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Imperfect future immunity Humans are infected by several seasonal and cross-reacting coronaviruses. None provokes fully protective immunity, and repeat infections are the norm. Vaccines tend to be less efficient than natural infections at provoking immunity, and there are risks of adverse cross-reactions. Saad-Roy et al. used a series of simple models for a variety of immune scenarios to envisage immunological futures for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with and without vaccines. The model outcomes show that our imperfect knowledge about the imperfect coronavirus immune landscape can give rise to diverging scenarios ranging from recurring severe epidemics to elimination. It is critical that we accurately characterize immune responses to SARS-CoV-2 for translation into managing disease control. Science, this issue p. 811, Modeling shows how essential it is to improve precise understanding of immune responses to SARS-CoV-2., 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.

The path to elimination Measles is highly infectious and can be dangerous. The classic 1968 vaccine is highly effective, and it should be possible to eliminate measles. Graham et al. found that measles transmission changes as vaccination coverage and birth rates (that is, the rate of arrival of susceptible individuals into the population) change in a country in response to socioeconomic variables. As a result, measles everywhere follows the canonical mode of decline in response to vaccination campaigns. Incidence is initially high, and variability is low. As incidence declines, variability increases, and as incidence drops toward elimination, so does variability. It is possible to identify countries that are deviating from this expectation and to adapt their vaccination programs to regain the path to elimination. Science , this issue p. 584

CORONAVIRUS In some quarters, it is hoped that increased humidity and higher temperatures over the Northern Hemisphere in the summer will snuff out the 2020 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. In reality, the situation is likely to be more complicated than that. Baker et al. used a climate-dependent epidemic model to simulate the SARS-CoV-2 pandemic, testing different scenarios of climate dependence based on known coronavirus biology. Levels of susceptibility among the population remain the driving factor for the pandemic, and without effective control measures, the pandemic will persist in the coming months, causing severe outbreaks even in humid climates. Summer will not substantially limit pandemic growth. Science this issue p. 315

Seasonal flu by ZIP code Influenza virus strikes communities in northern latitudes during winter, straining health care provision almost to the breaking point. Change in environmental humidity is a key driver, but many other seasonal and social factors contribute. Dalziel et al. obtained a geographical distribution of doctor visits for influenza-like illness for more than 600 U.S. cities (see the Perspective by Wallinga). Some ZIP codes regularly experienced sharply defined peaks of cases, or intense epidemics, and others showed a longer, more diffuse influenza season. The surges tended to occur in smaller cities with less residential density and lower household incomes. Larger, more densely populated cities had more-diffuse epidemics, presumably because of higher rates of personal contact, which makes influenza transmission less subject to climate variation. Science , this issue p. 75 ; see also p. 29

