Publications

A dynamic, ensemble learning approach to forecast dengue fever epidemic years in Brazil using weather and population susceptibility cycles.

Author(s): McGough SF, Clemente L, Kutz JN, Santillana MJournal: J R Soc InterfacePMID: 34129785 June 2021

Transmission of dengue fever depends on a complex interplay of human, climate and mosquito dynamics, which often change in time…

Nowcasting for Real-Time COVID-19 Tracking in New York City: Evaluation Study Using Reportable Disease Data From the Early Stages of the Pandemic.

Author(s): Greene SK, McGough SF, Culp GM, Graf LE, Lipsitch M, Menzies NA, Kahn RJournal: JMIR Public Health SurveillPMID: 33406053 January 2021

Nowcasting approaches enhance the utility of reportable disease data for trend monitoring by correcting for delays, but implementation details affect…

Rates of increase of antibiotic resistance and ambient temperature in Europe: a cross-national analysis of 28 countries between 2000 and 2016.

Author(s): McGough SF, MacFadden DR, Hattab MW, Mølbak K, Santillana MJournal: Euro SurveillPMID: 33183408 November 2020

BackgroundThe rapid increase of bacterial antibiotic resistance could soon render our most effective method to address infections obsolete. Factors influencing…

A dynamic, ensemble learning approach to forecast dengue fever epidemic years in Brazil using weather and population susceptibility cycles.

Nowcasting for Real-Time COVID-19 Tracking in New York City: Evaluation Study Using Reportable Disease Data From the Early Stages of the Pandemic.

Rates of increase of antibiotic resistance and ambient temperature in Europe: a cross-national analysis of 28 countries between 2000 and 2016.

Evaluation of Nowcasting for Real-Time COVID-19 Tracking – New York City, March-May 2020.

Real-time estimation of disease activity in emerging outbreaks using internet search information.

Nowcasting by Bayesian Smoothing: A flexible, generalizable model for real-time epidemic tracking.