Predicting COVID-19 new cases in California with Google Trends data and a machine learning approach.

Background: Google Trends data can be a valuable source of information for health-related issues such as predicting infectious disease trends.

Objectives: To evaluate the accuracy of predicting COVID-19 new cases in California using Google Trends data, we develop and use a GMDH-type neural network model and compare its performance with a LTSM model.

Methods: We predicted COVID-19 new cases using Google query data over three periods.

Association of social vulnerability and influenza vaccination rates for Annual Medicare Enrollees at the county-level in the United States.

Introduction: Influenza is a preventable acute respiratory illness with a high potential to cause serious complications and is associated with high mortality and morbidity in the US. We aimed to determine the specific community-level vulnerabilities for different race/ethnic communities that are most predictive of influenza vaccination rates.

Methods: We conducted a machine learning analysis (XGBoost) to identify community-level social vulnerability features that are predictive of influenza vaccination rates among Medicare enrollees across counties in the US and by race/ethnicity.

Body image dissatisfaction among school children in Turkey and its potential effect on body esteem.

Background: This study aimed to validate the Turkish version of Collins` Body Figure Perceptions and Preferences (BFPP) scale. The second aim of this study was to investigate the relationship between body image dissatisfaction (BID) and body esteem (BE), and between body mass index (BMI) and BID, among Turkish children.

Methods: A descriptive cross-sectional study was conducted among 2066 4th grade children (mean age was 10.

Predicting mobility using limited data during early stages of a pandemic.

The COVID-19 pandemic has changed consumer behavior substantially. In this study, we explore the drivers of consumer mobility in several metropolitan areas in the United States under the perceived risks of COVID-19. We capture multiple dimensions of perceived risk using local and national cases and death counts of COVID-19, along with real-time Google Trends data for personal protective equipment (PPE).

Structural equation model of physical activity in Turkish schoolchildren: an application of the integrated behavioural model.

Objectives: Childhood obesity is increasingly prevalent in the developing world including Turkey. This study examined constructs of the integrated behavioural model associated with physical activity in a sample of schoolchildren in Ankara, Turkey using structural equation modelling.

Design: Cross-sectional survey by probability sampling.

A decision analytic approach for social distancing policies during early stages of COVID-19 pandemic.

The COVID-19 pandemic has become a crucial public health problem in the world that disrupted the lives of millions in many countries including the United States. In this study, we present a decision analytic approach which is an efficient tool to assess the effectiveness of early social distancing measures in communities with different population characteristics. First, we empirically estimate the reproduction numbers for two different states.

Impact of Florida's prescription drug monitoring program on drug- related fatal vehicle crashes: a difference-in-differences approach.

Background: Prescription drug use has soared in the USA within the last two decades. Prescription drugs can impair motor skills essential for the safe operation of a motor vehicle, and therefore can affect traffic safety. As one of the epicentres of the opioid epidemic, Florida has been struck by high opioid misuse and overdose rates, and has concurrently suffered major threats to traffic disruptions safety caused by driving under the influence of drugs.

The importance of widespread testing for COVID-19 pandemic: systems thinking for drive-through testing sites.

On 11 March 2020, the World Health Organisation (WHO) declared COVID-19 a pandemic. Early epidemiological estimates show that COVID-19 is highly transmissible, infecting populations across the globe in a short amount of time. WHO has recommended widespread clinical testing in order to contain COVID-19.

The validity and reliability of the Turkish version of the Body Esteem Scale for Adolescents and Adults (BESAA) for children.

Background/aim: Body esteem (BE) is defined as the self-evaluation of one’s own body or appearance. The Body Esteem Scale for Adolescents and Adults (BESAA)consists of three subscales: BE-appearance, BE-weight, and BE-attribution. Though initially developed for adolescents and adults, the use of the scale has recently increased in health-related research on children.

Prevalence of childhood obesity and related parental factors across socioeconomic strata in Ankara, Turkey.

Background: Among low- and middle-income nations, the highest prevalence of child overweight and associated metabolic disorders has been found in Middle Eastern and Eastern European countries. Obesity has been on the rise in Turkey and past research has shown regional variations among adults. However, the prevalence of childhood obesity in different socioeconomic groups in the largest metropolitan areas in the country has not been reported.

Dynamic Empirically Based Model for Understanding Future Trends in US Obesity Prevalence in the Context of Social Influences.

Objective: This study aimed to (1) identify mechanistic model structures that produced quality fit to historic obesity prevalence trends and (2) evaluate the sensitivity of future obesity prevalence to social transmission and nonsocial parameters.

Methods: An age- and gender-structured compartmental model was used to describe transitions between weight status groups. Four model structures with different combinations of social transmission and nonsocial mechanisms were calibrated to match historic time series and assessed for quality of fit.

Perceptions of Obesity Prevention Policies: Socioeconomic Assessment in the Turkish Capital.

Purpose: The purpose of this study was to inform public policy opportunities to reduce childhood obesity by identifying parents' perceptions of factors contributing to childhood obesity, attribution of responsibility, and the extent of their support for public prevention policies with attention to socio-economic status.

Design And Methods: In 2015, 2066 parent-child dyads across socio-economic strata from 43 randomly selected schools in Ankara completed surveys and measurements to examine perceptions, attribution, and prevention policies related to childhood obesity.

Results: Parents across the socio-demographic spectrum recognized obesity as a serious problem.

Assessing the validity and reliability of family factors on physical activity: A case study in Turkey.

