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Predicting the evolution of the Lassa virus endemic area and population at risk over the next decades

Predicting the evolution of the Lassa virus endemic area and population at risk over the next decades

 


  • Morens, D. M. et al. The origin of COVID-19 and why it matters. Am. J. Trop. Med. Hyg. 103, 955–959 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Pierson, T. C. & Diamond, M. S. The emergence of Zika virus and its new clinical syndromes. Nature 560, 573–581 (2018).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Gates, B. The next epidemic—Lessons from Ebola., https://doi.org/10.1056/NEJMp1502918 (2015).

  • World Health Organization. Lassa fever research and development (R&D) roadmap. https://www.who.int/publications/m/item/lassa-fever-research-and-development-(r-d)-roadmap (2018).

  • World Health Organization. Prioritizing diseases for research and development in emergency contexts. https://www.who.int/activities/prioritizing-diseases-for-research-and-development-in-emergency-contexts.

  • Akpede, G. O. et al. Caseload and case fatality of Lassa fever in Nigeria, 2001–2018: A specialist center’s experience and its implications. Front. Public Health 7, https://doi.org/10.3389/fpubh.2019.00170 (2019).

  • Eberhardt, K. A. et al. Ribavirin for the treatment of Lassa fever: A systematic review and meta-analysis. Int. J. Infect. Dis. 87, 15–20 (2019).

    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Lukashevich, I. S., Paessler, S. & de la Torre, J. C. Lassa virus diversity and feasibility for universal prophylactic vaccine. F1000Res 8, https://doi.org/10.12688/f1000research.16989.1 (2019).

  • Purushotham, J., Lambe, T. & Gilbert, S. C. Vaccine platforms for the prevention of Lassa fever. Immunol. Lett. 215, 1–11 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Mateo, M. et al. A single-shot Lassa vaccine induces long-term immunity and protects cynomolgus monkeys against heterologous strains. Sci. Transl. Med. 13, eabf6348 (2021).

    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • McCormick, J. B. et al. Lassa Fever. N. Engl. J. Med. 314, 20–26 (1986).

    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Bell-Kareem, A. R. & Smither, A. R. Epidemiology of Lassa fever. in 1–23 (Springer, 2021). https://doi.org/10.1007/82_2021_234.

  • Nigeria Centre for Disease Control. https://ncdc.gov.ng/diseases/sitreps/?cat=5&name=An%20update%20of%20Lassa%20fever%20outbreak%20in%20Nigeria.

  • Manning, J. T., Forrester, N. & Paessler, S. Lassa virus isolates from Mali and the Ivory Coast represent an emerging fifth lineage. Front. Microbiol. 6, https://doi.org/10.3389/fmicb.2015.01037 (2015).

  • Dzotsi, E. K. et al. The first cases of Lassa fever in Ghana. Ghana. Med. J. 46, 166–170 (2012).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Patassi, A. A. et al. Emergence of Lassa fever disease in northern Togo: Report of two cases in Oti District in 2016. Case Rep. Infect. Dis. 2017, 8242313 (2017).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Yadouleton, A. et al. Lassa fever in Benin: Description of the 2014 and 2016 epidemics and genetic characterization of a new Lassa virus. Emerg. Microbes Infect. 9, 1761–1770 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • McCormick, J. B. & Fisher-Hoch, S. P. Lassa fever. Curr. Top. Microbiol. Immunol. 262, 75–109 (2002).

    CAS 
    PubMed 

    Google Scholar
     

  • Monath, T. P., Newhouse, V. F., Kemp, G. E., Setzer, H. W. & Cacciapuoti, A. Lassa virus isolation from Mastomys natalensis rodents during an epidemic in Sierra Leone. Science 185, 263–265 (1974).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Stephenson, E. H., Larson, E. W. & Dominik, J. W. Effect of environmental factors on aerosol-induced Lassa virus infection. J. Med. Virol. 14, 295–303 (1984).

