Economic factors influencing zoonotic disease dynamics: demand for poultry meat and seasonal transmission of avian influenza in Vietnam

While climate is often presented as a key factor influencing the seasonality of diseases, the importance of anthropogenic factors is less commonly evaluated. Using a combination of methods-wavelet analysis, economic analysis, statistical and disease transmission modelling-we aimed to explore the influence of climatic and economic factors on the seasonality of H5N1 Highly Pathogenic Avian Influenza in the domestic poultry population of Vietnam. We found that while climatic variables are associated with seasonal variation in the incidence of avian influenza outbreaks in the North of the country, this is not the case in the Centre and the South. In contrast, temporal patterns of H5N1 incidence are similar across these 3 regions: periods of high H5N1 incidence coincide with Lunar New Year festival, occurring in January-February, in the 3 climatic regions for 5 out of the 8 study years. Yet, daily poultry meat consumption drastically increases during Lunar New Year festival throughout the country. To meet this rise in demand, poultry production and trade are expected to peak around the festival period, promoting viral spread, which we demonstrated using a stochastic disease transmission model. This study illustrates the way in which economic factors may influence the dynamics of livestock pathogens

Bayesian data assimilation provides rapid decision support for vector-borne diseases

Predicting the spread of vector-borne diseases in response to incursions requires knowledge of both host and vector demographics in advance of an outbreak. Whereas host population data is typically available, for novel disease introductions there is a high chance of the pathogen utilising a vector for which data is unavailable. This presents a barrier to estimating the parameters of dynamical models representing host-vector-pathogen interaction, and hence limits their ability to provide quantitative risk forecasts. The Theileria orientalis (Ikeda) outbreak in New Zealand cattle demonstrates this problem: even though the vector has received extensive laboratory study, a high degree of uncertainty persists over its national demographic distribution. Addressing this, we develop a Bayesian data assimilation approach whereby indirect observations of vector activity inform a seasonal spatio-temporal risk surface within a stochastic epidemic model. We provide quantitative predictions for the future spread of the epidemic, quantifying uncertainty in the model parameters, case infection times, and the disease status of undetected infections. Importantly, we demonstrate how our model learns sequentially as the epidemic unfolds, and provides evidence for changing epidemic dynamics through time. Our approach therefore provides a significant advance in rapid decision support for novel vector-borne disease outbreaks

The climatic drivers of long-term population changes in rainforest montane birds

Climate-driven biodiversity erosion is escalating at an alarming rate. The pressure imposed by climate change is exceptionally high in tropical ecosystems, where species adapted to narrow environmental ranges exhibit strong physiological constraints. Despite the observed detrimental effect of climate change on ecosystems at a global scale, our understanding of the extent to which multiple climatic drivers affect population dynamics is limited. Here, we disentangle the impact of different climatic stressors on 47 rainforest birds inhabiting the mountains of the Australian Wet Tropics using hierarchical population models. We estimate the effect of spatiotemporal changes in temperature, precipitation, heatwaves, droughts and cyclones on the population dynamics of rainforest birds between 2000 and 2016. We find a strong effect of warming and changes in rainfall patterns across the elevational-segregated bird communities, with lowland populations benefiting from increasing temperature and precipitation, while upland species show an inverse strong negative response to the same drivers. Additionally, we find a negative effect of heatwaves on lowland populations, a pattern associated with the observed distribution of these extreme events across elevations. In contrast, cyclones and droughts have a marginal effect on spatiotemporal changes in rainforest bird communities, suggesting a species-specific response unrelated to the elevational gradient. This study demonstrated the importance of unravelling the drivers of climate change impacts on population changes, providing significant insight into the mechanisms accelerating climate-induced biodiversity degradation

Integrated assessment of ecosystem connectivity and functioning: coastal forest avifauna of northeast Australia

