Time Series Regression Analysis Research Articles

Proactive care management of AI-identified at-risk patients decreases preventable admissions.

We assessed whether proactive care management for artificial intelligence (AI)-identified at-risk patients reduced preventable emergency department (ED) visits and hospital admissions (HAs). Stepped-wedge cluster randomized design. Adults receiving primary care at 48 UCLA Health clinics and determined to be at risk based on a homegrown AI model were included. We employed a stepped-wedge cluster randomized design, assigning groups of clinics (pods) to 1 of 4 single-cohort waves during which the proactive care intervention was implemented. The primary end points were potentially preventable HAs and ED visits; secondary end points were all HAs and ED visits. Within each wave, we used an interrupted time series and segmented regression analysis to compare utilization trends. In the pooled analysis of high-risk and highest-risk patients (n = 3007), potentially preventable HAs showed a statistically significant level drop (-27% [95% CI, -44% to -6%]), without any corresponding change in trends. Potentially preventable ED visits did not show a substantial level drop in response to the intervention, although a nonsignificant differential change in trend was observed, with visit rates decelerating 7% faster in the intervention cohorts (95% CI, -13% to 0%). Nonsignificant drops were observed for all HAs (-19% [95% CI, -35% to 1%]; P = .06) and ED visits (-15% [95% CI, -28% to 1%]; P = .06). A care management intervention targeting AI-identified at-risk patients was followed by a onetime, significant, sizable reduction in preventable HA rates. Further exploration is needed to assess the potential of integrating AI and care management in preventing acute hospital encounters.

EFFECT OF TAX REVENUE ON EXPENDITURE ALLOCATION OF GOVERNMENT SECTORS IN SOUTHWEST STATE, NIGERIA

Taxation has been recognized as exerting a significant influence on government expenditures, which constitute a fundamental component of an economy, particularly in numerous developing and underdeveloped nations. Taxes stand out as the primary source of funding for government expenditures. The extent to which tax revenue affect expenditure allocation of government sectors in southwest state, has remained a subject of concern in the Nigerian context. Therefore the study examines the effect of tax revenue on expenditure allocation of government sectors in southwest state, Nigeria. The research design employed in this study is ex-post facto, and data were obtained from audited annual financial reports and budgets of the southwestern states governments spanning a period of forty years, from 1982 to 2022. The study encompassed all six states within the southwest region of Nigeria. Both descriptive and inferential statistical techniques were utilized for analysis. Descriptive statistics, such as minimum, maximum, mean, and standard deviation values, were computed. Variance Decomposition Analysis (VDA) and Impulse Response Function (IRF), integral components of time series regression analysis, were employed to assess all study variables at a significance level of 5%. Regression analysis was conducted to investigate the impact of tax revenue on the allocation of government expenditures across various sectors in the southwest states of Nigeria. The study concluded that there is significant relationship between revenue and expenditure profile of state governments in southwest states, Nigeria. The study therefore recommended that government should explore avenues to diversify revenue sources beyond taxes.

EFFECT OF PAYE AND OTHER INTERNALLY GENERATED REVENUE TAXES ON EXPENDITURE OF GOVERNMENT IN SOUTHWEST STATE, NIGERIA

A tax is a compulsory charge on income, consumption and production imposed upon an individual, Partnership or companies by the government of a nation in order to fund various public expenditures. The intricate relationship between the collection of PAYE and other internally generated revenue taxes and the allocation of funds towards public services, infrastructure development, and social welfare programs poses a complex challenge. The study therefore examines the tax revenue and government expenditure in Southwest, Nigeria. The study adopts ex-post facto research design while data was sourced secondarily from the audited annual financial reports and budgets of southwestern states governments for the period of forty (40) years 1982-2022. The population of the study were the entire six (6) states of south west Nigeria. Analytical techniques used in the study involved both descriptive and inferential statistics. Descriptive statistics include minimum, maximum, mean and standard deviation values. Variance Decomposition Analysis (VDA) and Impulse Response Function (IRF) as components of time series regression analysis was used in assessing all the study variables at 5% significant level. Regression analysis was used to examine the effect of PAYE and other internally generated revenue taxes on expenditure. The result of the regression analysis implies that four explanatory variables INT and COT were significant in explaining variation on the effect of PAYE and other internally generated revenue taxes on expenditure of government in southwest state with p values of (0.0202 and 0.0116). The study concludes that Pay AsYou Earn (PAYE) and other internal generated revenue taxes has significant effect to government expenditure in southwest states, Nigeria. Therefore, the study recommends that Government in the southwestern states should develop and implement effective strategies to further boost revenue generation, especially from internal sources like Pay As You Earn (PAYE) and other internally generated taxes..

