Could masks curtail the post-lockdown resurgence of COVID-19 in the US?

Abstract

The community lockdown measures implemented in the United States from late March to late May of 2020 resulted in a significant reduction in the community transmission of the COVID-19 pandemic throughout the country. However, a number of US states are currently experiencing an alarming post-lockdown resurgence of the pandemic, triggering fears for a devastating second pandemic wave. We designed a mathematical model for addressing the key question of whether or not the universal use of face masks can halt such resurgence (and possibly avert a second wave, without having to undergo another cycle of major community lockdown) in the states of Arizona, Florida, New York and the entire US. Model calibration, using cumulative mortality data for the four jurisdictions during their respective pre-lockdown and lockdown periods, show that pre-symptomatic and asymptomatically-infectious individuals are, by far, the main drivers of the COVID-19 pandemic in each of the jurisdictions. The implication of this result is that detecting and isolating individuals with clinical symptoms of the pandemic alone (even if all of them are found) may not be sufficient to effectively curtail the pandemic. To achieve such control, it is crucially-necessary that pre-symptomatic and asymptomatically-infectious individuals are rapidly detected and isolated (and their contacts rapidly traced and tested). Our study highlights the importance of early implementation of the community lockdown measures. In particular, a sizable reduction in the burden of the pandemic would have been recorded in each of the four jurisdictions if the community lockdown measures were implemented a week or two earlier. These reductions are significantly increased if the early implementation of the lockdown measures was complemented with a public face mask use strategy. With all related control measures maintained at their baseline levels, this study shows that the pandemic would have been almost completely suppressed from significantly taking off if the lockdown measures were implemented two weeks earlier, and if a sizable percentage of the residents of the four jurisdictions wore face masks during the respective lockdown periods. The burden of the second wave of the pandemic would have been reduced significantly if the lockdown measures were extended by two weeks. We simulated the pandemic in the four jurisdictions under three levels of lifting of community lockdown, namely mild, moderate and high. For the scenario where the control measures adopted are maintained at their baseline levels during the lockdown period, our simulations show that the states of Arizona and Florida will record devastating second waves of the pandemic by the end of 2020, while the state of New York and the entire US will record milder second waves. If the community lockdown measures were lifted at the mild lifting level (i.e., only limited community contacts and business activities are allowed, in comparison to the levels of these activities allowed during the corresponding lockdown period), only the state of Florida will experience a second wave. It is further shown that the severity of the projected second waves depend on the level of lifting of the community lockdown. For instance, the projected second wave for Arizona and Florida will be more severe than their respective first waves. It is further shown that, for high level of lifting of community lockdown measures, the increased use of face masks after the lockdown period greatly reduces the burden of the pandemic in each jurisdiction. In particular, for this high lockdown lifting scenario, none of the four jurisdictions will experience a second wave if half of their residents wear face masks consistently after their respective lockdown period. A diagnostic testing strategy that increases the maximum detection rate of asymptomatic infected individuals (followed by contact tracing and self-isolation of the detected cases) greatly reduces the burden of the pandemic in all four jurisdictions, particularly if also combined with a universal face mask use strategy. Finally, it is shown that the universal use of face masks in public, with at least moderate level of compliance, could halt the post-lockdown resurgence of COVID-19, in addition to averting the potential for (and severity of) a second wave of the pandemic in each of the four jurisdictions.

Keywords: Community lockdown lifting; Diagnostic testing and detection contact tracing; Face mask compliance; Mathematical model for COVID-19; Self-isolation.

Fig. 1

Flow diagram of the model (2.1), showing the transition of individuals between mutually-exclusive compartments based on disease status. Notation: ${\sigma }_a=r{\sigma }_p,{\sigma }_m=(1-r)g{\sigma }_p,{\sigma }_s=(1-r)(1-g){\sigma }_p$. The state variables and parameters are described in Table A2.

