Counterfactuals of effects of vaccination and public health measures on COVID-19 cases in Canada: What could have happened?

This study illustrates what may have happened, in terms of coronavirus disease 2019 (COVID-19) infections, hospitalizations and deaths in Canada, had public health measures not been used to control the COVID-19 epidemic, and had restrictions been lifted with low levels of vaccination, or no vaccination, of the Canadian population. The timeline of the epidemic in Canada, and the public health interventions used to control the epidemic, are reviewed. Comparisons against outcomes in other countries and counterfactual modelling illustrate the relative success of control of the epidemic in Canada. Together, these observations show that without the use of restrictive measures and without high levels of vaccination, Canada could have experienced substantially higher numbers of infections and hospitalizations and almost a million deaths.

Assessing the mechanism of citywide test-trace-isolate Zero-COVID policy and exit strategy of COVID-19 pandemic.

BACKGROUND: Countries that aimed for eliminating the cases of COVID-19 with test-trace-isolate policy are found to have lower infections, deaths, and better economic performance, compared with those that opted for other mitigation strategies. However, the continuous evolution of new strains has raised the question of whether COVID-19 eradication is still possible given the limited public health response capacity and fatigue of the epidemic. We aim to investigate the mechanism of the Zero-COVID policy on outbreak containment, and to explore the possibility of eradication of Omicron transmission using the citywide test-trace-isolate (CTTI) strategy. METHODS: We develop a compartmental model incorporating the CTTI Zero-COVID policy to understand how it contributes to the SARS-CoV-2 elimination. We employ our model to mimic the Delta outbreak in Fujian Province, China, from September 10 to October 9, 2021, and the Omicron outbreak in Jilin Province, China for the period from March 1 to April 1, 2022. Projections and sensitivity analyses were conducted using dynamical system and Latin Hypercube Sampling/ Partial Rank Correlation Coefficient (PRCC). RESULTS: Calibration results of the model estimate the Fujian Delta outbreak can end in 30 (95% confidence interval CI: 28-33) days, after 10 (95% CI: 9-11) rounds of citywide testing. The emerging Jilin Omicron outbreak may achieve zero COVID cases in 50 (95% CI: 41-57) days if supported with sufficient public health resources and population compliance, which shows the effectiveness of the CTTI Zero-COVID policy. CONCLUSIONS: The CTTI policy shows the capacity for the eradication of the Delta outbreaks and also the Omicron outbreaks. Nonetheless, the implementation of radical CTTI is challenging, which requires routine monitoring for early detection, adequate testing capacity, efficient contact tracing, and high isolation compliance, which constrain its benefits in regions with limited resources. Moreover, these challenges become even more acute in the face of more contagious variants with a high proportion of asymptomatic cases. Hence, in regions where CTTI is not possible, personal protection, public health control measures, and vaccination are indispensable for mitigating and exiting the COVID-19 pandemic.

The need for linked genomic surveillance of SARS-CoV-2.

Genomic surveillance during the coronavirus disease 2019 (COVID-19) pandemic has been key to the timely identification of virus variants with important public health consequences, such as variants that can transmit among and cause severe disease in both vaccinated or recovered individuals. The rapid emergence of the Omicron variant highlighted the speed with which the extent of a threat must be assessed. Rapid sequencing and public health institutions' openness to sharing sequence data internationally give an unprecedented opportunity to do this; however, assessing the epidemiological and clinical properties of any new variant remains challenging. Here we highlight a "band of four" key data sources that can help to detect viral variants that threaten COVID-19 management: 1) genetic (virus sequence) data; 2) epidemiological and geographic data; 3) clinical and demographic data; and 4) immunization data. We emphasize the benefits that can be achieved by linking data from these sources and by combining data from these sources with virus sequence data. The considerable challenges of making genomic data available and linked with virus and patient attributes must be balanced against major consequences of not doing so, especially if new variants of concern emerge and spread without timely detection and action.

Efficacy of a "stay-at-home" policy on SARS-CoV-2 transmission in Toronto, Canada: a mathematical modelling study.

