ArticlePloS one2017
Effects of reactive social distancing on the 1918 influenza pandemic.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A scoping review of COVID-19 modelling studies in Belgium 2020-2024: incorporation of behaviour and lessons learned.Archives of public health = Archives belges de sante publique · 2026Pooled it
- Optimal social distancing in epidemic control: cost prioritization, adherence and insights into preparedness principles.Scientific reports · 2024Article
- Business as (un)usual: A qualitative study of clerkship experiences during a health crisis.Medical education · 2022Article
- Closed-form expressions and nonparametric estimation of COVID-19 infection rate.Automatica : the journal of IFAC, the International Federation of Automatic Control · 2022Article
- Youth athletes sleep more, practice less, and may lose interest in playing sports due to social distancing mandates.Preventive medicine reports · 2022Article
- Social Distancing in Relation to Severe Exacerbations of Chronic Obstructive Pulmonary Disease: A Nationwide Semi-Experimental Study During the COVID-19 Pandemic.American journal of epidemiology · 2022Observational
- Social distancing and bacteraemia in the time of COVID-19.Internal medicine journal · 2022Article
- Impact of non-pharmaceutical interventions on the incidences of vaccine-preventable diseases during the COVID-19 pandemic in the eastern of China.Human vaccines & immunotherapeutics · 2021Article
- Tracking the time course of reproduction number and lockdown's effect on human behaviour during SARS-CoV-2 epidemic: nonparametric estimation.Scientific reports · 2021Article
- Exploring the growth of COVID-19 cases using exponential modelling across 42 countries and predicting signs of early containment using machine learning.Transboundary and emerging diseases · 2021Article
- The Effect of Chronic Diseases, Age and Gender on Morbidity and Mortality of COVID-19 Infection.Iranian journal of public health · 2021Article
- Mobile Phone GPS Data and Prevalence of COVID-19 Infections: Quantifying Parameters of Social Distancing in the U.S.The archives of bone and joint surgery · 2021Article
- The Cyclicity of coronavirus cases: "Waves" and the "weekend effect".Chaos, solitons, and fractals · 2021Article
- Dynamic coupling between the COVID-19 epidemic timeline and the behavioral response to PAUSE in New York State counties.PloS one · 2021Article
- Assessing effects of reopening policies on COVID-19 pandemic in Texas with a data-driven transmission model.Infectious Disease Modelling · 2021Article
- Social distanciation through COVID-19: A narrative analysis of Indian Peri-Urban Elderly.Social sciences & humanities open · 2021Article
- Impact of Wearing Masks, Hand Hygiene, and Social Distancing on Influenza, Enterovirus, and All-Cause Pneumonia During the Coronavirus Pandemic: Retrospective National Epidemiological Surveillance Study.Journal of medical Internet research · 2020Article
- No Place Like Home: Cross-National Data Analysis of the Efficacy of Social Distancing During the COVID-19 Pandemic.JMIR public health and surveillance · 2020Article
- Strategic decision making about travel during disease outbreaks: a game theoretical approach.Journal of the Royal Society, Interface · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The 1918 influenza pandemic was characterized by multiple epidemic waves. We investigated reactive social distancing, a form of behavioral response where individuals avoid potentially infectious contacts in response to available information on an ongoing epidemic or pandemic. We modelled its effects on the three influenza waves in the United Kingdom. In previous studies, human behavioral response was modelled by a Power function of the proportion of recent influenza mortality in a population, and by a Hill function, which is a function of the number of recent influenza mortality. Using a simple epidemic model with a Power function and one common set of parameters, we provided a good model fit for the observed multiple epidemic waves in London boroughs, Birmingham and Liverpool. We further applied the model parameters from these three cities to all 334 administrative units in England and Wales and including the population sizes of individual administrative units. We computed the Pearson's correlation between the observed and simulated for each administrative unit. We found a median correlation of 0.636, indicating that our model predictions are performing reasonably well. Our modelling approach is an improvement from previous studies where separate models are fitted to each city. With the reduced number of model parameters used, we achieved computational efficiency gain without over-fitting the model. We also showed the importance of reactive behavioral distancing as a potential non-pharmaceutical intervention during an influenza pandemic. Our work has both scientific and public health significance.
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