Impact on Nonfirearm Deaths of Firearm Laws Affecting Firearm Deaths: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 110 (10) ◽  
pp. e1-e9
Author(s):  
Rosanna Smart ◽  
Terry L. Schell ◽  
Matthew Cefalu ◽  
Andrew R. Morral

Background. There is debate whether policies that reduce firearm suicides or homicides are offset by increases in non–firearm-related deaths. Objectives. To assess the extent to which changes in firearm homicides and suicides following implementation of various gun laws affect nonfirearm homicides and suicides. Search Methods. We performed a literature search on 13 databases for studies published between 1995 and October 31, 2018 (PROSPERO CRD42019120105). Selection Criteria. We included studies if they (1) estimated an effect of 1 of 18 included classes of gun policy on firearm homicides or suicides, (2) included a control group or comparison group and evaluated time series data to establish that policies preceded their purported effects, and (3) provided estimated effects of the policy and inferential statistics for either total or nonfirearm homicides or suicides. Data Collection and Analysis. We extracted data from each study, including study timeframe, population, and statistical methods, as well as point estimates and inferential statistics for the effects of firearm policies on firearm deaths as well as either nonfirearm or overall deaths. We assessed quality at the estimate (study–policy–outcome) level by using prespecified criteria to evaluate the validity of inference and causal identification. For each estimate, we derived the mortality multiplier (i.e., the ratio of the policy’s effect on total homicides or suicides; expressed as a change in the number of deaths) as a proportion of its effect on firearm homicides or suicides. Finally, we performed a meta-analysis to estimate overall mortality multipliers for suicide and homicide that account for both within- and between-study heterogeneity. Main Results. We identified 16 eligible studies (study timeframes spanning 1977–2015). All examined state-level policies in the United States, with most estimating effects of multiple policies, yielding 60 separate estimates of the mortality multiplier. From these, we estimated that a firearm law’s effect on homicide, expressed as a change in the number of total homicide deaths, is 0.99 (95% confidence interval = 0.76, 1.22) times its effect on the number of firearm homicides. Thus, on average, changes in the number of firearm homicides caused by gun policies are neither offset nor compounded by second-order effects on nonfirearm homicides. There is insufficient evidence in the existing literature on suicide to indicate the extent to which the effects of gun policy changes on firearm suicides are offset or compounded by their effects on nonfirearm suicides. Authors’ Conclusions. State gun policies that reduce firearm homicides are likely to reduce overall homicides in the state by approximately the same number. It is currently unknown whether the same holds for state gun policies that significantly reduce firearm suicides. The small number of studies meeting our inclusion criteria, issues of methodological quality within those studies, and the possibility of reporting bias are potential limitations of this review. Public Health Implications. Policies that reduce firearm homicides likely have large benefits for public health as there is little evidence to support a strong substitution effect between firearm and nonfirearm homicides at the population level. Further research is needed to determine whether policies that produce population-level reductions in firearm suicides will translate to overall declines in suicide rates.

2021 ◽  
Author(s):  
Meshrif Alruily ◽  
Mohamed Ezz ◽  
Ayman Mohamed Mostafa ◽  
Nacim Yanes ◽  
Mostafa Abbas ◽  
...  

ABSTRACTAccurate forecasting of emerging infectious diseases can guide public health officials in making appropriate decisions related to the allocation of public health resources. Due to the exponential spread of the COVID-19 infection worldwide, several computational models for forecasting the transmission and mortality rates of COVID-19 have been proposed in the literature. To accelerate scientific and public health insights into the spread and impact of COVID-19, Google released the Google COVID-19 search trends symptoms open-access dataset. Our objective is to develop 7 and 14 -day-ahead forecasting models of COVID-19 transmission and mortality in the US using the Google search trends for COVID-19 related symptoms. Specifically, we propose a stacked long short-term memory (SLSTM) architecture for predicting COVID-19 confirmed and death cases using historical time series data combined with auxiliary time series data from the Google COVID-19 search trends symptoms dataset. Considering the SLSTM networks trained using historical data only as the base models, our base models for 7 and 14 -day-ahead forecasting of COVID cases had the mean absolute percentage error (MAPE) values of 6.6% and 8.8%, respectively. On the other side, our proposed models had improved MAPE values of 3.2% and 5.6%, respectively. For 7 and 14 -day-ahead forecasting of COVID-19 deaths, the MAPE values of the base models were 4.8% and 11.4%, while the improved MAPE values of our proposed models were 4.7% and 7.8%, respectively. We found that the Google search trends for “pneumonia,” “shortness of breath,” and “fever” are the most informative search trends for predicting COVID-19 transmission. We also found that the search trends for “hypoxia” and “fever” were the most informative trends for forecasting COVID-19 mortality.


