【Abstract】The successful introduction of the intracellular bacterium Wolbachia into Aedes aegypti mosquitoes enables a practical approach for dengue prevention through release of Wolbachia-infected mosquitoes. Wolbachia reduces dengue virus replication in the mosquito and, once established in the mosquito population, it is possible that this will provide a long-term and sustainable approach to reducing or eliminating dengue transmission. A critical next step is to assess the efficacy of Wolbachia deployments in reducing dengue virus transmission in the field. We describe and discuss the statistical design of a large-scale cluster randomised test-negative parallel arm study to measure the efficacy of such interventions. Comparison of permutation inferential approaches to model based methods will be described. Extensions to allow for individual covariates, and alternate designs such as the stepped wedge approach, will also be briefly introduced.

【CV】 Nicholas P. Jewell is Professor of Biostatistics and Statistics at the University of California, Berkeley. He was Vice Provost of the Berkeley campus from 1994 to 2000. A native of Scotland, Jewell was educated at the University of Edinburgh where he received a first class Honours degree in Applied Mathematics in 1973 and a PhD in Mathematics in 1976. Jewell is a member of the National Academy of Medicine, Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the American Association for the Advancement of Science (AAAS). In 2012 he was honored by Harvard University as the recipient of the Marvin Zelen Leadership Award in Statistical Science, and in 2016 by the Berkeley Citation from the University of California, Berkeley. Jewell has served on many editorial boards of the leading journals in statistics and biostatistics. He just stepped down as Editor of the Journal of the American Statistical Association. Jewell has published over 150 articles in several prestigious journals in biostatistics, statistics, mathematics, epidemiology, medicine, public health, and history. He is the author of Statistics in Epidemiology and co-author of Causal Inference in Statistics: A Primer, with Judea Pearl and Madelyn Glymour.