The role of evolution in the emergence of infectious diseases
Identifieur interne : 000447 ( Pmc/Corpus ); précédent : 000446; suivant : 000448The role of evolution in the emergence of infectious diseases
Auteurs : Rustom Antia ; Roland R. Regoes ; Jacob C. Koella ; Carl T. BergstromSource :
- Nature [ 0028-0836 ] ; 2003.
Abstract
It is unclear when, where and how novel pathogens such as human immunodeficiency virus (HIV), monkeypox and severe acute respiratory syndrome (SARS) will cross the barriers that separate their natural reservoirs from human populations and ignite the epidemic spread of novel infectious diseases. New pathogens are believed to emerge from animal reservoirs when ecological changes increase the pathogen's opportunities to enter the human population
The online version of this article (doi:10.1038/nature02104) contains supplementary material, which is available to authorized users.
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DOI: 10.1038/nature02104
PubMed: 14668863
PubMed Central: 7095141
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">The role of evolution in the emergence of infectious diseases</title><author><name sortKey="Antia, Rustom" sort="Antia, Rustom" uniqKey="Antia R" first="Rustom" last="Antia">Rustom Antia</name><affiliation><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="GRID">grid.189967.8</institution-id><institution-id institution-id-type="ISNI">0000 0001 0941 6502</institution-id><institution>Department of Biology,</institution><institution>Emory University,</institution></institution-wrap>Georgia 30322 Atlanta, USA</nlm:aff></affiliation></author><author><name sortKey="Regoes, Roland R" sort="Regoes, Roland R" uniqKey="Regoes R" first="Roland R." last="Regoes">Roland R. Regoes</name><affiliation><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="GRID">grid.189967.8</institution-id><institution-id institution-id-type="ISNI">0000 0001 0941 6502</institution-id><institution>Department of Biology,</institution><institution>Emory University,</institution></institution-wrap>Georgia 30322 Atlanta, USA</nlm:aff></affiliation></author><author><name sortKey="Koella, Jacob C" sort="Koella, Jacob C" uniqKey="Koella J" first="Jacob C." last="Koella">Jacob C. Koella</name><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.462844.8</institution-id><institution-id institution-id-type="ISNI">0000 0001 2308 1657</institution-id><institution>Laboratoire de Parasitologie Evolutive,</institution><institution>Université Pierre et Marie Curie,</institution></institution-wrap>75252 Paris, France</nlm:aff></affiliation></author><author><name sortKey="Bergstrom, Carl T" sort="Bergstrom, Carl T" uniqKey="Bergstrom C" first="Carl T." last="Bergstrom">Carl T. Bergstrom</name><affiliation><nlm:aff id="Aff3"><institution-wrap><institution-id institution-id-type="GRID">grid.34477.33</institution-id><institution-id institution-id-type="ISNI">0000000122986657</institution-id><institution>Department of Biology,</institution><institution>University of Washington,</institution></institution-wrap>Washington 98195 Seattle, USA</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">14668863</idno><idno type="pmc">7095141</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7095141</idno><idno type="RBID">PMC:7095141</idno><idno type="doi">10.1038/nature02104</idno><date when="2003">2003</date><idno type="wicri:Area/Pmc/Corpus">000447</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000447</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">The role of evolution in the emergence of infectious diseases</title><author><name sortKey="Antia, Rustom" sort="Antia, Rustom" uniqKey="Antia R" first="Rustom" last="Antia">Rustom Antia</name><affiliation><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="GRID">grid.189967.8</institution-id><institution-id institution-id-type="ISNI">0000 0001 0941 6502</institution-id><institution>Department of Biology,</institution><institution>Emory University,</institution></institution-wrap>Georgia 30322 Atlanta, USA</nlm:aff></affiliation></author><author><name sortKey="Regoes, Roland R" sort="Regoes, Roland R" uniqKey="Regoes R" first="Roland R." last="Regoes">Roland R. Regoes</name><affiliation><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="GRID">grid.189967.8</institution-id><institution-id institution-id-type="ISNI">0000 