As the Trump Administration’s Tiny Windows Close, Giant Doors Open for Science Advice
By Genna Reed
In his first week as president-elect, Joe Biden instituted an advisory board of experts to provide science-based recommendations to respond to COVID-19. This could be a signal that independent science advice under a Biden administration is valued. After four years of watching the norms of science advisory structures eroded and undermined, especially at the EPA, it is hard to visualize the possibilities of a government informed by experts. Once Biden takes office in January, here are the actions I hope his administration will take to shore up the government's fifth arm of external expert advice:
1. Rescind EO 13875 and Reinstate Disbanded Committees
In Executive Order 13875, titled "Evaluating and Improving the Utility of Federal Advisory Committees," issued in June 2019, President Trump mandated the elimination of one-third of federal advisory committees with an aim of reaching the arbitrary total of 350. Some agencies followed the order, cutting committees like EPA's Environmental Laboratory Advisory Board (ELAB) and the National Advisory Council for Environmental Policy and Technology (NACEPT), The Department of Commerce's Smart Grid Advisory Committee and Marine Protected Areas Advisory Committee, and DOI's Invasive Species Advisory Committee and CDC's Agency for Toxic Substances and Disease Registry's Board of Scientific Counselors and its Advisory Committee to the Director. Yes, you read that right. As the CDC director responded to a national public health crisis, he did not have a sounding board of leading public health experts to help guide a federal response, as had been readily available since 1962.
Neither the White House nor federal agencies released criteria or a full justification for disbanding these committees to the public. This is likely not an exhaustive list. Thus, the Biden administration should allow agencies to bring back disbanded committees quickly so that they can get back to work on projects left unfinished and take on new ones, especially those with direct relevance to providing expertise to the government on responding to COVID-19.
2. Issue a Proactive Executive Order to Affirm the Value of Advisory Committees
The president-elect should issue an executive order affirming the value of advisory committees and direct agencies to improve the integrity and transparency of processes to ensure committees meet their chartered objectives. Our fact sheet includes a long list of measures that should be included in that order, but the goal of the executive order should be threefold:
- address committee membership by requiring agencies to be more transparent and make decisions based solely on experience and technical qualifications in the topic the committees address, and not based on inappropriate criteria (e.g., party affiliation, political opinions, having received a government grant);
- protect the independence and integrity of advisory committees by protecting against conflicts of interest;
- ensure that the processes used to establish and terminate advisory committees are clear and transparent and that the government seeks out the advice it needs.
An order that sets a high ethical bar for external advice can help protect against some of the more egregious violations we saw under the Trump administration, like the appointment of a majority of members with clear issues of impartiality to the HHS's Human Fetal Tissue Ethics Advisory Board, which then issued sweeping rejections of grant proposals for critical research using fetal tissue.
3. Go Back to the Drawing Board at the EPA
The Biden administration should begin to reverse the damage done by former Administrator Pruitt and Administrator Wheeler to gerrymander science at EPA and signal a commitment to balanced, independent advice by instituting a new nominations process for all EPA committees, while promoting transparency and public input and listening to its own staff recommendations. The administration should begin by scrapping the Science Advisory Board and the Clean Air Scientific Advisory Committee and start over. Here's why.
There are still qualified experts on EPA's advisory committees, but since the process barred EPA-funded scientists from applying from fall 2017 to 2020, the expertise is not balanced and not the most relevant for the issues currently facing EPA. Further, it is unclear whether membership was adequately vetted for conflicts of interest. These are all fair questions, since we know Wheeler's administration failed to provide documentation on its selection process.
The only way to fix a broken process is to start from scratch, instituting some of the norms and processes that were in place before the Trump administration came in, but also updating them to ensure even more transparency. For example, we recommend that all agencies, including EPA, publish relevant basic information about each committee member on a public online portal (e.g., integrity.gov), including qualifications, background, employers, and funding sources for the previous five years, along with any conflict-of-interest waivers granted. Additionally, the decisionmaking processes used for committee formation, including how agencies screen members, how they assess committees for balance, and which political officials are involved, should be made public.
