Sub-Saharan African countries, Nigeria inclusive, are constrained by grossly limited access to quality pre-hospital trauma care services (PTCS). Findings from pragmatic approaches that explore ...spatial and temporal trends of past road crashes can inform novel interventions. To improve access to PTCS and reduce burden of road traffic injuries we explored geospatial trends of past emergency responses to road traffic crashes (RTCs) by Lagos State Ambulance Service (LASAMBUS), assessed efficiency of responses, and outcomes of interventions by local government areas (LGAs) of crash.
Using descriptive cross-sectional design and REDcap we explored pre-hospital care data of 1220 crash victims documented on LASAMBUS intervention forms from December 2017 to May 2018. We analyzed trends in days and times of calls, demographics of victims, locations of crashes and causes of delayed emergency responses. Assisted with STATA 16 and ArcGIS pro we conducted descriptive statistics and mapping of crash metrics including spatial and temporal relationships between times of the day, seasons of year, and crash LGA population density versus RTCs incidence. Descriptive analysis and mapping were used to assess relationships between 'Causes of Delayed response' and respective crash LGAs, and between Response Times and crash LGAs.
Incidences of RTCs were highest across peak commuting hours (07:00-12:59 and 13:00-18:59), rainy season and harmattan (foggy) months, and densely populated LGAs. Five urban LGAs accounted for over half of RTCs distributions: Eti-Osa (14.7%), Ikeja (14.4%), Kosofe (9.9%), Ikorodu (9.7%), and Alimosho (6.6%). On intervention forms with a Cause of Delay, Traffic Congestion (60%), and Poor Description (17.8%), had associations with LGA distribution. Two densely populated urban LGAs, Agege and Apapa were significantly associated with Traffic Congestion as a Cause of Delay. LASAMBUS was able to address crash in only 502 (36.8%) of the 1220 interventions. Other notable outcomes include: No Crash (false calls) (26.6%), and Crash Already Addressed (22.17%).
Geospatial analysis of past road crashes in Lagos state offered key insights into spatial and temporal trends of RTCs across LGAs, and identified operational constraints of state-organized PTCS and factors associated with delayed emergency responses. Findings can inform programmatic interventions to improve trauma care outcomes.
This study examined the public's sentiments about vaccines by analyzing Twitter data during the CDC's vaccination management planning stage in the United States. Sentiment scores were assigned to ...each tweet using a sentiment dictionary and the sentiment changes were analyzed over 52 weeks from November 2020 to November 2021. An interrupted time series model was used to analyze the difference in sentiment, which revealed that there was a shift. Initially, overall sentiments were negative but became positive as the stage of general vaccine supply approached. However, negative sentiments sharply rose when the vaccine supply transitioned to the phase of universalization. The results identified two dominant strategic action fields for vaccines providing polarized messages on Twitter and the negative trend was strong for most of the period. The findings highlight the importance of managing strategic action fields on social networks to prevent mass hysteria during vaccine policy implementation. This study stresses the significance of effectively managing strategic action fields on social media platforms to prevent mass hysteria while implementing vaccine policies.
Undiagnosed tuberculosis (TB) cases are the major challenge to TB control in Nigeria. An early warning outbreak recognition system (EWORS) is a system that is primarily used to detect infectious ...disease outbreaks; this system can be used as a case-based geospatial tool for the real-time identification of hot spot areas with clusters of TB patients. TB screening targeted at such hot spots should yield more TB cases than screening targeted at non-hot spots.
We aimed to demonstrate the effectiveness of an EWORS for TB hot spot mapping as a tool for detecting areas with increased TB case yields in high TB-burden states of Nigeria.
KNCV Tuberculosis Foundation Nigeria deployed an EWORS to 14 high-burden states in Nigeria. The system used an advanced surveillance mechanism to identify TB patients' residences in clusters, enabling it to predict areas with elevated disease spread (ie, hot spots) at the ward level. TB screening outreach using the World Health Organization 4-symptom screening method was conducted in 121 hot spot wards and 213 non-hot spot wards selected from the same communities. Presumptive cases identified were evaluated for TB using the GeneXpert instrument or chest X-ray. Confirmed TB cases from both areas were linked to treatment. Data from the hot spot and non-hot spot wards were analyzed retrospectively for this study.
During the 16-month intervention, a total of 1,962,042 persons (n=734,384, 37.4% male, n=1,227,658, 62.6% female) and 2,025,286 persons (n=701,103, 34.6% male, n=1,324,183, 65.4% female) participated in the community TB screening outreaches in the hot spot and non-hot spot areas, respectively. Presumptive cases among all patients screened were 268,264 (N=3,987,328, 6.7%) and confirmed TB cases were 22,618 (N=222,270, 10.1%). The number needed to screen to diagnose a TB case in the hot spot and non-hot spot areas was 146 and 193 per 10,000 people, respectively.
