Deborah Nelson, Professor of Investigative Journalism at University of Maryland, and freelance reporter for Reuters dnelson4@umd.edu �

Ryan McNeill, Deputy Data Journalism Editor, Reuter ryan.mcneill@thomsonreuters.com

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GIJC 2023 Pandemics Past and Future Panel

Tipsheet: tinyurl.com/GIJC23Spillover

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Pandemics: What the past tells us

about the future

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Investigating local risks and global threats

I have typed my remarks directly into the slides to help those who understand written English better than spoken

(especially when spoken in a heavy Chicago accent like mine)

Tipsheet: tinyurl.com/GIJC23Spillover

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But first….

In spring 2020, Reuters asked me to help investigate how the pandemic started. In the months ahead, debate grew increasingly politicized and acrimonious on whether the virus came from a lab or the wild.

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Meanwhile, Chinese authorities had a stranglehold on whatever evidence did exist.

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It became clear we would not have a definitive answer anytime soon if ever.

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With many excellent journalists in pursuit of that important story, I asked to pursue a different one -- also important -- that emerged from my early research.

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I'd been reading about past outbreaks on Google Scholar to try to understand this one...

.....and was struck by how frequently they happen.

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We hear about the big ones.

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But they are happening all the time on a smaller scale, a drumbeat of tragedy, each claiming 1 life or 10 or 100, with unpredictable potential to turn into something much bigger in the right circumstances.

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It seemed less a question of whether

something bigger would happen

than when, where and how.

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A little science-y background:

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Most human viruses initially came from animals.

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The jump from animals is called zoonotic spillover.

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And some of the deadliest new viruses in the last half century have been linked to bats.* They are a leading incubator for viruses..

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(Even though we don't know yet how people were first infected by SARS-CoV-2, we know it’s related to a family of viruses, found in certain bat species, that started the SARS pandemic in China in 2003.)

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SARS, Ebola, Nipah, Marburg – all are on WHO’s list of priority pathogens that have potential to cause epidemics.

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The first 3 already have.

DON’T BLAME THE BATS! THE EARTH NEEDS THEM! (We are the problem.)

Some are natural -- like precipitation and temperature.

I was intrigued by the growing body of scientific evidence

linking spillover to environmental factors.

Others are tied to human activity: tree loss, urbanization, intensive farming

The loss of habitat increases contact among different types of animals, which helps viruses to mutate and spread. And it increases contact with people, so more opportunities for the germs to jump. There’s also evidence the stress actually makes bats shed more virus.

While doing some deep reading on the subject, I also came across a spillover database from the past 20 years. I found a reference to it in a footnote* of a report. The data is maintained by Gingko, a public benefit company, and includes location information for the start of each outbreak.

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* I footnotes

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He thought we may be able to use the data on past outbreaks to predict where future ones may occur by:

1. geolocating where past outbreaks began
2. analyzing environmenetal conditions at the sites
3. identifying where else on earth similar conditions exist.

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So that’s what we did…

I mentioned all this to my longtime reporting partner Ryan McNeill, a brilliant data journalist at Reuters. (He's here and doing a panel tomorrow at 9:15 on investigating climate change impacts.)

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Ryan and Allison Martell developed a machine learning model -- in consultation with scientists -- that used satellite imagery in combination with other data to examine conditions around 95 locations of bat-virus spillovers between 2002 and 2020.

For more info: tinyurl.com/Batlandsmethod

Even finer: The Researchers at the company provided us with a list of spillovers of diseases in which bats are the reservoirs. Ryan and Allison Martell, another Reuters data journalist mined studies, public health records and other documents to vet the list and expand on it. Then they geolocated and mapped each spillover. Ryan built a dataset of 56 covariates at a 25-square-kilometer resolution. Bat species richness was calculated from IUCN Red List data. Most of the others came from satellites, including elevation, land surface temperatures, precipitation, land cover and tree loss.

I won’t read the rest of this slide but you can later!

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Tipsheet: tinyurl.com/GIJC23Spillover

Based on that analysis, they identified other places where similar conditions exist. We called those scoring in the 95^th percentile “JUMP ZONES.”

Jump zones = the highest risk areas on earth for spillover.

In other words: potential starting points for future outbreaks, epidemics, pandemics.

WHAT WE FOUND:

• The number of people living in areas at highest risk for spillover has grown by 57% over the two decades ending in 2020.