The extraordinary diversity of species-environment relationships that occur across space and time can engender a deep curiosity of their mechanistic underpinnings. Moreover, the rapid rate of ecosystem change associated with anthropogenic and climatic pressures makes information regarding species' landscape and resource use ever more important. Without this information, we will be unable to effectively protect landscapes and their constituent species. The coastal ecosystem mosaic of northeast Australia, which is comprised of a high diversity of habitat types, provides a suitable region for investigating how species respond to heterogeneity in habitat and resource availability. The present thesis examined ecosystem functioning in heterogeneous coastal landscapes of northeast Australia for forest avifauna. An array of analytical approaches were employed to establish a comprehensive understanding: 1) spatial assessment to determine relationships between regional landscape connectivity and coastal forest bird assemblages, 2) isotopic assessment to evaluate the local foraging ecology of mangrove bird assemblages, and 3) nutrient assessment of cross-ecosystem connectivity provided by a migratory coastal forest bird species (i.e. the Pied Imperial-Pigeon (Ducula bicolor)). Within the coastal ecosystem mosaic, mangrove forests sit at the land-sea interface. Therefore, to effectively 'set the scene' I review how mangrove birds require and facilitate connectivity through their use of the broader coastal landscape. Next, to specifically assess regional landscape patterns and processes influencing northeast Australia's coastal forest avifauna, I surveyed the composition of bird assemblages in four of the major coastal forest types occurring throughout the region (i.e. Eucalypt, Melaleuca, mangrove, and rainforest). Following this, spatial patterns of habitat configuration within the coastal landscape (i.e. structural connectivity) were quantified to understand broad relationships between coastal forest bird assemblage composition and landscape heterogeneity at multiple spatial scales. Most bird species in coastal northeast Australia occurred in multiple forest types. Spatial assessment suggested that Melaleuca woodlands are a keystone structure that supports use of the entire coastal landscape mosaic by coastal forest generalist species. However, the species composition of mangrove bird assemblages was distinct relative to other coastal forest types. Therefore, to provide more detailed information regarding the response of coastal forest generalists and mangrove specialists to specific forest attributes, functionally connected forest networks were developed to assess the relative importance of forest area, availability, and connectivity to their compositional turnover. This revealed that mangrove specialists and coastal generalists differ in the forest attributes they require (i.e. area vs. availability) to maintain regional beta diversity. Understanding landscape pattern-process relationships that drive bird assemblage composition and turnover can inform the prioritization of regional-scale landscape features for protection. However, species' responses to local-scale spatiotemporal variability in resource availability may also play a role in these relationships. I used isotopic analysis to better understand the foraging ecology of coastal forest birds in a highly dynamic mangrove forest environment. This demonstrated that flexible and opportunistic foraging strategies were prevalent among coastal forest generalist species. However, specialized foraging strategies were employed by some species, primarily for resources that were uniquely available in mangrove forests (i.e. estuarine fish and crabs). Mobile species not only respond to landscape patterns and processes, but can also facilitate connectivity processes through their movement (e.g. nutrient transfer, pollination, genetic linking, etc.). To determine the implications of avian mobility for ecosystem functioning in northeast Australia, I focused on a migratory coastal forest bird species, the Pied Imperial-Pigeon (Ducula bicolor). Nutrient measurements demonstrated that Pied Imperial-Pigeons provide mainland-derived nutrient subsidies to island forests, highlighting their important role as an avian mobile-link species. The integrated analytical approach used in this thesis has provided insight to the complexity of coastal landscapes and their use by forest avifauna. This has broadened our understanding of coastal ecosystem functioning to include a hierarchy of ecosystem components that exist at local and regional scales. The ecosystem properties that emerge from interactions across coastal ecosystem components include: vegetative connectivity, compositional turnover, avian foraging strategy, and nutrient transfer. Results from this thesis can inform the holistic conservation and management strategies that are required to maintain coastal ecosystem functioning in regional northeast Australia

Host Specificity in Variable Environments

Host specificity encompasses the range and diversity of host species that a parasite is capable of infecting and is considered a crucial measure of a parasite's potential to shift hosts and trigger disease emergence. Yet empirical studies rarely consider that regional observations only reflect a parasite's 'realized' host range under particular conditions: the true 'fundamental' range of host specificity is typically not approached. We provide an overview of challenges and directions in modelling host specificity under variable environmental conditions. Combining tractable modelling frameworks with multiple data sources that account for the strong interplay between a parasite's evolutionary history, transmission mode, and environmental filters that shape host-parasite interactions will improve efforts to quantify emerging disease risk in times of global change

