Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
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...
Introduction to Epidemiology01:26

Introduction to Epidemiology

Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
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...
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This phenomenon...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Mapping the prevalence of molecular markers of Plasmodium falciparum artemisinin partial resistance in Africa: a systematic review and spatiotemporal modelling study.

The Lancet. Infectious diseases·2026
Same author

Bridging the gap between public health, academia and policy.

BMJ global health·2026
Same author

Large-scale genomic surveillance reveals immunosuppression drives mutation dynamics in persistent SARS-CoV-2 infections.

Nature communications·2026
Same author

Measuring the growth of infectious disease modelling publications and their impact on policymaking: A large language model-assisted bibliometric review.

Epidemics·2026
Same author

Patterns of antibiotic use for acute febrile illness in resource-limited settings: a multicenter study in DR Congo, Kenya and Uganda.

Frontiers in public health·2026
Same author

Determinants of measles-rubella second dose vaccine uptake among children in Mathare informal settlement, Nairobi, Kenya: a mixed-methods study.

The Pan African medical journal·2026

Related Experiment Video

Updated: Jun 6, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

Enhancing epidemic forecast usability for policymakers: A global mixed-methods study.

Paula Christen1,2, Loice Achieng Ombajo2, Anne Cori1

  • 1School of Public Health, Imperial College London, London, United Kingdom.

PLOS Global Public Health
|June 4, 2026
PubMed
Summary

Epidemic forecasts are crucial for public health but face challenges in lower-income countries. Improving their use requires user-oriented tools and better integration into response teams, especially in resource-constrained settings.

Related Experiment Videos

Last Updated: Jun 6, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

Area of Science:

  • Epidemiology
  • Public Health
  • Health Policy

Background:

  • The COVID-19 pandemic highlighted deficiencies in generating, interpreting, and utilizing epidemic forecasts for public health decisions.
  • Effective epidemic forecasting is essential for informed policy and intervention planning.

Purpose of the Study:

  • To examine the perception, utilization, and communication of epidemic forecasts among stakeholders in COVID-19 policy dialogues globally.
  • To identify barriers and facilitators to the effective use of epidemic forecasts across different income settings.

Main Methods:

  • A global mixed-methods study combining an online survey (n=143, 46 countries) with 13 semi-structured interviews.
  • Descriptive analysis of survey data stratified by country income group and thematic analysis of interview transcripts using the Framework Method.

Main Results:

  • Forecasts informed policy on intervention planning, peak estimation, and prevalence, with projected intervention impact being a key metric.
  • Preference for explicit uncertainty presentation in forecasts varied significantly by country income level (72% HIC vs. 23% LIC).
  • Barriers to forecast use, such as lack of understanding of methodology, were more pronounced in lower-income countries (47% LIC/LMIC vs. 3% HIC).

Conclusions:

  • Forecast credibility relies on trust, relationships, and context, not just statistical methods.
  • Enhancing forecast impact necessitates user-oriented tools, integrated modeling teams, co-developed metrics, and strengthened health information systems, particularly in resource-limited settings.