Targeted vaccination and the speed of SARS-CoV-2 adaptation

Evolution of parasite transmission dispersion

An open question in epidemiology is why transmission is often overdispersed, meaning that most new infections are driven by few infected individuals. For example, around 10% of COVID-19 cases cause 80% of new COVID-19 cases. This overdispersion in parasite transmission is likely driven by intrinsic heterogeneity among hosts, i.e. variable SARS-CoV-2 viral loads. However, host heterogeneity could also indirectly increase transmission dispersion by driving parasite adaptation. Specifically, transmission variation among hosts could drive parasite specialization to highly infectious hosts. Adaptation to rare, highly infectious hosts could amplify transmission dispersion by simultaneously decreasing transmission from common, less infectious hosts. This study considers whether increased transmission dispersion can be, in part, an emergent property of parasite adaptation to heterogeneous host populations. We develop a mathematical model using a Price equation framework to address this question that follows the epidemiological and evolutionary dynamics of a general host-parasite system. The results predict that parasite adaptation to heterogeneous host populations drives high transmission dispersion early in epidemics. Furthermore, parasite adaptation can maintain increased transmission dispersion at endemic equilibria if virulence differs between hosts in a heterogeneous population. More broadly, this study provides a framework for predicting how parasite adaptation determines transmission dispersion for emerging and re-emerging infectious diseases.

Assessing marginal effects of non-pharmaceutical interventions on the transmission of SARS-CoV-2 across Africa: a hybrid modeling study

Since 2019, a new strain of coronavirus has challenged global health systems. Due its fragile healthcare systems, Africa was predicted to be the most affected continent. However, past experiences of African countries with epidemics and other factors, including actions taken by governments, have contributed to reducing the spread of SARS-CoV-2. This study aims to assess the marginal impact of non-pharmaceutical interventions in fifteen African countries during the pre-vaccination period. To describe the transmission dynamics and control of SARS-CoV-2 spread, an extended time-dependent SEIR model was used. The transmission rate of each infectious stage was obtained using a logistic model with NPI intensity as a covariate. The results revealed that the effects of NPIs varied between countries. Overall, restrictive measures related to assembly had, in most countries, the largest reducing effects on the pre-symptomatic and mild transmission, while the transmission by severe individuals is influenced by privacy measures (more than $10\%$). Countries should develop efficient alternatives to assembly restrictions to preserve the economic sector. This involves e.g. training in digital tools and strengthening digital infrastructures.

Prioritising older individuals for COVID-19 booster vaccination leads to optimal public health outcomes in a range of socio-economic settings

The rapid development of vaccines against SARS-CoV-2 altered the course of the COVID-19 pandemic. In most countries, vaccinations were initially targeted at high-risk populations, including older individuals and healthcare workers. Now, despite substantial infection- and vaccine-induced immunity in host populations worldwide, waning immunity and the emergence of novel variants continue to cause significant waves of infection and disease. Policy makers must determine how to deploy booster vaccinations, particularly when constraints in vaccine supply, delivery and cost mean that booster vaccines cannot be administered to everyone. A key question is therefore whether older individuals should again be prioritised for vaccination, or whether alternative strategies (e.g. offering booster vaccines to the individuals who have most contacts with others and therefore drive infection) can instead offer indirect protection to older individuals. Here, we use mathematical modelling to address this question, considering SARS-CoV-2 transmission in a range of countries with different socio-economic backgrounds. We show that the population structures of different countries can have a pronounced effect on the impact of booster vaccination, even when identical booster vaccination targeting strategies are adopted. However, under the assumed transmission model, prioritising older individuals for booster vaccination consistently leads to the most favourable public health outcomes in every setting considered. This remains true for a range of assumptions about booster vaccine supply and timing, and for different assumed policy objectives of booster vaccination.

