No abstract

International trade in wildlife is one contributing factor to zoonotic disease risk. Using descriptive statistics, this paper shows that in the last decades, the volume and pattern of internationally traded wildlife has changed considerably and, with it, the zoonotic pathogens that are traded. In an econometric analysis, we give evidence that an international environmental trade agreement could be used to limit the spread of zoonotic pathogens and disease. More specifically, combining zoonotic disease data with wildlife trade data from the Convention on International Trade in Endangered Species of Wildlife and Fauna (CITES), we show that making trade requirements more stringent leads to a decrease in the number of animals traded and, incidentally, also the number of zoonotic diseases that are traded. Our results contribute to the discussion of policy measures that manage the spread of zoonotic diseases.

Debate regarding the relationship between socioeconomic development and natural disasters remains at the fore of global discussions, as the potential risk from climate extremes and uncertainty pose an increasing threat to developmental prospects. This study reviews statistical investigations of disaster and development linkages, across topics of macroeconomic growth, public governance and others to identify key challenges to the current approach to macro-level statistical investigation. Both theoretically and qualitatively, disaster is known to affect development through a number of channels: haphazard development, weak institutions, lack of social safety nets and short-termism of our decision-making practices are some of the factors that drive natural disaster risk. Developmental potentials, including the prospects for sustainable and equitable growth, are in turn threatened by such accumulation of disaster risks. However, quantitative evidence regarding these complex causality chains remains contested due to several reasons. A number of theoretical and methodological limitations have been identified, including the use of GDP as a proxy measurement of welfare, issues with natural disaster damage reporting and the adoption of ad hoc model specifications and variables, which render interpretation and cross-comparison of statistical analysis difficult. Additionally, while greater attention is paid to economic and institutional parameters such as GDP, remittance, corruption and public expenditure as opposed to hard-to-quantify yet critical factors such as environmental conditions and social vulnerabilities. These are gaps in our approach that hamper our comprehensive understanding of the disaster-development nexus. Important areas for further research are identified, including recognizing and addressing the data constraints, incorporating sustainability and equity concerns through alternatives to GDP, and finding novel approaches to examining the complex and dynamic relationships between risk, vulnerability, resilience, adaptive capacity and development.

No abstract

No abstract