Nonpharmaceutical Public Health Interventions Research Articles

Wastewater surveillance for COVID-19 in shelters: A creative strategy for a complex setting.

People experiencing homelessness experience disproportionate rates of morbidity and mortality from coronavirus disease 2019 (COVID-19) compared to the general population and shelters for people experiencing homelessness are a major contributing factor to these negative outcomes. As a result of their unique structure, population and physical space, these settings pose several challenges to the prevention of COVID-19 infection that are not adequately addressed by conventional non-pharmaceutical public health interventions. Wastewater surveillance for COVID-19 is a viable strategy for health protection in shelters due to its ability to meet these unique challenges. Its passive nature does not depend on individual health-seeking behaviours, and it can provide useful epidemiological information early on in an outbreak setting. In this commentary, the authors examine a recent application of wastewater surveillance of COVID-19 in a men's shelter in Toronto. Further applications of wastewater surveillance for other infectious diseases of concern in shelters are proposed, and the need for the development of ethical frameworks governing the use of this technology is discussed.

COVID-19 Vaccine Breakthrough Infections and Compliance to Non-Pharmaceutical Public Health Interventions: A Nested Case-Control Study

COVID-19 Vaccine Breakthrough Infections and Compliance to Non-Pharmaceutical Public Health Interventions: A Nested Case-Control Study

What is COVID-19 anyway? Narcissism and pandemic attitudes and behaviours

Researchers have demonstrated relationships between dark personality traits (e.g., narcissism) and pandemic behaviours (e.g., disregard for public health interventions). Individuals who disregard public health measures risk spreading COVID-19 infection, which has important public health implications. The present study was designed to examine the relationship between narcissism and pandemic attitudes and behaviours using a large population representative sample of North American adults (N = 5812). Participants completed measures of narcissism, psychological entitlement, non-adherence to non-pharmaceutical public health interventions (NPI), COVID disregard, anti-vaccination attitudes, reasons for social distancing, and COVID stress. Results of MANOVA demonstrated that individuals with high levels of narcissism self-reported greater levels of non-adherence to NPI, COVID disregard, COVID stress, anti-vaccination attitudes, and psychological entitlement compared to those with low levels of narcissism. Further, men with high levels of narcissism self-reported greater levels of non-adherence to NPI, COVID disregard, COVID stress, and psychological entitlement, in comparison to women with high levels of narcissism. These findings provide a nuanced understanding of the relationship between narcissistic traits, sex, and pandemic attitudes and behaviours and have implications for tailoring pandemic-specific public health interventions based on individual difference variables.

The impacts and implications of the community face mask use during the Covid‐19 pandemic: A qualitative narrative interview study

A range of nonpharmaceutical public health interventions has been introduced in many countries following the rapid spread of Covid-19 since 2020, including recommendations or mandates for the use of face masks or coverings in the community. While the effectiveness of face masks in reducing Covid-19 transmission has been extensively discussed, scant attention has been paid to the lived experience of those wearing face masks. Drawing on 40 narrative interviews with a purposive sample of people in the United Kingdom, with a particular focus on marginalised and minoritized groups, our paper explores experiences of face mask use during the pandemic. We find that face masks have a range of societal, health and safety impacts, and prompted positive and negative emotional responses for users. We map our findings onto Lorenc and Oliver's framework for intervention risks.We suggest that qualitative data offer particular insights into the experiences of public health interventions, allowing the potential downsides and risks of interventions to be more fully considered and informing public health policies that might avoid inadvertent harm, particularly towards marginalised groups. The study primarily involved members of the public in the conduct of the research, namely through participation in interviews (email and telephone). The conception for the study involved extensive discussions on social media with a range of people, and we received input and ideas from presentations we delivered on the preliminary analysis.