Generalized Linear Models in Bayesian Phylogeography

abstract: Bayesian phylogeography is a framework that has enabled researchers to model the spatiotemporal diffusion of pathogens. In general, the framework assumes that discrete geographic sampling traits follow a continuous-time Markov chain process along the branches of an unknown phylogeny that is informed through nucleotide sequence data. Recently, this framework has been extended to model the transition rate matrix between discrete states as a generalized linear model (GLM) of predictors of interest to the pathogen. In this dissertation, I focus on these GLMs and describe their capabilities, limitations, and introduce a pipeline that may enable more researchers to utilize this framework. I first demonstrate how a GLM can be employed and how the support for the predictors can be measured using influenza A/H5N1 in Egypt as an example. Secondly, I compare the GLM framework to two alternative frameworks of Bayesian phylogeography: one that uses an advanced computational technique and one that does not. For this assessment, I model the diffusion of influenza A/H3N2 in the United States during the 2014-15 flu season with five methods encapsulated by the three frameworks. I summarize metrics of the phylogenies created by each and demonstrate their reproducibility by performing analyses on several random sequence samples under a variety of population growth scenarios. Next, I demonstrate how discretization of the location trait for a given sequence set can influence phylogenies and support for predictors. That is, I perform several GLM analyses on a set of sequences and change how the sequences are pooled, then show how aggregating predictors at four levels of spatial resolution will alter posterior support. Finally, I provide a solution for researchers that wish to use the GLM framework but may be deterred by the tedious file-manipulation requirements that must be completed to do so. My pipeline, which is publicly available, should alleviate concerns pertaining to the difficulty and time-consuming nature of creating the files necessary to perform GLM analyses. This dissertation expands the knowledge of Bayesian phylogeographic GLMs and will facilitate the use of this framework, which may ultimately reveal the variables that drive the spread of pathogens.Dissertation/ThesisDoctoral Dissertation Biomedical Informatics 201

