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TropicalMed
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Advancing Mathematical Models of Mosquito-Borne Diseases
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Advancing Mathematical Models of Mosquito-Borne Diseases

A special issue of Tropical Medicine and Infectious Disease (ISSN 2414-6366). This special issue belongs to the section "Neglected and Emerging Tropical Diseases".

Deadline for manuscript submissions: closed (20 March 2023) | Viewed by 12314

Special Issue Editors

Dr. Michael A. Robert

E-Mail Website
Guest Editor
Department of Mathematics, Virginia Tech, Blacksburg, VA 24061, USA
Interests: developing mathematical models to study evolutionary, ecological, and anthropogenic processes underlying the emergence, spread, and control of infectious diseases; mathematical and statistical models play an important role in understanding disease emergence and spread as well as helping in the development of control programs; my recent work has focused primarily on (1) utilizing models to investigate potential drivers of disease emergence in naïve populations and predicting transmission in endemic populations; (2) building and analyzing models for designing and investigating potential disease control programs; (3) optimizing integrated mosquito-borne disease control in endemic and epidemic populations; (4) using models to explore data-sparse problems and to improve future data collection. Recently, I have also been interested in (5) investigating impacts of human behavior on disease transmission and control; although the approaches I utilize and the questions that I address in my research are applicable
Dr. Zhuolin Qu

E-Mail Website
Guest Editor
Department of Mathematics, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA
Interests: mathematical biology with particular interests in the mathematical modeling of infectious diseases, computational epidemiology, dynamical systems, and numerical methods for PDEs, and equation-based compartmental models for mosquito-borne diseases and agent-based stochastic models for sexually transmitted diseases at different scales and complexities; collaborating with researchers in/outside the mathematics community and developing computational tools that advance the fields of both mathematics and biology
Dr. Nick W. Ruktanonchai

E-Mail Website
Guest Editor
1. School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
2. Department of Population Health Sciences, VA-MD College of Veterinary Medicine, Virginia Tech, Blacksburg, VA 24061, USA
Interests: infectious disease modeling; vector-borne disease; human mobility; emergining pathogens

Special Issue Information

Dear Colleagues,

Mosquito-borne diseases are a significant global health burden. The incidence and global distribution of some mosquito-borne diseases have increased substantially in the past two decades, driven by urbanization, increased global travel, and changes in climate, among other factors. Mathematical models have proven to be a useful tool for studying the epidemiology of infectious diseases as they provide a framework to describe the complex interactions and characterize feedback between groups in dynamic systems. There is an increasing need for improved models to better understand the complex transmission processes that drive disease spread and better inform and optimize disease mitigation efforts.

Mosquito-borne disease dynamics are often complicated by interactions between environmental factors, meteorological changes, population dynamic processes, anthropogenic interactions, and more across multiple temporal and spatial scales. Mathematical models that consider these factors can help us to better understand the mosquito population dynamics and what drives mosquito-borne disease spread. Furthermore, mathematical models provide quantitative and qualitative assessments for potential control measures. Many mosquito-borne diseases lack pharmaceutical interventions, so most mosquito-borne disease control relies on controlling the vector population and preventing the vector population from interacting with hosts. Traditional control via source reduction and application of insecticides has not been sufficient to eliminate some mosquito-borne diseases, and substantial progress has been made in developing novel control measures, such as releasing genetically or biologically modified mosquitoes into wild populations to reduce wild populations or replace them with mosquitoes incapable of transmitting diseases.

This Special Issue is dedicated to examining mathematical models of mosquito-borne diseases and control measures.  We hope to feature models that integrate ecological and epidemiological dynamics across different scales to understand the mechanisms underlying disease spread and mitigation.

Dr. Michael A. Robert
Dr. Zhuolin Qu
Dr. Nick W. Ruktanonchai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Tropical Medicine and Infectious Disease is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • mosquito-borne disease
  • mathematical modeling
  • dengue
  • malaria
  • west nile virus
  • zika virus
  • chikungunya
  • eastern equine encephalitis
  • Japanese encephalitis
  • Ross River fever
  • St. Louis encephalitis
  • La Crosse encephalitis
  • Eastern equine encephalitis
  • western equine encephalitis
  • rift valley fever
  • yellow fever
  • filariasis
  • mayaro virus
  • vector control
  • genetic pest management
  • wolbachia
  • stochastic modeling
  • epidemic modeling

Published Papers (5 papers)

