scholarly journals The Role of the California Tier System in Controlling Population Mobility During the COVID-19 Pandemic

2021 ◽  
Author(s):  
Emilie L. Schwarz ◽  
Lara Schwarz ◽  
Anaïs Teyton ◽  
Katie Crist ◽  
Tarik Benmarhnia
Keyword(s):  
Demographic Data ◽  
Geographic Region ◽  
Median Income ◽  
County Level ◽  
Population Mobility ◽  
Policy Changes ◽  
Contagious Diseases ◽  
Novel Approach ◽  
Tier System ◽  
The Impact

Abstract Policies to restrict population mobility are a commonly used strategy to limit the transmission of contagious diseases. Among measures implemented during the COVID-19 pandemic were dynamic stay-at-home orders informed by real-time, regional-level data. California was the only state in the U.S. to implement this novel approach; however, the effectiveness of California’s four-tier system on population mobility has not been quantified. Utilizing data from mobile devices and county-level demographic data, we evaluated the impact of policy changes on population mobility and explored whether demographic characteristics explained variability in responsiveness to policy changes. For each Californian county, we calculated the proportion of people staying home and the average number of daily trips taken per 100 persons, across different trip distances and compared this to pre-COVID-19 levels. We found that overall mobility decreased when counties moved to a more restrictive tier and increased when moving to a less restrictive tier, as the policy intended. When placed in a more restrictive tier, the greatest decrease in mobility was observed for shorter and medium-range trips, while there was an unexpected increase in the longer trips. The mobility response varied by geographic region, as well as county-level median income, gross domestic product, the prevalence of farms, and recent election results. This analysis provides evidence of the effectiveness of the tier-based system in decreasing overall population mobility to ultimately reduce COVID-19 transmission. Results demonstrate that economic and political indicators drive important variability in such patterns across counties.

Local Option, Alcohol and Crime

2014 ◽  
Vol 14 (3) ◽  
pp. 791-816 ◽  
Author(s):  
Stephen B. Billings
Keyword(s):  
Alcohol Use ◽  
Drug Use ◽  
Criminal Behavior ◽  
Positive Relationship ◽  
County Level ◽  
Policy Changes ◽  
Panel Models ◽  
Local Option ◽  
The Impact

Abstract With the end of National Prohibition in 1933, 30 states gave counties and municipalities the local option to continue alcohol restrictions. Currently, 10% of U.S. counties still maintain a ban on some or all alcohol. Since the Prohibition movement advanced on the association between alcohol use and criminal behavior, this research examines the impact of county-level alcohol restrictions on multiple types of crime across five U.S. states. Standard panel models show a positive relationship between local option policy changes to allow alcohol and crime. The novelty of this research involves comparing the impact of alcohol restrictions across crimes classified by the degree to which an offense is often committed under the influence of alcohol. Results highlight impacts across a number of crime categories with crimes commonly committed under the influence of alcohol as well as crimes involving drug use and even crimes associated with obtaining alcohol all increasing when counties allow the sale and consumption of alcohol.

scholarly journals The Impact of U.S. County-Level Factors on COVID-19 Morbidity and Mortality

2021 ◽  
Author(s):  
Nevo Itzhak ◽  
Tomer Shahar ◽  
Robert Moskovich ◽  
Yuval Shahar
Keyword(s):  
Socioeconomic Factors ◽  
Age Distribution ◽  
Poverty Rate ◽  
Mortality Prediction ◽  
Morbidity And Mortality ◽  
Income Poverty ◽  
Median Income ◽  
County Level ◽  
Mortality And Morbidity ◽  
The Impact

