Which Risks to Health Matter Most?

2021 ◽  
pp. 126-156
Author(s):  
James Wilson
Keyword(s):  
Public Health ◽  
Health Interventions ◽  
Health Policies ◽  
Public Health Interventions ◽  
Philosophical Literature ◽  
Public Health Policies ◽  
Policy Challenge

This chapter addresses how to prioritize public health policies. Public health interventions need to be justifiable to individuals, but designing approaches to prioritization that are adequately justifiable to individuals can be extremely difficult. One tool for clarifying the problem, which has been widely explored in the philosophical literature, is the idea of a claim—where the strength of an individual’s claim depends on features such as how badly off they are, their capacity to benefit, the time at which their need arises, and whether the bad that will befall them is certain or merely possible. The chapter argues that it is mistaken to think that there is a single and uniquely correct way of measuring claims. Approaches to prioritization need to be pluralistic, and need to reflect on the measures most appropriate for a particular policy challenge.

scholarly journals Public Health Policies and Global COVID-19 Outbreak

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M Komaroff ◽  
A A Belhouchet
Keyword(s):  
Public Health ◽  
South Korea ◽  
Health Interventions ◽  
Health Policies ◽  
P Value ◽  
Public Health Interventions ◽  
Public Health Policies ◽  
The Public ◽  
Health Measures ◽  
The Usa

Abstract Background Was the world prepared to face the pandemic with a standard strategy? Objectives To evaluate the association between public health interventions against the COVID-19 outbreak and the outcome. Methods The observational study included data on incidence of confirmed COVID-19 cases (outcome) and public health non-pharmaceutical interventions (exposure) from five countries: France, Italy, Japan, South Korea, and the USA, December 31, 2019 through April 12, 2020. The public health measures were grouped into five categories: lockdown, movement restrictions, public health measures, social (including social distancing) and economic measures, and use of facial mask. The multiple linear regressions were utilized to test the hypothesis that implementation of some public health measures was associated with the change in the incident number of COVID-19 cases, 2-sided, α = 0.05. Results The incidence of COVID-19 would be significantly greater without lockdown (1.89 times, p-value <.0001), public health and economic measures (25.17, p-value <.0001), and using masks (11.93, p-value=0.002), assuming that all other public health policies are the same. The effectiveness increases with earlier time of implementation. Among considered countries, South Korea was the most efficacious, where all measures were statistically significantly efficacious (p-value <0.05). Conclusions The findings demonstrate an association between public health measures and the outcome. The experience from South Korea should be studied further as the most effective non-pharmacological approach to fight the disease. This paper is the first step to develop the standardized approach utilizing the public health interventions to be applied effectively to the globe population. Key messages the most effective measures to control the COVID-19, and future outbreaks. The effect of particular measure varied by country and time of implementation.

Public Health Programs and Policies: Ethical Justifications

2019 ◽  
pp. 20-32 ◽  
Author(s):  
Ruth R. Faden ◽  
Sirine Shebaya
Keyword(s):  
Public Health ◽  
Collective Action ◽  
Public Health Intervention ◽  
Health Interventions ◽  
Health Policies ◽  
Health Programs ◽  
Moral Justification ◽  
Public Health Interventions ◽  
Public Health Programs ◽  
Public Health Policies

Public health policies sometimes make demands on individuals who do not stand to benefit from the policies, and they sometimes interfere with liberty even when they do benefit the individuals in question. In such instances, a moral justification for a public health intervention is required. This chapter sets forth five justifications for public health interventions: (1) overall benefit, (2) collective action and efficiency, (3) fairness in the distribution of burdens, (4) prevention of harm (the harm principle), and (5) paternalism. The chapter discusses each justification in turn, posits that often more than one justification applies to a given policy, and argues against frameworks that place disproportionate attention on conflicts between liberty and health.

scholarly journals SARS-CoV-2 Transmission Potential and Policy Changes in South Carolina, February 2020 - January 2021

