The SARS-CoV-2 pandemic: remaining uncertainties in our understanding of the epidemiology and transmission dynamics of the virus, and challenges to be overcome

Great progress has been made over the past 18 months in scientific understanding of the biology, epidemiology and pathogenesis of SARS-CoV-2. Extraordinary advances have been made in vaccine development and the execution of clinical trials of possible therapies. However, uncertainties remain, and this review assesses these in the context of virus transmission, epidemiology, control by social distancing measures and mass vaccination and the effect on all of these on emerging variants. We briefly review the current state of the global pandemic, focussing on what is, and what is not, well understood about the parameters that control viral transmission and make up the constituent parts of the basic reproductive number R 0 . Major areas of uncertainty include factors predisposing to asymptomatic infection, the population fraction that is asymptomatic, the infectiousness of asymptomatic compared to symptomatic individuals, the contribution of viral transmission of such individuals and what variables influence this. The duration of immunity post infection and post vaccination is also currently unknown, as is the phenotypic consequences of continual viral evolution and the emergence of many viral variants not just in one location, but globally, given the high connectivity between populations in the modern world. The pattern of spread of new variants is also examined. We review what can be learnt from contact tracing, household studies and whole-genome sequencing, regarding where people acquire infection, and how households are seeded with infection since they constitute a major location for viral transmission. We conclude by discussing the challenges to attaining herd immunity, given the uncertainty in the duration of vaccine-mediated immunity, the threat of continued evolution of the virus as demonstrated by the emergence and rapid spread of the Delta variant, and the logistics of vaccine manufacturing and delivery to achieve universal coverage worldwide. Significantly more support from higher income countries (HIC) is required in low- and middle-income countries over the coming year to ensure the creation of community-wide protection by mass vaccination is a global target, not one just for HIC. Unvaccinated populations create opportunities for viral evolution since the net rate of evolution is directly proportional to the number of cases occurring per unit of time. The unit for assessing success in achieving herd immunity is not any individual country, but the world.

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Caveats on COVID-19 herd immunity threshold: the Spain case

Scientific Reports ◽

10.1038/s41598-021-04440-z ◽

2022 ◽

Vol 12 (1) ◽

Author(s):

David García-García ◽

Enrique Morales ◽

Eva S. Fonfría ◽

Isabel Vigo ◽

Cesar Bordehore

Keyword(s):

Upper Bound ◽

Generation Time ◽

Time Distribution ◽

Herd Immunity ◽

Late Summer ◽

Spanish Population ◽

Basic Reproductive Number ◽

Reproductive Number ◽

Population Estimates ◽

Parameter Measuring

AbstractAfter a year of living with the COVID-19 pandemic and its associated consequences, hope looms on the horizon thanks to vaccines. The question is what percentage of the population needs to be immune to reach herd immunity, that is to avoid future outbreaks. The answer depends on the basic reproductive number, R0, a key epidemiological parameter measuring the transmission capacity of a disease. In addition to the virus itself, R0 also depends on the characteristics of the population and their environment. Additionally, the estimate of R0 depends on the methodology used, the accuracy of data and the generation time distribution. This study aims to reflect on the difficulties surrounding R0 estimation, and provides Spain with a threshold for herd immunity, for which we considered the different combinations of all the factors that affect the R0 of the Spanish population. Estimates of R0 range from 1.39 to 3.10 for the ancestral SARS-CoV-2 variant, with the largest differences produced by the method chosen to estimate R0. With these values, the herd immunity threshold (HIT) ranges from 28.1 to 67.7%, which would have made 70% a realistic upper bound for Spain. However, the imposition of the delta variant (B.1.617.2 lineage) in late summer 2021 may have expanded the range of R0 to 4.02–8.96 and pushed the upper bound of the HIT to 90%.

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Epidemiology of the Zika virus outbreak in the Cabo Verde Islands, West Africa

10.1101/198952 ◽

2017 ◽

Author(s):

José Lourenço ◽

Maria de Lourdes Monteiro ◽

Tomás Valdez ◽

Júlio Monteiro Rodrigues ◽

Oliver G. Pybus ◽

...

