyword(s):

United States ◽

Heart Failure ◽

Cause Of Death ◽

Negative Binomial ◽

The United States ◽

Mortality Rates ◽

County Level ◽

Physician Density ◽

Rural And Urban ◽

Related Mortality

Background Adults in rural counties in the United States (US) experience higher rates broadly of cardiovascular disease (CVD) compared with adults in urban counties. Mortality rates specifically due to heart failure (HF) have increased since 2011, but estimates of heterogeneity at the county-level in HF-related mortality have not been produced. The objectives of this study were 1) to quantify nationwide trends by rural-urban designation and 2) examine county-level factors associated with rural-urban differences in HF-related mortality rates. Methods and findings We queried CDC WONDER to identify HF deaths between 2011–2018 defined as CVD (I00-78) as the underlying cause of death and HF (I50) as a contributing cause of death. First, we calculated national age-adjusted mortality rates (AAMR) and examined trends stratified by rural-urban status (defined using 2013 NCHS Urban-Rural Classification Scheme), age (35–64 and 65–84 years), and race-sex subgroups per year. Second, we combined all deaths from 2011–2018 and estimated incidence rate ratios (IRR) in HF-related mortality for rural versus urban counties using multivariable negative binomial regression models with adjustment for demographic and socioeconomic characteristics, risk factor prevalence, and physician density. Between 2011–2018, 162,314 and 580,305 HF-related deaths occurred in rural and urban counties, respectively. AAMRs were consistently higher for residents in rural compared with urban counties (73.2 [95% CI: 72.2–74.2] vs. 57.2 [56.8–57.6] in 2018, respectively). The highest AAMR was observed in rural Black men (131.1 [123.3–138.9] in 2018) with greatest increases in HF-related mortality in those 35–64 years (+6.1%/year). The rural-urban IRR persisted among both younger (1.10 [1.04–1.16]) and older adults (1.04 [1.02–1.07]) after adjustment for county-level factors. Main limitations included lack of individual-level data and county dropout due to low event rates (<20). Conclusions Differences in county-level factors may account for a significant amount of the observed variation in HF-related mortality between rural and urban counties. Efforts to reduce the rural-urban disparity in HF-related mortality rates will likely require diverse public health and clinical interventions targeting the underlying causes of this disparity.

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Lifestyle Effects on the Risk of Transmission of COVID-19 in the United States: Evaluation of Market Segmentation Systems

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18094826 ◽

2021 ◽

Vol 18 (9) ◽

pp. 4826

Author(s):

Esra Ozdenerol ◽

Jacob Seboly

Keyword(s):

United States ◽

The United States ◽

Mortality Rates ◽

Incidence Rates ◽

Statistical Testing ◽

Average Risk ◽

County Level ◽

Household Level ◽

The Impact ◽

The U.S

The aim of this study was to associate lifestyle characteristics with COVID-19 infection and mortality rates at the U.S. county level and sequentially map the impact of COVID-19 on different lifestyle segments. We used analysis of variance (ANOVA) statistical testing to determine whether there is any correlation between COVID-19 infection and mortality rates and lifestyles. We used ESRI Tapestry LifeModes data that are collected at the U.S. household level through geodemographic segmentation typically used for marketing purposes to identify consumers’ lifestyles and preferences. According to the ANOVA analysis, a significant association between COVID-19 deaths and LifeModes emerged on 1 April 2020 and was sustained until 30 June 2020. Analysis of means (ANOM) was also performed to determine which LifeModes have incidence rates that are significantly above/below the overall mean incidence rate. We sequentially mapped and graphically illustrated when and where each LifeMode had above/below average risk for COVID-19 infection/death on specific dates. A strong northwest-to-south and northeast-to-south gradient of COVID-19 incidence was identified, facilitating an empirical classification of the United States into several epidemic subregions based on household lifestyle characteristics. Our approach correlating lifestyle characteristics to COVID-19 infection and mortality rate at the U.S. county level provided unique insights into where and when COVID-19 impacted different households. The results suggest that prevention and control policies can be implemented to those specific households exhibiting spatial and temporal pattern of high risk.

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County-level Predictors of Coronavirus Disease 2019 (COVID-19) Cases and Deaths in the United States: What Happened, and Where Do We Go from Here?

Clinical Infectious Diseases ◽

10.1093/cid/ciaa1729 ◽

2020 ◽

Author(s):

John M McLaughlin ◽

Farid Khan ◽

Sarah Pugh ◽

Frederick J Angulo ◽

Heinz-Josef Schmitt ◽

...

