Dataset Information

A mathematical model for Zika virus transmission dynamics with a time-dependent mosquito biting rate.

ABSTRACT:

Background

Mathematical modeling has become a tool used to address many emerging diseases. One of the most basic and popular modeling frameworks is the compartmental model. Unfortunately, most of the available compartmental models developed for Zika virus (ZIKV) transmission were designed to describe and reconstruct only past, short-time ZIKV outbreaks in which the effects of seasonal change to entomological parameters can be ignored. To make an accurate long-term prediction of ZIKV transmission, the inclusion of seasonal effects into an epidemic model is unavoidable.

Methods

We developed a vector-borne compartmental model to analyze the spread of the ZIKV during the 2015-2016 outbreaks in Bahia, Brazil and to investigate the impact of two vector control strategies, namely, reducing mosquito biting rates and reducing mosquito population size. The model considered the influences of seasonal change on the ZIKV transmission dynamics via the time-varying mosquito biting rate. The model was also validated by comparing the model prediction with reported data that were not used to calibrate the model.

Results

We found that the model can give a very good fit between the simulation results and the reported Zika cases in Bahia (R-square?=?0.9989). At the end of 2016, the total number of ZIKV infected people was predicted to be 1.2087 million. The model also predicted that there would not be a large outbreak from May 2016 to December 2016 due to the decrease of the susceptible pool. Implementing disease mitigation by reducing the mosquito biting rates was found to be more effective than reducing the mosquito population size. Finally, the correlation between the time series of estimated mosquito biting rates and the average temperature was also suggested.

Conclusions

The proposed ZIKV transmission model together with the estimated weekly biting rates can reconstruct the past long-time multi-peak ZIKV outbreaks in Bahia.

SUBMITTER: Suparit P

PROVIDER: S-EPMC6069545 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Publications

A mathematical model for Zika virus transmission dynamics with a time-dependent mosquito biting rate.

Suparit Parinya P Wiratsudakul Anuwat A Modchang Charin C

Theoretical biology & medical modelling 20180801 1

<h4>Background</h4>Mathematical modeling has become a tool used to address many emerging diseases. One of the most basic and popular modeling frameworks is the compartmental model. Unfortunately, most of the available compartmental models developed for Zika virus (ZIKV) transmission were designed to describe and reconstruct only past, short-time ZIKV outbreaks in which the effects of seasonal change to entomological parameters can be ignored. To make an accurate long-term prediction of ZIKV tran ...[more]

PMID: 30064447

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Project description:The yellow fever mosquito, Aedes aegypti, serves as the primary vector for epidemic transmission of yellow fever, dengue, Zika (ZIKV), and chikungunya viruses to humans. Control of Ae. aegypti is currently limited to insecticide applications and larval habitat management; however, to combat growing challenges with insecticide resistance, novel genetic approaches for vector population reduction or transmission interruption are being aggressively pursued. The objectives of this study were to assess the ability of the Ae. aegypti antiviral exogenous-small interfering RNA (exo-siRNA) response to inhibit ZIKV infection and transmission, and to identify the optimal RNA interference (RNAi) target region in the ZIKV genome. We accomplished these objectives by in vitro transcription of five long double-stranded RNAs (dsRNAs) from the genome region spanning the NS2B-NS3-NS4A genes, which were the most highly conserved among ZIKV RNA sequences representing both East and West African and Asian-American clades, and evaluation of the ability of these dsRNAs to trigger an effective antiviral exo-siRNA response after intrathoracic injection into Ae. aegypti. In a pilot study, five ZIKV dsRNAs were tested by intrathoracic inoculation of 250?ng dsRNA into groups of approximately 5-day-old mosquitoes. Three days post-inoculation, mosquitoes were provided an infectious blood-meal containing ZIKV strain PRVABC59 (Puerto Rico), MR766 (Uganda), or 41525 (Senegal). On days 7 and 14 post-infection individual whole mosquito bodies were assessed for ZIKV infectious titer by plaque assays. Based on the results of this initial assessment, three dsRNAs were selected for further evaluation of viral loads of matched body and saliva expectorants using a standardized infectious dose of 1?×?107?PFU/mL of each ZIKV strain. Fourteen days post-exposure to ZIKV, paired saliva and carcass samples were harvested from individual mosquitoes and assessed for ZIKV RNA load by qRT-PCR. Injection of each of the three dsRNAs resulted in significant inhibition of replication of all three strains of ZIKV in mosquito bodies and saliva. This study lays critical groundwork for pursuing ZIKV transmission-blocking strategies that exploit the Ae. aegypti exo-siRNA response for arbovirus suppression in natural populations.

Dataset Information

A mathematical model for Zika virus transmission dynamics with a time-dependent mosquito biting rate.

Background

Methods

Results

Conclusions

Publications

A mathematical model for Zika virus transmission dynamics with a time-dependent mosquito biting rate.

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