Report: SANParks Global Environmental Change Project: Disease Summary Report

Background: Disease is recognized as a long term driver of ecosystem change. There is currently a lack of data on disease in South Africa, especially in protected areas. Most available information details human, livestock and large game diseases, while there is little knowledge of disease in plants, lower order vertebrates and invertebrates. Increasing habitat fragmentation, especially outside parks, results in an increased interface risk between humans and wildlife, with a greater opportunity for disease transfer. Agricultural activities could also become an important source of disease outbreaks and emerging infectious disease, especially with an increase in wildlife farming, aquaculture and mariculture. The loss of biodiversity itself, and the resulting loss of genetic diversity, species abundance and community membership, may also result in an increase in the number and frequency of outbreaks of emerging infectious diseases. The potential for interaction between habitat fragmentation, climate change and emerging infectious diseases have made active collection of disease data for protected areas a priority if unacceptable biodiversity and economic losses and livelihood threats to neighbouring communities are to be detected and, where possible, prevented.

Methods: All potential disease threats for SANParks were listed and categorized using published data and expert opinion. Information on the distribution, risk factors and records of outbreaks were gathered for the diseases deemed important (most likely to be linked to global environmental change) or are regulated by the Diseases Act (n = 15: anthrax, African swine fever, African horse sickness, avian influenza, bovine tuberculosis, botulism, bovine brucellosis, Crimean Congo hemorrhagic fever, corridor disease, canine distemper, foot and mouth diseases, heart water, malignant catarrhal fever, rabies & rift valley fever). Summary statistics regarding the distribution of and trends in diseases were calculated from available data.

Major findings: Disease as a driver of Global Environmental Change proved to be a very challenging assessment. Reliable data on disease distribution, presence and impacts are scarce and it proved too difficult to assess where disease will act as a GEC driver. It is however clear that disease can often end up being part of the mechanism that influences populations negatively, exacerbating the impact of global environmental change. Ungulates are the group most commonly affected by the 15 diseases analyzed (probably because livestock and buffalo are tested most frequently), but some of these diseases can also spill over into their predators. Most of the disease information is present for savanna parks, mostly Kruger. This is likely because the best and most long-standing surveillance is present in these parks, as are most of the large mammals and the climate of these regions is better suited to several of the diseases. More data also occurs in areas where commercial farming is prevalent. Intensification of farming allows certain diseases to become expressed in animals where this would not happen if animals were free ranging. Surveillance and outbreak data are incomplete, making it difficult to determine trends. The data are also biased: although surveillance of disease is carried out, this is mostly conducted for controlled diseases with data collection being intensified during outbreaks. Obtaining better data is however costly and is challenged by the fact that most diseases can only be diagnosed from samples collected from post mortem of affected animals. Active surveillance is mostly prohibited by costs unless linked to a specifically funded project but passive surveillance and data repository in a central SANParks database will go a long way to record diseases that are present and to track changes over time. This does not, however, allow for predictions to be made, which this assessment was hoping to achieve.

Monitoring, management and policy implications: Recommendations from this assessment are for SANParks to develop a surveillance system for detecting disease, but more importantly, a central depository for disease data and mortality reports where incidents can be and assimilated centrally in SANParks. This is especially important in the savanna parks where most of the “top-15” diseases are present. Deciding how the disease distribution database and the trends databases from this project will be updated and included in management decision making will be an important part of this. Metadata that includes a measure of data collection effort is essential to enable detection of changes in patterns of disease outbreak. Making predictions regarding disease is difficult but regular scenario planning to interpret how other global environmental change factors will interact with disease is an important tool that can be used. A flexible and rapid response decision making framework is required to be able to reactively and proactively respond to major disease events that could result in global environmental change acceleration and needs to be developed as part of Phase II of the project.