    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Wozniak, D. M. et al. Inoculation route-dependent Lassa virus dissemination and shedding dynamics in the natural reservoir – Mastomys natalensis. Emerg. Microbes Infect. 10, 2313–2325 (2021).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Ter Meulen, J. et al. Hunting of peridomestic rodents and consumption of their meat as possible risk factors for rodent-to-human transmission of Lassa virus in the Republic of Guinea. Am. J. Trop. Med. Hyg. 55, 661–666 (1996).

    PubMed 
    Article 

    Google Scholar
     

  • Downs, I. L. et al. Natural history of aerosol induced Lassa fever in non-human primates. Viruses 12, 593 (2020).

    CAS 
    PubMed Central 
    Article 

    Google Scholar
     

  • Lecompte, E. et al. Mastomys natalensis and Lassa Fever, West Africa. Emerg. Infect. Dis. 12, 1971–1974 (2006).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Smither, A. R. & Bell-Kareem, A. R. Ecology of Lassa Virus. in 1–20 (Springer, 2021). https://doi.org/10.1007/82_2020_231.

  • Ogbu, O., Ajuluchukwu, E. & Uneke, C. J. Lassa fever in West African sub-region: An overview. J. Vector Borne Dis. 44, 1–11 (2007).

    CAS 
    PubMed 

    Google Scholar
     

  • Fichet-Calvet, E. et al. Fluctuation of abundance and Lassa virus prevalence in Mastomys natalensis in Guinea, West Africa. Vector Borne Zoonotic Dis. 7, 119–128 (2007).

    PubMed 
    Article 

    Google Scholar
     

  • Fichet-Calvet, E., Becker-Ziaja, B., Koivogui, L. & Günther, S. Lassa serology in natural populations of rodents and horizontal transmission. Vector Borne Zoonotic Dis. 14, 665–674 (2014).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Lo Iacono, G. et al. Using modelling to disentangle the relative contributions of zoonotic and anthroponotic transmission: The case of Lassa fever. PLoS Negl. Trop. Dis. 9, e3398 (2015).

  • Siddle, K. J. et al. Genomic analysis of Lassa virus during an increase in cases in Nigeria in 2018. N. Engl. J. Med. 379, 1745–1753 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Kafetzopoulou, L. E. et al. Metagenomic sequencing at the epicenter of the Nigeria 2018 Lassa fever outbreak. Science 363, 74–77 (2019).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Andersen, K. G. et al. Clinical sequencing uncovers origins and evolution of Lassa virus. Cell 162, 738–750 (2015).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Lalis, A. & Wirth, T. Mice and men: An evolutionary history of Lassa fever. in Biodiversity and Evolution (eds. Grandcolas, P. & Maurel, M.-C.) 189–212, https://doi.org/10.1016/B978-1-78548-277-9.50011-5 (Elsevier, 2018).

  • Mylne, A. Q. N. et al. Mapping the zoonotic niche of Lassa fever in Africa. Trans. R. Soc. Trop. Med. Hyg. 109, 483–492 (2015).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Colangelo, P. et al. A mitochondrial phylogeographic scenario for the most widespread African rodent, Mastomys natalensis. Biol. J. Linn. Soc. 108, 901–916 (2013).

    Article 

    Google Scholar
     

  • Gryseels, S. et al. When viruses don’t go viral: The importance of host phylogeographic structure in the spatial spread of arenaviruses. PLoS Path 13, e1006073 (2017).

    Article 

    Google Scholar
     

  • Cuypers, L. N. et al. Three arenaviruses in three subspecific natal multimammate mouse taxa in Tanzania: Same host specificity, but different spatial genetic structure? Virus Evol. https://doi.org/10.1093/ve/veaa039 (2020).

