With the start of summer coming soon, many are hopeful that the warmer weather will slow the spread of SARS-CoV-2, the novel coronavirus that causes COVID-19. There have been hints from lab experiments that increased temperature and humidity may reduce the viability of SARS-CoV-2. Meanwhile, other coronaviruses that cause less severe diseases, such as the common cold, do spread more slowly among people during the summer.
We’ll obviously have to wait a few months to get the data. But for now, many researchers have their doubts that the COVID-19 pandemic will enter a needed summertime lull. Among them are some experts on infectious disease transmission and climate modeling, who ran a series of sophisticated computer simulations of how the virus will likely spread over the coming months . This research team found that humans’ current lack of immunity to SARS-CoV-2—not the weather—will likely be a primary factor driving the continued, rapid spread of the novel coronavirus this summer and into the fall.
These sobering predictions, published recently in the journal Science, come from studies led by Rachel Baker and Bryan Grenfell at Princeton Environmental Institute, Princeton, NJ. The Grenfell lab has long studied the dynamics of infectious illnesses, including seasonal influenza and respiratory syncytial virus (RSV). Last year, they published one of the first studies to look at how our warming climate might influence those dynamics in the coming years .
Those earlier studies focused on well-known human infectious diseases. Less clear is how seasonal variations in the weather might modulate the spread of a new virus that the vast majority of people and their immune systems have yet to encounter.
In the new study, the researchers developed a mathematical model to simulate how seasonal changes in temperature might influence the trajectory of COVID-19 in cities around the world. Of course, because the virus emerged on the scene only recently, we don’t know very much about how it will respond to warming conditions. So, the researchers ran three different scenarios based on what’s known about the role of climate in the spread of other viruses, including two coronaviruses, called OC43 and HKU1, that are known to cause common colds in people.
In all three scenarios, their models showed that climate only would become an important seasonal factor in controlling COVID-19 once a large proportion of people within a given community are immune or resistant to infection. In fact, the team found that, even if one assumes that SARS-CoV-2 is as sensitive to climate as other seasonal viruses, summer heat still would not be enough of a mitigator right now to slow its initial, rapid spread through the human population. That’s also clear from the rapid spread of COVID-19 that’s currently occurring in Brazil, Ecuador, and some other tropical nations.
Over the longer term, as more people develop immunity, the researchers suggest that COVID-19 may likely fall into a seasonal pattern similar to those seen with diseases caused by other coronaviruses. Long before then, NIH is working intensively with partners from all sectors to make sure that safe, effective treatments and vaccines will be available to help prevent the tragic, heavy loss of life that we’re seeing now.
Of course, climate is just one key factor to consider in evaluating the course of this disease. And, there is a glimmer of hope in one of the group’s models. The researchers incorporated the effects of control measures, such as physical distancing, with climate. It appears from this model that such measures, in combination with warm temperatures, actually might combine well to help slow the spread of this devastating virus. It’s a reminder that physical distancing will remain our best weapon into the summer to slow or prevent the spread of COVID-19. So, keep wearing those masks and staying 6 feet or more apart!
Caption: Human colon cancer cells. Credit: National Cancer Institute, NIH
Thanks to improvements in screening technologies and public health outreach, more cancers are being detected early. While that’s life-saving news for many people, it does raise some important questions about the management of small, early-stage tumors. Do some tumors take a long time to smolder in their original location before they spread, or metastasize, while others track to new, distant, and dangerous sites early in their course? Or, as the authors of a new NIH-funded study put it, are certain tumors just “born to be bad”?
To get some answers, these researchers recently used genomic data from 19 human colorectal tumors (malignant and benign) to model tumor development over time . Their computer simulations showed that malignant tumors displayed distinctive spatial patterns of genetic mutations associated with early cell mobility. Cell mobility is a prerequisite for malignancy, and it indicates an elevated risk of tumors invading the surrounding tissue and spreading to other parts of the body. What’s more, the team’s experimental work uncovered evidence of early abnormal cell movement in more than half of the invasive tumors.
Much more remains to be done to validate these findings and extend them to other types of cancer. But the study suggests that spatial mutation patterns may someday prove useful in helping decide whether to pursue aggressive treatment for early-stage cancer or opt for careful monitoring instead.
After graduating college with degrees in physics and computer science, Amanda Randles landed her dream first job. She joined IBM in 2005 to work on its Blue Gene Project, which had just unveiled the world’s fastest supercomputer. So fast, in fact, it’s said that a scientist with a calculator would have to work nonstop for 177,000 years to perform the operations that Blue Gene could complete in one second. As a member of the applications team, Randles was charged with writing new code to make the next model run even faster.
Randles left IBM in 2009 for graduate school, with the goal to apply her supercomputing expertise to biomedical research. She spent the next several years developing the necessary algorithms to produce a high-resolution 3D model of the human cardiovascular system, complete with realistic blood flow. Now, an assistant professor at Duke University, Durham, NC, and a 2014 NIH Director’s Early Independence awardee, Randles will build on her earlier work to attempt something even more challenging: simulating the movement of cancer cells through the circulation to predict where a tumor is most likely to spread. Randles hopes all of her late nights writing code will one day lead to software that helps doctors stage cancer more precisely and gives patients accurate personalized computer simulations that put an earlier, potentially life-saving bullseye on secondary tumors.
Avatar. Pick your Sim. The entertainment world has done an amazing job developing software that generates animated characters with strikingly realistic movement. But scientists have taken this one step further to create models that can help kids with cerebral palsy walk better, delay the onset of osteoarthritis, and even answer a question in the minds of children of all ages: How exactly did T. rex run?
That’s what the researchers behind this video—an entrant in the NIH Common Fund’s recent video competition—have done. They’ve developed OpenSim: a free software tool that combines state-of-the-art musculoskeletal modeling and dynamic computer simulations to produce highly accurate representations of the underlying biomechanics of motion. OpenSim was designed at the NIH-supported center for physics-based Simulation of Biological Structures (Simbios) at Stanford University, Palo Alto, CA. And now, researchers around the world are using OpenSim to find more effective interventions for a variety of movement disorders.