September 28th, 2020
It’s been six months since I made my first COVID-19 projections. What started as a small side project became a months long endeavor. 180 days and 180 forecasts later, the pandemic shows no signs of abating as we head towards winter. When I started covid19-projections.com, there were only a handful of existing models, and very few of them were accurate. Now, there are over 30 models on the CDC Forecasting page. A lot of great progress has been made in the modeling space over the past six months, and I hope others will get to better know these other models in the months to come. After much consideration, I have come to the difficult decision to not extend my projections beyond November 1, 2020. I plan to make the last forecast update to covid19-projections.com on Monday, October 5. This was undoubtedly a tough choice for me, and I hope to convey my thoughts in this post.
There are several reasons that went into my decision, which I describe below:
With that said, I firmly believe that the modeling community is in good hands. Below, I will present a few models that I have found to be the most reliable.
I know this news is disappointing for the many people who have been closely following my model over the past few months, so I want to provide a few reputable alternatives. It’s important that we focus on models which have a proven track record and not just those that have generated the biggest headlines. No single model is perfect, hence this is why I believe it is important to look at different models and understand the assumptions of each one in order to interpret the forecasts. Due to this reasoning, I recommend the COVID-19 Forecast Hub, which aggregates forecasts from over 30 models and sends them to the CDC each week to help inform public health decision making.
From among the Forecast Hub, below are a list of models that I have found to be the most reliable over the past few weeks and months. You can find a visualization of all the models listed below here. In addition to forecasting reported deaths, the below models also have forecasts for confirmed cases. The UCLA, COVIDAnalytics, USC and LANL models also have forecasts for international countries.
I highly recommend those who have been following my work to take some time studying the aforementioned models. I have personally spoken to most of the groups and have listened to their presentations. I can attest to their proven track record and hope they can continue to provide reliable forecasts in the weeks and months to come. When viewed in tandem, these models can help provide a clearer picture of what will most likely happen in the upcoming weeks. While not crystal balls, I believe these forecasts can be very useful tools for researchers and policy makers.
The above list is not necessarily an exhaustive list of reliable models. You can learn more about my weekly evaluations of the different models here. I hope to continue updating these model evaluations in the near future.
Ending my model forecasts does not mean that my work in COVID-19 is over. This decision will allow me to dedicate my freed up time to other areas of COVID-19 data analysis. In this day and age, misinterpretation of data (both intentional and unintentional) is pervasive. Anyone can cherry-pick data to support his or her narrative. My goal is to continue presenting COVID-19 data in a rigorous, unbiased manner. Follow me on Twitter at @youyanggu to stay up to date with my latest analysis.
I am forever grateful to have the support of so many people from across the US and around the world. I want to thank everyone who believed in my work from the early days, especially Nicholas Reich, his group at UMass Amherst, and the scientists at the CDC. I also want to thank all the scientists, researchers, and everyone else with whom I’ve had the pleasure of interacting with online; at a time where in-person contact has been limited, these interactions have been tremendously helpful. I feel honored to be able to contribute to the scientific community in improving our understanding of the disease. This was certainly not something that I, a data scientist with no background in infectious diseases, expected just a year ago. I haven’t always been right, but I’m thankful to be part of a community that is constantly helping me learn.
I am currently working on a piece that outlines the things I have learned over the past six months. I hope to post it here in the next week or two. Stay tuned!
While I no longer will be making public forecasts, I hope to continue to be involved in the forecasting space in some shape or form. If you are interested in hearing more about my work, feel free to send me a message.
I still don’t know what the future holds. I am always open to new challenges and projects, especially those involving the use of data-oriented modeling to tackle public health problems. If you have any suggestions or ideas, please don’t hesitate to reach out to me using the contact button below. I would love to get in touch.
In the meantime, let’s all work together to continue fighting this pandemic. Each one of us can make a difference.