Keyword(s):

United States ◽

Negative Binomial ◽

Preventive Measures ◽

Severe Disease ◽

Multivariable Analysis ◽

The United States ◽

County Level ◽

Residential Housing ◽

Minority Communities ◽

Racial Ethnic

Abstract Background The United States has been heavily impacted by the coronavirus disease 2019 (COVID-19) pandemic. Understanding microlevel patterns in US rates of COVID-19 can inform specific prevention strategies. Methods Using a negative binomial mixed-effects regression model, we evaluated the associations between a broad set of US county-level sociodemographic, economic, and health status–related characteristics and cumulative rates of laboratory-confirmed COVID-19 cases and deaths between 22 January 2020 and 31 August 2020. Results Rates of COVID-19 cases and deaths were higher in US counties that were more urban or densely populated or that had more crowded housing, air pollution, women, persons aged 20–49 years, racial/ethnic minorities, residential housing segregation, income inequality, uninsured persons, diabetics, or mobility outside the home during the pandemic. Conclusions To our knowledge, this study provides results from the most comprehensive multivariable analysis of county-level predictors of rates of COVID-19 cases and deaths conducted to date. Our findings make clear that ensuring that COVID-19 preventive measures, including vaccines when available, reach vulnerable and minority communities and are distributed in a manner that meaningfully disrupts transmission (in addition to protecting those at highest risk of severe disease) will likely be critical to stem the pandemic.

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County-level exposures to greenness and associations with COVID-19 incidence and mortality in the United States

10.1101/2020.08.26.20181644 ◽

2020 ◽

Author(s):

Jochem O Klompmaker ◽

Jaime E Hart ◽

Isabel Holland ◽

M Benjamin Sabath ◽

Xiao Wu ◽

...

Keyword(s):

United States ◽

Population Density ◽

Vegetation Index ◽

Negative Binomial ◽

The United States ◽

Systems Science ◽

County Level ◽

Incidence And Mortality ◽

The Us ◽

At Home

AbstractBackgroundCOVID-19 is an infectious disease that has killed more than 246,000 people in the US. During a time of social distancing measures and increasing social isolation, green spaces may be a crucial factor to maintain a physically and socially active lifestyle while not increasing risk of infection.ObjectivesWe evaluated whether greenness is related to COVID-19 incidence and mortality in the United States.MethodsWe downloaded data on COVID-19 cases and deaths for each US county up through June 7, 2020, from Johns Hopkins University, Center for Systems Science and Engineering Coronavirus Resource Center. We used April-May 2020 Normalized Difference Vegetation Index (NDVI) data, to represent the greenness exposure during the initial COVID-19 outbreak in the US. We fitted negative binomial mixed models to evaluate associations of NDVI with COVID-19 incidence and mortality, adjusting for potential confounders such as county-level demographics, epidemic stage, and other environmental factors. We evaluated whether the associations were modified by population density, proportion of Black residents, median home value, and issuance of stay-at-home order.ResultsAn increase of 0.1 in NDVI was associated with a 6% (95% Confidence Interval: 3%, 10%) decrease in COVID-19 incidence rate after adjustment for potential confounders. Associations with COVID-19 incidence were stronger in counties with high population density and in counties with stay-at-home orders. Greenness was not associated with COVID-19 mortality in all counties; however, it was protective in counties with higher population density.DiscussionExposures to NDVI had beneficial impacts on county-level incidence of COVID-19 in the US and may have reduced county-level COVID-19 mortality rates, especially in densely populated counties.

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Associations between governor political affiliation and COVID-19 cases, deaths, and testing in the United States

10.1101/2020.10.08.20209619 ◽

2020 ◽

Author(s):

Brian Neelon ◽

Fedelis Mutiso ◽

Noel T Mueller ◽

John L Pearce ◽

Sara E Benjamin-Neelon

Keyword(s):