0001 0941 6502</institution-id><institution>Department of Biology,</institution><institution>Emory University,</institution></institution-wrap>Georgia 30322 Atlanta, USA</nlm:aff></affiliation></author><author><name sortKey="Koella, Jacob C" sort="Koella, Jacob C" uniqKey="Koella J" first="Jacob C." last="Koella">Jacob C. Koella</name><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.462844.8</institution-id><institution-id institution-id-type="ISNI">0000 0001 2308 1657</institution-id><institution>Laboratoire de Parasitologie Evolutive,</institution><institution>Université Pierre et Marie Curie,</institution></institution-wrap>75252 Paris, France</nlm:aff></affiliation></author><author><name sortKey="Bergstrom, Carl T" sort="Bergstrom, Carl T" uniqKey="Bergstrom C" first="Carl T." last="Bergstrom">Carl T. Bergstrom</name><affiliation><nlm:aff id="Aff3"><institution-wrap><institution-id institution-id-type="GRID">grid.34477.33</institution-id><institution-id institution-id-type="ISNI">0000000122986657</institution-id><institution>Department of Biology,</institution><institution>University of Washington,</institution></institution-wrap>Washington 98195 Seattle, USA</nlm:aff></affiliation></author></analytic><series><title level="j">Nature</title><idno type="ISSN">0028-0836</idno><idno type="eISSN">1476-4687</idno><imprint><date when="2003">2003</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p id="Par1">It is unclear when, where and how novel pathogens such as human immunodeficiency virus (HIV), monkeypox and severe acute respiratory syndrome (SARS) will cross the barriers that separate their natural reservoirs from human populations and ignite the epidemic spread of novel infectious diseases. New pathogens are believed to emerge from animal reservoirs when ecological changes increase the pathogen's opportunities to enter the human population<sup><xref ref-type="bibr" rid="CR1">1</xref></sup> and to generate subsequent human-to-human transmission<sup><xref ref-type="bibr" rid="CR2">2</xref></sup>. Effective human-to-human transmission requires that the pathogen's basic reproductive number, <italic>R</italic><sub>0</sub>, should exceed one, where <italic>R</italic><sub>0</sub> is the average number of secondary infections arising from one infected individual in a completely susceptible population<sup><xref ref-type="bibr" rid="CR3">3</xref></sup>. However, an increase in <italic>R</italic><sub>0</sub>, even when insufficient to generate an epidemic, nonetheless increases the number of subsequently infected individuals. Here we show that, as a consequence of this, the probability of pathogen evolution to <italic>R</italic><sub>0</sub> > 1 and subsequent disease emergence can increase markedly.</p><sec><title>Supplementary information</title><p>The online version of this article (doi:10.1038/nature02104) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Hahn, Bh" uniqKey="Hahn B">BH Hahn</name></author><author><name sortKey="Shaw, Gm" uniqKey="Shaw G">GM Shaw</name></author><author><name sortKey="De Cock, Km" uniqKey="De Cock K">KM De Cock</name></author><author><name sortKey="Sharp, Pm" uniqKey="Sharp P">PM Sharp</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="May, Rm" uniqKey="May R">RM May</name></author><author><name sortKey="Gupta, S" uniqKey="Gupta S">S Gupta</name></author><author><name sortKey="Mclean, Ar" uniqKey="Mclean A">AR 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Nature</journal-id><journal-id journal-id-type="iso-abbrev">Nature</journal-id><journal-title-group><journal-title>Nature</journal-title></journal-title-group><issn pub-type="ppub">0028-0836</issn><issn pub-type="epub">1476-4687</issn><publisher><publisher-name>Nature Publishing Group UK</publisher-name><publisher-loc>London</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">14668863</article-id><article-id pub-id-type="pmc">7095141</article-id><article-id pub-id-type="publisher-id">BFnature02104</article-id><article-id pub-id-type="doi">10.1038/nature02104</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>The role of evolution in the emergence of infectious diseases</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name><surname>Antia</surname><given-names>Rustom</given-names></name><address><email>rantia@emory.edu</email></address><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Regoes</surname><given-names>Roland R.