scholarly journals Unravelling Transmission in Epidemiological Models and its Role in the Disease-Diversity Relationship

Author(s):  
Marjolein E.M. Toorians ◽  
Ailene MacPherson ◽  
T. Jonathan Davies

With the decrease of biodiversity worldwide coinciding with an increase in disease outbreaks, investigating this link is more important then ever before. This review outlines the different modelling methods commonly used for pathogen transmission in animal host systems. There are a multitude of ways a pathogen can invade and spread through a host population. The assumptions of the transmission model used to capture disease propagation determines the outbreak potential, the net reproductive success (R0). This review offers an insight into the assumptions and motivation behind common transmission mechanisms and introduces a general framework with which contact rates, the most important parameter in disease dynamics, determines the transmission method. By using a general function introduced here and this general transmission model framework, we provide a guide for future disease ecologists for how to pick the contact function that best suites their system. Additionally, this manuscript attempts to bridge the gap between mathematical disease modelling and the controversially and heavily debated disease-diversity relationship, by expanding the summarized models to multiple hosts systems and explaining the role of host diversity in disease transmission. By outlining the mechanisms of transmission into a stepwise process, this review will serve as a guide to model pathogens in multi-host systems. We will further describe these models it in the greater context of host diversity and its effect on disease outbreaks, by introducing a novel method to include host species’ evolutionary history into the framework.

2013 ◽  
Author(s):  
Xavier Didelot ◽  
Jennifer Gardy ◽  
Caroline Colijn

Genomics is increasingly being used to investigate disease outbreaks, but an important question remains unanswered -- how well do genomic data capture known transmission events, particularly for pathogens with long carriage periods or large within-host population sizes? Here we present a novel Bayesian approach to reconstruct densely-sampled outbreaks from genomic data whilst considering within-host diversity. We infer a time-labelled phylogeny using BEAST, then infer a transmission network via a Monte-Carlo Markov Chain. We find that under a realistic model of within-host evolution, reconstructions of simulated outbreaks contain substantial uncertainty even when genomic data reflect a high substitution rate. Reconstruction of a real-world tuberculosis outbreak displayed similar uncertainty, although the correct source case and several clusters of epidemiologically linked cases were identified. We conclude that genomics cannot wholly replace traditional epidemiology, but that Bayesian reconstructions derived from sequence data may form a useful starting point for a genomic epidemiology investigation.


2018 ◽  
Author(s):  
Ramsès Djidjou-Demasse ◽  
Gbenga J. Abiodun ◽  
Abiodun M. Adeola ◽  
Joel O. Botai

AbstractIn this paper we develop and analyse a malaria model with seasonality of mosquito life-history traits: periodic-mosquitoes per capita birth rate, -mosquitoes death rate, -probability of mosquito to human disease transmission, -probability of human to mosquito disease transmission and -mosquitoes biting rate. All these parameters are assumed to be time dependent leading to a nonautonomous differential equation systems. We provide a global analysis of the model depending on two thresholds parametersand(with). When, then the disease-free stationary state is locally asymptotically stable. In the presence of the human disease-induced mortality, the global stability of the disease-free stationary state is guarantied when. On the contrary, if, the disease persists in the host population in the long term and the model admits at least one positive periodic solution. Moreover, by a numerical simulation, we show that a subcritical (backward) bifurcation is possible at. Finally, the simulation results are in accordance with the seasonal variation of the reported cases of a malaria-epidemic region in Mpumalanga province in South Africa.


2017 ◽  
Author(s):  
Edward M. Hill ◽  
Thomas House ◽  
Madhur S. Dhingra ◽  
Wantanee Kalpravidh ◽  
Subhash Morzaria ◽  
...  

AbstractIn Bangladesh, the poultry industry is an economically and socially important sector, but it is persistently threatened by the effects of H5N1 highly pathogenic avian influenza. Thus, identifying the optimal control policy in response to an emerging disease outbreak is a key challenge for policy-makers. To inform this aim, a common approach is to carry out simulation studies comparing plausible strategies, while accounting for known capacity restrictions. In this study we perform simulations of a previously developed H5N1 influenza transmission model framework, fitted to two separate historical outbreaks, to assess specific control objectives related to the burden or duration of H5N1 outbreaks among poultry farms in the Dhaka division of Bangladesh. In particular, we explore the optimal implementation of ring culling, ring vaccination and active surveillance measures when presuming disease transmission predominately occurs from premises-to-premises, versus a setting requiring the inclusion of external factors. Additionally, we determine the sensitivity of the management actions under consideration to differing levels of capacity constraints and outbreaks with disparate transmission dynamics. While we find that reactive culling and vaccination policies should pay close attention to these factors to ensure intervention targeting is optimised, across multiple settings the top performing control action amongst those under consideration were targeted proactive surveillance schemes. Our findings may advise the type of control measure, plus its intensity, that could potentially be applied in the event of a developing outbreak of H5N1 amongst originally H5N1 virus-free commercially-reared poultry in the Dhaka division of Bangladesh.


