A novel coronavirus emerged in December of 2019 (COVID-19), causing a pandemic that inflicted unprecedented public health and economic burden in all nooks and corners of the world. Although the control of COVID-19 largely focused on the use of basic public health measures (primarily based on using non-pharmaceutical interventions, such as quarantine, isolation, social-distancing, face mask usage, and community lockdowns) initially, three safe and highly-effective vaccines (by AstraZeneca Inc., Moderna Inc., and Pfizer Inc.), were approved for use in humans in December 2020. We present a new mathematical model for assessing the population-level impact of these vaccines on curtailing the burden of COVID-19. The model stratifies the total population into two subgroups, based on whether or not they habitually wear face mask in public. The resulting multigroup model, which takes the form of a deterministic system of nonlinear differential equations, is fitted and parameterized using COVID-19 cumulative mortality data for the third wave of the COVID-19 pandemic in the United States. Conditions for the asymptotic stability of the associated disease-free equilibrium, as well as an expression for the vaccine-derived herd immunity threshold, are rigorously derived. Numerical simulations of the model show that the size of the initial proportion of individuals in the mask-wearing group, together with positive change in behavior from the non-mask wearing group (as well as those in the mask-wearing group, who do not abandon their mask-wearing habit) play a crucial role in effectively curtailing the COVID-19 pandemic in the United States. This study further shows that the prospect of achieving vaccine-derived herd immunity (required for COVID-19 elimination) in the U.S., using the Pfizer or Moderna vaccine, is quite promising. In particular, our study shows that herd immunity can be achieved in the U.S. if at least 60% of the population are fully vaccinated. Furthermore, the prospect of eliminating the pandemic in the U.S. in the year 2021 is significantly enhanced if the vaccination program is complemented with non-pharmaceutical interventions at moderate increased levels of compliance (in relation to their baseline compliance). The study further suggests that, while the waning of natural and vaccine-derived immunity against COVID-19 induces only a marginal increase in the burden and projected time-to-elimination of the pandemic, adding the impacts of therapeutic benefits of the vaccines into the model resulted in a dramatic reduction in the burden and time-to-elimination of the pandemic.
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Modeling COVID-19 scenarios for the United States
Abstract We use COVID-19 case and mortality data from 1 February 2020 to 21 September 2020 and a deterministic SEIR (susceptible, exposed, infectious and recovered) compartmental framework to model possible trajectories of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and the effects of non-pharmaceutical interventions in the United States at the state level from 22 September 2020 through 28 February 2021. Using this SEIR model, and projections of critical driving covariates (pneumonia seasonality, mobility, testing rates and mask use per capita), we assessed scenarios of social distancing mandates and levels of mask use. Projections of current non-pharmaceutical intervention strategies by state—with social distancing mandates reinstated when a threshold of 8 deaths per million population is exceeded (reference scenario)—suggest that, cumulatively, 511,373 (469,578–578,347) lives could be lost to COVID-19 across the United States by 28 February 2021. We find that achieving universal mask use (95% mask use in public) could be sufficient to ameliorate the worst effects of epidemic resurgences in many states. Universal mask use could save an additional 129,574 (85,284–170,867) lives from September 22, 2020 through the end of February 2021, or an additional 95,814 (60,731–133,077) lives assuming a lesser adoption of mask wearing (85%), when compared to the reference scenario.
