The Landscape of Super-Spreading

Super-spreading individuals and disease hot spots have been known for over a century, but rarely have they been considered together. Sara Paull and colleagues [1] have pulled together all of the recent work the ecology of disease hot spots and transmission heterogeneity (super spreading) to explore the continuum between individual transmission heterogeneity and the landscape of disease, otherwise known as disease ecology. Hawley and Altizer [2] have developed the interrelationships further to the cellular level by linking disease ecology directly to ecological immunology, examining the effects of the environment on the immune system of  host populations. Taken together, these fields can be developed into a continuum of macro to micro landscapes  with transmission heterogeneity, better known as  super-spreading, at its center.

Adapted from Hawley and Altizer (2011). (Click to enlarge)

Disease Ecology

Disease ecology is the study of pathogens in the context of their dynamic environment. Unlike most medical experiments conducted in vitro, removing or stabilizing as many variables as possible, disease ecology seeks to understand the place of the pathogen in an an open, responsive environment with an unknown number of variables [3]. In disease ecology, multiple hosts and vectors of zoonotic diseases are considered together as a complex system. It is normal for the system to respond in unpredictable ways and for multiple stable states to be possible; the human gut microbiome consists of up to a thousand bacterial species that can come to at least three stable states (enterotypes) unrelated to easily identified variables (age, gender, ethnicity, etc.) [3].

Some of the basic areas of disease ecology include understanding the multiple hosts of a pathogen including factors effecting the lifecycle of the hosts, ecological drivers, endemic/enzootic and epidemic/epizootic dynamics,  characterization of the rural or urban landscape, and transmission dynamics. The US Environmental Protection Agency (EPA) defines an ecological driver as any biotic or abiotic factor that causes change to the ecological landscape. Ecological drivers can be as diverse as invasive species, climate change or changes to a man-made landscape. Transmission dynamics is also a basic factor in disease ecology.

Transmission Heterogeneity

Transmission between hosts is rarely, if ever, a uniform process. Extreme cases of transmission heterogeneity, where a small number of individuals are responsible for most successful transmissions, are called super-spreaders. These super-spreaders are major factors in epidemic dynamics of an increasing number of human pathogens. Drilling down into why transmission dynamics are heterogeneous yields a variety of causes.

Species level transmission heterogeneity has led to the recognition of ‘amplifying species’ that act as super-spreaders within the landscape.  American Robins as preferential hosts and transmitters of West Nile Virus are a classic example of an amplifying species [1]. Presumably changes in the landscape could alter the degree to which each possible host species contributes to the overall transmission within the environment and which host becomes the amplifying species. It would naturally follow that not all possible vectors are equally responsible for disease transmission. For example, we know that rat fleas, cat fleas, human fleas and possibly human lice can all transmit Yersinia pestis, but they are not equally responsible for transmission.

Landscape contributes to transmission heterogeneity as well. Studies have shown that oak tree vulnerability to sudden oak death syndrome varied with tree genotype but in field tests temperature and rainfall differences  mattered more than the genetics of individual trees [1]. These landscape characteristics go beyond the classical definitions of disease ‘hot spots’. Typical hot spots are defined as areas where there is higher pathogen levels or more amplification hosts [1].  For example, buffalo wallows and sites of buffalo deaths can become anthrax hot spots. Human have created animal disease hot spots; chronic wasting disease is increased among Colorado mule deer near human settlements rather than more remote areas [1]. In Belize, agricultural run-off alters the aquatic plant communities increasing breeding efficiency of the malaria vector Anopheles vestitipennis [1]. Some environmental hot spots can be so strong that they are “analogous to superspreaders” [1].

Which comes first, the hot spot or the super-spreader? Paull et al  note that “logically, superspreaders create hotspots of transmission around them, and hosts in a disease hotspot, by definition, experience an increased infection pressure as compared with others in the population” [1]. Ultimately what really matters is understanding why there is increased transmission. Does the ‘hot spot’ move with the hosts or is it tied to a locality or architectural structure? Some ‘hot spots’, like ships, are capable of moving although the increased transmission is tied to a piece of architecture. Likewise, some types of air conditioning systems can become ‘hot spots’ for Legionellosis, but redesign of the air conditioning system eliminates the ‘hot spot’.

Ecological Immunity

Ecological immunity takes factors of disease ecology and heterogeneous transmission particularly to the cellular and molecular level. For example, high testosterone levels suppress the male immune system (in birds and rodents) while triggering behavior that increases their territory and contact rates making them behavior super-spreaders [1,2]. It has been suggested that testosterone levels could be “a common driver of superspreading phenomena, broadly linking within- and among-host processes across vertebrate host taxa” [2].

The role of the environment and immunologic costs intersect when we look at seasonal effects and nutritional needs of the immune system. Malnutrition depresses the immune system directly and indirectly through hormones like leptin. The cost of immunity comes home when we realize that leptin intentionally cripples the immune system as part of the starvation response. Seasonal effects are easier to understand in animals that have a more defined seasonal pattern of migration, or a defined mating period [2]. Yet human infectious disease fluctuates with the season; influenza being a prime example of a disease with seasonal fluctuations.

Coinfections are also best understood for their impact at the cellular level of the immune system. The cost of the immune response makes immune trade-offs necessary during coinfections.  Focus has zeroed in on a classic immune trade-off between production of T-helper 1  and T-helper 2 cells as at least a partial explanation of poor prognosis for  helminth (worm)  and an intracellular pathogen coinfections [2].  Several studies have now shown that HIV infections progress faster if there is a helminth coinfection [2]. Likewise, in African buffalo helminth infections correlate with tuberculosis vulnerability and rapid progression; “Joelles et al (2008) found evidence for a direct trade-off between circulating levels of IFNγ (Th1 response) and eosinophils counts, their measure for Th2-type response in buffalo” [2]. To decrease vulnerability and improve prognosis for HIV and tuberculosis, treatment for helminths should become a priority.

What constitutes immune fitness must also be reevaluated in light of ecological immunity findings. The high cost of immune defenses are such that unnecessary defenses for the current environment are generally not maintained [2]. Likewise, costs and trade-offs may make it necessary for the immune system to develop tolerance to some pathogens deemed low risk to fight other greater risk challenges. Hawley and Altizer  note that “a ‘competent’ immune system may employ tolerance strategies, making immune ‘competence’ difficult to assess via infection outcome alone” [2].

Today we are only at the very beginning of understanding complex disease ecologies. For zoonotic diseases the impact of ecological drivers and enzootic dynamics all around the world make the identification of the best predictors an imperative. Yet, outbreak prediction will remain an imprecise science, not unlike the prediction of hurricanes or volcanic eruptions.  Increased surveillance will remain key to a rapid response and epidemic mitigation.


[1] Paull, S., Song, S., McClure, K., Sackett, L., Kilpatrick, A., & Johnson, P. (2012). From superspreaders to disease hotspots: linking transmission across hosts and space Frontiers in Ecology and the Environment, 10 (2), 75-82 DOI: 10.1890/110111

[2] Hawley, D., & Altizer, S. (2011). Disease ecology meets ecological immunology: understanding the links between organismal immunity and infection dynamics in natural populations Functional Ecology, 25 (1), 48-60 DOI: 10.1111/j.1365-2435.2010.01753.x

[3] Pepper, J.W. & Rosenfeld, S. (2012). The emerging medical ecology of the human gut microbiome, Trends in Ecology & Evolution, 27 (7) 384. DOI: 10.1016/j.tree.2012.03.002

2 thoughts on “The Landscape of Super-Spreading

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