Estimating unconfirmed COVID-19 infection cases and multiple waves of pandemic progression with consideration of testing capacity and non-pharmaceutical interventions: A dynamic spreading model

Abstract

The novel coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has unique epidemiological characteristics that include presymptomatic and asymptomatic infections, resulting in a large proportion of infected cases being unconfirmed, including patients with clinical symptoms who have not been identified by screening. These unconfirmed infected individuals move and spread the virus freely, presenting difficult challenges to the control of the pandemic. To reveal the actual pandemic situation in a given region, a simple dynamic susceptible-unconfirmed-confirmed-removed (D-SUCR) model is developed taking into account the influence of unconfirmed cases, the testing capacity, the multiple waves of the pandemic, and the use of non-pharmaceutical interventions. Using this model, the total numbers of infected cases in 51 regions of the USA and 116 countries worldwide are estimated, and the results indicate that only about 40% of the true number of infections have been confirmed. In addition, it is found that if local authorities could enhance their testing capacities and implement a timely strict quarantine strategy after identifying the first infection case, the total number of infected cases could be reduced by more than 90%. Delay in implementing quarantine measures would drastically reduce their effectiveness.

Keywords: COVID-19; Extended SEIR models; Infection estimation; Spreading dynamics; Testing capacity.

Fig. 1

Schemes used in the SEIR, SEAUCRD, Basic SUCR, and D-SUCR models, and the relationships between these four different models.

Fig. 2

Mean and 95% CI for the coefficient of determination ($R^2$) for 51 regions in the USA.

Fig. 3

Results for three states as illustrative examples and the whole USA. Lines and shaded areas represent the median and $5^{\mathit{th}}$ to ${95}^{\mathit{th}}$ percentiles, respectively, from 1,000 simulations: (a–d) Official cumulative confirmed, estimated cumulative confirmed, estimated unconfirmed and estimated total cases in California, New York, Washington, and the USA as a whole; (e–h) ratios between officially confirmed cases and the estimated total cases (%); (i–l) dynamic enhancement rates $\mathrm{\Phi }\left(t\right)$.

Fig. 4

Numbers of officially confirmed and estimated total cases per 100 people in different regions in the USA on four specific dates: (a) May 31, 2020; (b) Sep 31, 2020; (c) Dec 31, 2020; (d) May 1, 2021. The sizes of the bubbles represent the numbers of confirmed cases.

Fig. 5

Mean and 95% CI for the coefficient of determination ($R^2$) for 116 countries worldwide.

Fig. 6

Results for four countries (the Philippines, Japan, Italy, and Russia) as illustrative examples. Lines and shaded areas stand for the median and $5^{\mathit{th}}$–${95}^{\mathit{th}}$ percentiles, respectively: (a–d) Official cumulative confirmed cases, estimated cumulative confirmed, estimated unconfirmed and estimated total infections for the Phillipines, Japan, Italy and Russia; (e–h) ratios between the official confirmed cases and the estimated total cases (%); (i–l) dynamic enhancing rates $\mathrm{\Phi }\left(t\right)$.

Fig. 7

Numbers of officially confirmed cases (blue bubbles) and estimated numbers of total infectious (transparent red bubbles) for different states in the USA on four example dates: (a) June 24, 2020; (b) Aug 24, 2020; (c) Nov 24, 2020; (d) Feb 15, 2021. The sizes of the bubbles represent the numbers of cases.

Fig. 8

Statistical results for 116 countries. Lines and shaded areas stand for the median and $5^{\mathit{th}}$-${95}^{\mathit{th}}$ percentiles, respectively: (a) Official cumulative confirmed, estimated cumulative confirmed, estimated unconfirmed and estimated total infections in 116 countries (%); (b) ratios between estimated total infections and officially confirmed cases; (c) dynamic enhancement rates $\mathrm{\Phi }\left(t\right)$.

Fig. 9

The estimated total infections, confirmed, and unconfirmed cases under strict controlling measurement in the USA.

Fig. 10

Estimated numbers of total infections, confirmed, and unconfirmed cases under strict control measures in the USA.