scholarly journals High-risk regions and outbreak modelling of tularemia in humans

2016 ◽  
Vol 145 (3) ◽  
pp. 482-490 ◽  
Author(s):  
A. DESVARS-LARRIVE ◽  
X. LIU ◽  
M. HJERTQVIST ◽  
A. SJÖSTEDT ◽  
A. JOHANSSON ◽  
...  
Keyword(s):  
High Risk ◽  
Disease Surveillance ◽  
Negative Binomial ◽  
Warning System ◽  
Negative Binomial Regression ◽  
Weather Data ◽  
Annual Number ◽  
Mosquito Abundance ◽  
Annual Variations ◽  
Populations At Risk

SUMMARYSweden reports large and variable numbers of human tularemia cases, but the high-risk regions are anecdotally defined and factors explaining annual variations are poorly understood. Here, high-risk regions were identified by spatial cluster analysis on disease surveillance data for 1984–2012. Negative binomial regression with five previously validated predictors (including predicted mosquito abundance and predictors based on local weather data) was used to model the annual number of tularemia cases within the high-risk regions. Seven high-risk regions were identified with annual incidences of 3·8–44 cases/100 000 inhabitants, accounting for 56·4% of the tularemia cases but only 9·3% of Sweden's population. For all high-risk regions, most cases occurred between July and September. The regression models explained the annual variation of tularemia cases within most high-risk regions and discriminated between years with and without outbreaks. In conclusion, tularemia in Sweden is concentrated in a few high-risk regions and shows high annual and seasonal variations. We present reproducible methods for identifying tularemia high-risk regions and modelling tularemia cases within these regions. The results may help health authorities to target populations at risk and lay the foundation for developing an early warning system for outbreaks.

Evaluation of the efficacy of an intersection conflict warning system at two-way stop-controlled rural intersections: difference-in-differences and triple-difference analytical approaches

2021 ◽  
pp. injuryprev-2021-044321
Author(s):  
Disi Tian ◽  
Susan G Gerberich ◽  
Hyun Kim ◽  
Andrew D Ryan ◽  
Darin J Erickson ◽  
...  
Keyword(s):  
High Risk ◽  
Negative Binomial ◽  
Warning System ◽  
Negative Binomial Regression ◽  
Difference In Difference ◽  
Difference In Differences ◽  
Crash Data ◽  
Crash Rates ◽  
And Control ◽  
Analytical Approaches

ObjectiveIntersection conflict warning systems (ICWSs) have been implemented at high-risk two-way stop-controlled intersections to prevent right-angle crashes and associated injuries. This study involved investigation of the impacts of ICWSs on crash reductions.MethodsThe study used a quasi-experimental design to analyse the potential causal relations between Minnesota’s ICWSs and various crash rate outcomes (including total, injury, non-injury, targeted right-angle and non-right-angle crashes) in pre-post analyses. A restricted randomisation method enabled identification of three controls to each ICWS treatment intersection, and included as many comparable intersection characteristics as possible. Annual crash rates (per year per intersection) were analysed over the same periods before and after system activation for treatment and control intersections in each matched group. Pre-crash data for 3 years and post-crash data for up to 5 years were included, ranging from 2010 to 2018. Negative binomial regression models with generalised estimating equations were applied to estimate the average, immediate and continuing treatment effects of ICWSs, through the difference-in-differences and difference-in-difference-in-difference approaches, respectively.ResultsThe ICWS treatment was significantly associated with a decreasing trend for targeted right-angle crash rates posttreatment. Although not statistically significant, most crash rate outcomes appeared to be elevated immediately after treatment (statistically significant for sideswipe crashes only). Pre–post differences in average crash rates (over entire periods), except for incapacitating injury-related crashes, were not statistically significant between treatment and control intersections.ConclusionsThe study provided important insight into potential causal associations between intersection safety countermeasures and crashes at high-risk rural two-way stop-controlled intersections.

scholarly journals Reproductive history of the Danish multiple sclerosis population: A register-based study

2019 ◽  
Vol 26 (8) ◽  
pp. 902-911 ◽  
Author(s):  
Julie Yoon Moberg ◽  
Bjarne Laursen ◽  
Lau Caspar Thygesen ◽  
Melinda Magyari
Keyword(s):  
Multiple Sclerosis ◽  
Regression Model ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Annual Number ◽  
Negative Binomial Regression Model ◽  
Live Births ◽  
Multiple Sclerosis Population ◽  
History Of ◽  
Ectopic Pregnancies

