The COVID-19 pandemic highlighted several lessons for emergency management. It showed that while pandemics can't be predicted precisely, they are not unexpected occurrences. COVID-19 shared many similarities to the 1918 influenza pandemic in its transmission, symptoms, and impact. Managing the pandemic required balancing public health measures to control the spread of the virus with economic concerns, and different countries had varying levels of success with their responses. The pandemic significantly impacted critical infrastructure sectors and underscored the importance of protecting essential workers. It also demonstrated the power of misinformation spread on social media and the need for transparent, fact-based risk communication. Data analytics proved crucial for decision-making during the dynamic pandemic. The role of emergency management was challenged by the prolonged

1. COVID-19
Jose Laredo
April 2021
An Emergency Management Perspective

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Some definitions
• Disaster (BCI/DRJ): A sudden, unplanned catastrophic event causing unacceptable damage or loss
• Disaster (UNDRR) a serious disruption of the functioning of a community or society involving
widespread human, material, economic or environmental losses and impacts, which exceeds the
ability of the affected community or society
• Emergency (ISO 22399): Sudden, urgent, usually unexpected occurrence or event requiring
immediate action
• Epidemic (CDC) refers to an increase, often sudden, in the number of cases of a disease above
what is normally expected in that population in that area
• Mass Casualty Incident (WHO): an overwhelming event, which generates more patients at a time
than locally available resources can manage using routine procedures
• Pandemic (FFIEC): An epidemic or infectious disease that can have a worldwide impact
• Pandemic (The International Epidemiology Association): epidemic occurring worldwide, or over a
very wide area, crossing international boundaries and usually affecting a large number of people
The terms used are similar, but under certain circumstances these definitions may lead to different
categorizations and responses to epidemic/disasters/pandemics/emergencies
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3. JL Covid-19 Lessons Learned 3
Content
Why to have lessons learned
01
Was Covid-19 unexpected?
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1918 Influenza vs Covid-19
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Covid-19: protect people’s health
or the economy?
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05
Impact on Critical Infrastructure
Sectors
06
Misinformation: The Pandemic
of the social media age
Leadership during Covid-19
Data Analytics
Role of Emergency Management
Human & Social behavior
References
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08
09
10
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Actions, collaboration and
leadership

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Why to have lessons learned ?
• Disasters are tragedies, that can be used to understand the physical, economical,
and social factors governing them.
• Information gathered throughout the disaster: beginning, initial responses,
adjustments, which measures failed/improved, etc. may lead to consolidated best
practices during the disaster
• Information collected can be used to enhance the effectiveness of risk
assessments, awareness, mitigation, preparedness, prediction, and response to
other emergencies/disasters.
• Climate change may lead to future global crisis/emergencies; and health,
political and economic systems may need to be adapted to deal with new risks.
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Was Covid-19 something totally unexpected?
• Pandemics have happened from time to time since the mankind has been on earth
• Three great world pandemics have been recorded in history before 19th century: in 541 - Justinian
plague, 1347 -Black death, and 1894 -The third pandemic. They killed about 40 MM, 200 MM, and
12 MM respectively. Covid-19 may reach 4-5 MM in the following months by the end of the
pandemics
• As an average, three pandemics may happen in a century (David Finnoff, University of Wyoming
College of Business). In the 20th century we had three: 1918, 1957, and 1968. By 2019, the world
hadn’t had a pandemic for 50 years.
• Lately, the world has had viral outbreaks: SARS in 2002/2003, the swine flu (H1N1) in 2009, MERS in
2012, Ebola in 2014 to 2016, Zika in 2015 and Dengue fever in 2016.
• The WHO mentioned the chances for a pandemic in an event in September 2019. Known Speakers
such as Bill Gates and Laurie Garrett predicted, a pandemic event in the foreseeable future
• The World Health Organization declared Covid-19 a pandemic on March 11,2020.