Large-scale population dynamics of the Eurasian red squirrel

The size of an animal population is determined by the birth rate, mortality, and movement of individuals between populations. These demographic parameters, in turn, are affected by internal and external factors. Internal factors include, for example, the density and the sex ratio of the focal population. External factors can be divided to biotic and abiotic factors. In this thesis, I study the population dynamics of the Eurasian red squirrel (Sciurus vulgaris) and factors affecting it on different scales by utilizing snowtrack data, old hunting data and data on nest box occupancy. The red squirrel is widely distributed and common in boreal coniferous forests, and it acts both as a seed disperser and as an alternative prey for several predator species at the low phases of the vole cycle. It has also been an important game mammal, and red squirrel hunting was popular in Finland until the mid-1900s. The results of my thesis show that red squirrel populations fluctuate synchronously within hundreds of kilometers, and that this synchrony is driven by similarly fluctuating and spatially autocorrelated spruce (Picea abies) cone crop. The main predators, the pine marten (Martes martes) and the goshawk (Accipiter gentilis), on the other hand, do not negatively affect red squirrel numbers on the population level. On a smaller scale, however, both the red squirrel and the flying squirrel (Pteromys volans) more likely occupied nest boxes that were far from the nests of avian predators. Thus, the squirrels and their predators are negatively associated on individual level, but the red squirrel and its predators are positively associated on a larger scale. The variation in red squirrel numbers between census sites and years was most strongly affected by spruce cone crop. However, cone crop did not explain the remarkable variations in the red squirrel sex ratio, which were demonstrated by the re-analysis of old hunting data. Overall, food availability emerges as the most significant determinant of red squirrel population density, exceeding the direct and indirect effects of predators. I also found out that the red squirrel is well adapted to human-altered landscape and may even favor mosaic-like areas, even though it is arboreal and adapted to a life in the forest canopy. Both the snow-track data and nest box data suggest that there are more red squirrels near human settlement and in agricultural areas than in continuous forests. A mosaic-like landscape provides red squirrels with alternative food resources, which makes them less dependent on the highly variable conifer cone crop. The apparent preference for agricultural areas by both the red squirrel and the flying squirrel may be partially explained by the higher productivity of forest edges. Even though a red squirrel is still a common sight in backyards and bird-feeding sites, it seems that the species has declined in forests. The analysis of the snow-track data from Finland and north-western Russia revealed that the red squirrel declined in most parts of the 1000000 km2-study area between 1996 and 2012. This alarming trend is partially due to the global warming. I found that the red squirrel population growth rate was lowest in those regions where winters warmed the most. Other climatic parameters, deforestation, and the simultaneous increase in pine marten populations did not explain the decline of the red squirrel. The exact mechanism of how winter warming is detrimental for the red squirrel calls for further studies. The Finnish snow-track data from 1989 to 2017 shows that the red squirrel increased in Southern Finland but declined in other parts of the country. Drawn together, the results of this thesis show that synchrony occurs between red squirrel populations on a scale of hundreds of kilometers, and that the large-scale population dynamics are driven by conifer seed crop while predators have only a minor role. The red squirrel has adapted well to many anthropogenic changes, such as built areas and agricultural fields fragmenting forests, but the global warming seems to pose a threat to it. Studying the changes in red squirrel populations can help understand ecosystems of the boreal forests and the way anthropogenic changes affect them.Eläinpopulaation sisäiset ja ulkoiset tekijät vaikuttavat populaatiokokoon syntyvyyden, kuolleisuuden ja muuttoliikkeen kautta. Sisäisiä eli populaatioon itseensä liittyviä tekijöitä ovat esimerkiksi sukupuolijakauma ja tiheys. Ulkoiset tekijät puolestaan voidaan jakaa eliöiden välisiin vuorovaikutuksiin ja ympäristötekijöihin. Tässä väitöskirjassa tarkastelen oravan (Sciurus vulgaris) populaatiodynamiikkaa ja siihen vaikuttavia tekijöitä eri mittakaavoissa lumijälkiaineistojen, vanhojen metsästysaineistojen ja pönttöjen asutusaineistojen perusteella. Orava on yleinen ja laajalle levinnyt pohjoisella havumetsävyöhykkeellä, ja sillä on tärkeä rooli ekosysteemissä puiden siementen levittäjänä ja monien petojen vaihtoehtoisena saalislajina myyräkantojen ollessa alhaalla. Se on ollut myös tärkeä riistaeläin Suomessa aina 1900-luvun puoliväliin saakka. Tutkimuksissani selvisi, että oravapopulaatioiden koko vaihtelee samanaikaisesti ja -suuntaisesti satojen kilometrien laajuisilla alueilla, ja että tämän synkronisen vaihtelun syy on samalla tavalla voimakkaasti tilassa autokorreloitunut kuusen (Picea abies) käpysato. Oravan luontaisilla pääpedoilla, eli näädällä (Martes martes) ja kanahaukalla (Accipiter gentilis), ei puolestaan havaittu negatiivista vaikutusta oravamääriin populaatiotasolla. Pienemmässä mittakaavassa tarkasteltuna orava, ja myös liito-orava (Pteromys volans), kuitenkin käyttivät eniten sellaisia pönttöjä, jotka sijaitsivat kaukana petolintujen pesistä. Yksilötasolla oravat siis välttivät petoja, kun taas laajemmassa mittakaavassa orava ja sen saalistajat esiintyivät runsaina samoilla alueilla. Käpysato vaikutti myös voimakkaasti oravan runsauden vaihteluun eri laskenta-alueiden ja vuosien välillä. Käpysato ei kuitenkaan ollut yhteydessä oravan sukupuolijakaumaan, joka vaihteli laajoilla alueilla vanhan metsästysaineiston uudelleenanalysoinnin perusteella. Joka tapauksessa lajien välisistä vuorovaikutuksista ravinnon saatavuus ja sen vaihtelu olivat tärkeämpiä tekijöitä oravakantojen säätelyssä kuin petojen aiheuttama kuolleisuus tai petojen läsnäolon epäsuorat vaikutukset. Lisäksi, vaikka orava on sopeutunut elämään puissa ja on selkeästi metsälaji, se vaikuttaa sietävän hyvin ja jopa hyötyvän ihmisen muokkaamasta ympäristöstä. Oravia havaittiin enemmän lähellä ihmisasutusta ja maatalousympäristöä sekä lumijälki- että pönttöaineistoissa. Mosaiikkimainen, monipuolinen ympäristö tarjoaa oraville vaihtoehtoisia ravintoresursseja, jolloin ne eivät ole yhtä riipuvaisia voimakkasti vaihtelevasta kuusen käpysadosta kuin yhtenäisillä metsäalueilla. Valoisat, peltojen rajaamat metsänreunat saattavat olla muuta metsää tuottoisampia alueita, mikä selittäisi näennäisen avoimien alueiden suosimisen sekä oravalla että liito-oravalla. Vaikka oravat ovat yleinen näky ihmisten pihapiireissä, ne vaikuttavat vähentyneen metsissä. Suomen ja Luoteis-Venäjän lumijälkiaineistoista paljastui, että oravakannat laskivat suurimmassa osassa lähes miljoonan neliökilometrin tutkimusaluetta vuosien 1996–2012 välillä. Osasyy tähän huolestuttavaan kehitykseen vaikutti olevan ilmastonmuutos. Havaitsin, että oravan populaation kasvukerroin oli pienin niillä alueilla, joissa talvet lämpenivät eniten. Muut tarkastellut ilmastomuuttujat, metsien hakkuut ja näädän samanaikainen runsastuminen eivät olleet yhteydessä oravakannan laskuun. Ilmastonmuutoksen tarkka vaikutusmekanismi vaatii lisää tutkimuksia. Suomen lumijälkiaineiston perusteella orava runsastui Etelä-Suomessa vuosien 1989– 2017 välillä, mutta kanta on ollut laskussa muissa osissa maata. Väitöskirjani tulokset osoittavat, että oravien määrä vaihtelee synkronisesti satojen kilometrien laajuisilla alueilla, ja että laajan mittakaavan populaatiodynamiikka on vahvasti riippuvainen havupuiden siemensadosta, kun taas petojen rooli on verraten vähäinen. Orava on sopeutunut moniin ihmisen aiheuttamiin muutoksiin, kuten maatalouden pirstomaan maisemaan ja asutuksen läheisyyteen, mutta ilmastonmuutos saattaa vaikuttaa oraviin haitallisesti. Oravan kannanvaihtelujen tutkiminen auttaa osaltaan ymmärtämään pohjoisten havumetsien ekosysteemien toimintaa ja ihmisen vaikutuksia niissä sekä ilmaston että maisemarakenteen muutosten kautta