All members of committees re-formed could reapply if they wished to remain. But importantly, a new vetting process would ensure that expertise was prioritized and that conflicts of interest or appearance of impartiality was avoided.
4. Work With Congress on Bipartisan Legislation That Would Increase Transparency and Public Input
The Federal Advisory Committee Act Amendments of 2019 would require agencies to open nominations for committee positions, select and publicize from those nominations, and clearly distinguish independent scientists from those representing a particular interest group. The bill would also require disclosure of conflicts of interest to the agency and the public and greater transparency of the meetings themselves. Also, political party affiliation cannot be used as a criterion for selection for a committee, which is important as such political litmus tests have been used in the past to distort and stack advisory committees under previous administrations.
Congress could also consider legislation that would institute a formal petition process for the public to request an agency assemble a federal advisory committee for an issue based on a set of criteria. This could ensure a more inclusive and equitable approach to deciding what issues get paid adequate attention by agencies.
Making a Sound Investment in Science Advice
We have studied the ways in which science advisory committees have been sidelined or hijacked and over the past four years saw very clearly how changes to norms and the erosion of processes built to uphold integrity can wreak havoc on environmental and public health policy decisions.
As a new administration takes office, I hope that it takes advantage of this hindsight and sees the opportunities I see: not just bringing back old policies and signaling the importance of government science advice, but finding new ways to make it more responsive to the public than to special interests, and more inclusive of a diverse set of scientists and experts whose voices need to be heard right now. There's no time like the present to modernize our government advisory infrastructure, and our recommendations feature actions that can help get us there.
Reposted with permission from the Union of Concerned Scientists.
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By Eric Tate and Christopher Emrich
Disasters stemming from hazards like floods, wildfires, and disease often garner attention because of their extreme conditions and heavy societal impacts. Although the nature of the damage may vary, major disasters are alike in that socially vulnerable populations often experience the worst repercussions. For example, we saw this following Hurricanes Katrina and Harvey, each of which generated widespread physical damage and outsized impacts to low-income and minority survivors.
Mapping Social Vulnerability<p>Figure 1a is a typical map of social vulnerability across the United States at the census tract level based on the Social Vulnerability Index (SoVI) algorithm of <a href="https://onlinelibrary.wiley.com/doi/abs/10.1111/1540-6237.8402002" target="_blank"><em>Cutter et al.</em></a> . Spatial representation of the index depicts high social vulnerability regionally in the Southwest, upper Great Plains, eastern Oklahoma, southern Texas, and southern Appalachia, among other places. With such a map, users can focus attention on select places and identify population characteristics associated with elevated vulnerabilities.</p>
Fig. 1. (a) Social vulnerability across the United States at the census tract scale is mapped here following the Social Vulnerability Index (SoVI). Red and pink hues indicate high social vulnerability. (b) This bivariate map depicts social vulnerability (blue hues) and annualized per capita hazard losses (pink hues) for U.S. counties from 2010 to 2019.<p>Many current indexes in the United States and abroad are direct or conceptual offshoots of SoVI, which has been widely replicated [e.g., <a href="https://link.springer.com/article/10.1007/s13753-016-0090-9" target="_blank"><em>de Loyola Hummell et al.</em></a>, 2016]. The U.S. Centers for Disease Control and Prevention (CDC) <a href="https://www.atsdr.cdc.gov/placeandhealth/svi/index.html" target="_blank">has also developed</a> a commonly used social vulnerability index intended to help local officials identify communities that may need support before, during, and after disasters.</p><p>The first modeling and mapping efforts, starting around the mid-2000s, largely focused on describing spatial distributions of social vulnerability at varying geographic scales. Over time, research in this area came to emphasize spatial comparisons between social vulnerability and physical hazards [<a href="https://doi.org/10.1007/s11069-009-9376-1" target="_blank"><em>Wood et al.