Genetic diversity and disease spread: epidemiological models and empirical studies of a snail–trematode system

Abstract Background Knowing the genetic diversity of M. tuberculosis strains causing drug-resistant tuberculosis (DR-TB) in high burden TB and low resources countries such as Mozambique is a key factor to TB disease spread control and world TB epidemic control. Whole-genome sequencing (WGS) better describes molecular diversity, lineages and sub lineages, relationship between strains, underline mutations conferring drug-resistant TB, which may not be shown by molecular and phenotypic tests. As far as we know this is the first study that describes genetic diversity of M. tuberculosis strains causing DR-TB and using WGS in central region of Mozambique.We aim to describe genetic diversity of M. tuberculosis strains causing DR-TB in central Mozambique. Methods A total of 35 strains from Beira Mozambique were evaluated with genotypic tests (Genotype MTBDRplus™, and MTBDRsl™); phenotypic (MGIT-SIRE™) and DST. All isolates resistant to isoniazid (H) or rifampicin (R) or both were submitted to WGS Illumina HiSeq 2000 and analyzed with TB profiler database and phylogenetic tree was done using Figtree tool. This was a descriptive cross-sectional study. Results WGS shown that strains analyzed, belongs to three of six major lineages, with Lineage 4: 25(71.4%); Lineage 1: 5(14.3%); and Lineage 2 Beijing family: 5(14.3%)]. All pre-XDR strains 3(8.6%) were from lineage 4.3. By WGS, all 35 strains had any mutations conferring DR-TB while in one strain, mutation was not shown by genotypic neither phenotypic DST. Compared with genotypic tests, WGS had best performance in showing mutation conferring resistance to etambutol 12/35 (34.3%) and 7/35 (20%). Conclusion The DR-TB disease in Beira Mozambique is mainly caused by M. tuberculosis strains of Lineage 4, sub-lineage 3 although lineage 1 and 2 are also present. WGS shows underline mutations causing DR–TB that are not detected by genotypic and phenotypic DST test. Disclosures All authors: No reported disclosures.

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065 Genetic Diversity of the Allegheny Chinkapin (Castanea pumila var. pumila)

HortScience ◽

10.21273/hortsci.34.3.452c ◽

1999 ◽

Vol 34 (3) ◽

pp. 452C-452

Author(s):

Fenny Dane

Keyword(s):

Genetic Diversity ◽

Rapd Marker ◽

Cryphonectria Parasitica ◽

American Chestnut ◽

Disease Spread ◽

Conservation Strategies ◽

Chestnut Blight ◽

Geographic Populations ◽

Natural Range ◽

Conservation Plan

American species in the genus Castanea are susceptible to chestnut blight, caused by the Asian fungus Cryphonectria parasitica. This disease spread throughout the natural range of the American chestnut and reduced the species from a timber and nut producing tree to an understory shrub. The lesser known member of the genus, the chinkapin, has also been affected by this disease and a conservation plan is needed. Genetic diversity within and between geographic populations of the Allegheny chinkapin was evaluated to provide baseline genetic information pertinent to conservation of the species. Nuts of Allegheny chinkapin trees from populations in Mississippi, Florida, Alabama, Virginia, and Ohio were collected and evaluated for isozyme and RAPD marker polymorphism. The genetic diversity of these populations will be compared with that of Ozark chinkapin and American chestnut populations. Conservation strategies will be discussed.

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When individual behaviour matters: homogeneous and network models in epidemiology

Journal of The Royal Society Interface ◽

10.1098/rsif.2007.1100 ◽

2007 ◽

Vol 4 (16) ◽

pp. 879-891 ◽

Cited By ~ 360

Author(s):

Shweta Bansal ◽

Bryan T Grenfell ◽

Lauren Ancel Meyers

Keyword(s):

Compartmental Model ◽

Network Models ◽

Population Level ◽

Disease Spread ◽

Mixing Models ◽

Epidemiological Models ◽

Human Contact ◽

Contact Patterns ◽

Underlying Network ◽

Simplifying Assumptions

Heterogeneity in host contact patterns profoundly shapes population-level disease dynamics. Many epidemiological models make simplifying assumptions about the patterns of disease-causing interactions among hosts. In particular, homogeneous-mixing models assume that all hosts have identical rates of disease-causing contacts. In recent years, several network-based approaches have been developed to explicitly model heterogeneity in host contact patterns. Here, we use a network perspective to quantify the extent to which real populations depart from the homogeneous-mixing assumption, in terms of both the underlying network structure and the resulting epidemiological dynamics. We find that human contact patterns are indeed more heterogeneous than assumed by homogeneous-mixing models, but are not as variable as some have speculated. We then evaluate a variety of methodologies for incorporating contact heterogeneity, including network-based models and several modifications to the simple SIR compartmental model. We conclude that the homogeneous-mixing compartmental model is appropriate when host populations are nearly homogeneous, and can be modified effectively for a few classes of non-homogeneous networks. In general, however, network models are more intuitive and accurate for predicting disease spread through heterogeneous host populations.