Policy makers believe money motivates more than it does

To motivate contributions to public goods, should policy makers employ financial incentives like taxes, fines, subsidies, and rewards? While these are widely considered as the classic policy approach, a substantial academic literature suggests the impact of financial incentives is not always positive; they can sometimes fail or even backfire. To test whether policy makers are overly bullish about financial incentives, we asked county heads, mayors, and municipal government representatives of medium-to-large towns in Germany to predict the effects of a financial incentive on COVID-19 vaccination, and tested the exact same incentive in a field experiment involving all 41,548 inhabitants (clustered in 10,032 addresses) of the German town of Ravensburg. Whereas policy makers overwhelmingly predict that the financial incentive will increase vaccination-by 15.3 percentage points on average-the same financial incentive yielded a precisely estimated null effect on vaccination. We discuss when financial incentives are most likely to fail, and conclude that it is critical to educate policy makers on the potential pitfalls of employing financial incentives to promote contributions to public goods.

Utilizing river and wastewater as a SARS-CoV-2 surveillance tool in settings with limited formal sewage systems

The COVID-19 pandemic has profoundly impacted health systems globally and robust surveillance has been critical for pandemic control, however not all countries can currently sustain community pathogen surveillance programs. Wastewater surveillance has proven valuable in high-income settings, but less is known about the utility of water surveillance of pathogens in low-income countries. Here we show how wastewater surveillance of SAR-CoV-2 can be used to identify temporal changes and help determine circulating variants quickly. In Malawi, a country with limited community-based COVID-19 testing capacity, we explore the utility of rivers and wastewater for SARS-CoV-2 surveillance. From May 2020-May 2022, we collect water from up to 112 river or defunct wastewater treatment plant sites, detecting SARS-CoV-2 in 8.3% of samples. Peak SARS-CoV-2 detection in water samples predate peaks in clinical cases. Sequencing of water samples identified the Beta, Delta, and Omicron variants, with Delta and Omicron detected well in advance of detection in patients. Our work highlights how wastewater can be used to detect emerging waves, identify variants of concern, and provide an early warning system in settings with no formal sewage systems.

Vaccine hesitancy promotes emergence of new SARS-CoV-2 variants

The successive emergence of SARS-CoV-2 mutations has led to an unprecedented increase in COVID-19 incidence worldwide. Currently, vaccination is considered to be the best available solution to control the ongoing COVID-19 pandemic. However, public opposition to vaccination persists in many countries, which can lead to increased COVID-19 caseloads and hence greater opportunities for vaccine-evasive mutant strains to arise. To determine the extent that public opinion regarding vaccination can induce or hamper the emergence of new variants, we develop a model that couples a compartmental disease transmission framework featuring two strains of SARS-CoV-2 with game theoretical dynamics on whether or not to vaccinate. We combine semi-stochastic and deterministic simulations to explore the effect of mutation probability, perceived cost of receiving vaccines, and perceived risks of infection on the emergence and spread of mutant SARS-CoV-2 strains. We find that decreasing the perceived costs of being vaccinated and increasing the perceived risks of infection (that is, decreasing vaccine hesitation) will decrease the possibility of vaccine-resistant mutant strains becoming established by about fourfold for intermediate mutation rates. Conversely, we find increasing vaccine hesitation to cause both higher probability of mutant strains emerging and more wild-type cases after the mutant strain has appeared. We also find that once a new variant has emerged, perceived risk of being infected by the original variant plays a much larger role than perceptions of the new variant in determining future outbreak characteristics. Furthermore, we find that rapid vaccination under non-pharmaceutical interventions is a highly effective strategy for preventing new variant emergence, due to interaction effects between non-pharmaceutical interventions and public support for vaccination. Our findings indicate that policies that combine combating vaccine-related misinformation with non-pharmaceutical interventions (such as reducing social contact) will be the most effective for avoiding the establishment of harmful new variants.

