Identifying Public Health Problems

Author(s):  
Scott Burris ◽  
Micah L. Berman ◽  
Matthew Penn, and ◽  
Tara Ramanathan Holiday

Chapter 5 discusses the use of epidemiology to identify the source of public health problems and inform policymaking. It uses a case study to illustrate how researchers, policymakers, and practitioners detect diseases, identify their sources, determine the extent of an outbreak, and prevent new infections. The chapter also defines key measures in epidemiology that can indicate public health priorities, including morbidity and mortality, years of potential life lost, and measures of lifetime impacts, including disability-adjusted life years and quality-adjusted life years. Finally, the chapter reviews epidemiological study designs, differentiating between experimental and observational studies, to show how to interpret data and identify limitations.

2020 ◽  
Vol 5 (7) ◽  
pp. e003259 ◽  
Author(s):  
Sanjay G Reddy

Are the steps that have been taken to arrest the spread of COVID-19 justifiable? Specifically, are they likely to have improved public health understood according to widely used aggregate population health measures, such as Quality Adjusted Life Years (QALYs) and Disability Adjusted Life Years (DALYs) as much or more than alternatives? This is a reasonable question, since such measures have been promoted extensively in global and national health policy by influential actors, and they have become almost synonymous with quantification of public health. If the steps taken against COVID-19 did not meet this test, then either the measures or the policies must be re-evaluated. There are indications that policies against COVID-19 may have been unbalanced and therefore not optimal. A balanced approach to protecting population health should be proportionate in its effects across distinct health concerns at a moment, across populations over time and across populations over space. These criteria provide a guide to designing and implementing policies that diminish harm from COVID-19 while also providing due attention to other threats to aggregate population health. They should shape future policies in response to this pandemic and others.


2020 ◽  
Vol 36 (2) ◽  
pp. 96-103 ◽  
Author(s):  
Xue Feng ◽  
David D. Kim ◽  
Joshua T. Cohen ◽  
Peter J. Neumann ◽  
Daniel A. Ollendorf

ObjectivesQuality-adjusted life-years (QALYs) and disability-adjusted life-years (DALYs) are commonly used in cost-effectiveness analysis (CEA) to measure health benefits. We sought to quantify and explain differences between QALY- and DALY-based cost-effectiveness ratios, and explore whether using one versus the other would materially affect conclusions about an intervention's cost-effectiveness.MethodsWe identified CEAs using both QALYs and DALYs from the Tufts Medical Center CEA Registry and Global Health CEA Registry, with a supplemental search to ensure comprehensive literature coverage. We calculated absolute and relative differences between the QALY- and DALY-based ratios, and compared ratios to common benchmarks (e.g., 1× gross domestic product per capita). We converted reported costs into US dollars.ResultsAmong eleven published CEAs reporting both QALYs and DALYs, seven focused on pharmaceuticals and infectious disease, and five were conducted in high-income countries. Four studies concluded that the intervention was “dominant” (cost-saving). Among the QALY- and DALY-based ratios reported from the remaining seven studies, absolute differences ranged from approximately $2 to $15,000 per unit of benefit, and relative differences from 6–120 percent, but most differences were modest in comparison with the ratio value itself. The values assigned to utility and disability weights explained most observed differences. In comparison with cost-effectiveness thresholds, conclusions were consistent regardless of the ratio type in ten of eleven cases.ConclusionsOur results suggest that although QALY- and DALY-based ratios for the same intervention can differ, differences tend to be modest and do not materially affect comparisons to common cost-effectiveness thresholds.


2021 ◽  
Vol 24 (3) ◽  
pp. 353-360
Author(s):  
Maša Davidović ◽  
Nadine Zielonke ◽  
Iris Lansdorp-Vogelaar ◽  
Nereo Segnan ◽  
Harry J. de Koning ◽  
...  

