Global Pandemic Statistics: How Data Helps Save Lives

Global Pandemic Statistics: How Data Helps Save Lives
Global Pandemic Statistics: How Data Helps Save Lives

Applied statistics is one of the most important tools that scientists, doctors, and national and local leaders can use to help save lives in a global pandemic. Whether they need to evaluate the risk to a given population, assess the impact of treatments and preventive measures, or determine public policies, leaders rely on pandemic statistics to take the guesswork out of decision-making.

Pandemic Statistics and the COVID-19 Crisis

Ever since the COVID-19 virus began to spread around the world in January 2020, global leaders have relied on coronavirus statistics to analyze its progression. According to Michigan Technological University professor Dr. Qiuying Sha, “Improvements in data science and technology help us to build more accurate and [reliable] statistical models to predict the number of COVID-19 cases and the number of deaths for each county, state, and the whole United States.”


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In the U.S., while the number of identified cases has continued to rise, hospitalizations have declined from a peak of 59,718 on July 23 to just over 30,000 at the end of September. Pandemic statistics and data management have played a key role in this decline by helping health officials:

  • Identify cases more quickly.
  • Slow transmission of the disease.
  • Provide timely lifesaving care.

Pandemic statistics have helped medical institutions prepare to treat seriously ill patients and identify vulnerable populations. Data management systems enable health care workers to:

  • Track coronavirus statistics on cases and outcomes.
  • Offer testing to those who could be disease carriers without realizing it.
  • Evaluate which treatments most effectively counteract symptoms.

As researchers pursue a vaccine to reduce the risk of infection, statistics will be an essential component of the large-scale studies needed to test vaccine effectiveness.

Health officials also use coronavirus statistics to monitor testing, positivity, and hospitalization rates, and create visualizations to help local, state, and national leaders to make policy decisions that affect everyone. Dr. Sha notes, “Based on the predictions, decision-makers can make data-driven decisions, such as the restrictions on bars and restaurants; hospitals can make decisions on the reserves of critical response products like ventilators, masks, and swabs and on the utilization of hospital beds.” Educators also use statistics to determine how to do school during the pandemic with minimal risk to students, teachers, and families.

How Pandemic Statistics Have Been Used in the Past

How Pandemic Statistics Have Been Used in the Past

A pandemic is a widespread outbreak of disease across several countries or regions—and a global pandemic is an outbreak whose impact is felt throughout the world. Many of the diseases that caused pandemics in the past, such as bubonic plague, cholera, smallpox, and polio, have been eradicated or severely restricted today. Recent new diseases that have had a significant impact include HIV-AIDS, Ebola, and the Zika virus. Pandemic statistics have enabled researchers to track progress in dealing with these outbreaks around the world.

Many of the most severe global pandemics in the past century have been various types of influenza. Historians believe that the 1918-1919 flu epidemic infected about 500 million people—about a third of the world’s population—and killed as many as 50 million. Scientists discovered the viruses that cause the flu in the 1930s and began to develop preventive vaccines in the 1940s.

After the World Health Organization (WHO) was created in 1948, one of its early initiatives was developing the Global Influenza Surveillance and Response System (GISRS) to monitor how influenza viruses were evolving. A decade later, the Center for Disease Control (CDC) in the United States set up the 122 Cities Mortality Reporting System, which was the system used to track flu-related deaths throughout the U.S. until 2016. In 1997, WHO developed FluNet, a global, web-based tool to track and interpret epidemiological data on the movement of flu viruses around the world.

These data systems, along with improved vaccines and treatments, helped save many lives in the flu pandemics of 1957, 1968, and 2009. With better access to pandemic statistics, the US government developed a national influenza plan that includes an Influenza Risk Assessment Tool and a Pandemic Severity Assessment Framework to help leaders at all levels respond effectively when pandemics strike.

How Have Coronavirus Statistics Helped Save Lives?

How Have Coronavirus Statistics Helped Save Lives?

Since WHO began publishing technical guidance to help countries stem the tide of COVID-19 in January 2020, health experts and policy makers have relied on coronavirus statistics to understand the growing body of information about the disease. Doctors, scientists, government leaders, and ordinary people are looking at the data to make decisions that will help save lives.

Preparing Medical Institutions and Communities to Face the Pandemic

Pandemic statistics enable scientists and engineers to develop models and tracking tools that help them anticipate when and where the pandemic will strike. By tracking the number of cases, experts could:

  • Anticipate medical and testing needs.
  • Make sure that ventilators, hospital beds, and test kits were available.
  • Deploy extra medical personnel where most needed.

Some cities set up mobile test sites in preparation before the number of victims increased, based on coronavirus statistics from experience in other places.

Identifying Vulnerable Populations

When the COVID-19 pandemic began, pandemic statistics quickly enabled doctors to determine who were at greatest risk of serious illness from the virus, including:

  • People more than 65 years old.
  • People with underlying medical conditions, such as heart disease, respiratory illness, or diabetes.
  • People with compromised immune systems.