Keyword(s):

West Africa ◽

Zika Virus ◽

Attack Rate ◽

Herd Immunity ◽

Basic Reproductive Number ◽

Reproductive Number ◽

Mathematical Framework ◽

Single Wave ◽

Cabo Verde ◽

Small Observation

AbstractIntroductionThe Zika virus (ZIKV) outbreak in the island nation of Cabo Verde was of unprecedented magnitude in Africa and the first to be associated with microcephaly in the continent.MethodsUsing a simple mathematical framework we present a first epidemiological assessment of attack and observation rates from 7,580 ZIKV notified cases and 18 microcephaly reports between July 2015 and May 2016.ResultsIn line with observations from the Americas and elsewhere, the single-wave Cabo Verdean ZIKV epidemic was characterized by a basic reproductive number of 1.85 (95% CI, 1.5 −2.2), with overall the attack rate of 51.1% (range 42.1 - 61.1) and observation rate of 2.7% (range 2.29 - 3.33).ConclusionCurrent herd-immunity may not be sufficient to prevent future small-to-medium epidemics in Cabo Verde. Together with a small observation rate, these results highlight the need for rapid and integrated epidemiological, molecular and genomic surveillance to tackle forthcoming outbreaks of ZIKV and other arboviruses.

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A stochastic epidemiological model to estimate the size of an outbreak at the first case identification

10.1101/2020.11.17.20233403 ◽

2020 ◽

Author(s):

Peter Czuppon ◽

François Blanquart ◽

Florence Débarre

Keyword(s):

Branching Processes ◽

Single Point ◽

Basic Reproductive Number ◽

Contact Tracing ◽

Upper And Lower Bounds ◽

Reproductive Number ◽

Related Case ◽

Epidemic Size ◽

First Case ◽

Over Time

AbstractThe identification of a first case (e.g. by a disease-related death or hospitalization event) raises the question of the actual size of a local outbreak. Quick estimates of the outbreak size are required to assess the necessary testing, contact tracing and potential containment effort. Using general branching processes and assuming that epidemic parameters (including the basic reproductive number) are constant over time, we characterize the distribution of the first hospitalization time and of the epidemic size at this random time. We find that previous estimates either overestimate or largely underestimate the actual epidemic size. In addition, we provide upper and lower bounds for the number of infectious individuals of the local outbreak over time. The upper bound is the cumulative epidemic size, and the lower bound is a constant fraction of it. Lastly, we compute the number of detectable cases if one were to test the whole local outbreak at a single point in time. In a growing epidemic, most individuals have been infected recently, which can strongly limit the detection of infected individuals when there is a delay between an infection and its potential detection. Overall, our analysis provides new analytical estimates about the epidemic size at identification of a first disease-related case. This piece of information is important to inform policy makers during the early stages of an epidemic outbreak.

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The basic reproductive number and particle-to-plaque ratio: comparison of these two parameters of viral infectivity

Virology Journal ◽

10.1186/s12985-021-01566-4 ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Winston McCormick ◽

Leonard A. Mermel

Keyword(s):

Viral Transmission ◽

Transmission Dynamics ◽

Basic Reproductive Number ◽

Reproductive Number ◽

Viral Infectivity ◽

Two Parameters

AbstractThe COVID-19 pandemic has brought more widespread attention to the basic reproductive number (Ro), an epidemiologic measurement. A lesser-known measure of virologic infectivity is the particle-to-plaque ratio (P:PFU). We suggest that comparison between the two parameters may assist in better understanding viral transmission dynamics.

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The Novel Coronavirus, 2019-nCoV, is Highly Contagious and More Infectious Than Initially Estimated

10.1101/2020.02.07.20021154 ◽

2020 ◽

Cited By ~ 61

Author(s):

Steven Sanche ◽

Yen Ting Lin ◽

Chonggang Xu ◽

Ethan Romero-Severson ◽

Nick Hengartner ◽

...

Keyword(s):

Case Reports ◽

Individual Case ◽

Control Measures ◽

Basic Reproductive Number ◽

Contact Tracing ◽

Reproductive Number ◽

The Novel ◽

Transmission Potential ◽

Novel Coronavirus ◽

Strong Control

AbstractThe novel coronavirus (2019-nCoV) is a recently emerged human pathogen that has spread widely since January 2020. Initially, the basic reproductive number, R0, was estimated to be 2.2 to 2.7. Here we provide a new estimate of this quantity. We collected extensive individual case reports and estimated key epidemiology parameters, including the incubation period. Integrating these estimates and high-resolution real-time human travel and infection data with mathematical models, we estimated that the number of infected individuals during early epidemic double every 2.4 days, and the R0 value is likely to be between 4.7 and 6.6. We further show that quarantine and contact tracing of symptomatic individuals alone may not be effective and early, strong control measures are needed to stop transmission of the virus.One-sentence summaryBy collecting and analyzing spatiotemporal data, we estimated the transmission potential for 2019-nCoV.

