Archive for Bayesian geostatistics

postdoctoral position on the Malaria Atlas Project, Oxford [advert]

Posted in pictures, Statistics, Travel, University life with tags , , , , , on September 21, 2018 by xi'an

The Malaria Atlas Project is opening a postdoctoral position in Oxford in geospatial modelling toward collaborating with other scientists to develop probabilistic maps of malaria risk at national and sub-national level to evaluate the efficacy of past intervention strategies and to assist with the planning of future interventions. An understanding of spatiotemporal modelling and expertise in geostatistics, random-field models, or equivalent are essential. An understanding of the epidemiology of a vector-borne disease such as malaria is desirable but not essential. You must have a PhD or equivalent experience in mathematics, statistics, biostatistics, or a similar quantitative discipline.

You will contribute to and, as appropriate, lead in the preparation of scientific reports and journal articles for publication of research findings from this work in open access journals. Travel to collaborators in Europe, the United States, Africa, and Asia will be part of the role.

This full-time position is fixed-term until 31 December 2019 in the first instance. The closing date for this position will be 12.00 noon on Wednesday 17 October 2018.

Bayesian maps of Africa

Posted in pictures, Statistics with tags , , , , , , on March 21, 2018 by xi'an

A rather special issue of Nature this week (1 March 2018) as it addresses Bayesian geo-cartography and mapping childhood growth failure and educational achievement (along with sexual differences) all across Africa! Including the (nice) cover of the journal, a preface by Kofi Annan, a cover article by Brian Reich and Murali Haran, and the first two major articles of the journal, one of which includes Ewan Cameron as a co-author. As I was reading this issue of Nature in the train back from Brussels, I could not access the supplementary material, so could not look at the specifics of the statistics, but the maps look quite impressive with a 5×5 km² resolution. And inclusion not only of uncertainty maps but also of predictive maps on the probability of achieving WHO 2025 goals. Surprisingly close to one in some parts of Africa. In terms of education, there are strong oppositions between different regions, with the south of the continent, including Madagascar, showing a positive difference for women in terms of years of education. While there is no reason (from my train seat) to doubt the statistical analyses, I take quite seriously the reservation of the authors that the quality of the prediction cannot be better than the quality of the data, which is “determined by the volume and fidelity of nationally representative surveys”. Which relates to an earlier post of mine about a similar concern with the deaths in Congo.