COVID-19: Treatment and Prevention

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Table of Contents

The Condition in Terms of Magnitude, Person, Place, and Time
The Risk and Protective Factors
Population At-Risk
The Study Methodology, Data Collection, and Potential Sources of Bias
Results
Potential Sources of Bias
Alternative Methodology
References

The COVID-19 epidemic is wreaking havoc on public health and well-being and certainly persists due to its detrimental influence on the economy. Despite significant advances in clinical research that have resulted in a better knowledge of and treatment of COVID-19, restricting the further transmission of this disease and its mutations is now an issue of growing concern as its impacts continue to be felt globally. Several countries are facing subsequent waves of the outbreak, mainly linked to the advent of mutant versions. Against this backdrop, many studies have been conducted to understand COVID-19 and identify ways to prevent, manage, and control the virus. One such study was conducted by Mehra et al. and was heavily criticized for failing to prove the veracity of their primary data sources. The critical evaluation of the research reveals areas of bias in the aims, methods, confusing variables and results and recommends an alternative research approach.

The Condition in Terms of Magnitude, Person, Place, and Time

The rate of infections was exponential such that the world health organization declared it an outbreak in January of 2020. In March of the same year, it was said a pandemic due to its increasingly high infection rate and spread. Until early 2020, scientists believed the disease could only be transmitted through cough and sneeze droplets. However, it was then discovered the virus could survive in the open air and thus was airborne. Almost three years have passed since the first case of infection was recorded, and in this period, the virus developed a range of variants, which contributed significantly to its fast rate of spread. Some of these variants, as recorded by the World Health Organization (2020), include; Alpha, Beta, Gamma, Delta, and Omicron. Each variant became more infectious than its predecessor in three years. The virus variant acted as a survival mechanism for the virus, making vaccine development even more difficult.

The coronavirus disease affects everyone but has devastating effects on older adults, especially those sixty-five years and above. Also, it affects people with underlying health conditions. For instance, people living with HIV/AIDS and those living with diabetes were at higher risks of succumbing to the infection because their immune systems were already stretched. Even though the pandemic was worldwide, some areas were affected more than others, and causalities varied worldwide. Europe was the most hit with 249,105,808 cases, followed by America with 176,342,137 points, then Western Pacific with 85,868,508 cases (WHO, 2020). As per WHO records, Africa was the least affected continent, with only 9,298,893 instances. According to the World Health Organization, the pandemic had a varying effect pattern in that, depending on the variant, the infections would either increases exponentially or reduce. For instance, the highest infection rates were recorded between December 2021 and March 2022, and deaths caused by the disease were highest between November 2020 and February 2021 (WHO, 2020). Thus, the pandemic had a varying effect across different regions.

The Risk and Protective Factors

During the pandemic, it was noted that certain factors predisposed different groups of people to the coronavirus disease. These factors included age, very young, ethnic disparities, pre-existing conditions, and male sex. Older people risk being infected because their immunity is weakened over time and thus might easily contract the disease. Very young children also risk being easily infected and succumbing to the contagion because their immune system is not yet fully developed. People with pre-existing comorbidities also have a higher risk of infection because their conditions stretch their immunity (Anesi, 2021). As such, the virus will easily infect them and even result in their death effortlessly.

Despite the high risk of being infected with the COVID-19 virus, which suggested steps to improve an individual’s fighting chances against the coronavirus disease. Some of these actions include; a healthy diet, better nutrition, regular exercise, and COVID-19 vaccination. The vaccination is significant because it improves a person’s immunity and capability to combat the virus in case of infection (Centers for Disease Control and Prevention (CDC), 2022). On the other hand, a healthy diet and regular exercise help keep one’s body fit and immunity active in case of an infection.

Population At-Risk

The COVID-19 virus has affected everyone from different walks of life; nonetheless, it has affected others more than others. Some groups affected the most included; Black, Hispanic, NHOPI, AIAN, and older adults (CDC, 2022). Over 84 million recorded cases, 65% of which were attributed to ethnic differences (CDC, 2022). Black, Hispanic, and NHOPI people were more likely to contract and die from coronavirus than White people (Fauci et al., 2020). However, in terms of old age, COVID-19-related deaths were higher among White people than other races.

