Thinking clearly about social aspects of infectious disease transmission

C Buckee, A Noor, L Sattenspiel - Nature, 2021 - nature.com
Social and cultural forces shape almost every aspect of infectious disease transmission in
human populations, as well as our ability to measure, understand, and respond to …

Deep learning for Covid-19 forecasting: State-of-the-art review.

F Kamalov, K Rajab, AK Cherukuri, A Elnagar… - Neurocomputing, 2022 - Elsevier
The Covid-19 pandemic has galvanized scientists to apply machine learning methods to
help combat the crisis. Despite the significant amount of research there exists no …

The united states covid-19 forecast hub dataset

EY Cramer, Y Huang, Y Wang, EL Ray, M Cornell… - Scientific data, 2022 - nature.com
Academic researchers, government agencies, industry groups, and individuals have
produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage …

Predictive performance of international COVID-19 mortality forecasting models

J Friedman, P Liu, CE Troeger, A Carter… - Nature …, 2021 - nature.com
Forecasts and alternative scenarios of COVID-19 mortality have been critical inputs for
pandemic response efforts, and decision-makers need information about predictive …

A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave

J Bracher, D Wolffram, J Deuschel, K Görgen… - Nature …, 2021 - nature.com
Disease modelling has had considerable policy impact during the ongoing COVID-19
pandemic, and it is increasingly acknowledged that combining multiple models can improve …

Incorporating variant frequencies data into short-term forecasting for COVID-19 cases and deaths in the USA: a deep learning approach

H Du, E Dong, HS Badr, ME Petrone, ND Grubaugh… - Ebiomedicine, 2023 - thelancet.com
Background Since the US reported its first COVID-19 case on January 21, 2020, the science
community has been applying various techniques to forecast incident cases and deaths. To …

Hawkes process modeling of COVID-19 with mobility leading indicators and spatial covariates

WH Chiang, X Liu, G Mohler - International journal of forecasting, 2022 - Elsevier
Hawkes processes are used in statistical modeling for event clustering and causal inference,
while they also can be viewed as stochastic versions of popular compartmental models used …

Evaluation of FluSight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations

SM Mathis, AE Webber, TM León, EL Murray… - Nature …, 2024 - nature.com
Accurate forecasts can enable more effective public health responses during seasonal
influenza epidemics. For the 2021–22 and 2022–23 influenza seasons, 26 forecasting …

Can auxiliary indicators improve COVID-19 forecasting and hotspot prediction?

DJ McDonald, J Bien, A Green, AJ Hu… - Proceedings of the …, 2021 - National Acad Sciences
Short-term forecasts of traditional streams from public health reporting (such as cases,
hospitalizations, and deaths) are a key input to public health decision-making during a …

Improving pandemic response: employing mathematical modeling to confront coronavirus disease 2019

M Biggerstaff, RB Slayton… - Clinical Infectious …, 2022 - academic.oup.com
Modeling complements surveillance data to inform coronavirus disease 2019 (COVID-19)
public health decision making and policy development. This includes the use of modeling to …