Impact of national COVID-19 restrictions on incidence of notifiable communicable diseases in England: an interrupted time series analysis

BackgroundNon-pharmaceutical interventions (NPIs), such as travel restrictions, social distancing and isolation policies, aimed at controlling the spread of COVID-19 may have reduced transmission of other endemic communicable diseases, such as measles, mumps and meningitis in England.MethodsAn interrupted time series analysis was conducted to examine whether NPIs was associated with trends in endemic communicable diseases, using weekly reported cases of seven notifiable communicable diseases (food poisoning, measles, meningitis, mumps, scarlet fever and pertussis) between 02/01/2017 to 02/01/2021 for England.ResultsFollowing the introduction of COVID-19 restrictions, there was an 81.1% (95% CI; 77.2–84.4) adjusted percentage reduction in the total number of notifiable diseases recorded per week in England. The greatest decrease was observed for measles, with a 90.5% percentage reduction (95% CI; 86.8–93.1) from 42 to 5 cases per week. The smallest decrease was observed for food poisoning, with a 56.4% (95%CI; 42.5–54.2) decrease from 191 to 83 cases per week.ConclusionsA total reduction in the incidence of endemic notifiable diseases was observed in England following the implementation of public health measures aimed at reducing transmission of SARS-COV-2 on March 23, 2020. The greatest reductions were observed in diseases most frequently observed during childhood that are transmitted via close human-to-human contact, such as measles and pertussis. A less substantive reduction was observed in reported cases of food poisoning, likely due to dining services (i.e., home deliveries and takeaways) remaining open and providing a potential route of transmission. This study provides further evidence of the effectiveness of non-pharmaceutical public health interventions in reducing the transmission of both respiratory and food-borne communicable diseases.

91 The impact of non-pharmaceutical public health interventions on hospital admissions and mortality from common causes of pediatric respiratory distress: a single center perspective

Abstract Background In response to the COVID-19 pandemic, jurisdictions around the world implemented policies to reduce COVID-19 transmission through public masking, travel restrictions, and closure of non-essential businesses. Collectively known as non-pharmaceutical interventions (NPI), these strategies reliably reduce the spread of COVID-19. International data suggests NPI also reduce hospitalizations for pediatric respiratory infections and their consequences, particularly asthma exacerbation. However, few Canadian studies have examined the impact of NPI on hospitalizations for common causes of pediatric respiratory distress. Objectives This study describes the impact of NPI on admissions for bronchiolitis, pneumonia, and asthma at a Canadian pediatric tertiary care centre. Design/Methods A retrospective chart review was conducted including all pediatric patients <18 years admitted to the general pediatric and pediatric intensive care units with bronchiolitis, pneumonia, or asthma. Data regarding diagnosis, length of hospitalization, and mortality were collected before (September 2016-March 2020) and in the 6 months after provincial NPI implementation (March 2020-September 2020). NPI were present throughout this period, however, specific measures varied due to evolving public health orders. Chi-squared testing was conducted to describe the impact of NPI on number of admissions, length of hospitalization, and mortality. Results Participants (n=1631) included 111 (6.8%) patients <1 month, 878 (53.8%) patients 1-23 months, 331 (20.3%) patients 24 months-4 years, and 311 (19.1%) patients ≥5 years. A mean of 205 patients were admitted every 6 months with respiratory distress (bronchiolitis, pneumonia, and/or asthma) prior to NPI implementation. During this timeframe, the 6-month mean admissions due to asthma, pneumonia, and bronchiolitis were 48, 56, and 101, respectively. In the 6 months following NPI implementation, there were 56 admissions for respiratory distress, including 15 for asthma, 19 for pneumonia, and 22 for bronchiolitis. Mean length of stay increased following the implementation of NPI from 8.49 to 11.68 days, whereas 6-month mean mortality decreased from two to zero deaths. Results did not attain statistical significance (p>0.05). Conclusion Results suggest NPI reduce hospitalizations and mortality from bronchiolitis, pneumonia, and asthma. Given the similar seasonality of these conditions, periodic use of NPI beyond the COVID-19 pandemic may reduce pediatric morbidity and mortality from common causes of respiratory distress. However, additional research is needed to describe the relationship between NPI and length of hospitalization. Future studies should also examine the impact of NPI on other pediatric infectious diseases to better characterize their utility.

A sliding window approach to optimize the time-varying parameters of a spatially-explicit and stochastic model of COVID-19.