Covid-19 was not a black swam event or something entirely unpredictable with huge impact
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1918 Influenza versus Covid-19
Covid-19 characteristics are very similar to 1918 Influenza
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1918 Influenza COVID-19
Years 1918-1920 2020–present
Worldwide deaths Approx. 40 MM people Estimated 4-5MM by the end
Virus H1N1 influenza virus SARS-CoV-2 coronavirus
Transmission airborne, droplets, contaminated surfaces airborne, droplets, contaminated surfaces
Contagiousness
starts
from 1 day before symptoms begin until 5 to 7 days
after becoming sick
from 2-3 days before symptoms begin until 10
days after testing positive
Symptoms
fever, muscle aches, headache, and respiratory
symptoms most common
Similar symptoms to influenza, and also loss of
smell and taste
Symptom onset After 1 to 4 days Gradual after 2 to 14 days
Age ++ impacted 25-40 over age 65
Illness severity 94–98 percent mild 80 percent mild, 20 percent severe or critical
Other mortality
factors
Many people died because of poorer hygiene, public
health and safety
More advanced medical care and public health
systems
Complications
Pneumonia and other bacterial infections,
worsening of underlying health conditions,
Similar to influenza but also long-haul COVID-19,
and blood clots

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Covid-19: protect people’s health or the economy?
• Restrictive public health measures reduce human costs but impact negatively the economy; however,
some countries have performed better than others: New Zealand, Australia, Vietnam, Taiwan etc.
• Lockdowns and restriction cannot go on too long because the economic consequences could be even
more complicated than the disease; thus, a coordinated plan is necessary for public health purposes
and the economy
• There is a need to assess the different variables that may influence the response to the Pandemic; at
first glance, it looks like all factors are intertwined; let’s see them in the following slides.
A Pandemic misery index combines excess mortality rates
and unemployment by country, and it’s used to compare
results obtained by countries. The USA has the lowest
position in this index.
Source: A pandemic ‘misery index’: Ranking countries’ economic
and health performance during Covid-19, Tim Vlandas, Associate
Professor of Comparative Social Policy at the University of Oxford.
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Actions, collaboration and leadership
Leadership
Social &
Human
behavior
Infrastructure,
supplies &
staff
Prioritization of
affected people
and CI staff
Comms.
Campaign
Emerg. Mgmt.
Activities
Data Analytics
& Reports
Baseline
There could be many
cycles and interactions
depending on waves,
policies; variants of
concern, people’s
response, economy,
resources, etc., or other
emergencies, or disasters
that may happen at the
same time
Having a comprehensive strategy is a very difficult challenge. Organizations must be agile and flexible
for an endless number of scenarios.
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Impact on Critical Infrastructure (CI) Sectors
• CI sectors provide essential services
necessary for the security, economic
prosperity, and health and safety
(H&S) of Nations.
• Covid-19 impacts on the H&S of
workers may impede the normal
functioning of each CI sector
• Some CI staff may work from home,
increasing Cyber Security risks*
• CI staff who work on-site have a higher
risk of infection: public transit, closed
spaces, etc.
Healthcare &
Public Health
Manufacturing
& Supply Chains
Finance
Food
Transportation Government
I. &Comm.
Technology
Water
Safety
Energy
Providing health services to vulnerable people should be prioritized, and next Critical Infrastructure
staff
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* Note: An important topic not to be discussed here

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Misinformation: The Pandemic of the social media age
Overabundance of Covid-19 false information has caused many problems. Two main types:
1 - Misinformation: unfounded medical advice which is not accurate but unintentional; it creates problems
off-line when people follow those bad recommendations (e.g. hot water, vitamins, high-acid foods)
2 - Disinformation: false, harmful and misleading content which is shared to cause harm. There are two
types: (a) created by people who want to benefit $$ from “snake oil” products (e.g. chlorine dioxide), and
(b) ideologically driven people (or “enemies”) who sow seeds of doubt and division (e.g. people against
vaccines, anti-masks, 5G virus, Covid-19 is like a flu, natural immunity is better, etc.)
• False information leads to low levels of confidence among citizens (e.g. vaccine hesitancy). People need
to process conflicting information and make sense of it.
• Misinformation threatens the compliance with measures against the Pandemic; thus, it may be
considered as an offence to public health, the economy, and the social fabric.
• All information should be transparent and based on data science & behavioral analytics
• Public health promises must be matched with the capabilities to deliver
Right information is crucial to obtain support and participation from people to fight Covid-19. Authorities
should use all means, technology, and various communications methods to reach all audiences
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Data Analytics
• The various Pandemic fronts require fast evidence based decisions: health care, supplies,
vulnerable groups identification, clinical trials, therapies results, etc.
