Good Evidence? A 2013 Panel Discussion

A reader shared this with me (thanks MP), I was unaware that it was online. From 7 years ago …

Recording of a debate held at the Institute of Physics, 4th Feb 2013. Co-organised by Science Policy Research Unit, University of Sussex and the UCL’s department of Science & Technology Studies.

Policymakers often talk up the importance of evidence-based policy, with increasing calls for randomised controlled trials (RCTs) as the best way of testing whether particular interventions work. But finding and applying evidence in policy is anything but straightforard. Evidence alone rarely wins complex political arguments. Often this merely shifts the locus of debate to what counts as evidence.

Speakers: Roger Pielke Jr, Professor of Environmental Studies, University of Colorado at Boulder; Richard Horton, Editor of The Lancet; Georgina Mace, Professor of Biodiversity and Ecosystems, University College London; Jonathan Breckon, Alliance for Useful Evidence.

Chair: James Wilsdon, Professor in Science and Democracy, SPRU, University of Sussex.

Papers on Use and Misuse of Climate Scenarios


Non-technical overview: Pielke, Jr. R. (2018). Opening up the climate policy envelope. Issues in Science and Technology34(4), 30-36.

Detailed history and critique: Pielke, Jr. R. and Ritchie, J., Systemic Misuse of Scenarios in Climate Research and Assessment (April 21, 2020). Available at SSRN:

Quantitative evaluation (GDP and CO2): Burgess, M. G., Ritchie, J., Shapland, J., & Pielke, R., Jr. (2020, February 18). IPCC baseline scenarios over-project CO2 emissions and economic growth.

Quantitative evaluation (energy intensity and carbon intensity, AR5): Stevenson, S., & Pielke Jr, R. (2018). Assumptions of Spontaneous Decarbonization in the IPCC AR5 Baseline Scenarios. (PDF)

Quantitative evaluation (energy intensity and carbon intensity, AR4): Pielke, R., Wigley, T., & Green, C. (2008). Dangerous assumptions. Nature, 452(7187), 531-532. (PDF)

Case study (tropical cyclones): Pielke Jr, R. A. (2007). Future economic damage from tropical cyclones: sensitivities to societal and climate changesPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences365(1860), 2717-2729.

Case study (disaster loss projections): Pielke Jr, R. (2007). Mistreatment of the economic impacts of extreme events in the Stern Review Report on the Economics of Climate Change. Global Environmental Change, 17(3-4), 302-310.

Case study (tropical cyclones): Pielke Jr, R. A., Klein, R., & Sarewitz, D. (2000). Turning the big knob: An evaluation of the use of energy policy to modulate future climate impactsEnergy & Environment11(3), 255-275.

More general discussion: Pielke Jr, R. A. (2003). The role of models in prediction for decision. Models in ecosystem science, 111-135. (PDF)

Covid-19 Resources for Research and Teaching: Models and Forecasts

MIDAS – Online Portal for COVID-19 Modeling Research (link)

U.K.  Scientific Pandemic Influenza Group on Modelling (SPI-M) Modelling
Summary (2018 report, link) (advisory subcommittee)

Public Health Agency of Canada, 2020. COVID-19 in Canada: Using data and modelling to inform public health action: Technical Briefing for Canadians, 9 April (PDF).

Begley, S. 2020. Influential Covid-19 model uses flawed methods and shouldn’t guide U.S. policies, critics say, Stat, 17 April.

Bender, M. and R. Ballhaus, 2020. Trump’s Coronavirus Focus Shifts to Reopening Economy, Defending His Response, The Washington Post, 17 April.

Wan, W. and C. Johnson, 2020. America’s most influential coronavirus model just revised its estimates downward. But not every model agrees. The Washington Post, 8 April.

Wan, W. 2020. Experts and Trump’s advisers doubt White House’s 240,000 coronavirus deaths estimate, The Washington Post, 2 April.

Koerth et al. 2020. Why It’s So Freaking Hard To Make A Good COVID-19 Model, FiveThirtyEight, 31 March.

Wan, W. and A. Blake, 2020. Coronavirus modelers factor in new public health risk: Accusations their work is a hoax, The Washington Post, 27 March.

IHME Covid-19 Projections (link) based on: IHME COVID-19 health service utilization forecasting team. Forecasting COVID-19 impact on hospital bed-days, ICU-days, ventilator days and deaths by US state in the next 4 months. MedRxiv. 26 March 2020.

