Computing human to human Avian influenza $\mathcal{R}_0$ via transmission chains and parameter estimation

Omar Saucedo; Maia Martcheva; Abena Annor; Omar Saucedo; Maia Martcheva; Abena Annor

doi:10.3934/mbe.2019174

Mathematical Biosciences and Engineering

2019, Volume 16, Issue 5: 3465-3487. doi: 10.3934/mbe.2019174

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Computing human to human Avian influenza $\mathcal{R}_0$ via transmission chains and parameter estimation

1.
Mathematical Biosciences Institute, The Ohio State University, Columbus, OH 43210, USA
2.
Department of Mathematics, University of Florida, Gainesville, FL 32611, USA
3.
Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA

Received: 14 February 2019 Accepted: 10 April 2019 Published: 19 April 2019

The transmission of avian influenza between humans is extremely rare, and it mostly affects individuals who are in contact with infected family member. Although this scenario is uncommon, there have been multiple outbreaks that occur in small infection clusters in Asia with relatively lowtransmissibility, and thus are too weak to cause an epidemic. Still, subcritical transmission from stut-tering chain data is vital for determining whether avian influenza is close to the threshold of $\mathcal{R}_0$ > 1.In this article, we will explore two methods of estimating $\mathcal{R}_0$ using transmission chains and parameterestimation through data fitting. We found that $\mathcal{R}_0$ = 0.2205 when calculating the $\mathcal{R}_0$ using the maxi-mum likelihood method. When we computed the reproduction number for human to human transmis-sion through differential equations and fitted the model to data from the cumulative cases, cumulativedeaths, and cumulative secondary cases, we estimated $\mathcal{R}_0$ = 0.1768. To avoid violating the assumptionof the least square method, we fitted the model to incidence data to obtain $\mathcal{R}_0$ = 0.1520. We tested thestructural and practical identifiability of the model, and concluded that the model is identifiable undercertain assumptions. We further use two more methods to estimate $\mathcal{R}_0$ : by the $\mathcal{R}_0$ definition whichgives an overestimate of 0.28 and by Ferguson approach which yields $\mathcal{R}_0$ = 0.1586. We conclude that $\mathcal{R}_0$ for human to human transmission was about 0.2.
- avian influenza,
- transmission chains,
- identifiability,
- parameter estimation,
- basic reproduction number
Citation: Omar Saucedo, Maia Martcheva, Abena Annor. Computing human to human Avian influenza $\mathcal{R}_0$ via transmission chains and parameter estimation[J]. Mathematical Biosciences and Engineering, 2019, 16(5): 3465-3487. doi: 10.3934/mbe.2019174

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Abstract

The transmission of avian influenza between humans is extremely rare, and it mostly affects individuals who are in contact with infected family member. Although this scenario is uncommon, there have been multiple outbreaks that occur in small infection clusters in Asia with relatively lowtransmissibility, and thus are too weak to cause an epidemic. Still, subcritical transmission from stut-tering chain data is vital for determining whether avian influenza is close to the threshold of $\mathcal{R}_0$ > 1.In this article, we will explore two methods of estimating $\mathcal{R}_0$ using transmission chains and parameterestimation through data fitting. We found that $\mathcal{R}_0$ = 0.2205 when calculating the $\mathcal{R}_0$ using the maxi-mum likelihood method. When we computed the reproduction number for human to human transmis-sion through differential equations and fitted the model to data from the cumulative cases, cumulativedeaths, and cumulative secondary cases, we estimated $\mathcal{R}_0$ = 0.1768. To avoid violating the assumptionof the least square method, we fitted the model to incidence data to obtain $\mathcal{R}_0$ = 0.1520. We tested thestructural and practical identifiability of the model, and concluded that the model is identifiable undercertain assumptions. We further use two more methods to estimate $\mathcal{R}_0$ : by the $\mathcal{R}_0$ definition whichgives an overestimate of 0.28 and by Ferguson approach which yields $\mathcal{R}_0$ = 0.1586. We conclude that $\mathcal{R}_0$ for human to human transmission was about 0.2.

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