Looking back at the COVID pandemic, what does hindsight teach us? Do we remember the decade of transition as the year that ultimately made the real difference in preparing for a pandemic, or that the final return to a “normal” state hindered our progress? Do you?
Epidemiologists have long warned of a possible pandemic, but their warnings have been largely ignored.But industrialized livestock practices, increased human-animal contact, globalization, reduced biodiversity, and all other factors Point out the possibility An example of another zoonotic disease that may be a pandemic (an animal-to-human transmission).
The slim silver lining of the current COVID-19 pandemic means that if we use what we have learned correctly, it will help us prepare for future outbreaks. In particular, we can better leverage real-world data, one of our most important resources for preparing for a pandemic.
Importance of real-time insights
The pandemic has created a pile of data to help plan future outbreaks of the disease. Extensive research into the US pandemic response provides insights into the benefits and consequences of different behavioral policies, and this knowledge can be used for future response.
One of the main points is that healthcare systems need to be visualized in real time.While the observer is speaking again And again The ineffective deployment of the test was (and still is) one of the biggest failures in the United States ahead of COVID-19, which is rich in other data that can provide insights into the spread of the virus. It is in. We need to improve the collection, sharing, and analysis of this real-world data so that we can quickly recognize the symptoms of COVID-19, identify effective treatments, and track the spread more quickly.
For example, when the pandemic began, information disseminated by public health agencies identified sore throat, shortness of breath, cough, and fever as symptoms.But a few months later Additional symptoms Rash, discoloration of the skin, etc. Toes and feet— Recognized as a potential indicator of the virus. further,”Silent hypoxia— COVID-19 causes very low blood oxygen levels without any noticeable external effects on breathing — killing many patients before they realize that doctors are monitoring it. It was.
Why didn’t you recognize these symptoms earlier? Electronic Health Records (EHRs), where doctors record patient visits, do not have an easy and effective way to share data on a large scale. If we could mine anonymized patient data at the national level, artificial intelligence and machine learning algorithms would have been able to identify patterns much faster than isolated researchers working in small patient pools. Instead of looking at the COVID-19 data altogether, researchers within 6 months 23,500 treatises— A wealth of information, but too much data to analyze and identify valuable research.
Centralized data access not only speeded up the identification of COVID symptoms, but also enabled rapid research of effective treatments. Researchers can use a truly robust database to analyze and identify the most effective treatments for patients with a variety of underlying disorders or medical histories.
In addition, using machine learning techniques within shared databases can generate predictive insights, show patterns of communities prior to their occurrence, and help determine when and where to implement blockade and social distance commands. .. Some countries use unconventional data sources such as anonymized cell phones and fitness tracking data to predict the occurrence of COVID.For example, Germany Anonymized tracking app Identifying abnormalities in daily habits, such as predicting when outbreaks are likely to occur in the community by regularly active users skipping or walking, before the outbreak worsens. To prevent.
Israeli experience Provides a great example Learn how to analyze and share real-world data. By rapidly deploying the Pfizer vaccine to more than half of the population and tracking the results, the country was able to demonstrate a dramatic reduction in serious infections and hospitalizations. vaccine.. This real-world evidence is the key to understanding how vaccines work in much larger populations outside the scope of controlled clinical trials.
These measures are just the basis of what policy makers can do to provide real-time insights. And that benefit doesn’t have to be used just to prepare for a pandemic. Anonymized data mining and analysis can be used to identify effective strategies for combating conditions ranging from mental health concerns to chronic illnesses.
Hindsight, foresight, insight
If the next new virus of potential pandemic inevitably occurs, changes and preparations to be made in the coming months and years will allow better management of another crisis at the scale of COVID-19. Whether or not it is decided. Our healthcare system continues to experience data sharing disruptions at all levels, so urgent action is needed. COVID-19 testing has increased dramatically, but the organization remains Difficult to share test results, Because some facilities still rely on fax machines to convey information in a timely manner. When fighting an ongoing pandemic, the results delivered weeks after the test have little purpose in preventing the spread of the disease. To be foresighted to prevent the next pandemic, we must enable real-time insights and recognize the importance of studying past events.
Some countries, such as the United Kingdom, spend significant resources on sequencing additional COVID-19 genomes, America is the 32nd in the world The number of sequences completed per 1,000 COVID cases. Not only the inability to identify mutated viruses, but also the inability to easily recognize significant changes in viral epidemiology at that level, continues to impede the ability to predict and prevent spread.
There are always different opinions about the best course of action for pandemic preparedness and prevention, but we need to create more effective forums for discussion and various social, economic and physiology. Courses that should continue to encourage discussions across many disciplines to weigh potential impacts. These discussions should not wait until the next pandemic arrives. Instead, think tanks and committees should be set up and well funded to imagine possible scenarios and responses.
You need to answer important questions such as: How long can companies of different socio-economic levels survive the closure, and what kind of aid is most effective? What are the long-term consequences of a child’s absence from school for a year or effectively attending school? How does isolation affect the mental health of people of different age groups, income levels, and urban and rural environments? And what strategies work to mitigate these impacts? What lessons can we learn from countries with advanced data capture systems?
With the right data to analyze and the right experts to analyze such data, we can answer these questions and gather the insights needed to understand the ongoing impact of COVID-19. I will. Armed with this knowledge and global awareness of the consequences of ineffective responses, there are motivations and means to take appropriate precautions and prevent them before a future pandemic begins.
This is an opinion and analysis article.
How real-world data can help you better prepare for your next pandemic
https://www.scientificamerican.com/article/how-real-world-data-can-help-us-better-prepare-for-the-next-pandemic/ How real-world data can help you better prepare for your next pandemic