Fig. 2

Data fitting of the model (2.1), for the pre-lockdown and lockdown periods for the states of Arizona, Florida, New York and the entire US. (a)–(d): cumulative mortality data and model fit for the pre-lockdown period for the state of Arizona, Florida, New York, and the entire US, respectively. (e)–(h): cumulative mortality data and model fit for the lockdown period for the states of Arizona, Florida, New York and for the entire US, respectively. The data is displayed in red dots.

Fig. 3

Simulations of the model (2.1) using values of the 13 known parameters of the model obtained from the literature (given in Table A3 in Appendix A) and those for the 12 unknown parameters obtained from fitting the model with the cumulative COVID-19 mortality data (given in Tables A4–A7 in Appendix A). (a)–(d): Daily mortality data and daily mortality prediction generated from the model for the pre-lockdown period for the states of Arizona, Florida, New York, and for the entire US, respectively. (e)–(h): Daily mortality data and daily mortality prediction from the model for the lockdown period for the state of Arizona, Florida, New York and the entire US, respectively. The data is displayed in red dots.

Fig. 4

Sensitivity of the control reproduction number (${ℛ}_c$) to face masks usage and diagnostic detection rate of asymptomatic individuals. Heat maps of the control reproduction number, as a function of cloth face mask use compliance ($c_m$) and percentage increases in the maximum detection rate of asymptomatic infected individuals (${\tau }_{dmax}$), for various efficacy levels of face masks in the states of Arizona, Florida, New York and the entire US. (a)–(d): cloth masks used (with efficacy ${\epsilon }_m=0.25$) in the states of Arizona, Florida, New York and all of US, respectively. (e)–(h): surgical/medical masks used (with efficacy ${\epsilon }_m=0.50$) in the state of Arizona, Florida, New York and all of US, respectively. Parameter values used in the simulations are as given in Tables A3–A7 in Appendix A.

Fig. 5

Sensitivity of the control reproduction number (${ℛ}_c$) to face masks compliance ($c_m$) and efficacy (${\epsilon }_m$) for the states of Arizona (a), Florida (b), New York (c) and the entire US (d). Parameter values used in the simulations are as given in Tables A3–A7 in Appendix A.

Fig. 6

Impact of early lockdown: Simulations of the model (2.1), showing the daily and cumulative mortality, as a function of time, for various durations of the onset of lockdown measures for the states of Arizona, Florida, New York and the whole of US. The model is ran from the date of the index case, for each of the four jurisdictions, and extended one month beyond the first day of the relaxation (or partial lifting) of the lockdown measures. (a)–(d): daily deaths for the state of Arizona, Florida, New York and all of US, respectively. (e)–(h): cumulative deaths for the state of Arizona, Florida, New York and all of US, respectively. The predictions of the model, for the case when community lockdown measures were implemented one week earlier, two weeks earlier, or on the actual date the lockdown measures were implemented, are represented by magenta, green, and blue curves, respectively. Red dots represent the actual observed data, while blue dashed vertical lines depict the start and end of the actual lockdown period (shaded in cyan). The dashed vertical green and magenta lines depict the starting point of lockdown measures if they were implemented one and two weeks earlier, respectively. Parameter values used for the simulations are given in Tables A3–A7 in Appendix A, with various start dates for the implementation of community lockdown.

Fig. 7

Impact of face masks compliance during lockdown: Simulations of the model (2.1), showing cumulative mortality, as a function of time, for the US state of Arizona, Florida, New York and the entire US. The model is simulated from the date of the index case for each of the four jurisdictions, for different levels of face masks compliance ($c_m$). (a)–(d): cumulative deaths for the states of Arizona, Florida, New York and all of US, respectively. The blue curve represents the case for the baseline value of the face masks compliance, and the red dots represent the actual data. The blue dashed vertical lines represent the onset and termination dates for the lockdown measures (this region is shaded in cyan color). Parameter values used in the simulations are as given in Tables A3–A7 in Appendix A, with various levels of face masks compliance ($c_m$).

