Background The sudden appearance of SARS CoV 2 has opened a new research horizon to explain any new replication mechanisms and expand what is known already about members of this family of novel Coronaviruses so as to assist their control and prophylaxis. Objectives: This study was designed to access the risk for acquisition and transmission, of the novel Severe-Acute Respiratory Syndrome Corona Virus 2, (SARS-COV 2) in different geographical communities. Materials and methods In this qualitative questionnaire-based online survey, randomly selected 136 participants were selected from the researcher’s mailing lists using defined inclusion criteria. Using a survey monkey online tool, original emails were sent followed by 4 consecutive follow-up emails in a period of 4-6 weeks during the time of this study. Five Likert scale (Strongly Agree, Agree, Indifferent, Disagree, Strongly Disagree and others) formed the basis for which selected participants were questioned on nine factors (Exposure rate, population density, movement, and timely testing, age, compliance, conflict, and displacement, type of exposure and demographic data of clients) for “COVID-19” transmission. The correlation between questions asked and consenting participants’ responses were analyzed using the Heatmap software. Results One hundred and thirty-six questionnaires were sent out to be answered in 4-6 weeks but 37 were completely filled and returned and Ninety were not returned while 7 emails bounced and were not delivered giving a response rate of 28.68% and a non-response rate of 71.32% respectively. There was no correlation (Heatmap value <50) between all questions asked and strongly disagree, agree and others implying that all respondents were correct if they disagreed with questions suggesting a negative relationship between “COVID-19” distribution and all questions. There was also no correlation between travel reasons types of exposure and indifference confirmed by the fact that respondents were indifferent on whether travel reasons and type of exposure are risk factors for “COVID-19” distribution. Exposure rate, Age, timely testing, displacement, and population density showed the greatest correlation when compared to strongly agree response rate (Heatmap value >0.5). This means that respondents were correct when they said they strongly agree that exposure rate, age, timely testing, displacement, and population densities were all factors for “COVID-19” distribution. Conclusions Therefore, this study has shown that exposure rate, population density, timely testing, and age, were strong factors that significantly affected the distribution of “COVID-19” with a hit map value of greater than 50). Exposures to different strains of Coronaviruses as well as their impact on virus transmission in tropical settings were discussed.
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