</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Koella</surname><given-names>Jacob C.</given-names></name><xref ref-type="aff" rid="Aff2">2</xref></contrib><contrib contrib-type="author"><name><surname>Bergstrom</surname><given-names>Carl T.</given-names></name><xref ref-type="aff" rid="Aff3">3</xref></contrib><aff id="Aff1"><label>1</label><institution-wrap><institution-id institution-id-type="GRID">grid.189967.8</institution-id><institution-id institution-id-type="ISNI">0000 0001 0941 6502</institution-id><institution>Department of Biology,</institution><institution>Emory University,</institution></institution-wrap>Georgia 30322 Atlanta, USA</aff><aff id="Aff2"><label>2</label><institution-wrap><institution-id institution-id-type="GRID">grid.462844.8</institution-id><institution-id institution-id-type="ISNI">0000 0001 2308 1657</institution-id><institution>Laboratoire de Parasitologie Evolutive,</institution><institution>Université Pierre et Marie Curie,</institution></institution-wrap>75252 Paris, France</aff><aff id="Aff3"><label>3</label><institution-wrap><institution-id institution-id-type="GRID">grid.34477.33</institution-id><institution-id institution-id-type="ISNI">0000000122986657</institution-id><institution>Department of Biology,</institution><institution>University of Washington,</institution></institution-wrap>Washington 98195 Seattle, USA</aff></contrib-group><pub-date pub-type="ppub"><year>2003</year></pub-date><volume>426</volume><issue>6967</issue><fpage>658</fpage><lpage>661</lpage><history><date date-type="received"><day>6</day><month>7</month><year>2003</year></date><date date-type="accepted"><day>25</day><month>9</month><year>2003</year></date></history><permissions><copyright-statement>© Macmillan Magazines Ltd. 2003</copyright-statement><license><license-p>This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.</license-p></license></permissions><abstract id="Abs1"><p id="Par1">It is unclear when, where and how novel pathogens such as human immunodeficiency virus (HIV), monkeypox and severe acute respiratory syndrome (SARS) will cross the barriers that separate their natural reservoirs from human populations and ignite the epidemic spread of novel infectious diseases. New pathogens are believed to emerge from animal reservoirs when ecological changes increase the pathogen's opportunities to enter the human population<sup><xref ref-type="bibr" rid="CR1">1</xref></sup> and to generate subsequent human-to-human transmission<sup><xref ref-type="bibr" rid="CR2">2</xref></sup>. Effective human-to-human transmission requires that the pathogen's basic reproductive number, <italic>R</italic><sub>0</sub>, should exceed one, where <italic>R</italic><sub>0</sub> is the average number of secondary infections arising from one infected individual in a completely susceptible population<sup><xref ref-type="bibr" rid="CR3">3</xref></sup>. However, an increase in <italic>R</italic><sub>0</sub>, even when insufficient to generate an epidemic, nonetheless increases the number of subsequently infected individuals. Here we show that, as a consequence of this, the probability of pathogen evolution to <italic>R</italic><sub>0</sub> > 1 and subsequent disease emergence can increase markedly.</p><sec><title>Supplementary information</title><p>The online version of this article (doi:10.1038/nature02104) contains supplementary material, which is available to authorized users.</p></sec></abstract><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© Springer Nature Limited 2003</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="Sec1"><title>Main</title><p id="Par2">The emergence of a disease combines two elements: the introduction of the pathogen into the human population and its subsequent spread and maintenance within the population. Ecological factors such as human behaviour can influence both of these elements, and consequently ecology has been recognized to have an important role in the emergence of disease<sup><xref ref-type="bibr" rid="CR1">1</xref>,<xref ref-type="bibr" rid="CR2">2</xref>,<xref ref-type="bibr" rid="CR4">4</xref></sup>. In contrast, evolutionary factors including the adaptation of the pathogen to growth within humans and the subsequent transmission of the pathogen between humans are mostly considered in terms of changes in the virulence of the pathogen, and are often thought to have a lesser role in the initial emergence of pathogens<sup><xref ref-type="bibr" rid="CR4">4</xref></sup>. One exception<sup><xref ref-type="bibr" rid="CR5">5</xref></sup> suggests that immunocompromised individuals might provide “stepping stones” for the evolution of pathogens.