BACKGROUND: Globally, nonpharmaceutical interventions for COVID-19, including stay-at-home policies, limitations on gatherings and closure of public spaces, are being lifted. We explored the effect of lifting a stay-at-home policy on virus resurgence under different conditions. METHODS: Using confirmed case data from Toronto, Canada, between Feb. 24 and June 24, 2020, we ran a compartmental model with household structure to simulate the impact of the stay-at-home policy considering different levels of compliance. We estimated threshold values for the maximum number of contacts, probability of transmission and testing rates required for the safe reopening of the community. RESULTS: After the implementation of the stay-at-home policy, the contact rate outside the household fell by 39% (from 11.58 daily contacts to 7.11). The effective reproductive number decreased from 3.56 (95% confidence interval [CI] 3.02-4.14) on Mar. 12 to 0.84 (95% CI 0.79-0.89) on May 6. Strong adherence to stay-at-home policies appeared to prevent SARS-CoV-2 resurgence, but extending the duration of stay-at-home policies beyond 2 months had little added effect on cumulative cases (25 958 for 65 days of a stay-at-home policy and 23 461 for 95 days, by July 2, 2020) and deaths (1404 for 65 days and 1353 for 95 days). To avoid a resurgence, the average number of contacts per person per day should be kept below 9, with strict nonpharmaceutical interventions in place. INTERPRETATION: Our study demonstrates that the stay-at-home policy implemented in Toronto in March 2020 had a substantial impact on mitigating the spread of SARS-CoV-2. In the context of the early pandemic, before the emergence of variants of concern, reopening schools and workplaces was possible only with other nonpharmaceutical interventions in place.

Projections of the transmission of the Omicron variant for Toronto, Ontario, and Canada using surveillance data following recent changes in testing policies.

At the end of 2021, with the rapid escalation of COVID19 cases due to the Omicron variant, testing centers in Canada were overwhelmed. To alleviate the pressure on the PCR testing capacity, many provinces implemented new strategies that promote self testing and adjust the eligibility for PCR tests, making the count of new cases underreported. We designed a novel compartmental model which captures the new testing guidelines, social behaviours, booster vaccines campaign and features of the newest variant Omicron. To better describe the testing eligibility, we considered the population divided into high risk and non-high-risk settings. The model is calibrated using data from January 1 to February 9, 2022, on cases and severe outcomes in Canada, the province of Ontario and City of Toronto. We conduct analyses on the impact of PCR testing capacity, self testing, different levels of reopening and vaccination coverage on cases and severe outcomes. Our results show that the total number of cases in Canada, Ontario and Toronto are 2.34 (95%CI: 1.22-3.38), 2.20 (95%CI: 1.15-3.72), and 1.97(95%CI: 1.13-3.41), times larger than reported cases, respectively. The current testing strategy is efficient if partial restrictions, such as limited capacity in public spaces, are implemented. Allowing more people to have access to PCR reduces the daily cases and severe outcomes; however, if PCR test capacity is insufficient, then it is important to promote self testing. Also, we found that reopening to a pre-pandemic level will lead to a resurgence of the infections, peaking in late March or April 2022. Vaccination and adherence to isolation protocols are important supports to the testing policies to mitigate any possible spread of the virus.

Decision analysis support for evaluating transmission risk of COVID-19 in places where people gather.

BACKGROUND: The coronavirus diseases 2019 (COVID-19) pandemic has presented an unprecedented public health challenge. Prior to vaccination, non-pharmaceutical interventions, including closures, were necessary to help control the epidemic. With the arrival of variants of concern and insufficient population vaccination coverage, ongoing evaluation of transmission risk in settings and the use of non-pharmaceutical interventions are necessary to help control the epidemic. This study aimed to produce a framework for evaluating transmission risk in settings where individuals gather and inform decision-making. METHODS: A multi-criteria decision analysis process was used to structure the framework. Fifteen criteria were identified as important to consider for COVID-19 transmission risk based on the literature. This list was ranked by experts and then categorized. The analysis was structured by the consensus list of criteria and relative positioning of each criteria within the list to produce sets of factors to consider when assessing transmission risk at gatherings. RESULTS: Fifteen experts from across Canada participated in ranking the criteria. Strong consensus was found on the relative importance of criteria and this relative consensus was used to create four categories: critical (3 criteria); important (6 criteria); good to consider (5 criteria); and if time permits (1 criterion). CONCLUSION: The resulting consensus list and categories constitutes a set of important elements that can be applied to any setting as an objective and transparent framework to assess transmission risk in the venue. In conjunction with further consideration of the local epidemiology of COVID-19, an overall risk of transmission assessment can be established and uniformly implemented.

