Category Archives: ecology

General Principles of Zoonotic Landscape Epidemiology

Zoonoses, pathogens with animal reservoirs, exist as part of a complex system of interactions between animal reservoirs, vectors, ecological factors and human interaction. Landscape epidemiology has existed as a field of study since Russian epidemiologist E.N. Pavlovsky coined the term and laid the groundwork in the 1960s. Landscape epidemiology is in essence the study of environmental foci of zoonotic disease, what Pavlovsky called a nidas. Many of the variables have been identified and studied in individual pathogen systems.

Each system seems so complex and unique that it can be easy to think that they each exist as separate entities with little to do with each other. It is necessary to develop some general principles to both see the bigger picture, and guide research and response to less studied and newly discovered pathogens. Lambin et al. set out to do just that by doing a meta-analysis of eight regional case studies of zoonotic diseases in Europe and East Africa: West Nile Virus in Senegal, Tick-borne Encephalitis in Latvia, Sandfly abundance (leishmaniasis vector) in the French Pyrenees, Rift Valley Fever in Senegal, West Nile Virus hosts in Camargue, Rodent-borne Puumala hantavirus in Belgium, human cases of Lyme borreliosis in Belgium, and risk of malaria re-emergence in Camargue. Obviously, as indicated, not all of these studies look at all factors involved in landscape epidemiology so validation is not solely based on the number of case studies that support each principle.

The ten proposed principles by Lambin et al are shown graphically below where they fit into the system of variables.

Graphical representation of the landscape determinants of disease transmission. The numbers refer to the ten propositions formulated in this paper. Lambin et al. International Journal of Health Geographics 2010 9:54   doi:10.1186/1476-072X-9-54
Graphical representation of the landscape determinants of disease transmission. The numbers refer to the ten propositions formulated in this paper.
Lambin et al. International Journal of Health Geographics 2010 9:54 doi:10.1186/1476-072X-9-54

Proposed general principles (Lambin et al, 2010):

  1. Landscape attributes may influence the level of transmission of an infection” This proposal is found in all case species. Features of the landscape influence vector and host distribution across the region of study. Distribution and type of water (fresh, brackish, or salt water) is a common landscape feature that influences density of insect vectors.
  2. Spatial variations in disease risk depend not only on the presence and area of critical habitats but also on their spatial configuration“.   The sheer size of the critical area is not the only or necessarily the most important characteristic to determine risk in an area. Some vectors like ticks thrive along border zones between ecosystems, like edges between woodland and grasslands.
  3. Disease risk depends on the connectivity of habitats for vectors and hosts” Creating contact zones or contiguous zones that create linked areas are also important. The spatial configuration can create corridors for disease persistence in harsh landscapes. Type and connectivity of  vegetation is as important as terrain for vector habitats. Connectivity between suitable habitat for rodents and insects allows the disease to spread from one patch to the next amplifying the pathogen to a level that increases risks of human transmission. Connections between patches of critical habitats allows for recolonization after local extinction.
  4. The landscape is a proxy for specific associations of reservoir hosts and vectors linked with the emergence of multi-host disease.” Their principle could be better fleshed out; their primary evidence coming from West Nile Virus (WNV). Like other multi-host pathogens, WNV has some hosts that are much more important than others for transmission across wide regions. In WNV migratory birds are a key to understanding its spread and epidemic dynamics. WNV is also an example of a disease with different proxies and amplification hosts in different regions of the world.
  5. To understand ecological factors influencing spatial variations of disease risk, one needs to take into account the pathways of pathogen transmission between vectors, hosts, and the physical environment.” Vector-borne diseases require direct contact between humans and the vector. For other zoonoses like hantavirus contact between humans and animal hosts can be via aerosols of material with rodent feces or dust containing rodent remains. For example, people have contracted hantavirus by vacuuming up rodent remains in homes. When estimating risk of transmission to humans, abiotic (non-living) environmental conditions that can preserve or transmit to humans have to be considered. Climate and moisture content of the soil are common abiotic factors to be concerned about. Additional support for this principle comes from the role of the rodent burrow system on plague (Yersinia pestis) hosts and vectors.
  6. The emergence and distribution of infection through time and space is controlled by different factors acting at multiple scales” In their discussion of this principle, they focus on human interaction with the environment and particularly urbanization altering disease risk. They note that climate change and natural environmental change do not account for all emerging and re-emerging disease but the activities of humans including urbanization and ecological change like deforestation. Ben-Ari et al‘s study on plague and climate change also looks at the many factors at all levels from micro to macro scales effect the abundance and likelihood of transmission of the plague.