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Serological antibody testing in the COVID-19 pandemic: their molecular basis and applications

Biochemical Society Transactions ◽

10.1042/bst20200744 ◽

2020 ◽

Vol 48 (6) ◽

pp. 2851-2863

Author(s):

Jiayue-Clara Jiang ◽

Yan Zhang

Keyword(s):

Antibody Response ◽

Molecular Basis ◽

Molecular Mechanisms ◽

Vaccine Development ◽

Point Of Care ◽

Herd Immunity ◽

Contact Tracing ◽

Antibody Testing ◽

Serological Tests ◽

Molecular Tests

The ongoing COVID-19 pandemic has placed an overwhelming burden on the healthcare system, and caused major disruption to the world economy. COVID-19 is caused by SARS-CoV-2, a novel coronavirus that leads to a variety of symptoms in humans, including cough, fever and respiratory failure. SARS-CoV-2 infection can trigger extensive immune responses, including the production of antibodies. The detection of antibody response by serological testing provides a supplementary diagnostic tool to molecular tests. We hereby present a succinct yet comprehensive review on the antibody response to SARS-CoV-2 infection, as well as molecular mechanisms behind the strengths and limitations of serological antibody tests. The presence of antibodies can be detected in patient sera within days post symptom onset. Serological tests demonstrate superior sensitivity to molecular tests in some periods of time during disease development. Compared with the molecular tests, serological tests can be used for point-of-care testing, providing faster results at a lower cost. Commercially available serological tests show variable sensitivity and specificity, and the molecular basis of these variabilities are analysed. We discuss assays of different complexities that are used to specifically quantitate neutralising antibodies against SARS-CoV-2, which has important implications for vaccine development and herd immunity. Furthermore, we discuss examples of successful applications of serological tests to contact tracing and community-level sero-surveying, which provide invaluable information for pandemic management and assessment.

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Implications of Test Characteristics and Population Seroprevalence on “Immune Passport” Strategies

Clinical Infectious Diseases ◽

10.1093/cid/ciaa1019 ◽

2020 ◽

Cited By ~ 7

Author(s):

Daniel B Larremore ◽

Kate M Bubar ◽

Yonatan H Grad

Keyword(s):

False Positive ◽

Herd Immunity ◽

Basic Reproductive Number ◽

Reproductive Number ◽

Serological Tests ◽

Test Characteristics ◽

Simple Question ◽

Minimum Requirements ◽

Test Specificity ◽

Repeat Infection

Abstract Various forms of “immune passports” or “antibody certificates” are being considered in conversations around reopening economies after periods of social distancing. A critique of such programs focuses on the uncertainty around whether seropositivity means immunity from repeat infection. However, an additional important consideration is that the low positive predictive value of serological tests in the setting of low population seroprevalence and imperfect test specificity will lead to many false-positive passport holders. Here, we pose a simple question: how many false-positive passports could be issued while maintaining herd immunity in the workforce? Answering this question leads to a simple mathematical formula for the minimum requirements of serological tests for a passport program, which depend on the population prevalence and the value of the basic reproductive number, R0. Our work replaces speculation in the press with rigorous analysis, and will need to be considered in policy decisions that are based on individual and population serology results.

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Modelling the Transmission Dynamics of Tuberculosis in the Ashanti Region of Ghana

Interdisciplinary Perspectives on Infectious Diseases ◽

10.1155/2020/4513854 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16

Author(s):

Felix Okoe Mettle ◽

Prince Osei Affi ◽

Clement Twumasi

Keyword(s):

