Publications by authors named "Bryan T Grenfell"

183 Publications

Vaccine nationalism and the dynamics and control of SARS-CoV-2.

Science 2021 Sep 24;373(6562):eabj7364. Epub 2021 Sep 24.

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08540, USA.

[Figure: see text].
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http://dx.doi.org/10.1126/science.abj7364DOI Listing
September 2021

Trip duration drives shift in travel network structure with implications for the predictability of spatial disease spread.

PLoS Comput Biol 2021 Aug 10;17(8):e1009127. Epub 2021 Aug 10.

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.

Human travel is one of the primary drivers of infectious disease spread. Models of travel are often used that assume the amount of travel to a specific destination decreases as cost of travel increases with higher travel volumes to more populated destinations. Trip duration, the length of time spent in a destination, can also impact travel patterns. We investigated the spatial patterns of travel conditioned on trip duration and find distinct differences between short and long duration trips. In short-trip duration travel networks, trips are skewed towards urban destinations, compared with long-trip duration networks where travel is more evenly spread among locations. Using gravity models to inform connectivity patterns in simulations of disease transmission, we show that pathogens with shorter generation times exhibit initial patterns of spatial propagation that are more predictable among urban locations. Further, pathogens with a longer generation time have more diffusive patterns of spatial spread reflecting more unpredictable disease dynamics.
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http://dx.doi.org/10.1371/journal.pcbi.1009127DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378725PMC
August 2021

Why are there so few (or so many) circulating coronaviruses?

Trends Immunol 2021 09 12;42(9):751-763. Epub 2021 Jul 12.

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA; Princeton School of Public and International Affairs, Princeton University, Princeton, NJ, USA.

Despite vast diversity in non-human hosts and conspicuous recent spillover events, only a small number of coronaviruses have been observed to persist in human populations. This puzzling mismatch suggests substantial barriers to establishment. We detail hypotheses that might contribute to explain the low numbers of endemic coronaviruses, despite their considerable evolutionary and emergence potential. We assess possible explanations ranging from issues of ascertainment, historically lower opportunities for spillover, aspects of human demographic changes, and features of pathogen biology and pre-existing adaptive immunity to related viruses. We describe how successful emergent viral species must triangulate transmission, virulence, and host immunity to maintain circulation. Characterizing the factors that might shape the limits of viral persistence can delineate promising research directions to better understand the combinations of pathogens and contexts that are most likely to lead to spillover.
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http://dx.doi.org/10.1016/j.it.2021.07.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8272969PMC
September 2021

Evolution of an asymptomatic first stage of infection in a heterogeneous population.

J R Soc Interface 2021 06 16;18(179):20210175. Epub 2021 Jun 16.

Department of Molecular Biology, Princeton University, Princeton, NJ, USA.

Pathogens evolve different life-history strategies, which depend in part on differences in their host populations. A central feature of hosts is their population structure (e.g. spatial). Additionally, hosts themselves can exhibit different degrees of symptoms when newly infected; this latency is a key life-history property of pathogens. With an evolutionary-epidemiological model, we examine the role of population structure on the evolutionary dynamics of latency. We focus on specific power-law-like formulations for transmission and progression from the first infectious stage as a function of latency, assuming that the across-group to within-group transmission ratio increases if hosts are less symptomatic. We find that simple population heterogeneity can lead to local evolutionarily stable strategies (ESSs) at zero and infinite latency in situations where a unique ESS exists in the corresponding homogeneous case. Furthermore, there can exist more than one interior evolutionarily singular strategy. We find that this diversity of outcomes is due to the (possibly slight) advantage of across-group transmission for pathogens that produce fewer symptoms in a first infectious stage. Thus, our work reveals that allowing individuals without symptoms to travel can have important unintended evolutionary effects and is thus fundamentally problematic in view of the evolutionary dynamics of latency.
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http://dx.doi.org/10.1098/rsif.2021.0175DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8205539PMC
June 2021

Epidemiological dynamics of enterovirus D68 in the United States and implications for acute flaccid myelitis.

Sci Transl Med 2021 03;13(584)

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08540, USA.