</em></a>, 2010], modeling population dynamics following disasters [<a href="https://link.springer.com/article/10.1007%2Fs11111-008-0072-y" target="_blank" rel="noopener noreferrer"><em>Myers et al.</em></a>, 2008], and quantifying the robustness of social vulnerability measures [<a href="https://doi.org/10.1007/s11069-012-0152-2" target="_blank" rel="noopener noreferrer"><em>Tate</em></a>, 2012].</p><p>More recent work is beginning to dissolve barriers between social vulnerability and environmental justice scholarship [<a href="https://doi.org/10.2105/AJPH.2018.304846" target="_blank" rel="noopener noreferrer"><em>Chakraborty et al.</em></a>, 2019], which has traditionally focused on root causes of exposure to pollution hazards. Another prominent new research direction involves deeper interrogation of social vulnerability drivers in specific hazard contexts and disaster phases (e.g., before, during, after). Such work has revealed that interactions among drivers are important, but existing case studies are ill suited to guiding development of new indicators [<a href="https://doi.org/10.1016/j.ijdrr.2015.09.013" target="_blank" rel="noopener noreferrer"><em>Rufat et al.</em></a>, 2015].</p><p>Advances in geostatistical analyses have enabled researchers to characterize interactions more accurately among social vulnerability and hazard outcomes. Figure 1b depicts social vulnerability and annualized per capita hazard losses for U.S. counties from 2010 to 2019, facilitating visualization of the spatial coincidence of pre‑event susceptibilities and hazard impacts. Places ranked high in both dimensions may be priority locations for management interventions. Further, such analysis provides invaluable comparisons between places as well as information summarizing state and regional conditions.</p><p>In Figure 2, we take the analysis of interactions a step further, dividing counties into two categories: those experiencing annual per capita losses above or below the national average from 2010 to 2019. The differences among individual race, ethnicity, and poverty variables between the two county groups are small. But expressing race together with poverty (poverty attenuated by race) produces quite different results: Counties with high hazard losses have higher percentages of both impoverished Black populations and impoverished white populations than counties with low hazard losses. These county differences are most pronounced for impoverished Black populations.</p>
Fig. 2. Differences in population percentages between counties experiencing annual per capita losses above or below the national average from 2010 to 2019 for individual and compound social vulnerability indicators (race and poverty).<p>Our current work focuses on social vulnerability to floods using geostatistical modeling and mapping. The research directions are twofold. The first is to develop hazard-specific indicators of social vulnerability to aid in mitigation planning [<a href="https://doi.org/10.1007/s11069-020-04470-2" target="_blank" rel="noopener noreferrer"><em>Tate et al.</em></a>, 2021]. Because natural hazards differ in their innate characteristics (e.g., rate of onset, spatial extent), causal processes (e.g., urbanization, meteorology), and programmatic responses by government, manifestations of social vulnerability vary across hazards.</p><p>The second is to assess the degree to which socially vulnerable populations benefit from the leading disaster recovery programs [<a href="https://doi.org/10.1080/17477891.2019.1675578" target="_blank" rel="noopener noreferrer"><em>Emrich et al.</em></a>, 2020], such as the Federal Emergency Management Agency's (FEMA) <a href="https://www.fema.gov/individual-disaster-assistance" target="_blank" rel="noopener noreferrer">Individual Assistance</a> program and the U.S. Department of Housing and Urban Development's Community Development Block Grant (CDBG) <a href="https://www.hudexchange.info/programs/cdbg-dr/" target="_blank" rel="noopener noreferrer">Disaster Recovery</a> program. Both research directions posit social vulnerability indicators as potential measures of social equity.</p>