Author(s):  
Joel Hellewell ◽  
Sam Abbott ◽  
Amy Gimma ◽  
Nikos I Bosse ◽  
Christopher I Jarvis ◽  
...  

AbstractBackgroundTo assess the viability of isolation and contact tracing to control onwards transmission from imported cases of 2019-nCoV.MethodsWe developed a stochastic transmission model, parameterised to the 2019-nCoV outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a 2019 nCoV-like pathogen. We considered scenarios that varied in: the number of initial cases; the basic reproduction number R0; the delay from symptom onset to isolation; the probability contacts were traced; the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort.FindingsWhile simulated outbreaks starting with only 5 initial cases, R0 of 1.5 and little transmission before symptom onset could be controlled even with low contact tracing probability, the prospects of controlling an outbreak dramatically dropped with the number of initial cases, with higher R0, and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R0 of 1.5 were controllable with under 50% of contacts successfully traced. For R0 of 2.5 and 3.5, more than 70% and 90% of contacts respectively had to be traced to control the majority of outbreaks. The delay between symptom onset and isolation played the largest role in determining whether an outbreak was controllable for lower values of R0. For higher values of R0 and a large initial number of cases, contact tracing and isolation was only potentially feasible when less than 1% of transmission occurred before symptom onset.InterpretationWe found that in most scenarios contact tracing and case isolation alone is unlikely to control a new outbreak of 2019-nCov within three months. The probability of control decreases with longer delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts.FundingWellcome Trust, Global Challenges Research Fund, and HDR UK.Research in ContextEvidence before this studyContact tracing and isolation of cases is a commonly used intervention for controlling infectious disease outbreaks. This intervention can be effective, but may require intensive public health effort and cooperation to effectively reach and monitor all contacts. When the pathogen has infectiousness before symptom onset, control of outbreaks using contact tracing and isolation is more challenging.Added value of this studyThis study uses a mathematical model to assess the feasibility of contact tracing and case isolation to control outbreaks of 2019-nCov, a newly emerged pathogen. We used disease transmission characteristics specific to the pathogen and therefore give the best available evidence if contact tracing and isolation can achieve control of outbreaks.Implications of all the available evidenceContact tracing and isolation may not contain outbreaks of 2019-nCoV unless very high levels of contact tracing are achieved. Even in this case, if there is asymptomatic transmission, or a high fraction of transmission before onset of symptoms, this strategy may not achieve control within three months.


2017 ◽  
Author(s):  
Pratha Sah ◽  
Michael Otterstatter ◽  
Stephan T. Leu ◽  
Sivan Leviyang ◽  
Shweta Bansal

AbstractThe spread of pathogens fundamentally depends on the underlying contacts between individuals. Modeling infectious disease dynamics through contact networks is sometimes challenging, however, due to a limited understanding of pathogen transmission routes and infectivity. We developed a novel tool, INoDS (Identifying Network models of infectious Disease Spread) that estimates the predictive power of empirical contact networks to explain observed patterns of infectious disease spread. We show that our method is robust to partially sampled contact networks, incomplete disease information, and enables hypothesis testing on transmission mechanisms. We demonstrate the applicability of our method in two host-pathogen systems: Crithidia bombi in bumble bee colonies and Salmonella in wild Australian sleepy lizard populations. The performance of INoDS in synthetic and complex empirical systems highlights its role in identifying transmission pathways of novel or neglected pathogens, as an alternative approach to laboratory transmission experiments, and overcoming common data-collection constraints.


2021 ◽  
pp. 1-5
Author(s):  
Melissa T. Ibarra ◽  
Cheryl L. Meehan ◽  
Miles Daniels ◽  
Woutrina A. Smith ◽  
Martin H. Smith

Disease outbreaks among visitors at venues where animals are exhibited, such as animal shows at county fairs or petting zoos, are national public health concerns. Zoonotic disease transmission at fairs can occur through a variety of pathways, including direct contact with livestock and indirect exposure through contact with animals' immediate surroundings. Handwashing can reduce pathogen transmission. The goal of this observational study was to determine rates of handwashing among county fair visitors and to learn whether signage and/or contact with animals were correlated with handwashing practice. The investigation was conducted at four county fairs located across two geographic regions of California. Observations occurred over the course of one summer. Results from our observations of fair visitors revealed a low overall prevalence (5%) of handwashing behavior. However, fair visitors who made contact with animals were more likely to wash their hands. Additionally, those individuals who walked through barns where handwashing signage was present were significantly more likely to wash their hands than those who visited barns without signage.


