The Barcelona Institute for Global Health (ISGlobal) is a cutting-edge institute addressing global public health challenges through research, translation into policy and education. ISGlobal has a broad portfolio in communicable and non-communicable diseases including environmental and climate determinants, and applies a multidisciplinary scientific approach ranging from the molecular to the population level. Research is organized in five programs: Climate, Air Pollution, Nature and Urban Health; Environment and Health over the Lifecourse; Global Viral and Bacterial Infections; Malaria and Neglected Parasitic Diseases and Maternal Child and Reproductive Health. ISGlobal is accredited with the Severo Ochoa distinction, a seal of excellence of the Spanish Science Ministry.

What We Are Looking for
The Climate and Health Group (led by ICREA Professor Xavier Rodó) invites applications for a postdoctoral position (exceptional PhD candidates may also be considered) in the area of mathematical modelling of vectorborne diseases and in general, the epidemiological dynamics of communicable diseases. The position is full-time available immediately and for a fixed-term period of 24 months (1+1 year after successful evaluation) with the possibility of further extensions.


We are seeking a highly motivated individual with a degree (PhD) in mathematics, physics, engineering, computer science, meteorology or theoretical ecology. A broad interest in natural sciences and more specifically in ecology is essential. We are looking for candidates motivated by science with the ability to run simulations and eventually help develop code and to integrate scientific knowledge into numerical schemes.

Project Code: ARBOTHAI Multi-scale seamless prediction of arboviral outbreaks in Thailand WELLCOME TRUST Grant Number UNS138749.


About the postdoctoral position
At a time when Bangladesh and Brazil are facing dengue epidemics on an unprecedented scale, the question of monitoring and controlling arboviral diseases has never seemed so urgent in endemic regions. Arboviral diseases are seen to be strongly conditioned by climate, essentially through the modulation of the vector population and the vectorial capacity. Skill exists for these diseases and regions and it can be incorporated into actionable alert systems for enhanced seasonal incidences.

However, despite the scarcity of actionable Early-Warning Systems available for forecasting infectious diseases driven by climate, a recent report identified vector borne diseases as being the target of most of those tools. A closer inspection, though, indicates that prediction models that can be used on an operational basis are lacking and their skill for out-of-fit prediction is limited. To this end, the present project intend to adapt a formerly developed platform for arboviral risk prediction in Catalonia (Spain), named ARBOCAT (www.arbocat.org) to a fully endemic country, Thailand, to be used as an operational prediction tool for national stakeholders at the scale of the 77 provinces in Thailand and also locally in Bangkok. To this end, we will adapt the current model architecture in ARBOCAT to work in ARBOTHAI and we will use for ARBOBANG an urban climate model to downscale it to a 200-m resolution in Bangkok.


Similarly, recent studies published point to a contraction of malaria-prone regions in Africa due to the future rising in continental temperatures beyond the optimal conditions for vector liveability. The studies to be conducted aim to either challenge those results or eventually confirm.