AbstractBackgroundThe effect of socioeconomic factors, ethnicity, and other variables, on the frequency of COVID-19 cases [morbidity] and induced deaths [mortality] at sub-population, rather than at individual levels, is only partially understood.ObjectiveTo determine which county-level features best predict COVID-19 morbidity and mortality for a given county in the U.S.DesignA Machine-Learning model that predicts COVID-19 mortality and morbidity using county-level features, followed by a SHAP-values-based importance analysis of the predictive features.SettingPublicly available data from various American government and news websites.Participants3,071 U.S. counties, from which 53 county-level features, as well as morbidity and mortality numbers, were collected.MeasurementsFor each county: Ethnicity, socioeconomic factors, educational attainment, mask usage, population density, age distribution, COVID-19 morbidity and mortality, air quality indicators, presidential election results, ICU beds.ResultsA Random Forest classifier produced an AUROC of 0.863 for morbidity prediction and an AUROC of 0.812 for mortality prediction. A SHAP-values-based analysis indicated that poverty rate, obesity rate, mean commute time to work, and proportion of people that wear masks significantly affected morbidity rates, while ethnicity, median income, poverty rate, and education levels, heavily influenced mortality rates. The correlation between several of these factors and COVID-19 morbidity and mortality, from 4/2020 to 11/2020 shifted, probably due to COVID-19 being initially associated with more urbanized areas, then with less urbanized ones.LimitationsData are still coming in.ConclusionsEthnicity, education, and economic disparity measures are major factors in predicting the COVID-19 mortality rate in a county. Between-counties low-variance factors (e.g., age), are not meaningful predictors.Differing correlations can be explained by the COVID-19 spread from metropolitan to less metropolitan areas.Primary Funding SourceNone.

Impact of time from diagnosis to initiation of curative chemotherapy on survival of patients with diffuse large B-cell lymphoma (DLBCL).

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 8552-8552
Author(s):  
Kevin A. Hay ◽  
Benny Lee ◽  
Ozge Goktepe ◽  
Joseph M. Connors ◽  
Laurie Helen Sehn ◽  
...  
Keyword(s):  
Demographic Data ◽  
International Prognostic Index ◽  
Prognostic Index ◽  
Progression Free Survival ◽  
B Cell Lymphoma ◽  
Geographic Region ◽  
Time Interval ◽  
Curative Intent ◽  
Significant Difference ◽  
The Impact

8552 Background: DLBCL is potentially curable with combination chemotherapy such as CHOP-R. Although it is generally regarded appropriate to start chemotherapy promptly after diagnosis, the impact of the time from diagnosis to treatment initiation on treatment outcome is unknown. Methods: Patients diagnosed with DLBCL and treated with at least one cycle of CHOP-R with curative intent during 2003 – 2008 in British Columbia were identified in the Lymphoid Cancer Database. Additional demographic data were obtained from the BC Cancer Registry. The BC Cancer Agency provincial pharmacy database was used to obtain dates of chemotherapy administration. The impact of the time interval from the date of pathologic diagnosis to treatment on overall survival (OS) and progression-free survival (PFS) was evaluated. Results: A total of 793 patients were identified: 199 (25%) received CHOP-R <2 weeks after diagnosis, 244 (31%) at 2-4 weeks, 293 (37%) at 5-8 weeks, and 57 (7%) at >8 weeks. High international prognostic index, primary mediastinal DLBCL, and hospitalization at the time of CHOP-R start were associated with earlier initiation of chemotherapy (p<0.001 for all factors). Distance to chemotherapy from home (p=0.237), rural vs. urban location (p=0.952), geographic region (p=0.458), and median household income (p=0.127) were not associated to treatment start. Five-year PFS and OS respectively were 54% (SD 4%) and 61% (SD 4%) for treatment <2 weeks, 63% (SD 3%) and 66% (SD 3%) for 2-4 weeks, 70% (SD 3%) and 74% (SD 3%) for 5-8 weeks, and 60% (SD 7%) and for 61% (SD 8%) >8 weeks, p=0.006 (PFS) and p=0.024 (OS). A multivariate analysis demonstrated no significant difference between the groups. Conclusions: In a publicly funded healthcare system, earlier initiation of chemotherapy was strongly associated with poor prognostic factors, as well as inferior PFS and OS. The timing of chemotherapy initiation appears to be related to clinical factors instead of system or socioeconomic barriers. Notwithstanding the lack of detrimental outcomes in those commencing CHOP-R after 8 weeks, clinicians should endeavor to initiate curative chemotherapy as soon as possible after a diagnosis of DLBCL is established.

