Malaria Journal (Jun 2024)

Fine-scale maps of malaria incidence to inform risk stratification in Laos

  • Su Yun Kang,
  • Punam Amratia,
  • Julia Dunn,
  • Phoutnalong Vilay,
  • Mark Connell,
  • Tasmin Symons,
  • Susan Rumisha,
  • Song Zhang,
  • Abigail Ward,
  • Odai Sichanthongthip,
  • Virasack Banouvong,
  • Mathew Shortus,
  • Rita Reyburn,
  • Phonephet Butphomvihane,
  • Vilaisak Phiphakavong,
  • Mary Hahm,
  • Vilayphone Phongchantha,
  • Boualam Khamlome,
  • Keobouphaphone Chindavongsa,
  • Chitsavang Chanthavisouk,
  • Daniel J. Weiss,
  • Peter W. Gething,
  • Ewan Cameron

DOI
https://doi.org/10.1186/s12936-024-05007-9
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 13

Abstract

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Abstract Background Malaria risk maps are crucial for controlling and eliminating malaria by identifying areas of varying transmission risk. In the Greater Mekong Subregion, these maps guide interventions and resource allocation. This article focuses on analysing changes in malaria transmission and developing fine-scale risk maps using five years of routine surveillance data in Laos (2017–2021). The study employed data from 1160 geolocated health facilities in Laos, along with high-resolution environmental data. Methods A Bayesian geostatistical framework incorporating population data and treatment-seeking propensity was developed. The models incorporated static and dynamic factors and accounted for spatial heterogeneity. Results Results showed a significant decline in malaria cases in Laos over the five-year period and a shift in transmission patterns. While the north became malaria-free, the south experienced ongoing transmission with sporadic outbreaks. Conclusion The risk maps provided insights into changing transmission patterns and supported risk stratification. These risk maps are valuable tools for malaria control in Laos, aiding resource allocation, identifying intervention gaps, and raising public awareness. The study enhances understanding of malaria transmission dynamics and facilitates evidence-based decision-making for targeted interventions in high-risk areas.