The implementation of non-pharmaceutical public health interventions can have simultaneous impacts on pathogen transmission rates as well as host mobility rates. For instance, with SARS-CoV-2, masking can influence host-to-host transmission, while stay-at-home orders can influence mobility. Importantly, variations in transmission rates and mobility patterns can influence pathogen-induced hospitalization rates. This poses a significant challenge for the use of mathematical models of disease dynamics in forecasting the spread of a pathogen; to create accurate forecasts in spatial models of disease spread, we must simultaneously account for time-varying rates of transmission and host movement. In this study, we develop a statistical model-fitting algorithm to estimate dynamic rates of SARS-CoV-2 transmission and host movement from geo-referenced hospitalization data. Using simulated data sets, we then test whether our method can accurately estimate these time-varying rates simultaneously, and how this accuracy is influenced by the spatial population structure. Our model-fitting method relies on a highly parallelized process of grid search and a sliding window technique that allows us to estimate time-varying transmission rates with high accuracy and precision, as well as movement rates with somewhat lower precision. Estimated parameters also had lower precision in more rural data sets, due to lower hospitalization rates (i.e., these areas are less data-rich). This model-fitting routine could easily be generalized to any stochastic, spatially-explicit modeling framework, offering a flexible and efficient method to estimate time-varying parameters from geo-referenced data sets.

Non-pharmaceutical interventions and mortality in U.S. cities during the great influenza pandemic, 1918–1919

A key issue for the ongoing COVID-19 pandemic is whether non-pharmaceutical public-health interventions (NPIs) retard death rates. Good information about causal effects from NPIs comes from flu-related excess deaths in large U.S. cities during the second wave of the Great Influenza Pandemic, September 1918-February 1919. The measured NPIs are in three categories: school closings, prohibitions of public gatherings, and quarantine/isolation. Although an increase in NPIs flattened the curve in the sense of reducing the ratio of peak to overall flu-related excess death rates, the estimated effect on overall deaths is small and statistically insignificant. These findings differ from those associated with COVID-19 in the sense that facemask mandates and usage seem to reduce COVID-related cases.

Nonpharmaceutical public health interventions to curb the COVID-19 pandemic: a narrative review.

Nonpharmaceutical Interventions (NPI) consist of compulsory (isolation, quarantine, stay-at-home orders, banning public gatherings, nonessential business closures, school closures), and voluntary (social distancing, handwashing, respiratory etiquette, and universal mask wearing) measures. The aim of this narrative review is to evaluate the different forms of NPI and their effectiveness in combating the pandemic. Isolation can be indicated for symptomatic and asymptomatic infected people at home or at hospitals depending on the patient's clinical picture. Quarantine is a social distancing intervention in asymptomatic uninfected people who had contact with SARS-CoV-2 infected individuals. Stay-at-home orders refer to statewide mandates imposing nonessential business closures, prohibition of public events and gatherings, and travel restrictions. Studies have suggested that stay-at-home orders may be associated with a reduction in the incidence of COVID-19 in some countries. Mask wearing decreases the risk of COVID-19 in the community, especially when the surgical masks are used for vulnerable people. N-95 respirators protect health workers from COVID-19. NPI may be helpful to curb the COVID-19 pandemic while mass vaccination worldwide is not attainable, and the threat of SARS-COV-2 variants remain on the horizon.

Properties of the Omicron Variant of SARS-CoV-2 Affect Public Health Measure Effectiveness in the COVID-19 Epidemic.

Nonpharmaceutical and pharmaceutical public health interventions are important to mitigate the coronavirus disease 2019 (COVID-19) epidemic. However, it is still unclear how the effectiveness of these interventions changes with the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) novel variants. This simulation study utilized data from Japan and investigated how the characteristic properties of the Omicron variant, which emerged in late 2021, influence the effectiveness of public health interventions, including vaccination, the reduction of interpersonal contact, and the early isolation of infectious people. Although the short generation time of the Omicron variant increases the effectiveness of vaccination and the reduction of interpersonal contact, it decreases the effectiveness of early isolation. The latter feature may make the containment of case clusters difficult. The increase of infected children during the Omicron-dominant epidemic diminishes the effects of previously adult-targeted interventions. These findings underscore the importance of monitoring viral evolution and consequent changes in epidemiological characteristics. An assessment and adaptation of public health measures against COVID-19 are required as SARS-CoV-2 novel variants continue to emerge.

