Literature DB >> 33292095

Disease control across urban-rural gradients.

Konstans Wells1, Miguel Lurgi1, Brendan Collins2,3, Biagio Lucini4, Rowland R Kao5, Alun L Lloyd6, Simon D W Frost7,8, Mike B Gravenor9.   

Abstract

Controlling the regional re-emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after its initial spread in ever-changing personal contact networks and disease landscapes is a challenging task. In a landscape context, contact opportunities within and between populations are changing rapidly as lockdown measures are relaxed and a number of social activities re-activated. Using an individual-based metapopulation model, we explored the efficacy of different control strategies across an urban-rural gradient in Wales, UK. Our model shows that isolation of symptomatic cases or regional lockdowns in response to local outbreaks have limited efficacy unless the overall transmission rate is kept persistently low. Additional isolation of non-symptomatic infected individuals, who may be detected by effective test-and-trace strategies, is pivotal to reducing the overall epidemic size over a wider range of transmission scenarios. We define an 'urban-rural gradient in epidemic size' as a correlation between regional epidemic size and connectivity within the region, with more highly connected urban populations experiencing relatively larger outbreaks. For interventions focused on regional lockdowns, the strength of such gradients in epidemic size increased with higher travel frequencies, indicating a reduced efficacy of the control measure in the urban regions under these conditions. When both non-symptomatic and symptomatic individuals are isolated or regional lockdown strategies are enforced, we further found the strongest urban-rural epidemic gradients at high transmission rates. This effect was reversed for strategies targeted at symptomatic individuals only. Our results emphasize the importance of test-and-trace strategies and maintaining low transmission rates for efficiently controlling SARS-CoV-2 spread, both at landscape scale and in urban areas.

Entities:  

Keywords:  disease spread; epidemiological metapopulation dynamics; pandemic control; source–sink dynamics

Mesh:

Year:  2020        PMID: 33292095      PMCID: PMC7811581          DOI: 10.1098/rsif.2020.0775

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  26 in total

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Journal:  Nat Hum Behav       Date:  2020-06-04

4.  Virus genomes reveal factors that spread and sustained the Ebola epidemic.

Authors:  Gytis Dudas; Luiz Max Carvalho; Trevor Bedford; Andrew J Tatem; Guy Baele; Nuno R Faria; Daniel J Park; Jason T Ladner; Armando Arias; Danny Asogun; Filip Bielejec; Sarah L Caddy; Matthew Cotten; Jonathan D'Ambrozio; Simon Dellicour; Antonino Di Caro; Joseph W Diclaro; Sophie Duraffour; Michael J Elmore; Lawrence S Fakoli; Ousmane Faye; Merle L Gilbert; Sahr M Gevao; Stephen Gire; Adrianne Gladden-Young; Andreas Gnirke; Augustine Goba; Donald S Grant; Bart L Haagmans; Julian A Hiscox; Umaru Jah; Jeffrey R Kugelman; Di Liu; Jia Lu; Christine M Malboeuf; Suzanne Mate; David A Matthews; Christian B Matranga; Luke W Meredith; James Qu; Joshua Quick; Suzan D Pas; My V T Phan; Georgios Pollakis; Chantal B Reusken; Mariano Sanchez-Lockhart; Stephen F Schaffner; John S Schieffelin; Rachel S Sealfon; Etienne Simon-Loriere; Saskia L Smits; Kilian Stoecker; Lucy Thorne; Ekaete Alice Tobin; Mohamed A Vandi; Simon J Watson; Kendra West; Shannon Whitmer; Michael R Wiley; Sarah M Winnicki; Shirlee Wohl; Roman Wölfel; Nathan L Yozwiak; Kristian G Andersen; Sylvia O Blyden; Fatorma Bolay; Miles W Carroll; Bernice Dahn; Boubacar Diallo; Pierre Formenty; Christophe Fraser; George F Gao; Robert F Garry; Ian Goodfellow; Stephan Günther; Christian T Happi; Edward C Holmes; Brima Kargbo; Sakoba Keïta; Paul Kellam; Marion P G Koopmans; Jens H Kuhn; Nicholas J Loman; N'Faly Magassouba; Dhamari Naidoo; Stuart T Nichol; Tolbert Nyenswah; Gustavo Palacios; Oliver G Pybus; Pardis C Sabeti; Amadou Sall; Ute Ströher; Isatta Wurie; Marc A Suchard; Philippe Lemey; Andrew Rambaut
Journal:  Nature       Date:  2017-04-12       Impact factor: 49.962

5.  Social encounter networks: characterizing Great Britain.

Authors:  Leon Danon; Jonathan M Read; Thomas A House; Matthew C Vernon; Matt J Keeling
Journal:  Proc Biol Sci       Date:  2013-06-26       Impact factor: 5.349

6.  A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2.

Authors:  Tom Britton; Frank Ball; Pieter Trapman
Journal:  Science       Date:  2020-06-23       Impact factor: 47.728

7.  The role of routine versus random movements on the spread of disease in Great Britain.

Authors:  Leon Danon; Thomas House; Matt J Keeling
Journal:  Epidemics       Date:  2009-11-14       Impact factor: 4.396

8.  Spatially explicit models for exploring COVID-19 lockdown strategies.

Authors:  David O'Sullivan; Mark Gahegan; Daniel J Exeter; Benjamin Adams
Journal:  Trans GIS       Date:  2020-06-15

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Authors:  Christopher I Jarvis; Kevin Van Zandvoort; Amy Gimma; Kiesha Prem; Petra Klepac; G James Rubin; W John Edmunds
Journal:  BMC Med       Date:  2020-05-07       Impact factor: 8.775

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Authors:  Luca Ferretti; Chris Wymant; David Bonsall; Christophe Fraser; Michelle Kendall; Lele Zhao; Anel Nurtay; Lucie Abeler-Dörner; Michael Parker
Journal:  Science       Date:  2020-03-31       Impact factor: 47.728

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  2 in total

Review 1.  Risk Perceptions, Knowledge and Behaviors of General and High-Risk Adult Populations Towards COVID-19: A Systematic Scoping Review.

Authors:  Nathalie Clavel; Janine Badr; Lara Gautier; Mélanie Lavoie-Tremblay; Jesseca Paquette
Journal:  Public Health Rev       Date:  2021-11-15

2.  Disruption of Metapopulation Structure Reduces Tasmanian Devil Facial Tumour Disease Spread at the Expense of Abundance and Genetic Diversity.

Authors:  Rowan Durrant; Rodrigo Hamede; Konstans Wells; Miguel Lurgi
Journal:  Pathogens       Date:  2021-12-08
  2 in total

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