Hanage and Russell conjecture [see also ([ 1 ][1])] that intermediate levels of immunity may sufficiently restrict within-host viral population size and thus limit adaptive mutations. The evolutionary model in our Research Article encompasses a wide range of scenarios, including the optimistic one Hanage and Russell propose (see scenario 1 in Fig. 4A of the Research Article). However, we also argued that uncertainties in immunodynamics, and in particular evolutionary dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), dominate our ability to project key scenarios. We therefore produced generic models in an effort to encompass this variability while providing a useful framework for considering possible future outcomes. We would also like to clarify that the calculations for evolutionary potential in our Research Article involve only infections after natural or vaccinal immunity has waned [i.e., I S (secondary infection after waned natural immunity), I S1 (infection after waned one-dose vaccinal immunity), and I S2 (infection after waned two-dose vaccinal immunity), see Fig. 1]. Our accompanying interactive online application allows for the exploration of the effect of an even wider range of parameters on immunological and epidemiological outcomes. We stress that the understanding of viral phylodynamics (the intersection of the epidemiological and evolutionary dynamics of pathogens) is still in its infancy, especially for novel pathogens like SARS-CoV-2. We therefore believe that exploring the resulting uncertainty is key. Understanding the dynamics of different classes of individuals experiencing infections after the waning of natural or vaccinal immunity will be crucial for teasing out drivers of viral immune escape (i.e., the ability of a virus to evolve to evade host immune factors); this is at the heart of our model. Along these lines, and as we highlight in the Research Article, an important area of future work will be to develop phylodynamic models with explicit within-host dynamics ([ 2 ][2]). The other major source of uncertainties is in epidemiological outcomes. In their Letter, Hanage and Russell emphasize the likely epidemiological importance of widespread vaccine deployment. This echoes a conclusion of our Research Article, wherein we stress that short-term dose sparing deployment of a vaccine reduces infections and buys much time in public health planning. However, we also stressed the range of uncertainties that may modulate the longer-term outcomes of this strategy; in particular, less robust immunity could lead to more complex epidemiological and evolutionary outcomes. 1. [↵][3]1. S. Cobey, 2. D. B. Larremore, 3. Y. H. Grad, 4. M. Lipsitch , “Concerns about SARS-CoV-2 evolution should not hold back efforts to expand vaccination,” preprint, Harvard University (2021); . 2. [↵][4]1. D. H. Morris et al ., eLife 9, e62105 (2020). [OpenUrl][5][CrossRef][6][PubMed][7] [1]: #ref-1 [2]: #ref-2 [3]: #xref-ref-1-1 "View reference 1 in text" [4]: #xref-ref-2-1 "View reference 2 in text" [5]: {openurl}?query=rft.jtitle%253DeLife%26rft.volume%253D9%26rft.spage%253De62105%26rft_id%253Dinfo%253Adoi%252F10.7554%252FeLife.62105%26rft_id%253Dinfo%253Apmid%252F33174838%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [6]: /lookup/external-ref?access_num=10.7554/eLife.62105&link_type=DOI [7]: /lookup/external-ref?access_num=33174838&link_type=MED&atom=%2Fsci%2F372%2F6540%2F354.2.atom

Thakkar and McCarthy suggest that periodicity in measles incidence artifactually drives our estimates of a 2- to 3-year duration of measles “immune-amnesia.” We show that periodicity has a negligible effect relative to the immunological signal we detect, and demonstrate that immune-amnesia is largely undetectable in small populations with large fluctuations in mortality of the type they use for illustration.

Extra dividends from measles vaccine Vaccination against measles has many benefits, not only lifelong protection against this potentially serious virus. Mina et al. analyzed data collected since mass vaccination began in high-income countries when measles was common. Measles vaccination is associated with less mortality from other childhood infections. Measles is known to cause transient immunosuppression, but close inspection of the mortality data suggests that it disables immune memory for 2 to 3 years. Vaccination thus does more than safeguard children against measles; it also stops other infections taking advantage of measles-induced immune damage. Science , this issue p. 694

Vaccinate children despite Ebola During the medical emergency caused by the Ebola virus outbreak in West Africa, routine childhood vaccination programs have been suspended. If vaccination is not resumed soon, there could be even more deaths. Measles is highly infectious, and outbreaks are a sign of health care systems in trouble. Using mathematical modelling, Takahashi et al. estimate that about a million children across Liberia, Sierra Leone, and Guinea are vulnerable to measles. Aggressive public health programs are vital for this region to minimize harm, not only from measles but also from polio, malaria, tuberculosis, and other childhood infections. Science , this issue p. 1240

Immune clearance and resource limitation (via red blood cell depletion) shape the peaks and troughs of malaria parasitemia, which in turn affect disease severity and transmission. Quantitatively partitioning the relative roles of these effects through time is challenging. Using data from rodent malaria, we estimated the effective propagation number, which reflects the relative importance of contrasting within-host control mechanisms through time and is sensitive to the inoculating parasite dose. Our analysis showed that the capacity of innate responses to restrict initial parasite growth saturates with parasite dose and that experimentally enhanced innate immunity can affect parasite density indirectly via resource depletion. Such a statistical approach offers a tool to improve targeting of drugs or vaccines for human therapy by revealing the dynamics and interactions of within-host regulatory mechanisms.

Zeroing in on Zoonoses Influenza, plague, and Lyme disease are classic examples of zoonoses—diseases that circulate in livestock and wildlife, as well as in humans. When a pathogen transfers among multiple hosts, the dynamics of circulation, transmission, and outbreak are complex. Lloyd-Smith et al. (p. 1362 ) review the use of analytical mathematical tools, particularly modeling, in the development of control policies and research agendas. Significant gaps are highlighted in analytical efforts during spillover transmission from animals into humans. Moreover, the tendency has been to focus on pathogens with simpler life cycles and of immediate global urgency, such as influenza, whereas insect-transmitted pathogens with complex, multihost life cycles are less well understood.

