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Gaps in mobility data and implications for modelling epidemic spread: A scoping review and simulation study.

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Summary

Accurate human mobility data is crucial for tracking infectious disease spread in Africa. Using mobility proxies can lead to significant, unpredictable biases in epidemic predictions, highlighting the need for better empirical data.

Keywords:
Gravity modelHuman mobility dataInfectious disease spreadMathematical modellingRadiation model

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Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Public Health

Background:

  • Accurate human mobility data is vital for understanding and controlling infectious disease spread.
  • Limited availability of high-resolution human mobility data in Africa often necessitates the use of model-derived mobility proxies.
  • Existing empirical mobility data in Africa often captures long-term patterns, unsuitable for short-generation-time pathogens.

Purpose of the Study:

  • To review human mobility data sources and models used in Africa.
  • To assess the impact of using mobility proxies on infectious disease spread predictions through a simulation study.

Main Methods:

  • Systematic review of human mobility data sources and models in Africa.
  • Simulation study to evaluate the effects of mobility proxies on epidemic dynamics predictions.

Main Results:

  • Significant gaps exist in empirical subnational mobility data across African nations (available for only 17/54 countries).
  • Mobility proxies introduce complex and non-intuitive biases in predicting epidemic invasion times, order, and peak timing.
  • The impact of mobility proxies varies significantly based on the proxy type and the specific country context.

Conclusions:

  • There is a critical need for regularly updated, empirical population movement data within and between African countries.
  • Developing an evidence base is essential to guide the selection of appropriate mobility data for different infectious disease scenarios.
  • Improved mobility data is crucial for effective infectious disease outbreak prevention and control in Africa.