Predicting the issuance of COVID-19 stay-at-home orders in Africa: Using machine learning to develop insight for health policy research-Reference-Cited by-同舟云学术

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Predicting the issuance of COVID-19 stay-at-home orders in Africa: Using machine learning to develop insight for health policy research

Published:2023-04 Issue: Volume:88 Page:103598
ISSN:2212-4209
Container-title:International Journal of Disaster Risk Reduction
language:en
Short-container-title:International Journal of Disaster Risk Reduction

Author:

Mansell Jordan^ORCID,Lee Rhea Carter^ORCID,Murray Gregg R.^ORCID

Publisher

Elsevier BV

Subject

Geology,Safety Research,Geotechnical Engineering and Engineering Geology,Building and Construction

Reference57 articles.

1. State, Territorial, and County COVID-19 Orders and Proclamations for Individuals to Stay Home,2020

2. Evaluating the impact of stay-at-home orders on the time to reach the peak burden of Covid-19 cases and deaths: does timing matter?;Medline;BMC Publ. Health,2020

3. Timing of state and territorial COVID-19 stay-at-home orders and changes in population movement—United States, March 1–May 31, 2020;Moreland;MMWR (Morb. Mortal. Wkly. Rep.),2020

4. Big Data, new epistemologies and paradigm shifts;Kitchin;Big Data & Society,2014

5. Social science data analysis: the ethical imperative;Scime,2013

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The effects of COVID-19 on domestic and international security in democratic and authoritarian regimes;Politics and the Life Sciences;2023-10-12

2. Risk Messages, Form, and Context;Risk and Crisis Communication During the COVID-19 Pandemic;2023-08-11

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