United States ◽

Political Ideology ◽

Negative Binomial ◽

The United States ◽

Incidence Rates ◽

Political Affiliation ◽

Party Affiliation ◽

Policy Decisions ◽

Daily Risk ◽

Future Policy

AbstractIntroductionThe response to the COVID-19 pandemic became increasingly politicized in the United States (US) and political affiliation of state leaders may contribute to policies affecting the spread of the disease. This study examined differences in COVID-19 infection, death, and testing by governor party affiliation across 50 US states and the District of Columbia.MethodsA longitudinal analysis was conducted in December 2020 examining COVID-19 incidence, death, testing, and test positivity rates from March 15 through December 15, 2020. A Bayesian negative binomial model was fit to estimate daily risk ratios (RRs) and posterior intervals (PIs) comparing rates by gubernatorial party affiliation. The analyses adjusted for state population density, rurality, census region, age, race, ethnicity, poverty, number of physicians, obesity, cardiovascular disease, asthma, smoking, and presidential voting in 2020.ResultsFrom March to early June, Republican-led states had lower COVID-19 incidence rates compared to Democratic-led states. On June 3, the association reversed, and Republican-led states had higher incidence (RR=1.10, 95% PI=1.01, 1.18). This trend persisted through early December. For death rates, Republican-led states had lower rates early in the pandemic, but higher rates from July 4 (RR=1.18, 95% PI=1.02, 1.31) through mid-December. Republican-led states had higher test positivity rates starting on May 30 (RR=1.70, 95% PI=1.66, 1.73) and lower testing rates by September 30 (RR=0.95, 95% PI=0.90, 0.98).ConclusionGubernatorial party affiliation may drive policy decisions that impact COVID-19 infections and deaths across the US. Future policy decisions should be guided by public health considerations rather than political ideology.

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Disparities in Shigellosis Incidence by Census Tract Poverty, Crowding, and Race/Ethnicity in the United States, FoodNet, 2004–2014

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa030 ◽

2020 ◽

Vol 7 (2) ◽

Author(s):

Tanya Libby ◽

Paula Clogher ◽

Elisha Wilson ◽

Nadine Oosmanally ◽

Michelle Boyle ◽

...

Keyword(s):

United States ◽

Incidence Rate ◽

Census Tract ◽

Negative Binomial ◽

Geographic Location ◽

Negative Binomial Regression ◽

The United States ◽

Incidence Rates ◽

Surveillance Network ◽

Race Ethnicity

Abstract Background Shigella causes an estimated 500 000 enteric illnesses in the United States annually, but the association with socioeconomic factors is unclear. Methods We examined possible epidemiologic associations between shigellosis and poverty using 2004–2014 Foodborne Diseases Active Surveillance Network (FoodNet) data. Shigella cases (n = 21 246) were geocoded, linked to Census tract data from the American Community Survey, and categorized into 4 poverty and 4 crowding strata. For each stratum, we calculated incidence by sex, age, race/ethnicity, and FoodNet site. Using negative binomial regression, we estimated incidence rate ratios (IRRs) comparing the highest to lowest stratum. Results Annual FoodNet Shigella incidence per 100 000 population was higher among children <5 years old (19.0), blacks (7.2), and Hispanics (5.6) and was associated with Census tract poverty (incidence rate ratio [IRR], 3.6; 95% confidence interval [CI], 3.5–3.8) and household crowding (IRR, 1.8; 95% CI, 1.7–1.9). The association with poverty was strongest among children and persisted regardless of sex, race/ethnicity, or geographic location. After controlling for demographic variables, the association between shigellosis and poverty remained significant (IRR, 2.3; 95% CI, 2.0–2.6). Conclusions In the United States, Shigella infections are epidemiologically associated with poverty, and increased incidence rates are observed among young children, blacks, and Hispanics.

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COVID-19 in Youth Soccer During Summer 2020

Journal of Athletic Training ◽

10.4085/610-20 ◽

2021 ◽

Author(s):

Andrew M. Watson ◽

Kristin Haraldsdottir ◽

Kevin Biese ◽

Leslie Goodavish ◽

Bethany Stevens ◽

...

Keyword(s):

