Conference Abstract | Volume 8, Abstract ELIC202552 (Poster 066) | Published:  01 Aug 2025

Comparative analysis of human-to-human transmission in two different population settings (community and healthcare): A mathematical modelling approach

Sylvia Ezenwa-Ahanene1,2, Polycarp Dauda Madaki1,3,&, Nwadiuto Chidinma Ojielo1,4

1Corona Management Systems, Abuja, Nigeria, 2Nigeria Center for Disease Control and Prevention (NCDC), Abuja Nigeria, 3Department of Veterinary Tropical Diseases, University of Pretoria, Pretoria 0110, South Africa, 4University of Nigeria Teaching Hospital,Enugu, Nigeria

&Corresponding author: Polycarp Dauda Madaki, Corona Management Systems, Abuja, Nigeria; Department of Veterinary Tropical Diseases, University of Pretoria, Pretoria, South Africa. Email: pmadaki@mmf.coronams.com: polycarp.madaki@tuks.co.za

Received: 30 Apr 2025, Accepted: 09 Jul 2025, Published: 01 Aug 2025

Domain: Infectious Disease Epidemiology, Disease Modelling

This is part of the Proceedings of the ECOWAS 2nd Lassa fever International Conference in Abidjan, September 8 – 11, 2025

Keywords: Lassa fever (LF), SEIR model, Transmission dynamics, Healthcare settings, Infection control (IPC).

©Sylvia Ezenwa-Ahanene et al. Journal of Interventional Epidemiology and Public Health (ISSN: 2664-2824). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cite this article: Sylvia Ezenwa-Ahanene et al., Comparative analysis of human-to-human transmission in two different population settings (community and healthcare): A mathematical modelling approach. Journal of Interventional Epidemiology and Public Health. 2025;8(ConfProc5):00210. https://doi.org/10.37432/JIEPH-CONFPRO5-00210

Introduction

Lassa fever (LF) is a viral infectious disease with various symptoms, resulting from an infection of the Lassa virus. It is a disease of significance in public health because it can be transmitted from person to person, often with high fatality rates in healthcare and community setting.

Methods

This study applies a mathematical modelling approach using a Susceptible-Exposed-Infectious-Recovered (SEIR) model to compare LF transmission dynamics in community and healthcare settings. Incidence data obtained from the Nigeria Centre for Disease Control (NCDC) and parameters from published literature were used to estimate model inputs.

Results

The values of R0​ indicated increased transmission in the healthcare settings than in the community at 1.9991 and 1.9822, respectively. This is because the infected persons are likely to have close contact with healthcare providers most of the time. Sensitivity analysis showed that a decrease in transmission rates leads to fewer infections, promoting infection control (IPC) measures in healthcare and increasing community awareness, encouraging more testing, and supporting measures directed at controlling vector populations. The study found that although community transmission is less likely than in healthcare, it needs focused prevention measures than healthcare-acquired transmission. However, better hygiene, community involvement, coordination and collaboration of key stakeholders using the One Health approach are important strategies in preventing LF epidemics.

Conclusion

The quantitative recommendations based on the model can contribute significantly to managing Lassa fever infection across the simulated scenarios. Collaboration among stakeholders using a One Health approach is essential for effective LF prevention and control.

 
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Keywords

  • Lassa fever (LF)
  • SEIR model
  • Transmission dynamics
  • Healthcare settings
  • Infection control (IPC)
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