Background: Childhood obesity rates have been rising rapidly in developing countries. A better understanding of the risk factors and social context is necessary to inform public health interventions and policies. This paper describes the validation of several measurement scales for use in Turkey, which relate to child and parent perceptions of physical activity (PA) and enablers and barriers of physical activity in the home environment.

Stockpiling Ventilators for Influenza Pandemics.

In preparing for influenza pandemics, public health agencies stockpile critical medical resources. Determining appropriate quantities and locations for such resources can be challenging, given the considerable uncertainty in the timing and severity of future pandemics. We introduce a method for optimizing stockpiles of mechanical ventilators, which are critical for treating hospitalized influenza patients in respiratory failure.

Social Networking in an Agricultural Research Center: Using Data to Enhance Outcomes.

The purpose of this article is to present a case study of one midwestern Agricultural Center (Ag Center) that used social network analysis (SNA) to (1) evaluate its collaborations with extramural stakeholders and (2) strategically plan for extending outreach for goal achievement. An evaluation team developed a data collection instrument based on SNA principles. It was administered to the Ag Center's intramural stakeholders (N = 9), who were asked to identify the key extramural stakeholders with whom they had collaborated within the previous 12 months.

The Association of Gasoline Prices With Hospital Utilization and Costs for Motorcycle and Nonmotorcycle Motor Vehicle Injuries in the United States.

Objectives: This study examined the association between gasoline prices and hospitalizations for motorcycle and nonmotorcycle motor vehicle crash (MVC) injuries.

Methods: Data on inpatient hospitalizations were obtained from the 2001 to 2010 Nationwide Inpatient Sample. Panel feasible generalized least squares models were used to estimate the effects of monthly inflation-adjusted gasoline prices on hospitalization rates for MVC injuries and to predict the impact of increasing gasoline taxes.

A decision support tool to determine cost-to-benefit of a family-centered in-home program for at-risk adolescents.

Family-centered program research has demonstrated its effectiveness in improving adolescent outcomes. However, given current fiscal constraints faced by governmental agencies, a recent report from the Institute of Medicine and National Research Council highlighted the need for cost-benefit analyses to inform decision making by policymakers. Furthermore, performance management tools such as balanced scorecards and dashboards do not generally include cost-benefit analyses.

Community-Engaged Public Health Research to Inform Hospital Campus Planning in a Low Socioeconomic Status Urban Neighborhood.

Objective: To compare sociodemographic and motivational factors for healthcare use and identify desirable health-promoting resources among groups in a low socioeconomic status (SES) community in Chicago, IL.

Background: Disparities in health services and outcomes are well established in low SES urban neighborhoods in the United States and many factors beyond service availability and quality impact community health. Yet there is no clear process for engaging communities in building resources to improve population-level health in such locales.

Using Google Flu Trends data in forecasting influenza-like-illness related ED visits in Omaha, Nebraska.

Introduction: Emergency department (ED) visits increase during the influenza seasons. It is essential to identify statistically significant correlates in order to develop an accurate forecasting model for ED visits. Forecasting influenza-like-illness (ILI)-related ED visits can significantly help in developing robust resource management strategies at the EDs.

Share of mass transit miles traveled and reduced motor vehicle fatalities in major cities of the United States.

The USA leads the developed world in motor vehicle fatalities, presenting a critical public health threat. We examined whether an increasing share of mass transit use, relative to vehicle miles traveled on public roads, was associated with reduced motor vehicle fatalities. We used annual city-level data for the USA from 1982-2010 provided by the Fatality Accident Reporting System, the Texas A&M Transportation Institute, the Census Bureau, and the National Oceanic and Atmospheric Administration to estimate a structural equation model of the factors associated with mass transit miles and motor vehicle fatalities.

Modeling social transmission dynamics of unhealthy behaviors for evaluating prevention and treatment interventions on childhood obesity.

Research evidence indicates that obesity has spread through social networks, but lever points for interventions based on overlapping networks are not well studied. The objective of our research was to construct and parameterize a system dynamics model of the social transmission of behaviors through adult and youth influence in order to explore hypotheses and identify plausible lever points for future childhood obesity intervention research. Our objectives were: (1) to assess the sensitivity of childhood overweight and obesity prevalence to peer and adult social transmission rates, and (2) to test the effect of combinations of prevention and treatment interventions on the prevalence of childhood overweight and obesity.

Simulating school closure policies for cost effective pandemic decision making.

Background: Around the globe, school closures were used sporadically to mitigate the 2009 H1N1 influenza pandemic. However, such closures can detrimentally impact economic and social life.

Methods: Here, we couple a decision analytic approach with a mathematical model of influenza transmission to estimate the impact of school closures in terms of epidemiological and cost effectiveness.

Geographic prioritization of distributing pandemic influenza vaccines.

Pandemic influenza is an international public health concern. In light of the persistent threat of H5N1 avian influenza and the recent pandemic of A/H1N1swine influenza outbreak, public health agencies around the globe are continuously revising their preparedness plans. The A/H1N1 pandemic of 2009 demonstrated that influenza activity and severity might vary considerably among age groups and locations, and the distribution of an effective influenza vaccine may be significantly delayed and staggered.

A new method of exercising pandemic preparedness through an interactive simulation and visualization.

As seen in the spring 2009 A/H1N1 influenza outbreak, influenza pandemics can have profound social, legal and economic effects. This experience has also made the importance of public health preparedness exercises more evident. Universities face unique challenges with respect to pandemic preparedness due to their dense student populations, location within the larger community and frequent student/faculty international travel.