</p><p id="Par3">The successful emergence of a pathogen requires <italic>R</italic><sub>0</sub> to exceed one in the new host. Only then can an introduction trigger emergence<sup><xref ref-type="bibr" rid="CR2">2</xref></sup>. (Here we use <italic>R</italic><sub>0</sub> to refer to spread in human populations, not in the natural reservoir.) If <italic>R</italic><sub>0</sub> for a potential pathogen exceeds one, this scenario represents an epidemic waiting to happen. By contrast, when <italic>R</italic><sub>0</sub> is initially less than one, infections will inevitably die out and there will be no epidemic unless genetic or ecological changes drive <italic>R</italic><sub>0</sub> above one.</p><p id="Par4">There are a number of ways in which <italic>R</italic><sub>0</sub> can increase. Ecological changes such as changes in host density or behaviour can increase <italic>R</italic><sub>0</sub>, as can genetic changes in the pathogen population or in the population of its new host. Genetic changes in the pathogen can arise either through ‘coincidental’ processes such as neutral drift or coevolution of the pathogen and its reservoir host, or through adaptive evolution of the pathogen during chains of transmission in humans. Genetic changes of the new host might be more likely for domesticated or endangered species than for humans.</p><p id="Par5">Here we show that factors, such as ecological changes, that increase the <italic>R</italic><sub>0</sub> value of the potential pathogen to a level not sufficient to cause an epidemic (that is, <italic>R</italic><sub>0</sub> remains less than one) can greatly increase the length of the stochastic chains of disease transmission. These long transmission chains provide an opportunity for the pathogen to adapt to human hosts, and thus for the disease to emerge.</p><p id="Par6">Our model is illustrated in <xref rid="Fig1" ref-type="fig">Fig. 1</xref>. Introductions occur stochastically from the natural reservoir of the pathogen, and each primary case is followed by stochastic transmission that generates a variable number of subsequent infections in the human population. We assume that the number of secondary cases follows a Poisson distribution with a mean equal to <italic>R</italic><sub>0</sub>. Each introduction thus forms branched chains of transmission, which stutter to extinction if <italic>R</italic><sub>0</sub> < 1, and the pathogen cannot evolve (<italic>µ</italic> = 0). The probability that the pathogen evolves and a secondary infection is caused by the mutant is equal to <italic>µ</italic> for each of the secondary infections (we note that <italic>µ</italic> incorporates not only the pathogen's mutation rate, but also its dynamics within the host and its transmissibility). We use multi-type branching processes<sup><xref ref-type="bibr" rid="CR6">6</xref>,<xref ref-type="bibr" rid="CR7">7</xref>,<xref ref-type="bibr" rid="CR8">8</xref>,<xref ref-type="bibr" rid="CR9">9</xref></sup> to describe the initial spread of the infection, incorporating the evolution of the pathogen.<fig id="Fig1"><label>Figure 1</label><caption><title>Schematic for the emergence of an infectious disease.</title><p>Introductions from the reservoir are followed by chains of transmission in the human population. Infections with the introduced strain (open circles) have a basic reproductive number <italic>R</italic><sub>0</sub> < 1. Pathogen evolution generates an evolved strain (filled circles) with <italic>R</italic><sub>0</sub> > 1. The infections caused by the evolved strain can go on to cause an epidemic. Daggers indicate no further transmission.</p></caption><graphic xlink:href="41586_2003_Article_BFnature02104_Fig1_HTML" id="d29e408"></graphic></fig></p><p id="Par7">In the simplest case (see <xref rid="Fig2" ref-type="fig">Fig. 2a</xref>) only one mutation is required for the <italic>R</italic><sub>0</sub> of the evolved pathogen to exceed one. The probability that a single introduction evolves, causing one (or more) infections with the evolved pathogen (a filled circle in <xref rid="Fig1" ref-type="fig">Fig. 1</xref>) before it goes extinct, depends very strongly on the <italic>R</italic><sub>0</sub> of the introduced pathogen, particularly for low <italic>µ</italic> values as <italic>R</italic><sub>0</sub> approaches 1. This probability is approximately linearly dependent on the rate of evolution <italic>µ</italic>.