scholarly journals Following Doctors’ Advice: Explaining the Issuance of Stay-at-Home Orders Related to the Coronavirus Disease 2019 (COVID-19) by U.S. Governors

2020 ◽  
Author(s):  
Gregg R. Murray ◽  
Susan M. Murray

Public health experts widely and strongly advocate for aggressive social distancing to slow the spread of serious infectious diseases. While government mandates to social distance protect public health, they can also impose substantial social and economic costs on those subject to them. As a result, government leaders may be reluctant to issue such mandates. The objective of this study is to identify political, social, economic, and scientific factors that influence governors of U.S. states to issue stay-at-home orders (SAHOs) or not to slow the spread of coronavirus disease 2019 (COVID-19). It uses event history analysis to investigate the issuance of COVID-19-related gubernatorial SAHOs in the 50 U.S. states from March 1, 2020, the day after the first reported COVID-19-related death in the U.S., to April 10, 2020, several days after the last SAHO was issued. During this 41-day period, 42 of the 50 governors issued such orders affecting more than 90 percent of the country’s residents. The results indicate that scientific factors alone did not inform governors’ decisions. While public health factors related to the spread of the disease informed these decisions, political factors related to the partisanship of the governor and economic factors related to the health of the economy also informed them. The results also provide mixed support for scientific factors related to state healthcare capacity and external factors related to geographic diffusion.

2022 ◽  
Vol 2 (1) ◽  
pp. e0000112
Author(s):  
Gregg R. Murray ◽  
Joshua Rutland

COVID-19 has sickened and killed millions of people globally. Conventional non-pharmaceutical interventions, particularly stay-at-home orders (SAHOs), though effective for limiting the spread of disease have significantly disrupted social and economic systems. The effects also have been dramatic in Africa, where many states are already vulnerable due to their developmental status. This study is designed to test hypotheses derived from the public health policymaking literature regarding the roles played by medical and political factors as well as social, economic, and external factors in African countries’ issuance of SAHOs in response to the early stages of the COVID-19 pandemic. Using event history analysis, this study analyzed these five common factors related to public health policy to determine their impact on African states’ varying decisions regarding the issuance of SAHOs. The results of this analysis suggest that medical factors significantly influenced decisions as did factors external to the states, while the role of political factors was limited. Social and economic factors played no discernible role. Overall, this study suggests how African leaders prioritized competing factors in the early stages of a public health crisis.


2020 ◽  
Vol 16 (4) ◽  
pp. 935-942 ◽  
Author(s):  
Laine P. Shay

AbstractThe 2019–20 coronavirus pandemic has significantly altered lives across the globe. In the United States, several states attempted to manage the pandemic by issuing stay-at-home orders. In this research note, I examine whether the gender of state policy makers in the executive branch might impact a state's adoption of a stay-at-home order. Using event history analysis, I find that the governor's gender has no impact on the likelihood of a state adopting a stay-at-home order. However, I find that gender plays a significant role for agency heads. Specifically, my analysis shows that states with a female-headed health agency tend to adopt stay-at-home orders earlier than states with a male administrator. These findings shed light on how female leadership in the executive branch may impact public policy regarding COVID-19.


Author(s):  
Sangeetha Padalabalanarayanan ◽  
Vidya Sagar Hanumanthu ◽  
Bisakha P. Sen

AbstractImportanceTo cope with the continuing COVID-19 pandemic, state and local health officials need information on the effectiveness of policies aimed at curbing contagion, as well as area-specific socio-demographic characteristics that can portend vulnerability to the disease.ObjectiveTo investigate whether state-imposed stay-at-home orders, African American population in the state, state poverty and other state socio-demographic characteristics, were associated with the state-level incidence of COVID-19 infection.Design, Setting, ParticipantsState-level, aggregated, publicly available data on positive COVID-19 cases and tests were used. The period considered was March 1st-May 4th. All U.S. states except Washington were included. Outcomes of interest were daily cumulative and daily incremental COVID-19 infection rates. Outcomes were log-transformed. Log-linear regression models with a quadratic time-trend and random intercepts for states were estimated. Covariates included log-transformed test-rates, a binary indicator for stay-at-home, percentage of African American, poverty, percentage elderly, state population and prevalence of selected comorbidities. Binary ‘fixed effects’ for date each state first started reporting test data were included.ResultsStay-at-home orders were associated with decreases in cumulative (β:-1.23; T-stat: - 6.84) and daily (β:-0.46; T-stat: −2.56) infection-rates. Predictive analyses indicated that expected cumulative infection rates would be 3 times higher and expected daily incremental rates about 60% higher in absence of stay-at-home orders. Higher African American population was associated with higher cumulative (β: 0.08; T-stat: 4.01) and daily (β: 0.06; T-stat: 3.50) rates. State poverty rates had mixed results and were not robust to model specifications. There was strong evidence of a quadratic daily trend for cumulative and daily rates. Results were largely robust to alternate specifications.ConclusionsWe find evidence that stay-at-home orders, which were widely supported by public-health experts, helped to substantially curb COVID-19 infection-rates. As we move to a phased re-opening, continued precautions advised by public-health experts should be adhered to. Also, a larger African American population is strongly associated with incidence of COVID-19 infection. Policies and resources to help mitigate African American vulnerability to COVID-19 is an urgent public health and social justice issue, especially since the ongoing mass protests against police brutality may further exacerbate COVID-19 contagion in this community.Key PointsQuestionDid the stay-at-home orders, African American population and other socio demographic factors across states have any associations with COVID-19 infection rates across states?FindingsMultivariate log-linear regression models using daily state level data from March-May found evidence that when stay-at-home orders were implemented, they helped reduce state COVID-19 cumulative and daily infection rates substantially. Further, we found that states with larger African-American population had higher COVID-19 infection rates.MeaningResults suggest that state-level stay-at-home orders helped reduce COVID-19 infection rates substantially, and also that African American populations may be especially vulnerable to COVID-19 infection.