Human influenza A (subtype H3N2) is characterized genetically by the limited standing diversity of its hemagglutinin and antigenically by clusters that emerge and replace each other within 2 to 8 years. By introducing an epidemiological model that allows for differences between the genetic and antigenic properties of the virus's hemagglutinin, we show that these patterns can arise from cluster-specific immunity alone. Central to the formulation is a genotype-to-phenotype mapping, based on neutral networks, with antigenic phenotypes, not genotypes, determining the degree of strain cross-immunity. The model parsimoniously explains well-known, as well as previously unremarked, features of interpandemic influenza dynamics and evolution. It captures the observed boom-and-bust pattern of viral evolution, with periods of antigenic stasis during which genetic diversity grows, and with episodic contraction of this diversity during cluster transitions.

Quantifying long-range dissemination of infectious diseases is a key issue in their dynamics and control. Here, we use influenza-related mortality data to analyze the between-state progression of interpandemic influenza in the United States over the past 30 years. Outbreaks show hierarchical spatial spread evidenced by higher pairwise synchrony between more populous states. Seasons with higher influenza mortality are associated with higher disease transmission and more rapid spread than are mild ones. The regional spread of infection correlates more closely with rates of movement of people to and from their workplaces (workflows) than with geographical distance. Workflows are described in turn by a gravity model, with a rapid decay of commuting up to around 100 km and a long tail of rare longer range flow. A simple epidemiological model, based on the gravity formulation, captures the observed increase of influenza spatial synchrony with transmissibility; high transmission allows influenza to spread rapidly beyond local spatial constraints.

Most emerging infectious diseases in humans originate from animal reservoirs; to contain and eradicate these diseases we need to understand how and why some pathogens become capable of crossing host species barriers. Influenza virus illustrates the interaction of factors that limit the transmission and subsequent establishment of an infection in a novel host species. Influenza species barriers can be categorized into virus-host interactions occurring within individuals and host-host interactions, either within or between species, that affect transmission between individuals. Viral evolution can help surmount species barriers, principally by affecting virus-host interactions; however, evolving the capability for sustained transmission in a new host species represents a major adaptive challenge because the number of mutations required is often large.

A key priority for infectious disease research is to clarify how pathogen genetic variation, modulated by host immunity, transmission bottlenecks, and epidemic dynamics, determines the wide variety of pathogen phylogenies observed at scales that range from individual host to population. We call the melding of immunodynamics, epidemiology, and evolutionary biology required to achieve this synthesis pathogen “phylodynamics.” We introduce a phylodynamic framework for the dissection of dynamic forces that determine the diversity of epidemiological and phylogenetic patterns observed in RNA viruses of vertebrates. A central pillar of this model is the Evolutionary Infectivity Profile, which captures the relationship between immune selection and pathogen transmission.

On 14 January 2016, Liberia was declared Ebola-free. A new case was identified shortly after the announcement, but it is nevertheless clear that the West African epidemic has moved on to a more hopeful phase. What lessons can be drawn from the Ebola crisis to help the international community to prepare for and respond to the next global epidemic? This question is particularly pertinent given the recent declaration of the Zika virus as a public health emergency.

Foot-and-mouth is one of the world's most economically important livestock diseases. We developed an individual farm–based stochastic model of the current UK epidemic. The fine grain of the epidemiological data reveals the infection dynamics at an unusually high spatiotemporal resolution. We show that the spatial distribution, size, and species composition of farms all influence the observed pattern and regional variability of outbreaks. The other key dynamical component is long-tailed stochastic dispersal of infection, combining frequent local movements with occasional long jumps. We assess the history and possible duration of the epidemic, the performance of control strategies, and general implications for disease dynamics in space and time.

