Much of public policy regarding COVID-19 has to do with limiting the spread of the virus. While it may seem like a totally random occurrence, popping up unexpectedly here and there, the spread can be calculated by a model based on the virus biology and the structural landscape of potential hosts (you and me). The predicted spread, however, cannot account for random variation and depends on the accuracy of the information fed into the model. What makes this process difficult for COVID-19 is that little is known yet about the infectious nature of the virus.
Below are a group of maps that allow us to visualize the spread of the virus.
A. Predicted Spread
On March 12, 2020, Time Magazine produced a dynamic map of the predicted spread of the virus. The data came from models produced for the CDC based on knowledge of the virus at that point and on population density, mobility, commuting patterns and air travel. The user could select one of three surveillance levels: low - indicating minimal testing; moderate - greater testing coverage; and high - comprehensive testing of individuals.
What is pictured in map "A" is the lowest testing scenario, where little can be determined about the status of the outbreak. The virus would then spread undetected among the population and unmitigated by government or health official policies. The number of cases in an area are represented by colored pixels, ranging from high density - orange, to medium density - yellow, to low density - green. The actual level of testing in the US has been at best in the moderate range, but many states have either chosen not to test in sufficient numbers or have not been able to obtain the necessary testing supplies and lab evaluation resources.
B. Recent Increases - 7/9/2020
Map "B" is a snapshot of a dynamic map produced by USA Today based on data from John Hopkins University. The original map is updated regularly and shows total cases and deaths per county since the infection began or just for the last seven days. The number of cases are indicated by colored circles whose size is relative to the case totals. In the map above, total increase in cases for the last seven days is shown, as of July 9, 2020.
The overall appearance of map "A" and map "B" is strikingly similar. While the symbolization of the two maps differs, both maps are still designed to show the extent of the spread of the virus over time. The areas that are most active are the same in both maps, but when the size differences between areas are compared on one map to the same areas in the other, some differences are apparent.
If we look at the relative sizes of case areas within map "A" (predicted spread) for California, Texas and Florida, they seem to correspond to the relative sizes of case circles between the same states in the map "B"(current increases). Arizona and New York case areas and case circles, however, do not seem to match the scale of other area extents, Arizona being relatively larger in map "B" and New York being smaller. This would seem to correspond to the level of surveillance (testing) that has been done in New York versus Arizona, where New York practiced very strict mitigation and Arizona less so.
C. Global Path of the Virus
The map of global paths of the virus as it spread is based on genetic sequencing of the virus in samples taken from patients all over the world. The circle symbols in the map represent the relative size of the outbreaks and the color of the paths relate to where the virus originated from.Genetic sequencing identifies the molecular building blocks of the virus and the order in which they are assembled into chains. As with most viruses, the Coronavirus that causes COVID-19 (SARS-CoV-2) makes mistakes occasionally when it creates copies of the genome (genetic blueprint). These mistakes are referred to as mutations and are passed on to future generations of the virus. As the copies of the virus infect new hosts, they can then be carried to other locations where they might infect additional people.
The researchers who constructed the map, analyzed the genetic sequences to create inheritance trees. This made it possible to link later generations of the virus in one country to ancestors in source countries. Besides the map above, they also created one of the time period from December 3, 2019, to February 3, 2020. That map indicated the source for all initial cases in other countries as being China. In the period shown in the map above (Feb. 3, 2020 to April 21,2020), however, later generations of the virus spread from these secondary infection sites to other countries. As an outbreak began at a location with little or no travel restrictions, the virus was free to spread back and forth on the airways by tagging along with human hosts.
D. Highways and Urban Areas
I built map "D" by overlaying maps from two different sources. The base layer is a map of the National Highway System, including US Highways and the Interstate System produced by the US Department of Transportation. The overlay is based on US Census Urban Areas defined as "clusters of development that meet a minimum population density" (Urban Areas). The size of the circles are relative to the total population within the area.
This map also bears a strong resemblance to maps "A" and "B". Which is to say that COVID-19 goes where the people are - and it gets there riding along with infected people traveling our highways and byways. People go everywhere in their cars and trucks, and, eventually, they carry the virus to your home town, or close to it. COVID-19 spreads by certain physical mechanisms (coughing, sneezing, talking) and as long as nothing gets in the way of those processes, it will find the next host. Until we have a vaccine to stop the spread, there are only a few physical barriers that can slow the infection: masks, hand washing, hand sanitizer, and social distancing. These counter measures will work, but only if the majority of people practice them. Where people ignore these guidelines, the disease has a wide open path to their front door.
How Many Degrees of Separation Are You From the Infection?
In early April of 2020, a team of network epidemiologists, who study the prevalence of disease, put together a thought project at the University of Washington designed to simulate various levels of social distancing and the resulting infection rate. The initial population was represented by a group of equidistant dots. As connections were made, the dots became networked beyond the point of initial contact, represented by linked lines. Three scenarios are shown below.
The first scenario represents households (dots) that are all perfectly self-isolating. Under this scenario, no one would catch the disease, even if some people were infected. Without close personal contact there is no transmission. This is not a realistic option, though: people in the same household would find it very difficult to isolate from each other and without some interaction with others, it would not be possible to obtain food, medicine, healthcare and and other public services.
At the other end of the scale is scenario 3, where interactions are the same as before the pandemic. People would be very closely connected and if only a few people were infected, eventually all would contract the disease. Somewhere in between 1 and 3 is scenario 2. It represents the situation where slightly more than essential contacts are taking place, perhaps allowing for some on site work and socializing, but still without social distancing practiced. Even in this case, 90% of all households would be connected and that is a path the virus can use to infect more individuals. If you get sick, you may not have symptoms, but you will continue to be contagious. If you visit a friend, a neighbor or a relative without precautions, you may infect them. What if they also have an existing health condition that puts them more at risk of experiencing a life threatening infection? One that you could have prevented.
The longer people stay away from work, the more precarious their economic well-being will become. On the other hand. the more that people reengage with others, the more important it will be to use masks and separation to keep their distance from infected individuals. The solution seems to be to take it slow, monitor things closely and go no faster than the numbers allow.