Revealing the spatial shifting pattern of COVID-19 pandemic in the United States.
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ABSTRACT:
SUBMITTER: Zhu D
PROVIDER: S-EPMC8055907 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Objectives:The paper highlights US health policy and technology responses to the COVID-19 pandemic from January 1, 2020 - August 9, 2020. Methods:A review of primary data sources in the US was conducted. The data were summarized to describe national and state-level trends in the spread of COVID-19 and in policy and technology solutions. Results:COVID-19 cases and deaths initially peaked in late March and April, but after a brief reduction in June cases and deaths began rising again July and continued to climb into early August. The US policy response is best characterized by its federalist, decentralized nature. The national government has led in terms of economic and fiscal response, increasing funding for scientific research into testing, treatment, and vaccines, and in creating more favorable regulations for the use of telemedicine. State governments have been responsible for many of the containment, testing, and treatment responses, often with little federal government support. Policies that favor economic re-opening are often followed by increases in state-level case numbers, which are then followed by stricter containment measures, such as mask wearing or pausing re-opening plans. Conclusions:While all US states have begun to "re-open" economic activities, this trend appears to be largely driven by social tensions and economic motivations than an ability to effectively test and surveil populations.
| S-EPMC7451131 | biostudies-literature
Project description:The novel coronavirus (COVID-19) pandemic presents a severe threat to human health worldwide. The United States (US) has the highest number of reported COVID-19 cases, and over 16 million people were infected up to the 12 December 2020. To better understand and mitigate the spread of the disease, it is necessary to recognize the pattern of the outbreak. In this study, we explored the patterns of COVID-19 cases in the US from 1 March to 12 December 2020. The county-level cases and rates of the disease were mapped using a geographic information system (GIS). The overall trend of the disease in the US, as well as in each of its 50 individual states, were analyzed by the seasonal-trend decomposition. The disease curve in each state was further examined using K-means clustering and principal component analysis (PCA). The results showed that three clusters were observed in the early phase (1 March-31 May). New York has a unique pattern of the disease curve and was assigned one cluster alone. Two clusters were observed in the middle phase (1 June-30 September). California, Texas and Florida were assigned in the same cluster, which has the pattern different from the remaining states. In the late phase (1 October-12 December), California has a unique pattern of the disease curve and was assigned a cluster alone. In the whole period, three clusters were observed. California, Texas and Florida still have similar patterns and were assigned in the same cluster. The trend analysis consolidated the patterns identified from the cluster analysis. The results from this study provide insight in making disease control and mitigation strategies.
| S-EPMC7967616 | biostudies-literature
Project description: Not available
| S-EPMC7862912 | biostudies-literature
Project description:What factors explain spatial variation in the severity of COVID-19 across the United States? To answer this question, we analyze the correlates of COVID-19 cases and deaths across US counties. We document four sets of facts. First, effective density is an important and persistent determinant of COVID-19 severity. Second, counties with more nursing home residents, lower income, higher poverty rates, and a greater presence of African Americans and Hispanics are disproportionately impacted, and these effects show no sign of disappearing over time. Third, the effect of certain characteristics, such as the distance to major international airports and the share of elderly individuals, dies out over time. Fourth, Trump-leaning counties are less severely affected early on, but later suffer from a large severity penalty.
| S-EPMC7948676 | biostudies-literature
Project description:Social distancing, a non-pharmaceutical tactic aimed at reducing the spread of COVID-19, can arise because individuals voluntarily distance from others to avoid contracting the disease. Alternatively, it can arise because of jurisdictional restrictions imposed by local authorities. We run reduced form models of social distancing as a function of county-level exogenous demographic variables and jurisdictional fixed effects for 49 states to assess the relative contributions of demographic and jurisdictional effects in explaining social distancing behavior. To allow for possible spatial aspects of a contagious disease, we also model the spillovers associated with demographic variables in surrounding counties as well as allow for disturbances that depend upon those in surrounding counties. We run our models weekly and examine the evolution of the estimated coefficients over time since the onset of the COVID-19 pandemic in the United States. These estimated coefficients express the revealed preferences of individuals who were able to and chose to stay at home to avoid the disease. Stay-at-home behavior measured using cell phone tracking data exhibits considerable cross-sectional variation, increasing over nine-fold from the end of January 2020 to the end of March 2020, and then decreasing by about 50% through mid-June 2020. Our estimation results show that demographic exogenous variables explain substantially more of this variation than predictions from jurisdictional fixed effects. Moreover, the explanations from demographic exogenous variables and jurisdictional fixed effects show an evolving correlation over the sample period, initially partially offsetting, and eventually reinforcing each other. Furthermore, the predicted social distance from demographic exogenous variables shows substantial spatial autoregressive dependence, indicating clustering in social distancing behavior. The increased variance of stay-at-home behavior coupled with the high level of spatial dependence can result in relatively intense hotspots and coldspots of social distance, which has implications for disease spread and mitigation.
| S-EPMC7508394 | biostudies-literature
Project description:Currently, the world is facing its 3rd coronavirus outbreak of the 21st century, which has turned to a pandemic recently. Starting on December 2019, coronavirus disease (COVID-19) was first detected in Wuhan City, Hubei province, China. As of 31st March, 2020, more than 900,000 COVID-19 cases have been reported across the globe involving more than 200 countries. The first case of the United States (US) was confirmed on 20th January, 2020 in a 35-year-old male who had a travel history to Wuhan, China, before returning to the U.S. Since then, the SARS-CoV-2 virus has spread to all the 50 states of US, with more cases being reported every day. New York, New Jersey, Michigan, and California are the worst-hit states. As COVID-19 is growing, every day has been marked by novel developments and updates. We hereby talk about how the U.S. is leading the multiagency effort to fight against this pandemic and the steps that have been taken so far.