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Research

23 pages, 5252 KiB  
Article
A Multi-Species Simulation of Mosquito Disease Vector Development in Temperate Australian Tidal Wetlands Using Publicly Available Data
by Kerry Staples, Steven Richardson, Peter J. Neville and Jacques Oosthuizen
Trop. Med. Infect. Dis. 2023, 8(4), 215; https://doi.org/10.3390/tropicalmed8040215 - 03 Apr 2023
Cited by 3 | Viewed by 1618
Abstract
Worldwide, mosquito monitoring and control programs consume large amounts of resources in the effort to minimise mosquito-borne disease incidence. On-site larval monitoring is highly effective but time consuming. A number of mechanistic models of mosquito development have been developed to reduce the reliance [...] Read more.
Worldwide, mosquito monitoring and control programs consume large amounts of resources in the effort to minimise mosquito-borne disease incidence. On-site larval monitoring is highly effective but time consuming. A number of mechanistic models of mosquito development have been developed to reduce the reliance on larval monitoring, but none for Ross River virus, the most commonly occurring mosquito-borne disease in Australia. This research modifies existing mechanistic models for malaria vectors and applies it to a wetland field site in Southwest, Western Australia. Environmental monitoring data were applied to an enzyme kinetic model of larval mosquito development to simulate timing of adult emergence and relative population abundance of three mosquito vectors of the Ross River virus for the period of 2018–2020. The model results were compared with field measured adult mosquitoes trapped using carbon dioxide light traps. The model showed different patterns of emergence for the three mosquito species, capturing inter-seasonal and inter-year variation, and correlated well with field adult trapping data. The model provides a useful tool to investigate the effects of different weather and environmental variables on larval and adult mosquito development and can be used to investigate the possible effects of changes to short-term and long-term sea level and climate changes. Full article
(This article belongs to the Special Issue Advancing Mathematical Models of Mosquito-Borne Diseases)
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21 pages, 1132 KiB  
Article
Modeling Sustained Transmission of Wolbachia among Anopheles Mosquitoes: Implications for Malaria Control in Haiti
by Daniela Florez, Alyssa J. Young, Kerlly J. Bernabé, James M. Hyman and Zhuolin Qu
Trop. Med. Infect. Dis. 2023, 8(3), 162; https://doi.org/10.3390/tropicalmed8030162 - 09 Mar 2023
Viewed by 1698
Abstract
Wolbachia infection in Anopheles albimanus mosquitoes can render mosquitoes less capable of spreading malaria. We developed and analyzed a mechanistic compartmental ordinary differential equation model to evaluate the effectiveness of Wolbachia-based vector control strategies among wild Anopheles mosquitoes in Haiti. The model [...] Read more.
Wolbachia infection in Anopheles albimanus mosquitoes can render mosquitoes less capable of spreading malaria. We developed and analyzed a mechanistic compartmental ordinary differential equation model to evaluate the effectiveness of Wolbachia-based vector control strategies among wild Anopheles mosquitoes in Haiti. The model tracks the mosquito life stages, including egg, larva, and adult (male and female). It also accounts for critical biological effects, such as the maternal transmission of Wolbachia through infected females and cytoplasmic incompatibility, which effectively sterilizes uninfected females when they mate with infected males. We derive and interpret dimensionless numbers, including the basic reproductive number and next-generation numbers. The proposed system presents a backward bifurcation, which indicates a threshold infection that needs to be exceeded to establish a stable Wolbachia infection. The sensitivity analysis ranks the relative importance of the epidemiological parameters at baseline. We simulate different intervention scenarios, including prerelease mitigation using larviciding and thermal fogging before the release, multiple releases of infected populations, and different release times of the year. Our simulations show that the most efficient approach to establishing Wolbachia is to release all the infected mosquitoes immediately after the prerelease mitigation process. Moreover, the model predicts that it is more efficient to release during the dry season than the wet season. Full article
(This article belongs to the Special Issue Advancing Mathematical Models of Mosquito-Borne Diseases)
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19 pages, 7861 KiB  
Article
The Influence of Anthropogenic and Environmental Disturbances on Parameter Estimation of a Dengue Transmission Model
by Alexandra Catano-Lopez, Daniel Rojas-Diaz and Carlos M. Vélez
Trop. Med. Infect. Dis. 2023, 8(1), 5; https://doi.org/10.3390/tropicalmed8010005 - 22 Dec 2022
Viewed by 2131
Abstract
Some deterministic models deal with environmental conditions and use parameter estimations to obtain experimental parameters, but they do not consider anthropogenic or environmental disturbances, e.g., chemical control or climatic conditions. Even more, they usually use theoretical or measured in-lab parameters without worrying about [...] Read more.
Some deterministic models deal with environmental conditions and use parameter estimations to obtain experimental parameters, but they do not consider anthropogenic or environmental disturbances, e.g., chemical control or climatic conditions. Even more, they usually use theoretical or measured in-lab parameters without worrying about uncertainties in initial conditions, parameters, or changes in control inputs. Thus, in this study, we estimate parameters (including chemical control parameters) and confidence contours under uncertainty conditions using data from the municipality of Bello (Colombia) during 2010–2014, which includes two epidemic outbreaks. Our study shows that introducing non-periodic pulse inputs into the mathematical model allows us to: (i) perform parameter estimation by fitting real data of consecutive dengue outbreaks, (ii) highlight the importance of chemical control as a method of vector control, and (iii) reproduce the endemic behavior of dengue. We described a methodology for parameter and sub-contour box estimation under uncertainties and performed reliable simulations showing the behavior of dengue spread in different scenarios. Full article