  • Vazeille, M., Gaborit, P., Mousson, L., Girod, R. & Failloux, A.-B. Competitive advantage of a dengue 4 virus when co-infecting the mosquito Aedes aegypti with a dengue 1 virus. BMC Infect. Dis. 16, 318 (2016).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Chan, K. F. et al. Investigating viral interference between influenza A virus and human respiratory syncytial virus in a ferret model of infection. J. Infect. Dis. 218, 406–417 (2018).

    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Meunier, D. Y., McCormick, J. B., Georges, A. J., Georges, M. C. & Gonzalez, J. P. Comparison of Lassa, Mobala, and Ippy virus reactions by immunofluorescence test. Lancet 1, 873–874 (1985).

    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Howard, C. R. Antigenic diversity among the Arenaviruses. in The Arenaviridae (ed. Salvato, M. S.) 37–49, https://doi.org/10.1007/978-1-4615-3028-2_3 (Springer US, 1993).

  • Bhattacharyya, S., Gesteland, P. H., Korgenski, K., Bjørnstad, O. N. & Adler, F. R. Cross-immunity between strains explains the dynamical pattern of paramyxoviruses. Proc. Natl Acad. Sci. U. S. A. 112, 13396–13400 (2015).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Luis, A. D., Douglass, R. J., Mills, J. N. & Bjørnstad, O. N. Environmental fluctuations lead to predictability in Sin Nombre hantavirus outbreaks. Ecology 96, 1691–1701 (2015).

    Article 

    Google Scholar
     

  • Anderson, R. M., Jackson, H. C., May, R. M. & Smith, A. M. Population dynamics of fox rabies in Europe. Nature 289, 765–771 (1981).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Tian, H. et al. Anthropogenically driven environmental changes shift the ecological dynamics of hemorrhagic fever with renal syndrome. PLoS Pathog. 13, e1006198 (2017).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Redding, D. W., Moses, L. M., Cunningham, A. A., Wood, J. & Jones, K. E. Environmental-mechanistic modelling of the impact of global change on human zoonotic disease emergence: a case study of Lassa fever. Methods Ecol. Evol. 7, 646–655 (2016).

    Article 

    Google Scholar
     

  • Peterson, A. T., Moses, L. M. & Bausch, D. G. Mapping transmission risk of Lassa fever in West Africa: the importance of quality control, sampling bias, and error weighting. PLoS One 9, e100711 (2014).

    ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Fichet-Calvet, E. & Rogers, D. J. Risk maps of Lassa fever in West Africa. PLoS. Negl. Trop. Dis. 3, e388 (2009).

  • Basinski, A. J. et al. Bridging the gap: Using reservoir ecology and human serosurveys to estimate Lassa virus spillover in West Africa. PLoS Comput. Biol. 17, e1008811 (2021).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Iacono, G. L. et al. A unified framework for the infection dynamics of zoonotic spillover and spread. PLoS Negl. Trop. Dis. 10, e0004957 (2016).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Coumou, D. & Rahmstorf, S. A decade of weather extremes. Nat. Clim. Change 2, 491–496 (2012).

    ADS 
    Article 

    Google Scholar
     

  • Coumou, D., Robinson, A. & Rahmstorf, S. Global increase in record-breaking monthly-mean temperatures. Clim. Change 118, 771–782 (2013).

    ADS 
    Article 

    Google Scholar
     

  • Bathiany, S., Dakos, V., Scheffer, M. & Lenton, T. M. Climate models predict increasing temperature variability in poor countries. Sci. Adv. 4, eaar5809 (2018).

    ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Arneth, A. Uncertain future for vegetation cover. Nature 524, 44–45 (2015).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Brandt, M. et al. Human population growth offsets climate-driven increase in woody vegetation in sub-Saharan Africa. Nat. Ecol. Evol. 1, 81 (2017).

    PubMed 
    Article 

    Google Scholar
     

  • Herrmann, S. M., Brandt, M., Rasmussen, K. & Fensholt, R. Accelerating land cover change in West Africa over four decades as population pressure increased. Com. Earth Envir 1, 1–10 (2020).