A combined theory-based explanatory model for predicting tourists’ travel intentions during the COVID-19 pandemic: the role of individual’s assessment of the compliance with non-pharmaceutical interventions

This study examines the impact of the COVID-19 pandemic and tourist’s assessments of non-pharmaceutical public-health interventions (NPIs) in relation to their travel intentions. It uses a combined theoretical model that incorporates the Domain-Specific Risk-Taking Scale (DOSPERT) in the recreational domain, the Health Belief Model (HBM) and the Theory of Planned Behaviour (TPB). A large-scale population study that is representative of Switzerland has been carried out to validate the model (N = 1683; 39% response rate). We use a regression model based on mean indices for our explanatory model. Health beliefs, namely perceived susceptibility and severity, are important predictors of travel intentions. The perceived benefits of and barriers to compliance with NPIs when travelling also have a substantial influence on travel intentions. The results demonstrated that the factors of the HBM tend to have a stronger influence than other significant factors, such as the perceived behavioural control of the TPB. As a situational context, the ability to work from home increases the intention to travel. The achievement of the present research is a validated empirical theory-based model that is suitable for practical and managerial implications. It can be used to create and evaluate measures and interventions that address the social psychological influencing factors.

Effectiveness of non-pharmaceutical public health interventions against COVID-19: A systematic review and meta-analysis.

Non-Pharmaceutical Public Health Interventions (NPHIs) have been used by different countries to control the spread of the COVID-19. Despite available evidence regarding the effectiveness of NPHSs, there is still no consensus about how policymakers can trust these results. Studies on the effectiveness of NPHSs are single studies conducted in specific communities. Therefore, they cannot individually prove if these interventions have been effective in reducing the spread of the infection and its adverse health outcomes. In this systematic review, we aimed to examine the effects of NPHIs on the COVID-19 case growth rate, death growth rate, Intensive Care Unit (ICU) admission, and reproduction number in countries, where NPHIs have been implemented. We searched relevant electronic databases, including Medline (via PubMed), Scopus, CINAHL, Web of Science, etc. from late December 2019 to February 1, 2021. The key terms were primarily drawn from Medical Subject Heading (MeSh and Emtree), literature review, and opinions of experts. Peer-reviewed quasi-experimental studies were included in the review. The PROSPERO registration number is CRD42020186855. Interventions were NPHIs categorized as lockdown, stay-at-home orders, social distancing, and other interventions (mask-wearing, contact tracing, and school closure). We used PRISMA 2020 guidance for abstracting the data and used Cochrane Effective Practice and Organization of Practice (EPOC) Risk of Bias Tool for quality appraisal of the studies. Hartung-Knapp-Sidik-Jonkman random-effects model was performed. Main outcomes included COVID-19 case growth rate (percentage daily changes), COVID-19 mortality growth rate (percentage daily changes), COVID-19 ICU admission (percentage daily changes), and COVID-19 reproduction number changes. Our search strategies in major databases yielded 12,523 results, which decreased to 7,540 articles after eliminating duplicates. Finally, 35 articles qualified to be included in the systematic review among which 23 studies were included in the meta-analysis. Although studies were from both low-income and high-income countries, the majority of them were from the United States (13 studies) and China (five studies). Results of the meta-analysis showed that adoption of NPHIs has resulted in a 4.68% (95% CI, -6.94 to -2.78) decrease in daily case growth rates, 4.8% (95 CI, -8.34 to -1.40) decrease in daily death growth rates, 1.90 (95% CI, -2.23 to -1.58) decrease in the COVID-19 reproduction number, and 16.5% (95% CI, -19.68 to -13.32) decrease in COVID-19 daily ICU admission. A few studies showed that, early enforcement of lockdown, when the incidence rate is not high, contributed to a shorter duration of lockdown and a lower increase of the case growth rate in the post-lockdown era. The majority of NPHIs had positive effects on restraining the COVID-19 spread. With the problems that remain regarding universal access to vaccines and their effectiveness and considering the drastic impact of the nationwide lockdown and other harsh restrictions on the economy and people’s life, such interventions should be mitigated by adopting other NPHIs such as mass mask-wearing, patient/suspected case isolation strategies, and contact tracing. Studies need to address the impact of NPHIs on the population’s other health problems than COVID-19.

A Mathematical Model of COVID-19 with Vaccination and Treatment.