Drug prescription pattern in European neonatal units

2018 ◽  
Author(s):  
Inge Mesek ◽  
Georgi Nellis ◽  
Jana Lass ◽  
Tuuli Metsvaht ◽  
Heili Varendi ◽  
...  
Keyword(s):  
Drug Use ◽  
Parenteral Nutrition ◽  
Large Scale ◽  
Alimentary Tract ◽  
Drug Prescription ◽  
Demographic Data ◽  
Geographic Region ◽  
International Studies ◽  
Prescription Rate ◽  
The Impact

ABSTRACTBackgroundHospitalized neonates receive the highest number of drugs compared to all other age groups, but consumption rates vary between studies depending on patient characteristics and local practices. There are no large scale international studies on drug use in neonatal units. We aimed to describe drug use in European neonatal units and characterize its associations with geographic region and gestational age (GA).MethodsA one-day point prevalence study (PPS) was performed as part of the European Study of Neonatal Exposure to Excipients (ESNEE) from January to June 2012. All neonatal prescriptions and demographic data were registered in a web-based database. The impact of GA and region on prescription rate were analyzed with logistic regression.ResultsIn total, 21 European countries with 89 neonatal units participated. Altogether 2173 prescriptions given to 726 neonates were registered. The 10 drugs with the highest prescription rate were multivitamins, vitamin D, caffeine, gentamicin, amino acids for parenteral nutrition, phytomenadione, ampicillin, benzylpenicillin, fat emulsion for parenteral nutrition and probiotics. The six most commonly prescribed ATC groups (alimentary tract and metabolism, blood and blood-forming organs, systemic anti-infectives, nervous, respiratory and cardiovascular system) covered 98% of prescriptions. GA significantly affected the use of all commonly used drug groups. Geographic region influenced the use of alimentary tract and metabolism, blood and blood-forming organs, systemic anti-infectives, nervous and respiratory system drugs.ConclusionsWhile GA-dependent differences in neonatal drug use were expected, regional variations (except for systemic anti-infectives) indicate a need for cooperation in developing harmonized evidence-based guidelines and suggest priorities for collaborative work.

scholarly journals Towards human distance estimation using a thermal sensor array

2021 ◽  
Author(s):  
Abdallah Naser ◽  
Ahmad Lotfi ◽  
Joni Zhong
Keyword(s):  
High Resolution ◽  
Independent Living ◽  
Sensor Array ◽  
Distance Estimation ◽  
Thermal Sensor ◽  
Indoor Environments ◽  
Contagious Diseases ◽  
Novel Approach ◽  
Thermal Cameras ◽  
Distance Estimator

AbstractHuman distance estimation is essential in many vital applications, specifically, in human localisation-based systems, such as independent living for older adults applications, and making places safe through preventing the transmission of contagious diseases through social distancing alert systems. Previous approaches to estimate the distance between a reference sensing device and human subject relied on visual or high-resolution thermal cameras. However, regular visual cameras have serious concerns about people’s privacy in indoor environments, and high-resolution thermal cameras are costly. This paper proposes a novel approach to estimate the distance for indoor human-centred applications using a low-resolution thermal sensor array. The proposed system presents a discrete and adaptive sensor placement continuous distance estimators using classification techniques and artificial neural network, respectively. It also proposes a real-time distance-based field of view classification through a novel image-based feature. Besides, the paper proposes a transfer application to the proposed continuous distance estimator to measure human height. The proposed approach is evaluated in different indoor environments, sensor placements with different participants. This paper shows a median overall error of $$\pm 0.2$$ ± 0.2  m in continuous-based estimation and $$96.8\%$$ 96.8 % achieved-accuracy in discrete distance estimation.

scholarly journals Detection of diarrhoea associated rotavirus and co-infection with diarrhoeagenic pathogens in the Littoral region of Cameroon using ELISA, RT-PCR and Luminex xTAG GPP assays

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rahinatou N. Ghapoutsa ◽  
Maurice Boda ◽  
Rashi Gautam ◽  
Valantine Ngum Ndze ◽  
Akongnwi E. Mugyia ◽  
...  
Keyword(s):  
Demographic Data ◽  
Laboratory Diagnosis ◽  
Epidemiological Studies ◽  
Sub Saharan Africa ◽  
Rt Pcr ◽  
Mortality And Morbidity ◽  
Vaccine Introduction ◽  
Littoral Region ◽  
Rotavirus Vaccines ◽  
The Impact

