Duration of Behavioral Policy Interventions and Incidence of COVID-19 by Social Vulnerability of US Counties, April–December 2020
Szu-Yu Zoe KaoJ. Danielle SharpeRashon I. LaneRashid NjaiRussell F. McCordAderonke AjiboyeChandresh N. LadvaLinda Trinh VõDonatus U. Ekwueme
5
Citation
33
Reference
10
Related Paper
Citation Trend
Abstract:
Objective: State-issued behavioral policy interventions (BPIs) can limit community spread of COVID-19, but their effects on COVID-19 transmission may vary by level of social vulnerability in the community. We examined the association between the duration of BPIs and the incidence of COVID-19 across levels of social vulnerability in US counties. Methods: We used COVID-19 case counts from USAFacts and policy data on BPIs (face mask mandates, stay-at-home orders, gathering bans) in place from April through December 2020 and the 2018 Social Vulnerability Index (SVI) from the Centers for Disease Control and Prevention. We conducted multilevel linear regression to estimate the associations between duration of each BPI and monthly incidence of COVID-19 (cases per 100 000 population) by SVI quartiles (grouped as low, moderate low, moderate high, and high social vulnerability) for 3141 US counties. Results: Having a BPI in place for longer durations (ie, ≥2 months) was associated with lower incidence of COVID-19 compared with having a BPI in place for <1 month. Compared with having no BPI in place or a BPI in place for <1 month, differences in marginal mean monthly incidence of COVID-19 per 100 000 population for a BPI in place for ≥2 months ranged from –4 cases in counties with low SVI to –401 cases in counties with high SVI for face mask mandates, from –31 cases in counties with low SVI to –208 cases in counties with high SVI for stay-at-home orders, and from –227 cases in counties with low SVI to –628 cases in counties with high SVI for gathering bans. Conclusions: Establishing COVID-19 prevention measures for longer durations may help reduce COVID-19 transmission, especially in communities with high levels of social vulnerability.Keywords:
Social vulnerability
Vulnerability
Actually the hazards are not the direct causes of disaster, the degree of vulnerability of populations to hazards do not depend solely on the proximity of the source of threat or the physical nature of hazard, social factors also plays an important role in determining vulnerability. According to the risk management model, physical and social vulnerability are linked to the place of vulnerability. In this research we explain disparities of losses and damages after the disaster of Boumerdes cities in 2003. We assess the relation between social and physical vulnerabilities and how they built the disaster of 2003. A geographic information system was used to establish areas of vulnerability based upon the expertise of the built environment and 10 social characteristics for the cities of Boumerdes Province.The important result is the intersection of degrees of physical vulnerability with those of social vulnerability; the other result is that the most socially vulnerable cities are those living in areas of high physical vulnerability. This manuscript contributes to the development of a general theory on disasters as an intersection between social and physical vulnerabilities and highlights the importance of integrating vulnerabilities into risk and disaster reduction policies in Algeria.
Vulnerability
Social vulnerability
Disaster risk reduction
Physical hazard
Cite
Citations (0)
Vulnerability
Social vulnerability
Cite
Citations (18)
Vulnerability
Social vulnerability
Adaptive capacity
Cite
Citations (4)
Vulnerability to climate change is a complex and dynamic phenomenon involving both social and physical/environmental aspects. It is presented as a method for the quantification of the vulnerability of all municipalities of Minas Gerais, a state in southeastern Brazil. It is based on the aggregation of different kinds of environmental, climatic, social, institutional, and epidemiological variables, to form a composite index. This was named "Index of Human Vulnerability" and was calculated using a software (SisVuClima®) specifically developed for this purpose. Social, environmental, and health data were combined with the climatic scenarios RCP 4.5 and 8.5, downscaled from ETA-HadGEM2-ES for each municipality. The Index of Human Vulnerability associated with the RCP 8.5 has shown a higher vulnerability for municipalities in the southern and eastern parts of the state of Minas Gerais.
Vulnerability
Social vulnerability
Composite index
Vulnerability index
Cite
Citations (25)
While recent research has recognized the importance of considering social vulnerability, the changing patterns of social vulnerability within cities and the climate adaptation challenges these shifts pose have yet to receive much attention. In this article, we evaluate the changing patterns of social vulnerability in three coastal cities (Houston, New Orleans, and Tampa) over a thirty-year time period (1980–2010) and integrate neighborhood change theories with theories of social vulnerability to explain those patterns. Through this analysis, we highlight emerging dimensions of vulnerability that warrant attention in the future adaptation efforts of these cities.