Background: A diagnosis of multiple sclerosis (MS) may impact the choice of parenthood. Objective: To investigate the number of live births, abortions and ectopic pregnancies among persons with MS. Methods: From the Danish Multiple Sclerosis Registry, we extracted data from all persons diagnosed with MS from 1960 to 1996 and matched each MS person with four reference persons. We used a negative binomial regression model for the live births and Poisson regression model for abortions and ectopic pregnancies. The total fertility rate (TFR) during 1960–2016 and the annual number of live births in the MS population were analysed. Results: Persons with MS had fewer children than reference persons. Fewer women with MS had elective abortions after diagnosis (incidence rate ratio (IRR) = 0.88; 95% confidence interval (CI) = 0.78–1.00) than reference persons. There was no difference regarding the number of elective abortions, spontaneous abortions or ectopic pregnancies after onset. The TFR was lower for women with MS than for reference persons, and the number of annual live births by MS persons increased during 1960–2016. Conclusion: MS seems to considerably impact reproductive choices, especially after clinical diagnosis, resulting in the MS population having fewer children than the general population.

scholarly journals Temporal Trends in Opioid Prescribing Patterns Among Oncologists in the Medicare Population

2020 ◽  
Author(s):  
Vikram Jairam ◽  
Daniel X Yang ◽  
Saamir Pasha ◽  
Pamela R Soulos ◽  
Cary P Gross ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Temporal Trends ◽  
State Level ◽  
Negative Binomial Regression ◽  
Time Frame ◽  
Prescribing Patterns ◽  
Annual Number ◽  
Medicare Beneficiaries ◽  
Care Providers ◽  
Opioid Prescribing

Abstract Background In the wake of the US opioid epidemic, there have been efforts to curb opioid prescribing. However, it is unknown whether these efforts have affected prescribing among oncologists, whose patients often require opioids for symptom management. We investigated temporal patterns in opioid prescribing for Medicare beneficiaries among oncologists and nononcologists. Methods We queried the Centers for Medicare and Medicaid Services Part D prescriber dataset for all physicians between January 1, 2013, and December 31, 2017. We used population-averaged multivariable negative binomial regression to estimate the association between time and per-provider opioid and gabapentinoid prescribing rate, defined as the annual number of drug claims (original prescriptions and refills) per beneficiary, among oncologists and nononcologists on a national and state level. Results From 2013 to 2017, the national opioid-prescribing rate declined by 20.7% (P < .001) among oncologists and 22.8% (P < .001) among non oncologists. During this time frame, prescribing of gabapentin increased by 5.9% (P < .001) and 23.1% (P < .001) among oncologists and nononcologists, respectively. Among palliative care providers, opioid prescribe increased by 15.3% (P < .001). During the 5-year period, 43 states experienced a decrease (P < .05) in opioid prescribing among oncologists, and in 5 states, opioid prescribing decreased more among oncologists than nononcologists (P < .05). Conclusions Between 2013 and 2017, the opioid-prescribing rate statistically significantly decreased nationwide among oncologists and nononcologists, respectively. Given similar declines in opioid prescribing among oncologists and nononcologists, there is concern that opioid-prescribing guidelines intended for the noncancer population are being applied inappropriately to patients with cancer and cancer survivors.

scholarly journals Meteorological factors affecting scrub typhus occurrence: a retrospective study of Yamagata Prefecture, Japan, 1984–2014

2016 ◽  
Vol 145 (3) ◽  
pp. 462-470 ◽  
Author(s):  
J. SETO ◽  
Y. SUZUKI ◽  
R. NAKAO ◽  
K. OTANI ◽  
K. YAHAGI ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Scrub Typhus ◽  
Meteorological Factors ◽  
Negative Relationship ◽  
Warning System ◽  
Negative Binomial Regression ◽  
Early Summer ◽  
Vector Borne Diseases ◽  
Cumulative Rainfall ◽  
Northern Japan