Acute flaccid myelitis (AFM) recently emerged in the United States as a rare but serious neurological condition since 2012. Enterovirus D68 (EV-D68) is thought to be a main causative agent, but limited surveillance of EV-D68 in the United States has hampered the ability to assess their causal relationship. Using surveillance data from the BioFire Syndromic Trends epidemiology network in the United States from January 2014 to September 2019, we characterized the epidemiological dynamics of EV-D68 and found latitudinal gradient in the mean timing of EV-D68 cases, which are likely climate driven. We also demonstrated a strong spatiotemporal association of EV-D68 with AFM. Mathematical modeling suggested that the recent dominant biennial cycles of EV-D68 dynamics may not be stable. Nonetheless, we predicted that a major EV-D68 outbreak, and hence an AFM outbreak, would have still been possible in 2020 under normal epidemiological conditions. Nonpharmaceutical intervention efforts due to the ongoing COVID-19 pandemic are likely to have reduced the sizes of EV-D68 and AFM outbreaks in 2020, illustrating the broader epidemiological impact of the pandemic.
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http://dx.doi.org/10.1126/scitranslmed.abd2400DOI Listing
March 2021

Epidemiological and evolutionary considerations of SARS-CoV-2 vaccine dosing regimes.

Science 2021 04 9;372(6540):363-370. Epub 2021 Mar 9.

Department of Bioengineering, McGill University, Montreal, QC H3A 0C3, Canada.

Given vaccine dose shortages and logistical challenges, various deployment strategies are being proposed to increase population immunity levels to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Two critical issues arise: How timing of delivery of the second dose will affect infection dynamics and how it will affect prospects for the evolution of viral immune escape via a buildup of partially immune individuals. Both hinge on the robustness of the immune response elicited by a single dose as compared with natural and two-dose immunity. Building on an existing immuno-epidemiological model, we find that in the short term, focusing on one dose generally decreases infections, but that longer-term outcomes depend on this relative immune robustness. We then explore three scenarios of selection and find that a one-dose policy may increase the potential for antigenic evolution under certain conditions of partial population immunity. We highlight the critical need to test viral loads and quantify immune responses after one vaccine dose and to ramp up vaccination efforts globally.
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http://dx.doi.org/10.1126/science.abg8663DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8128287PMC
April 2021

Superinfection and the evolution of an initial asymptomatic stage.

R Soc Open Sci 2021 Jan 27;8(1):202212. Epub 2021 Jan 27.

Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.

Pathogens have evolved a variety of life-history strategies. An important strategy consists of successful transmission by an infected host before the appearance of symptoms, that is, while the host is still partially or fully asymptomatic. During this initial stage of infection, it is possible for another pathogen to superinfect an already infected host and replace the previously infecting pathogen. Here, we study the effect of superinfection during the first stage of an infection on the evolutionary dynamics of the degree to which the host is asymptomatic (host latency) in that same stage. We find that superinfection can lead to major differences in evolutionary behaviour. Most strikingly, the duration of immunity following infection can significantly influence pathogen evolutionary dynamics, whereas without superinfection the outcomes are independent of host immunity. For example, changes in host immunity can drive evolutionary transitions from a fully symptomatic to a fully asymptomatic first infection stage. Additionally, if superinfection relative to susceptible infection is strong enough, evolution can lead to a unique strategy of latency that corresponds to a local fitness minimum, and is therefore invasible by nearby mutants. Thus, this strategy is a branching point, and can lead to coexistence of pathogens with different latencies. Furthermore, in this new framework with superinfection, we also find that there can exist two interior singular strategies. Overall, new evolutionary outcomes can cascade from superinfection.
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http://dx.doi.org/10.1098/rsos.202212DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890506PMC
January 2021

Epidemiological and evolutionary considerations of SARS-CoV-2 vaccine dosing regimes.

medRxiv 2021 Feb 3. Epub 2021 Feb 3.

Department of Bioengineering, McGill University, Montreal QC H3A 0C3, Canada.

