Estimating unobserved SARS-CoV-2 infections in the United States

Abstract

By March 2020, COVID-19 led to thousands of deaths and disrupted economic activity worldwide. As a result of narrow case definitions and limited capacity for testing, the number of unobserved SARS-CoV-2 infections during its initial invasion of the US remains unknown. We developed an approach for estimating the number of unobserved infections based on data that are commonly available shortly after the emergence of a new infectious disease. The logic of our approach is, in essence, that there are bounds on the amount of exponential growth of new infections that can occur during the first few weeks after imported cases start appearing. Applying that logic to data on imported cases and local deaths in the US through March 12, we estimated that 22,876 (95% posterior predictive interval: 7,451 - 53,044) infections occurred in the US by this date. By comparing the model's predictions of symptomatic infections to local cases reported over time, we obtained daily estimates of the proportion of symptomatic infections detected by surveillance. This revealed that detection of symptomatic infections decreased throughout February as exponential growth of infections outpaced increases in testing. Between February 21 and March 12, we estimated an increase in detection of symptomatic infections, which was strongly correlated (median: 0.97, 95% PPI: 0.85 - 0.98) with increases in testing. These results suggest that testing was a major limiting factor in assessing the extent of SARS-CoV-2 transmission during its initial invasion of the US.

Optimal control of the COVID-19 pandemic with non-pharmaceutical interventions

“…The first known case of COVID-19 in the United States arrived from China on January 15, 2020 [22]. In the weeks that followed, deficiencies in testing allowed the virus that causes this disease to spread largely undetected [41], with the number of reported cases growing to 429,319 by April 8, 2020 [36]. Social distancing-such as closing schools, working from home, and sheltering in place-has been adopted widely and appears capable of impacting transmission [26,12].…”

Coast-to-coast spread of SARS-CoV-2 in the United States revealed by genomic epidemiology

“…From March 1 to 19, 2020, the number of reported COVID-19 cases in the U.S. rapidly increased from 74 to 13,677, and the virus was detected in all 50 U.S. states (Dong et al, 2020) . It was recently estimated that the true number of COVID-19 cases in the U.S. is likely in the tens of thousands (Perkins et al, 2020) , suggesting substantial undetected infections and spread within the country. We hypothesized that, with the growing number of COVID-19 cases in the U.S. and the large volume of domestic travel, new U.S. outbreaks are now more likely to result from interstate rather than international spread.…”

Early estimates of COVID-19 infections in small, medium and large population clusters

“…Thus, our results many have overestimated the impact of contact tracing as implemented on the ground. In addition, our assumptions of the initial number of cases may not be realistic given evidences large number of unobserved infections [10]. Finally, the fact that our model does not have age structure has limited our capacity to include mortality estimates.…”

“…The rapid progression of the number of infections and deaths due to SARS-CoV-2 has taken many by surprise, with many of its characteristics related to its transmissibility under continuous update [2]. While the disease is still actively spreading in many regions of the world, researchers are working to quantify transmission parameters [2][3][4][5][6][7], and make estimates of infections and resulting deaths under different scenarios [8][9][10][11]. However, these studies are either too specific to certain geographies [10,12] or are too general to handle realistic scenarios [8,11] in the context of Sub Saharan Africa where majority of the population live in rural and semi urban areas with poor physical interconnections.…”

“…While the disease is still actively spreading in many regions of the world, researchers are working to quantify transmission parameters [2][3][4][5][6][7], and make estimates of infections and resulting deaths under different scenarios [8][9][10][11]. However, these studies are either too specific to certain geographies [10,12] or are too general to handle realistic scenarios [8,11] in the context of Sub Saharan Africa where majority of the population live in rural and semi urban areas with poor physical interconnections. To overcome this problem and make estimates of infections in clusters of population with different sizes, we developed a mathematical based model with Susceptible-Exposed-Infectious-Removed states, with parameters obtained from recent studies, and based on 54 scenarios of initial number of cases, coverage of contact tracing, and population size, more suited to realities in resource poor, less inter-connected regions around the world.…”