This information enabled health officials to issue warnings so the most vulnerable could be especially careful. Employers, public services, and medical institutions put extra precautions in place. The goal? To minimize the danger of infection for the people most likely to become seriously ill if they contracted the disease.

Community Transmission, Testing Availability, and Contact Tracing

Community transmission is present when people are diagnosed with COVID-19 who have not traveled to high-risk areas or had direct contact with known COVID-19 cases. When such cases are identified, health officials in affected regions prioritize testing people with few or no symptoms who could unknowingly infect others. Those who test positive for the virus quarantine themselves until they are no longer infectious. This can save many lives among the people they would normally come in contact with.

Contact tracers use coronavirus statistics data management systems to monitor and document recent interactions of people who have tested positive or become ill with COVID-19. They can then notify those concerned that they may have come in contact with the virus, so they can be tested before they can infect others. Breaking the transmission chain in this way can save many lives.

Demographic Disparities and High-Risk Situations

Demographic Disparities and High-Risk Situations

As COVID-19 swept through the US, pandemic statistics soon showed serious disparities in the way different communities were affected. For example, people of color living in low-income neighborhoods experienced disproportionately high rates of both illness and death. This realization prompted public health officials to call for:

  • Renewed concern for historic racial inequities in health care access.
  • Accurate monitoring and reporting of racial disparities in COVID-19 outcomes.
  • Better equipment and practices to protect those working in health care and service industries.
  • Culturally responsive messaging to inform minority communities.

Coronavirus statistics also revealed that nursing homes had become high-risk communities, where the virus spread quickly among residents and staff. State and local leaders who learned about these dangers were able to take preventive measures, reallocate protective equipment to these facilities, and lock down vulnerable communities before further transmission occurred.

Evaluating Treatments and Vaccines

As researchers around the world work to develop effective treatments and vaccines, they employ pandemic statistics applications to analyze their findings and understand the mechanisms and receptors the virus uses to infect people. Going forward, large-scale tests requiring extensive data analysis will be used to gauge the effectiveness of proposed vaccines.

When an effective vaccine becomes available, coronavirus statistics will also help health leaders determine how to deploy it most strategically and fairly. These decisions have an important ethical component, but accurate data will be needed to inform those ethical discussions.

Pandemic Statistics Guiding Public Policy Decisions

Pandemic Statistics Guiding Public Policy Decisions

From Maine to Hawaii, New York City to Montana, state and local leaders are making decisions about openings and closings, mask wearing and social distancing. To determine the best course of action, they rely on CDC guidelines and local health data to set thresholds and weigh the consequences of various options. Statistical models help them anticipate how closing businesses will affect the local economy, or how online learning will alter children’s academic progress.

Similarly, organizations, institutions, and businesses are watching pandemic statistics closely to plan for the future. National and regional conferences are on the line, as well as which products to stock for retail and wholesale marketing. Entire sectors of the national economy are deeply affected by COVID-19; national and regional data models enable decision makers to prepare accordingly.

Informing Individuals and Families

Should you take that long-awaited vacation? How can you convince your boss to let you teleconference instead of making a business trip? Visualizations built on coronavirus statistics—like the Johns Hopkins University state-by-state tracker, or its animated world map—can help you decide what to do, and make your point persuasively.

Or maybe you need to make decisions about:

  • Whether to work from home.
  • Whether to let your kids play sports.
  • How to keep an elderly relative safe.

Knowing the coronavirus statistics about trends in your region won’t eliminate risks entirely, but it will help you make wise, informed decisions. A new app, COVIDWISE, now traces contacts anonymously and advises users if they’ve been in close proximity to someone who’s tested positive for the virus.

Explore Your Career Potential in the Life-Saving Field of Applied Statistics

Explore Your Career Potential in the Life-Saving Field of Applied Statistics

Data scientists play a key role in saving lives at every level of health care, research, and public policy. They also possess skills that are sought after in every sector of government, business, scientific and consumer research. According to the Bureau of Labor Statistics, statisticians are in one of the fastest-growing and best-paid sectors of the workforce, with a median annual salary of $91,160. The number of jobs is expected to grow by 35% from 2019 to 2029.

Here are some of the career opportunities in health-related fields available to those with advanced training in applied statistics:

  • Data analysts work with data sets to analyze information, spot trends and patterns, and produce reports for their colleagues to use in a variety of work contexts.
  • Data scientists use deep math and statistical expertise to identify and analyze large data sets, developing models and algorithms to provide clean, actionable information.
  • Research statisticians design surveys and experiments to collect data and analyze it to support research projects.
  • Biostatisticians write program code for statistical analysis software, analyze data and make predictions, and prepare tables and graphs for medical and biological professionals.
  • Statistical programmers use specialized skills to create computer software that collects and analyzes information from very large databases in various fields.

Entry-level positions in this dynamic field typically require a master’s degree. This training develops important skills in:

Whether you’re a working professional in data science or considering a shift from another field, such as business, math, or public health, earning a master’s degree in Applied Statistics could be the most valuable career decision you ever make. Discover more about the online Master of Science in Applied Statistics from Michigan Technological University.


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