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WHAT WE FOUND:

• The number of people living in areas at highest risk for spillover has grown by 57% over the two decades.

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• Nearly 1.8 billion people -- 1 of 5 on the planet – now live in these areas.

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WHAT WE FOUND:

• The number of people living in areas at highest risk for spillover has grown by 57% over the two decades.

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• Nearly 1.8 billion people -- 1 of 5 on the planet -- now live in these areas.

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• They cover more than 9 million sq km in 113 countries on every continent except Antarctica.

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WHAT WE FOUND:

• The number of people living in areas at highest risk for spillover, mostly tropical locales rich in bats and undergoing rapid urbanization, has grown by 57% over the two decades.

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• Nearly 1.8 billion people -- 1 of 5 on the planet -- now live in these areas.

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• They cover more than 9 million sq km in 113 countries on every continent except Antartica.

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• Nearly all (99%) are in low- and middle-income countries across Asia, Africa and Latin America.

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WHAT WE FOUND:

• The number of people living in areas at highest risk for spillover, mostly tropical locales rich in bats and undergoing rapid urbanization, has grown by 57% over the two decades.
• Nearly 1.8 billion people -- 1 of 5 on the planet -- now live in these areas.

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• Human incursions have created a minefield of risk covering more than 9 million sq km in 113 countries on every continent except Antartica.

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• Nearly all (99%) of the highest-risk areas are in low- and middle-income countries across Asia, Africa and Latin America.

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• But much of the deforestation and development in those places is driven by demand by wealthier countries for raw materials.

WHY IS THIS IMPORTANT?

Here is what public health authorities, experts and intergovernmental agencies working on this issue told us. Identifying local hotspots of risk is important to:

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• focus limited resources where they are most needed surveillance, early detection and response, biosafety

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• address outbreak risk in development decisions on vulnerable areas and ways to mitigate it through conservation, buffer zones, wildlife corridors..

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• tailor public education campaigns and solutions to local customs and economics

Since 2020 (the last year of our analysis) there have been..

• 7 Ebola and Marburg outbreaks reported in Africa.
• >20 Nipah outbreaks reported in Bangladesh and India, most recently 2 weeks ago in Kerala, India -- its 4th appearance there in 5 years.
• All in jump zones identified in our analysis -- including some places that had no previous known occurrences of the virus.

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A sobering proof of concept

We asked scientists

why many high-risk places had not yet had an outbreak.

Their response:

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We asked scientists

why many high-risk places had not yet had an outbreak.

Their response:

“Luck”

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WHERE TO GO FROM HERE

The analysis told us what and where. But it takes investigative ground truthing to determine how, who and why – essential questions to inform the public and hold government accountable.

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We did that in several places – I’ll talk about that next -- but we didn’t have the wherewithal to go deep in 113 countries.

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Some questions to investigate:

1. What are the local and global economic forces driving up risks?
2. What are governments doing to reduce the risks?
3. What are they doing to prepare for when outbreaks happen?
4. How are they holding the beneficiaries -- wealthy countries and companies -- accountable?

Tipsheet: tinyurl.com/GIJC23Spillover

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GROUND-TRUTHING THE DATA

Tipsheet: tinyurl.com/GIJC23Spillover

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We used the analysis to zero-in on specific locations to better understand the changes that turned them into hotspots…. and to help to decide where to put reporters’ feet on the ground

…or drones in the air…

…in order to report on local dynamics that couldn’t be seen from the satellites or measured in the data.

IN INDIA

The data identified a dramatic increase in risk in the state of Kerala in the years leading up to Nipah’s first known appearance there in 2018.

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The view from the sky on Google Earth Pro, showed rapid urbanization of once heavily wooded areas.

(Try this at home!)

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On the ground with reporter Sreekanth Sivadasan, we found backyards full of fruit trees and colonies of a type fruit bats known to carry of Nipah, roosting in nearby trees Their natural food sources gone, they’d raid the gardens at night. Unaware of the danger, residents would pick up and eat the discarded fruit. Scientists told us the virus from an infected bat’s saliva could survive days on a piece of fruit.

Throughout West Africa, where the 2013 Ebola epidemic killed more than 11,000 people, the data showed governments are granting scores of mining concessions in ecologically risky areas without requiring companies to assess and address the dangers.

The view on the ground in Ghana, where Marburg virus made its first known appearance last year.

