Articles related to Biostatistics in epidemiological studies

## Common pipeline for statistical analysis in epidemiological studies

Previous articles discussed the need for statistical analysis and modelling of epidemiological studies in public health studies. The analysis in epidemiological studies typically requires descriptive and analytical methods. Descriptive analysis of epidemiological data includes hypotheses development. This is based on the variability of disease outcome rates with demographic variables. On the other hand, analytical epidemiology determines the cause or mode of disease epidemic outbreak. Read more »

## Statistical tests in descriptive and analytical epidemiology

In the previous article, the importance of statistical analysis in epidemiological studies was established. Statistical analysis can contribute towards strategic planning of public health strategies. Consequently, this analysis is mainly done through mathematical and statistical techniques. Both offer unique advantages and purposes. 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 »

## Significance of statistical analysis in epidemiological studies

Infectious diseases continue to pose a significant threat to humans and animals. Stringent disease control policies and advancement in vaccines have not eradicated them. Therefore, in 2015 alone, 10 top deadly diseases were responsible for killing 30 million people. Among these diseases, communicable diseases like lower respiratory infections, diarrhoea, tuberculosis and HIV were the major culprits (World Health Organization, 2017). Read more »

## Extracting information of TGF-β1 gene using National Center for Biotechnology Information (NCBI)

In order to understand the process of using National Center for Biotechnology Information (NCBI) for extraction of gene information for bioinformatics studies, the author uses case example of Transforming Growth Factor beta 1 (TGFβ1) gene which encodes for the TGFB1 protein found in humans. Transforming growth factor beta 1 or TGF-β1 is a polypeptide and therefore belongs to the superfamily of cytokines (Ciftci et al., 2014). It has many cellular functions, such as cell growth, cell proliferation, cell differentiation and apoptosis (Jackowska et al., 2013).

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