Dean Samet Archive

I write these comments as the Colorado School of Public Health enters its second week of physical closure and moves into a new phase of online instruction through the end of the Spring semester. Last week was marked by making this transition for faculty, staff and students. We recognize that there are many challenges facing the ColoradoSPH community and questions to be answered about them. To that end, we have established a COVID-19 page on our website. For our faculty and staff at the CU Anschutz campus, we also urge you to follow announcements at the CU Anschutz website while those at CSU and UNC should use the corresponding resources at their campuses: CSU COVID-19 resources and UNC COVID-19 resources.   

In my commentary on March 13, I addressed infectious disease modeling and the landmark work of Lowell Reed and Wade Hampton Frost. The current generation of computer-based models that we are now using to make decisions is grounded in this pioneering framework.  The basics of these models are intuitive: prior to infection, individuals are susceptible (S) and once exposed (E) and infected (I) they are contagious, whether symptomatic or asymptomatic; those infected may recover and become resistant (R) or become sufficiently ill to need hospitalization and possibly critical care and to die. One standard model being used is thus abbreviated as the SEIR model. Another important number in the model is the reproductive number (R0), that is, the average number of new cases generated per infected person. If that number exceeds one then the infection will spread. Various figures for R0 have been reported at the start of the COVID-19 epidemic, ranging from about 3 to 5. The goal of social distancing, what we are all experiencing now, is to reduce the reproductive number with a target value below one so that contagion ends. A critical question is how much social distancing is needed to control the epidemic and for how long does it need to be in place? 

Faculty from the Colorado School of Public Health, the CU School of Medicine, and the University of Colorado Boulder have teamed to carry out modeling in support of decision-making by the Colorado Department of Public Health and Environment (CDPHE). This volunteer team includes the following: Debashis Ghosh, Beth Carlton, Andrea Buchwald, Tatiane Santos, Meghan Buran, Rich Lindrooth, and myself from ColoradoSPH; Katie Colburn from ColoradoSPH and the CU School of Medicine; and David Bortz from the University of Colorado Boulder. The experience and depth of the team matches the challenge of modeling the epidemic and evaluating scenarios of control.   

Initially the team prepared a report based on extrapolation of findings from a model developed by a leading group at Imperial College London. That report provided models for the course of the epidemic and its consequences for the healthcare system; under most scenarios, capacity to manage critically-ill patients is exceeded to a frightening extent. Extended to Colorado, the estimates reach the same alarming peaks.   

The team then turned to an SEIR model based on Colorado data. This model, tailored to the epidemic in Colorado, is now being used to explore decisions on additional restrictions intended to further reduce social distancing, the fundamental tool of epidemic management. Using the model, we can explore outcomes based on scenarios of social distancing and their implementation and lifting once the epidemic abates.   

Decisions are being made worldwide on the basis of infectious disease models. For example, on March 19, California’s Governor Newsome asked for assistance from the Administration with: "We project that roughly 56% of our state's population—25.5 million people—will be infected with the virus over an eight-week period," (see CNN). 

And, these models only address one component of the health consequences of the epidemic—the infection itself. A full health impact assessment adds the immediate shocks—unemployment, economic losses, and intolerable uncertainty—and the long-term consequences as the economy recovers and deaths are mourned. And, we are all worried and anxious. Optimistically, we have measures that will work to end the epidemic; some nations have already done so. Pessimistically, we know that our lives have been changed. For my parents, the Great Depression was a lasting scar. I hope that memories of the COVID-19 epidemic are not so enduring.   

Public health students—watch the press conferences and the communications. Contrast the credibility and sincerity of Dr. Anthony (Tony) Fauci, a trusted veteran of epidemics, with the communications of others. And use the incredible data resources available to watch this epidemic evolve and end.   

All—you may find this telling of the epidemic by Tomas Pueyo to be useful, too.

I write these comments as the Colorado School of Public Health enters its second week of physical closure and moves into a new phase of online instruction through the end of the Spring semester. Last week was marked by making this transition for faculty, staff and students. We recognize that there are many challenges facing the ColoradoSPH community and questions to be answered about them. To that end, we have established a COVID-19 page on our website. For our faculty and staff at the CU Anschutz campus, we also urge you to follow announcements at the CU Anschutz website while those at CSU and UNC should use the corresponding resources at their campuses: CSU COVID-19 resources and UNC COVID-19 resources.   

In my commentary on March 13, I addressed infectious disease modeling and the landmark work of Lowell Reed and Wade Hampton Frost. The current generation of computer-based models that we are now using to make decisions is grounded in this pioneering framework.  The basics of these models are intuitive: prior to infection, individuals are susceptible (S) and once exposed (E) and infected (I) they are contagious, whether symptomatic or asymptomatic; those infected may recover and become resistant (R) or become sufficiently ill to need hospitalization and possibly critical care and to die. One standard model being used is thus abbreviated as the SEIR model. Another important number in the model is the reproductive number (R0), that is, the average number of new cases generated per infected person. If that number exceeds one then the infection will spread. Various figures for R0 have been reported at the start of the COVID-19 epidemic, ranging from about 3 to 5. The goal of social distancing, what we are all experiencing now, is to reduce the reproductive number with a target value below one so that contagion ends. A critical question is how much social distancing is needed to control the epidemic and for how long does it need to be in place? 

Faculty from the Colorado School of Public Health, the CU School of Medicine, and the University of Colorado Boulder have teamed to carry out modeling in support of decision-making by the Colorado Department of Public Health and Environment (CDPHE). This volunteer team includes the following: Debashis Ghosh, Beth Carlton, Andrea Buchwald, Tatiane Santos, Meghan Buran, Rich Lindrooth, and myself from ColoradoSPH; Katie Colburn from ColoradoSPH and the CU School of Medicine; and David Bortz from the University of Colorado Boulder. The experience and depth of the team matches the challenge of modeling the epidemic and evaluating scenarios of control.   

Initially the team prepared a report based on extrapolation of findings from a model developed by a leading group at Imperial College London. That report provided models for the course of the epidemic and its consequences for the healthcare system; under most scenarios, capacity to manage critically-ill patients is exceeded to a frightening extent. Extended to Colorado, the estimates reach the same alarming peaks.   

The team then turned to an SEIR model based on Colorado data. This model, tailored to the epidemic in Colorado, is now being used to explore decisions on additional restrictions intended to further reduce social distancing, the fundamental tool of epidemic management. Using the model, we can explore outcomes based on scenarios of social distancing and their implementation and lifting once the epidemic abates.   

Decisions are being made worldwide on the basis of infectious disease models. For example, on March 19, California’s Governor Newsome asked for assistance from the Administration with: "We project that roughly 56% of our state's population—25.5 million people—will be infected with the virus over an eight-week period," (see CNN). 

And, these models only address one component of the health consequences of the epidemic—the infection itself. A full health impact assessment adds the immediate shocks—unemployment, economic losses, and intolerable uncertainty—and the long-term consequences as the economy recovers and deaths are mourned. And, we are all worried and anxious. Optimistically, we have measures that will work to end the epidemic; some nations have already done so. Pessimistically, we know that our lives have been changed. For my parents, the Great Depression was a lasting scar. I hope that memories of the COVID-19 epidemic are not so enduring.   

Public health students—watch the press conferences and the communications. Contrast the credibility and sincerity of Dr. Anthony (Tony) Fauci, a trusted veteran of epidemics, with the communications of others. And use the incredible data resources available to watch this epidemic evolve and end.   

All—you may find this telling of the epidemic by Tomas Pueyo to be useful, too.