Deterministic Model ◽

Equilibrium Points ◽

Herd Immunity ◽

Transmission Dynamics ◽

Basic Reproductive Number ◽

Reproductive Number ◽

Seir Model ◽

High Burden ◽

Ashanti Region ◽

Over Time

Mathematical models can aid in elucidating the spread of infectious disease dynamics within a given population over time. In an attempt to model tuberculosis (TB) dynamics among high-burden districts in the Ashanti Region of Ghana, the SEIR epidemic model with demography was employed within both deterministic and stochastic settings for comparison purposes. The deterministic model showed success in modelling TB infection in the region to the transmission dynamics of the stochastic SEIR model over time. It predicted tuberculosis dying out in ten of twelve high-burden districts in the Ashanti Region, but an outbreak in Obuasi municipal and Amansie West district. The effect of introducing treatment at the incubation stage of TB transmission was also investigated, and it was discovered that treatment introduced at the exposed stage decreased the spread of TB. Branching process approximation was used to derive explicit forms of relevant epidemiological quantities of the deterministic SEIR model for stability analysis of equilibrium points. Numerical simulations were performed to validate the overall infection rate, basic reproductive number, herd immunity threshold, and Malthusian parameter based on bootstrapping, jackknife, and Latin Hypercube sampling schemes. It was recommended that the Ghana Health Service should find a good mechanism to detect TB in the early stages of infection in the region. Public health attention must also be given to districts with a potentially higher risk of experiencing endemic TB even though the estimates of the overall epidemic thresholds from our SEIR model suggested that the Ashanti Region as a whole had herd immunity against TB infection.

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Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA

Scientific Reports ◽

10.1038/s41598-021-83722-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Sifat A. Moon ◽

Caterina M. Scoglio

Keyword(s):

Basic Reproductive Number ◽

Contact Tracing ◽

Reproductive Number ◽

Contact Network ◽

Model Parameters ◽

Maximum Point ◽

College Town ◽

Interesting Phenomenon ◽

The Usa ◽

Rural College

AbstractContact tracing can play a key role in controlling human-to-human transmission of a highly contagious disease such as COVID-19. We investigate the benefits and costs of contact tracing in the COVID-19 transmission. We estimate two unknown epidemic model parameters (basic reproductive number $$R_0$$ R 0 and confirmed rate $$\delta _2$$ δ 2 ) by using confirmed case data. We model contact tracing in a two-layer network model. The two-layer network is composed by the contact network in the first layer and the tracing network in the second layer. In terms of benefits, simulation results show that increasing the fraction of traced contacts decreases the size of the epidemic. For example, tracing $$25\%$$ 25 % of the contacts is enough for any reopening scenario to reduce the number of confirmed cases by half. Considering the act of quarantining susceptible households as the contact tracing cost, we have observed an interesting phenomenon. The number of quarantined susceptible people increases with the increase of tracing because each individual confirmed case is mentioning more contacts. However, after reaching a maximum point, the number of quarantined susceptible people starts to decrease with the increase of tracing because the increment of the mentioned contacts is balanced by a reduced number of confirmed cases. The goal of this research is to assess the effectiveness of contact tracing for the containment of COVID-19 spreading in the different movement levels of a rural college town in the USA. Our research model is designed to be flexible and therefore, can be used to other geographic locations.

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Estimating the reproductive number R0 of SARS-CoV-2 in the United States and eight European countries and implications for vaccination

10.1101/2020.07.31.20166298 ◽

2020 ◽

Cited By ~ 2

Author(s):

Ruian Ke ◽

Ethan Obie Romero-Severson ◽

Steven Sanche ◽

Nick Hengartner

Keyword(s):

United States ◽

Herd Immunity ◽

The United States ◽

Control Measures ◽

European Countries ◽

Basic Reproductive Number ◽

Reproductive Number ◽

Individual Level ◽

Epidemic Period ◽

Induced Immunity

SARS-CoV-2 rapidly spread from a regional outbreak to a global pandemic in just a few months. Global research efforts have focused on developing effective vaccines against SARS-CoV-2 and the disease it causes, COVID-19. However, some of the basic epidemiological parameters, such as the exponential epidemic growth rate and the basic reproductive number, R0, across geographic areas are still not well quantified. Here, we developed and fit a mathematical model to case and death count data collected from the United States and eight European countries during the early epidemic period before broad control measures were implemented. Results show that the early epidemic grew exponentially at rates between 0.19-0.29/day (epidemic doubling times between 2.4-3.6 days). We discuss the current estimates of the mean serial interval, and argue that existing evidence suggests that the interval is between 6-8 days in the absence of active isolation efforts. Using parameters consistent with this range, we estimated the median R0 value to be 5.8 (confidence interval: 4.7-7.3) in the United States and between 3.6 and 6.1 in the eight European countries. This translates to herd immunity thresholds needed to stop transmission to be between 73% and 84%. We further analyze how vaccination schedules depends on R0, the duration of vaccine-induced immunity to SARS-CoV-2, and show that individual-level heterogeneity in vaccine induced immunity can significantly affect vaccination schedules.

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