Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave in Europe and the United States

Abstract

Given the narrowness of the initial testing criteria, the SARS-CoV-2 virus spread through cryptic transmission in January and February, setting the stage for the epidemic wave experienced in March and April, 2020. We use a global metapopulation epidemic model to provide a mechanistic understanding of the global dynamic underlying the establishment of the COVID-19 pandemic in Europe and the United States (US). The model is calibrated on international case introductions at the early stage of the pandemic. We find that widespread community transmission of SARS-CoV-2 was likely in several areas of Europe and the US by January 2020, and estimate that by early March, only 1 - 3 in 100 SARS-CoV-2 infections were detected by surveillance systems. Modeling results indicate international travel as the key driver of the introduction of SARS-CoV-2 with possible importation and transmission events as early as December, 2019. We characterize the resulting heterogeneous spatio-temporal spread of SARS-CoV-2 and the burden of the first COVID-19 wave (February-July 2020). We estimate infection attack rates ranging from 0.78%-15.2% in the US and 0.19%-13.2% in Europe. The spatial modeling of SARS-CoV-2 introductions and spreading provides insights into the design of innovative, model-driven surveillance systems and preparedness plans that have a broader initial capacity and indication for testing.

Figure 1:. Early picture of the COVID-19 outbreak in Europe and the United States.

(A) Timelines of the daily reported and confirmed cases of COVID-19 in Europe and US including information on initial reported cases and other significant events related to the outbreak. (B) Model-based estimates for the daily number of new infections in Europe and US. The inset plot compares the weekly incidence of reported cases with the weekly incidence of infections estimated by the model for the week of March 8 – 14, 2020 for the continental US-states and European countries that reported at least 1 case. Circle size corresponds to the population size of each state and country. (C) The probability that a city in Europe and the US had generated at least 100 cumulative infections by February 21, 2020. Color and circle size are proportional to the probability.

Figure 2:. Timing of the onset of local transmission.

We plot the posterior distributions of the week when each US state (A) or European country (B) first reached 10 locally generated SARS-CoV-2 transmission events per day. Countries/states are ordered by the median date of their posterior distribution. The week of this date corresponds to the dates reported on the the vertical axis.

Figure 3:. Importation sources.

Each US state (A) and European country (B) is displayed in a clockwise order with respect to the start of the local outbreak (as seen in Fig. 2). Importation flows are directed and weighted. We normalize links considering the total in-flow for each state so that the sum of importations flows, for each state, is one. In the SM we report the complete list of countries contributing, as importation sources, in each group (i.e., geographical region).

Figure 4:. The burden of the first wave in Europe and the US

(A-D) Model projection results of the weekly deaths for selected countries in Europe. (E) Estimated infection attack rates and infection fatality rates by July 4, 2020 for European countries where there were at least 100 reported deaths. (F-I) Model projection results of the weekly deaths for selected states in the US. (J) Estimated infection attack rates and infection fatality rates by July 4, 2020 for 20 US states.

Figure 5:. Correlation Analysis for European countries and US states.

(A) The correlation between the ordering of each country/state to reach 100 infections in the model projections and to reach 100 reported cases in the surveillance data. Correlation is computed considering the Kendall rank correlation coefficient, τ. (B) The correlation between the ordering of each country/state considering the time needed to reach 100 reported cases in the surveillance data and the ranking of the combined international and domestic air traffic. (C) Left: the correlation between the number of cases reported by the date of lockdown for selected European countries (from Table 4 in (55)) and the projected total number of infections by July 4, 2020. Right: the correlation between the number of cases reported by March 16, 2020 for each US state and the projected total infections by July 4, 2020. (D) The correlation between the model-projected infection attack rate and the serological prevalence collected from studies. Data points refer to different dates and locations (table with values and dates reported in the SI). The correlations are calculated using the Pearson correlation coefficient r in (C-D).