Published November 10, 2022 | Version v1
Poster Open

Harnessing the Potential of Digital Data for Infectious Disease Surveillance in sub-Saharan Africa

Creators

  • 1. Department Health Sciences, Hamburg University of Applied Sciences, Germany
  • 2. MARS (Multi-Agent Research and Simulation) Group, Department Computer Sciences, Hamburg University of Applied Sciences, Germany
  • 3. Heidelberg Institute of Global Health, Heidelberg University Hospital, Germany
  • 4. Institute of Medical Biometry and Epidemiology, University Medical CenterHamburg-Eppendorf, Germany
  • 5. Department Health Sciences, Hamburg University of Applied Sciences, Germany; MARS (Multi-Agent Research and Simulation) Group, Department Computer Sciences, Hamburg University of Applied Sciences, Germany; Department Infectious Disease Epidemiology, Bernhard Nocht Institute forTropical Medicine, Germany
  • 6. Department Infectious Disease Epidemiology, Bernhard Nocht Institute forTropical Medicine, Germany
  • 7. Department for Microbiology and Biotechnology, Institute for Plant Sciences and Microbiology, University of Hamburg, Germany
  • 8. School of Life Sciences and Bioengineering, The Nelson Mandela African Institution of Sciences and Technology, Tanzania
  • 9. Research and Transfer Centre "Sustainable Development and Climate Change Management", Hamburg University of Applied Sciences, Germany
  • 10. School of Computational and Communication Science and Engineering,The Nelson Mandela African Institution of Sciences and Technology, Tanzania

Description

Despite efforts by the WHO to support local surveillance strategies in developing countries, there is a lack of robust public health surveillance frameworks. As a result, early infectious disease outbreak detection and response remain a significant challenge for local health systems in low-resource settings such as sub-Saharan African countries. In contrast, the growing digital infrastructure, especially in the mobile phone sector, and the global availability of extensive digital data offer promising solutions to enhance and strengthen epidemiological surveillance. Yet, there is little insight into concepts of utilisation and transfer into local public health practice. Using Tanzania as an example, a novel electronic surveillance and early outbreak alert framework is being developed that links signals on emerging diseases with relevant contextual Open Data for rapid outbreak risk assessment. The concept focuses on haemorrhagic fever diseases, specifically dengue virus disease, which is increasingly spreading in sub-Saharan Africa. A data stack framework forms the core of the system, which augments electronic information on the occurrence of acute haemorrhagic fever syndrome, e.g., collected via mobile phone-based surveillance tools, with openly available socio-ecological context data specific to dengue. Preliminary results on the data and information flow within the surveillance framework are presented and strategies for an automated indicator-based risk assessment for dengue outbreaks will be discussed, supplemented by an agent-based simulation framework to model possible short-term outbreak scenarios. In addition, adequate data inputs, identified through an appraisal of various data sources available for Tanzania, are outlined. The framework could serve as a blueprint for designing locally implementable early warning and decision support systems integrated with existing digital surveillance infrastructure.

Notes

Corresponding Author: Juliane Boenecke (juliane.boenecke@bnitm.de) Funding: German Federal Ministry of Education and Research (BMBF) / CONNECT Education-Research-Innovation (Grant ID: 01DU20005)

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Additional details

Related works

Is described by
Journal article: 10.1093/eurpub/ckac131.569 (DOI)

References

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