Statistical Methods with Applications in Human Health and Disease

Dear Colleagues,

In a broad sense, biostatistics is the branch of statistics that centres on the development and use of statistical methods to address problems that arise in biology. Nowadays, talking about biology supposes considering a vast area of knowledge, and biostatistics accompanies all of these fields. In particular, human biology and medicine have made this discipline their own, in such a way that biostatistics is often conceived as the set of methods that solve the problems that arise in biomedical research. This Special Issue of IJERPH intends to address some of the subjects that appear in this biomedical facet of biostatistics.

Any manuscripts related to the development of statistical methods with applications in human health and disease are welcome. Nevertheless, let us consider some topics of particular interest.

Nowadays, our society is experiencing what it means to live through a pandemic firsthand. Mathematical modelling has proven to be a handy tool to predict the evolution of infections and to decide the best policy of action. Formal models can be built from different points of view, namely deterministic, stochastic, and statistical approaches. Although it is a more complex task, the stochastic approach is more realistic than the classical deterministic one. Moreover, the statistical approach is based on the observed data. Both stochastic and statistical modelling of the evolution of the infectious disease and the interaction of pathogen–organism are of interest in this Issue, particularly, the estimation strategies of formal parameters from observable data.

Medical diagnosis is another area in need of attention. Diagnosis is often challenging. On the one hand, the predictive values of the diagnostic procedures depend on the prevalence of the illness. On the other hand, many indexes of the disease can be difficult to be observed and quantified, so that, frequently, the diagnosis relies on agreement among specialists. Moreover, diagnosis sometimes requires categorization of continuous scales through cutpoints. This procedure is sometimes far from optimal, and frequently grey zones can appear where the diagnosis can be fuzzy.

Related to diagnostics is measuring the effect size due to the exposition of risk factors or interventions. In the presence of comorbidities or specific demographic characteristics, effect modification is related to the concept of interaction. Frequently, studying interactions relies on non-standard and intricate designs. Risk evaluation and strategies of data acquisition are also topics of interest.

Dr. Pedro Femia-Marzo
Guest Editor

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