State-level needs for social distancing and contact tracing to contain COVID-19 in the United States

Abstract

Starting in mid-May 2020, many US states began relaxing social-distancing measures that were put in place to mitigate the spread of COVID-19. To evaluate the impact of relaxation of restrictions on COVID-19 dynamics and control, we developed a transmission dynamic model and calibrated it to US state-level COVID-19 cases and deaths. We used this model to evaluate the impact of social distancing, testing and contact tracing on the COVID-19 epidemic in each state. As of 22 July 2020, we found that only three states were on track to curtail their epidemic curve. Thirty-nine states and the District of Columbia may have to double their testing and/or tracing rates and/or rolling back reopening by 25%, while eight states require an even greater measure of combined testing, tracing and distancing. Increased testing and contact-tracing capacity is paramount for mitigating the recent large-scale increases in US cases and deaths.

Extended Data Fig. 1:. Correlations across states between R_eff(t) and (A) θ_min, (B) η, (C) Δ, and (D) f_C.

For each state, 500 posterior samples are shown. Substantial state-to-state heterogeneity is evident in all parameters, with η,θ_min, r_max, and f_C contribute over 50% of the variance in R_eff(t) under a linear model (estimated from ANOVA table [Table S1] using the sum-of-squares relative to the total sum-of-squares). For θ_min, while lower values appear to be associated with greater current values of R_eff(t) in a univariate model (linear model coefficient = −0.54, t statistic = −78.14, p < 2.2e-16, 95% CI = [−0.56,−0.53]), the correlation is positive in the multivariate model (coefficient = 0.11, t statistic = 13.65, p < 2.2e-16, 95% CI = [0.09, 0.13]). The other parameters correlate as expected: higher R_eff(t) is correlated with lower contribution from hygiene practices (smaller η) (coefficient = −0.39, t statistic = −59.7, p < 2.2e-16, 95% CI = [−0.40,−0.38]), more reopening (larger r_max) (coefficient = 0.44, t statistic = 119.0, p < 2.2e-16, 95% CI = [0.43, 0.45]), and lower rates of contact tracing (smaller f_C) (coefficient = −0.90, t statistic = −114.6, p < 2.2e-16, 95% CI = [−0.92, −0.89]).

Extended Data Fig. 2:. Contour maps for each state of the probability that R_eff(t) at different levels contact tracing f_C and testing λ.

Contours are labelled as by median and 95% Credible interval, and current median estimates of f_C and λ are shown by the circle.

Extended Data Fig. 3:. Estimated testing and contact tracing rates needed for R_eff(t) < 1 as of July 22, 2020.

Boxplots (line = median, box = IQR, whiskers = 95% CrI) are filled based on the estimated R_eff(t) on July 22, 2020, as shown in the legend. Top panel is changing testing rate alone, the middle panel is changing contact tracing rate alone, and the bottom panel is changing both to the same value. Also shown are the current median estimates of the testing and contact tracing rates.

Extended Data Fig. 4:. Estimated testing and contact tracing rates needed for R(t) < 1 with complete re-opening (i.e., removal of all social distancing and hygiene mitigation).

Boxplots (line = median, box = IQR, whiskers = 95% CrI) are filled based on the estimated R_eff(t) on July 22, 2020, as shown in the legend. Top panel is changing testing rate alone, the middle panel is changing contact tracing rate alone, and the bottom panel is changing both to the same value. Also shown are the current median estimates of the testing and contact tracing rates.

Figure 1.. SEIR model structure, parameter, data sources, and fitting/validation methods.

We used mobility data to constrain the time-dependence of the contact rate. We fitted the model to daily reported cases and confirmed deaths from March 19^th to April 30^th and validated its projections against data from May 1^st to June 20^th. On the model projections, the black solid line is the median, the pink band is the 95% credible interval (CrI) and the orange is the interquartile range (IQR). We show model fitting and validation for four states: New York (NY), Ohio (OH), Texas (TX), and Washington (WA).

Figure 2.. Estimated effective reproduction number R_eff and the level of reopening/rebound in transmission as of July 22^nd, 2020 for all states.

(A) shows estimated R_eff (median, IQR, and 95% CrI) across States. The figure shows the value of R_eff on July 22^nd, 2020, as well as the “minimum” value of R_eff between March 19^th, 2020 and July 22^nd, 2020, in lighter shades of each color. It also includes the date of the minimum R_eff. (B) shows the level of reopening/rebound in disease transmission in each state relative to its minimum value during state shelter-in-place (median, IQR, and 95% CrI).

Figure 3.

Predicted time-course (median, IQR, and 95% CrI) of daily reported cases and deaths under different testing and contact tracing rates (1X and 2X) in New York (A), Ohio (B), Texas (C), and Washington State (D).

Figure 4.. Reopening/rebound in transmission Δ_crit permitted (0% = minimum shelter-in-place value, 100% = return to no restrictions) to keep R_eff < 1.

(A) If testing and contact rates are unchanged, (B) testing rate is doubled, (C) contact tracing is doubled, or (D) both testing and contact tracing are doubled. Δ(t) the level of reopening/rebound in transmission on July 22^nd, 2020 is shown by the circle. All boxplots show median, IQR, and 95% CrI.

Figure 5.. State-specific level of mitigation needed as a July 22^nd, 2020 to curtail the spread of COVID-19

(keeping R < 1 with at least 75% confidence, equivalent to the upper bound of the Interquartile range (IQR)). Categories based on evaluating scenarios with different combinations of baseline/doubling testing, baseline/doubling contact tracing, and baseline/+25%/−25% in the reopening parameter Δ. Categories are defined as follows: Very Low (no states): Can reopen further by >25% while keeping R(t)<1; Low (3 states): Can reopen further by < 25% with up to 2X increase in testing while keeping R(t)<1; Moderate (9 states): Requires 2X contact tracing or reversal of reopening by 25% to keep R(t)<1; High (30 states and DC): Requires multiple interventions (2X testing, 2X contract tracing, reversal of reopening by 25%) to keep R(t)<1; Very High (8 states): Reverse of reopening by 50%, combined with 2X testing and/or 2X contact tracing with to keep R(t)<1. The U.S. map shapefile is from the “usmap” R package, which is open source under GPL-3.