scholarly journals Evaluating the Health Impact of Large-Scale Public Policy Changes: Classical and Novel Approaches

2017 ◽  
Vol 38 (1) ◽  
pp. 351-370 ◽  
Author(s):  
Sanjay Basu ◽  
Ankita Meghani ◽  
Arjumand Siddiqi
Keyword(s):  
Public Health ◽  
Public Policy ◽  
Large Scale ◽  
Health Impact ◽  
Synthetic Control ◽  
Policy Changes ◽  
Difference In Differences ◽  
Policy Effect ◽  
Tobacco Taxes ◽  
Poverty Relief

Large-scale public policy changes are often recommended to improve public health. Despite varying widely—from tobacco taxes to poverty-relief programs—such policies present a common dilemma to public health researchers: how to evaluate their health effects when randomized controlled trials are not possible. Here, we review the state of knowledge and experience of public health researchers who rigorously evaluate the health consequences of large-scale public policy changes. We organize our discussion by detailing approaches to address three common challenges of conducting policy evaluations: distinguishing a policy effect from time trends in health outcomes or preexisting differences between policy-affected and -unaffected communities (using difference-in-differences approaches); constructing a comparison population when a policy affects a population for whom a well-matched comparator is not immediately available (using propensity score or synthetic control approaches); and addressing unobserved confounders by utilizing quasi-random variations in policy exposure (using regression discontinuity, instrumental variables, or near-far matching approaches).

Impact of nations meeting the MPOWER targets between 2014 and 2016: an update

2019 ◽  
pp. tobaccocontrol-2018-054837 ◽  
Author(s):  
David T Levy ◽  
Yameng Li ◽  
Zhe Yuan
Keyword(s):  
Tobacco Control ◽  
Tobacco Use ◽  
Health Impact ◽  
Health Warnings ◽  
Control Policies ◽  
The Public ◽  
Policy Effect ◽  
Tobacco Taxes ◽  
Tobacco Control Policies ◽  
Free Air

ObjectiveSince the WHO released the Monitoring tobacco use and tobacco control policies; Protecting from the dangers of tobacco smoke; Offering help to quit tobacco; Warning the public about the dangers; Enforcing bans on advertising, promotion and sponsorship; and Raising tobacco taxes (MPOWER) policy package to assist nations with implementing the Framework Convention on Tobacco Control (FCTC), 88 countries have adopted at least one MPOWER policy at the highest level as of 2014. Building on previous evaluations, we estimated the reduction in smoking-attributable deaths (SADs) from all policies newly adopted at the highest level between 2014 and 2016.MethodsFor each nation that implemented highest level policies, the difference in policy effect sizes from previously validated SimSmoke models for the policies in effect in 2014 and 2016 were multiplied by the number of smokers in that nation to derive the reduction in the number of smokers. Based on research that half of all smokers die from smoking, we derived SADs averted.FindingsIn total, 43 nations adopted at least one highest-level MPOWER policy between 2014 and 2016, resulting in 14.6 million fewer SADs. The largest number of SADs averted were due to stronger health warnings (13.3 million), followed by raising taxes (0.6 million), increased marketing bans (0.4 million), smoke-free air laws (0.3 million) and cessation interventions (2500).ConclusionThese findings demonstrate the continuing public health impact of tobacco control policies adopted globally since the FCTC, and highlight the importance of more countries adopting MPOWER policies at the highest level to reduce the global burden of tobacco use.

Results of Rapid Needs Assessments in Rural and Urban Iowa Following Large-scale Flooding Events in 2008

2011 ◽  
Vol 5 (4) ◽  
pp. 287-292 ◽  
Author(s):  
Patricia Quinlisk ◽  
Mary J. Jones ◽  
Nathan A. Bostick ◽  
Lauren E. Walsh ◽  
Rebecca Curtiss ◽  
...  
Keyword(s):  
Public Health ◽  
Needs Assessment ◽  
Large Scale ◽  
Health Impact ◽  
Cluster Sampling ◽  
Future Health ◽  
Human Needs ◽  
Needs Assessments ◽  
Acute Injuries ◽  
Ongoing Surveillance