United States ◽

Risk Reduction ◽

Incidence Rate ◽

Negative Binomial ◽

Risk Mitigation ◽

Negative Binomial Regression ◽

The United States ◽

Incidence Rates ◽

Negative Binomial Regression Model ◽

Youth Soccer

ABSTRACT Context: As sports reinitiate around the country, the incidence of COVID-19 among youth soccer athletes remains unknown. Objective: To determine the incidence of COVID-19 among youth soccer athletes and the risk mitigation practices utilized by youth soccer organizations. Design: Retrospective cohort. Participants: Youth soccer club directors throughout the United States. Main Outcome Measures: Surveys were completed in late August 2020 regarding phase of return to soccer (individual only, group non-contact, group contact), date of reinitiation, number of players, cases of COVID-19, and risk reduction procedures being implemented. Case and incidence rates were compared to national pediatric data and county data from the prior 10 weeks. A negative binomial regression model was developed to predict club COVID-19 cases with local incidence rate and phase of return as covariates and the log of club player-days as an offset. Results: 124 respondents had reinitiated soccer, representing 91,007 players with a median duration of 73 days (IQR: 53-83 days) since restarting. Of the 119 that had progressed to group activities, 218 cases of COVID-19 were reported among 85,861 players. Youth soccer players had a lower case rate and incidence rate than children in the US (254 v. 477 cases per 100,000; incidence rate ratio [IRR]=0.511, 95% CI = [0.40-0.57], p<0.001) and the general population from the counties where data was available (268 v. 864 cases per 100,000; IRR=0.202 [0.19–0.21], p<0.001). After adjusting for local COVID-19 incidence, there was no relationship between club COVID-19 incidence and phase of return (non-contact: b=0.35±0.67, p=0.61; contact: b=0.18±0.67, p=0.79). Soccer clubs reported utilizing a median of 8 (IQR: 6-10) risk reduction procedures. Conclusions: The incidence of COVID-19 among youth soccer athletes is relatively low when compared to the background incidence among children in the United States in summer of 2020. No relationship was identified between club COVID-19 incidence and phase of return to soccer.

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Risk factors associated with mortality of COVID-19 in 3125 counties of the United States

10.1101/2020.05.18.20105544 ◽

2020 ◽

Author(s):

Ting Tian ◽

Jingwen Zhang ◽

Liyuan Hu ◽

Yukang Jiang ◽

Congyuan Duan ◽

...

Keyword(s):

United States ◽

Risk Factors ◽

Negative Binomial ◽

The United States ◽

Outdoor Environment ◽

Local Health ◽

County Level ◽

Factors Associated ◽

High Prevalence ◽

The Impact

Background The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States. Methods To find out the risk factors associated with county-level mortality of COVID-19 with various levels of prevalence, a negative binomial design was applied to the county-level mortality counts of COVID-19 as of August 27, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to August 27, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies. Results 3125 infected counties were assigned into three classes corresponding to low, median, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where higher level of air pollution (0.153, P<0.001) increased the mortality in the low prevalence counties and elder individuals were more vulnerable in both the median and high prevalence counties . The segregation between non-Whites and Whites and higher Hispanic population had higher likelihood of risk of the deaths in all infected counties. Conclusions The mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may lead to the reduction in the mortality of COVID-19.

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Evolving Epidemiology of Reported Giardiasis Cases in the United States, 1995–2016

Clinical Infectious Diseases ◽

10.1093/cid/ciaa128 ◽

2020 ◽

Author(s):

Cushla M Coffey ◽

Sarah A Collier ◽

Michelle E Gleason ◽

Jonathan S Yoder ◽

Martyn D Kirk ◽

...

Keyword(s):

United States ◽

Negative Binomial ◽

Age Groups ◽

Negative Binomial Regression ◽

The United States ◽

Incidence Rates ◽

Age Group ◽

Case Definitions ◽

Reporting Practices ◽

System Data

Abstract Background Giardiasis is the most common intestinal parasitic disease of humans identified in the United States (US) and an important waterborne disease. In the United States, giardiasis has been variably reportable since 1992 and was made a nationally notifiable disease in 2002. Our objective was to describe the epidemiology of US giardiasis cases from 1995 through 2016 using National Notifiable Diseases Surveillance System data. Methods Negative binomial regression models were used to compare incidence rates by age group (0–4, 5–9, 10–19, 20–29, 30–39, 40–49, 50–64, and ≥ 65 years) during 3 time periods (1995–2001, 2002–2010, and 2011–2016). Results During 1995–2016, the average number of reported cases was 19 781 per year (range, 14 623–27 778 cases). The annual incidence of reported giardiasis in the United States decreased across all age groups. This decrease differs by age group and sex and may reflect either changes in surveillance methods (eg, changes to case definitions or reporting practices) or changes in exposure. Incidence rates in males and older age groups did not decrease to the same extent as rates in females and children. Conclusions Trends suggest that differences in exposures by sex and age group are important to the epidemiology of giardiasis. Further investigation into the risk factors of populations with higher rates of giardiasis will support prevention and control efforts.

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