Ending Covid
VDMP Determining a Grid for Calculation Purposes
The primary objective is to define different methods on how one can declare areas free of a disease.
In order to determine what the most effective methods to start to reduce numbers of Covid-19 cases in your region are, a criteria must be created. One such option to, is via the creation of a grid model to determine specific parameters to measure and reflect the decline of a disease, within a given area using vaccination along with natural population exposure in order to verify a decrease in cases.
First define a region by placing an arbitrary line around an area. It is best to use pre-existing borders such as county lines, or establish new ones specific to the issue being studied (Covid-19 case reduction).
After specific border lines have been established to create an area to be observed, we can further define the criteria. For example, the first criteria was to create a grid outlining the area with the least amount of people per capita (by population counts).
Next would be to determine which area has the most available of preexisting information. Hence, the second objective would be to obtain Covid-19 test results from tests that have been previously conducted in that area.
Next is a case example of a county borderline showing the amount of individuals who reside in a given location. The expected initial start point would be from the area with the least amount of individuals present in a region. In this case that can be observed by the population count which reflects the smallest amount of people.
In this next example, the amount of Covid-19 positive test results are reflected in a given region, removing the time points established in order to interpret the data in another format including positive test scores.
This is an example with multiple data points utilizing the available numbers in a given area with real time positive results for Covid-19 testing. These can be used to superimpose with current population demographics that would be used to reflect a basic general summary predicting whether or not an area is in the process of implementing a decline in positive cases with the health measures in effect. Because the chart does not reflect a consistency of decline in simultaneous consistency with the implementation of health measures clearly there are factors that are not being accounted for.
In the current situation with the expected availability of vaccines among the population it should be determined which method will be most effective to observe an immediate decline in cases from the projected time point of two weeks post vaccination. In addition in order to calculate the impact of positive virus exposure to the mainstream population it must be taken into consideration that first, most test results have shown that the test was positive (refer to chart below), and second that there is a consistency in the increase of positive exposure results throughout the time point.
There are a number of options on how to proceed in order to categorically organize the distribution of vaccines throughout the country.
Additional questions to consider after the identification of the population in the region where a given demographic is being documented include the following.
A basic ratio of cases exposed, asymptomatic vs. symptomatic, numbers exposed with negative test results and projected vaccinations impact.
Establish out a time line for in effect, recall that the vaccine should be working within 2 weeks so projections should be prepared accordingly in addition to predictive values measured.
With larger demographics and large scale populations there are several more variations to consider.
Starting by state, county, demographic, gender, age, and institutions. Regarding institutions, within each, numbers can be documented as well, such as as schools, private businesses, corporations, etc.