1995 ◽  
Vol 49 (2) ◽  
pp. 355-357
Author(s):  
Johannes Huinink

1998 ◽  
Vol 10 (1-3) ◽  
pp. 1-9
Author(s):  
Onno Boonstra ◽  
Maarten Panhuysen

Population registers are recognised to be a very important source for demographic research, because it enables us to study the lifecourse of individuals as well as households. A very good technique for lifecourse analysis is event history analysis. Unfortunately, there are marked differences in the way the data are available in population registers and the way event history analysis expects them to be. The source-oriented approach of computing historical data calls for a ‘five-file structure’, whereas event history analysis only can handle fiat files. In this article, we suggest a series of twelve steps with which population register data can be transposed from a five-file structured database into a ‘flat file’ event history analysis dataset.


2020 ◽  
Vol 15 (2) ◽  
pp. 105-110
Author(s):  
Haile Kassahun ◽  
Dugessa Tesfaye

Background: Disposal of pharmaceutical waste among patients is a global challenge especially in developing countries like Ethiopia. Improper medication disposal can lead to health problems and environmental contaminations. Therefore, the present study aimed to assess disposal practices of unused medications among patients in public health centers of Dessie town, Northeast Ethiopia. Methods: A descriptive cross-sectional study was conducted among 263 patients in four public health centers of Dessie town, Ethiopia from March to June, 2019. Face-to-face interviews using structured questionnaires were used to collect data from each study subject. Results: The majority of the respondents, 224 (85.17%) had unused medications at their home during the study period. The most commonly reported disposal method in the present study was flushing down into a toilet 66 (25.09%). None of the respondents practiced returning unused medications to Pharmacy. Moreover, 85 (32.31%) of the respondents reported never disposing their medications and believed that it is acceptable to store medications at home for future use. Conclusion: In the present study, there was a high practice of keeping medications at home and most of the disposal practices were not recommended methods. In addition, most of the respondents did not get advice from pharmacists and other health care professionals on how to dispose off unused medications. Hence, there is a need for proper education and guidance of patients regarding disposal practices of unused medications.


Author(s):  
Edward Newman ◽  
Eamon Aloyo

Progress in conflict prevention depends upon a better understanding of the underlying circumstances that give rise to violent conflict and mass atrocities, and of the warning signs that a crisis is imminent. While a substantial amount of empirical research on the driving forces of conflict exists, its policy implications must be exploited more effectively, so that the enabling conditions for violence can be addressed before it occurs. Violence prevention involves a range of social, economic, and political factors; the chapter highlights challenges—many of them international—relating to deprivation, inequality, governance, and environmental management. Prevention also requires overcoming a number of acute political obstacles embedded within the values and institutions of global governance. The chapter concludes with a range of proposals for structural conflict prevention and crisis response, as well as the prevention of mass atrocities.


Author(s):  
Yujin Kim

In the context of South Korea, characterized by increasing population aging and a changing family structure, this study examined differences in the risk of cognitive impairment by marital status and investigated whether this association differs by gender. The data were derived from the 2006–2018 Korean Longitudinal Study of Aging. The sample comprised 7,568 respondents aged 45 years or older, who contributed 30,414 person-year observations. Event history analysis was used to predict the odds of cognitive impairment by marital status and gender. Relative to their married counterparts, never-married and divorced people were the most disadvantaged in terms of cognitive health. In addition, the association between marital status and cognitive impairment was much stronger for men than for women. Further, gender-stratified analyses showed that, compared with married men, never-married men had a higher risk of cognitive impairment, but there were no significant effects of marital status for women.


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