Different ontologies: land change science and health research

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Highlights

  • Different ontologies impede progress in basic land change and health science.

  • Land change models must expand beyond ecologic studies of disease.

  • LULC and disease are synergistically related.

  • LULC methods translate well to vector bionomics and transmission risks.

Land use and land cover (LULC) is now recognized as an important driver of disease. For emerging or re-emerging infectious diseases, LULC offers context and serves as a likely proximate driver of risk particularly when considering vector-borne or zoonotic diseases. Ontological differences embedded within disciplinary structures impede progress limiting the ultimate potential of both LULC data and land change theory within disease research. Geography, space, and time serve as effective complements to traditional health and place organizational and disease-research strategies. Improved systemic clarity is obtained if one orients the disease relationship to particular contexts and if the scales of the relationships are clearly defined.

Introduction

Land use and cover matter. It is often cited as the most important factor in the emergence or re-emergence of infectious disease [1]. The role of land use and land cover (LULC) as cause, contributor, or facilitator of health and disease systems is known, but it curiously remains a distant third wheel of the epidemiological triangle model of disease causation (Figure 1). It might be simply that the chain of transmission emphasizes factors related to host and agent. But we assert that the ontological differences between the health research and land change science communities substantively impede relevant basic science. Land change models best fit epidemiological evidence structures when firmly rooted in ecologic studies (Figure 2). To be clear, we define ecologic studies, specifically within the epidemiological evidence framework, as those where the unit of analysis is a population rather than an individual. This is a precise definition and distinct from what might be considered ‘ecologic(al)’ in the land change science community, particularly, the lack of any ‘biotic’ reference. These are ontological differences.

It is important to recognize that land use and cover models are abstractions often only loosely, or more commonly indirectly, tied to relevant drivers of health and disease. This abstraction and associated causation problem permeates the consumers of land change data for health research. Understanding the relationship between LULC data and disease requires intimate knowledge of the dynamic relationship between the environment, people, and pathogens. This becomes increasingly complex as disease lifecycles often alternate between humans and nonhuman vertebrates, invertebrates or other mediating living organisms. Among the several, fine reviews previously conducted linking humans and altered landscapes to increased disease risk [2, 3, 4, 5] practical generalizations have proven rare. Further, the emergence of the focus on human–environment relationships in health research mediated by LULC has largely driven the thematic questions by region. For example, most studies in the tropics focus on rapidly emerging diseases due to increased human–vector/animal contacts, but in temperate regions far more research explores climate change impacts or otherwise small changes that allow subpopulations (animal/human/vector) to be exposed and begin infective/epidemic cycles. While sensitive to the human–environment theoretical core, space and time should serve as complementary to traditional health and place organizational strategies. Until space and time become equal to place and health (agent and host), land change science and related data products will remain relegated to ecologic scale research questions.

Section snippets

Framework

The International Geosphere–Biosphere Program (IGBP) and the International Human Dimensions Program have offered a categorization of land change models: comparative land use dynamics models used to improve understanding of the relationships among human decision making across scales, empirical diagnostic models that rely on remotely sensed observations of spatial and temporal land cover dynamics, and integrative assessment models emergent through the development of land use and cover change

Vector-borne diseases

Vector-borne diseases are those in which transmission between an infected and susceptible human or animal is dependent on another living organism or vector. Vectors can be biological with pathogens reproducing within the vector and transmitted (usually) during feeding, or mechanical with pathogens migrating between hosts by attaching themselves to vectors. The epidemiology of a vector-borne disease is predicated primarily on the lifecycle, preferred habitat and feeding behavior of a vector

Malaria

Malaria is endemic in more than 100 countries with more than 3.3 billion people at risk. Its continued impact across generations has made it one of the most widely studied diseases in human history. Malaria is transmitted by the female Anopheles mosquito and is the result of infection due to the presence of Plasmodium parasites, primarily P. vivax, P. falciparum, P. malariae, and P. ovale. Studies of malaria epidemiology are vast and risk is multidimensional involving human population growth

Trypanosomiasis

African trypanosomiasis (sleeping sickness) is a zoonotic, parasitic infection of wildlife, domesticated animals, and humans. The causative agents (parasites of the Trypanosoma brucei species complex) are transmitted by the bite of the tsetse fly (genus Glossina). Approximately 8.5 million km2 in 36 sub-Saharan Africa countries are infested with tsetse [36], resulting in approximately 70 million people with exposure risk [37, 38]. In recent years, African trypanosomiasis has emerged in new

Conclusions

Ontological differences particularly around space and time continue to impede basic health and land change science. Further, the land change science community tends to focus on continuous, synoptic space and discrete time, while the health community tends to focus on discrete space and continuous time. The dominant land change science paradigm will continue to promote the production of models with restricted applicability in health research. Despite this, within the broader health community,

References and recommended reading

Papers of particular interest, published within the period of review, have been highlighted as:

  • • of special interest

  • •• of outstanding interest

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