EFFECT OF PAYE AND OTHER INTERNALLY GENERATED REVENUE TAXES ON EXPENDITURE OF GOVERNMENT IN SOUTHWEST STATE, NIGERIA

A tax is a compulsory charge on income, consumption and production imposed upon an individual, Partnership or companies by the government of a nation in order to fund various public expenditures. The intricate relationship between the collection of PAYE and other internally generated revenue taxes and the allocation of funds towards public services, infrastructure development, and social welfare programs poses a complex challenge. The study therefore examines the tax revenue and government expenditure in Southwest, Nigeria. The study adopts ex-post facto research design while data was sourced secondarily from the audited annual financial reports and budgets of southwestern states governments for the period of forty (40) years 1982-2022. The population of the study were the entire six (6) states of south west Nigeria. Analytical techniques used in the study involved both descriptive and inferential statistics. Descriptive statistics include minimum, maximum, mean and standard deviation values. Variance Decomposition Analysis (VDA) and Impulse Response Function (IRF) as components of time series regression analysis was used in assessing all the study variables at 5% significant level. Regression analysis was used to examine the effect of PAYE and other internally generated revenue taxes on expenditure. The result of the regression analysis implies that four explanatory variables INT and COT were significant in explaining variation on the effect of PAYE and other internally generated revenue taxes on expenditure of government in southwest state with p values of (0.0202 and 0.0116). The study concludes that Pay AsYou Earn (PAYE) and other internal generated revenue taxes has significant effect to government expenditure in southwest states, Nigeria. Therefore, the study recommends that Government in the southwestern states should develop and implement effective strategies to further boost revenue generation, especially from internal sources like Pay As You Earn (PAYE) and other internally generated taxes..

Health impact of the Serious Accidents Punishment Act in Korean occupational settings

Abstract Background Interrupted time series analysis serves as a valuable study design for assessing the efficacy of public health interventions implemented at a specific moment in time at the population level. We aim to elucidate the effects of the Serious Accidents Punishment Act implemented in February 2021 in Korea by analyzing changes in the incidence rates of occupational diseases. Methods The monthly data from patients with occupational diseases was extracted from the National Health Insurance Service Cohort database from 2011 to 2023. An Interrupted time series analysis with Poisson segmented regression was used to compare the rates before and after the Serious Accidents Punishment Act introduction in both outpatients and inpatients. Adjustments or stratification variables included sex, age, company size, and injury-related international classification of diseases codes (Injury, poisoning, and certain other consequences of external causes, S00-T88). Results Based on injury rates, men’s inpatient injury rates remained stable, but outpatient rates decreased after the act implementation, while women’s injury rates consistently declined in both inpatient and outpatient settings. The Interrupted time series regression analysis indicates that the Serious Accidents Punishment Act led to a significant reduction in both outpatient and inpatient injury rates for men and women, with a marked decline in outpatient rates and hospital admissions among women post-intervention. Conclusions The Interrupted time series regression results suggest that the Serious Accidents Punishment Act has been effective in reducing injury-related healthcare usage, highlighting the necessity of gender-specific interventions and the potential impact on lowering inpatient visits, although causality remains uncertain without further analysis. Key messages • The Serious Accidents Punishment Act significantly reduced occupational injury rates in Korea, especially among women, demonstrating effective public health intervention. • Interrupted time series analysis reveals Serious Accidents Punishment Act’s impact on reducing healthcare usage for occupational injuries, highlighting the need for gender-specific approaches.