ABSTRACTBackground: On June 8 and 9, 2008, more than 4 inches of rain fell in the Iowa-Cedars River Basin causing widespread flooding along the Cedar River in Benton, Linn, Johnson, and Cedar Counties. As a result of the flooding, there were 18 deaths, 106 injuries, and over 38 000 people displaced from their homes; this made it necessary for the Iowa Department of Health to conduct a rapid needs assessment to quantify the scope and effect of the floods on human health.Methods: In response, the Iowa Department of Public Health mobilized interview teams to conduct rapid needs assessments using Geographic Information Systems (GIS)-based cluster sampling techniques. The information gathered was subsequently employed to estimate the public health impact and significant human needs that resulted from the flooding.Results: While these assessments did not reveal significant levels of acute injuries resulting from the flood, they did show that many households had been temporarily displaced and that future health risks may emerge as the result of inadequate access to prescription medications or the presence of environmental health hazards.Conclusions: This exercise highlights the need for improved risk communication measures and ongoing surveillance and relief measures. It also demonstrates the utility of rapid needs assessment survey tools and suggests that increasing use of such surveys can have significant public health benefits.(Disaster Med Public Health Preparedness. 2011;5:287–292)

scholarly journals Comparing serotyping with whole-genome sequencing for subtyping of non-typhoidal Salmonella enterica: a large-scale analysis of 37 serotypes with a public health impact in the USA

2020 ◽  
Vol 6 (9) ◽  
Author(s):  
Ehud Elnekave ◽  
Samuel L. Hong ◽  
Seunghyun Lim ◽  
Timothy J. Johnson ◽  
Andres Perez ◽  
...  
Keyword(s):  
Public Health ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Large Scale ◽  
Health Impact ◽  
Public Health Impact ◽  
Whole Genome ◽  
Scale Analysis ◽  
Large Scale Analysis ◽  
The Usa

Serotyping has traditionally been used for subtyping of non-typhoidal Salmonella (NTS) isolates. However, its discriminatory power is limited, which impairs its use for epidemiological investigations of source attribution. Whole-genome sequencing (WGS) analysis allows more accurate subtyping of strains. However, because of the relative newness and cost of routine WGS, large-scale studies involving NTS WGS are still rare. We aimed to revisit the big picture of subtyping NTS with a public health impact by using traditional serotyping (i.e. reaction between antisera and surface antigens) and comparing the results with those obtained using WGS. For this purpose, we analysed 18 282 sequences of isolates belonging to 37 serotypes with a public health impact that were recovered in the USA between 2006 and 2017 from multiple sources, and were available at the National Center for Biotechnology Information (NCBI). Phylogenetic trees were reconstructed for each serotype using the core genome for the identification of genetic subpopulations. We demonstrated that WGS-based subtyping allows better identification of sources potentially linked with human infection and emerging subpopulations, along with providing information on the risk of dissemination of plasmids and acquired antimicrobial resistance genes (AARGs). In addition, by reconstructing a phylogenetic tree with representative isolates from all serotypes (n=370), we demonstrated genetic variability within and between serotypes, which formed monophyletic, polyphyletic and paraphyletic clades. Moreover, we found (in the entire data set) an increased detection rate for AARGs linked to key antimicrobials (such as quinolones and extended-spectrum cephalosporins) over time. The outputs of this large-scale analysis reveal new insights into the genetic diversity within and between serotypes; the polyphyly and paraphyly of certain serotypes may suggest that the subtyping of NTS to serotypes may not be sufficient. Moreover, the results and the methods presented here, leading to differentiation between genetic subpopulations based on their potential risk to public health, as well as narrowing down the possible sources of these infections, may be used as a baseline for subtyping of future NTS infections and help efforts to mitigate and prevent infections in the USA and globally.

scholarly journals CDC Surveillance Strategy – A Strategy for Improving CDC Activities in Public Health Surveillance

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Chesley Richards ◽  
Brian Lee
Keyword(s):  
Public Health ◽  
Large Scale ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Policy Changes ◽  
Surveillance Strategy ◽  
The Public ◽  
Public Health Professionals ◽  
Health Surveillance Data ◽  
The Impact

Public health surveillance guides efforts to detect and monitor disease and injuries, assess the impact of interventions and assist in the management of and recovery from large-scale public health incidents. Actions informed by surveillance information take many forms, such as policy changes, new program interventions, public communications and investments in research. Local, state and federal public health professionals, government leaders, public health partners and the public are dependent on high quality, timely and actionable public health surveillance data. This Surveillance Strategy aims to improve overall surveillance capabilities, and by extension those of the public health system at large.