• At the beginning of the pandemics, decision makers had very limited scientific information, there
was an urgent need for data and process analytics
• Data analytics provide visualization capabilities that allow all stakeholders to identify patterns and
propose solutions to the challenges raised by the ongoing pandemic
• Internet searches, mobile applications, and social media usage, may be stored, processed,
summarized and presented to decision makers fast enough to have an idea of the Covid-19
common operating picture at certain point in time.
• Information should focus on the impact, evolution, and trends of the pandemic itself, medical
situation, governmental actions, public reactions, and social media activity
• Data analytics could help epidemiological scientists understand how the virus spread and its
impact on people: by age, by gender, ethnicity, income level, postal code, severity, variants of
concern, beds occupied, ICU usage, supplies levels, testing, trends, etc.
Data analytics may help to understand leaders, scientists, medical doctors, emergency management
and other stakeholders many details of the Pandemic: evolution, impact, policy responses, etc.
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Role of Emergency Management (EM)
• Before Covid-19, EM staff could have developed a Pandemic plan which includes prevention, mitigation,
preparedness, response, and recovery activities to create awareness, understanding of the risks, and
alternative actions available to deal with the pandemic.
• Based on the After-Action Reports of pandemic exercises, mutual aid agreements or contracts with
other jurisdictions, partners or suppliers should be established before the actual event, technological
tools should be considered to work online, Governance structure for disasters, and organization
boilerplates ready to be adapted.
• All private, public organizations regardless of their size may need to identify, assess and take actions
with other stakeholders, EM staff and Emergency Operations Centers could be use as hubs for
coordination and information sharing, including scientific modelling, health results, and its impact to
other CI sectors, and for releasing regular situational reports and recommendations to decision makers
• Covid-19 could be considered as a prolonged mass casualty incident, that may coincide with other
disasters (e.g. earthquakes, flooding, fires, power outages, etc.). EM staff should have plans to respond
to simultaneous disasters (e.g. surge capacity, critical infrastructure impact, public/cyber security,
evacuations, shelters, loss of facilities, etc.)
Emergency management plays a pivotal role during incidents, emergencies, crises, disasters, and the
Covid-19 pandemic
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Leadership during Covid-19
• Leaders dealing with Covid-19 have limited information, several unknowns, and the need to respond
quickly to different scenarios prioritizing the wellbeing of people
• Even if there was a previous Pandemic plan, Leaders need to adapt it, anticipate new challenges, and
articulate strict rapid responses based on health, economy and what may happen if an action is
delayed
• In a complex situation like Covid-19, a taskforce should be gathered to coordinate actions and provide
advice in different areas with the best available knowledge; e.g. science, public health, analytics, etc.
Leaders should always consider these recommendations
• Truth and empathy should prevail at all time, neither fear creation nor downplaying the risks about
Covid-19, and avoiding loss of trust and anxiety in people
• Leader must work to obtain trust and confidence from people; this is the baseline for the successful
implementation of public health measures. Bad leaders erode the social response in the Pandemic
Leaders should inspire confidence to their people, by being confident and trustworthy, committed to
overcoming Covid-19 challenges, and acting decisively
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Human & Social behavior
• Explaining the risks of COVID-19 to people may not change their attitudes/behaviors; even if people
understand and accept the facts, people count more on the potential magnitude of the effect rather
than the probability of getting sick
• This risk perception is different by age, education, income, etc. by each one and also as a group. These
behaviors may lead to different acceptance levels to public health recommendations
• There is a need to evaluate different factors to motivate a community to accept Covid-19
recommendations: threat perceptions, collective interests, social context, and mental health