Temporal, age, and geographical variation in vaccine efficacy against infection by the Delta and Omicron variants in the community in France, December 2021 to March 2022

OBJECTIVES

We aimed to quantify how the vaccine efficacy of BNT162b2, messenger RNA-1273, AD26.COV2-S, and ChAdOx1 nCoV-19 against detected infection by the SARS-CoV-2 Delta and Omicron variants varied by time since the last dose, vaccine scheme, age, and geographic areas.

METHODS

We analyzed 3,261,749 community polymerase chain reaction tests conducted by private laboratories in France from December 2021 to March 2022 with a test-negative design comparing vaccinated to unvaccinated individuals.

RESULTS

Efficacy against detected infection by Delta was 89% (95% confidence interval, 86-91%) at 2 weeks, down to 59% (56-61%) at 26 weeks and more after the second dose. Efficacy against Omicron was 48% (45-51%) at 2 weeks, down to 4% (2-5%) at 16 weeks after the second dose. A third dose temporarily restored efficacy. Efficacy against Omicron was lower in children and the elderly. Geographical variability in efficacy may reflect variability in the ratio of the number of contacts of vaccinated vs unvaccinated individuals. This ratio ranged from 0 to +50% across departments and correlated with the number of restaurants and bars per inhabitant (beta = 15.0 [0.75-29], P-value = 0.04), places that only vaccinated individuals could access in the study period.

CONCLUSION

SARS-CoV-2 vaccines conferred low and transient protection against Omicron infection.

Utilizing river and wastewater as a SARS-CoV-2 surveillance tool to predict trends and identify variants of concern in settings with limited formal sewage systems

The COVID-19 pandemic continues to impact health systems globally and robust surveillance is critical for pandemic control, however not all countries can sustain community surveillance programs. Wastewater surveillance has proven valuable in high-income settings, but little is known about how river and informal sewage in low-income countries can be used for environmental surveillance of SARS-CoV-2. In Malawi, a country with limited community-based COVID-19 testing capacity, we explored the utility of rivers and wastewater for SARS-CoV-2 surveillance. From May 2020 - January 2022, we collected water from up to 112 river or informal sewage sites/month, detecting SARS-CoV-2 in 8.3% of samples. Peak SARS-CoV-2 detection in water samples predated peaks in clinical cases. Sequencing of water samples identified the Beta, Delta, and Omicron variants, with Delta and Omicron detected well in advance of detection in patients. Our work highlights wastewater can be used for detecting emerging waves, identifying variants of concern and function as an early warning system in settings with no formal sewage systems.

Immune Response to Vaccination against COVID-19 at Different Second-Dose Intervals and Their Associations with Metabolic Parameters

Obesity and diabetes are associated with severe outcomes of coronavirus disease (COVID-19). Vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been proven protective against infection and severe COVID-19. However, the immune response of metabolically burdened individuals to the vaccines remains unclear. Thus, we aimed to assess whether the metabolic status of individuals affects their humoral immune responses to the vaccination. Moreover, we evaluated whether the interval between the first two doses influenced antibody concentration. Sixty-seven individuals (21 males, 46 females) were vaccinated with the BNT162b2 mRNA COVID-19 vaccine. Fifty-four individuals were vaccinated with the second dose after 3 weeks and 13 after 5 weeks. We measured the antibody titers in all participants during the 19-week follow-up period. Patients diagnosed with COVID-19 were excluded. In the 5-week interval group, a significantly higher level of maximal antibody titers was observed. However, there were no differences in antibody concentrations after 19 weeks and no significant correlation between cardiometabolic factors and humoral response. The elongation of second-dose timing to 5 weeks leads to a higher acute antibody response but does not change long-term levels of antibody titers. Moreover, dysregulation of metabolic parameters does not lead to a diminished immune response to vaccination.

Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support

This paper describes an integrated, data-driven operational pipeline based on national agent-based models to support federal and state-level pandemic planning and response. The pipeline consists of (i) an automatic semantic-aware scheduling method that coordinates jobs across two separate high performance computing systems; (ii) a data pipeline to collect, integrate and organize national and county-level disaggregated data for initialization and post-simulation analysis; (iii) a digital twin of national social contact networks made up of 288 Million individuals and 12.6 Billion time-varying interactions covering the US states and DC; (iv) an extension of a parallel agent-based simulation model to study epidemic dynamics and associated interventions. This pipeline can run 400 replicates of national runs in less than 33 h, and reduces the need for human intervention, resulting in faster turnaround times and higher reliability and accuracy of the results. Scientifically, the work has led to significant advances in real-time epidemic sciences.

Antigenic escape is accelerated by the presence of immunocompromised hosts

The repeated emergence of SARS-CoV-2 escape mutants from host immunity has obstructed the containment of the current pandemic and poses a serious threat to humanity. Prolonged infection in immunocompromised patients has received increasing attention as a driver of immune escape, and accumulating evidence suggests that viral genomic diversity and emergence of immune-escape mutants are promoted in immunocompromised patients. However, because immunocompromised patients comprise a small proportion of the host population, whether they have a significant impact on antigenic evolution at the population level is unknown. We consider an evolutionary epidemiological model that combines antigenic evolution and epidemiological dynamics. Applying this model to a heterogeneous host population, we study the impact of immunocompromised hosts on the evolutionary dynamics of pathogen antigenic escape from host immunity. We derived analytical formulae of the speed of antigenic evolution in heterogeneous host populations and found that even a small number of immunocompromised hosts in the population significantly accelerates antigenic evolution. Our results demonstrate that immunocompromised hosts play a key role in viral adaptation at the population level and emphasize the importance of critical care and surveillance of immunocompromised hosts.

Effects of epistasis and recombination between vaccine-escape and virulence alleles on the dynamics of pathogen adaptation

Pathogen adaptation to public health interventions such as vaccination may take tortuous routes and involve multiple mutations at different locations in the pathogen genome, acting on distinct phenotypic traits. Yet how these multi-locus adaptations jointly evolve is poorly understood. Here we consider the joint evolution of two adaptations: pathogen escape from the vaccine-induced immune response and adjustments to pathogen virulence affecting transmission or clearance. We elucidate the role played by epistasis and recombination, with an emphasis on the different protective effects of vaccination. We show that vaccines blocking infection, reducing transmission and/or increasing clearance generate positive epistasis between the vaccine-escape and virulence alleles, favouring strains that carry both mutations, whereas vaccines reducing virulence mortality generate negative epistasis, favouring strains that carry either mutation but not both. High rates of recombination can affect these predictions. If epistasis is positive, frequent recombination can prevent the transient build-up of more virulent escape strains. If epistasis is negative, frequent recombination between loci can create an evolutionary bistability, favouring whichever adaptation is more accessible. Our work provides a timely alternative to the variant-centred perspective on pathogen adaptation and captures the effect of different types of vaccine on the interference between multiple adaptive mutations.

Evolution of resistance to COVID-19 vaccination with dynamic social distancing

The greatest hope for a return to normalcy following the COVID-19 pandemic is worldwide vaccination. Yet, a relaxation of social distancing that allows increased transmissibility, coupled with selection pressure due to vaccination, will probably lead to the emergence of vaccine resistance. We analyse the evolutionary dynamics of COVID-19 in the presence of dynamic contact reduction and in response to vaccination. We use infection and vaccination data from six different countries. We show that under slow vaccination, resistance is very likely to appear even if social distancing is maintained. Under fast vaccination, the emergence of mutants can be prevented if social distancing is maintained during vaccination. We analyse multiple human factors that affect the evolutionary potential of the virus, including the extent of dynamic social distancing, vaccination campaigns, vaccine design, boosters and vaccine hesitancy. We provide guidelines for policies that aim to minimize the probability of emergence of vaccine-resistant variants.