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Genetics of reintroduced populations of the narrowly endemic thistle, Cirsium pitcheri (Asteraceae)

Botany ◽

10.1139/cjb-2012-0232 ◽

2013 ◽

Vol 91 (5) ◽

pp. 301-308 ◽

Cited By ~ 12

Author(s):

Jeremie B. Fant ◽

Andrea Kramer ◽

Eileen Sirkin ◽

Kayri Havens

Keyword(s):

Genetic Diversity ◽

Population Size ◽

Empirical Studies ◽

Small Population ◽

Native Plant ◽

Effective Population ◽

Term Survival ◽

Inbreeding Coefficients ◽

Native Populations ◽

Population Sizes

The aim of any reintroduction is to provide sufficient genetic variability to buffer against changing selection pressures and ensure long-term survival. To date, few empirical studies have compared levels of genetic diversity in reintroduced and native plant populations. Using microsatellite markers, we measured the genetic diversity within reintroduced and native populations of the threatened Cirsium pitcher (Eaton) Torrey and Gray. We found that the use of local mixed source was successful in establishing populations with significantly higher genetic diversity (P < 0.005) than the native populations (allelic richness is 3.39 in reintroduced and 1.84 in native populations). However, the reintroduced populations had significantly higher inbreeding coefficients (P < 0.002) (FIS is 0.405 and 0.213 in reintroduced and in native populations, respectively), despite having multiple genetic founders, population sizes equivalent to native populations and a positive growth rate. These results may be due to inbreeding or the Wahlund effect, driven by genetic substructuring. This suggests that the small population size of these reintroduced populations may lead to genetic issues in the future, given the low number of flowering individuals each year. This highlights the importance of considering not only the number of source individuals but the effective population size of the reintroduction.

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Economics of Infectious Diseases

The Oxford Handbook of Health Economics ◽

10.1093/oxfordhb/9780199238828.013.0009 ◽

2011 ◽

pp. 188-205 ◽

Cited By ~ 2

Author(s):

Ramanan Laxminarayan ◽

Anup Malani

Keyword(s):

Infectious Diseases ◽

Public Goods ◽

Risk Taking ◽

Disease Spread ◽

Treatment Programs ◽

Individual Risk ◽

Epidemiological Models ◽

Global Public Goods ◽

Prevention And Treatment ◽

Models Of Disease

Infectious diseases remain a central preoccupation in many countries. This article sets out the economic issues that arise in this highly complex domain. It reviews four main strands of literature on the economics of infectious diseases. It discusses the economic impact of infectious diseases on labor productivity and investment decisions. It focuses on the interplay between disease prevention and treatment and individual risk-taking behavior. It discusses vaccination as an important tool in the prevention of infectious diseases and presents a classic public goods problem. Disease reporting and eradication efforts are also global public goods. A fourth strand of literature is on the optimal design and allocation of resources for prevention and treatment programs. These programs are based on epidemiological models of disease spread that present significant mathematical challenges.

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Genetic differentiation in an artificial population of the threatened plant Lupinus oreganus (Fabaceae)

Botany ◽

10.1139/cjb-2012-0278 ◽

2013 ◽

Vol 91 (5) ◽

pp. 319-322 ◽

Cited By ~ 2

Author(s):

Paul M. Severns

Keyword(s):

Genetic Diversity ◽

Genetic Differentiation ◽

Empirical Studies ◽

Allelic Diversity ◽

Small Population ◽

Rare Plant ◽

Genetic Rescue ◽

Threatened Plant ◽

Artificial Seed ◽

Dna Genotyping

Reintroduction, supplemental planting for genetic rescue, and the creation of artificial seed production populations are common methods to conserve rare plant species, but empirical studies assessing the effects of artificial selection on genetic diversity are rare. I conducted a retrospective DNA genotyping study on an artificial population (hereinafter Office) of the threatened plant, Lupinus oreganus Heller, to determine whether the process of establishing the Office population facilitated genetic differentiation and if genetic diversity was maintained in the Office cohort. Genotyping indicated that uncommon maternal lineages (cpDNA haplotypes) were selected for in the artificial population and that the Office population was genetically distinct from both seed source patches. Furthermore, despite a small population size of seven individuals, cpDNA haplotype and nDNA simple sequence repeat allelic diversity was maintained in the surviving Office cohort. This study suggests that small artificial rare plant populations may be beneficial for capitalizing on the existing within-population genetic diversity, but they may also select for uncommon allelic diversity and facilitate genetic differentiation.