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- Award ID(s):
- 2031096
- NSF-PAR ID:
- 10227893
- Date Published:
- Journal Name:
- Nature Medicine
- Volume:
- 27
- Issue:
- 1
- ISSN:
- 1078-8956
- Page Range / eLocation ID:
- 94 to 105
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract The United States approached the COVID‐19 pandemic with inconsistent responses that varied by state. In Florida, legislators passed laws contrary to mitigating the pandemic. These laws included banning county and municipal efforts to control the spread of COVID‐19 through mask mandates, social distancing, and prohibiting vaccination mandates during infectious disease epidemics. Moreover, the Legislature simultaneously prioritized policies of social exclusion, passing bills that constrained the rights of transgender individuals, Black Lives Matter protestors, and educators. In this article, I use the perspectives of critical medical anthropology and “governing through contagion” to examine Florida's COVID‐19 response. I argue the COVID‐19 pandemic provided an opportunity for legislators to obfuscate their political power and advance a politics of social division while simultaneously passing policies that undermined human health. I refer to this process as governing
with contagion: Using a pandemic as a politically expedient backdrop to conceal power and simultaneously harm human health. -
Eksin, Ceyhun (Ed.)We simulated epidemic projections of a potential COVID-19 outbreak in a residential university population in the United States under varying combinations of asymptomatic tests (5% to 33% per day), transmission rates (2.5% to 14%), and contact rates (1 to 25), to identify the contact rate threshold that, if exceeded, would lead to exponential growth in infections. Using this, we extracted contact rate thresholds among non-essential workers, population size thresholds in the absence of vaccines, and vaccine coverage thresholds. We further stream-lined our analyses to transmission rates of 5 to 8%, to correspond to the reported levels of face-mask-use/physical-distancing during the 2020 pandemic. Our results suggest that, in the absence of vaccines, testing alone without reducing population size would not be sufficient to control an outbreak. If the population size is lowered to 34% (or 44%) of the actual population size to maintain contact rates at 4 (or 7) among non-essential workers, mass tests at 25% (or 33%) per day would help control an outbreak. With the availability of vaccines, the campus can be kept at full population provided at least 95% are vaccinated. If vaccines are partially available such that the coverage is lower than 95%, keeping at full population would require asymptomatic testing, either mass tests at 25% per day if vaccine coverage is at 63–79%, or mass tests at 33% per day if vaccine coverage is at 53–68%. If vaccine coverage is below 53%, to control an outbreak, in addition to mass tests at 33% per day, it would also require lowering the population size to 90%, 75%, and 60%, if vaccine coverage is at 38–53%, 23–38%, and below 23%, respectively. Threshold estimates from this study, interpolated over the range of transmission rates, can collectively help inform campus level preparedness plans for adoption of face mask/physical-distancing, testing, remote instructions, and personnel scheduling, during non-availability or partial-availability of vaccines, in the event of SARS-Cov2-type disease outbreaks.more » « less
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The early phases of the COVID-19 pandemic in the United States caused unprecedented disruption to engineering students and society-at-large. Residential students suddenly found themselves forced off-campus and into a new regime of online learning. On top of this, students faced pandemic related uncertainty about their health and the health of their loved ones, restrictions on social life, and the privations of a stuttering economy. It is perhaps unsurprising, then, that during the early days of the COVID-19 pandemic the engineering student population saw large increases in incidences of depression and other psychological conditions. While COVID-19 continues to be a concern, many of the restrictions and precautions associated with the early outbreak have been relaxed. Most engineering programs are back to in person learning, and strict COVID-testing regimes, mask mandates, and limits on large public gatherings have been largely phased out. With academia and society slowly adjusting to this “new normal,” it is important to know whether and to what extent mental health of engineering students has changed over the course of the pandemic. This work explores this question by analyzing longitudinal data collected at four times from 2019-2021. We analyze how the prevalence of different conditions changed with the onset of the COVID-19 pandemic, and whether they have returned to pre-pandemic levels. Among other results, we found statistically significant increases were observed in total depressive disorders between our initial sample (Fall 2019) and a sample taken immediately post-COVID (Spring 2020). While measured rates of depression decreased between Spring 2020 and Fall 2021, it was not statistically significant, potentially indicating that the student population is still recovering on this metric. Conversely our data shows a statistically significant drop in moderate-to-major psychological distress between our Fall 2019 pre-pandemic sampling and our Fall 2021 post-pandemic sampling indicating, potentially indicating an improvement in overall mental health. Breaking the data down by gender, no significant changes were observed across any measure during the four sample periods for women respondents. Men, however, showed a significant increase in depressive disorders from Fall 2019 to Spring 2020; and a significant decrease in depressive disorders from Spring 2020 to Fall 2021.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1038/s41591-020-1132-9
