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Updated: May 23, 2025

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
Verhulst-type equation and the universal pattern for global population growth
Agata Angelika Sojecka1, Aleksandra Drozd-Rzoska2
1Department of Marketing, University of Economics, Katowice, Poland.
Global population growth shows two distinct linear phases, challenging traditional Verhulst models. Analysis reveals historical events impact population dynamics, suggesting a need for refined scaling equations for accurate global population predictions.
Area of Science:
- Demography
- Mathematical Modeling
- Sustainable Development
Background:
- The Verhulst model is a standard for population growth.
- Sustainable development concepts are linked to population dynamics.
- Accurate global population data is crucial for long-term planning.
Purpose of the Study:
- To analyze global population growth patterns using a novel data preparation method.
- To evaluate the adequacy of Verhulst-type scaling for describing population changes.
- To identify potential correlations between population "disturbations" and historical events.
Main Methods:
- Analysis of per capita global population growth rate ([Formula: see text]) from 10,000 BCE to 2023.
- Application of a 'reversed protocol' analysis involving data transformation and fitting.
- Numerical filtering of collected data to create an optimal dataset.
Main Results:
- Identified two near-linear domains for population growth rate changes (700 CE–1968 and 1968–2023).
- Found that Verhulst scaling with a single parameter set does not adequately describe observed population changes.
- Revealed links between local population "disturbations" and historical/prehistorical events.
Conclusions:
- Standard Verhulst models may be insufficient for describing long-term global population dynamics.
- A refined approach to data preparation and analysis is necessary for accurate population modeling.
- Historical events have demonstrably impacted global population trends.
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