Transmission dynamics reveal the impracticality of COVID-19 herd immunity strategies

Significance Confronted with escalating COVID-19 outbreaks, countries at the leading edge of the pandemic have had to resort to imposing drastic social distancing measures which have serious societal and economic repercussions. Establishing herd immunity in a population by allowing the epidemic to spread, while mitigating the negative health impacts of COVID-19, presents a tantalizing resolution to the crisis. Our study simulating SARS-CoV-2 spread in the United Kingdom finds that achieving herd immunity without overwhelming hospital capacity leaves little room for error. Intervention levels must be carefully manipulated in an adaptive manner for an extended period, despite acute sensitivity to poorly quantified epidemiological factors. Such fine-tuning of social distancing renders this strategy impractical. The rapid growth rate of COVID-19 continues to threaten to overwhelm healthcare systems in multiple countries. In response, severely affected countries have had to impose a range of public health strategies achieved via nonpharmaceutical interventions. Broadly, these strategies have fallen into two categories: 1) “mitigation,” which aims to achieve herd immunity by allowing the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus to spread through the population while mitigating disease burden, and 2) “suppression,” aiming to drastically reduce SARS-CoV-2 transmission rates and halt endogenous transmission in the target population. Using an age-structured transmission model, parameterized to simulate SARS-CoV-2 transmission in the United Kingdom, we assessed the long-term prospects of success using both of these approaches. We simulated a range of different nonpharmaceutical intervention scenarios incorporating social distancing applied to differing age groups. Our modeling confirmed that suppression of SARS-CoV-2 transmission is possible with plausible levels of social distancing over a period of months, consistent with observed trends. Notably, our modeling did not support achieving herd immunity as a practical objective, requiring an unlikely balancing of multiple poorly defined forces. Specifically, we found that 1) social distancing must initially reduce the transmission rate to within a narrow range, 2) to compensate for susceptible depletion, the extent of social distancing must be adaptive over time in a precise yet unfeasible way, and 3) social distancing must be maintained for an extended period to ensure the healthcare system is not overwhelmed.

[1]  Christl A. Donnelly,et al.  The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries , 2020, Science.

[2]  Heba Habib Has Sweden’s controversial covid-19 strategy been successful? , 2020, BMJ.

[3]  A. Flahault,et al.  Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): a population-based study , 2020, The Lancet.

[4]  N. G. Davies,et al.  Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study , 2020, The Lancet Public Health.

[5]  K. Abbasi,et al.  The UK’s public health response to covid-19 , 2020, BMJ.

[6]  P. Horby,et al.  Features of 16,749 hospitalised UK patients with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol , 2020, medRxiv.

[7]  W. Wei,et al.  Presymptomatic Transmission of SARS-CoV-2 — Singapore, January 23–March 16, 2020 , 2020, MMWR. Morbidity and mortality weekly report.

[8]  Chonggang Xu,et al.  High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2 , 2020, Emerging infectious diseases.

[9]  A. Vespignani,et al.  Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study , 2020, The Lancet Infectious Diseases.

[10]  M. Mello,et al.  Thinking Globally, Acting Locally - The U.S. Response to Covid-19. , 2020, The New England journal of medicine.

[11]  P. Vollmar,et al.  Virological assessment of hospitalized patients with COVID-2019 , 2020, Nature.

[12]  C. Whittaker,et al.  Estimates of the severity of coronavirus disease 2019: a model-based analysis , 2020, The Lancet Infectious Diseases.

[13]  Carl A. B. Pearson,et al.  The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study , 2020, The Lancet Public Health.

[14]  David J. Hunter Covid-19 and the Stiff Upper Lip - The Pandemic Response in the United Kingdom. , 2020, The New England journal of medicine.

[15]  C. Whittaker,et al.  Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand , 2020 .

[16]  Peng Wu,et al.  Detection of Covid-19 in Children in Early January 2020 in Wuhan, China , 2020, The New England journal of medicine.

[17]  Hannah R. Meredith,et al.  The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application , 2020, Annals of Internal Medicine.

[18]  Yonatan H. Grad,et al.  Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period , 2020, Science.

[19]  Yongsheng Wu,et al.  Epidemiology and Transmission of COVID-19 in Shenzhen China: Analysis of 391 cases and 1,286 of their close contacts , 2020, medRxiv.

[20]  T. Hollingsworth,et al.  How will country-based mitigation measures influence the course of the COVID-19 epidemic? , 2020, The Lancet.

[21]  R. Horton Offline: COVID-19—a reckoning , 2020, The Lancet.

[22]  A. Schuchat,et al.  COVID-19: towards controlling of a pandemic , 2020, The Lancet.

[23]  K. Yuen,et al.  Clinical Characteristics of Coronavirus Disease 2019 in China , 2020, The New England journal of medicine.

[24]  E. Dong,et al.  An interactive web-based dashboard to track COVID-19 in real time , 2020, The Lancet Infectious Diseases.

[25]  Min Kang,et al.  SARS-CoV-2 Viral Load in Upper Respiratory Specimens of Infected Patients , 2020, The New England journal of medicine.

[26]  Jing Zhao,et al.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia , 2020, The New England journal of medicine.

[27]  N. Linton,et al.  Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data , 2020, medRxiv.

[28]  Y. Hu,et al.  Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China , 2020, The Lancet.

[29]  G. Gao,et al.  A Novel Coronavirus from Patients with Pneumonia in China, 2019 , 2020, The New England journal of medicine.

[30]  A. Handel,et al.  Heterogeneity and longevity of antibody memory to viruses and vaccines , 2018, PLoS biology.

[31]  A. King,et al.  The impact of past vaccination coverage and immunity on pertussis resurgence , 2018, Science Translational Medicine.

[32]  Pejman Rohani,et al.  Combating pertussis resurgence: One booster vaccination schedule does not fit all , 2015, Proceedings of the National Academy of Sciences.

[33]  Jérôme Hugues,et al.  Model‐Based Analysis , 2013 .

[34]  T. Déirdre Hollingsworth,et al.  Mitigation Strategies for Pandemic Influenza A: Balancing Conflicting Policy Objectives , 2011, PLoS Comput. Biol..

[35]  R. Mikolajczyk,et al.  Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases , 2008, PLoS medicine.

[36]  M. Keeling,et al.  Modeling Infectious Diseases in Humans and Animals , 2007 .

[37]  Pejman Rohani,et al.  Appropriate Models for the Management of Infectious Diseases , 2005, PLoS medicine.

[38]  J. Watmough,et al.  Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. , 2002, Mathematical biosciences.

[39]  A L Lloyd,et al.  Realistic distributions of infectious periods in epidemic models: changing patterns of persistence and dynamics. , 2001, Theoretical population biology.

[40]  S. Leeder,et al.  A population based study , 1993, The Medical journal of Australia.

[41]  R. May,et al.  Infectious Diseases of Humans: Dynamics and Control , 1991, Annals of Internal Medicine.