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)...

A primer on using mathematics to understand COVID-19 dynamics: Modeling, analysis and simulations

“…The Kermack-McKendrick-type epidemic models are built based on a number of simplifying assumptions, such as (a) a homogeneously-mixed population (i.e., all individuals in the community are assumed to have equal probability of coming in contact with one another), (b) exponentially-distributed waiting time in each epidemiological compartment ( Hethcote, 2000 ; Ngonghala et al., 2020a ; Nishiura & Chowell, 2009 ) and (c) no human demographic processes (i.e., no migration, births or deaths due to causes other than the disease being modeled). The assumption of no human demographic processes (i.e., vital dynamics) stems from the fact that, for a novel disease, such as COVID-19 (where, at the time of introduction, no member of the community has immunity due to natural recovery from prior exposure to the disease or due to immunization), the time scale of the disease is much smaller than the demographic time scale (i.e., the average lifespan of humans in the affected community).…”

“…By August 31, 2020, the US has recorded over 6 million confirmed cases and 187, 700 deaths. Although recent modeling data showed that COVID-19 was already spreading in the State of New York by late January 2020 ( Ngonghala et al., 2020a ), the officially reported “index case” for the State was documented on March 1, 2020 (which was traced to a woman who traveled to New York city from Iran, a country that was ravaged by COVID-19 at that time). Starting with the official “index case” on March 1, 2020, the State of New York recorded nearly 70, 000 confirmed cases and about 1, 000 deaths by the end of March 2020.…”

“…A variety of mathematical model types, including statistical (e.g., Srivastava & Chowell, 2020 ), deterministic (e.g., Eikenberry et al., 2020 ; Iboi et al., 2020 ; Ngonghala et al., 2020a ; Ngonghala et al., 2020b ), stochastic (e.g., Hellewell et al., 2020 ; Kucharski et al., 2020 ), network (e.g., Xue et al., 2020 ) and agent-based (e.g., Ferguson et al., 2020 ) models, have been used to study the transmission dynamics and control of COVID-19. A brief description of some of these modeling approaches is provided in Section 5 .…”

The potential contribution of face coverings to the control of SARS-CoV-2 transmission in schools and broader society in the UK: a modelling study

“…Unlike previous work that has considered specific values of testing level and projecting outcomes, our modelling provides all combinations of thresholds for testing and tracing coverage that could prevent a COVID-19 resurgence and a secondary wave whether or not mask were mandatory in secondary schools. Furthermore, previous studies [32][33][34][35][36][37][38][39] have explored the broader impact of masks by simulating lowered transmission across all layers in society. The Covasim model instead has the granularity to consider specific layers, hence allowing our study to specifically explore the impact of mandatory masks in secondary schools, in combination with different levels of TTI coverage.…”

“…A growing number of modelling studies have evaluated the impact of face coverings on the COVID-19 epidemic [32][33][34][35][36][37][38][39]. While the overall message from these models is that, as lockdown measures are relaxed, masks are likely to be effective if they are worn by a large percentage of the population, they often optimistically assumed that a large proportion of transmission events could be prevented with face masks by overestimating their efficacy and guided by evidence of the impact of masks on influenza transmission reduction [15]; hence their results are likely to overestimate impact.…”