We formulate and theoretically analyze a mathematical model of COVID-19 transmission mechanism incorporating vital dynamics of the disease and two key therapeutic measures—vaccination of susceptible individuals and recovery/treatment of infected individuals. Both the disease-free and endemic equilibrium are globally asymptotically stable when the effective reproduction number R0(v) is, respectively, less or greater than unity. The derived critical vaccination threshold is dependent on the vaccine efficacy for disease eradication whenever R0(v) > 1, even if vaccine coverage is high. Pontryagin's maximum principle is applied to establish the existence of the optimal control problem and to derive the necessary conditions to optimally mitigate the spread of the disease. The model is fitted with cumulative daily Senegal data, with a basic reproduction number R0 = 1.31 at the onset of the epidemic. Simulation results suggest that despite the effectiveness of COVID-19 vaccination and treatment to mitigate the spread of COVID-19, when R0(v) > 1, additional efforts such as nonpharmaceutical public health interventions should continue to be implemented. Using partial rank correlation coefficients and Latin hypercube sampling, sensitivity analysis is carried out to determine the relative importance of model parameters to disease transmission. Results shown graphically could help to inform the process of prioritizing public health intervention measures to be implemented and which model parameter to focus on in order to mitigate the spread of the disease. The effective contact rate b, the vaccine efficacy ε, the vaccination rate v, the fraction of exposed individuals who develop symptoms, and, respectively, the exit rates from the exposed and the asymptomatic classes σ and ϕ are the most impactful parameters.

The impact of social distancing, contact tracing, and case isolation interventions to suppress the COVID-19 epidemic: A modeling study

IntroductionMost countries are dependent on nonpharmaceutical public health interventions such as social distancing, contact tracing, and case isolation to mitigate COVID-19 spread until medicines or vaccines widely available. Minimal research has been performed on the independent and combined impact of each of these interventions based on empirical case data. MethodsWe obtained data from all confirmed COVID-19 cases from January 7th to February 22nd 2020 in Zhejiang Province, China, to fit an age-stratified compartmental model using human contact information before and during the outbreak. The effectiveness of social distancing, contact tracing, and case isolation was studied and compared in simulation. We also simulated a two-phase reopening scenario to assess whether various strategies combining nonpharmaceutical interventions are likely to achieve population-level control of a second-wave epidemic. ResultsOur study sample included 1,218 symptomatic cases with COVID-19, of which 664 had no inter-province travel history. Results suggest that 36.5 % (95 % CI, 12.8–57.1) of contacts were quarantined, and approximately five days (95 % CI, 2.2–11.0) were needed to detect and isolate a case. As contact networks would increase after societal and economic reopening, avoiding a second wave without strengthening nonpharmaceutical interventions compared to the first wave it would be exceedingly difficult. ConclusionsContinuous attention and further improvement of nonpharmaceutical interventions are needed in second-wave prevention. Specifically, contact tracing merits further attention.

The impacts of New Zealand's COVID-19 epidemic response on community antibiotic use and hospitalisation for pneumonia, peritonsillar abscess and rheumatic fever

BackgroundThe rate of community antibiotic use in New Zealand (NZ) is high and some may be unnecessary. Non-pharmaceutical public health interventions (Alert Levels) were implemented in 2020 to reduce the spread of COVID-19 in NZ and were likely to have affected antibiotic prescribing. MethodsWe aimed to identify the impact of these public health interventions on community antibiotic dispensing. We also examined rates of hospitalisation with infectious diseases that could be influenced by changing community antibiotic use. A retrospective review of two national databases was undertaken. Findings1.17 million people received 1.19 million prescriptions for antibiotics between 23/02/2020 and 18/07/2020. Antibiotic dispensing rates fell from 14 prescriptions per 1000 population per week during pre-Alert Level weeks to 9 prescriptions per 1000 population per week (a reduction of 36%) during the weeks of COVID Alert Level 3–4. Large reductions were seen with antibiotics predominantly used for respiratory- or urinary-tract infections. Hospital discharges with sentinel infections did not increase over this period; pneumonia discharges during Alert Level weeks were lower than in 2017-2019 (3 vs 6 discharges per 100,000 population). InterpretationA large reduction in community antibiotic dispensing was observed in NZ during the implementation of non-pharmaceutical public health interventions to eliminate COVID-19. Despite this marked reduction in antibiotic use, there was no increase in rates of hospitalisation for sentinel infections that community antibiotic use could prevent. These findings suggest that countries with high rates of antibiotic use could significantly reduce their use without an increase in morbidity. FundingNo financial support received.