Author(s):  
Rizki Rahma Kusumadewi ◽  
Wahyu Widayat

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.


Author(s):  
Jennifer D. Allen ◽  
Rachel C. Shelton ◽  
Karen M. Emmons ◽  
Laura A. Linnan

There is substantial variability in the implementation of evidence-based interventions across the United States, which leads to inconsistent access to evidence-based prevention and treatment strategies at a population level. Increased dissemination and implementation of evidence-based interventions could result in significant public health gains. While the availability of evidence-based interventions is increasing, study of implementation, adaptation, and dissemination has only recently gained attention in public health. To date, insufficient attention has been given to the issue of fidelity. Consideration of fidelity is necessary to balance the need for internal and external validity across the research continuum. There is also a need for a more robust literature to increase knowledge about factors that influence fidelity, strategies for maximizing fidelity, methods for measuring and analyzing fidelity, and examining sources of variability in implementation fidelity.


2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Takuya Ibara ◽  
Masaya Anan ◽  
Ryosuke Karashima ◽  
Kiyotaka Hada ◽  
Koichi Shinkoda ◽  
...  

There are limited reports on segment movement and their coordination pattern during gait in patients with hip osteoarthritis. To avoid the excessive stress toward the hip and relevant joints, it is important to investigate the coordination pattern between these segment movements, focusing on the time series data. This study aimed to quantify the coordination pattern of lumbar, pelvic, and thigh movements during gait in patients with hip osteoarthritis and in a control group. An inertial measurement unit was used to measure the lumbar, pelvic, and thigh angular velocities during gait of 11 patients with hip osteoarthritis and 11 controls. The vector coding technique was applied, and the coupling angle and the appearance rate of coordination pattern in each direction were calculated and compared with the control group. Compared with the control group, with respect to the lumbar/pelvic segment movements, the patients with hip osteoarthritis spent more rates in anti-phase and lower rates in in-phase lateral tilt movement. With respect to the pelvic/thigh segment movements, the patients with hip osteoarthritis spent more rates within the proximal- and in-phases for lateral tilt movement. Furthermore, patients with osteoarthritis spent lower rates in the distal-phase for anterior/posterior tilt and rotational movement. Patients with hip osteoarthritis could not move their pelvic and thigh segments separately, which indicates the stiffness of the hip joint. The rotational movement and lateral tilt movements, especially, were limited, which is known as Duchenne limp. To maintain the gait ability, it seems important to pay attention to these directional movements.


Author(s):  
Mostafa Abbas ◽  
Thomas B. Morland ◽  
Eric S. Hall ◽  
Yasser EL-Manzalawy

We utilize functional data analysis techniques to investigate patterns of COVID-19 positivity and mortality in the US and their associations with Google search trends for COVID-19-related symptoms. Specifically, we represent state-level time series data for COVID-19 and Google search trends for symptoms as smoothed functional curves. Given these functional data, we explore the modes of variation in the data using functional principal component analysis (FPCA). We also apply functional clustering analysis to identify patterns of COVID-19 confirmed case and death trajectories across the US. Moreover, we quantify the associations between Google COVID-19 search trends for symptoms and COVID-19 confirmed case and death trajectories using dynamic correlation. Finally, we examine the dynamics of correlations for the top nine Google search trends of symptoms commonly associated with COVID-19 confirmed case and death trajectories. Our results reveal and characterize distinct patterns for COVID-19 spread and mortality across the US. The dynamics of these correlations suggest the feasibility of using Google queries to forecast COVID-19 cases and mortality for up to three weeks in advance. Our results and analysis framework set the stage for the development of predictive models for forecasting COVID-19 confirmed cases and deaths using historical data and Google search trends for nine symptoms associated with both outcomes.


2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S843-S843
Author(s):  
John M McLaughlin ◽  
Farid L Khan ◽  
Heinz-Josef Schmitt ◽  
Yasmeen Agosti ◽  
Luis Jodar ◽  
...  