As the threat of Covid-19 continues and in the face of vaccine dose shortages and logistical challenges, various deployment strategies are being proposed to increase population immunity levels. How timing of delivery of the second dose affects infection burden but also prospects for the evolution of viral immune escape are critical questions. Both hinge on the strength and duration (i.e. robustness) of the immune response elicited by a single dose, compared to natural and two-dose immunity. Building on an existing immuno-epidemiological model, we find that in the short-term, focusing on one dose generally decreases infections, but longer-term outcomes depend on this relative immune robustness. We then explore three scenarios of selection, evaluating how different second dose delays might drive immune escape via a build-up of partially immune individuals. Under certain scenarios, we find that a one-dose policy may increase the potential for antigenic evolution. We highlight the critical need to test viral loads and quantify immune responses after one vaccine dose, and to ramp up vaccination efforts throughout the world.
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http://dx.doi.org/10.1101/2021.02.01.21250944DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7872380PMC
February 2021

Assessing the influence of climate on wintertime SARS-CoV-2 outbreaks.

Nat Commun 2021 02 8;12(1):846. Epub 2021 Feb 8.

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.

High susceptibility has limited the role of climate in the SARS-CoV-2 pandemic to date. However, understanding a possible future effect of climate, as susceptibility declines and the northern-hemisphere winter approaches, is an important open question. Here we use an epidemiological model, constrained by observations, to assess the sensitivity of future SARS-CoV-2 disease trajectories to local climate conditions. We find this sensitivity depends on both the susceptibility of the population and the efficacy of non-pharmaceutical interventions (NPIs) in reducing transmission. Assuming high susceptibility, more stringent NPIs may be required to minimize outbreak risk in the winter months. Our results suggest that the strength of NPIs remain the greatest determinant of future pre-vaccination outbreak size. While we find a small role for meteorological forecasts in projecting outbreak severity, reducing uncertainty in epidemiological parameters will likely have a more substantial impact on generating accurate predictions.
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http://dx.doi.org/10.1038/s41467-021-20991-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7870658PMC
February 2021

Variation in SARS-CoV-2 outbreaks across sub-Saharan Africa.

Nat Med 2021 03 2;27(3):447-453. Epub 2021 Feb 2.

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.

A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (for example, warmer environments, younger populations) have yet to be framed within a comprehensive analysis. We synthesized factors hypothesized to drive the pace and burden of this pandemic in SSA during the period from 25 February to 20 December 2020, encompassing demographic, comorbidity, climatic, healthcare capacity, intervention efforts and human mobility dimensions. Large diversity in the probable drivers indicates a need for caution in interpreting analyses that aggregate data across low- and middle-income settings. Our simulation shows that climatic variation between SSA population centers has little effect on early outbreak trajectories; however, heterogeneity in connectivity, although rarely considered, is likely an important contributor to variance in the pace of viral spread across SSA. Our synthesis points to the potential benefits of context-specific adaptation of surveillance systems during the ongoing pandemic. In particular, characterizing patterns of severity over age will be a priority in settings with high comorbidity burdens and poor access to care. Understanding the spatial extent of outbreaks warrants emphasis in settings where low connectivity could drive prolonged, asynchronous outbreaks resulting in extended stress to health systems.
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http://dx.doi.org/10.1038/s41591-021-01234-8DOI Listing
March 2021

Trajectory of individual immunity and vaccination required for SARS-CoV-2 community immunity: a conceptual investigation.

J R Soc Interface 2021 02 3;18(175):20200683. Epub 2021 Feb 3.

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.

SARS-CoV-2 is an international public health emergency; high transmissibility and morbidity and mortality can result in the virus overwhelming health systems. Combinations of social distancing, and test, trace, and isolate strategies can reduce the number of new infections per infected individual below 1, thus driving declines in case numbers, but may be both challenging and costly. These interventions must also be maintained until development and (now likely) mass deployment of a vaccine (or therapeutics), since otherwise, many susceptible individuals are still at risk of infection. We use a simple analytical model to explore how low levels of infection, combined with vaccination, determine the trajectory to community immunity. Understanding the repercussions of the biological characteristics of the viral life cycle in this scenario is of considerable importance. We provide a simple description of this process by modelling the scenario where the effective reproduction number [Formula: see text] is maintained at 1. Since the additional complexity imposed by the strength and duration of transmission-blocking immunity is not yet clear, we use our framework to probe the impact of these uncertainties. Through intuitive analytical relations, we explore how the necessary magnitude of vaccination rates and mitigation efforts depends crucially on the durations of natural and vaccinal immunity. We also show that our framework can encompass seasonality or preexisting immunity due to epidemic dynamics prior to strong mitigation measures. Taken together, our simple conceptual model illustrates the importance of individual and vaccinal immunity for community immunity, and that the quantification of individuals immunized against SARS-CoV-2 is paramount.
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http://dx.doi.org/10.1098/rsif.2020.0683DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086877PMC
February 2021

Economic and Behavioral Influencers of Vaccination and Antimicrobial Use.

