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.

## Archive for epidemiology

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

Posted in pictures, Statistics, Travel, University life with tags Bayesian geostatistics, epidemiology, malaria, Malaria Atlas Project, postdoctoral position, University of Oxford on September 21, 2018 by xi'an## ABC [almost] in the front news

Posted in pictures, Statistics, University life with tags ABC, Badger Trust, badgers, Britain, cattle, cows, England, epidemiology, media, SMC-ABC, summary statistics, TB, The Guardian, tuberculosis, University of Warwick on July 7, 2014 by xi'an**M**y friend and Warwick colleague Gareth Roberts just published a paper in Nature with Ellen Brooks-Pollock and Matt Keeling from the University of Warwick on the modelling of bovine tuberculosis dynamics in Britain and on the impact of control measures. The data comes from the Cattle Tracing System and the VetNet national testing database. The mathematical model is based on a stochastic process and its six parameters are estimated by sequential ABC (SMC-ABC). The summary statistics chosen in the model are the number of infected farms per county per year and the number of reactors (cattle failing a test) per county per year.

“Therefore, we predict that control of local badger populations and hence control of environmental transmission will have a relatively limited effect on all measures of bovine TB incidence.”

**T**his advanced modelling of a comprehensive dataset on TB in Britain quickly got into a high profile as it addresses the highly controversial (not to say plain stupid) culling of badgers (who also carry TB) advocated by the government. The study concludes that “only generic measures such as more national testing, whole herd culling or vaccination that affect all routes of transmission are effective at controlling the spread of bovine TB.” While the elimination of badgers from the English countryside would have a limited effect. Good news for badgers! And the Badger Trust. Unsurprisingly, the study was immediately rejected by the UK farming minister! Not only does he object to the herd culling solution for economic reasons, but he “cannot accept the paper’s findings”. Maybe he does not like ABC… More seriously, the media oversimplified the findings of the study, “as usual”, with e.g. The Guardian headline of “tuberculosis threat requires mass cull of cattle”.

## epidemiology in Le Monde

Posted in Books, Statistics, University life with tags Académie de Médecine, causality, epidemiology, impact factor, INSERM, John Maynard Keynes, Le Monde, R.A. Fisher, Science, Statistics on February 19, 2012 by xi'an**Q**uite an interesting weekend *Le Monde* issue: a fourth (2 pages!) of the science folder is devoted to epidemiology… In the statistical sense. (The subtitle is actually *Strengths and limitations of Statistics*.) The paper does not delve into technical statistical issues but points out the logical divergence between a case-by-case study and an epidemiological study. The impression that the higher the conditioning (i.e. the more covariates), the better the explanation is a statistical fallacy some of the opponents interviewed in the paper do not grasp. (Which reminded me of Keynes seemingly going the same way.) The short paragraph written on causality and Hill’s criteria is vague enough to concur to the overall remark that causality can never been proved or disproved… The fourth examples illustrating the strengths and limitations are tobacco *vs.* lung cancer, a clear case except for R.A. Fisher!, mobile phones *vs.* brain tumors, a not yet conclusive setting, hepatitis B vaccine *vs.* sclerosis, lacking data (the pre-2006 records were destroyed for legal reasons), and leukemia *vs.* nuclear plants, with a significant [?!] correlation between the number of cases and the distance to a nuclear plant. *(The paper was inspired by a report recently published by the French Académie de Médecine on epidemiology in France.)* The science folder also includes a review of a recent Science paper by Wilhite and Fong on the coercive strategies used by some journals/editors to increase their impact factor, e.g., “you cite *Leukemia* [once in 42 references]. Consequently, we kindly ask you to add references of articles published in *Leukemia* to your present article”.

## the cult of significance

Posted in Books, Statistics, University life with tags Bayesian decision theory, book review, econometrics, economics, epidemiology, Error and Inference, Jean-Paul Sartre, loss functions, power, psychometrics, R.A. Fisher, Significance, testing of hypotheses, W. Gosset on October 18, 2011 by xi'an“

Statistical significance is not a scientific test. It is a philosophical, qualitative test. It asks “whether”. Existence, the question of whether, is interesting. But it is not scientific.” S. Ziliak and D. McCloskey, p.5

**T**he book, written by economists Stephen Ziliak and Deirdre McCloskey, has a theme bound to attract Bayesians and all those puzzled by the absolute and automatised faith in significance tests. The main argument of the authors is indeed that an overwhelming majority of papers stop at rejecting variables (“coefficients”) on the sole and unsupported basis of non-significance at the 5% level. Hence the subtitle “*How the standard error costs us jobs, justice, and lives*“… This is an argument I completely agree with, however, the aggressive style of the book truly put me off! As with * Error and Inference*, which also addresses a non-Bayesian issue, I could have let the matter go, however I feel the book may in the end be counter-productive and thus endeavour to explain why through this review.

*(I wrote the following review in batches, before and during my trip to Dublin, so the going is rather broken, I am afraid…)*Continue reading

## Numbers rule your world

Posted in Books, Statistics with tags Bayes theorem, credit scoring, epidemiology, False positive, Fung, popular science, queuing theory, randomness, struck by lightning, Taleb, The Black Swan, variability on February 22, 2010 by xi'an**A**ndrew Gelman gave me a copy of the recent book ** Numbers rule your world** by Kaiser Fung, along with the comment that it was a nice book but not for us. I spend my “lazy Sunday” morning reading the book at the breakfast table and agree with Andrew on his assessment. (waiting for the incoming blog review!).

**is unlikely to bring enlightment to professional or academic statisticians, but it provides a nice and soft introduction to the use of statistics in everyday’s life, to the point I would encourage my second and third year students to read it. It covers a few topics that are central to Statistics via ten newspaper-ised stories that make for a very light read, but nonetheless make the point. The themes in**

*Numbers rule your world***are**

*Numbers rule your world*- variability matters more than average, as illustrated by queuing phenomena;
- correlation is not causation, but is often good enough to uncover patterns, as illustrated by epidemiology and credit scoring;
- Simpson’s paradox explains for apparent bias in group differences, as illustrated by SAT score differences between black students and white students;
- false positives and false negatives have different impacts on the error (here comes Bayes theorem!), depending on population sizes and settings, as illustrated by the (great!) case of cheating athletes and polygraph tests (with a reference to Steve Fienberg‘s work);
- extreme events may exhibit causes, or not, as illustrated by a cheating lottery case (involving Jeff Rosenthal as the expert, not the cheater!) and a series of air crashes.

The overall tone of ** Numbers rule your world **is pleasant and engaging, at the other end of the stylistic spectrum from Taleb’s

**. Fung’s point is obviously the opposite of Taleb‘s: he is showing the reader how well statistical modelling can explain for apparently paradoxical behaviour. Fung is also adopting a very neutral tone, again a major change from Taleb, maybe being even too positive (no the only mention is made of the current housing crisis in the pages**

*Black Swan***dedicates to credit scoring comes in the conclusion, pp. 176-7). Now, in terms of novelty, I cannot judge of the amount of innovation when compared with (numerous) other popular science books on the topic. For instance, I think Jeff Rosenthal’s**

*Numbers rule your world***brings a rather deeper perspective, but maybe thus restricts the readership further…**

*Struck by Lightning*