Abstract Background Despite the global roll-out of rotavirus vaccines (RotaTeq/Rotarix / ROTAVAC/Rotasiil), mortality and morbidity due to group A rotavirus (RVA) remains high in sub-Saharan Africa, causing 104,000 deaths and 600,000 hospitalizations yearly. In Cameroon, Rotarix™ was introduced in March 2014, but, routine laboratory diagnosis of rotavirus infection is not yet a common practice, and vaccine effectiveness studies to determine the impact of vaccine introduction have not been done. Thus, studies examining RVA prevalence post vaccine introduction are needed. The study aim was to determine RVA prevalence in severe diarrhoea cases in Littoral region, Cameroon and investigate the role of other diarrheagenic pathogens in RVA-positive cases. Methods We carried out a study among hospitalized children < 5 years of age, presenting with acute gastroenteritis in selected hospitals of the Littoral region of Cameroon, from May 2015 to April 2016. Diarrheic stool samples and socio-demographic data including immunization and breastfeeding status were collected from these participating children. Samples were screened by ELISA (ProSpecT™ Rotavirus) for detection of RVA antigen and by gel-based RT-PCR for detection of the VP6 gene. Co-infection was assessed by multiplexed molecular detection of diarrheal pathogens using the Luminex xTAG GPP assay. Results The ELISA assay detected RVA antigen in 54.6% (71/130) of specimens, with 45, positive by VP6 RT-PCR and 54, positive using Luminex xTAG GPP. Luminex GPP was able to detect all 45 VP6 RT-PCR positive samples. Co-infections were found in 63.0% (34/54) of Luminex positive RVA infections, with Shigella (35.3%; 12/34) and ETEC (29.4%; 10/34) detected frequently. Of the 71 ELISA positive RVA cases, 57.8% (41/71) were fully vaccinated, receiving two doses of Rotarix. Conclusion This study provides insight on RVA prevalence in Cameroon, which could be useful for post-vaccine epidemiological studies, highlights higher than expected RVA prevalence in vaccinated children hospitalized for diarrhoea and provides the trend of RVA co-infection with other enteric pathogens. RVA genotyping is needed to determine circulating rotavirus genotypes in Cameroon, including those causing disease in vaccinated children.

scholarly journals National movement patterns during the COVID-19 pandemic in New Zealand: the unexplored role of neighbourhood deprivation

2021 ◽  
pp. jech-2020-216108 ◽  
Author(s):  
Malcolm Campbell ◽  
Lukas Marek ◽  
Jesse Wiki ◽  
Matthew Hobbs ◽  
Clive E Sabel ◽  
...  
Keyword(s):  
New Zealand ◽  
Mobile Phone ◽  
Well Being ◽  
Policy Debate ◽  
Population Mobility ◽  
Neighbourhood Deprivation ◽  
Movement Data ◽  
Spatial Inequalities ◽  
The Impact

BackgroundThe COVID-19 pandemic has asked unprecedented questions of governments around the world. Policy responses have disrupted usual patterns of movement in society, locally and globally, with resultant impacts on national economies and human well-being. These interventions have primarily centred on enforcing lockdowns and introducing social distancing recommendations, leading to questions of trust and competency around the role of institutions and the administrative apparatus of state. This study demonstrates the unequal societal impacts in population movement during a national ‘lockdown’.MethodsWe use nationwide mobile phone movement data to quantify the effect of an enforced lockdown on population mobility by neighbourhood deprivation using an ecological study design. We then derive a mobility index using anonymised aggregated population counts for each neighbourhood (2253 Census Statistical Areas; mean population n=2086) of national hourly mobile phone location data (7.45 million records, 1 March 2020–20 July 2020) for New Zealand (NZ).ResultsCurtailing movement has highlighted and exacerbated underlying social and spatial inequalities. Our analysis reveals the unequal movements during ‘lockdown’ by neighbourhood socioeconomic status in NZ.ConclusionIn understanding inequalities in neighbourhood movements, we are contributing critical new evidence to the policy debate about the impact(s) and efficacy of national, regional or local lockdowns which have sparked such controversy.

scholarly journals Influenza With an Infiltrate: Investigating the New Community-Acquired Pneumonia Guidelines

2020 ◽  
Vol 41 (S1) ◽  
pp. s302-s302
Author(s):  
Amanda Barner ◽  
Lou Ann Bruno-Murtha
Keyword(s):  
Demographic Data ◽  
Retrospective Chart Review ◽  
Vaccination Rate ◽  
Community Acquired Pneumonia ◽  
Teaching Hospitals ◽  
Antibiotic Prescribing ◽  
Supporting Evidence ◽  
Radiographic Findings ◽  
Significant Difference ◽  
The Impact

