Prevalence of COVID 19 and Possible Risk Mitigation

Epidemiology COVID 19

COVID-19, caused by the SARS-CoV-2 virus, has been associated with several risk factors. Age and pre-existing health conditions, such as cardiovascular disease, diabetes, chronic respiratory disease, and cancer, are prominent factors that increase the severity of the disease (Rahman et al., 2021). Behavioral factors, like smoking, can also exacerbate the risk (Ko et al., 2020).

The primary mode of transmission for COVID-19 is through respiratory droplets when an infected person coughs, sneezes, or talks (Ko et al., 2020). It can also spread by touching surfaces contaminated with the virus, then touching the face. A study published in The Lancet confirmed these modes of transmission, suggesting the need for hand hygiene and respiratory precautions (Chu et al., 2020).

To calculate incidence, one needs the number of new cases in a specific time frame divided by the at-risk population. Prevalence is determined by the total number of cases (new and existing) during the same timeframe divided by the current population. Assuming the global population at the beginning of the period is 7.821 billion, and that there are 20 million new cases reported within a year, and that there are a total of 50 million cases (both new and existing) by the end of the year. The calculated rates are as follows:

· Incidence Rate: Approximately 255.72 new cases per 100,000 people in the population. This reflects the frequency of new cases occurring during the year.

· Prevalence Rate: Approximately 639.30 total cases per 100,000 people in the population. This indicates how widespread the condition is at a particular point in time, considering all cases.

The mortality rate can be calculated by dividing the number of deaths by the number of confirmed cases. This rate provides insights into the lethality of the disease. If we have the total number of deaths and the total number of confirmed cases, 1,500,000 deaths due to COVID-19 (50,000,000 confirmed cases of COVID-19), the calculated mortality rate would be 3.0%. This means that in the scenario, for every 100 confirmed cases of COVID-19, there were 3 deaths attributed to the virus.

The odds ratio (OR) is a measure of association between an exposure and an outcome. An OR greater than 1 indicates a positive association; less than 1 indicates a negative association. For COVID-19, examining the OR could reveal how strongly factors like travel history or contact with confirmed cases are associated with contracting the disease. If there are 400 cases with severe disease outcomes have pre-existing conditions.

· 100 cases with severe disease outcomes do not have pre-existing conditions.

· 600 cases without severe disease outcomes have pre-existing conditions.

· 900 cases without severe disease outcomes do not have pre-existing conditions.

The calculated odds ratio (OR) is 6.0. This would suggest that in this scenario, the odds of patients with pre-existing conditions having severe disease outcomes are 6 times higher than for those without pre-existing conditions.

With respect to the levels of prevention, Primary Prevention aims to prevent the disease before it occurs. This includes measures like vaccinations, health education, and lifestyle modifications such as diet and exercise. Secondary Prevention aims to reduce the impact of the disease that has already occurred. This includes early detection and prompt intervention, such as screening tests and treatment. Tertiary Prevention aims to soften the impact of an ongoing illness or injury that has lasting effects. This includes rehabilitation and support services, and also measures to prevent recurrence and maximize quality of life.

In essence, the difference lies in the timing and the objectives: Primary prevention seeks to avoid the development of disease. Secondary prevention aims to identify and treat asymptomatic disease which has already started to develop. Tertiary prevention focuses on treating symptomatic disease to slow progression, prevent complications, and restore function. Each level of prevention plays a crucial role in the continuum of care and contributes differently to the control and reduction of healthcare problems.

Conclusion

Given the high OR for severe outcomes in patients with pre-existing conditions, a possible research question could be: "What are the effective intervention strategies to reduce the risk of severe COVID-19 outcomes among patients with pre-existing conditions?"

An observational study could be appropriate for initial exploration of the effectiveness of existing interventions, while an experimental study might be used to test new interventions in a controlled setting.