What’s pension got to do with it? Mortality inequality at older ages

Abstract Background The potential role of social protection systems and welfare states for population health and mortality has attracted increased interest in recent decades but mostly focused on overall characteristics or clusters of countries. Moreover, often neglecting older people even though the great majority of all deaths in high-income countries occur at later ages. We focus on the key social protection scheme for old adults: the generosity of the level of pensions. We compare pensions based on previous work history to basic minimum pensions. Our study is novel both by linking pension system to remaining life expectancy at age 65(LE65+), but also by studying the association to variation in LE65+, since that gives a measure of inequality. We do so across countries and over time. Methods and Materials Our sources of data are from the Human Mortality Database and the Social Policy Indicator Database. Data for OECD countries are matched over a long period of time and analysed by pooled time-series regression analyses with fixed effects. Results Although the results indicate that the generosity of pensions based on both pervious work history and basic minimum income our results primarily show the importance of basic minimum income. Here the effect sizes are larger and especially for women than for men (0.149*** vs. 0,.0715***). Concerning the variation in LE (65+) we find that more generous basic pensions are associated with reduced variation for women -4.64e-05**. Conclusions We provide new insights in how pension policies potentially influence mortality among older persons especially by extending our analyses also to inequality in mortality. Our results points to the importance of basic pensions. The gendered division of labour is a plausible explanation for the findings and to have an adequate pension for all should be of primary concern for public health. Key messages • Adequate basic pension for all of importance for remaining life expectancy among older people. • Adequate basic pension for all of importance for reducing mortality inequality among women.

Trends in medicine utilisation in public and private healthcare facilities before and during COVID-19: a nationwide analysis of medicine procurement and sales data, 2018-2022.

There was a fluctuation in medication demand and supply during COVID-19 pandemic. This study aimed to assess the trend of drug utilisation in Malaysia in 2018-2022 and evaluate the impact of COVID-19 on drug utilisation rates. We conducted a repeated cross-sectional study of pharmaceutical sales data from public and private sectors in Malaysia from 2018 to 2022. Drug utilisation rates for the period after the onset of COVID-19 (2020-2022) was compared with the earlier period (2018-2019). Interrupted time-series regression analyses evaluated level and slope changes compared to pre-COVID-19 pandemic level for quarterly rates of drugs utilisation in public and private sectors. There was an immediate reduction in the utilisation rates for all drugs after COVID-19 in public (-20.4%; p = 0.043) and private sectors (-22.4%; p = 0.003). In both sectors, significant level changes were observed for anti-infectives, musculoskeletal, neurological, respiratory, and sensory organs preparations following COVID-19 pandemic, followed by a sustained increase in trend from 2020 to 2022. Public sector had a 22.2% reduction in the utilisation of cardiovascular drugs (p = 0.002), particularly for renin-angiotensin system (RAS) agents (-47.4%, p = 0.019). Private sector had large changes for anti-infectives (-53.6%, p < 0.001) and neurological drugs (-51.4%, p < 0.001), driven by an immediate level reduction in antibacterials (-54.2%, p < 0.001) and cough and cold preparations (-59.2%, p < 0.001). Classes with agents used for COVID-19 treatment, such as systemic corticosteroids, antibiotics, and antivirals had an increasing trend between April 2020 and December 2022, although some slope changes were not statistically significant. A significant reduction in the overall drug utilisation rates was observed in the public and private sectors in Malaysia as an immediate impact of the COVID-19 pandemic in 2020. The impacts varied by therapeutic class and health sector. This finding provides an understanding of the changing patterns of drug utilisation that were affected by disease outbreaks for future planning of pandemic preparedness.

Analysis of health claims data on vaccination coverage in older adults in Bavaria, Germany: Influenza, pneumococcus and herpes zoster

BackgroundVaccination is essential, especially in older adults whose immune system function declines with age. The COVID-19 pandemic and its associated lockdowns temporarily disrupted routine vaccination services. We aimed to assess vaccination coverage for Influenza, Pneumococcus, and Herpes zoster among older adults in Bavaria over time and investigate potential pandemic effects on these rates. MethodsBased on health claims data from the Bavarian Association of Statutory Health Insurance Physicians (KVB), we estimated the percentage of adults aged 60 years and older vaccinated following the German Standing Committee on Vaccinations (STIKO) recommendation for Influenza (2012−2021), Pneumococcus (2017–2021) and Herpes zoster (2019–2021), stratified by sex and 10-year age groups. Using time series regression analysis, we estimated the effect of the pandemic period (2020−2021) on quarterly Influenza and Pneumococcal vaccination rates. ResultsIn the first year of the pandemic (2020), Influenza, Pneumococcus and Herpes zoster coverage in both sexes increased by 9.9, 8.7, and 2.5 percentage points (pp), respectively. In 2021, Influenza coverage decreased by 4.7 pp., while Pneumococcus and Herpes zoster coverage increased by 2.7 and 3.8 pp., respectively. Influenza and Pneumococcal vaccinations showed a seasonal pattern, with vaccinations occurring mainly in the fourth quarter; this pattern was distorted for Pneumococcus during the pandemic. Per the time series regression analysis, Influenza vaccination rates in the fourth quarters of 2020 and 2021 were 7.86 (95 %CI: 5.10–10.62) and 8.87 (95 %CI: 5.80–11.54) pp. higher for males and females, respectively, compared to that of the pre-pandemic period. During the pandemic, the quarterly Pneumococcal vaccination rates increased by 0.68 (95 %CI: 0.19–1.18) pp. in males and 0.80 (95 %CI: 0.30–1.30) pp. in females. ConclusionThe heightened increase in vaccination rates observed in 2020 may have resulted from increased vaccination awareness during the pandemic. As the pandemic effect wanes, more efforts are needed to sustain and increase these vaccination rates.

