scispace - formally typeset
H

Hugh J. W. Sturrock

Researcher at University of California, San Francisco

Publications -  77
Citations -  3039

Hugh J. W. Sturrock is an academic researcher from University of California, San Francisco. The author has contributed to research in topics: Malaria & Population. The author has an hindex of 24, co-authored 68 publications receiving 2445 citations. Previous affiliations of Hugh J. W. Sturrock include University of London & University of California, Berkeley.

Papers
More filters
Journal ArticleDOI

The changing epidemiology of malaria elimination: new strategies for new challenges

TL;DR: The shift in the populations most at risk of malaria raises important questions for malaria-eliminating countries, since traditional control interventions are likely to be less effective.
Journal ArticleDOI

Targeting asymptomatic malaria infections: active surveillance in control and elimination.

TL;DR: It is argued that the evidence for its effectiveness is sparse and that targeted mass drug administration should be evaluated as an alternative or addition to active case detection.
Journal ArticleDOI

Communicating and Monitoring Surveillance and Response Activities for Malaria Elimination: China's “1-3-7” Strategy

TL;DR: China's 1-3-7 strategy for eliminating malaria is described: reporting of malaria cases within one day, their confirmation and investigation within three days, and the appropriate public health response to prevent further transmission within seven days.
Journal ArticleDOI

Spatial modelling of soil-transmitted helminth infections in Kenya: a disease control planning tool.

TL;DR: Bayesian space-time geostatistical models can be used to reliably estimate the combined observed prevalence of STH and suggest that a quarter of Kenya's school-aged children live in areas of high prevalence and warrant mass treatment.
Journal ArticleDOI

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

TL;DR: The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources to better understand many of the Earth’s land surface processes.