Fig. 8

Impact of re-opening of community lockdown. Simulations of the model (2.1), showing daily and cumulative mortality, as a function of time, for various levels of re-opening of community lockdown measures in the states of Arizona, Florida, New York and the entire US. Mild, moderate, and high re-opening of community lockdown corresponds to a $5\text{\%},10\text{\%}$, and $20\text{\%}$ increase in the baseline value of the community contact rate parameters (${\beta }_p,{\beta }_a,{\beta }_i$, and ${\beta }_s$), respectively. (a)–(d): Daily deaths for the state of Arizona, Florida, New York and all of US, respectively. (e)–(h): Cumulative deaths for the state of Arizona, Florida, New York and all of US, respectively. Solid blue curves represent daily and cumulative mortality during the lockdown period, while blue dashed vertical lines depict the start and end of the actual lockdown period (shaded in cyan). Other parameter values used for the simulations are as given in Tables A3–A7 in Appendix A.

Fig. 9

Impact of face mask usage on COVID-19 burden after high lifting of community lockdown. Simulations of the model (2.1), for high lifting of community lockdown in the states of Arizona, Florida, New York and the entire US, and various levels of face mask compliance ($c_m$). (a)–(d): Daily mortality for the state of Arizona, Florida, New York and all of US, respectively. (e)–(h): Cumulative mortality for the state of Arizona, Florida, New York and all of US, respectively. Solid blue curves represent daily and cumulative mortality during the lockdown period, while blue dashed vertical lines depict the start and end of the actual lockdown period (shaded in cyan). The parameter values used for the simulations are as given in Tables A3–A7 in Appendix A.

Fig. 10

Impact of higher lifting of community lockdown measures (as measured in terms of $50\text{\%}$ increase in the baseline values of the community contact rate parameters, ${\beta }_e$, ${\beta }_i$, ${\beta }_a$ and ${\beta }_s$) and various compliance levels of face mask usage in the four jurisdictions. Simulations for the model (2.1) showing the daily mortality, as a function of time. (a)–(d): daily deaths for the state of Arizona, Florida, New York and all of US, respectively. The solid blue curve represents daily mortality during lockdown, while blue dashed vertical lines depict the start and end of the actual lockdown period (shaded in cyan). Parameter values used are as given in Tables A3–A7 in Appendix A, with various levels of face masks compliance ($c_m$).

Fig. 11

Impact of percentage increase in maximum detection rate of asymptomatic infected individuals, for the case where high level of lifting of community lockdown (i.e., $20\text{\%}$ increase in the community contact rates) was implemented in each of the four jurisdictions. Simulations of the model (2.1), showing daily and cumulative mortality, as a function of time. (a)–(d): daily deaths for the state of Arizona, Florida, New York and all of US, respectively. (e)–(h): cumulative deaths for the state of Arizona, Florida, New York and all of US, respectively. Solid blue curves represent daily and cumulative mortality during the lockdown period, while blue dashed vertical lines depict the start and end of the actual lockdown period (shaded in cyan). Parameter values used are as given in Tables A3–A7 in Appendix A, with various percentage increase in the value of ${\tau }_{dmax}$.

Fig. 12

Impact of increase in maximum detection rate of asymptomatic infected individuals$\left({\tau }_{dmax}\right)$and face masks use. Simulations of the model (2.1), showing daily and cumulative mortality, as a function of time, for high level of lockdown lifting in the states of Arizona, Florida, New York and the entire US. (a)–(d): daily deaths for the state of Arizona, Florida, New York and all of US, respectively. (e)–(h): cumulative deaths for the state of Arizona, Florida, New York and all of US, respectively. Solid blue curves represent daily and cumulative mortality during the lockdown period, while blue dashed vertical lines depict the start and end of the actual lockdown period (shaded in cyan). Parameter values used are as given in Tables A3–A7 in Appendix A, with various values of percentage increases in ${\tau }_{dmax}$ and face masks compliance fixed at $25\text{\%}$ (i.e., $c_m=0.25$).