Is heat wave a predictor of diarrhoea in Dhaka, Bangladesh? A time-series analysis in a South Asian tropical monsoon climate.

While numerous studies have assessed the association between temperature and diarrhoea in various locations, evidence of relationship between heat wave and diarrhoea is scarce. We defined elevated daily mean and maximum temperature over the 95th and 99th percentiles lasting for at least one day between March to October 1981-2010 as TAV95 and TAV99 and D95 and D99 heat wave, respectively. We investigated the association between heat wave and daily counts of hospitalisations for all-cause diarrhoea in Dhaka, Bangladesh using time series regression analysis employing constrained distributed lag-linear models. Effects were assessed for all ages and children aged under 5 years of age. Diarrhoea hospitalisation increased by 6.7% (95% CI: 4.6%- 8.9%), 8.3% (3.7-13.1), 7.0 (4.8-9.3) and 7.4 (3.1-11.9) in all ages on a TAV95, TAV99, D95 and D99 heat wave day, respectively. These effects were more pronounced for under-5 children with an increase of 13.9% (95% CI: 8.3-19.9), 24.2% (11.3-38.7), 17.0 (11.0-23.5) and 19.5 (7.7-32.6) in diarrhoea hospitalisations on a TAV95, TAV99, D95 and D99 heat wave day, respectively. At lags of 3 days, we noticed a negative association indicating a 'harvesting' effect. Our findings suggest that heat wave was a significant risk factor for diarrhoea hospitalisation in Dhaka. Further research is needed to elucidate the causal pathways and identify the preventive measures necessary to mitigate the impacts of heat waves on diarrhoea. Given that no heat wave definitions exist for Dhaka, these results may help to define heat waves for Dhaka and trigger public health interventions including heat alerts to prevent heat-related morbidity in Dhaka, Bangladesh.

Effect of Temperature and Precipitation on Acute Appendicitis Incidence in Seoul: A Time Series Regression Analysis.

This study aimed to investigate the relationship between meteorological factors, specifically temperature and precipitation, and the incidence of appendicitis in Seoul, South Korea. Using data from the National Health Insurance Service spanning 2010-2020, the study analyzed 165,077 appendicitis cases in Seoul. Time series regression modeling with distributed-lag non-linear models was employed. Regarding acute appendicitis and daily average temperature, the incidence rate ratio (IRR) showed an increasing trend from approximately - 10°C to 10°C. At temperatures above 10°C, the increase was more gradual. The IRR approached a value close to 1 at temperatures below - 10°C and above 30°C. Both total and complicated appendicitis exhibited similar trends. Increased precipitation was negatively associated with the incidence of total acute appendicitis around the 50mm/day range, but not with complicated appendicitis. The findings suggest that environmental factors, especially temperature, may play a role in the occurrence of appendicitis. This research underscores the potential health implications of global climate change and the need for further studies to understand the broader impacts of environmental changes on various diseases.

Effects of COVID-19-targeted non-pharmaceutical interventions on pediatric emergency department use: a quasi-experimental study interrupted time-series analysis in North Italian hospitals, 2017 to 2022.

