PCD logo

Estimating the Burden and Distribution of Post–COVID-19 Condition in Washington State, March 2020–October 2023

PEER REVIEWED

The figure shows 4 connected boxes. Boxes on either side of the figure represent PCC; on the left, PCC related to COVID-19 cases and, on the right, PCC related to COVID-19 hospitalizations. The top and bottom boxes, respectively, represent COVID-19 cases where the patient has recovered and where the patient has not recovered. Nonhospitalized COVID-19 cases and hospitalized COVID-19 cases enter the acute PCC compartments PCC(NH) and PCC(H), respectively. Patients progress to either recovered (R) or unrecovered (U) with the probability α(NH) and α(H) or β(NH) or β(H), respectively. All compartments have a background death rate (bd).


Figure 1.

Diagram of the mathematical model for the progression of post–COVID-19 condition (PCC). Abbreviations: bd, background death rate; H, hospitalized; NH, nonhospitalized; R, recovered; U, unrecovered; α, the proportion moving to the recovered compartment; β, the proportion moving to the unrecovered compartment; ρ, the probability of a case or hospitalization developing PCC.

Return to Article

The figure consists of 2 line graphs. Graph A shows 3 lines: the estimated number of SARS-CoV-2 infections (asymptomatic and symptomatic), the estimated number of symptomatic SARS-CoV-2 infections, and the reported number of COVID-19 cases. The estimated number of SARS-CoV-2 infections is substantially higher than the reported number of COVID-19 cases for the entire study period (March 2020 through October 2023), but in particular, the rates diverge after early 2022, when the reported number of COVID-19 cases dropped to around 72,000 in March 2022. Graph B shows a single line for COVID-19 case ascertainment: from mid-2020 until early 2022, the percentage of cases ascertained fluctuated from approximately 30% to 55%. After early 2022, the percentage fell to about 7.5%.


Figure 2.

SARS-CoV-2 infections, COVID-19 cases, and COVID-19 case ascertainment in Washington State, March 2020–October 2023. A) Estimated number of SARS-CoV-2 infections (asymptomatic and symptomatic), estimated number of symptomatic SARS-CoV-2 infections, and reported number of COVID-19 cases. B) Case ascertainment calculated as the reported number of COVID-19 cases divided by the estimated number of symptomatic SARS-CoV-2 infections. Data source: Washington Disease Reporting System.

Return to Article

The top chart (A) shows Household Pulse Survey estimates and model estimates of the prevalence of PCC among adults aged 18 years or older in Washington State. Prevalence slowly rises from 2020 till a peak in January 2022 of around 8%. From here it falls to around 5% in March of 2022, but remains relatively stable between 5% and 6% until the final time point, October 2023. The 95% CIs of the model estimates and the Household Pulse Survey point estimates overlap across all but 1 time point in late 2022. The bottom chart (B) shows the incidence of PCC from January 2020 through October 2023. There are several peaks and troughs in this graph; the largest peak occurred in January 2022 with an incidence of 143,000 PCC cases. From there, incidence oscillated but remained above 5,000 per month at the lowest points and above 12,500 at the highest points.


Figure 3.

Prevalence and incidence of post–COVID-19 condition (PCC) among adults aged 18 years or older in Washington State, January 2020–October 2023. A) Model predictions (solid blue line) and Household Pulse Survey estimates (black circles) of PCC prevalence. Blue shading and error bars indicate 95% CIs. B) Estimated monthly incidence of PCC, in thousands. Shading indicates 95% CIs.

Return to Article


Figure 4.

Estimated relative prevalence of post–COVID-19 condition, relative to the median, by sex, race and ethnicity, and age group among adults aged 18 years or older in Washington State in October 2023. The red dashed line indicates a prevalence ratio of 100% (no difference from the median prevalence). Error bars indicate 95% CIs.

Estimated relative prevalence of post–COVID-19 condition, relative to the median, by sex, race and ethnicity, and age group among adults aged 18 years or older in Washington State in October 2023. The red dashed line indicates a prevalence ratio of 100% (no difference from the median prevalence). Error bars indicate 95% CIs.
Characteristic % (95% CI)
Sex
Female 120.8 (109.0–132.7)
Male 79.2 (71.2–87.1)
Race and ethnicity
Non-Hispanic Asian 52.4 (45.8–58.9)
Non-Hispanic Black 138.2 (123.0–153.3)
Hispanic or Latino of any race 150.6 (136.0–165.2)
Non-Hispanic White 77.2 (69.9–84.6)
Non-Hispanic ≥2 races and Other races 100.0 (88.2–111.8)
Age group, y
0-17 87.1 (78.5–95.7)
18-29 133.3 (120.1–146.6)
30-39 138.7 (124.9–152.6)
40-49 147.2 (132.7–161.7)
50-59 112.9 (101.9–123.9)
60-69 72.5 (65.1–79.9)
70-79 58.5 (51.6–65.3)
≥80 76.7 (66.3–87.2)

Return to Article

The first image (A) is a map of Washington State counties and the normalized prevalence of PCC in October 2023. It shows that central Washington had the highest normalized prevalence of PCC in the state. The second (B) is a heatmap of Washington State counties and the normalized prevalence of PCC from January 2020 through October 2023. Franklin County, in the southeastern corner of the state, had the highest prevalence of PCC over time.


Figure 5.

Estimated relative prevalence of post–COVID-19 condition (PCC), by county, Washington State. A) Map of the normalized prevalence of PCC in October 2023. B) Heatmap of counties normalized prevalence over time. The heatmap normalized prevalence values are specific to each time point to emphasize which counties at each time point were experiencing the highest PCC prevalence. Normalized prevalence is the prevalence recalculated on a 0-1 scale where 0 indicates the lowest prevalence and 1 the highest prevalence across all counties.

Return to Article

Top

Error processing SSI file

The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the U.S. Department of Health and Human Services, the Public Health Service, the Centers for Disease Control and Prevention, or the authors’ affiliated institutions.