Abstract Background Understanding the true magnitude of infant respiratory syncytial virus (RSV) burden is critical for determining the potential public-health benefit of RSV prevention strategies. Although global reviews of infant RSV burden exist, none have summarized data from the United States or evaluated how RSV burden estimates are influenced by variations in study design. Methods We performed a systematic literature review and meta-analysis of studies describing RSV-associated hospitalization rates among US infants. We also examined the impact of key study characteristics on these estimates. Results After review of 3058 articles through January 2020, we identified 25 studies with 31 unique estimates of RSV-associated hospitalization rates. Among US infants < 1 year of age, annual rates ranged from 8.4 to 40.8 per 1000 with a pooled rate= 19.4 (95%CI= 17.9–20.9). Study type was associated with RSV hospitalization rates (P =.003), with active surveillance studies having pooled rates per 1000 (11.1; 95%CI: 9.8–12.3) that were half that of studies based on administrative claims (21.4; 95%CI: 19.5–23.3) or modeling approaches (23.2; 95%CI: 20.2–26.2). Conclusion Applying the pooled rates identified in our review to the 2020 US birth cohort suggests that 73,680 to 86,020 RSV-associated infant hospitalizations occur each year. To date, public-health officials have used conservative estimates from active surveillance as the basis for defining US infant RSV burden. The full range of RSV-associated hospitalization rates identified in our review better characterizes the true RSV burden in infants and can better inform future evaluations of RSV prevention strategies. Disclosures John M. McLaughlin, PhD, Pfizer (Employee, Shareholder) Farid L. Khan, MPH, Pfizer (Employee, Shareholder) Heinz-Josef Schmitt, MD, Pfizer (Employee, Shareholder) Yasmeen Agosti, MD, Pfizer (Employee, Shareholder) Luis Jodar, PhD, Pfizer (Employee, Shareholder) Eric Simões, MD, Pfizer (Consultant, Research Grant or Support) David L. Swerdlow, MD, Pfizer (Employee, Shareholder)


2011 ◽  
Vol 44 (23) ◽  
pp. 2955-2968 ◽  
Author(s):  
Fabrizio Iacone ◽  
Steve Martin ◽  
Luigi Siciliani ◽  
Peter C. Smith

2020 ◽  
Author(s):  
Peter Turchin ◽  
Andrey Korotayev

This article revisits the prediction, made in 2010, that the 2010–2020 decade would likely be a period of growing instability in the United States and Western Europe (Turchin 2010). This prediction was based on a computational model that quantified in the USA such structural-demographic forces for instability as popular immiseration, intraelite competition, and state weakness prior to 2010. Using these trends as inputs, the model calculated and projected forward in time the Political Stress Index, which in the past was strongly correlated with socio-political instability. Ortmans et al. (2017) conducted a similar structural-demographic study for the United Kingdom and obtained similar results. Here we use the Cross-National Time-Series Data Archive for the US, UK, and Western European countries to assess these structural-demographic predictions. We find that such measures of socio-political instability as anti-government demonstrations and riots increased dramatically during the 2010–2020 decade in all of these countries.


2021 ◽  
pp. 089976402110574
Author(s):  
Lauren Dula

Representative bureaucracy theory posits that the passive representation of women in leadership positions will lead to active representation of the concerns of women in general. This article attempts to identify whether this theory plays out on boards of nonprofit funding organizations, specifically United Ways across the United States. Using random effects modeling of interrupted time series data covering 15 years, the findings suggest a small yet significant nonlinear effect of women in leadership positions on boards upon the size of funding for women- and girl-serving organizations. This partially supports representative bureaucracy theory, but raises questions as to why there is a negative representational effect past a certain “critical mass” of women.


Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Shaker M Eid ◽  
Aiham Albaeni ◽  
Rebeca Rios ◽  
May Baydoun ◽  
Bolanle Akinyele ◽  
...  

Background: The intent of the 5-yearly Resuscitation Guidelines is to improve outcomes. Previous studies have yielded conflicting reports of a beneficial impact of the 2005 guidelines on out-of-hospital cardiac arrest (OHCA) survival. Using a national database, we examined survival before and after the introduction of both the 2005 and 2010 guidelines. Methods: We used the 2000 through 2012 National Inpatient Sample database to select patients ≥18 years admitted to hospitals in the United States with non-traumatic OHCA (ICD-9 CM codes 427.5 & 427.41). A quasi-experimental (interrupted time series) design was used to compare monthly survival trends. Outcomes for OHCA were compared pre- and post- 2005 and 2010 resuscitation guidelines release as follows: 01/2000-09/2005 vs. 10/2005-9/2010 and 10/2005-9/2010 vs. 10/2010-12/2012. Segmented regression analyses of interrupted time series data were performed to examine changes in survival to hospital discharge. Results: For the pre- and post- guidelines periods, 81600, 69139 and 36556 patients respectively survived to hospital admission following OHCA. Subsequent to the release of the 2005 guidelines, there was a statistically significant worsening in survival trends (β= -0.089, 95% CI -0.163 – -0.016, p =0.018) until the release of the 2010 guidelines when a sharp increase in survival was noted which persisted for the period of study (β= 0.054, 95% CI -0.143 – 0.251, p =0.588) but did not achieve statistical significance (Figure). Conclusion: National clinical guidelines developed to impact outcomes must include mechanisms to assess whether benefit actually occurs. The worsening in OHCA survival following the 2005 guidelines is thought provoking but the improvement following the release of the 2010 guidelines is reassuring and worthy of perpetuation.


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