2020 ◽  
Vol 26 (4) ◽  
pp. 652-661
Author(s):  
Seung Ha Park ◽  
Dong Joon Kim

Alcohol is a well-known risk factor for premature morbidity and mortality. The per capita alcohol consumption of the world’s population rose from 5.5 L in 2005 to 6.4 L in 2010 and was still at the level of 6.4 L in 2016. Alcohol-attributable deaths and disability-adjusted life years (DALYs) declined from 2000 to 2016 by 17.9% and 14.5%, respectively. However, these gains observed in the alcohol-attributable burden have proportionally not kept pace with the total health gains during the same period. In 2016, 3.0 million deaths worldwide and 132 million DALYs were attributable to alcohol, responsible for 5.3% of all deaths and 5.0% of all DALYs. These burdens are the highest in the regions of Eastern Europe and sub-Saharan Africa. The alcohol-attributable burden is particularly heavy among young adults, accounting for 7.2% of all premature mortalities. Among the disease categories to which alcohol is related, injuries, digestive diseases, and cardiovascular diseases are the leading causes of the alcohol-attributable burden. To reduce the harmful use of alcohol in a country, the ‘whole of government’ and ‘whole of society’ approaches are required with the implementation of evidence-based alcohol control policies, the pursuit of public health priorities, and the adoption of appropriate policies over a long period of time. In this review, we summarize previous efforts to investigate the alcohol-attributable disease burden and the best ways to protect against harmful use of alcohol and promote health.


Author(s):  
James Love-Koh ◽  
Andrew Mirelman ◽  
Marc Suhrcke

Abstract Distributional economic evaluation estimates the value for money of health interventions in terms of population health and health equity impacts. When applied to interventions delivered at the population and health system-level interventions (PSIs) instead of clinical interventions, additional practical and methodological challenges arise. Using the example of the Programme Saúde da Familia (PSF) in Brazil, a community-level primary care system intervention, we seek to illustrate these challenges and provide potential solutions. We use a distributional cost-effectiveness analysis (DCEA) approach to evaluate the impact of the PSF on population health and between-state health inequalities in Brazil. Data on baseline health status, disease prevalence and PSF effectiveness are extracted from the literature and incorporated into a Markov model to estimate the long-term impacts in terms of disability-adjusted life years. The inequality and average health impacts are analysed simultaneously using health-related social welfare functions. Uncertainty is computed using Monte Carlo simulation. The DCEA encountered several challenges in the context of PSIs. Non-randomized, quasi-experimental methods may not be powered to identify treatment effect heterogeneity estimates to inform a decision model. PSIs are more likely to be funded from multiple public sector budgets, complicating the calculation of health opportunity costs. We estimate a cost-per-disability-adjusted life years of funding the PSF of $2640. Net benefits were positive across the likely range of intervention cost. Social welfare analysis indicates that, compared to gains in average health, changes in health inequalities accounted for a small proportion of the total welfare improvement, even at high levels of social inequality aversion. Evidence on the population health and health equity impacts of PSIs can be incorporated into economic evaluation methods, although with additional complexity and assumptions. The case study results indicate that the PSF is likely to be cost-effective but that the inequality impacts are small and highly uncertain.


2021 ◽  
Vol 15 (8) ◽  
pp. e0009711
Author(s):  
Shuaibu Ahijo Abdullahi ◽  
Abdulrazaq Garba Habib ◽  
Nafiu Hussaini

A mathematical model is designed to assess the impact of some interventional strategies for curtailing the burden of snakebite envenoming in a community. The model is fitted with real data set. Numerical simulations have shown that public health awareness of the susceptible individuals on snakebite preventive measures could reduce the number of envenoming and prevent deaths and disabilities in the population. The simulations further revealed that if at least fifty percent of snakebite envenoming patients receive early treatment with antivenom a substantial number of deaths will be averted. Furthermore, it is shown using optimal control that combining public health awareness and antivenom treatment averts the highest number of snakebite induced deaths and disability adjusted life years in the study area. To choose the best strategy amidst limited resources in the study area, cost effectiveness analysis in terms of incremental cost effectiveness ratio is performed. It has been established that the control efforts of combining public health awareness of the susceptible individuals and antivenom treatment for victims of snakebite envenoming is the most cost effective strategy. Approximately the sum of US$72,548 is needed to avert 117 deaths or 2,739 disability adjusted life years that are recorded within 21 months in the study area. Thus, the combination of these two control strategies is recommended.


2002 ◽  
Vol 5 (2) ◽  
pp. 395-412 ◽  
Author(s):  
Randall Spalding-Fecher ◽  
Shomenthree Moodley

Malaria is one of the world's most serious and complex health problems. It is also one of the diseases identified as most likely to be affected by climate change, because transmission is sensitive to temperature and rainfall. The objective of this paper is to provide an initial economic valuation of the increased incidence of malaria due to projected changes in climate in South Africa, excluding costs and benefits of prevention and adaptation. We use market based economic valuation tools for morbidity, including cost of treatment and lost short term productivity, and report lost disability adjusted life years from malaria mortality due to climate change. We also discuss how human capital and willingness to pay approaches could be used for mortality valuation. The results show that the opportunity cost of increased morbidity from malaria would be between R277 million and R466 million in 2010, while the lost disability adjusted life years from increased mortality would be from 11 800 to 18 300 years in that year.


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