The Study Methodology, Data Collection, and Potential Sources of Bias

This worldwide research used a patient registry of 671 hospitals from six continents. These comprised North America, Europe, South America, Asia, Africa, and Australia (Mehra et al., 2020). The real-world evidence was given by the Surgical Outcomes Collaborative and was gathered from EHR systems, supply chain records, and accounting transactions. All patients with PCR-verified cases of COVID-19 who were hospitalized between 20 December 2019 and 14 April 2020 and had a release or in-hospital death were considered. Patients who began treatment with hydroxychloroquine/chloroquine (HCQ/CQ) more than 48 hours following COVID-19 detection were eliminated (Mehra et al., 2020). In addition, patients who began medication while undergoing mechanical ventilation or Remdesivir medication were disqualified.

There were four therapy options: CQ only, CQ plus a macrolide, HCQ only, and HCQ plus a macrolide. The remaining patients comprised the control population. Regarding data collection, patients’ baseline characteristics, such as age, BMI, sex, race, underlying ailments, and other medications, were recorded (Mehra et al., 2020). Information on the administration of HCQ, CQ, and enhanced macrolides was documented.

Results

The main result was the correlation between in-hospital death and the usage of therapeutic interventions comprising HCQ/CQ. In this case, the researchers did not consider whether the interventions included macrolides. The incidence of medically relevant ventricular arrhythmias was a tertiary result related to various treatment plans (Mehra et al., 2020). Other results comprised the incidences of mechanical ventilation usage and the overall duration of care in the ICU.

Potential Sources of Bias

Whenever a patient developed diabetes but it was not documented in his clinical file, they were not deemed diabetic. Since doctors are already stretched, such gaps in data are likely common across all medical records worldwide, leaving room for enormous biases. For example, a simple arrhythmia diagnosis without any further detail introduces a substantial possibility of misidentification bias in a crucial study conclusion (Mehra et al., 2020). Additionally, when patients’ outcomes at baseline are completely unexpected, it raises concerns about substantial bias in selecting individuals.

Indeed, except for Australia, the baseline documentation of patients was similar among the six regions investigated, despite the significant variances expected due to heterogeneity in epidemiology, demographic, age, weight, and more. Lastly, the hospital fatality rate in this research was 11% (Mehra et al., 2020), which appears incongruous with the data published in other regions, where it varied from 23% to 50% (Bains, 2020). The low hospital death rate in this research suggests a bias in the cohort. This is congruent with the below-mentioned low severity of the research population, which contradicts the hospitalization in all regions.

Alternative Methodology

In this case, the ideal study approach would be a cross-sectional research design. This research method is selected because it can assess the frequency of health outcomes, health indicators, or both in a community at a particular time (Geto et al., 2021). Accordingly, the approach would be useful in discovering information regarding the etiology of COVID-19, such as the specific point of the essence in Wuhan, China. The area under study must be equipped with adequate screening, quarantine, and testing centers. The population under investigation must be a community comprising all people, making it a representative sample. Those suspected to be infected are isolated, and the participants are randomly selected using a random sampling technique.

Lastly, data collection is done cautiously, following all the guidelines. The medical personnel then collect pharyngeal specimens using sterile cotton swabs and place them in transport medium containers (CDC, 2022). The samples are in favorable temperatures and taken to the laboratory for testing. The community-based cross-section study will help guarantee reliable findings. Nevertheless, one of the most likely sources of biasness in this study method is the non-response problem. Here the features of a responder tend to differ from those of the responders.

References

Anesi, J. (2021). Commentary: Effectiveness of two‐dose vaccination with mRNA COVID‐19 vaccines against COVID‐19‐associated hospitalizations among immunocompromised adults—nine states, January–September 2021.American Journal of Transplantation, 22(1), 304–305. Web.

Bains, M. (2020). COVID-19 death rate at Metro Vancouver hospital ICUs notably lower than in other countries: study. CBC. Web.

CDC. (2022). Stay Up to Date with COVID-19 Vaccines Including Boosters. Centers for Disease Control and Prevention. Web.

Fauci, A. S., Lane, H. C., & Redfield, R. R. (2020). Covid-19—navigating the uncharted.New England Journal of Medicine, 382(13), 1268-1269. Web.

Geto, Z., Gebremichael, S., Belete, M. A., Gedefie, A., Molla, G., Tesfaye, M., Demsiss, W., & Gebretsadik, D. (2021). The escalating magnitude of COVID-19 infections among the Northeastern Ethiopia Region: A Community-Based Cross-Sectional Study.International Journal of Microbiology, 2021, 1–9. Web.

Mehra, M. R., Ruschitzka, F., & Patel, A. N. (2020). Retraction-Hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19: a multinational registry analysis.Lancet (London, England), 395(10240), 1820. Web.

WHO (2020). WHO Coronavirus Disease (COVID-19) Dashboard.Bangladesh Physiotherapy Journal, 10(1). Web.

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