Climate Change Influences on the Global Potential Distribution of Bluetongue Virus

A grant from the One-University Open Access Fund at the University of Kansas was used to defray the author's publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.The geographic distribution of arboviruses has received considerable attention after several dramatic emergence events around the world. Bluetongue virus (BTV) is classified among category “A” diseases notifiable to the World Organization of Animal Health (OIE), and is transmitted among ruminants by biting midges of the genus Culicoides. Here, we developed a comprehensive occurrence data set to map the current distribution, estimate the ecological niche, and explore the future potential distribution of BTV globally using ecological niche modeling and based on diverse future climate scenarios from general circulation models (GCMs) for four representative concentration pathways (RCPs). The broad ecological niche and potential geographic distribution of BTV under present-day conditions reflected the disease’s current distribution across the world in tropical, subtropical, and temperate regions. All model predictions were significantly better than random expectations. As a further evaluation of model robustness, we compared our model predictions to 331 independent records from most recent outbreaks from the Food and Agriculture Organization Emergency Prevention System for Transboundary Animal and Plant Pests and Diseases Information System (EMPRES-i); all were successfully anticipated by the BTV model. Finally, we tested ecological niche similarity among possible vectors and BTV, and could not reject hypotheses of niche similarity. Under future-climate conditions, the potential distribution of BTV was predicted to broaden, especially in central Africa, United States, and western Russia

Geographic distribution modeling of infectious disease dynamics in space and time

The geographic distribution of infectious diseases has received considerable attention after several dramatic emergence events around the world. Here, I took the full advantages of several approaches available in a single toolbox to examine geographic distribution and spread of several neglected and zoonotic diseases across the world. These approaches included geographic information system, remote sensing, ecological niche modeling, and phylogeography of disease outbreaks. The results assessed and evaluated several diseases based on their public health importance, data availability, and geographic dimension. These diseases included major neglected tropical diseases of potential public health worldwide (e.g. mycetoma, and leishmaniasis), zoonosis (e.g. Rift Valley Fever), and livestock diseases (e.g. Bluetongue). In 2013, the World Health Organization (WHO) recognized mycetoma as one of the neglected tropical conditions due to the efforts of the mycetoma consortium. This same consortium formulated knowledge gaps that require further research. One of these gaps was that very few data are available on the epidemiology and transmission cycle of the causative agents. Previous work suggested a soil-borne or Acacia thorn-prick-mediated origin of mycetoma infections, but no studies have investigated effects of soil type and Acacia geographic distribution on mycetoma case distributions. In chapter 1, the study mapped risk of mycetoma infection across Sudan and South Sudan using ecological niche modeling (ENM). I developed ENMs based on case occurrences, and digital GIS data layers summarizing soil characteristics, land-surface temperature, and greenness indices to provide a rich picture of environmental variation across Sudan and South Sudan. ENMs were calibrated in known endemic districts and transferred countrywide; model results suggested that risk is greatest in an east-west belt across central Sudan. Visualizing ENMs in environmental dimensions, mycetoma occurs under diverse environmental conditions. The study also compared niches of mycetoma and Acacia trees, and could not reject the null hypothesis of niche similarity. This study revealed contributions of different environmental factors to mycetoma infection risk, identified suitable environments and regions for transmission, signaled a potential mycetoma-Acacia association, and provided steps towards a robust risk map for the disease. In chapter 2, I studied another neglected tropical disease in Libya where political instability prevent active surveillance of cutaneous leishmaniasis (CL). CL ranks among the tropical diseases least known and most neglected in Libya. World Health Organization reports recognized associations of Phlebotomus papatasi, Psammomys obesus, and Meriones spp., with transmission of zoonotic cutaneous leishmaniasis (ZCL; caused by Leishmania major) across Libya. Here, the study map risk of ZCL infection based on occurrence records of L. major, P. papatasi, and four potential animal reservoirs (Meriones libycus, Meriones shawi, Psammomys obesus, and Gerbillus gerbillus). Ecological niche models identified limited risk areas for ZCL across the northern coast of the country; most species associated with ZCL transmission were confined to this same region, but some had ranges extending to central Libya. All ENM predictions were significant based on partial ROC tests. As a further evaluation of L. major ENM predictions, the study compared predictions with 98 additional independent records provided by the Libyan National Centre for Disease Control (NCDC); all of these records fell inside the belt predicted as suitable for ZCL. The study tested ecological niche similarity among vector, parasite, and reservoir species and could not reject any null hypotheses of niche similarity. Finally, I tested among possible combinations of vector and reservoir that could predict all recent human ZCL cases reported by NCDC; only three combinations could anticipate the distribution of human cases across the country. Further in chapter 3, I developed a comprehensive occurrence data set to map the current distribution, estimate the ecological niche, and explore the future potential distribution of BTV globally using ecological niche modeling and based on diverse future climate scenarios from general circulation models (GCMs) for four representative concentration pathways (RCPs). The broad ecological niche and potential geographic distribution of BTV under present-day conditions reflected the disease’s current distribution across the world in tropical, subtropical, and temperate regions. All model predictions were significantly better than random expectations. As a further evaluation of model robustness, I compared our model predictions to 331 independent records from most recent outbreaks from the Food and Agriculture Organization Emergency Prevention System for Transboundary Animal and Plant Pests and Diseases Information System (EMPRES-i); all were successfully anticipated by the BTV model. Finally, I tested ecological niche similarity among possible vectors and BTV, and could not reject hypotheses of niche similarity. Under future-climate conditions, the potential distribution of BTV was predicted to broaden, especially in central Africa, United States, and western Russia. Finally, in chapter 4, I used phylogenetic analyses to understand the demographic history of RVFV populations, using sequence data from the three minigenomic segments of the virus. I used phylogeographic approaches to infer RVFV historical movement patterns across its geographic range, and to reconstruct transitions among host species. Results revealed broad circulation of the virus in East Africa, with many lineages originating in Kenya. Arrival of RVFV in Madagascar resulted from three major waves of virus introduction: the first from Zimbabwe, and the second and third from Kenya. The two major outbreaks in Egypt since 1977 possibly resulted from a long-distance introduction from Zimbabwe during the 1970s, and a single introduction took RVFV from Kenya to Saudi Arabia. Movement of the virus between Kenya and Sudan, and CAR and Zimbabwe was in both directions. Viral populations in West Africa appear to have resulted from a single introduction from Central African Republic. Finally, host transition analysis identified both humans and livestock as natural hosts of RVFV. The overall picture of RVFV history is thus one of considerable mobility, and dynamic evolution and biogeography, emphasizing its invasive potential, potentially more broadly than its current distributional limits. The results raised by all these analyses offered the potential capacity of ecological modeling and phylogeographic approaches to understand the potential distribution and spread of different disease systems and open the possibilities for their applications in understanding disease epidemiology for surveillance and control efforts of several other disease systems emerged recently across the world