    Google Scholar
     

  • Gibb, R., Moses, L. M., Redding, D. W. & Jones, K. E. Understanding the cryptic nature of Lassa fever in West Africa. Pathog. Glob. Health 111, 276–288 (2017).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Elith, J., Leathwick, J. R. & Hastie, T. A working guide to boosted regression trees. J. Anim. Ecol. 77, 802–813 (2008).

    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Frieler, K. et al. Assessing the impacts of 1.5 °C global warming—simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b). Geosci. Model Dev. 10, 4321–4345 (2017).

    ADS 
    Article 

    Google Scholar
     

  • Soberón, J. & Nakamura, M. Niches and distributional areas: Concepts, methods, and assumptions. Proc. Natl Acad. Sci. U. S. A. 106, 19644–19650 (2009).

    ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Moss, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Lemey, P., Rambaut, A., Welch, J. J. & Suchard, M. A. Phylogeography takes a relaxed random walk in continuous space and time. Mol. Biol. Evol. 27, 1877–1885 (2010).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Lukashevich, I. S. Generation of reassortants between African arenaviruses. Virology 188, 600–605 (1992).

    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Vijaykrishna, D., Mukerji, R. & Smith, G. J. D. RNA virus reassortment: an evolutionary mechanism for host jumps and immune evasion. PLoS Path 11, e1004902 (2015).

    Article 

    Google Scholar
     

  • Whitmer, S. L. M. et al. New lineage of Lassa Virus, Togo, 2016. Emerg. Infect. Dis. 24, 599 (2018).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Ehichioya, D. U. et al. Phylogeography of Lassa virus in Nigeria. J. Virol. 93, e00929–19 (2019).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Dellicour, S., Rose, R., Faria, N. R., Lemey, P. & Pybus, O. G. SERAPHIM: studying environmental rasters and phylogenetically informed movements. Bioinformatics 32, 3204–3206 (2016).

    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Dellicour, S. et al. Using viral gene sequences to compare and explain the heterogeneous spatial dynamics of virus epidemics. Mol. Biol. Evol. 34, 2563–2571 (2017).

    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Dellicour, S. et al. Epidemiological hypothesis testing using a phylogeographic and phylodynamic framework. Nat. Commun. 11, 5620 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Dijkstra, E. W. A note on two problems in connexion with graphs. Numer. Math. 1, 269–271 (1959).

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • Strahler, A. N. Quantitative analysis of watershed geomorphology. Eos, Trans. Am. Geophys. Union 38, 913–920 (1957).

    Article 

    Google Scholar
     

  • Kass, R. E. & Raftery, A. E. Bayes factors. J. Am. Stat. Assoc. 90, 773–795 (1995).

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • Ehichioya, D. U. et al. Current molecular epidemiology of Lassa virus in Nigeria. J. Clin. Microbiol. 49, 1157 (2011).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Oloniniyi, O. K. et al. Genetic characterization of Lassa virus strains isolated from 2012 to 2016 in southeastern Nigeria. PLoS Negl. Trop. Dis. 12, e0006971 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Olesen, J. E. et al. Uncertainties in projected impacts of climate change on European agriculture and terrestrial ecosystems based on scenarios from regional climate models. Clim. Change 81, 123–143 (2007).

    Article 

    Google Scholar
     

  • Simo Tchetgna, H. et al. Molecular characterization of a new highly divergent Mobala related arenavirus isolated from Praomys sp. rodents. Sci. Rep. 11, 10188 (2021).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Olayemi, A. et al. New hosts of the Lassa virus. Sci. Rep. 6, 25280 (2016).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Zaidi, M. B. et al. Competitive suppression of dengue virus replication occurs in chikungunya and dengue co-infected Mexican infants. Parasit. Vectors 11, 378 (2018).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Olayemi, A. et al. Widespread arenavirus occurrence and seroprevalence in small mammals, Nigeria. Parasit. Vectors 11, 416 (2018).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Nigeria Centre for Disease Control. https://ncdc.gov.ng/diseases/sitreps/?cat=5&name=An%20update%20of%20Lassa%20fever%20outbreak%20in%20Nigeria.