Background: The Infectious Diseases Society of America released updated community-acquired pneumonia (CAP) guidelines in October 2019. One of the recommendations, with a low quality of supporting evidence, is the standard administration of antibiotics in adult patients with influenza and radiographic evidence of pneumonia. Procalcitonin (PCT) is not endorsed as a strategy to withhold antibiotic therapy, but it could be used to de-escalate appropriate patients after 48–72 hours. Radiographic findings are not indicative of the etiology of pneumonia. Prescribing antibiotics for all influenza-positive patients with an infiltrate has significant implications for stewardship. Therefore, we reviewed hospitalized, influenza-positive patients at our institution during the 2018–2019 season, and we sought to assess the impact of an abnormal chest x-ray (CXR) and PCT on antibiotic prescribing and outcomes. Methods: We conducted a retrospective chart review of all influenza-positive admissions at 2 urban, community-based, teaching hospitals. Demographic data, vaccination status, PCT levels, CXR findings, and treatment regimens were reviewed. The primary outcome was the difference in receipt of antibiotics between patients with a negative (<0.25 ng/mL) and positive PCT. Secondary outcomes included the impact of CXR result on antibiotic prescribing, duration, 30-day readmission, and 90-day mortality. Results: We reviewed the medical records of 117 patients; 43 (36.7%) received antibiotics. The vaccination rate was 36.7%. Also, 11% of patients required intensive care unit (ICU) admission and 84% received antibiotics. Moreover, 109 patients had a CXR: 61 (55.9%) were negative, 29 (26.6%) indeterminate, and 19 (17.4%) positive per radiologist interpretation. Patients with a positive PCT (OR, 12.7; 95% CI, 3.43–60.98; P < .0007) and an abnormal CXR (OR, 7.4; 95% CI, 2.9–20.1; P = .000003) were more likely to receive antibiotics. There was no significant difference in 30-day readmission (11.6% vs 13.5%; OR, 0.89; 95% CI, 0.21–3.08; P = 1) and 90-day mortality (11.6% vs 5.4%; OR, 2.37; 95% CI, 0.48–12.75; P = .28) between those that received antibiotics and those that did not, respectively. Furthermore, 30 patients (62.5%) with an abnormal CXR received antibiotics and 21 (43.7%) had negative PCT. There was no difference in 30-day readmission or 90-day mortality between those that did and did not receive antibiotics. Conclusions: Utilization of PCT allowed selective prescribing of antibiotics without impacting readmission or mortality. Antibiotics should be initiated for critically ill patients and based on clinical judgement, rather than for all influenza-positive patients with CXR abnormalities.Funding: NoneDisclosures: None

scholarly journals Brain drain and brain gain in Russia: Analyzing international migration of researchers by discipline using Scopus bibliometric data 1996–2020

2021 ◽  
Author(s):  
Alexander Subbotin ◽  
Samin Aref
Keyword(s):  
Brain Drain ◽  
Policy Development ◽  
Donor Country ◽  
International Mobility ◽  
Science System ◽  
Migration Rates ◽  
Net Migration ◽  
Novel Approach ◽  
Five Disciplines ◽  
The Impact

AbstractWe study international mobility in academia, with a focus on the migration of published researchers to and from Russia. Using an exhaustive set of over 2.4 million Scopus publications, we analyze all researchers who have published with a Russian affiliation address in Scopus-indexed sources in 1996–2020. The migration of researchers is observed through the changes in their affiliation addresses, which altered their mode countries of affiliation across different years. While only 5.2% of these researchers were internationally mobile, they accounted for a substantial proportion of citations. Our estimates of net migration rates indicate that while Russia was a donor country in the late 1990s and early 2000s, it has experienced a relatively balanced circulation of researchers in more recent years. These findings suggest that the current trends in scholarly migration in Russia could be better framed as brain circulation, rather than as brain drain. Overall, researchers emigrating from Russia outnumbered and outperformed researchers immigrating to Russia. Our analysis on the subject categories of publication venues shows that in the past 25 years, Russia has, overall, suffered a net loss in most disciplines, and most notably in the five disciplines of neuroscience, decision sciences, mathematics, biochemistry, and pharmacology. We demonstrate the robustness of our main findings under random exclusion of data and changes in numeric parameters. Our substantive results shed light on new aspects of international mobility in academia, and on the impact of this mobility on a national science system, which have direct implications for policy development. Methodologically, our novel approach to handling big data can be adopted as a framework of analysis for studying scholarly migration in other countries.

Sign in / Sign up

Export Citation Format

Share Document