Dataset Information

Internet search patterns reveal firearm sales, policies, and deaths.

ABSTRACT: Firearm-related violence is a leading cause of morbidity and mortality and is at the center of a major public health and policy debate in the United States. Despite the critical role of data in informing this debate, accurate and comprehensive data on firearm sales and ownership is not readily available. In this study, we evaluate the potential of using firearm-related internet search queries as a complementary, freely available, and near-real-time data source for tracking firearm sales and ownership that enables analysis at finer geographic and temporal scales. (Here, we examine data by state and by month to compare with other data sources, but search engine volume can be analyzed by city and by the week or by day). We validate search query volume against available data on background checks in all 50 US states, and find that they are highly correlated over time (Pearson's r?=?0.96, Spearman's ??=?0.94) and space (Pearson's r?=?0.78, Spearman's ??=?0.76). We find that stratifying this analysis by gun type (long-gun vs. handgun) increases this correlation dramatically, across both time and space. We also find a positive association between firearm-related search query volume and firearm-related mortality (Pearson's r?=?0.87, Spearman's ??=?0.90), and a negative association with the strength of state-level firearm control policies (Pearson's r?=?-0.82, Spearman's ??=?-0.83). Based on these findings, we propose a framework for prospective surveillance that incorporates firearm-related internet search volume as a useful complementary data source to inform the public health policy debate on this issue.

SUBMITTER: Brownstein JS

PROVIDER: S-EPMC7679459 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Internet search patterns reveal firearm sales, policies, and deaths.

Brownstein John S JS Nahari Adam D AD Reis Ben Y BY

NPJ digital medicine 20201120 1

Firearm-related violence is a leading cause of morbidity and mortality and is at the center of a major public health and policy debate in the United States. Despite the critical role of data in informing this debate, accurate and comprehensive data on firearm sales and ownership is not readily available. In this study, we evaluate the potential of using firearm-related internet search queries as a complementary, freely available, and near-real-time data source for tracking firearm sales and owne ...[more]

PMID: 33299072

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Project description:Despite high social and public health costs of firearm violence in the United States, the effects of many policies designed to reduce firearm mortality remain uncertain. To estimate the individual and joint effect sizes of state firearm policies on firearm-related mortality. In this comparative effectiveness study, bayesian methods were used to model panel data of annual, state-level mortality rates (1979-2019) for all US firearm decedents, with analyses conducted in October 2023. Six classes of firearms policies: background checks, minimum age, waiting periods, child access, concealed carry, and stand-your-ground laws. Primary outcomes (total firearm deaths, firearm homicide deaths, and firearm suicide deaths) were assessed using the National Vital Statistics System. Bayesian estimation was used to estimate the partial association of changes in firearms policies with subsequent changes in firearm mortality. The estimated effect sizes of individual policies 5 or more years after implementation were generally small in magnitude and had considerable uncertainty. The policy class with the highest probability of reducing firearm deaths was child-access prevention laws, estimated to reduce overall firearm mortality by 6% (80% credible interval [CrI], -2% to -9%). The policy class with the highest probability of increasing firearm deaths was stand-your-ground laws, estimated to increase firearm homicides by 6% (80% CrI, 0% to 13% increase). Estimates of association of implementing multiple firearm restrictions with subsequent changes in firearm mortality yielded larger effect sizes. Moving from the most permissive to most restrictive set of firearm policies was associated with an estimated 20% reduction in firearm deaths (80% CrI, 10% to 28% reduction), with a 0.99 probability of any reductions in firearm death rates. In this comparative effectiveness study of state firearm policies, the joint effect estimates of combinations of firearm laws were calculated, showing that restrictive firearm policies were associated with substantial reductions in firearm mortality. Although policymakers would benefit from knowing the effects of individual policies, the estimated changes in firearm mortality following implementation of individual policies were often small and uncertain.

Project description:BackgroundThe prevalence of chronic conditions such as obesity, hypertension, and diabetes is increasing in African countries. Many chronic diseases have been linked to risk factors such as poor diet and physical inactivity. Data for these behavioral risk factors are usually obtained from surveys, which can be delayed by years. Behavioral data from digital sources, including social media and search engines, could be used for timely monitoring of behavioral risk factors.ObjectiveThe objective of our study was to propose the use of digital data from internet sources for monitoring changes in behavioral risk factors in Africa.MethodsWe obtained the adjusted volume of search queries submitted to Google for 108 terms related to diet, exercise, and disease from 2010 to 2016. We also obtained the obesity and overweight prevalence for 52 African countries from the World Health Organization (WHO) for the same period. Machine learning algorithms (ie, random forest, support vector machine, Bayes generalized linear model, gradient boosting, and an ensemble of the individual methods) were used to identify search terms and patterns that correlate with changes in obesity and overweight prevalence across Africa. Out-of-sample predictions were used to assess and validate the model performance.ResultsThe study included 52 African countries. In 2016, the WHO reported an overweight prevalence ranging from 20.9% (95% credible interval [CI] 17.1%-25.0%) to 66.8% (95% CI 62.4%-71.0%) and an obesity prevalence ranging from 4.5% (95% CI 2.9%-6.5%) to 32.5% (95% CI 27.2%-38.1%) in Africa. The highest obesity and overweight prevalence were noted in the northern and southern regions. Google searches for diet-, exercise-, and obesity-related terms explained 97.3% (root-mean-square error [RMSE] 1.15) of the variation in obesity prevalence across all 52 countries. Similarly, the search data explained 96.6% (RMSE 2.26) of the variation in the overweight prevalence. The search terms yoga, exercise, and gym were most correlated with changes in obesity and overweight prevalence in countries with the highest prevalence.ConclusionsInformation-seeking patterns for diet- and exercise-related terms could indicate changes in attitudes toward and engagement in risk factors or healthy behaviors. These trends could capture population changes in risk factor prevalence, inform digital and physical interventions, and supplement official data from surveys.

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Internet search patterns reveal firearm sales, policies, and deaths.

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Internet search patterns reveal firearm sales, policies, and deaths.

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