Front Public Health 2020 21;8:614113. Epub 2020 Dec 21.

Princeton Environmental Institute, Princeton University, Princeton, NJ, United States.

Despite vast improvements in global vaccination coverage during the last decade, there is a growing trend in vaccine hesitancy and/or refusal globally. This has implications for the acceptance and coverage of a potential vaccine against COVID-19. In the United States, the number of children exempt from vaccination for "philosophical belief-based" non-medical reasons increased in 12 of the 18 states that allowed this policy from 2009 to 2017 (1). Meanwhile, the overuse and misuse of antibiotics, especially in young children, have led to increasing rates of drug resistance that threaten our ability to treat infectious diseases. Vaccine hesitancy and antibiotic overuse exist side-by-side in the same population of young children, and it is unclear why one modality (antibiotics) is universally seen as safe and effective, while the other (vaccines) is seen as potentially hazardous by some. In this review, we consider the drivers shaping the use of vaccines and antibiotics in the context of three factors: individual incentives, risk perceptions, and social norms and group dynamics. We illustrate how these factors contribute to the societal and individual costs of vaccine underuse and antimicrobial overuse. Ultimately, we seek to understand these factors that are at the nexus of infectious disease epidemiology and social science to inform policy-making.
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http://dx.doi.org/10.3389/fpubh.2020.614113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779682PMC
January 2021

Tensor decomposition for infectious disease incidence data.

Methods Ecol Evol 2020 Dec 22;11(12):1690-1700. Epub 2020 Sep 22.

Office of Population Research Princeton University Princeton NY USA.

Many demographic and ecological processes generate seasonal and other periodicities. Seasonality in infectious disease transmission can result from climatic forces such as temperature and humidity; variation in contact rates as a result of migration or school calendar; or temporary surges in birth rates. Seasonal drivers of acute immunizing infections can also drive longer-term fluctuations.Tensor decomposition has been used in many disciplines to uncover dominant trends in multi-dimensional data. We introduce tensors as a novel method for decomposing oscillatory infectious disease time series.We illustrate the reliability of the method by applying it to simulated data. We then present decompositions of measles data from England and Wales. This paper leverages simulations as well as much-studied data to illustrate the power of tensor decomposition to uncover dominant epidemic signals as well as variation in space and time. We then use tensor decomposition to uncover new findings and demonstrate the potential power of the method for disease incidence data. In particular, we are able to distinguish between annual and biennial signals across locations and shifts in these signals over time.Tensor decomposition is able to isolate variation in disease seasonality as a result of variation in demographic rates. The method allows us to discern variation in the strength of such signals by space and population size. Tensors provide an opportunity for a concise approach to uncovering heterogeneity in disease transmission across space and time in large datasets.
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http://dx.doi.org/10.1111/2041-210X.13480DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7756762PMC
December 2020

Forward-looking serial intervals correctly link epidemic growth to reproduction numbers.

Proc Natl Acad Sci U S A 2021 01;118(2)

Department of Biology, McMaster University, Hamilton, ON L8S 4L8, Canada.

The reproduction number R and the growth rate r are critical epidemiological quantities. They are linked by generation intervals, the time between infection and onward transmission. Because generation intervals are difficult to observe, epidemiologists often substitute serial intervals, the time between symptom onset in successive links in a transmission chain. Recent studies suggest that such substitution biases estimates of R based on r. Here we explore how these intervals vary over the course of an epidemic, and the implications for R estimation. Forward-looking serial intervals, measuring time forward from symptom onset of an infector, correctly describe the renewal process of symptomatic cases and therefore reliably link R with r. In contrast, backward-looking intervals, which measure time backward, and intrinsic intervals, which neglect population-level dynamics, give incorrect R estimates. Forward-looking intervals are affected both by epidemic dynamics and by censoring, changing in complex ways over the course of an epidemic. We present a heuristic method for addressing biases that arise from neglecting changes in serial intervals. We apply the method to early (21 January to February 8, 2020) serial interval-based estimates of R for the COVID-19 outbreak in China outside Hubei province; using improperly defined serial intervals in this context biases estimates of initial R by up to a factor of 2.6. This study demonstrates the importance of early contact tracing efforts and provides a framework for reassessing generation intervals, serial intervals, and R estimates for COVID-19.
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http://dx.doi.org/10.1073/pnas.2011548118DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812760PMC
January 2021

