Applied Stochastic Solutions, Dynamic Analysis, and Mathematical Models for Issues in Demography, Epidemiology, and Environmetrics
Deadline for manuscript submissions: 20 September 2024 | Viewed by 54
2. Department of Health Monitoring and Biometrics, aQua-Institut, 37073 Göttingen, Germany
Interests: forecasting; time series analysis; multivariate methods; stochastics; demography; epidemiology; econometrics; social insurance; gerontology
Interests: complexity/diversity and stability; species coexistence; community ecology; conservation biology; biostatistics
Special Issues, Collections and Topics in MDPI journals
Many real-world phenomena, be they social, ecological, or biological in general, do not follow predefined patterns but rather exhibit random behavior. To name a few examples, we do not know ex ante the number of migrants arriving at a certain destination during a given period; neither do we know the damages and associated costs that will arise for an insurance company due to natural hazards (e.g., hurricanes) before they occur. We also do not know how a specific individual will respond to a certain treatment for a disease, or even if/when the individual will contract the disease. These examples illustrate that phenomena are often stochastic, although they are often modeled using deterministic methods that typically identify a mean or median outcome. However, uncertainty or risk are often not quantified at all or may only be quantified by scenario analyses that cover only a minor share of possible scenarios and commonly do not assign probabilities to these scenarios.
This Special Issue stresses the engineering and application of stochastic approaches for real-world applications, such as in economics, sociology, geography, epidemiology, biometry, or ecology. You are cordially invited to submit papers related to all aspects of stochasticity in real-world applications. These might be approaches in forecasting, the estimation of bias due to underdetection (e.g., in migration or disease research), or interpolation and imputation methods. Another current example is how to appropriately include stochasticity in disease modeling. Other applications involve the modeling of natural disasters. This list is not exhaustive, and fitting papers that present either theoretical or empirical approaches to deal with issues in fields associated with demography, epidemiology, biometry, or environmetrics are welcome. Please note that innovative approaches that develop novel ideas instead of applying established approaches to new data or topics are especially encouraged. The major intention of this Special Issue is to advance methodological standards, although illustrative applications of established methods to a broad readership are also welcome.
Authors who would like to make sure that their paper concept fits the scope of the Special Issue are highly encouraged to send a proposal (about 1–2 pages) to Patrizio Vanella ([email protected]) on their intended paper beforehand. We look forward to your submissions.
Dr. Patrizio Vanella
Dr. Giorgos Kokkoris
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- applied mathematics
- error assessment
- bias estimation