The Importance of Vaccination in the Mitigation of Coronavirus Epidemic: Computer Simulations on a F
At the onset of a viral epidemic, individual measures in combination with the isolation of the symptomatic are practical means of mitigating the disease. These approaches delay infection rates such that the acquisition of quarantine and other community resources can cope with the rise of the seriously ill. The infection cycle, however, will continue until all susceptible members of the community have been infected. Only vaccination can reduce the number of those susceptible and break the progress of infection. The problem with vaccines lies in the length of time it takes to identify the virus and to develop, manufacture and deploy the vaccine throughout the community. The current pandemic underscores the importance of a rapid vaccine development facility at a state of constant readiness in responding against any new infectious disease.
To quantify the relative effectiveness of placing symptomatic people in quarantine and mass inoculation, we at Mgmtlaboratory.com used a flu epidemic computer model (1) (2) with minor modifications to accommodate new information about the COVID-19 disease.
The computer model simulated a city of 3 million in population with estimated susceptible residents of 14 thousand. The chart above shows “flattening of the curve” with the increased quarantine of the symptomatic as expressed in percentage of the population. The chart below,
on the other hand, Illustrates the reduction of symptomatic cases as the number of people vaccinated increased. The magnitude of the reduction made us conclude that while individual measures and the quarantine can attenuate the exponential rate of infection, vaccination remains the key in managing the COVID-19.
Experiments on a Computer Epidemic Model. The dynamic system (1) (2) (3), illustrated below describes how the flu, a viral disease spreads through a closed population over time. The settings of that model were left intact with minor modifications. For our purpose, we assumed that on the average of six days after infection, symptoms become detectable either by testing or being physically visible. From this point, while still remaining infectious the person eventually recovers on an average of 14 days. At this time about three percent of those that have been symptomatic will die.
The first set of simulations consisted of varying the proportion of those isolated or quarantined from symptomatic residents, from no isolation, 20% isolation, and 40% isolation. At each of these three settings, the number of cases, deaths at the peak and days to peak cases were noted under the curve’s peak. The experimental data tabulated below shows the modest flattening of the curve.
The second experiment involved simulations on the epidemic model with varying reduction of the susceptible population, from none vaccinated, to 1%, 3% and finally 5% vaccinated. At each of these four settings, the number of cases, deaths at the peak and days to peak cases were noted under the peak of the curve. This time, the experimental data tabulated below shows a marked reduction in the number of COVID-19 cases. The migration of peak cases tended towards shorter days from infection.
The notion of the superior mitigating effect of anti-viral vaccines on viral epidemics such as COVID-19 in comparison to quarantine is supported by these experiments.
By Mgmtlaboratory.com Staff, 2020.
References:
Systems Dynamic Model by George P. Richardson. Visiting Professor in Science Technology and Public Policy, Humphrey Institute of Public Affairs, University of Minnesota 2009.
Systems dynamic model developed using Vensim, a software by Ventana Systems, Inc.
Noel Jagolino. Epidemic Basics for Health and Human Services Administrators, Mgmtlaboratory.com. March 3, 2020.