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Related Concept Videos

Principles of Disease Surveillance01:26

Principles of Disease Surveillance

Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
Investigation of Disease Outbreaks01:23

Investigation of Disease Outbreaks

Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...

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Related Experiment Video

Updated: Jun 20, 2026

Measuring Dengue Virus RNA in the Culture Supernatant of Infected Cells by Real-time Quantitative Polymerase Chain Reaction
08:36

Measuring Dengue Virus RNA in the Culture Supernatant of Infected Cells by Real-time Quantitative Polymerase Chain Reaction

Published on: November 1, 2018

Quantifying, Understanding, and Correcting for Delays in Routine Dengue Case Reporting in the Americas.

Katie M Susong1,2, Ahyoung Lim1,2, Kishen Joshi1,2

  • 1Department of Infectious Disease Epidemiology and Dynamics, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom.

The American Journal of Tropical Medicine and Hygiene
|June 18, 2026
PubMed
Summary
This summary is machine-generated.

Dengue surveillance in the Americas faces challenges due to reporting delays. Understanding these delays is crucial for accurate epidemic assessment and effective public health response.

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Related Experiment Videos

Last Updated: Jun 20, 2026

Measuring Dengue Virus RNA in the Culture Supernatant of Infected Cells by Real-time Quantitative Polymerase Chain Reaction
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Published on: November 1, 2018

Multiplexed Isothermal Amplification Based Diagnostic Platform to Detect Zika, Chikungunya, and Dengue 1
06:18

Multiplexed Isothermal Amplification Based Diagnostic Platform to Detect Zika, Chikungunya, and Dengue 1

Published on: March 13, 2018

Area of Science:

  • Public Health
  • Epidemiology
  • Infectious Diseases

Background:

  • Dengue virus poses a significant public health threat in the Americas, characterized by endemic-epidemic transmission and frequent surges.
  • Timely and accurate surveillance is essential for managing dengue outbreaks, but real-time reporting systems often suffer from delays and backfilling.
  • These reporting issues can lead to underestimation of epidemic size, potentially compromising control efforts.

Purpose of the Study:

  • To quantify reporting delays in dengue case counts across countries in the Americas.
  • To identify factors influencing the duration and extent of reporting delays.
  • To provide methodological insights for improving near-real-time dengue forecasting and public health decision-making.

Main Methods:

  • A longitudinal dataset of weekly World Health Organization (WHO) Pan American Health Organization (PAHO) dengue reports from 2022-2025 was compiled for 46 countries and territories.
  • Reporting delays were quantified across periods of up to 60 weeks.
  • Regression modeling was used to analyze the relationship between country-specific characteristics (disaster risk, population size, outbreak severity) and reporting delays.

Main Results:

  • 91.4% of countries exhibited reporting delays, with an average time to reach the final case count of 13.9 weeks.
  • Countries with very low disaster risk and smaller populations experienced fewer reporting delays.
  • Outbreak severity was a stronger predictor of reporting delays than outbreak size, leading to less timely reports.

Conclusions:

  • Significant heterogeneity exists in dengue reporting delay dynamics across countries, necessitating country-specific analyses and corrections.
  • The findings offer insights for developing robust priors in near-real-time forecasting models when direct delay observations are absent.
  • This research establishes a foundation for improved dengue modeling, enhanced outbreak response, and more resilient public health decision-making.