  • Norris, K. et al. Biodiversity in a forestagriculture mosaic: the changing face of west Africa rainforests. Biol. Conserv. 143, 2341–2350 (2010).

    Article 

    Google Scholar
     

  • Stocker, T. F. et al. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the fifth assessment report of the Intergovernmental Panel on Climate Change. (Cambridge University Press, Cambridge, United Kingdom and New York, 2013).

  • Buba, M. I. et al. Mortality among confirmed Lassa fever cases during the 2015-2016 outbreak in Nigeria. Am. J. Public Health 108, 262–264 (2018).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Tobin, E. A. et al. Knowledge of secondary school children in Edo State on Lassa fever and its implications for prevention and control. West. Afr. J. Med. 34, 101–107 (2015).

    CAS 
    PubMed 

    Google Scholar
     

  • Saez, A. M. et al. Rodent control to fight Lassa fever: Evaluation and lessons learned from a 4-year study in Upper Guinea. PLoS Negl. Trop. Dis. 12, e0006829 (2018).

    Article 

    Google Scholar
     

  • Ejembi, J. et al. Contact tracing in Lassa fever outbreak response, an effective strategy for control? Online J. Public Health Inf. 11, e378 (2019).


    Google Scholar
     

  • ECHO Flash List. https://erccportal.jrc.ec.europa.eu/ECHO-Flash/ECHO-Flash-List/yy/2018/mm/2.

  • Pigott, D. M. et al. Local, national, and regional viral haemorrhagic fever pandemic potential in Africa: a multistage analysis. Lancet 390, 2662–2672 (2017).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Kraemer, M. U. G. et al. Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus. Nature Microbiology https://doi.org/10.1038/s41564-019-0376-y (2019).

  • Elith, J. et al. Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29, 129–151 (2006).

    Article 

    Google Scholar
     

  • Dhingra, M. S. et al. Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation. eLife 5, e19571 (2016).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Model. 190, 231–259 (2006).

    Article 

    Google Scholar
     

  • Elith, J. et al. A statistical explanation of MaxEnt for ecologists. Divers. Distrib. 17, 43–57 (2011).

    Article 

    Google Scholar
     

  • Phillips, S. J. et al. Sample selection bias and presence-only distribution models: Implications for background and pseudo-absence data. Ecol. Appl. 19, 181–197 (2009).

    PubMed 
    Article 

    Google Scholar
     

  • Valavi, R., Elith, J., Lahoz‐Monfort, J. J. & Guillera‐Arroita, G. blockCV: An r package for generating spatially or environmentally separated folds for k-fold cross-validation of species distribution models. Methods Ecol. Evol. 10, 225–232 (2019).

    Article 

    Google Scholar
     

  • Suchard, M. A. et al. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol. 4, vey016 (2018).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Randin, C. F. et al. Are niche-based species distribution models transferable in space? J. Biogeogr. 33, 1689–1703 (2006).

    Article 

    Google Scholar
     

  • Lange, S. Bias correction of surface downwelling longwave and shortwave radiation for the EWEMBI dataset. Earth Syst. Dyn. 9, 627–645 (2018).

    ADS 
    Article 

    Google Scholar
     

  • Dunne, J. P. et al. GFDL’s ESM2 global coupled climate–carbon earth system models. Part I: physical formulation and baseline simulation characteristics. J. Clim. 25, 6646–6665 (2012).

    ADS 
    Article 

    Google Scholar
     

  • Jones, C. D. et al. The HadGEM2-ES implementation of CMIP5 centennial simulations. Geosci. Model Dev. 4, 543–570 (2011).