RECIPE

1. Research the science.

• What questions do you want your project to answer?
• After framing the questions, type them into a Google Scholar search box. Are there studies that have been asking the same or related questions?
• You can zero in on particular countries, districts or even towns by including the name in the search terms.

2. Mine the studies.

• Mine the top for experts in the list of authors.
• Mine the middle for methodology.
• Mine the bottom for data sources -- in the footnotes and supplements -- that you can access and analyze yourself.

3. Ground truth the data, whether your own or from studies.

• Visit locations in person if possible. In not, visit virtually through multiple sources: satellite, street view mapping, social media (using verification tools) and trusted sources on the ground.

4. Don't try this alone.

• Consult with scientists and statisticians in developing your methodology, interpreting your findings and translating the science into words and graphics.

Tipsheet: tinyurl.com/GIJC23Spillover

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TIPS FOR WORKING WITH SCIENTISTS:

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• Check back to make sure you're translating their words and science accurately in your story. They will be more willing to help if they know you’ll do this.

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• Be mindful of their expertise. Research on zoonotic outbreaks is often done by an interdisciplinary team of experts in epidemiology, virology, veterinary science and environment. Don't rely on an epidemiologist as your primary source on veterinary science or a virologist on the environment.

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• ALWAYS ask how they know. What is the evidence? Where does it come from? Can it be interpreted differently? If so, why do they interpret it the way they do? Do this even if someone’s a leading expert and frequently quoted.

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• Verify verify verify. Check for letters and comments on their studies. Look for other peer-reviewed studies on the same topic. Talk to multiple experts. In the current environment: Get to know the influencers. Follow them on X/Twitter, so you can identify which are trolls versus less biased (no one is unbiased).

Tipsheet: tinyurl.com/GIJC23Spillover

Resources to track environmental changes locally, nationally, regionally, globally

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• GIJN's Resources for Finding and Using Satellite Data -- a tipsheet that Ryan, Toby McIntosh and I just updated – has links to a wide range of free satellite data sources, tutorials and experts.
• Google Earth Pro on desktop provides satellite and street views. It has historical imagery and an–easy-to-use tool for tracking changes over time.
• Global Forest Watch provides free access to satellite data to track tree loss and deforestation plus tools to embed maps and to set up customized deforestation and fire alerts for places of interest. They produce a journalist user guide and staff is available to help. Contact Kaitlyn.Thayer@wri.org
• Global Forest Change on Google Earth Engine allows you to track changes to land cover over time and includes a tutorial on how to use it.
• The Google News Initiative also has journalist-friendly tutorials on Google Earth Engine , such as how to create time-lapse videos.
• Radiant Earth Foundation provides tools and tutorials for accessing satellite, drone, and aerial imagery to track climate climate change and conservation issues.
• WorldPop is a collaborative organization that provides data and analysis of population trends and demographics at the global, regional and local level.

Tipsheet: tinyurl.com/GIJC23Spillover

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You can access slides, tipsheets and the supplements below

at tinyurl.com/GIJC23Spillover and (soon) at GIJN.org

Biggest reporting challenge: Laos.

Jump zones more than doubled to 73%

-- a bigger % increase than any other country

That was accompanied by a 19% increase in tree loss.

To figure out what was driving those changes and to understand the risks they were creating, we needed to know what was happening on the ground.

The challenge: Laos is not a historically open country.

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We grabbed jigsaw pieces from every resource we could find to see that much of the changes was being driven by development to demand from its northern neighbor China for rubber, cassava and other cash crops and raw materials:

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In the research papers, we found a 2017 paper detailing the discovery of coronaviruses in bats for sale at markets across Laos.

The paper's data showed us the widespread nature of risky human contact with bats….

... and provided the locations of those markets that allowed us to:

• verify that bats were still being sold
• photograph the evidence and….

…map their location in our risk analysis

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Last year, a team led by Pasteur Institute scientists detailed the discovery of sarbecoviruses, infectious to humans, in bats tested in a few locations across northern Laos. They included the closest relative of SARS-CoV-2.

The studies included the lat/long of the locations, so we could dig deeper into what was happening in the surroundings – for example, a thriving industry mining caves for bat guano (feces) to sell as fertilizer….

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… and a station stop on a new high-speed train financed by China and expected to bring in a flood of tourists and commerce….

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You can access slides, tipsheets and the supplements below

at tinyurl.com/GIJC23Spillover and (later) at GIJN.org