Disentangling the dynamical underpinnings of differences in SARS-CoV-2 pathology using within-host ecological models.

PLoS Pathog 2020 12 11;16(12):e1009105. Epub 2020 Dec 11.

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America.

Health outcomes following infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) are remarkably variable. The way the virus spreads inside hosts, and how this spread interacts with host immunity and physiology, is likely to determine variation in health outcomes. Decades of data and dynamical analyses of how other viruses spread and interact with host cells could shed light on SARS-CoV-2 within-host trajectories. We review how common axes of variation in within-host dynamics and emergent pathology (such as age and sex) might be combined with ecological principles to understand the case of SARS-CoV-2. We highlight pitfalls in application of existing theoretical frameworks relevant to the complexity of the within-host context and frame the discussion in terms of growing knowledge of the biology of SARS-CoV-2. Viewing health outcomes for SARS-CoV-2 through the lens of ecological models underscores the value of repeated measures on individuals, especially since many lines of evidence suggest important contingence on trajectory.
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http://dx.doi.org/10.1371/journal.ppat.1009105DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732095PMC
December 2020

Asynchrony between virus diversity and antibody selection limits influenza virus evolution.

Elife 2020 11 11;9. Epub 2020 Nov 11.

Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands.

Seasonal influenza viruses create a persistent global disease burden by evolving to escape immunity induced by prior infections and vaccinations. New antigenic variants have a substantial selective advantage at the population level, but these variants are rarely selected within-host, even in previously immune individuals. Using a mathematical model, we show that the temporal asynchrony between within-host virus exponential growth and antibody-mediated selection could limit within-host antigenic evolution. If selection for new antigenic variants acts principally at the point of initial virus inoculation, where small virus populations encounter well-matched mucosal antibodies in previously-infected individuals, there can exist protection against reinfection that does not regularly produce observable new antigenic variants within individual infected hosts. Our results provide a theoretical explanation for how virus antigenic evolution can be highly selective at the global level but nearly neutral within-host. They also suggest new avenues for improving influenza control.
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http://dx.doi.org/10.7554/eLife.62105DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7748417PMC
November 2020

The impact of COVID-19 nonpharmaceutical interventions on the future dynamics of endemic infections.

Proc Natl Acad Sci U S A 2020 12 9;117(48):30547-30553. Epub 2020 Nov 9.

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544.

Nonpharmaceutical interventions (NPIs) have been employed to reduce the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), yet these measures are already having similar effects on other directly transmitted, endemic diseases. Disruptions to the seasonal transmission patterns of these diseases may have consequences for the timing and severity of future outbreaks. Here we consider the implications of SARS-CoV-2 NPIs for two endemic infections circulating in the United States of America: respiratory syncytial virus (RSV) and seasonal influenza. Using laboratory surveillance data from 2020, we estimate that RSV transmission declined by at least 20% in the United States at the start of the NPI period. We simulate future trajectories of both RSV and influenza, using an epidemic model. As susceptibility increases over the NPI period, we find that substantial outbreaks of RSV may occur in future years, with peak outbreaks likely occurring in the winter of 2021-2022. Longer NPIs, in general, lead to larger future outbreaks although they may display complex interactions with baseline seasonality. Results for influenza broadly echo this picture, but are more uncertain; future outbreaks are likely dependent on the transmissibility and evolutionary dynamics of circulating strains.
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http://dx.doi.org/10.1073/pnas.2013182117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720203PMC
December 2020

Cyclic epidemics and extreme outbreaks induced by hydro-climatic variability and memory.