Active TB case finding in EWORS-mapped hot spot areas yielded higher TB cases than the non-hot spot areas in the 14 high-burden states of Nigeria. With the application of EWORS, the precision of diagnosing TB among presumptive cases increased from 0.077 to 0.103, and the number of presumptive cases needed to diagnose a TB case decreased from 14.047 to 10.255 per 10,000 people.
This study aims to investigate how the demographic characteristics of offenders have changed after the COVID-19 pandemic. Specifically, our research focuses on shifts in the nationality, gender ...distribution, and age profiles of money mules during this period. We utilized arrest reports data provided by the Seoul Metropolitan Police Agency in South Korea, including all 1407 individuals arrested for money mules in Seoul from February 1, 2018, to December 31, 2021. Our findings, derived from interrupted time series analyses, show a decrease in the percentage of non-Korean money mules, an increase in the proportion of female individuals engaged in money mule activities, and a rise in the average age of money mules after the outbreak of the pandemic. These insights hold significant implications for developing targeted policy interventions to mitigate potential threats associated with money mule activities.
•The demographic characteristics of offenders have changed since the COVID-19 pandemic.•The percentage of foreign (non-Korean) money mules has decreased since the onset of the pandemic.•The proportion of female money mules has increased since the onset of the pandemic.•The average age of money mules has increased since the onset of the pandemic.
The transmission of COVID-19 suddenly shifted most school classes to online lectures, and these unexpected changes often exacerbated existing imbalances by region and school. Our study used land ...price data as a proxy for regional wealth and empirically examined the inflation of education inequality between the areas with high and low land prices during the COVID-19 pandemic in South Korea. The gaps in the average high school Math and English scores between 2019 and 2020 (Y1 effect) and 2019 and 2021 (Y2 effect) are used as the main educational outcomes. We utilized the spatial difference-in-difference (DID) method to reflect the spatial autocorrelation on the school-level distribution of the score changes. The impact of the online class conversion on student performances was found to be significantly different between the regions with low and high land price and was more noticeable for the Math score during the first year of the pandemic. During the second year of the pandemic (2021), the scores increased in both regions, but the regional gap remained persistent. Evidence-based policies should be implemented to enhance regional educational conditions and resources, which, in turn, should prevent educational inequality across the regions stemming from the conversion to online classes.
본 연구는 미끄러운 경사이론을 활용하여 조세순응이 납세태도에 미치는 영향을 살펴보고, 납세자의 납세태도 결정요인을 예측·확인함으로써 성실한 납세태도를 제고할 수 있는 과세당국의 다양한 정책방향을 모색하려고 한다. 특히 조세순응의 이론 중 ‘미끄러운 경사이론’에 기반을 두어 납세자들의 조세순응을 강요된 순응과 자발적 순응으로 구분하여, 납세태도에 대한 ...영향관계를 중심으로 분석하였다. 분석에 사용한 자료는 한국조세재정연구원의 ‘9차년도 재정패널’ 자료이다. 분석은 서열 로짓 분석, 의사결정나무 모형과 신경망 모형을 중심으로 하는 데이터 마이닝 기법을 활용하였다.
서열 로짓 분석 결과에 따르면, 강요된 순응은 납세태도에 부정적인 영향을 주는 반면, 자발적 순응은 긍정적인 영향을 주는 것으로 나타났다. 그 다음 신경망을 근거한 의사결정나무 분석 결과, 세금 집행에 대한 신뢰, 신용-직불카드 사용금액, 수평적 형평성 인식, 일반공무원에 대한 신뢰가 긍정적인 납세태도 형성에 주요한 영향을 미치는 것으로 예측되었다.
이러한 결과를 토대로 성실한 납세태도를 위한 정책형성에 있어 기존의 납세유도 정책과 함께 세금 집행과 공무원에 대한 납세자의 신뢰환경 조성에 대한 시사점 및 정책적 방향을 제시하였다.
This study examines the effects of tax compliance on tax attitude using the slippery slope framework. By predicting and confirming the determinants of taxpayer's attitude, it explores the various policy directions of taxation authorities that can enhance taxpayer's attitude. In particular, by distinguishing forced and voluntary compliances on the basis of 'the slippery slope framework', it analyzes the relationships between taxpayer's tax compliance and tax attitude. The data used in this study is 'the ninth fiscal panel of the Korea Institute of Public Finance.' The analysis utilizes data mining techniques based on ordered logit regression model, decision tree model and neural network model.
The results show that forced compliance had a negative effect on tax attitude, while voluntary compliance had a positive effect. A decision tree analysis based on neural networks then predicted that trust in tax enforcement, awareness of horizontal equity, and confidence in public officials had major impacts on the formation of positive tax attitude. Thus, in order to form the policies for positive tax incentives, this study suggests the importance of tax enforcement and creating taxpayers' trust environment for public officials.
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