Enserink, M. and K. Kupferschmidt, 2020. Mathematics of life and death: How disease models shape national shutdowns and other pandemic policies, Science, 25 March.

Rivers, C. et al. 2020. Modernizing and Expanding Outbreak Science to Support Better Decision Making During Public Health Crises: Lessons for COVID-19 and Beyond, Johns Hopkins Center for Health Security, 24 March. (PDF).

Rivers, C., Chretien, J.P., Riley, S., Pavlin, J.A., Woodward, A., Brett-Major, D., Berry, I.M., Morton, L., Jarman, R.G., Biggerstaff, M. and Johansson, M.A., 2019. Using “outbreak science” to strengthen the use of models during epidemicsNature communications10(1), pp.1-3.

Chowell, G., Sattenspiel, L., Bansal, S., & Viboud, C. (2016). Mathematical models to characterize early epidemic growth: A reviewPhysics of life reviews18, 66-97.

Glasser, J. W., Hupert, N., McCauley, M. M., & Hatchett, R. (2011). Modeling and public health emergency responses: Lessons from SARSEpidemics3(1), 32-37.

Fealty Trumps Truth


The figure above shows published estimates of “R naught” (or R0) a measure of the contagiousness of coronavirus (from Liu et al. 2020, published 13 Feb). The figure shows that 13 different estimates of R0 were published during the month of January 2020, and these estimates ranged from ~2 to >6, indicating that coronavirus was highly contagious.

Thus, when Dr. Deborah Birx said today that “it wasn’t until the beginning of March that we could all fully see how contagious this virus was” she is either lying or revealing complete incompetence. Strong words, yes, but there is no other choice. Dr. Birx is a political appointee by Donald Trump and it appears that fealty trumps truth.

See the comments of Dr. Birx below.

Did the Trump Administration Delay the WHO Emergency Declaration?


Yesterday in the White House Rose Garden, President Trump announced that the U.S. government would be suspending payments to the World Health Organization. Among the president’s complaints was this: “The delays the WHO experienced in declaring a public health emergency caused valuable time, tremendous amounts of time.”

Here I take a look at this claim, and conclude that the United States government either contributed to the delay in the WHO emergency declaration or the US government outsourced its decision to the WHO to declare a domestic emergency declaration — which occurred only after the WHO eventually declared a global emergency.

Let’s look at the facts.

Continue reading “Did the Trump Administration Delay the WHO Emergency Declaration?”

Eight Weeks Behind: Clarifying the Early U.S. Coronavirus Testing Failure


Bottom line: It is normal for the US government to develop its own disease testing under CDC. Experts in CDC are typically very good at it. But in the case of coronavirus, the US government developed a flawed test, creating lengthy delays in testing and in parallel left obstacles in place that would have shortened the delay. Meanwhile, U.S. government officials have repeatedly misled the public and policy makers. In total, more than 8 weeks were lost due to policy failure. This post explains and documents this remarkable policy failure.

Continue reading “Eight Weeks Behind: Clarifying the Early U.S. Coronavirus Testing Failure”

Covid-19 Resources for Research and Teaching: Pielke Analysis and Commentary

Podcast: COVID Knowledge, Technology, and Politics: Dispatches from Around the World (20 April)

Pielke, Jr. R. 2020. Fealty Trumps Truth, 19 April.

Pielke, Jr., R. 2020. Did the Trump Administration Delay the WHO Emergency Declaration? 15 April.

Pielke, Jr. R. 2020. Eight Weeks Behind: Clarifying the Early U.S. Coronavirus Testing Failure, 13 April.

Pielke, Jr., R. 2020. Why Isn’t the White House Using the Nation’s Pandemic Experts? Slate, 10 April.

Covid-19 Resources for Research and Teaching


This set of resources related to Coronavirus and COVID-19 is focused on science advice and policy evaluation. It is intended to support my professional research and teaching, and if you find it useful, so much the better. It is the next iteration of an earlier syllabus, that became too unwieldy due to the amount of materials.

Updated 20 April 2020

Pielke Analysis and Commentary

Current COVID-19 Information

COVID-19 Scenarios and Dynamics

Models and Forecasts

Science Advice and Emergency Situations

COVID-19 Policy Options and Evaluation

United States Pandemic Policy and Planning

Unheeded Warnings

Pandemics, Society, Politics and Policy Dynamics

Pandemics, SARS-Cov-2 and Relevant Research

Tools and Training