    ADS 
    Article 

    Google Scholar
     

  • Dufresne, J.-L. et al. Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5. Clim. Dyn. 40, 2123–2165 (2013).

    Article 

    Google Scholar
     

  • Watanabe, M. et al. Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Clim. 23, 6312–6335 (2010).

    ADS 
    Article 

    Google Scholar
     

  • Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteor. Soc. 93, 485–498 (2012).

    ADS 
    Article 

    Google Scholar
     

  • Hurtt, G. C. et al. Harmonization of global land-use change and management for the period 850-2100 (LUH2) for CMIP6. Geosci. Model Dev. 1–65 https://doi.org/10.5194/gmd-2019-360 (2020)

  • Jones, B. & O’Neill, B. C. Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways. Environ. Res. Lett. 11, 084003 (2016).

    ADS 
    Article 

    Google Scholar
     

  • Katoh, K. & Standley, D. M. MAFFT Multiple Sequence Alignment Software version 7: Improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Larsson, A. AliView: a fast and lightweight alignment viewer and editor for large datasets. Bioinformatics 30, 3276–3278 (2014).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Ayres, D. L. et al. BEAGLE 3: Improved performance, scaling, and usability for a high-performance computing library for statistical phylogenetics. Syst. Biol. https://doi.org/10.1093/sysbio/syz020 (2019).

  • Tavaré, S. Some probabilistic and statistical problems in the analysis of DNA sequences. Lect. Math. Life Sci. 17, 57–86 (1986).

    MathSciNet 
    MATH 

    Google Scholar
     

  • Rambaut, A., Drummond, A. J., Xie, D., Baele, G. & Suchard, M. A. Posterior summarization in Bayesian phylogenetics using Tracer 1.7. Syst. Biol. 67, 901–904 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Laenen, L. et al. Spatio-temporal analysis of Nova virus, a divergent hantavirus circulating in the European mole in Belgium. Mol. Ecol. 25, 5994–6008 (2016).

    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Dellicour, S. et al. Landscape genetic analyses of Cervus elaphus and Sus scrofa: comparative study and analytical developments. Heredity 123, 228–241 (2019).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Dellicour, S. et al. Phylodynamic assessment of intervention strategies for the West African Ebola virus outbreak. Nat. Commun. 9, 2222 (2018).

    ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Dellicour, S. et al. Phylogeographic and phylodynamic approaches to epidemiological hypothesis testing. bioRxiv https://doi.org/10.1101/788059 (2020).

  • Dellicour, S., Rose, R. & Pybus, O. G. Explaining the geographic spread of emerging epidemics: a framework for comparing viral phylogenies and environmental landscape data. BMC Bioinform 17, 1–12 (2016).

    Article 

    Google Scholar
     

  • McRae, B. H. Isolation by resistance. Evolution 60, 1551–1561 (2006).

    PubMed 
    Article 

    Google Scholar
     

  • Jacquot, M., Nomikou, K., Palmarini, M., Mertens, P. & Biek, R. Bluetongue virus spread in Europe is a consequence of climatic, landscape and vertebrate host factors as revealed by phylogeographic inference. Proc. R. Soc. Lond. B 284, 20170919 (2017).


    Google Scholar
     

  • Gill, M. S. et al. Improving Bayesian population dynamics inference: A coalescent-based model for multiple loci. Mol. Biol. Evol. 30, 713–724 (2013).

    CAS 
    PubMed 
    Article 

    Google Scholar
     

  • Karcher, M. D., Palacios, J. A., Bedford, T., Suchard, M. A. & Minin, V. N. Quantifying and mitigating the effect of preferential sampling on phylodynamic inference. PLoS Comput. Biol. 12, e1004789 (2016).

    ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar
     

  • Sources

    1/ https://Google.com/

    2/ https://www.nature.com/articles/s41467-022-33112-3

    The mention sources can contact us to remove/changing this article

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