Literature DB >> 23665296

The scaling of contact rates with population density for the infectious disease models.

Hao Hu1, Karima Nigmatulina, Philip Eckhoff.   

Abstract

Contact rates and patterns among individuals in a geographic area drive transmission of directly-transmitted pathogens, making it essential to understand and estimate contacts for simulation of disease dynamics. Under the uniform mixing assumption, one of two mechanisms is typically used to describe the relation between contact rate and population density: density-dependent or frequency-dependent. Based on existing evidence of population threshold and human mobility patterns, we formulated a spatial contact model to describe the appropriate form of transmission with initial growth at low density and saturation at higher density. We show that the two mechanisms are extreme cases that do not capture real population movement across all scales. Empirical data of human and wildlife diseases indicate that a nonlinear function may work better when looking at the full spectrum of densities. This estimation can be applied to large areas with population mixing in general activities. For crowds with unusually large densities (e.g., transportation terminals, stadiums, or mass gatherings), the lack of organized social contact structure deviates the physical contacts towards a special case of the spatial contact model - the dynamics of kinetic gas molecule collision. In this case, an ideal gas model with van der Waals correction fits well; existing movement observation data and the contact rate between individuals is estimated using kinetic theory. A complete picture of contact rate scaling with population density may help clarify the definition of transmission rates in heterogeneous, large-scale spatial systems.
Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Contact rate; Crowd dynamics; Epidemic model; Population density; Transmission scaling

Mesh:

Year:  2013        PMID: 23665296     DOI: 10.1016/j.mbs.2013.04.013

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  61 in total

1.  Endogenous social distancing and its underappreciated impact on the epidemic curve.

Authors:  Marko Gosak; Moritz U G Kraemer; Heinrich H Nax; Matjaž Perc; Bary S R Pradelski
Journal:  Sci Rep       Date:  2021-02-04       Impact factor: 4.379

2.  Concerns for others increases the likelihood of vaccination against influenza and COVID-19 more in sparsely rather than densely populated areas.

Authors:  Haesung Jung; Dolores Albarracín
Journal:  Proc Natl Acad Sci U S A       Date:  2020-12-18       Impact factor: 11.205

3.  COVID-19 outbreak on the Diamond Princess cruise ship: estimating the epidemic potential and effectiveness of public health countermeasures.

Authors:  J Rocklöv; H Sjödin; A Wilder-Smith
Journal:  J Travel Med       Date:  2020-05-18       Impact factor: 8.490

4.  The impact of shared sanitation facilities on diarrheal diseases with and without an environmental reservoir: a modeling study.

Authors:  Matthew R Just; Stephen W Carden; Sheng Li; Kelly K Baker; Manoj Gambhir; Isaac Chun-Hai Fung
Journal:  Pathog Glob Health       Date:  2018-06-06       Impact factor: 2.894

5.  Integrated vaccination and physical distancing interventions to prevent future COVID-19 waves in Chinese cities.

Authors:  Bo Huang; Jionghua Wang; Jixuan Cai; Shengjie Lai; Shiqi Yao; Paul Kay Sheung Chan; Tony Hong-Wing Tam; Ying-Yi Hong; Corrine W Ruktanonchai; Alessandra Carioli; Jessica R Floyd; Nick W Ruktanonchai; Weizhong Yang; Zhongjie Li; Andrew J Tatem
Journal:  Nat Hum Behav       Date:  2021-02-18

6.  The Uromodulin Gene Locus Shows Evidence of Pathogen Adaptation through Human Evolution.

Authors:  Silvia Ghirotto; Francesca Tassi; Guido Barbujani; Linda Pattini; Caroline Hayward; Peter Vollenweider; Murielle Bochud; Luca Rampoldi; Olivier Devuyst
Journal:  J Am Soc Nephrol       Date:  2016-03-10       Impact factor: 10.121

7.  The density paradox: Are densely-populated regions more vulnerable to Covid-19?

Authors:  Imad A Moosa; Ibrahim N Khatatbeh
Journal:  Int J Health Plann Manage       Date:  2021-05-18

8.  On the heterogeneous spread of COVID-19 in Chile.

Authors:  Danton Freire-Flores; Nyna Llanovarced-Kawles; Anamaria Sanchez-Daza; Álvaro Olivera-Nappa
Journal:  Chaos Solitons Fractals       Date:  2021-06-12       Impact factor: 5.944

9.  Using Constrained Optimization for the Allocation of COVID-19 Vaccines in the Philippines.

Authors:  Christian Alvin H Buhat; Destiny S M Lutero; Yancee H Olave; Kemuel M Quindala; Mary Grace P Recreo; Dylan Antonio S J Talabis; Monica C Torres; Jerrold M Tubay; Jomar F Rabajante
Journal:  Appl Health Econ Health Policy       Date:  2021-06-25       Impact factor: 2.561

10.  The impact of super-spreader cities, highways, and intensive care availability in the early stages of the COVID-19 epidemic in Brazil.

Authors:  Miguel A L Nicolelis; Rafael L G Raimundo; Pedro S Peixoto; Cecilia S Andreazzi
Journal:  Sci Rep       Date:  2021-06-21       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.