The lack of conversion of surveillance microdata into actionable epidemiological intelligence

The gap

Evidence profile

Sourced from the stated research gap and future-work section of the source papers, classified as general, drawn from work published between 2025 and 2026, spanning 2 journals. Those papers have been cited 11 times in total.

Supporting evidence — 3 representative gaps

• An Anonymized Geospatial Dengue Surveillance Dataset for Risk Stratification: A Municipality–Year Analytical Resource for Unsupervised Clustering (2026) · Data · doi

  The lack of conversion of surveillance microdata into actionable epidemiological intelligence. The need for a reproducible dataset and analytical resource for transforming routine records into a spatiotemporal framework for territorial risk stratification. The absence of a unified analytical database that integrates multiple years of anonymized dengue surveillance records.

  generalstated research gapevidence 5/5
  Keywords: lack conversion surveillance microdata actionable epidemiological intelligence need
• Assessing Aedes mosquito larval indicators, dengue virus infection rates, and risk factors in Khyber Pakhtunkhwa: Insights for improved vector control strategies (2025) · PLoS neglected tropical diseases · cited 4× · doi

  integrate pupal surveys, adult mosquito surveillance, climatic factors, and human mobility across outbreak phases to establish predictive thresholds, - include year-round surveillance to model climatic impacts and enhance outbreak prediction in the region, - consider multivariable approaches to account for potential confounders and interdependencies among variables, - investigate the relationship between vector index levels, MIRs, and dengue incidence in various geographic locations across the province/country

  generalfuture-work sectionevidence 5/5
  Keywords: integrate pupal surveys adult mosquito surveillance climatic factors
• Dengue dynamics beyond biological factors: Revealing the nexus between urbanisation planning, and mobilities in Vientiane, Lao PDR (2025) · PLoS neglected tropical diseases · cited 7× · doi

  Further explore the interactions between land-use change, mobility, and vector ecology, while incorporating longitudinal and climate data to enhance risk prediction in evolving urban environments. Expanding the temporal dimension of analysis-for instance, through monthly-level studies or finer-scale spatiotemporal modelling-could help identify seasonal variations and outbreak triggers more precisely. Integrating high-resolution mobility datasets and climatic fluctuations would provide a more dynamic understanding of how human movement and environmental conditions shape dengue transmission patterns over time.

  generalfuture-work sectionevidence 5/5
  Keywords: further explore interactions between land-use change mobility vector

Questions about this gap