Phylogeography of Rift Valley Fever Virus in Africa and the Arabian Peninsula

Rift Valley Fever is an acute zoonotic viral disease caused by Rift Valley Fever virus (RVFV) that affects ruminants and humans in Sub-Saharan Africa and the Arabian Peninsula. We used phylogenetic analyses to understand the demographic history of RVFV populations, using sequence data from the three minigenomic segments of the virus. We used phylogeographic approaches to infer RVFV historical movement patterns across its geographic range, and to reconstruct transitions among host species. Results revealed broad circulation of the virus in East Africa, with many lineages originating in Kenya. Arrival of RVFV in Madagascar resulted from three major waves of virus introduction: the first from Zimbabwe, and the second and third from Kenya. The two major outbreaks in Egypt since 1977 possibly resulted from a long-distance introduction from Zimbabwe during the 1970s, and a single introduction took RVFV from Kenya to Saudi Arabia. Movement of the virus between Kenya and Sudan, and CAR and Zimbabwe, was in both directions. Viral populations in West Africa appear to have resulted from a single introduction from Central African Republic. The overall picture of RVFV history is thus one of considerable mobility, and dynamic evolution and biogeography, emphasizing its invasive potential, potentially more broadly than its current distributional limits

Species composition of sand flies and bionomics of Phlebotomus papatasi and P. sergenti (Diptera: Psychodidae) in cutaneous leishmaniasis endemic foci, Morocco

Detailed data set for sand fly species sampled in 48 sites across Morocco from April to June 2013. The specimens were sorted as male or female for each species. The coordinates (longitude and latitude) for each site is also presented in this data set. (XLSX 23 kb

First Report of Leishmania tropica from a Classical Focus of L. major in North-Sinai, Egypt

This is the publisher's version, also available electronically from http://www.ajtmh.org/content/81/2/213.long.Cutaneous leishmaniasis (CL) is prevalent in the Egyptian Sinai Peninsula and previous research has consistently documented the etiologic agent to be Leishmania major. We report the first isolation of Leishmania tropica from human cases of CL in a Northern Sinai community bordering Palestine. Parasite culturing, real-time polymerase chain reaction (PCR), gene sequencing, and restriction fragment length polymorphism (RFLP) analyses indicate CL cases in this community were caused by either L. major or L. tropica (three cases each). Two wild-caught rodents (Gerbillus pyramidum floweri) were infected with L. tropica. Phlebotomus papatasi sand flies were found harboring L. major, however only non-infected individuals of Phlebotomus sergenti, a vector for L. tropica, were caught. Patients with L. tropica had not traveled from the region in over a year, suggesting these cases are autochthonous. This scenario is consistent with an incursion of L. tropica from bordering countries and raises concerns about expansion of this parasite further into Egypt

Coarse-resolution Ecology of Etiological Agent, Vector, and Reservoirs of Zoonotic Cutaneous Leishmaniasis in Libya