• Covid-19 has been evolving in medical treatment, practices, etc.; thus uncertainty needs to be
acknowledged and informed based on the group culture. Segmentation strategies should be used for
specific actions when the group is large and diverse. Covid-19 policies should consider these factors
• Understanding how Covid-19 policies interact with social and personal behaviors is critical to measure
the policies impact on transmission dynamics
Behavioural Science may help authorities to persuade people to follow Covid-19 recommendations
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References (1/4)
• https://apps.who.int/gpmb/assets/annual_report/GPMB_annualreport_2019.pdf
• https://www.dw.com/en/world-unprepared-for-pandemic-panel-warns/a-50471785
• https://www.ted.com/talks/bill_gates_the_next_outbreak_we_re_not_ready
• Book “The coming Plague” – Laurie Garret
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7874133/
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7123574/
• https://www.weforum.org/agenda/2020/03/coronavirus-great-influenza-pandemic-covid19-prepared-
outbreak/
• https://www.cdc.gov/flu/pandemic-resources/1918-commemoration/three-waves.htm
• https://www.who.int/emergencies/diseases/novel-coronavirus-2019/question-and-answers-hub/q-a-
detail/coronavirus-disease-covid-19-similarities-and-differences-with-influenza
• https://www.slideshare.net/webmaster_wfd101/pandemic-flu-presentation-presentation
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7292046/
• https://www.sciencedirect.com/science/article/pii/S1201971220305117
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References (2/4)
• https://www.oecd.org/coronavirus/policy-responses/transparency-communication-and-trust-the-role-of-
public-communication-in-responding-to-the-wave-of-disinformation-about-the-new-coronavirus-bef7ad6e/
• https://www150.statcan.gc.ca/n1/pub/45-28-0001/2021001/article/00003-eng.htm
• https://hbr.org/2020/09/5-principles-to-guide-adaptive-leadership
• https://bmjleader.bmj.com/content/early/2020/09/29/leader-2020-000271
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333999/
• https://www.vox.com/2020/10/2/21498493/trump-coronavirus-bolsonaro-johnson
• https://www.vox.com/2020/10/2/21498493/trump-coronavirus-bolsonaro-johnson
• https://theconversation.com/donald-trump-boris-johnson-and-the-dangers-of-excessive-positivity-146356
• https://www.cmswire.com/information-management/how-data-analytics-are-gaining-ground-during-covid-
19/
• https://penntoday.upenn.edu/news/role-data-world-reshaped-covid-19
• https://www.healthline.com/health/h1n1-vs-covid-19#quick-comparison-table
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References (3/4)
• https://mitsloan.mit.edu/ideas-made-to-matter/how-covid-19-disrupting-data-analytics-strategies
• https://opendatawatch.com/what-is-being-said/data-in-the-time-of-covid-19/
• https://www.itproportal.com/features/taking-a-step-back-reflections-on-data-analytics-during-covid-
19/
• https://healthitanalytics.com/news/intersection-of-big-data-analytics-covid-19-top-focus-of-2020
• https://govinsider.asia/health/aws-amazon-web-services-cloud-the-importance-of-data-in-the-fight-
against-covid-19/
• https://pmj.bmj.com/content/early/2021/02/08/postgradmedj-2020-139070
• https://govinsider.asia/health/aws-amazon-web-services-cloud-the-importance-of-data-in-the-fight-
against-covid-19
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141631/
• https://www.cision.com/2017/12/press-release-boilerplate-examples/
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7158272/
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7938880/
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References (4/4)
• https://www.fmlink.com/articles/emergency-preparedness-lessons-from-the-pandemic/
• https://www.firefighternation.com/contributors/covid-19-emergency-management-lessons-
learned/#gref
• https://reliefweb.int/report/world/lessons-learned-covid-19-how-private-sector-can-support-disaster-
prevention-response
• https://occ.ca/wp-content/uploads/OCC-Pandemic-Preparedness-Toolkit-for-COVID-19_final.pdf
• https://www.fema.gov/disasters/coronavirus/best-practices
• https://www.liebertpub.com/doi/full/10.1089/hs.2020.0151
• https://covid19-sciencetable.ca/sciencebrief/behavioural-science-principles-for-supporting-covid-19-
vaccine-confidence-and-uptake-among-ontario-health-care-workers/
• https://covid19-sciencetable.ca/sciencebrief/behavioural-science-principles-for-enhancing-adherence-
to-public-health-measures/
• https://www.semanticscholar.org/paper/Using-social-and-behavioural-science-to-support-Bavel-
Baicker/b97c72d4ca1009d1e0bc8ac1eab87f0fd4bd1527
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