J R Soc Interface 2020 10 21;17(171):20200521. Epub 2020 Oct 21.

CEE and PEI, Princeton University, Princeton, NJ, USA.

A minimalist model of ecohydrologic dynamics is coupled to the well-known susceptible-infected-recovered epidemiological model to explore hydro-climatic controls on infection dynamics and extreme outbreaks. The resulting HYSIR model reveals the existence of a noise-induced bifurcation producing oscillations in infection dynamics. Linearization of the governing equations allows for an analytic expression for the periodicity of infections in terms of both epidemiological (e.g. transmission and recovery rate) and hydrologic (i.e. soil moisture decay rate or memory) parameters. Numerical simulations of the full stochastic, nonlinear system show extreme outbreaks in response to particular combinations of hydro-climatic conditions, neither of which is extreme , rather than a single major climatic event. These combinations depend on the assumed functional relationship between the hydrologic variables and the transmission rate. Our results emphasize the importance of hydro-climatic history and system memory in evaluating the risk of severe outbreaks.
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http://dx.doi.org/10.1098/rsif.2020.0521DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653386PMC
October 2020

The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology.

Nat Commun 2020 09 30;11(1):4961. Epub 2020 Sep 30.

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

The ongoing coronavirus disease 2019 (COVID-19) pandemic has heightened discussion of the use of mobile phone data in outbreak response. Mobile phone data have been proposed to monitor effectiveness of non-pharmaceutical interventions, to assess potential drivers of spatiotemporal spread, and to support contact tracing efforts. While these data may be an important part of COVID-19 response, their use must be considered alongside a careful understanding of the behaviors and populations they capture. Here, we review the different applications for mobile phone data in guiding and evaluating COVID-19 response, the relevance of these applications for infectious disease transmission and control, and potential sources and implications of selection bias in mobile phone data. We also discuss best practices and potential pitfalls for directly integrating the collection, analysis, and interpretation of these data into public health decision making.
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http://dx.doi.org/10.1038/s41467-020-18190-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528106PMC
September 2020

Immune life history, vaccination, and the dynamics of SARS-CoV-2 over the next 5 years.

Science 2020 11 21;370(6518):811-818. Epub 2020 Sep 21.

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.

The future trajectory of the coronavirus disease 2019 (COVID-19) pandemic hinges on the dynamics of adaptive immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); however, salient features of the immune response elicited by natural infection or vaccination are still uncertain. We use simple epidemiological models to explore estimates for the magnitude and timing of future COVID-19 cases, given different assumptions regarding the protective efficacy and duration of the adaptive immune response to SARS-CoV-2, as well as its interaction with vaccines and nonpharmaceutical interventions. We find that variations in the immune response to primary SARS-CoV-2 infections and a potential vaccine can lead to markedly different immune landscapes and burdens of critically severe cases, ranging from sustained epidemics to near elimination. Our findings illustrate likely complexities in future COVID-19 dynamics and highlight the importance of immunological characterization beyond the measurement of active infections for adequately projecting the immune landscape generated by SARS-CoV-2 infections.
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http://dx.doi.org/10.1126/science.abd7343DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857410PMC
November 2020

Potential Role of Social Distancing in Mitigating Spread of Coronavirus Disease, South Korea.

Emerg Infect Dis 2020 Nov 14;26(11):2697-2700. Epub 2020 Aug 14.

In South Korea, the coronavirus disease outbreak peaked at the end of February and subsided in mid-March. We analyzed the likely roles of social distancing in reducing transmission. Our analysis indicated that although transmission might persist in some regions, epidemics can be suppressed with less extreme measures than those taken by China.
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http://dx.doi.org/10.3201/eid2611.201099DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588540PMC
November 2020

Epidemiological dynamics of enterovirus D68 in the US: implications for acute flaccid myelitis.

medRxiv 2021 Jan 28. Epub 2021 Jan 28.

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08540, USA.