Modelling the impact of age-stratified public health measures on SARS-CoV-2 transmission in Canada.

Public health measures applied exclusively within vulnerable populations have been suggested as an alternative to community-wide interventions to mitigate SARS-CoV-2 transmission. With the population demography and healthcare capacity of Canada as an example, a stochastic age-stratified agent-based model was used to explore the progression of the COVID-19 epidemic under three intervention scenarios (infection-preventing vaccination, illness-preventing vaccination and shielding) in individuals above three age thresholds (greater than or equal to 45, 55 and 65 years) while lifting shutdowns and physical distancing in the community. Compared with a scenario with sustained community-wide measures, all age-stratified intervention scenarios resulted in a substantial epidemic resurgence, with hospital and ICU bed usage exceeding healthcare capacities even at the lowest age threshold. Individuals under the age threshold were severely impacted by the implementation of all age-stratified interventions, with large numbers of avoidable deaths. Among all explored scenarios, shielding older individuals led to the most detrimental outcomes (hospitalizations, ICU admissions and mortality) for all ages, including the targeted population. This study suggests that, in the absence of community-wide measures, implementing interventions exclusively within vulnerable age groups could result in unmanageable levels of infections, with serious outcomes within the population. Caution is therefore warranted regarding early relaxation of community-wide restrictions.

Modelling the impact of shutdowns on resurging SARS-CoV-2 transmission in Canada.

BACKGROUND: Shutdowns are enacted when alternative public health measures are insufficient to control the epidemic and the population is largely susceptible. An age-stratified agent-based model was developed to explore the impact of shutdowns to control SARS-CoV-2 transmission in Canada under the assumption that current efforts to control the epidemic remains insufficient and in the absence of a vaccine. METHODS: We estimated the current levels of interventions in Canada to generate a baseline scenario from 7 February to 7 September 2020. Four aspects of shutdowns were explored in scenarios that ran from 8 September 2020 to 7 January 2022, these included the impact of how quickly shutdowns are implemented, the duration of shutdowns, the minimum break (delays) between shutdowns and the types of sectors to shutdown. Comparisons among scenarios were made using cases, hospitalizations, deaths and shutdown days during the 700-day model runs. RESULTS: We found a negative relationship between reducing SARS-CoV-2 transmission and the number of shutdown days. However, we also found that for shutdowns to be optimally effective, they need to be implemented fast with minimal delay, initiated when community transmission is low, sustained for an adequate period and be stringent and target multiple sectors, particularly those driving transmission. By applying shutdowns in this manner, the total number of shutdown days could be reduced compared to delaying the shutdowns until further into the epidemic when transmission is higher and/or implementing short insufficient shutdowns that would require frequent re-implementation. This paper contrasts a range of shutdown strategies and trade-offs between health outcomes and economic metrics that need to be considered within the local context. INTERPRETATION: Given the immense socioeconomic impact of shutdowns, they should be avoided where possible and used only when other public health measures are insufficient to control the epidemic. If used, the time it buys to delay the epidemic should be used to enhance other equally effective, but less disruptive, public health measures.

A window of opportunity for intensifying testing and tracing efforts to prevent new COVID-19 outbreaks due to more transmissible variants.

BACKGROUND: When public health interventions are being loosened after several days of decline in the number of coronavirus disease 2019 (COVID-19) cases, it is of critical importance to identify potential strategies to ease restrictions while mitigating a new wave of more transmissible variants of concern (VOCs). We estimated the necessary enhancements to public health interventions for a partial reopening of the economy while avoiding the worst consequences of a new outbreak, associated with more transmissible VOCs. METHODS: We used a transmission dynamics model to quantify conditions that combined public health interventions must meet to reopen the economy without a large outbreak. These conditions are those that maintain the control reproduction number below unity, while accounting for an increase in transmissibility due to VOC. RESULTS: We identified combinations of the proportion of individuals exposed to the virus who are traced and quarantined before becoming infectious, the proportion of symptomatic individuals confirmed and isolated, and individual daily contact rates needed to ensure the control reproduction number remains below unity. CONCLUSION: Our analysis indicates that the success of restrictive measures including lockdown and stay-at-home orders, as reflected by a reduction in number of cases, provides a narrow window of opportunity to intensify case detection and contact tracing efforts to prevent a new wave associated with circulation of more transmissible VOCs.