    Plague cycle including hosts and vectors with abiotic influences
    Plague cycle including hosts and vectors with abiotic influences (Ben-Ari et al, 2011).
  7. Landscape and meteorological factors control not just the emergence but also the spatial concentration and spatial diffusion of infection risk” This principle just adjusts the previous principles to take account of primarily rainfall by looking at temporary ponds or wetlands. This particularly affects mosquito abundance, but as the graphic above demonstrates also effects soil moisture.
  8. Spatial variation in disease risk depends not only on land cover but also on land use, via the probability of contact between, on one hand, human hosts and, on the other hand, infectious vectors, animal hosts or their infected habitats” Land use has been long known to affect mosquito abundance and disease transmission. Clearing land for settlements or agriculture always increases standing water in ditches, tire ruts, railroad ditches, animal troughs, incomplete building projects, and due to loss of water absorbing vegetation. A century of malaria research and management has focused on land use and the elimination of standing water.  Mature water management programs for cultivation or flood control can also alter vector abundance and human contact rates. For example flooding fields to grow rice not only provides habitat for mosquito production but also brings people into the fields to cultivate increasing contact rates. Irrigation canals would have a similar effect.
  9. The relationship between land use and the probability of contact between vectors and animal hosts and human hosts is influenced by land ownership” In Lambin et al, they looked at the contact rates between public (state) land and private ownership. In these studies state ownership increased access to forestland over private ownership.By the same token, state ownership could also prevent deforestation and urbanization by preserving the wilderness or reserving the land for other uses. Forest age and maturity also varies significantly between state forests and private land.
  10. Human behaviour is a crucial controlling factor of vector-human contacts, and of infection.”  Humans bring themselves into contact with vectors by risky behavior and can control exposure vectors and infections. Obviously, vaccination is one of the controlling factors of infection, although many zoonotic infections have either no or poor vaccines. Occupational and recreational exposure to vectors often explains gender difference in infection rates.

In conclusion these principles begin to mark out the three sides of a zoonotic triangle: biology of pathogen, vector and host; ecological system where they exist; and human behavior and ecological interaction. Human behavior including land use and constructed environments is as important as the other two sides of the triangle. Humans are not passive victims or collateral damage.


Lambin, E. F., Tran, A., Vanwambeke, S. O., Linard, C., & Soti, V. (2010). Pathogenic landscapes: Interactions between land, people, disease vectors, and their animal hosts. International Journal of Health Geographics, 9(1), 54. doi:10.1186/1476-072X-9-54 [open access]

Ben-Ari T, Neerinckx S, Gage KL, Kreppel K, Laudisoit A, et al. (2011) Plague and Climate: Scales Matter. PLoS Pathog 7(9): e1002160. doi:10.1371/journal.ppat.1002160

Reactivation of Ancient Plague Foci in Libya, 2009

Landscape around Oran, Algeria,  and Tobruk, Lybia in 2009 that produced plague cases. (Cabanel et al, 2013)
Landscape around Oran, Algeria (2003), and Tobruk, Lybia (2009) that produced plague cases. (Cabanel et al, 2013)

Plague has been called a re-emerging disease primarily because cases have begun to appear in areas where plague has been absent for decades. Two recent surprising outbreaks occurred in Algeria, where plague had been absent for over 50 years, and in Libya after a 25 year absence. A team led by the Institut Pasteur explored possible relationships between the recent Libyan outbreak and the Algerian outbreaks. All of the information in this post comes from their report to be published in the February issue of Emerging Infectious Diseases (citation and link below).

