Adolescent fertility trends and surveillance gaps in Latin America

Male infertility affects millions of couples worldwide, arising from various factors that impact different stages of the reproductive process. An endocrine imbalance resulting from conditions like hypogonadism, Klinefelter syndrome, or pituitary disorders can disrupt hormone levels and reduce sperm production. Testicular defects, such as tumors, cryptorchidism, atrophic testes, abnormal sperm morphology, and low sperm count or motility, may arise due to genetic factors, structural...

Female infertility is defined as the inability to conceive after a year of regular, unprotected intercourse and affects about 10–15% of couples worldwide. The primary cause of female infertility is ovulatory disorders, which hinder the release of eggs. These disorders can be classified as hypothalamic amenorrhea, polycystic ovarian syndrome (PCOS), premature ovarian failure, and hyperprolactinemic anovulation disorders.
Endometriosis, a condition characterized by abnormal growth of...

Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.

In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...

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:  

Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...