Population surveillance approach to detect and respond to new clusters of COVID-19.

BACKGROUND: To maintain control of the coronavirus disease 2019 (COVID-19) epidemic as lockdowns are lifted, it will be crucial to enhance alternative public health measures. For surveillance, it will be necessary to detect a high proportion of any new cases quickly so that they can be isolated, and people who have been exposed to them traced and quarantined. Here we introduce a mathematical approach that can be used to determine how many samples need to be collected per unit area and unit time to detect new clusters of COVID-19 cases at a stage early enough to control an outbreak. METHODS: We present a sample size determination method that uses a relative weighted approach. Given the contribution of COVID-19 test results from sub-populations to detect the disease at a threshold prevalence level to control the outbreak to 1) determine if the expected number of weekly samples provided from current healthcare-based surveillance for respiratory virus infections may provide a sample size that is already adequate to detect new clusters of COVID-19 and, if not, 2) to determine how many additional weekly samples were needed from volunteer sampling. RESULTS: In a demonstration of our method at the weekly and Canadian provincial and territorial (P/T) levels, we found that only the more populous P/T have sufficient testing numbers from healthcare visits for respiratory illness to detect COVID-19 at our target prevalence level-assumed to be high enough to identify and control new clusters. Furthermore, detection of COVID-19 is most efficient (fewer samples required) when surveillance focuses on healthcare symptomatic testing demand. In the volunteer populations: the higher the contact rates; the higher the expected prevalence level; and the fewer the samples were needed to detect COVID-19 at a predetermined threshold level. CONCLUSION: This study introduces a targeted surveillance strategy, combining both passive and active surveillance samples, to determine how many samples to collect per unit area and unit time to detect new clusters of COVID-19 cases. The goal of this strategy is to allow for early enough detection to control an outbreak.

The origins and potential future of SARS-CoV-2 variants of concern in the evolving COVID-19 pandemic.

One year into the global COVID-19 pandemic, the focus of attention has shifted to the emergence and spread of SARS-CoV-2 variants of concern (VOCs). After nearly a year of the pandemic with little evolutionary change affecting human health, several variants have now been shown to have substantial detrimental effects on transmission and severity of the virus. Public health officials, medical practitioners, scientists, and the broader community have since been scrambling to understand what these variants mean for diagnosis, treatment, and the control of the pandemic through nonpharmaceutical interventions and vaccines. Here we explore the evolutionary processes that are involved in the emergence of new variants, what we can expect in terms of the future emergence of VOCs, and what we can do to minimise their impact.

Simple mathematical modelling approaches to assessing the transmission risk of SARS-CoV-2 at gatherings.

BACKGROUND: Gatherings may contribute significantly to the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). For this reason, public health interventions have sought to constrain unrepeated or recurrent gatherings to curb the coronavirus disease 2019 (COVID-19) pandemic. Unfortunately, the range of different types of gatherings hinders specific guidance from setting limiting parameters (e.g. total size, number of cohorts, the extent of physical distancing). METHODS: We used a generic modelling framework, based on fundamental probability principles, to derive simple formulas to assess introduction and transmission risks associated with gatherings, as well as the potential efficiency of some testing strategies to mitigate these risks. RESULTS: Introduction risk can be broadly assessed with the population prevalence and the size of the gathering, while transmission risk at a gathering is mainly driven by the gathering size. For recurrent gatherings, the cohort structure does not have a significant impact on transmission between cohorts. Testing strategies can mitigate risk, but frequency of testing and test performance are factors in finding a balance between detection and false positives. CONCLUSION: The generality of the modelling framework used here helps to disentangle the various factors affecting transmission risk at gatherings and may be useful for public health decision-making.

A renewal equation model to assess roles and limitations of contact tracing for disease outbreak control.