The use of Non-Pharmaceutical Interventions (NPIs) during the COVID-19 pandemic is debated. Understanding the consequences these measures may have on vulnerable populations including children and adolescents is important. This is a multicenter, quasi-experimental before-after study involving 12 hospitals of the North Italian Emilia-Romagna Region, with NPI implementation as the intervention event. The 3 years preceding NPI implementation (in March 2020) constituted the pre-pandemic phase. The subsequent 2 years were further subdivided into a school closure phase (SC) and a subsequent mitigation measures phase (MM) with milder restrictions. Interrupted Time Series (ITS) regression analysis was used to calculate PED Standardized Incidence Rate Ratios (SIRR) on the diagnostic categories exhibiting the greatest frequency and/or variation. In the 60 months of the study there were 765,215 PED visits. Compared to the pre-pandemic rate, overall PED presentations dropped by 58 and 39% during SC and MM, respectively. "Symptoms, signs and Ill-defined conditions," "Injury and poisoning" and "Diseases of the Respiratory System" accounted for 74% of the reduction. A different pattern was instead seen for "Mental Disorders," which exhibited the smallest decrease during SC, and is the only category which rose already at the end of SC. ITS analysis confirmed the strong decrease during SC (level change, IRR 0.17, 95%CI 0.12-0.27) and a significant increase in MM (slope change, IRR 1.23, 95%CI 1.13-1.33), with the sharpest decline (-94%) and rise (+36%) observed in the "Diseases of the Respiratory System" category. Mental Disorders showed a significant increasing trend of 1% monthly over the whole study period exceeding pre-pandemic levels at the end of MM. Females and adolescents showed higher increasing rates both in SC and MM. NPIs appear to have influenced PED attendance in different ways according to diagnostic categories, mirroring different mechanisms of action. These effects are beneficial in some cases and harmful in others, and establishing a clear balance between pros and cons is a difficult task for public health decision makers. The role of NPIs on PED use appropriateness deserves investigation. The rise in pediatric mental disorders independent of the pandemic makes interventions addressing these issues urgent.

Different factors affecting the real estate market in the Egyptian context

Purpose Real estate projects are capital-intensive and deeply intertwined with economic factors, making them subject to various influences besides local housing needs. This paper aims to comprehensively understand the dynamics of the Egyptian real estate market, examining real estate cycles, driving factors and their correlation and scale of impact. Design/methodology/approach The study conducts a literature review to explore real estate cycles and their driving factors, along with the relationship between real estate and macroeconomic cycles. It then delves into the dynamics of the Egyptian real estate market, followed by a time series analysis that incorporates five key indicators: economic indicator, demand indicator, supply indicator, capital flow indicator and cost indicator over a 12-year interval (2012–2023), to examine short-term cycle factors, followed by correlation and multi-linear regression analysis to elucidate interrelations among these factors. Findings Through measuring and comparing the prementioned indicators with different economic and social events, the study paints a comprehensive picture of the macroeconomic environment and the real estate cycle in Egypt. Where demand has been found to be more sensitive and directly affected by macroeconomic factors than the supply. With the economic factor as the factor with the highest impact, especially in times of economic fluctuations, the impact has been immediate and short-term. These findings support the idea that the demand in Egypt is speculative, laying a threat of longer recession periods in the long term and having greater and more direct impact. Originality/value This paper contributes to the understanding of the Egyptian real estate market by integrating insights from real estate cycles, macroeconomics and specific market dynamics. The application of time series, correlation and multi-linear regression analysis provides a nuanced understanding of the interplay between several factors shaping the real estate cycle. Ultimately, the findings offer valuable insights for decision-makers involved in urban development planning, facilitating more informed and precise decision-making processes.

Labor migration, remittances, and the economy in the Gulf Cooperation Council region

The massive increase in labor migration to the Middle East during the past three decades has rivaled its historical trends bound to the West. This paper assesses how this growing trend of migration may have helped shape the economic structure and performance across the member countries of the Gulf Cooperation Council. Findings from a descriptive and time series regression analysis of the limited cross-country data show that the experience with labor migration and its linkage with other aspects of the economy are varied. The migration trend coinciding with increasing personal remittances attests to the competitive demand for foreign labor. While labor migration shows mixed association with the key aspects of the economy, the stock of migrant population is negatively associated with economic growth. Albeit seemingly contradictory, the insights from this six-country analysis covering the periods since 1990 are useful to understand the complex nature of relationship between labor migration and economic structure and performance in the region.

Impact of narcotics information management system on inappropriate benzodiazepine receptor agonist prescriptions: A quasi-experimental analysis in South Korea.

