Data and Disinformation during Pandemics


Five months into 2020, and COVID-19 continues to rage. In the span of a few months we’ve come from an environment of too little data into one of too much data and yet our collective knowledge about the virus, its extent, and implications remains limited. Let’s discuss the emerging data and disinformation trends about the pandemic, how to safeguard ourselves from spreading fake news, and how to regard and understand the expert opinions we read online.

We had a great podcast where we discussed:

  • Are we being petty with pointing out data errors?
  • Politicization of COVID-19
  • Bogus cures, inaccurate forecasts, armchair epidemiology
  • Debunking conspiracy theories about COVID-19
  • Dealing with data quality during a crisis
  • Too many experts and policy notes on Facebook
  • All models are wrong, some are helpful, but which?
  • Nowcasting and Forecasting: context over curve fitting
  • The question of significance: what 1% means
  • Over-reading political motivations behind data issues
  • Science, academics, and fear of criticism
  • Critical thinking during pandemics

In this fourth in a series of web-casts focusing on the pandemic, we are joined by two professionals who have made their careers seeking deeper truths behind the facts we see everyday.

About Our Guest Panelists


Aurora Almendral is an award-winning, multi-platform journalist, currently a contributing writer for The New York Times and National Geographic Magazine and a producer-reporter for NBC News. Aurora has reported on disaster, climate change, human trafficking, migration, business, politics, crime and culture. She was among the first foreign journalists to cover the violent drug war in the Philippines, and went on to produce expansive work on the subject, from the fervent support for the president, to the spectacles of execution and the unflinching reality of grief. Her work has taken her crocodile hunting in distant jungle islands, onboard a 432-foot cargo ship and into the world’s most crowded jails, as well as the back rooms of power while investigating the murky borderlands between business and politics in an authoritarian regime.


Dr. Peter Cayton is associate professor at the University of the Philippines School of Statistics. Peter has been at the data forefront of the Philippines’ fight against COVID-19 as part of the UP Pandemic Response Team. His modeling is behind some of the crucial statistics being used to monitor the extent of the pandemic which includes outbreak thresholds and case fatality rates. Dr. Cayton was one of the first to publicly calculate and share the important Time Varying Reproductive Number (Rt) statistic for the Philippines which measures the transmission rate of COVID-19 cases. Through Peter’s efforts, Rt is now being published daily at the regional, provincial and city level. He is also a member of the LEADS 4 HSR Consortium (L4H), which brings together public health specialists, data scientists, and epidemiologists to fight COVID-19 using data.