Social Vulnerability as a Measure of Equity<p>Given their focus on social marginalization and economic barriers, social vulnerability indicators are attracting growing scientific interest as measures of inequity resulting from disasters. Indeed, social vulnerability and inequity are related concepts. Social vulnerability research explores the differential susceptibilities and capacities of disaster-affected populations, whereas social equity analyses tend to focus on population disparities in the allocation of resources for hazard mitigation and disaster recovery. Interventions with an equity focus emphasize full and equal resource access for all people with unmet disaster needs.</p><p>Yet newer studies of inequity in disaster programs have documented troubling disparities in income, race, and home ownership among those who <a href="https://eos.org/articles/equity-concerns-raised-in-federal-flood-property-buyouts" target="_blank">participate in flood buyout programs</a>, are <a href="https://www.eenews.net/stories/1063477407" target="_blank" rel="noopener noreferrer">eligible for postdisaster loans</a>, receive short-term recovery assistance [<a href="https://doi.org/10.1016/j.ijdrr.2020.102010" target="_blank" rel="noopener noreferrer"><em>Drakes et al.</em></a>, 2021], and have <a href="https://www.texastribune.org/2020/08/25/texas-natural-disasters--mental-health/" target="_blank" rel="noopener noreferrer">access to mental health services</a>. For example, a recent analysis of federal flood buyouts found racial privilege to be infused at multiple program stages and geographic scales, resulting in resources that disproportionately benefit whiter and more urban counties and neighborhoods [<a href="https://doi.org/10.1177/2378023120905439" target="_blank" rel="noopener noreferrer"><em>Elliott et al.</em></a>, 2020].</p><p>Investments in disaster risk reduction are largely prioritized on the basis of hazard modeling, historical impacts, and economic risk. Social equity, meanwhile, has been far less integrated into the considerations of public agencies for hazard and disaster management. But this situation may be beginning to shift. Following the adage of "what gets measured gets managed," social equity metrics are increasingly being inserted into disaster management.</p><p>At the national level, FEMA has <a href="https://www.fema.gov/news-release/20200220/fema-releases-affordability-framework-national-flood-insurance-program" target="_blank">developed options</a> to increase the affordability of flood insurance [Federal Emergency Management Agency, 2018]. At the subnational scale, Puerto Rico has integrated social vulnerability into its CDBG Mitigation Action Plan, expanding its considerations of risk beyond only economic factors. At the local level, Harris County, Texas, has begun using social vulnerability indicators alongside traditional measures of flood risk to introduce equity into the prioritization of flood mitigation projects [<a href="https://www.hcfcd.org/Portals/62/Resilience/Bond-Program/Prioritization-Framework/final_prioritization-framework-report_20190827.pdf?ver=2019-09-19-092535-743" target="_blank" rel="noopener noreferrer"><em>Harris County Flood Control District</em></a>, 2019].</p><p>Unfortunately, many existing measures of disaster equity fall short. They may be unidimensional, using single indicators such as income in places where underlying vulnerability processes suggest that a multidimensional measure like racialized poverty (Figure 2) would be more valid. And criteria presumed to be objective and neutral for determining resource allocation, such as economic loss and cost-benefit ratios, prioritize asset value over social equity. For example, following the <a href="http://www.cedar-rapids.org/discover_cedar_rapids/flood_of_2008/2008_flood_facts.php" target="_blank" rel="noopener noreferrer">2008 flooding</a> in Cedar Rapids, Iowa, cost-benefit criteria supported new flood protections for the city's central business district on the east side of the Cedar River but not for vulnerable populations and workforce housing on the west side.</p><p>Furthermore, many equity measures are aspatial or ahistorical, even though the roots of marginalization may lie in systemic and spatially explicit processes that originated long ago like redlining and urban renewal. More research is thus needed to understand which measures are most suitable for which social equity analyses.</p>
Challenges for Disaster Equity Analysis<p>Across studies that quantify, map, and analyze social vulnerability to natural hazards, modelers have faced recurrent measurement challenges, many of which also apply in measuring disaster equity (Table 1). The first is clearly establishing the purpose of an equity analysis by defining characteristics such as the end user and intended use, the type of hazard, and the disaster stage (i.e., mitigation, response, or recovery). Analyses using generalized indicators like the CDC Social Vulnerability Index may be appropriate for identifying broad areas of concern, whereas more detailed analyses are ideal for high-stakes decisions about budget allocations and project prioritization.</p>
By Jessica Corbett
Sen. Bernie Sanders on Tuesday was the lone progressive to vote against Tom Vilsack reprising his role as secretary of agriculture, citing concerns that progressive advocacy groups have been raising since even before President Joe Biden officially nominated the former Obama administration appointee.