Vulnerability
Social vulnerability
Warrant
Climate Change Adaptation
Cite
Citations (56)
List of Figures and Tables List of Abbreviations Notes on Contributors Preface Acknowledgments PART I: CONCEPTS AND METHODOLOGY Social Vulnerability in Europe C.Ranci Bringing Territory Back in Social Comparative Research C.Ranci PART II: ASPECTS OF SOCIAL VULNERABILITY Beyond the Male Breadwinner Family Model E.Pavolini & C.Ranci Income Vulnerability in Europe S.Curatolo & G.Wolleb Unstable Employment in Western Europe: Exploring the Individual and Household Dimensions I. Fellini & M.Migliavacca Housing Deprivation and Vulnerability in Western Europe P.Palvarini & E.Pavolini Disability and Caregiving: A Step Towards Social Vulnerability? G.Costa & C.Ranci PART III: MULTIDIMENSIONAL ANALYSIS The Vulnerability of Young Adults on Leaving the Parental Home G.A.Micheli& A.Rosina Social Vulnerability: A Multidimensional Analysis C.Ranci & M.Migliavacca Explaining Social Vulnerability C.Ranci, B.Fiore & E.Pavolini General Conclusion C.Ranci References Notes
Vulnerability
Social vulnerability
Cite
Citations (54)
Abstract Purpose of this research to know 1) the level of social vulnerability, 2) socio economic description, and 3) mapping of comparison of social vulnerability in Watershed of Bengawan Solo covering Bojonegoro, Tuban, Lamongan and Gresik. The method used in this research by using Social Vulnerability Index (SoVI) method as social vulnerability analysis tool and Geography Information System (GIS) analysis tool to map the area and its vulnerability level. The results showed the highest level of social vulnerability with the highest score of SoVI score obtained by Tuban Regency with SoVI score of 7, then Bojonegoro with SoVI score of 6, Lamongan with SoVI score of 4, and Gresik with SoVI score of 1. Bojonegoro And Kabupaten Tuban have the same highest score on the components of social vulnerability level, then Lamongan regency, and the lowest level of social vulnerability is in Gresik regency. For the grade of social vulnerability, Kabupaten Tuban and Bojonegoro are categorized into high social vulnerability classes, Lamongan District with moderate social vulnerability, and Gresik Regency with the lowest social vulnerability.
Vulnerability
Social vulnerability
Vulnerability index
Cite
Citations (1)
Abstract The potential for natural disasters in Pandeglang Regency is enormous considering that various kinds of disasters can occur in Pandeglang Regency. There needs to be comprehensive efforts to reduce the impact of the risk of natural disasters, one of them is by knowing the level of social vulnerability of the community in Pandeglang. Social vulnerability calculates the level of social vulnerability of the community to scenarios of natural disasters. This study aims to determine the level of social vulnerability and its distribution. Concept method of Social Vulnerability Index (SOVI) is used to measure regional vulnerability based on social indicators to disasters using the aspects of exposure, sensitivity and adaptive capacity. The variables used are population density, proportion of informal sector workers, proportion of vulnerable age population, proportion of non-permanent houses, proportion of prosperous households, proportion of high school graduates and number of social institutions. The level of vulnerability that dominates is a low vulnerability area by number 25 sub-districts or 71.42 % while there are 9 sub-districts or 25.71 % for high vulnerability areas and only 1 sub-district or 2.85 % of high vulnerability areas, namely Cimanuk District, which is in the northern part of Pandeglang Regency. Based on the value of vulnerability in several areas that still show a fairly large level of medium-high vulnerability. So, this data can be used as a recommendation as early mitigation measures to reduce the level of social vulnerability in order to reduce the impact that will later be caused.
Vulnerability
Social vulnerability
Vulnerability index
Cite
Citations (0)
Despite of a recent increase in the number of vulnerability analysis, there has been relatively little discussion on vulnerability assessment of social system. The objective of this paper is to undertake a comprehensive systematic analysis of the social vulnerability hit by natural disasters as well as its application in China. Fourteen unique variations of the Social Vulnerability Index (SVI) were calculated for each study area and evaluated by factor analysis, and overall social vulnerability was calculated by applying principal components analysis (PCA), and then made use of GIS to get the spatial patterning of social vulnerability. The paper concludes that it is possible to construct an effective index of vulnerability, and our results can be also taken as an important way to recognize social characteristics of natural disasters.
Vulnerability
Social vulnerability
Vulnerability index
Cite
Citations (0)
Abstract This entry details a spatial social science perspective for environmental hazards vulnerability analysis. Vulnerability science is an interdisciplinary approach that integrates the characteristics of potential hazards such as magnitude, frequency, and duration (physical vulnerability) with characteristics of people and the built environment that either increase or decrease their impacts (social vulnerability). It is the combination of the physical and social processes and associated outcomes that contribute to the overall vulnerability of places. Spatial social science methods and tools (such as geographic information systems) provide the integrative mechanism for comparing vulnerability at various geographic scales such as census tracts, counties, or cities.
Vulnerability
Social vulnerability
Natural hazard
Cite
Citations (4)