2021 ◽  
Author(s):  
Margaret R. Davies ◽  
Xinyi Hua ◽  
Terrence D. Jacobs ◽  
Gabi I. Wiggill ◽  
Po-Ying Lai ◽  
...  
Keyword(s):  
Public Health ◽  
South Carolina ◽  
Case Series ◽  
Health Interventions ◽  
Health Policies ◽  
Reproductive Number ◽  
Policy Changes ◽  
Public Health Policies ◽  
Transmission Potential ◽  
Case Count

Introduction: We aimed to examine how public health policies influenced the dynamics of COVID-19 time-varying reproductive number (Rt) in South Carolina from February 26, 2020 to January 1, 2021. Methods: COVID-19 case series (March 6, 2020 - January 10, 2021) were shifted by 9 days to approximate the infection date. We analyzed the effects of state and county policies on Rt using EpiEstim. We performed linear regression to evaluate if per-capita cumulative case count varies across counties with different population size. Results: Rt shifted from 2-3 in March to <1 during April and May. Rt rose over the summer and stayed between 1.4 and 0.7. The introduction of statewide mask mandates was associated with a decline in Rt (-15.3%; 95% CrI, -13.6%, -16.8%), and school re-opening, an increase by 12.3% (95% CrI, 10.1%, 14.4%). Less densely populated counties had higher attack rate (p<0.0001). Conclusion: The Rt dynamics over time indicated that public health interventions substantially slowed COVID-19 transmission in South Carolina, while their relaxation may have promoted further transmission. Policies encouraging people to stay home, such as closing non-essential businesses, were associated with Rt reduction, while policies that encouraged more movement, such as re-opening schools, were associated with Rt increase.

scholarly journals An analysis of COVID-19 clusters in India

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Pooja Sengupta ◽  
Bhaswati Ganguli ◽  
Sugata SenRoy ◽  
Aditya Chatterjee
Keyword(s):  
Public Health ◽  
Cluster Analysis ◽  
Population Density ◽  
Case Studies ◽  
Compartment Model ◽  
Health Interventions ◽  
Disease Spread ◽  
Second Phase ◽  
Public Health Interventions ◽  
Homogeneous Groups

Abstract Background In this study we cluster the districts of India in terms of the spread of COVID-19 and related variables such as population density and the number of specialty hospitals. Simulation using a compartment model is used to provide insight into differences in response to public health interventions. Two case studies of interest from Nizamuddin and Dharavi provide contrasting pictures of the success in curbing spread. Methods A cluster analysis of the worst affected districts in India provides insight about the similarities between them. The effects of public health interventions in flattening the curve in their respective states is studied using the individual contact SEIQHRF model, a stochastic individual compartment model which simulates disease prevalence in the susceptible, infected, recovered and fatal compartments. Results The clustering of hotspot districts provide homogeneous groups that can be discriminated in terms of number of cases and related covariates. The cluster analysis reveal that the distribution of number of COVID-19 hospitals in the districts does not correlate with the distribution of confirmed COVID-19 cases. From the SEIQHRF model for Nizamuddin we observe in the second phase the number of infected individuals had seen a multitudinous increase in the states where Nizamuddin attendees returned, increasing the risk of the disease spread. However, the simulations reveal that implementing administrative interventions, flatten the curve. In Dharavi, through tracing, tracking, testing and treating, massive breakout of COVID-19 was brought under control. Conclusions The cluster analysis performed on the districts reveal homogeneous groups of districts that can be ranked based on the burden placed on the healthcare system in terms of number of confirmed cases, population density and number of hospitals dedicated to COVID-19 treatment. The study rounds up with two important case studies on Nizamuddin basti and Dharavi to illustrate the growth curve of COVID-19 in two very densely populated regions in India. In the case of Nizamuddin, the study showed that there was a manifold increase in the risk of infection. In contrast it is seen that there was a rapid decline in the number of cases in Dharavi within a span of about one month.

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