| S-EPMC7346962 | biostudies-literature
Project description:Despite calls for political consensus, there is growing evidence that the public response to the COVID-19 pandemic has been politicized in the US. We examined the extent to which this polarization exists among the US public across two national studies. In a representative US sample (N = 699, March 2020) we find that liberals (compared to conservatives) perceive higher risk, place less trust in politicians to handle the pandemic, are more trusting of medical experts such as the WHO, and are more critical of the government response. We replicate these results in a second, pre-registered study (N = 1000; April 2020), and find that results are similar when considering partisanship, rather than political ideology. In both studies we also find evidence that political polarization extends beyond attitudes, with liberals consistently reporting engaging in a significantly greater number of health protective behaviors (e.g., wearing face masks) than conservatives. We discuss the possible drivers of polarization on COVID-19 attitudes and behaviors, and reiterate the need for fostering bipartisan consensus to effectively address and manage the COVID-19 pandemic.
| S-EPMC8631569 | biostudies-literature
Project description:BackgroundAlthough the direct toll of COVID-19 in the United States has been substantial, concerns have also arisen about the indirect effects of the pandemic. Hospitalizations for acute cardiovascular conditions have declined, raising concern that patients may be avoiding hospitals because of fear of contracting severe acute respiratory syndrome- coronavirus-2 (SARS-CoV-2). Other factors, including strain on health care systems, may also have had an indirect toll.ObjectivesThis investigation aimed to evaluate whether population-level deaths due to cardiovascular causes increased during the COVID-19 pandemic.MethodsThe authors conducted an observational cohort study using data from the National Center for Health Statistics to evaluate the rate of deaths due to cardiovascular causes after the onset of the pandemic in the United States, from March 18, 2020, to June 2, 2020, relative to the period immediately preceding the pandemic (January 1, 2020 to March 17, 2020). Changes in deaths were compared with the same periods in the previous year.ResultsThere were 397,042 cardiovascular deaths from January 1, 2020, to June 2, 2020. Deaths caused by ischemic heart disease increased nationally after the onset of the pandemic in 2020, compared with changes over the same period in 2019 (ratio of the relative change in deaths per 100,000 in 2020 vs. 2019: 1.11, 95% confidence interval: 1.04 to 1.18). An increase was also observed for deaths caused by hypertensive disease (1.17, 95% confidence interval: 1.09 to 1.26), but not for heart failure, cerebrovascular disease, or other diseases of the circulatory system. New York City experienced a large relative increase in deaths caused by ischemic heart disease (2.39, 95% confidence interval: 1.39 to 4.09) and hypertensive diseases (2.64, 95% confidence interval: 1.52 to 4.56) during the pandemic. More modest increases in deaths caused by these conditions occurred in the remainder of New York State, New Jersey, Michigan, and Illinois but not in Massachusetts or Louisiana.ConclusionsThere was an increase in deaths caused by ischemic heart disease and hypertensive diseases in some regions of the United States during the initial phase of the COVID-19 pandemic. These findings suggest that the pandemic may have had an indirect toll on patients with cardiovascular disease.
| S-EPMC7800141 | biostudies-literature
Project description:We document large-scale urban flight in the United States during the COVID-19 pandemic. Regions that saw migrant influx experienced greater subsequent new COVID-19 cases, linking urban flight (as a disease vector) and coronavirus spread in destination areas. Urban residents fled to socially connected areas, consistent with the theory that individuals sheltered with friends and family, or in second homes. Populations that fled were disproportionately younger, whiter, and wealthier. The association between migration and subsequent new cases persists when instrumenting for migration with social networks.
| S-EPMC9344811 | biostudies-literature
Project description:IntroductionInternational studies have demonstrated increasing rates of sexual dysfunction amidst the coronavirus disease 2019 (COVID-19) pandemic; however, the impact of the pandemic on female sexual function in the United States is unknown.AimTo assess the impact of the COVID-19 pandemic on female sexual function and frequency in the United States.MethodsA pre-pandemic survey containing the Female Sexual Function Index (FSFI) and demographic questions was completed by adult women in the United States from October 20, 2019 and March 1, 2020. The same women were sent a follow-up survey also containing the FSFI, as well as the Patient Health Questionnaire for Depression and Anxiety with 4 items (PHQ-4), and questions pertaining to mask wearing habits, job loss, and relationship changes. Risk for female sexual dysfunction (RFSD) was defined as FSFI < 26.55.Main outcome measureDifferences in pre-pandemic and intra-pandemic female sexual function, measured by the FSFI, and sexual frequency.ResultsNinety-one women were included in this study. Overall FSFI significantly decreased during the pandemic (27.2 vs 28.8, P = .002), with domain-specific decreases in arousal (4.41 vs 4.86, P = .0002), lubrication (4.90 vs 5.22, P = .004), and satisfaction (4.40 vs 4.70, P = .04). There was no change in sexual frequency. Contingency table analysis of RFSD prior to and during the pandemic revealed significantly increased RFSD during the pandemic (P = .002). Women who developed RFSD during the pandemic had higher PHQ-4 anxiety subscale scores (3.74 vs 2.53, P = .01) and depression subscale scores (2.74 vs 1.43, P = .001) than those who did not. Development of FSD was not associated with age, home region, relationship status, mask wearing habits, knowing someone who tested positive for COVID-19, relationship change, or job loss and/or reduction during the pandemic.ConclusionIn this population of female cannabis users, risk for sexual dysfunction increased amidst the COVID-19 pandemic and is associated with depression and anxiety symptoms. Bhambhvani HP, Chen T, Wilson-King AM, et al. Female Sexual Function During the COVID-19 Pandemic in the United States. Sex Med 2021;9:100355.
| S-EPMC8360920 | biostudies-literature