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Trends and Prediction in Daily New Cases and Deaths of COVID-19 in the United States: An Internet Search-Interest Based Model.

ABSTRACT: Background and objectives:The daily incidence and deaths of coronavirus disease 2019 (COVID-19) in the USA are poorly understood. Internet search interest was found to be correlated with COVID-19 daily incidence in China, but has not yet been applied to the USA. Therefore, we examined the association of internet search-interest with COVID-19 daily incidence and deaths in the USA. Methods:We extracted COVID-19 daily new cases and deaths in the USA from two population-based datasets, namely 1-point-3-acres.com and the Johns Hopkins COVID-19 data repository. The internet search-interest of COVID-19-related terms was obtained using Google Trends. The Pearson correlation test and general linear model were used to examine correlations and predict trends, respectively. Results:There were 636,282 new cases and,325 deaths of COVID-19 in the USA from March 1 to April 15, 2020, with a crude mortality of 4.45%. The daily new cases peaked at 35,098 cases on April 10, 2020 and the daily deaths peaked at 2,494 on April 15, 2020. The search interest of COVID, "COVID pneumonia" and "COVID heart" were correlated with COVID-19 daily incidence, with 12 or 14 days of delay (Pearson's r = 0.978, 0.978 and 0.979, respectively) and deaths with 19 days of delay (Pearson's r = 0.963, 0.958 and 0.970, respectively). The 7-day follow-up with prospectively collected data showed no significant correlations of the observed data with the predicted daily new cases or daily deaths, using search interest of COVID, COVID heart, and COVID pneumonia. Conclusions:Search terms related to COVID-19 are highly correlated with the COVID-19 daily new cases and deaths in the USA.

SUBMITTER: Yuan X

PROVIDER: S-EPMC7176069 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Trends and Prediction in Daily New Cases and Deaths of COVID-19 in the United States: An Internet Search-Interest Based Model.

Yuan Xiaoling X Xu Jie J Hussain Sabiha S Wang He H Gao Nan N Zhang Lanjing L

Exploratory research and hypothesis in medicine 20200418 2

<h4>Background and objectives</h4>The daily incidence and deaths of coronavirus disease 2019 (COVID-19) in the USA are poorly understood. Internet search interest was found to be correlated with COVID-19 daily incidence in China, but has not yet been applied to the USA. Therefore, we examined the association of internet search-interest with COVID-19 daily incidence and deaths in the USA.<h4>Methods</h4>We extracted COVID-19 daily new cases and deaths in the USA from two population-based datasets ...[more]

PMID: 32348380

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Project description:BackgroundThe COVID-19 pandemic has affected virtually every region in the world. At the time of this study, the number of daily new cases in the United States was greater than that in any other country, and the trend was increasing in most states. Google Trends provides data regarding public interest in various topics during different periods. Analyzing these trends using data mining methods may provide useful insights and observations regarding the COVID-19 outbreak.ObjectiveThe objective of this study is to consider the predictive ability of different search terms not directly related to COVID-19 with regard to the increase of daily cases in the United States. In particular, we are concerned with searches related to dine-in restaurants and bars. Data were obtained from the Google Trends application programming interface and the COVID-19 Tracking Project.MethodsTo test the causation of one time series on another, we used the Granger causality test. We considered the causation of two different search query trends related to dine-in restaurants and bars on daily positive cases in the US states and territories with the 10 highest and 10 lowest numbers of daily new cases of COVID-19. In addition, we used Pearson correlations to measure the linear relationships between different trends.ResultsOur results showed that for states and territories with higher numbers of daily cases, the historical trends in search queries related to bars and restaurants, which mainly occurred after reopening, significantly affected the number of daily new cases on average. California, for example, showed the most searches for restaurants on June 7, 2020; this affected the number of new cases within two weeks after the peak, with a P value of .004 for the Granger causality test.ConclusionsAlthough a limited number of search queries were considered, Google search trends for restaurants and bars showed a significant effect on daily new cases in US states and territories with higher numbers of daily new cases. We showed that these influential search trends can be used to provide additional information for prediction tasks regarding new cases in each region. These predictions can help health care leaders manage and control the impact of the COVID-19 outbreak on society and prepare for its outcomes.