Author(s):  
Oluwatayo Michael Ogunmiloro

This article describes the mathematical model derivation describing river blindness disease transmission in human and vector (blackflies) host population. The effect of incomplete resistance to re-infection in human individuals who recovered from the disease after treatment but are still subjected to repeated exposures to infected blackflies bite is investigated. Also, the basic reproduction number [Formula: see text] is obtained and it is shown that if [Formula: see text], the onchocerciasis-free equilibrium is locally and globally asymptotically stable. Also, if [Formula: see text], the onchocerciasis-endemic equilibrium is globally asymptotically stable. Moreover, the Differential Transform Method (DTM) and Runge–Kutta fourth-order method is employed via the computational software Maple 18 to solve and obtain the approximate solutions of the model system equations, which showed that the numerical results favorably compare with each other. Simulations reveal that increase in biting and transmission rates leads to an increase of [Formula: see text] and incomplete resistance to re-infection due to consistent exposure to blackflies bites. Also, simulations of the approximate solutions of the model state equations are provided.


Author(s):  
Laura H. Backus ◽  
Andrés M. López Pérez ◽  
Janet E. Foley

Rhipicephalus sanguineus is a species complex of ticks that vector disease worldwide. Feeding primarily on dogs, members of the complex also feed incidentally on humans, potentially transmitting disease agents such as Rickettsia rickettsii, R. conorii, and Ehrlichia species. There are two genetic Rh. sanguineus lineages in North America, designated as the temperate and tropical lineages, which had occurred in discrete locations, although there is now range overlap in parts of California and Arizona. Rh. sanguineus in Europe are reportedly more aggressive toward humans during hot weather, increasing the risk of pathogen transmission to humans. The aim of this study was to assess the impact of hot weather on choice between humans and dog hosts among tropical and temperate lineage Rh. sanguineus individuals. Ticks in a two-choice olfactometer migrated toward a dog or human in trials at room (23.5°C) or high temperature (38°C). At 38°C, 2.5 times more tropical lineage adults chose humans compared with room temperature, whereas temperate lineage adults demonstrated a 66% reduction in preference for dogs and a slight increase in preference for humans. Fewer nymphs chose either host at 38°C than at room temperature in both lineages. These results demonstrate that risk of disease transmission to humans may be increased during periods of hot weather, where either lineage is present, and that hot weather events associated with climatic change may result in more frequent rickettsial disease outbreaks.


Author(s):  
Diana Erazo ◽  
Amy B. Pedersen ◽  
Kayleigh Gallagher ◽  
Andy Fenton

AbstractTo date, few studies of parasite epidemiology have investigated ‘who acquires infection from whom’ in wildlife populations. Nonetheless, identifying routes of disease transmission within a population, and determining the key groups of individuals that drive parasite transmission and maintenance, are fundamental to understanding disease dynamics. Gammaherpesviruses are a widespread group of DNA viruses that infect many vertebrate species, and murine gammaherpesviruses (i.e. MuHV-4) are a standard lab model for studying human herpesviruses, for which much about the pathology and immune response elicited to infection is well understood. However, despite this extensive research effort, primarily in the lab, the transmission route of murine gammaherpesviruses within their natural host populations is not well understood. Here, we aimed to understand wood mouse herpesvirus (WMHV) transmission, by fitting a series of population dynamic models to field data on wood mice naturally infected with WMHV and then estimating transmission parameters within and between demographic groups of the host population. Different models accounted for different combinations of host sex (male/female), age (subadult/adult) and transmission functions (density/frequency-dependent). We found that a density-dependent transmission model incorporating explicit sex groups fitted the data better than all other proposed models. Male-to-male transmission was the highest among all demographic groups, suggesting that male behaviour is a key factor driving WMHV transmission. Our models also suggest that transmission between sexes, although important, wasn’t symmetrical, with infected males playing a significant role in infecting naïve females but not vice versa. Overall this work shows the power of coupling population dynamic models with long-term field data to elucidate otherwise unobservable transmission processes in wild disease systems.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Buddhadeb Roy ◽  
Shailja Dubey ◽  
Amalendu Ghosh ◽  
Shalu Misra Shukla ◽  
Bikash Mandal ◽  
...  

AbstractLeaf curl, a whitefly-borne begomovirus disease, is the cause of frequent epidemic in chili. In the present study, transmission parameters involved in tripartite interaction are estimated to simulate disease dynamics in a population dynamics model framework. Epidemic is characterized by a rapid conversion rate of healthy host population into infectious type. Infection rate as basic reproduction number, R0 = 13.54, has indicated a high rate of virus transmission. Equilibrium population of infectious host and viruliferous vector are observed to be sensitive to the immigration parameter. A small increase in immigration rate of viruliferous vector increased the population of both infectious host and viruliferous vector. Migrant viruliferous vectors, acquisition, and transmission rates as major parameters in the model indicate leaf curl epidemic is predominantly a vector -mediated process. Based on underlying principles of temperature influence on vector population abundance and transmission parameters, spatio-temporal pattern of disease risk predicted is noted to correspond with leaf curl distribution pattern in India. Temperature in the range of 15–35 °C plays an important role in epidemic as both vector population and virus transmission are influenced by temperature. Assessment of leaf curl dynamics would be a useful guide to crop planning and evolution of efficient management strategies.


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