We propose a deterministic model capturing essential features of contact tracing as part of public health non-pharmaceutical interventions to mitigate an outbreak of an infectious disease. By incorporating a mechanistic formulation of the processes at the individual level, we obtain an integral equation (delayed in calendar time and advanced in time since infection) for the probability that an infected individual is detected and isolated at any point in time. This is then coupled with a renewal equation for the total incidence to form a closed system describing the transmission dynamics involving contact tracing. We define and calculate basic and effective reproduction numbers in terms of pathogen characteristics and contact tracing implementation constraints. When applied to the case of SARS-CoV-2, our results show that only combinations of diagnosis of symptomatic infections and contact tracing that are almost perfect in terms of speed and coverage can attain control, unless additional measures to reduce overall community transmission are in place. Under constraints on the testing or tracing capacity, a temporary interruption of contact tracing may, depending on the overall growth rate and prevalence of the infection, lead to an irreversible loss of control even when the epidemic was previously contained.

Effets projetés des mesures de santé publique non pharmacologiques visant à prévenir la recrudescence de la transmission du SRAS-CoV-2 au Canada.

CONTEXTE: Il faudra prendre des mesures continues contre la transmission communautaire du coronavirus du syndrome respiratoire aigu sévère 2 (SRAS-CoV-2) pour prévenir d'autres vagues d'infection. Nous avons exploré les effets des interventions non pharmacologiques sur la transmission projetée du SRAS-CoV-2 au Canada. MÉTHODES: Nous avons créé un modèle de la population canadienne à base d'agents intégrant l'âge qui simule les effets des mesures de santé publique, selon leur intensité actuelle et projetée, sur la transmission du SRAS-CoV-2. Les mesures étudiées sont le dépistage et l'isolement des cas, la recherche de contacts et la mise en quarantaine, l'éloignement sanitaire et la fermeture des espaces partagés. Nous avons évalué l'effet des mesures prises individuellement et celui des mesures combinées. RÉSULTATS: En l'absence de mesures, 64,6 % (intervalle de crédibilité [ICr] à 95 % : 63,9 %­65,0 %) des Canadiens contracteraient le SRAS-CoV-2 (taux d'attaque global), et 3,6 % (ICr à 95 % 2,4 %­3,8 %) des personnes infectées en mourraient. En poursuivant le dépistage et la recherche de contacts à la même intensité que pendant la période de référence, sans maintenir l'éloignement sanitaire ou refermer certains endroits, le pays connaîtrait un taux d'attaque global de 56,1 % (ICr à 95 % 0,05 %­57,1 %); si ces mesures étaient accrues, le taux d'attaque chuterait à 0,4 % (ICr à 95 % 0,03 %­23,5 %). En combinant ce dernier scénario et le maintien de l'éloignement sanitaire, le taux tomberait à 0,2 % (ICr à 95 % 0,03 %­1,7 %). Ce scénario est le seul qui garderait la demande en soins hospitaliers et intensifs sous la capacité, qui préviendrait presque tous les décès et qui mettrait fin à l'épidémie. La prolongation de la fermeture des écoles aurait un effet minime, mais réduirait la transmission en milieu scolaire. Par contre, la prolongation de la fermeture des lieux de travail et des lieux publics réduirait de manière marquée le taux d'attaque et mettait habituellement ou toujours fin à l'épidémie, selon les différents scénarios simulés. INTERPRÉTATION: Le contrôle de la transmission du SRAS-CoV-2 passera par l'amélioration et le maintien des mesures, tant communautaires qu'individuelles. Autrement, il y aura une recrudescence de l'épidémie, et un risque de surcharger le système de santé.

Quantifying the shift in social contact patterns in response to non-pharmaceutical interventions.

Social contact mixing plays a critical role in influencing the transmission routes of infectious diseases. Moreover, quantifying social contact mixing patterns and their variations in a rapidly evolving pandemic intervened by changing public health measures is key for retroactive evaluation and proactive assessment of the effectiveness of different age- and setting-specific interventions. Contact mixing patterns have been used to inform COVID-19 pandemic public health decision-making; but a rigorously justified methodology to identify setting-specific contact mixing patterns and their variations in a rapidly developing pandemic, which can be informed by readily available data, is in great demand and has not yet been established. Here we fill in this critical gap by developing and utilizing a novel methodology, integrating social contact patterns derived from empirical data with a disease transmission model, that enables the usage of age-stratified incidence data to infer age-specific susceptibility, daily contact mixing patterns in workplace, household, school and community settings; and transmission acquired in these settings under different physical distancing measures. We demonstrated the utility of this methodology by performing an analysis of the COVID-19 epidemic in Ontario, Canada. We quantified the age- and setting (household, workplace, community, and school)-specific mixing patterns and their evolution during the escalation of public health interventions in Ontario, Canada. We estimated a reduction in the average individual contact rate from 12.27 to 6.58 contacts per day, with an increase in household contacts, following the implementation of control measures. We also estimated increasing trends by age in both the susceptibility to infection by SARS-CoV-2 and the proportion of symptomatic individuals diagnosed. Inferring the age- and setting-specific social contact mixing and key age-stratified epidemiological parameters, in the presence of evolving control measures, is critical to inform decision- and policy-making for the current COVID-19 pandemic.

