Counting Coronavirus Disease 2019 (COVID-19) Cases: Case Definitions, Screened Populations and Testing Techniques...

Area of Science:

• Epidemiology
• Public Health Surveillance
• Infectious Disease Dynamics

Background:

• Counting disease cases during epidemics, such as Coronavirus Disease-2019 (COVID-19), presents significant challenges.
• Inconsistent case definitions and evolving testing capacities can lead to confusion in reported case numbers.

Purpose of the Study:

• To highlight the complexities and critical considerations in accurately enumerating disease cases during an epidemic.
• To examine the impact of varying case definitions and laboratory testing procedures on disease surveillance data.

Main Methods:

• Analysis of case definition changes and their impact on reported numbers, using COVID-19 as a primary example.
• Discussion of laboratory testing considerations, including specimen collection, test methodologies, and interpretation of results.
• Exploration of the relationship between testing capacity, case ascertainment, and epidemic response.

Main Results:

• Changes in case definitions, such as those observed in Hubei province for COVID-19, can cause significant fluctuations and confusion in reported case counts.
• Limited laboratory testing capacity in early epidemic phases leads to underdiagnosis and reliance on 'suspected case' definitions.
• Technical aspects of laboratory testing, including standardization, approval, and interpretation, directly influence the accuracy of disease surveillance.

Conclusions:

• Accurate disease counting requires standardized case definitions and robust laboratory infrastructure.
• The reliability of epidemic surveillance data is contingent upon addressing technical and logistical challenges in case ascertainment and testing.
• Inaccurate disease counts can compromise the effectiveness of public health responses to outbreaks.