(This article belongs to the Special Issue Advancing Mathematical Models of Mosquito-Borne Diseases)
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22 pages, 9759 KiB  
Article
Malaria in Senegal: Recent and Future Changes Based on Bias-Corrected CMIP6 Simulations
by Ibrahima Diouf, Jacques-André Ndione and Amadou Thierno Gaye
Trop. Med. Infect. Dis. 2022, 7(11), 345; https://doi.org/10.3390/tropicalmed7110345 - 01 Nov 2022
Cited by 2 | Viewed by 2695
Abstract
Malaria is a constant reminder of the climate change impacts on health. Many studies have investigated the influence of climatic parameters on aspects of malaria transmission. Climate conditions can modulate malaria transmission through increased temperature, which reduces the duration of the parasite’s reproductive [...] Read more.
Malaria is a constant reminder of the climate change impacts on health. Many studies have investigated the influence of climatic parameters on aspects of malaria transmission. Climate conditions can modulate malaria transmission through increased temperature, which reduces the duration of the parasite’s reproductive cycle inside the mosquito. The rainfall intensity and frequency modulate the mosquito population’s development intensity. In this study, the Liverpool Malaria Model (LMM) was used to simulate the spatiotemporal variation of malaria incidence in Senegal. The simulations were based on the WATCH Forcing Data applied to ERA-Interim data (WFDEI) used as a point of reference, and the biased-corrected CMIP6 model data, separating historical simulations and future projections for three Shared Socio-economic Pathways scenarios (SSP126, SSP245, and SSP585). Our results highlight a strong increase in temperatures, especially within eastern Senegal under the SSP245 but more notably for the SSP585 scenario. The ability of the LMM model to simulate the seasonality of malaria incidence was assessed for the historical simulations. The model revealed a period of high malaria transmission between September and November with a maximum reached in October, and malaria results for historical and future trends revealed how malaria transmission will change. Results indicate a decrease in malaria incidence in certain regions of the country for the far future and the extreme scenario. This study is important for the planning, prioritization, and implementation of malaria control activities in Senegal. Full article
(This article belongs to the Special Issue Advancing Mathematical Models of Mosquito-Borne Diseases)
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27 pages, 3533 KiB  
Article
Assessing the Impact of Relapse, Reinfection and Recrudescence on Malaria Eradication Policy: A Bifurcation and Optimal Control Analysis
by Hengki Tasman, Dipo Aldila, Putri A. Dumbela, Meksianis Z. Ndii, Fatmawati, Faishal F. Herdicho and Chidozie W. Chukwu
Trop. Med. Infect. Dis. 2022, 7(10), 263; https://doi.org/10.3390/tropicalmed7100263 - 24 Sep 2022
Cited by 13 | Viewed by 2930
Abstract
In the present study, we propose and analyze an epidemic mathematical model for malaria dynamics, considering multiple recurrent phenomena: relapse, reinfection, and recrudescence. A limitation in hospital bed capacity, which can affect the treatment rate, is modeled using a saturated treatment function. The [...] Read more.
In the present study, we propose and analyze an epidemic mathematical model for malaria dynamics, considering multiple recurrent phenomena: relapse, reinfection, and recrudescence. A limitation in hospital bed capacity, which can affect the treatment rate, is modeled using a saturated treatment function. The qualitative behavior of the model, covering the existence and stability criteria of the endemic equilibrium, is investigated rigorously. The concept of the basic reproduction number of the proposed model is obtained using the concept of the next-generation matrix. We find that the malaria-free equilibrium point is locally asymptotically stable if the basic reproduction number is less than one and unstable if it is larger than one. Our observation on the malaria-endemic equilibrium of the proposed model shows possible multiple endemic equilibria when the basic reproduction number is larger or smaller than one. Hence, we conclude that a condition of a basic reproduction number less than one is not sufficient to guarantee the extinction of malaria from the population. To test our model in a real-life situation, we fit our model parameters using the monthly incidence data from districts in Central Sumba, Indonesia called Wee Luri, which were collected from the Wee Luri Health Center. Using the first twenty months’ data from Wee Luri district, we show that our model can fit the data with a confidence interval of 95%. Both analytical and numerical experiments show that a limitation in hospital bed capacity and reinfection can trigger a more substantial possibility of the appearance of backward bifurcation. On the other hand, we find that an increase in relapse can reduce the chance of the appearance of backward bifurcation. A non-trivial result appears in that a higher probability of recrudescence (treatment failure) does not always result in the appearance of backward bifurcation. From the global sensitivity analysis using a combination of Latin hypercube sampling and partial rank correlation coefficient, we found that the initial infection rate in humans and the mosquito infection rate are the most influential parameters in determining the increase in total new human infections. We expand our model as an optimal control problem by including three types of malaria interventions, namely the use of bed net, hospitalization, and fumigation as a time-dependent variable. Using the Pontryagin maximum principle, we characterize our optimal control problem. Results from our cost-effectiveness analysis suggest that hospitalization only is the most cost-effective strategy required to control malaria disease. Full article
(This article belongs to the Special Issue Advancing Mathematical Models of Mosquito-Borne Diseases)
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