Exploring the percentage of COVID-19 cases reported in the community in Canada and associated case fatality ratios.

While surveillance can identify changes in COVID-19 transmission patterns over time and space, sections of the population at risk, and the efficacy of public health measures, reported cases of COVID-19 are generally understood to only capture a subset of the actual number of cases. Our primary objective was to estimate the percentage of cases reported in the general community, considered as those that occurred outside of long-term care facilities (LTCFs), in specific provinces and Canada as a whole. We applied a methodology using the delay-adjusted case fatality ratio (CFR) to all cases and deaths, as well as those representing the general community. Our second objective was to assess whether the assumed CFR (mean = 1.38%) was appropriate for calculating underestimation of cases in Canada. Estimates were developed for the period from March 11th, 2020 to September 16th, 2020. Estimates of the percentage of cases reported (PrCR) and CFR varied spatially and temporally across Canada. For the majority of provinces, and for Canada as a whole, the PrCR increased through the early stages of the pandemic. The estimated PrCR in general community settings for all of Canada increased from 18.1% to 69.0% throughout the entire study period. Estimates were greater when considering only those data from outside of LTCFs. The estimated upper bound CFR in general community settings for all of Canada decreased from 9.07% on March 11th, 2020 to 2.00% on September 16th, 2020. Therefore, the true CFR in the general community in Canada was likely less than 2% on September 16th. According to our analysis, some provinces, such as Alberta, Manitoba, Newfoundland and Labrador, Nova Scotia, and Saskatchewan reported a greater percentage of cases as of September 16th, compared to British Columbia, Ontario, and Québec. This could be due to differences in testing rates and criteria, demographics, socioeconomic factors, race, and access to healthcare among the provinces. Further investigation into these factors could reveal differences among provinces that could partially explain the variation in estimates of PrCR and CFR identified in our study. The estimates provide context to the summative state of the pandemic in Canada, and can be improved as knowledge of COVID-19 reporting rates and disease characteristics are advanced.

Projected effects of nonpharmaceutical public health interventions to prevent resurgence of SARS-CoV-2 transmission in Canada.

BACKGROUND: Continual efforts to eliminate community transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will be needed to prevent additional waves of infection. We explored the impact of nonpharmaceutical interventions on projected SARS-CoV-2 transmission in Canada. METHODS: We developed an age-structured agent-based model of the Canadian population simulating the impact of current and projected levels of public health interventions on SARS-CoV-2 transmission. Interventions included case detection and isolation, contact tracing and quarantine, physical distancing and community closures, evaluated alone and in combination. RESULTS: Without any interventions, 64.6% (95% credible interval [CrI] 63.9%-65.0%) of Canadians will be infected with SARS-CoV-2 (total attack rate) and 3.6% (95% CrI 2.4%-3.8%) of those infected and symptomatic will die. If case detection and contact tracing continued at baseline levels without maintained physical distancing and reimplementation of restrictive measures, this combination brought the total attack rate to 56.1% (95% CrI 0.05%-57.1%), but it dropped to 0.4% (95% CrI 0.03%-23.5%) with enhanced case detection and contact tracing. Combining the latter scenario with maintained physical distancing reduced the total attack rate to 0.2% (95% CrI 0.03%-1.7%) and was the only scenario that consistently kept hospital and intensive care unit bed use under capacity, prevented nearly all deaths and eliminated the epidemic. Extending school closures had minimal effects but did reduce transmission in schools; however, extending closures of workplaces and mixed-age venues markedly reduced attack rates and usually or always eliminated the epidemic under any scenario. INTERPRETATION: Controlling SARS-CoV-2 transmission will depend on enhancing and maintaining interventions at both the community and individual levels. Without such interventions, a resurgent epidemic will occur, with the risk of overwhelming our health care systems.