Evidence map›Paper›PMID 33910670›Full record

ArticleEpidemiology and infection2021

Use of the Hayami diffusive wave equation to model the relationship infected-recoveries-deaths of Covid-19 pandemic.

Roger Moussa, Samer Majdalani

Abstract read
In one paragraph

Article in Epidemiology and infection, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Roger MoussaLISAH, Univ. Montpellier, INRAE, IRD, Montpellier SupAgro, Montpellier, France.ORCID 0000-0003-0869-6172
Samer MajdalaniHSM, CNRS, IRD, Univ. Montpellier, Montpellier, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Susceptible S-Infected I-Recovered R-Death D (SIRD) compartmental models are often used for modelling of infectious diseases. On the basis of the analogy between SIRD and compartmental models in hydrology, this study makes mathematical formulations developed in hydrology available for modelling in epidemiology. We adapt the Hayami model solution of the diffusive wave equation generally used in hydrological modelling to compartmental I-R-D models in epidemiology by simulating the relationships between the number of infectious I(t), the number of recoveries R(t) and the number of deaths D(t). The Hayami model is easy-to-use, robust and parsimonious. We compare the empirical one-parameter exponential model usually used in SIRD models to the two-parameter Hayami model. Applications were implemented on the recent Covid-19 pandemic. The application on data from 24 countries shows that both models give comparable performances for modelling the I-D relationship. However, for modelling the I-R relationship and the active cases, the exponential model gives fair performances whereas the Hayami model substantially improves the model performances. The Hayami model also presents the advantage that its parameters can be easily estimated from the analysis of the data distributions of I(t), R(t) and D(t). The Hayami model is parsimonious with only two parameters which are useful to compare the temporal evolution of recoveries and deaths in different countries based on different contamination rates and recoveries strategies. This study highlights the interest of knowledge transfer between different scientific disciplines in order to model different processes.

Indexed as

Models, StatisticalCOVID-19Global HealthHumansHydrologySARS-CoV-2Coronavirus Covid-19diffusive wave equationepidemiologyHayami kernel functionhydraulichydrologySIRD compartmental modelsunit hydrograph

Identifiers

PMID33910670
PMCPMC8207560

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.