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The impact of non-pharmaceutical interventions on the spread of COVID-19 in Saudi Arabia: Simulation approach.
Alhomaid, Ahmad; Alzeer, Abdullah H; Alsaawi, Fahad; Aljandal, Abdulaziz; Al-Jafar, Rami; Albalawi, Marwan; Alotaibi, Dana; Alabdullatif, Raghad; AlGhassab, Razan; Mominkhan, Dalia M; Alharbi, Muaddi; Alghamdi, Ahmad A; Almoklif, Maryam; Alabdulaali, Mohammed K.
Afiliación
  • Alhomaid A; Data Services Sector, Lean Business Services, Riyadh, Saudi Arabia.
  • Alzeer AH; Data Services Sector, Lean Business Services, Riyadh, Saudi Arabia.
  • Alsaawi F; Data Services Sector, Lean Business Services, Riyadh, Saudi Arabia.
  • Aljandal A; Data Services Sector, Lean Business Services, Riyadh, Saudi Arabia.
  • Al-Jafar R; Data Services Sector, Lean Business Services, Riyadh, Saudi Arabia.
  • Albalawi M; School of Public Health, Imperial College London, London, UK.
  • Alotaibi D; Department of Digital Health, Lean Business Services, Riyadh, Saudi Arabia.
  • Alabdullatif R; Data Services Sector, Lean Business Services, Riyadh, Saudi Arabia.
  • AlGhassab R; Data Services Sector, Lean Business Services, Riyadh, Saudi Arabia.
  • Mominkhan DM; Data Services Sector, Lean Business Services, Riyadh, Saudi Arabia.
  • Alharbi M; National Health Command Center, Ministry of Health, Riyadh, Saudi Arabia.
  • Alghamdi AA; National Health Command Center, Ministry of Health, Riyadh, Saudi Arabia.
  • Almoklif M; National Health Command Center, Ministry of Health, Riyadh, Saudi Arabia.
  • Alabdulaali MK; National Health Command Center, Ministry of Health, Riyadh, Saudi Arabia.
Saudi Pharm J ; 32(1): 101886, 2024 Jan.
Article en En | MEDLINE | ID: mdl-38162709
ABSTRACT

Objectives:

This paper aims to measure the impact of the implemented nonpharmaceutical interventions (NPIs) in the Kingdom of Saudi Arabia (KSA) during the pandemic using simulation modeling.

Methods:

To measure the impact of NPI, a hybrid agent-based and system dynamics simulation model was built and validated. Data were collected prospectively on a weekly basis. The core epidemiological model is based on a complex Susceptible-Exposed-Infectious-Recovered and Dead model of epidemic dynamics. Reverse engineering was performed on a weekly basis throughout the study period as a mean for model validation which reported on four

outcomes:

total cases, active cases, ICU cases, and deaths cases. To measure the impact of each NPI, the observed values of active and total cases were captured and compared to the projected values of active and total cases from the simulation. To measure the impact of each NPI, the study period was divided into rounds of incubation periods (cycles of 14 days each). The behavioral change of the spread of the disease was interpreted as the impact of NPIs that occurred at the beginning of the cycle. The behavioral change was measured by the change in the initial reproduction rate (R0).

Results:

After 18 weeks of the reverse engineering process, the model achieved a 0.4 % difference in total cases for prediction at the end of the study period. The results estimated that NPIs led to 64 % change in The R0. Our breakdown analysis of the impact of each NPI indicates that banning going to schools had the greatest impact on the infection reproduction rate (24 %).

Conclusion:

We used hybrid simulation modeling to measure the impact of NPIs taken by the KSA government. The finding further supports the notion that early NPIs adoption can effectively limit the spread of COVID-19. It also supports using simulation for building mathematical modeling for epidemiological scenarios.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Saudi Pharm J Año: 2024 Tipo del documento: Article País de afiliación: Arabia Saudita Pais de publicación: Arabia Saudita
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Saudi Pharm J Año: 2024 Tipo del documento: Article País de afiliación: Arabia Saudita Pais de publicación: Arabia Saudita