The South Korean government implemented the narcotics information management system (NIMS) on 18 May 2018 to manage benzodiazepine receptor agonists (BzRAs) and narcotics effectively and establish a reporting mechanism for these drugs. This study assessed the effects of NIMS on inappropriate use of BzRAs. Using national patient sample data from 2016 to 2020, we analysed adult outpatients who were prescribed oral BzRAs. We conducted a time series and segmented regression analysis using selected indicators to analyse the monthly variations related to the inappropriate use of these medications. The study revealed no significant changes in the indicators of inappropriate BzRA use following the NIMS implementation. Contrary to expectations, there was a significant increase in the proportion of patients exceeding defined daily dose (DDD) and in those receiving concurrent prescriptions of multiple BzRAs, following the implementation of NIMS. The immediate impact of the COVID-19 pandemic was an increase in DDD exceedance; however, overall, this did not significantly affect BzRA use. The introduction of NIMS did not significantly enhance the management of BzRA misuse. Additional measures, including continuous monitoring, system improvements and comprehensive education for prescribers and patients, are recommended to ensure the appropriate use of psychotropic medications.

The Effects of Admission Policies on Rates of Family Migration in European States, 2008&amp;ndash;2019

This study investigates whether and how much family migration policies have influenced patterns of family migration in European states. Family migration has been the largest category of entry in many Western countries in recent decades, and it has been the subject of increasing contestation in political debates. While research on family migration policies has advanced in recent years, no comprehensive cross-country comparisons have been done of the impact of different policies on the size and composition of family migrant inflows. This study addresses this gap by analysing the connection between admission policies and rates of family migration in 31 European states during the 2008 to 2019 period. Combining data from Eurostat and the Migrant Integration Policy Index (MIPEX), this study uses a time-series regression analysis to assess the effects of admission policies on different types of family related immigration. While restrictive admission policies have led to falling overall levels of family migration, the analysis here reveals stratifying implications, whereby the effect has been greater where the sponsor is a non-EU citizen than where he/she is an EU citizen. By providing evidence on the differential impacts of admission policies on family related immigration, this study contributes new insights on the effects of restrictive migration policies.

Female Labor-Force Participation as Suicide Prevention: A Population Study in Taiwan

Objective Female labor-force participation (FLFP) has been theorized as contributing to higher suicide rates, including among women. Evidence on this relationship, however, has been mixed. This study explored the association between FLFP and suicide in an understudied context, Taiwan, and across 40-years. Methods Annual national labor-participation rates for women ages 25–64, and female and male suicide-rates, for 1980–2020, were obtained from Taiwan’s Department of Statistics. The associations between FLFP rates and sex/age-stratified suicide-rates, and between FLFP rates and male-to-female suicide-rates ratios were assessed via time-series regression-analyses, accounting for autoregressive effects. Results Higher FLFP rates were associated with lower female suicide-rates (ß = −0.06, 95% CI (Credibility Interval) = [−0.19, −0.01]) in the adjusted model. This association held in the age-stratified analyses. Associations for FLFP and lower male suicide-rates were observed in the ≥45 age-groups. FLFP rates were significantly and positively associated with widening male-to-female suicide-rates ratios in the adjusted model (ß = 0.24, 95% CI = [0.03, 0.59]). Conclusion This study’s findings suggest that FLFP protects women from suicide, and point to the potential value of FLFP as a way of preventing suicide. In Taiwan, employed women carry a double-load of paid and family unpaid care-work. Child care-work is still done by mothers, often with grandmothers’ support. Therefore, this study’s findings contribute to evidence that doing both paid work and unpaid family care-work has more benefits than costs, including in terms of suicide-protection. Men’s disengagement from family care-work may contribute to their high suicide rates, despite their substantial labor-force participation.

Effects of COVID-19-targeted non-pharmaceutical interventions on pediatric hospital admissions in North Italian hospitals, 2017 to 2022: a quasi-experimental study interrupted time-series analysis.