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Disruption of Metapopulation Structure Reduces Tasmanian Devil Facial Tumour Disease Spread at the Expense of Abundance and Genetic Diversity

Pathogens ◽

10.3390/pathogens10121592 ◽

2021 ◽

Vol 10 (12) ◽

pp. 1592

Author(s):

Rowan Durrant ◽

Rodrigo Hamede ◽

Konstans Wells ◽

Miguel Lurgi

Keyword(s):

Genetic Diversity ◽

Disease Transmission ◽

Transmission Rate ◽

Extinction Risk ◽

Disease Prevalence ◽

Disease Spread ◽

Tasmanian Devil ◽

Local Populations ◽

Metapopulation Structure ◽

Devil Facial Tumour Disease

Metapopulation structure plays a fundamental role in the persistence of wildlife populations. It can also drive the spread of infectious diseases and transmissible cancers such as the Tasmanian devil facial tumour disease (DFTD). While disrupting this structure can reduce disease spread, it can also impair host resilience by disrupting gene flow and colonisation dynamics. Using an individual-based metapopulation model we investigated the synergistic effects of host dispersal, disease transmission rate and inter-individual contact distance for transmission, on the spread and persistence of DFTD from local to regional scales. Disease spread, and the ensuing population declines, are synergistically determined by individuals’ dispersal, disease transmission rate and within-population mixing. Transmission rates can be magnified by high dispersal and inter-individual transmission distance. The isolation of local populations effectively reduced metapopulation-level disease prevalence but caused severe declines in metapopulation size and genetic diversity. The relative position of managed (i.e., isolated) local populations had a significant effect on disease prevalence, highlighting the importance of considering metapopulation structure when implementing metapopulation-scale disease control measures. Our findings suggest that population isolation is not an ideal management method for preventing disease spread in species inhabiting already fragmented landscapes, where genetic diversity and extinction risk are already a concern.

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Elucidating relationships between P.falciparum prevalence and measures of genetic diversity with a combined genetic-epidemiological model of malaria

PLoS Computational Biology ◽

10.1371/journal.pcbi.1009287 ◽

2021 ◽

Vol 17 (8) ◽

pp. e1009287

Author(s):

Jason A. Hendry ◽

Dominic Kwiatkowski ◽

Gil McVean

Keyword(s):

Genetic Diversity ◽

Nucleotide Diversity ◽

Genetic Data ◽

Parasite Prevalence ◽

Epidemiological Models ◽

Related Factors ◽

Malaria Epidemiology ◽

Moran Model ◽

Classical Models ◽

Parasite Evolution

There is an abundance of malaria genetic data being collected from the field, yet using these data to understand the drivers of regional epidemiology remains a challenge. A key issue is the lack of models that relate parasite genetic diversity to epidemiological parameters. Classical models in population genetics characterize changes in genetic diversity in relation to demographic parameters, but fail to account for the unique features of the malaria life cycle. In contrast, epidemiological models, such as the Ross-Macdonald model, capture malaria transmission dynamics but do not consider genetics. Here, we have developed an integrated model encompassing both parasite evolution and regional epidemiology. We achieve this by combining the Ross-Macdonald model with an intra-host continuous-time Moran model, thus explicitly representing the evolution of individual parasite genomes in a traditional epidemiological framework. Implemented as a stochastic simulation, we use the model to explore relationships between measures of parasite genetic diversity and parasite prevalence, a widely-used metric of transmission intensity. First, we explore how varying parasite prevalence influences genetic diversity at equilibrium. We find that multiple genetic diversity statistics are correlated with prevalence, but the strength of the relationships depends on whether variation in prevalence is driven by host- or vector-related factors. Next, we assess the responsiveness of a variety of statistics to malaria control interventions, finding that those related to mixed infections respond quickly (∼months) whereas other statistics, such as nucleotide diversity, may take decades to respond. These findings provide insights into the opportunities and challenges associated with using genetic data to monitor malaria epidemiology.

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Infections on the move: how transient phases of host movement influence disease spread

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2017.1807 ◽

2017 ◽

Vol 284 (1869) ◽

pp. 20171807 ◽

Cited By ~ 20

Author(s):

D. R. Daversa ◽

A. Fenton ◽

A. I. Dell ◽

T. W. J. Garner ◽

A. Manica

Keyword(s):

Animal Movement ◽

Experimental Testing ◽

Empirical Studies ◽

Disease Spread ◽

Wildlife Diseases ◽

Technological Advances ◽

Infection Dynamics ◽

Transient Phases ◽

Host Movement ◽

Infection Spread

Animal movement impacts the spread of human and wildlife diseases, and there is significant interest in understanding the role of migrations, biological invasions and other wildlife movements in spatial infection dynamics. However, the influence of processes acting on infections during transient phases of host movement is poorly understood. We propose a conceptual framework that explicitly considers infection dynamics during transient phases of host movement to better predict infection spread through spatial host networks. Accounting for host transient movement captures key processes that occur while hosts move between locations, which together determine the rate at which hosts spread infections through networks. We review theoretical and empirical studies of host movement and infection spread, highlighting the multiple factors that impact the infection status of hosts. We then outline characteristics of hosts, parasites and the environment that influence these dynamics. Recent technological advances provide disease ecologists unprecedented ability to track the fine-scale movement of organisms. These, in conjunction with experimental testing of the factors driving infection dynamics during host movement, can inform models of infection spread based on constituent biological processes.

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