EXODUS PROBABILITIES FROM A STRUCTURAL-ZERO CATEGORY: ILLUSTRAION OF PUBLIC, KNOWLEDGE, PERCEPTION, AND COMMUNICATION ON COVID-19

Background: Medical and healthcare professionals and governing agencies have faced big challenges to control, intervene and prevent the spread of COVID-19. In analysis of survey data on COVID-19, some practiced probability laws are nullified. Among those probability laws, the structural-zero (different from sampling zero) category with respect to the people’s knowledge, perception, and communication about the COVID-19 pandemics occurs in surveys is an example. Results: Exodus probabilities are derived and utilized. Using a recent survey data on COVID-19, the proposed method to configure such probabilities (proportions) is illustrated. Conclusion: The research question is about a way to configure the proportions who might have transited from the structurally zero category to other viable categories. This research question is answered in a novel manner.


Introduction
It is quite needless to formally describe the pandemic COVID-19 (otherwise known as coronavirus) ever since January 2020, the whole world is frightened by the viral nature of this pandemic. The virus was detected on 24th January 2020, in the Wuhan city (capital of the Hubei province), China (Cohen, 2020). China reported to have seen 1,287 coronavirus cases and 41 among them have died [7 for details]. When the World Health Organization (WHO) was informed by China, the WHO chose to give the name COVID-19 to this deadly virus and declared it a pandemic as it spread to almost all countries in the world. First, it was falsely understood that the COVID-19 was contagious from dead or alive animals and the virus did not spread from a human to another human [5].
Despite a pandemonium which existed in many nations around the world, China discovered that on 25th March 2020, an estimated 81,285 persons contracted COVID-19 and 3,287 of them died.
Alarmed by this rapid increase, many nations quarantined their people in their home and educated the citizens to do social distancing and adapt several personal hygienic practices as the incubation time between the exposure and disease onset was estimated (not medically proven) to be 2 to 14 days [1]. As of 30 th May 2020, there have been more than 5,817,385 COVID-19 cases worldwide and at least 362,705 deaths have occurred already (see https://www.who.int/situationreport-131.pdf for details). The numbers are staggering and changing daily. The gravity of the health hazards and the fear of death cannot be adequately described. The day to day activities were crippled. The productivity reached near zero everywhere on earth.
The COVID-19 has been destructive and challenging to medical and healthcare professionals and governing agencies. For analysis of survey data, some practiced probability laws are nullified.
Among those probability laws, the structural-zero (different from sampling zero) category with respect to the people's knowledge, perception, and communication about the COVID-19 pandemics occurs in surveys is an example. Is there a way to configure the proportions who might have transited from the fourth (structurally zero) category to other three viable categories?
This question is answered in a novel manner in this manuscript using a recent survey data on COVID-19.

Public Knowledge, Perception, and Scientific Communication
A COVID-19 [3] survey was conducted among the Malaysians to examine their public knowledge, perception, and scientific communication about the COVID-19. The public knowledge is often connected with the risk to survive. The perception is based on more of cultural or gender bias. The Science communication is a skill due to education to effectively disseminate information in the public domain. See also a follow-up article by [4] (1).
Because the probability of an intersection event is less than the marginal probability (that is is a proportionality statement and it yields an imbalance measure between the events A and B We name A  and B  the exodus probability to A and B respectively. In conjunction with the exodus probabilities, realize that Furthermore, we notice from (1) It is well known that the conditional probability is no lesser than the unconditional probability.
That is, Pr( ) Pr( ) B A B  . Hence, we can assess how much an impact of knowing that A has occurred on speculating the likelihood of B and such an impact is An analogous expression to quantify the impact of knowing that B has occurred on speculating the likelihood of A and such an impact is Definition2. The exodus odds of transiting from the structurally zero category, A B  to the category, B is We now could define the exodus odds ratio of transiting from the structurally zero category, When the odds ratio, Odds Ratio is more than one, the exodus odds to the category, A is more likely than its counterpart category, B from the structurally zero category, A B  .

Illustration Using Malaysian Survey Data on COVID-19
We now illustrate the derived expressions of Section 2 using the survey data about the Table 1 through Table 3 for the observed proportions in each category given in [3].   (7) are calculated and displayed in the Table 4, Table 5, and Table 6 below for the Malaysians' knowledge, perception, and communication, respectively.  Table 5. Exodus probabilities for perception on COVID-19 Odds Ratio

Declarations
Ethics approval and consent to participate No ethical approval required and no consent requirement to participate since the used data are from a public domain.

Consent for publication
Yes, we approve.