The outbreaks under consideration were just south of Oran, Algeria in 2003, at Lanhouat, Algeria in 2008 and near Tobruk near the Libyan-Egyptian border in 2009. Another possible outbreak of plague occurred at Tobruk during the Libyan revolution in 2011.  Political unrest prevented a complete disease investigation of the 2011 Libyan epidemic. Past Libyan plague outbreaks have occurred from 1913-1920, 1972, 1976, 1977, and 1984. The largest outbreak in 1917 is credited with 1,449 deaths.

The 2009 Libyan index cases consisted of three children from one nomad family; one child died after two days of intensive care and the other two eventually recovered. Only one child had a tender cervical node. The other two, including the child who died, had signs of a severe infection but no visible buboes. The father reported having axillary lymphadenitis and a couple of sudden deaths in the region in the previous two months. A week after admission Libyan authorities reported 13 possible cases to the World Health Organization and requested assistance. The WHO-Libyan team identified two more women with painful inguinal nodes and “infectious syndrome”, but also concluded the initial estimate overstated the number of cases. There are five confirmed cases. The cases were spread 30-60 km from the index family’s home in Eltarsha, 30 km south of Toburk. Regional response included antibiotic treatment of contact persons, and insect and rodent control measures. No further cases were reported.

Diagnosis was confirmed by standard bacteriological assays and molecular characterization. All five confirmed cases were positive with the F1 antigen dipstick.  Yersinia pestis cultures were isolated from three patients,  all phenotyped to the Medievalis biovar by metabolic assays. Molecular characterization confirmed that all are the same Medievalis strain. Hybridization analysis indicates that it is most closely related to, but distinct from, strains isolated from Iranian Kurdistan in 1947 – 1951.

Using the same methods, the 2003 Algerian isolates were phenotyped to the Orientalis biovar. Molecular characterization confirmed that they are all related but not identical Orientalis strains. Activation of multiple related strains from an ancient foci in the same year suggests an environmental trigger. Comparing the 2003 strains to those isolated in 1944 and 1945 illustrate the complexities of plague foci. The 1944 isolate is a Orientalis strain that belongs to the same cluster of strains as the 2003 isolates and other strains from Morocco and Senegal.  The 1945 strain matched a molecular characterization of  Orientalis isolates from Saigon, Vietnam and is believed to have been transmitted by military transports during World War II.  Cabanel et al conclude that the 2003 Algerian outbreaks were caused by local Yersinia pestis strains. It should be noted that the third pandemic from the turn of the 20th century was a Orientalis biovar (1.Ori1).

Cabanel et al. note this is the only instance they could find of a Medievalis strain in Africa. The spread of cases over a 30-60 km region and isolation of related but different strains support the reactivation of an ancient plague focus. Unfortunately they did not have access to isolates from previous 20th century Libyan outbreaks (if they exist) that could have provided more certainty.

Reactivation of plague foci around the Mediterranean has been associated with climate change. They note that an unusually humid winter and good crops in Libya in 2009 favored rodent and flea abundance. Long dormancies may be part of Yersinia pestis’ natural history particularly in resource limited environments. This possibility will be one of the topics of my next post.

Cabanel et al. note that camel meat and livers have been associated with human plague cases in Libya (1976), Saudi Arabia (1994), Jordan (1997), and Afghanistan (2007). Additional local evidence suggested that the highly susceptible camels contracted the plague from local foci in these instances. Although camels do not survive plague long enough to transmit it very far, camel caravan routes may still have played a role in transmission if only by the other organisms also along the camel caravan route. Camels would have provided an abundant host to amplify the organism along the route. Camel fleas could have been carried among the cargo not unlike rat fleas in ship cargoes. Camel caravans would provide an ancient route for a Medievalis strain to reach Libya from the central Asia.


Cabanel, N., Leclercq, A., Chenal-Francisque, V., Annajar, B., Rajerison, M., Bekkhoucha, S., Bertherat, E., & Carniel, E. (2013). Plague Outbreak in Libya, 2009, Unrelated to Plague in Algeria Emerging Infectious Diseases, 19 (2), 230-236 DOI: 10.3201/eid1902.121031

ResearchBlogging.orgplague series

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