Cutaneous leishmaniasis ranks among the tropical diseases least known and most neglected in Libya. World Health Organization reports recognized associations of Phlebotomus papatasi, Psammomys obesus, and Meriones spp., with transmission of zoonotic cutaneous leishmaniasis (ZCL; caused by Leishmania major) across Libya. Here, we map risk of ZCL infection based on occurrence records of L. major, P. papatasi, and four potential animal reservoirs (Meriones libycus, Meriones shawi, Psammomys obesus, and Gerbillus gerbillus). Ecological niche models identified limited risk areas for ZCL across the northern coast of the country; most species associated with ZCL transmission were confined to this same region, but some had ranges extending to central Libya. All ENM predictions were significant based on partial ROC tests. As a further evaluation of L. major ENM predictions, we compared predictions with 98 additional independent records provided by the Libyan National Centre for Disease Control (NCDC); all of these records fell inside the belt predicted as suitable for ZCL. We tested ecological niche similarity among vector, parasite, and reservoir species and could not reject any null hypotheses of niche similarity. Finally, we tested among possible combinations of vector and reservoir that could predict all recent human ZCL cases reported by NCDC; only three combinations could anticipate the distribution of human cases across the country

Mapping the Potential Risk of Mycetoma Infection in Sudan and South Sudan Using Ecological Niche Modeling

In 2013, the World Health Organization (WHO) recognized mycetoma as one of the neglected tropical conditions due to the efforts of the mycetoma consortium. This same consortium formulated knowledge gaps that require further research. On

Acknowledging uncertainty in evolutionary reconstructions of ecological niches

Reconstructing ecological niche evolution can provide insight into the biogeography and diversification of evolving lineages. However, comparative phylogenetic methods may infer the history of ecological niche evolution inaccurately because (a) species' niches are often poorly characterized; and (b) phylogenetic comparative methods rely on niche summary statistics rather than full estimates of species' environmental tolerances. Here, we propose a new framework for coding ecological niches and reconstructing their evolution that explicitly acknowledges and incorporates the uncertainty introduced by incomplete niche characterization. Then, we modify existing ancestral state inference methods to leverage full estimates of environmental tolerances. We provide a worked empirical example of our method, investigating ecological niche evolution in the New World orioles (Aves: Passeriformes: Icterus spp.). Temperature and precipitation tolerances were generally broad and conserved among orioles, with niche reduction and specialization limited to a few terminal branches. Tools for performing these reconstructions are available in a new R package called nichevol

Acknowledging uncertainty in evolutionary reconstructions of ecological niches

Reconstructing ecological niche evolution can provide insight into the biogeography and diversification of evolving lineages. However, comparative phylogenetic methods may infer the history of ecological niche evolution inaccurately because (a) species' niches are often poorly characterized; and (b) phylogenetic comparative methods rely on niche summary statistics rather than full estimates of species' environmental tolerances. Here, we propose a new framework for coding ecological niches and reconstructing their evolution that explicitly acknowledges and incorporates the uncertainty introduced by incomplete niche characterization. Then, we modify existing ancestral state inference methods to leverage full estimates of environmental tolerances. We provide a worked empirical example of our method, investigating ecological niche evolution in the New World orioles (Aves: Passeriformes: Icterus spp.). Temperature and precipitation tolerances were generally broad and conserved among orioles, with niche reduction and specialization limited to a few terminal branches. Tools for performing these reconstructions are available in a new R package called nichevol

Editorial: Coronavirus disease (COVID-19): pathophysiology, epidemiology, clinical management and public health response

During a pandemic, there are multiple concurrent clinical and scientific priorities, including the need to understand the pathophysiology of the disease, the different modes of transmission, how patient care can be optimized, as well as the need to develop mathematical models that can now cast and forecast the progression of infections within given populations and/or geographical regions. When the current SARS-CoV2 pandemic was declared a Public Health Emergency of International Concern by the World Health Organization, a formal declaration of its gravity, it became evident that there was an acute need to understand all of the above aspects. In doing so, by 11th February 2020, a special topic, entitled “Coronavirus Disease (COVID-19): Pathophysiology, Epidemiology, Clinical Management and Public Health Response,” was initiated with a dedicated team of handling editors to facilitate the timely peer-review and publication of relevant manuscripts (1). Frontiers, as the publisher of this special topic, took the bold step of waiving any article processing charges so that financial constraints would not be a barrier to communicating crucial information about the pandemic to a broad audience. Furthermore, this was the most extensive special topic to date in the Frontiers portfolio, in terms of the numbers of participating Frontiers journals, disciplines, and sections. This reflected the acute need for the scientific community to understand the many aspects of the pandemic. This special Research Topic captured the entire first wave in the northern hemisphere, from February to May 2020, and the intensity of the associated editorial work is evident by the reported numbers. Within 4 months, 194 abstracts were received; in total 851 manuscripts were submitted, of which 453 were rejected while 398 were published. From the scientific community perspective, by June 2020 the special topic achieved over 2 million views, by December 2020 over 4 million views, and by August 2021 over 8 million views. As an example of the breadth of subjects covered, manuscripts included the attempt by Larsen et al. to model the onset of symptoms of COVID-19; the observed gender differences on COVID-19 patients’ severity and mortality by Jin et al., the correlation between poverty levels and rates of COVID-19 incidence and death in the United States by Finch and Finch, as well as the careful review of the cytokine storm in COVID-19 (Tang et al.