Evaluation of the Factors Associated with Reinfections towards SARS-CoV-2 Using a Case Control Design

Giuseppe La Torre1, Gianluca Paglione1, Lavinia Camilla Barone1

  • 1Department of Public Health and Infectious Diseases, Sapienza University of Rome, 00185 Rome, Italy.

PubMed
Abstract

Insights

Female healthcare workers, those with diabetes, and individuals with higher alcohol consumption face increased risk of SARS-CoV-2 reinfection. Increased red blood cell counts also correlate with higher reinfection odds.

Area of Science:

  • Infectious Diseases
  • Epidemiology
  • Public Health

Background:

  • The emergence of SARS-CoV-2 variants has heightened concerns regarding reinfection risks.
  • Understanding factors contributing to reinfection is crucial for effective pandemic control strategies.

Purpose of the Study:

  • To identify and evaluate factors associated with SARS-CoV-2 reinfection among healthcare workers.
  • To compare reinfection risks between healthcare workers with multiple infections, single infections, and no prior infection.

Main Methods:

  • A case-control study was conducted at a teaching hospital between March 2020 and June 2022.
  • Cases comprised healthcare workers with SARS-CoV-2 reinfection; controls included those with one infection or no infection.
  • Statistical analysis determined odds ratios for various risk factors.

Main Results:

  • Female gender was associated with a 2.42-fold increased odds of reinfection.
  • Moderate to high alcohol consumption increased reinfection odds by 1.49 times.
  • Diabetes (OR: 3.45) and elevated red blood cell counts (OR: 1.69) were also significantly linked to higher reinfection risk.

Conclusions:

  • Healthcare workers with diabetes, women, and those with higher alcohol consumption require targeted preventive measures.
  • Contact tracing and health education are vital components of SARS-CoV-2 pandemic management.
  • Identifying specific risk factors aids in developing personalized prevention strategies.

Related Concept Videos

Factors Affecting the Risk of Infection01:26

Factors Affecting the Risk of Infection

The hosts' susceptibility to infection depends on several factors. The integrity of the skin and mucous membranes helps protect the body against microbial attacks. When the skin is altered, the chance of infection, limb loss, and even death increases.
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
12.0K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
148
Controls in Experiments01:13

Controls in Experiments

When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more reliable. Controls are elements in an experiment that have the same characteristics as the treatment groups but are not affected by the independent variable. By sorting these data into control and experimental conditions, the relationship between the dependent and independent variables can be drawn. A randomized experiment always includes a...
7.9K
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
198
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
288
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
380