Project description:ImportanceNotable increases in mortality from alcohol-induced causes over the past 2 decades in the United States have been reported. However, comprehensive assessments of trends in alcohol-induced mortality by sex, age, race/ethnicity, and social and geographic factors are lacking.ObjectiveTo examine trends in alcohol-induced mortality rates from 2000 to 2016, comparing results by demographic characteristics including sex, race/ethnicity, age, county-level socioeconomic status, and geographic location.Design, setting, and participantsThis serial cross-sectional study used US national vital statistics data for years 2000 to 2016 for all US residents older than 15 years. Data analysis was conducted from January to September 2019.ExposuresTrends in alcohol-induced mortality by sex, race/ethnicity, age, county-level socioeconomic status (ie, median income, percentage of unemployed residents, percentage of residents with a bachelor's degree), rurality level, and US state.Main outcomes and measuresAlcohol-induced mortality, ie, deaths for which alcohol holds a population-attributable fraction of 1. Deaths were expressed per 100 000 residents as absolute and age-standardized rates. Mortality trends were measured as average annual percentage changes (AAPCs) for the entire period (ie, 2000-2016) and annual percentage changes (APCs) for individual periods of change within the study period.ResultsA total of 425 045 alcohol-induced deaths were identified from 2000 to 2016 (2000: 19 627 deaths; 14 979 [76.3%] men; 2016: 34 857 deaths; 25 213 [73.3%] men). The rate of alcohol-induced deaths increased substantially among men (AAPC, 1.4%; 95% CI, 1.0% to 1.8%) and women (AAPC, 3.1%; 95% CI, 2.6% to 3.6%) and accelerated recently (men, 2012-2016: APC, 4.2%; 95% CI, 3.1% to 5.3%; women, 2013-2016: APC, 7.1%; 95% CI, 5.1% to 9.1%). The largest increases by race/ethnicity were observed among American Indian and Alaska Native men (AAPC, 3.3%; 95% CI, 2.6% to 4.0%), American Indian and Alaska Native women (AAPC, 4.2%; 95% CI, 3.8% to 4.6%), and white women (AAPC, 4.1%; 95% CI, 3.6% to 4.7%). Despite initial declines among black women, black men, and Latino men (eg, Latino men, 2000-2003: APC, -5.1%; 95% CI, -9.8% to -0.1%; 2003-2013: APC, -0.6%; 95% CI, -1.4% to 0.2%), increases occurred later in the study period (eg, Latino men, 2013-2016: APC, 4.1%; 95% CI, 0.3% to 8.1%). The rates of increase varied by age group and in turn by racial/ethnic group. Among white individuals, large absolute increases occurred in midlife (eg, men aged 55-59 years, 2000-2003: 25.5 deaths per 100 000 residents; 2013-2016: 43.3 deaths per 100 000 residents; women aged 50-54 years, 2000-2003: 7.4 deaths per 100 000 residents; 2013-2016: 16.5 deaths per 100 000 residents), although APCs were also large for ages 25 to 34 years, ranging from 4.6% to 6.9% per year among men and from 7.3% to 12.0% among women. Among American Indian and Alaska Native individuals, increases throughout the age range were observed, with the largest absolute increase occurring for ages 45 to 49 years among men (2000-2013: 113.6 deaths per 100 000 residents; 2013-2016: 193.1 deaths per 100 000 residents) and for ages 50 to 54 among women (2000-2013: from 56.1 deaths per 100 000 residents; 2013-2016: 105.1 deaths per 100 000 residents).Conclusions and relevanceThis study found large increases in alcohol-induced death rates across age and racial/ethnic subgroups of the US population, which have accelerated over recent years. Large increases in alcohol-induced deaths among younger age groups may be associated with future increases in alcohol-related disease.

Project description:ImportancePremature death rates vary in the United States by race/ethnicity. Despite their socioeconomic disadvantages, US Latino populations have lower premature mortality rates than do US white populations, a phenomenon termed the "Latino or Hispanic paradox."ObjectiveTo investigate whether there is a broader Latin American paradox by comparing premature mortality rates in the United States according to race/ethnicity with rates in Latin America and Puerto Rico from 2001 to 2015.Design, setting, and participantsThis descriptive cross-sectional study used mortality data from the World Health Organization Mortality Database. All deaths occurring in individuals aged 20 to 64 years among US Latino, African American, white, and Puerto Rican and 12 other Latin American populations from January 2001 to December 2015 were selected. The data analysis began in October 2018.ExposuresAge, sex, race/ethnicity, and country.Main outcomes and measuresAll-cause mortality, cause-specific mortality, age-standardized mortality rates (AMSRs), and average annual percentage change in mortality rates during 2001 to 2015.ResultsDuring 2001 to 2015, 22 million deaths (8 million women and 14 million men) occurred among individuals aged 20 to 64 years in the selected populations. Among women, US Latina individuals had the lowest premature mortality rates (ASMR for 2015, 144 deaths per 100 000 population) and US African American women had the highest premature mortality rate (ASMR for 2015, 340 deaths per 100 000 population) of the 16 populations studied. Rates among US white women shifted from the sixth lowest in 2001 (ASMR, 231 deaths per 100 000 population) to the 12th lowest in 2015 (ASMR, 235 deaths per 100 000 population). Among men, Peru had the lowest premature mortality rates (ASMR for 2015, 219 deaths per 100 000 population), and Belize had the highest premature mortality rates (ASMR for 2015, 702 deaths per 100 000 population). White men in the United States shifted from the fifth lowest rates in 2001 (ASMR, 396 deaths per 100 000 population) to the eighth lowest rates in 2015 (ASMR, 394 deaths per 100 000 population). Rates for both women and men decreased in all the populations studied from 2001 to 2015 (average annual percentage change range, 0.4% to 3.8% per year) except among US white populations, for which the rate plateaued (average annual percentage change, 0.02% per year [95% CI, -0.3% to 0.2% per year] for women; -0.2% per year [95% CI, -0.4% to 0.0% per year] for men) and among Nicaraguan men, for whom the rates increased (0.6% per year [95% CI, 0.2% to 1.0% per year]). The populations with the lowest mortality rates in 2015 had lower rates from all major causes, but rates were particularly lower for heart disease (21 deaths per 100 000 population) and cancer (50 deaths per 100 000 population).Conclusions and relevancePremature mortality rates are lower for US Latino populations and several Latin American countries than for US white populations, suggesting that there may be a broader Latin American paradox. This analysis also highlights the high premature mortality rates among US African American populations, especially women, compared with many Latin American populations.

Dataset Information

Trends and Prediction in Daily New Cases and Deaths of COVID-19 in the United States: An Internet Search-Interest Based Model.

Publications

Trends and Prediction in Daily New Cases and Deaths of COVID-19 in the United States: An Internet Search-Interest Based Model.

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