Articles related to Modelling in epidemiology

Role of serological and molecular marker analysis in emerging infectious diseases

Traditional methods of infectious disease diagnosis are Gram- staining, pathogen culturing, and study of virus morphology by inoculating culture. Conventional techniques are time-consuming and lack sensitivity. Serological and molecular markers are new diagnostic approaches that offer rapid, sensitive and more accurate diagnostic results. Molecular markers are a specific short sequence of DNA or RNA. Molecular markers are capable of detecting polymorphism in the specific chromosomal region associated with unique chromosomal locations, that can be random. On the other hand, serological markers are used to measure the concentrations of an antibody. These are potentially the most direct way to decipher the dynamics of a population’s responsiveness and diagnosis of a disease (Metcalf et al., 2016). Read more »

Spatial modeling in disease epidemic studies

Epidemiology of infectious diseases often requires geographical information. Both spatial and temporal factors of a population can affect disease spread. Spatial factors refer to the geographical or topological factors associated with a disease. Temporal factors mean time-bound progress of a disease in a population. These factors influence the virulence of the disease, patterns of prevalence and also future incidents. Read more »

Time series and forecasting models in disease epidemiology

Time series analysis refers to the analysis of observations that are time-dependent. Therefore, observations from an event are dependent upon the time at which it took place. Time intervals can be minutes, hours, days, months or years. Observing the trends of these events over a long period enables identifying hidden relationships. Moreover, future trends can be predicted using this analysis. Read more »

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