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Epidemics of chikungunya, Zika, and COVID-19 reveal bias in case-based mapping

Fausto Andres Bustos Carrillo1, Brenda Lopez Mercado2, Jairo Carey Monterrey2

  • 1University of California, Berkeley, Berkeley, California, USA.

Medrxiv : the Preprint Server for Health Sciences
|August 3, 2021
PubMed

Insights

Incidence rates often underestimate epidemic risks. This study reveals significant spatial biases, impacting effective disease control strategies and public health policies during outbreaks.

Area of Science:

  • Epidemiology
  • Public Health
  • Spatial Analysis

Background:

  • Accurate spatial tracing of epidemic spread is crucial for effective control measures.
  • Traditional incidence rates may not fully capture the true extent of infection and disease risks.
  • Understanding spatial patterns of epidemics informs public health interventions.

Approach:

  • Compared spatial incidence rates, infection risks, and disease risks in pediatric and household cohorts during chikungunya, Zika, and COVID-19 epidemics in Managua, Nicaragua.
  • Employed generalized additive and mixed-effects models, Kulldorf's spatial scan statistic, and intracluster correlation coefficients.
  • Analyzed data from approximately 3,000 children and 1,793 individuals in households.

Key Points:

  • Incidence rates consistently underestimated infection and disease risks across multiple epidemics.
  • Significant, spatially non-uniform biases were observed, distinct from ascertainment issues.
  • Infection and disease risks displayed different spatial patterns, with incidence clusters not reliably indicating high-risk areas.

Conclusions:

  • Relying solely on incidence rates can lead to substantial biases in assessing epidemic spread and risk.
  • These biases can adversely affect the development and implementation of epidemic control policies.
  • Accurate risk assessment requires metrics beyond simple incidence rates for effective public health management.
Keywords:
COVID-19ChikungunyaZikabiasepidemiologyspatial analysis

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