The use of Non-Pharmaceutical Interventions (NPIs), such as lockdowns, social distancing and school closures, against the COVID-19 epidemic is debated, particularly for the possible negative effects on vulnerable populations, including children and adolescents. This study therefore aimed to quantify the impact of NPIs on the trend of pediatric hospitalizations during 2 years of pandemic compared to the previous 3 years, also considering two pandemic phases according to the type of adopted NPIs. This is a multicenter, quasi-experimental before-after study conducted in 12 hospitals of the Emilia-Romagna Region, Northern Italy, with NPI implementation as the intervention event. The 3 years preceding the beginning of NPI implementation (in March 2020) constituted the pre-pandemic phase. The subsequent 2 years were further subdivided into a school closure phase (up to September 2020) and a subsequent mitigation measures phase with less stringent restrictions. School closure was chosen as delimitation as it particularly concerns young people. Interrupted Time Series (ITS) regression analysis was applied to calculate Hospitalization Rate Ratios (HRR) on the diagnostic categories exhibiting the greatest variation. ITS allows the estimation of changes attributable to an intervention, both in terms of immediate (level change) and sustained (slope change) effects, while accounting for pre-intervention secular trends. Overall, in the 60 months of the study there were 84,368 cases. Compared to the pre-pandemic years, statistically significant 35 and 19% decreases in hospitalizations were observed during school closure and in the following mitigation measures phase, respectively. The greatest reduction was recorded for "Respiratory Diseases," whereas the "Mental Disorders" category exhibited a significant increase during mitigation measures. ITS analysis confirms a high reduction of level change during school closure for Respiratory Diseases (HRR 0.19, 95%CI 0.08-0.47) and a similar but smaller significant reduction when mitigation measures were enacted. Level change for Mental Disorders significantly decreased during school closure (HRR 0.50, 95%CI 0.30-0.82) but increased during mitigation measures by 28% (HRR 1.28, 95%CI 0.98-1.69). Our findings provide information on the impact of COVID-19 NPIs which may inform public health policies in future health crises, plan effective control and preventative interventions and target resources where needed.

Fama and French Three Factor Model

This study seeks to investigate the application of FF3FM in the Nigerian stock market. The study examined the behaviour of stock returns in relation to market beta, firm size (market equity), and book-to-market equity (BE/ME) factors. Sixty- eight (68) sample size was selected from all stocks quoted on the Nigerian Stock Exchange (NSE) from 2013 to 2022. Time series regression analysis was adopted. Monthly excess portfolio returns were regressed on firm size, excess market returns and book-to-market-equity ratio. The findings showed a strong correlation between book-to-market equity variables, firm size, and excess stock market returns and predicted portfolio returns. This suggests that the variation in stock returns in the Nigerian stock market can be explained by the FF3FM.

Implementation of the 2015 American Thyroid Association guideline changes across a health system: A quality improvement opportunity

BackgroundWith the release of the 2015 management guidelines, the American Thyroid Association narrowed the indications for postoperative radioactive iodine (RAI) in well-differentiated thyroid cancer. However, the adoption of new guidelines varies between healthcare entities. The goal of this study was to characterize the appropriateness of RAI use within our health system, before and after the 2015 guideline changes. MethodsIn this retrospective cohort study, we identified patients who were treated for well-differentiated thyroid cancer between 2011–2020. Patients were characterized as “undertreated,” “appropriately treated,” or “overtreated” with RAI. Variation in RAI use was assessed using interrupted time series and multivariable logistic regression analyses. ResultsAmong 6310 patients, the mean age was 50 ± 15 years, and 74% were female. There was an immediate drop in the likelihood of receiving RAI after the release of the 2015 guidelines (p = 0.016), and the likelihood of receiving RAI therapy continued to significantly decline over time (OR 0.83, p < 0.001). Despite this trend in the absolute rate of RAI use, there was a significant increase in overtreatment with RAI after the release of the 2015 guidelines (p < 0.001), indicating imperfect uptake of the new criteria. Two hospitals within the health system were identified as disproportionate contributors to overtreatment (Hospital 4: OR 6.50, p < 0.001; Hospital 6: OR 8.63, p < 0.001). ConclusionsWhile the use of postoperative RAI was largely appropriate across our health system, rates of guideline adherence differed between hospitals. Efforts to standardize treatment protocols systemwide may enable more rapid and consistent uptake of new management guidelines.

Determinants of Household Savings

The household savings growth in Malaysia has shown a great declining trend annually. The main causes of these deteriorating patterns could have been due to low-income levels, overspending, economic conditions as well as uncertainties that people are facing daily. In deliberating this issue further, this study has empirically examined factors affecting household savings in Malaysia. The analysis was based on time-series data gathered from World Bank Data and the Department of Statistics of Malaysia from 1970 until 2020. The time series regression analysis was used to examine the significant influence on the dependent variable, savings, by independent variables, which consist of income level, interest rate, and money supply. The findings from this study revealed that income level and money supply have significant positive influences on savings, while interest rate has an insignificant influence on savings. Through these findings, policymakers have to formulate a suitable policy that can cushion the impact of macroeconomic variables on the level of savings in the country.