Understanding and predicting effects of global environmental change on zoonotic disease

Global environmental change is increasingly recognized to influence risk of numerous zoonotic (animal-borne) infectious diseases. There is a fast-growing body of research into climate change effects on zoonotic risks, but broad-scale studies have rarely investigated how climate interacts with other key drivers, in particular land use change. Here, I evaluate effects of land use and climate on zoonotic disease risk, both generally and in a case study disease, by integrating multiple data types (ecological, epidemiological, satellite) and tools from biodiversity science, spatiotemporal epidemiology and land use modelling. First, I compile and analyse a global database of local species communities and their pathogens, and show that ecological communities in anthropogenic land uses globally are increasingly dominated by zoonotic host species, including mammalian reservoirs of globally-significant zoonoses, and that these trends are likely mediated by species traits. Second, I examine interacting effects of land, climate and socioeconomic factors on Lassa fever (LF), a neglected rodent-borne viral zoonosis that is a significant public health concern in West Africa, focusing on disease risk projection at both short (interannual) and long (multi-decadal) time horizons. In an epidemiological analysis of case surveillance time series from Nigeria, I show that present-day human LF incidence is associated with climate, agriculture and poverty, that periodic surges in LF cases are predicted by seasonal climate-vegetation dynamics, and that recent emergence trends are most likely underpinned by improving surveillance. At longer timescales, I then couple a mechanistic disease risk model with a dynamic land change model and climate projections, to show that different economic and climate policy futures (Shared Socioeconomic Pathways) may result in markedly different outcomes for LF risk and burden by 2030 and 2050 across West Africa. Finally, I synthesise the implications of these results for our understanding of the global change ecology of zoonotic disease, the epidemiology and control of LF, and for broader Planetary Health perspectives on managing zoonotic risks