Dramatic changes in patterns of epidemics have been observed throughout this century. For childhood infectious diseases such as measles, the major transitions are between regular cycles and irregular, possibly chaotic epidemics, and from regionally synchronized oscillations to complex, spatially incoherent epidemics. A simple model can explain both kinds of transitions as the consequences of changes in birth and vaccination rates. Measles is a natural ecological system that exhibits different dynamical transitions at different times and places, yet all of these transitions can be predicted as bifurcations of a single nonlinear model.

C ontinual news on the outbreak status of the H5N1 subtype of influenza A virus in Southeast Asia points to one of the greatest challenges facing 21st-century society: the prediction and management of disasters. Hundreds of thousands die from influenza annually, with widespread and often devastating pandemics occurring episodically. The last flu pandemic occurred in 1968. Are we better able to mitigate the effect of a new pandemic than we were 37 years ago? Advances in science, vaccine strategies, and antiviral drugs provide this potential, but whether these can be applied in the short term in an effective global policy is not guaranteed. The continual threat of influenza A viruses such as avian H5N1 lies in their basic biology. The virus is easily transmitted and can be highly virulent. It is present at high frequencies in reservoirs of wild birds that can infect domestic animals, including horses, pigs, and poultry. Add to that the genetic plasticity of the virus, with high rates of mutation and a ready capacity for reassortment that allows it to combine with other strains to produce new and sometimes highly pathogenic variants. Most worrisome, the reassortment of human and bird strains could result in a pandemic virus that is transmissible among humans. A highly pathogenic avian H5N1 virus first appeared in Hong Kong in 1997. A mass cull of chickens alleviated the problem locally, but H5N1 viruses continued to circulate in birds in Asia, most recently among migratory species that could theoretically carry the virus for long distances. In 2003, H5N1 re-emerged in humans, causing almost 60 deaths in Asia to date, although there is no convincing evidence that the virus has evolved human-to-human transmission. ![Figure][1] CREDIT: CHRISTOPHER FURLONG/GETTY IMAGES How might we prevent and manage a future influenza pandemic? The most obvious requirement is a rapid and expansive influenza surveillance and response network. A permanent global task force has been proposed to perform this role,[*][2] and we strongly endorse this idea. However, such a task force will only be successful if national governments release data promptly and adhere to control measures should a pandemic arise. Such surveillance activity also needs to include humans, domestic animals, and wild birds. Second, we must develop further, effective intervention strategies to reduce transmission and disease. The development of vaccines against H5N1 strains, and ultimately against all subtypes, is a clear priority. Recent preliminary tests of a potential vaccine are encouraging. But using traditional approaches, fewer than 500 million people could currently be vaccinated with a two-dose monovalent pandemic influenza vaccine. New vaccine methodologies are in reach, but international agreements on production, intellectual property, distribution, and administration need to be aggressively pursued. Antiviral drug stockpiles are equally limited. Thus, because rapid global distribution networks of vaccines and antiviral agents have yet to be established, it is essential that logistical simulations be conducted to determine their possible limitations. Third, we need epidemiological models, to explore the spread and impact of potential influenza pandemics in the face of realistic control measures and how to manage pandemics when they arise. Two recent reports suggest that antiviral-based containment policies could be an effective strategy,[†][3] although this is contingent on a rapid, coordinated response to the emergence of a pandemic. We must also develop strategies to reduce the probability of pandemics. This will require a multitude of basic scientific information, including the probability and mechanism of reassortment; a measure of the exposure rates of influenza viruses at the human/animal interface; and, most critically, an understanding of how avian viruses evolve to develop sustained transmission networks in humans. It is therefore essential to conduct a global surveillance of genetic diversity in avian influenza viruses, sequencing complete genomes from these and mammalian strains to explore the polygenic nature of host adaptation. We also need to determine the extent of clonal genetic variation within individual hosts, because consensus sequences invariably hide strains with varying phenotypic properties. These data would also provide perspective on the evolutionary dynamics of viral pathogens at different spatial scales. Although a unified political effort is essential to avert or mitigate a major influenza pandemic, it must proceed in parallel with advances in basic science. The potential for avian H5N1 to cause a global human pandemic is presently uncertain because it cannot be predicted with current data. However, if an H5N1 pandemic does not emerge in the near term, the political will to continue the global preparations necessary for a future pandemic may falter. We cannot afford such a misstep. [1]: pending:yes [2]: #fn-1 [3]: #fn-2