Optic neuritis and vaccination investigation: failure to consider significant sex differences and multiple vaccine...

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:

Encephalitis is inflammation of the brain parenchyma, most often due to infections or autoimmune processes. It presents with neuropsychiatric features such as fever, altered mental status, behavioral changes, cognitive dysfunction, seizures, focal deficits, and sometimes autonomic instability. In some cases, the meninges are also involved, resulting in meningoencephalitis.Infectious CausesInfectious encephalitis is most commonly viral but can also result from bacterial, fungal, or parasitic...

Arboviral encephalitis refers to brain inflammation caused by arthropod-borne viruses, particularly those transmitted through mosquito vectors. Among these, West Nile virus (WNV), a member of the Flaviviridae family, is a significant public health concern. WNV is an enveloped, positive-sense, single-stranded RNA virus. Human infection typically begins when an infected mosquito introduces the virus into the dermis during feeding. The primary transmission cycle involves birds as amplifying hosts...

Encephalitis is inflammation of the brain parenchyma caused by direct viral invasion or immune-mediated mechanisms triggered by infections or tumors. Both processes lead to neuronal injury, disrupted neurotransmission, and diverse neurological symptoms, often with overlapping clinical and pathological features.Autoimmune EncephalitisIn autoimmune encephalitis, antibodies target neuronal antigens on cell surfaces, synapses, or within neurons. A key example is anti-NMDAR encephalitis, which can...

Overview

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 phenomenon...