The Combined Effect of Vaccination and Nonpharmaceutical Public Health Interventions—Ending the COVID-19 Pandemic

Mehul D. Patel, PhD; Erik Rosenstrom, BS; Julie S. Ivy, PhD; Maria E. Mayorga, PhD; Pinar Keskinocak, PhD; Ross M. Boyce, MD, MSc; Kristen Hassmiller Lich, PhD; Raymond L. Smith III, PhD; Karl T. Johnson, BA; Paul L. Delamater, PhD; Julie L. Swann, PhD

Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States

BackgroundThe widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs), such as non-essential business closures and gathering bans, to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is greatly needed to assist in guiding individualized decision making for adjustment of interventions in the US and around the world. However, the impacts of these approaches remain uncertain.MethodsBased on the reported cases, the effective reproduction number (Rt) of COVID-19 epidemic for 50 states in the US was estimated. Measurements on the effectiveness of nine different NPIs were conducted by assessing risk ratios (RRs) between Rt and NPIs through a generalized linear model (GLM).ResultsDifferent NPIs were found to have led to different levels of reduction in Rt. Stay-at-home contributed approximately 51% (95% CI 46–57%), wearing (face) masks 29% (15–42%), gathering ban (more than 10 people) 19% (14–24%), non-essential business closure 16% (10–21%), declaration of emergency 13% (8–17%), interstate travel restriction 11% (5–16%), school closure 10% (7–14%), initial business closure 10% (6–14%), and gathering ban (more than 50 people) 7% (2–11%).ConclusionsThis retrospective assessment of NPIs on Rt has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases.

The Impact of COVID-19 Interventions on Influenza and Mycobacterium Tuberculosis Infection.

A series of public health interventions have been implemented to prevent the transmission of SARS-CoV-2 in China. However, the effect of non-pharmaceutical interventions to COVID-19 on the incidence of the influenza virus and Mycobacterium tuberculosis infections is not clear. In current study, we analyzed surveillance data on influenza and Mycobacterium tuberculosis from Henan Provincial People’s Hospital in Zhengzhou, Henan province, China from 2019 to 2020. The monthly positive test rate for influenza and Mycobacterium tuberculosis to estimate transmissibility changes was calculated. The positive detection rate of influenza A declined significantly during the implementation of inventions in 2020, from a total positive rate of 17.69% in 2019 to 5.77% in 2020. Similarly, a 2.15% reduction in positive detective rate was seen for influenza B, from a total positive rate of 5.15% in 2019 to 3% in 2020. The positive rate curve of Mycobacterium tuberculosis measured by x-pert in 2020 remained above the curve in 2019 from March to June, and August, showing the rising trend under these precautions. Our study suggests that non-pharmaceutical public health interventions likely reduced influenza transmission significantly and have less effect on Mycobacterium tuberculosis transmission in 2020.

Pandemics and regional economic growth: evidence from the Great Influenza in Italy

Abstract We investigate the link between the 1918 Great Influenza and regional economic growth in Italy, a country in which the measures implemented by public authorities to contain the contagion were limited or ineffective. The pandemic caused 600,000 deaths in Italy: 1.2% of the population. Going from regions with the lowest mortality to those with the highest mortality is associated to a decline in per capita GDP growth of 6.5%, which dissipated within 3 years. Our estimates provide an upper bound of the adverse effect of pandemics on regional economic growth in the absence of non-pharmaceutical public-health interventions.

A Spatiotemporal Tool to Project Hospital Critical Care Capacity and Mortality From COVID-19 in US Counties.

Objectives. To create a tool to rapidly determine where pandemic demand for critical care overwhelms county-level surge capacity and to compare public health and medical responses.Methods. In March 2020, COVID-19 cases requiring critical care were estimated using an adaptive metapopulation SEIR (susceptible‒exposed‒infectious‒recovered) model for all 3142 US counties for future 21-day and 42-day periods from April 2, 2020, to May 13, 2020, in 4 reactive patterns of contact reduction-0%, 20%, 30%, and 40%-and 4 surge response scenarios-very low, low, medium, and high.Results. In areas with increased demand, surge response measures could avert 104 120 additional deaths-55% through high clearance of critical care beds and 45% through measures such as greater ventilator access. The percentages of lives saved from high levels of contact reduction were 1.9 to 4.2 times greater than high levels of hospital surge response. Differences in projected versus actual COVID-19 demands were reasonably small over time.Conclusions. Nonpharmaceutical public health interventions had greater impact in minimizing preventable deaths during the pandemic than did hospital critical care surge response. Ready-to-go spatiotemporal supply and demand data visualization and analytics tools should be advanced for future preparedness and all-hazards disaster response.