The lack of active surveillance for enterovirus D68 (EV-D68) in the US has hampered the ability to assess the relationship with predominantly biennial epidemics of acute flaccid myelitis (AFM), a rare but serious neurological condition. Using novel surveillance data from the BioFire Syndromic Trends (Trend) epidemiology network, we characterize the epidemiological dynamics of EV-D68 and demonstrate strong spatiotemporal association with AFM. Although the recent dominant biennial cycles of EV-D68 dynamics may not be stable, we show that a major EV-D68 epidemic, and hence an AFM outbreak, would still be possible in 2020 under normal epidemiological conditions. Significant social distancing due to the ongoing COVID-19 pandemic could reduce the size of an EV-D68 epidemic in 2020, illustrating the potential broader epidemiological impact of the pandemic.
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http://dx.doi.org/10.1101/2020.07.23.20069468DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7402064PMC
January 2021

High variation expected in the pace and burden of SARS-CoV-2 outbreaks across sub-Saharan Africa.

medRxiv 2020 Jul 29. Epub 2020 Jul 29.

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.

A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (e.g., warmer environments, younger populations) have yet to be framed within a comprehensive analysis accounting for factors that may offset the effects of climate and demography. Here, we synthesize factors hypothesized to shape the pace of this pandemic and its burden as it moves across SSA, encompassing demographic, comorbidity, climatic, healthcare and intervention capacity, and human mobility dimensions of risk. We find large scale diversity in probable drivers, such that outcomes are likely to be highly variable among SSA countries. While simulation shows that extensive climatic variation among SSA population centers has little effect on early outbreak trajectories, heterogeneity in connectivity is likely to play a large role in shaping the pace of viral spread. The prolonged, asynchronous outbreaks expected in weakly connected settings may result in extended stress to health systems. In addition, the observed variability in comorbidities and access to care will likely modulate the severity of infection: We show that even small shifts in the infection fatality ratio towards younger ages, which are likely in high risk settings, can eliminate the protective effect of younger populations. We highlight countries with elevated risk of 'slow pace', high burden outbreaks. Empirical data on the spatial extent of outbreaks within SSA countries, their patterns in severity over age, and the relationship between epidemic pace and health system disruptions are urgently needed to guide efforts to mitigate the high burden scenarios explored here.
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http://dx.doi.org/10.1101/2020.07.23.20161208DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7386522PMC
July 2020

Reconciling early-outbreak estimates of the basic reproductive number and its uncertainty: framework and applications to the novel coronavirus (SARS-CoV-2) outbreak.

J R Soc Interface 2020 07 22;17(168):20200144. Epub 2020 Jul 22.

Department of Biology, McMaster University, Hamilton, Ontario, Canada.

A novel coronavirus (SARS-CoV-2) emerged as a global threat in December 2019. As the epidemic progresses, disease modellers continue to focus on estimating the basic reproductive number [Formula: see text]-the average number of secondary cases caused by a primary case in an otherwise susceptible population. The modelling approaches and resulting estimates of [Formula: see text] during the beginning of the outbreak vary widely, despite relying on similar data sources. Here, we present a statistical framework for comparing and combining different estimates of [Formula: see text] across a wide range of models by decomposing the basic reproductive number into three key quantities: the exponential growth rate, the mean generation interval and the generation-interval dispersion. We apply our framework to early estimates of [Formula: see text] for the SARS-CoV-2 outbreak, showing that many [Formula: see text] estimates are overly confident. Our results emphasize the importance of propagating uncertainties in all components of [Formula: see text], including the shape of the generation-interval distribution, in efforts to estimate [Formula: see text] at the outset of an epidemic.
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http://dx.doi.org/10.1098/rsif.2020.0144DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7423425PMC
July 2020

Using Serology with Models to Clarify the Trajectory of the SARS-CoV-2 Emerging Outbreak.

Trends Immunol 2020 10 29;41(10):849-851. Epub 2020 Jun 29.

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA; Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.

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http://dx.doi.org/10.1016/j.it.2020.06.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7323642PMC
October 2020

Waning immunity and re-emergence of measles and mumps in the vaccine era.

Curr Opin Virol 2020 02 4;40:48-54. Epub 2020 Jul 4.