한국 SARS-CoV-2 대유행의 베이지안 계통지리학적 분석과 이에 영향을 미치는 요인

학위논문(석사) -- 서울대학교대학원 : 보건대학원 보건학과(보건학전공), 2023. 2. 조성일.Following the global emergence of the Alpha variant of concern (VOC) of SARS-CoV-2 in 2019, another wave emerged due to the SARS-CoV-2 Delta variant in 2021. The AY.69 lineage, a Delta VOC, was particularly prevalent in Korea between May 2021 and January 2022, despite the synchronized implementation of vaccine programs and non-pharmaceutical interventions (NPIs), such as social distancing. Here, we used phylogeographic analysis supplemented by a generalized linear model (GLM) to determine the influence of human movement and vaccination on viral transmission. The results suggested that transmission began predominantly in the metropolitan areas of South Korea, and that total human mobility tracked by GPS using mobile phones and estimated by credit card consumption had a positively affected the occurrence of introduction events. This phylodynamic findings also supported the notion that non-vaccinated persons dominantly transmitted the virus during the study period, despite of vaccination programs that started three months before the propagation of AY.69. Therefore, our results suggest that co-implementing both NPIs and an early vaccination program would effectively reduce viral spread.2019년에 SARS-CoV-2 알파 우려 변종(VOC, Variant of Concern)이 유행한 이후 2021년 델타 변이 중 특히 AY.69 우려 변종 바이러스가 한국의 코로나바이러스 유행을 이끌었다. AY.69는 2021년 5월부터 2022년 1월까지 백신접종 프로그램이나 사회적 거리두기와 같은 비약물적 중재정책을 도입했음에도 불구하고 한국에서 특히 큰 유행을 이끌었다. 본 연구에서는 선형회귀모델(GLM) 분석을 통해 사람들의 이동과 면역도와 바이러스의 전파와의 관계를 알아보기 위해 계통지리학적 분석을 실시하였다. 결과에 따르면 전파는 한국의 수도권 지역에서 시작되었으며, 해당 지역 사람들의 신용카드 사용량과 휴대용 이동통신기기의 GPS로 측정한 사람들의 모든 이동량이 다른 지역으로의 바이러스 유입과 관련이 있는 것으로 나타났다. 또한 본 계통역학적 연구는 한국에서는 AY.69 변이 바이러스가 유행하기 3개월 전에 백신접종 프로그램이 시작되었지만, 백신 접종을 하지 않은 사람들이 유행기간동안 바이러스 전파를 주도하였다는 것을 계통 지리학적 분석을 통해 밝혔다. 따라서 본 연구는 비약물적 중재정책과 백신접종 프로그램을 동시에 실시하는 것이 바이러스의 전파를 효율적으로 막을 수 있다는 것을 제안한다.Chapter 1. Introduction 1 1.1. Study background 1 1.2. Purposes of research 2 Chapter 2. Methods 6 2.1. Sequence data and subsampling 6 2.2. Bayesian Phylogeographic Analysis 8 2.3. Mobility Data 9 2.4. Generalized linear model of discrete trait diffusion 10 Chapter 3. Results 11 3.1. The AY.69 variant was predominant in mid-2021 in South Korea 11 3.2. AY.69 variant mostly spread from Seoul and Gyeong-gi 16 3.3. AY.69 variant mostly spread from Non-vaccinated group 20 3.4. GLM analysis of mobility data and phylogeography 23 Chapter 4. Discussion 30 Chapter 5. Conclusion 35 Bibliography 36 국문초록 43 Appendix 45석

Exploring the phylodynamics, genetic reassortment and RNA secondary structure formation patterns of orthomyxoviruses by comparative sequence analysis

RNA viruses are among the most virulent microorganisms that threaten the health of humans and livestock. Among the most socio-economically important of the known RNA viruses are those found in the family Orthomyxovirus. In this era of rapid low-cost genome sequencing and advancements in computational biology techniques, many previously difficult research questions relating to the molecular epidemiology and evolutionary dynamics of these viruses can now be answered with ease. Using sequence data together with associated meta-data, in chapter two of this dissertation I tested the hypothesis that the Influenza A/H1N1 2009 pandemic virus was introduced multiple times into Africa, and subsequently dispersed heterogeneously across the continent. I further tested to what degree factors such as road distances and air travel distances impacted the observed pattern of spread of this virus in Africa using a generalised linear modelbased approach. The results suggested that their were multiple simultaneous introductions of 2009 pandemic A/H1N1 into Africa, and geographical distance and human mobility through air travel played an important role towards dissemination. In chapter three, I set out to test two hypotheses: (1) that there is no difference in the frequency of reassortments among the segments that constitute influenza virus genomes; and (2) that there is epochal temporal reassortment among influenza viruses and that all geographical regions are equally likely sources of epidemiologically important influenza virus reassortant lineages. The findings suggested that surface segments are more frequently exchanges than internal genes and that North America/Asia, Oceania, and Asia could be the most likely source locations for reassortant Influenza A, B and C virus lineages respectively. In chapter four of this thesis, I explored the formation of RNA secondary structures within the genomes of orthomyxoviruses belonging to five genera: Influenza A, B and C, Infectious Salmon Anaemia Virus and Thogotovirus using in silico RNA folding predictions and additional molecular evolution and phylogenetic tests to show that structured regions may be biologically functional. The presence of some conserved structures across the five genera is likely a reflection of the biological importance of these structures, warranting further investigation regarding their role in the evolution and possible development of antiviral resistance. The studies herein demonstrate that pathogen genomics-based analytical approaches are useful both for understanding the mechanisms that drive the evolution and spread of rapidly evolving viral pathogens such as orthomyxoviruses, and for illuminating how these approaches could be leveraged to improve the management of these pathogens