SUMMARYClimate change, by its influence on the ecology of vectors might affect the occurrence of vector-borne diseases. This study examines the effects of meteorological factors in Japan on the occurrence of scrub typhus, a mite-borne zoonosis caused byOrientia tsutsugamushi. Using negative binomial regression, we analysed the relationships between meteorological factors (including temperature, rainfall, snowfall) and spring–early summer cases of scrub typhus in Yamagata Prefecture, Japan, during 1984–2014. The average temperature in July and August of the previous year, cumulative rainfall in September of the previous year, snowfall throughout the winter, and maximum depth of snow cover in January and February were positively correlated with the number of scrub typhus cases. By contrast, cumulative rainfall in July of the previous year showed a negative relationship to the number of cases. These associations can be explained by the life-cycle ofLeptotrombidium pallidum, a predominant vector of spring–early summer cases of scrub typhus in northern Japan. Our findings show that several meteorological factors are useful to estimate the number of scrub typhus cases before the endemic period. They are applicable to establish an early warning system for scrub typhus in northern Japan.

scholarly journals Diversity and Abundance of Mosquitoes Inhabiting Waste Tires in a Subtropical Swamp in Urban Florida

2018 ◽  
Vol 34 (1) ◽  
pp. 47-49 ◽  
Author(s):  
Emily T. N. Dinh ◽  
Robert J. Novak
Keyword(s):  
Public Health ◽  
Negative Binomial ◽  
Urban Forest ◽  
Health Hazard ◽  
Species Abundance ◽  
Negative Binomial Regression ◽  
Freshwater Wetland ◽  
Forest Fragments ◽  
Waste Tires ◽  
Mosquito Abundance

ABSTRACT Automobile tires discarded in urban forest fragments may be a public health hazard, as they can support a population of vector mosquitoes. However, little is known about what factors may affect mosquito abundance and diversity within waste tires in a freshwater wetland forest. This study aimed to determine whether mosquito population dynamics in this environment in Florida differed over a year due to the site of collection and variation in vegetation greenness and elevation. We constructed negative binomial regression models to determine which of these characteristics were significant (α = 0.05) in affecting mosquito count data. Our findings suggest that in this specific environment, none of the covariates scrutinized had significant impacts on modulating overall mosquito and Aedes albopictus (the dominant species) abundance; waste tire habitats in urban freshwater wetland forests may be a year-round public health hazard.

Spatiotemporal variation and social determinants of suicide in China, 2006–2012: findings from a nationally representative mortality surveillance system

2015 ◽  
Vol 45 (15) ◽  
pp. 3259-3268 ◽  
Author(s):  
S. Liu ◽  
A. Page ◽  
P. Yin ◽  
T. Astell-Burt ◽  
X. Feng ◽  
...  
Keyword(s):  
Social Determinants ◽  
Rural Areas ◽  
Urban Areas ◽  
Disease Surveillance ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Spatiotemporal Variation ◽  
Geographic Variations ◽  
Family Relation ◽  
Suicide Rates

BackgroundSuicide in China has declined since the 1990s. However, there has been limited investigation of the potential spatiotemporal variation and social determinants of suicide during subsequent periods.MethodAnnual suicide counts from 2006 to 2012 stratified by county, 5-year age group (⩾15 years) and gender were obtained from the Chinese Disease Surveillance Points system. Trends and geographic differentials were examined using multilevel negative binomial regression models to explore spatiotemporal variation in suicide, and the role of key sociodemographic factors associated with suicide.ResultsThe suicide rate (per 100 000) in China decreased from 14.7 to 9.1, 2006–2012. Rates of suicide were higher in males than females and increased substantially with age. Suicide rates were higher in rural areas compared with urban areas; however, urban–rural disparities reduced over time with a faster decline for rural areas. Within both urban and rural areas, higher rates of suicide were evident in areas with lower socio-economic circumstances (SEC) [rate ratio (RR) 1.85, 95% confidence interval (CI) 1.31–2.62]. Suicide rates varied more than twofold (median RR 2.06) across counties, and were highest in central and southwest regions of China. A high proportion of the divorced population, especially for younger females, was associated with lower suicide rates (RR 0.60, 95% CI 0.46–0.79).ConclusionsGeographic variations for suicide should be taken into account in policy making, particularly for older males living in rural areas and urban areas with low SEC. Measures to reduce disparities in socio-economic level and alleviate family relation stress are current priorities.

scholarly journals Is area deprivation associated with greater impacts of COVID-19 in care homes across England? A preliminary analysis of COVID-19 outbreaks and deaths

2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti
Keyword(s):  
Negative Binomial ◽  
Care Home ◽  
Negative Binomial Regression ◽  
Population Characteristics ◽  
Care Homes ◽  
Future Research ◽  
Area Deprivation ◽  
Binomial Regression ◽  
Index Of Multiple Deprivation

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.

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