tetano
Editor, Senior Moderator
PLoS One
. 2025 Feb 21;20(2):e0319263.
doi: 10.1371/journal.pone.0319263. eCollection 2025. Multi-level quality assessment of United States COVID-19 epidemiological surveillance
Megan S Irgens[SUP] 1 [/SUP], Riley M O'Neill[SUP] 2 [/SUP], John M Ruiz[SUP] 2 [/SUP]
Affiliations
Although the coronavirus disease 2019 (COVID-19) tasked United States (U.S.) health departments with tracking and informing disease mitigation efforts, there has been no national assessment of public COVID-19 data quality. The current study aimed to illustrate U.S. COVID-19 reporting quality by examining epidemiological surveillance from U.S. health departments in 50 states and the District of Columbia between July and August 2020 along five central quality dimensions: timeliness, reliability, completeness, accuracy, and accessibility. A follow-up assessment was conducted 19 months later for a subset of states. Results broadly demonstrated that the quality of COVID-19 data reporting was significantly heterogenous. States varied in timeliness of initial data reports (median: 3/2/2020, minimum: 9/29/2019, maximum: 4/20/2020). Most states (56.8%) did not indicate sources of data for their official published reports. In assessing for 10 standard variables from the Centers for Disease Control and Prevention (CDC), states widely differed in granularity of reported variables and no state health department reported data for all CDC surveillance variables (e.g., race, ethnicity, sex). Most same-day comparisons of state-specific counts reported by the CDC differed from respective state health departments (cases: 84.3% differed; deaths: 68.6% differed). Follow-up examination indicated improvements in reliability, accuracy, and accessibility, but issues in data source verification and completeness persisted. Authors conclude with recommendations to improve disease mitigation efficiency and improve public trust in health protection efforts: establish formal reporting guidelines; standardize operational definitions for key disease variables; and, require health departments to publicly identify sources of reported data.
. 2025 Feb 21;20(2):e0319263.
doi: 10.1371/journal.pone.0319263. eCollection 2025. Multi-level quality assessment of United States COVID-19 epidemiological surveillance
Megan S Irgens[SUP] 1 [/SUP], Riley M O'Neill[SUP] 2 [/SUP], John M Ruiz[SUP] 2 [/SUP]
Affiliations
- PMID: 39982920
- PMCID: PMC11844846
- DOI: 10.1371/journal.pone.0319263
Although the coronavirus disease 2019 (COVID-19) tasked United States (U.S.) health departments with tracking and informing disease mitigation efforts, there has been no national assessment of public COVID-19 data quality. The current study aimed to illustrate U.S. COVID-19 reporting quality by examining epidemiological surveillance from U.S. health departments in 50 states and the District of Columbia between July and August 2020 along five central quality dimensions: timeliness, reliability, completeness, accuracy, and accessibility. A follow-up assessment was conducted 19 months later for a subset of states. Results broadly demonstrated that the quality of COVID-19 data reporting was significantly heterogenous. States varied in timeliness of initial data reports (median: 3/2/2020, minimum: 9/29/2019, maximum: 4/20/2020). Most states (56.8%) did not indicate sources of data for their official published reports. In assessing for 10 standard variables from the Centers for Disease Control and Prevention (CDC), states widely differed in granularity of reported variables and no state health department reported data for all CDC surveillance variables (e.g., race, ethnicity, sex). Most same-day comparisons of state-specific counts reported by the CDC differed from respective state health departments (cases: 84.3% differed; deaths: 68.6% differed). Follow-up examination indicated improvements in reliability, accuracy, and accessibility, but issues in data source verification and completeness persisted. Authors conclude with recommendations to improve disease mitigation efficiency and improve public trust in health protection efforts: establish formal reporting guidelines; standardize operational definitions for key disease variables; and, require health departments to publicly identify sources of reported data.