Center for Communicable Disease Dynamics, Department of Epidemiology, Dept. of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. Electronic address:

Vaccine-preventable diseases (VPD) including measles and mumps have been re-emerging in countries with sustained high vaccine coverage. For mumps, waning immunity has been recognized as a major contributor to recent outbreaks. Although unvaccinated individuals account for most cases in recent measles outbreaks, the role of immune waning remains unclear. Accumulating serological and epidemiological evidence suggests that natural immunity induced by infection may be more durable compared to vaccine-induced immunity. As the proportion of population immunity via vaccination gradually increases and boosting through natural exposures becomes rare, risk of outbreaks may increase. Mechanistic insights into the coupled immuno-epidemiological dynamics of waning and boosting will be important to understand optimal vaccination strategies to combat VPD re-emergence and achieve eradication.
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http://dx.doi.org/10.1016/j.coviro.2020.05.009DOI Listing
February 2020

Structure, space and size: competing drivers of variation in urban and rural measles transmission.

J R Soc Interface 2020 07 8;17(168):20200010. Epub 2020 Jul 8.

Office of Population Research, Princeton University, Princeton, NJ, USA.

A key concern in public health is whether disparities exist between urban and rural areas. One dimension of potential variation is the transmission of infectious diseases. In addition to potential differences between urban and rural local dynamics, the question of whether urban and rural areas participate equally in national dynamics remains unanswered. Specifically, urban and rural areas may diverge in local transmission as well as spatial connectivity, and thus risk for receiving imported cases. Finally, the potential confounding relationship of spatial proximity with size and urban/rural district type has not been addressed by previous research. It is rare to have sufficient data to explore these questions thoroughly. We use exhaustive weekly case reports of measles in 954 urban and 468 rural districts of the UK (1944-1965) to compare both local disease dynamics as well as regional transmission. We employ the time-series susceptible-infected-recovered model to estimate disease transmission, epidemic severity, seasonality and import dependence. Congruent with past results, we observe a clear dependence on population size for the majority of these measures. We use a matched-pair strategy to compare proximate urban and rural districts and control for possible spatial confounders. This analytical strategy reveals a modest difference between urban and rural areas. Rural areas tend to be characterized by more frequent, smaller outbreaks compared to urban counterparts. The magnitude of the difference is slight and the results primarily reinforce the importance of population size, both in terms of local and regional transmission. In sum, urban and rural areas demonstrate remarkable epidemiological similarity in this recent UK context.
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http://dx.doi.org/10.1098/rsif.2020.0010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7423418PMC
July 2020

Implications of localized charge for human influenza A H1N1 hemagglutinin evolution: Insights from deep mutational scans.

PLoS Comput Biol 2020 06 25;16(6):e1007892. Epub 2020 Jun 25.

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America.

Seasonal influenza A viruses of humans evolve rapidly due to strong selection pressures from host immune responses, principally on the hemagglutinin (HA) viral surface protein. Based on mouse transmission experiments, a proposed mechanism for immune evasion consists of increased avidity to host cellular receptors, mediated by electrostatic charge interactions with negatively charged cell surfaces. In support of this, the HA charge of the globally circulating H3N2 has increased over time since its pandemic. However, the same trend was not seen in H1N1 HA sequences. This is counter-intuitive, since immune escape due to increased avidity (due itself to an increase in charge) was determined experimentally. Here, we explore whether patterns of local charge of H1N1 HA can explain this discrepancy and thus further associate electrostatic charge with immune escape and viral evolutionary dynamics. Measures of site-wise functional selection and expected charge computed from deep mutational scan data on an early H1N1 HA yield a striking division of residues into three groups, separated by charge. We then explored evolutionary dynamics of these groups from 1918 to 2008. In particular, one group increases in net charge over time and consists of sites that are evolving the fastest, that are closest to the receptor binding site (RBS), and that are exposed to solvent (i.e., on the surface). By contrast, another group decreases in net charge and consists of sites that are further away from the RBS and evolving slower, but also exposed to solvent. The last group consists of those sites in the HA core, with no change in net charge and that evolve very slowly. Thus, there is a group of residues that follows the same trend as seen for the entire H3N2 HA. It is possible that the H1N1 HA is under other biophysical constraints that result in compensatory decreases in charge elsewhere on the protein. Our results implicate localized charge in HA interactions with host cells, and highlight how deep mutational scan data can inform evolutionary hypotheses.
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http://dx.doi.org/10.1371/journal.pcbi.1007892DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7316228PMC
June 2020
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