March – June 2020
This update: 3 April 2020
Cascading risks from rising prices and supply disruptions, April 2022.
Global resource markets are still reeling from the impacts of Russia’s invasion of Ukraine; the two countries are major suppliers of energy, food and fertilizers. Supply disruption and the sudden imposition, in response to the... crisis, of unprecedented economic sanctions, trade restrictions and policy interventions have caused prices of commodities to skyrocket.
Before the conflict, demand for global resources already exceeded supply and drove up prices as economies rebounded after the COVID-19 pandemic. This gave rise to a global cost-of-living crisis, characterized by increasing levels of energy and food poverty. This situation is likely to become much worse as a consequence of the war in Ukraine, and poses a threat to human security, particularly among low-income and vulnerable populations.
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The aim of this toolkit is to guide countries on how to best estimate their current burden of dengue by combining existing data from dengue surveillance systems with on-going research efforts to measure the community burden
of dengue.
Chagas disease is currently endemic and also predicted to be at increased transmission risk under future climate change scenarios. Similarly, an expansion of areas in the United States at increased risk for Chagas disease transmission is also expected over the next several decades under climate chan...ge scenarios. Of particular interest is the predicted northern shift of triatomine species to central regions of the United States with historically unsuitable climates for T. cruzi vectors. The weight of evidence regarding the influences climate change may pose on T. cruzi vector species distributions demonstrates the sensitivity of Chagas disease transmission to future climate variability. In order to advance forecasts for the impact climate change may have on Chagas disease transmission in the Americas, it is imperative to
further develop, utilize, and perhaps combine predictive species distribution modeling approaches that integrate accurate, long term data on climate variables, vector species distributions, Chagas disease incidence, as well as other socio-ecological variables.
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