scholarly journals Healthy diet and lifestyle clustering and glucose intolerance

2002 ◽  
Vol 61 (4) ◽  
pp. 543-551 ◽  
Author(s):  
I. J. Perry
Keyword(s):  
Public Health ◽  
Type 2 Diabetes ◽  
Public Policy ◽  
Fatty Acids ◽  
Glucose Intolerance ◽  
Large Scale ◽  
Vigorous Physical Activity ◽  
Overweight And Obesity ◽  
Global Epidemic

Glucose intolerance represents a spectrum of abnormalities, including impaired fasting glucose, impaired glucose tolerance and type 2 diabetes. It is a major public health challenge worldwide, with rapidly increasing prevalence rates in both developed and developing countries. This global epidemic of diabetes is largely driven by the globalisation of Western culture and lifestyles. Specifically, there is now evidence from large-scale observational studies, and from intervention studies, of powerful synergistic interactions between diet, obesity, exercise, smoking and alcohol in the development of glucose intolerance. It is estimated that > 90 % of cases of type 2 diabetes in the population could be prevented with the adoption of a prudent diet (high in cereal fibre and polyunsaturated fatty acids and low in trans-fatty acids and glycaemic load), avoidance of overweight and obesity (BMI < 25 kg/m2), engagement in moderate to vigorous physical activity for at least 05 h/d, non-smoking and moderate alcohol consumption. These findings are biologically plausible and have major public health implications. They form the basis for a clear, simple and coherent message for health promotion and public policy. However, to make progress on these issues health will need to be placed at the centre of public policy and relevant vested interests tackled, notably in the food, entertainment, tobacco and automobile industries.

The Effect of Large-scale Performance-Based Funding in Higher Education

2021 ◽  
Vol 16 (1) ◽  
pp. 92-124 ◽  
Author(s):  
Jason Ward ◽  
Ben Ost
Keyword(s):  
Higher Education ◽  
Large Scale ◽  
Performance Metrics ◽  
State Funding ◽  
Synthetic Control ◽  
Difference In Differences ◽  
Control Approach ◽  
Performance Based Funding ◽  
State Higher Education ◽  
Identification Strategy

The use of performance-based funding that ties state higher education appropriations to performance metrics has increased dramatically in recent years, but most programs place at stake a small percent of overall funding. We analyze the effect of two notable exceptions—Ohio and Tennessee—where nearly all state funding is tied to performance measures. Using a difference-in-differences identification strategy along with a synthetic control approach, we find no evidence that these programs improve key academic outcomes.

scholarly journals Effect of emergency declaration on mental health during the COVID-19 pandemic in Japan: A social network service-based difference-in-differences approach

2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110297
Author(s):  
Akifumi Eguchi ◽  
Daisuke Yoneoka ◽  
Shoi Shi ◽  
Yuta Tanoue ◽  
Takayuki Kawashima ◽  
...  
Keyword(s):  
Mental Health ◽  
Large Scale ◽  
Causal Effect ◽  
Population Level ◽  
Health Impact ◽  
The State ◽  
Difference In Differences ◽  
State Of Emergency ◽  
Psychological Harm ◽  
Reported Data

Strong lockdowns to control COVID-19 pandemic have been enforced globally and strongly restricted social activities with consequent negative effects on mental health. Japan has effectively implemented a unique voluntary policy to control COVID-19, but the mental health impact of the policy has not been examined on a large scale. In this study, we examined the effect of the first declaration on the mental health of affected residents. We used population-level questionnaire data of 17,400 people living under the state of emergency and 9208 who were not through a social-networking-service app and applied a difference-in-differences regression model to estimate the causal effect of the declaration of the state of emergency on psychological wellbeing, stratified by job category. No statistically significant effect of the declaration was observed among all job categories. This suggests that residents’ psychological situation has gradually changed, possibly influenced by other factors such as the surrounding environment, rather than the declaration itself. Given that Japan has a unique policy to control COVID-19 instead of a strict lockdown, our results showed the Japanese-style policy may serve as a form of harm reduction strategy, to control the epidemic with minimal psychological harm, and enable a policy that balances disease control and mental health. Caution is necessary that this study used self-reported data from a limited time period before and after the first declaration in April 2020.

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