<fig id="Fig2"><label>Figure 2</label><caption><title>One-step evolution. A single change is required for the pathogen to evolve to <italic>R</italic><sub>0</sub> > 1.</title><p><bold>a</bold>, The probability that an introduction leads to an infection with an evolved strain of the pathogen (filled circle in Fig. 1) is highly sensitive to <italic>R</italic><sub>0</sub>, and is approximately linearly dependent on the mutation rate <italic>µ</italic>. Lines correspond to numerical solutions to the branching process model (see Supplementary Information) and symbols correspond to Monte-Carlo simulations following 10<sup>5</sup> introductions. <bold>b</bold>, The probability of emergence per introduction depends on the <italic>R</italic><sub>0</sub> value of the introduced pathogen and of the evolved pathogen. The solid, dashed and dotted lines correspond to the evolved pathogen having an <italic>R</italic><sub>0</sub> of 1,000, 1.5 and 1.2 respectively.</p></caption><graphic xlink:href="41586_2003_Article_BFnature02104_Fig2_HTML" id="d29e481"></graphic></fig></p><p id="Par8">The probability that the introduction leads to an epidemic (the ‘probability of emergence’) depends on the probability of evolution and the probability that the evolved infections do not go extinct due to stochastic effects. In <xref rid="Fig2" ref-type="fig">Fig. 2b</xref> we plot the probability of emergence for three different <italic>R</italic><sub>0</sub> values of the evolved strain. The probability of emergence approaches the probability of evolution when <italic>R</italic><sub>0</sub> of the evolved strain is large, and is lower when the <italic>R</italic><sub>0</sub> of the evolved strain is close to 1. We find that the probability of emergence depends most strongly on the <italic>R</italic><sub>0</sub> of the introduced pathogen, increases approximately linearly with the mutation rate <italic>µ</italic>, and depends only modestly on the <italic>R</italic><sub>0</sub> of the evolved pathogen.</p><p id="Par9">We extend the simple one-step mutation model to consider the situation in which multiple evolutionary changes are required for the pathogen to attain <italic>R</italic><sub>0</sub> > 1 in the human population. We begin with a simple scenario, which we call the jackpot model, where the <italic>R</italic><sub>0</sub> of the pathogen with the intermediate mutations is the same as that of the introduced pathogen, and where only the addition of the final mutation results in an increase in <italic>R</italic><sub>0</sub> to greater than one. As seen in <xref rid="Fig3" ref-type="fig">Fig. 3</xref>, increasing the number of required evolutionary steps greatly reduces the probability of emergence and increases its sensitivity to changes in <italic>R</italic><sub>0</sub>. The probability of emergence is approximately proportional to the mutation rate to the power of the number of evolutionary steps required (see <xref rid="MOESM1" ref-type="media">Supplementary Information</xref>).<fig id="Fig3"><label>Figure 3</label><caption><title>Multiple-step evolution.</title><p>Here multiple evolutionary changes are required for evolution of the pathogen to have an <italic>R</italic><sub>0</sub> > 1. <bold>a</bold>, Jackpot model with <italic>µ</italic> = 0.1 and <italic>n</italic> intermediate changes each with <italic>R</italic><sub>0</sub> equal to that of the introduced pathogen: increasing the number of steps (<italic>n</italic>) greatly decreases the probability of evolution, and makes it more sensitive to the <italic>R</italic><sub>0</sub> of the introduced pathogen. <bold>b</bold>, Alternative multi-step models for the one-intermediate (<italic>n</italic> = 1) case. The jackpot model (solid line), additive model (dashed line) and fitness valley model (dotted line) are shown (see text for details).</p></caption><graphic xlink:href="41586_2003_Article_BFnature02104_Fig3_HTML" id="d29e589"></graphic></fig></p><p id="Par10">The fitness landscape on which evolution occurs is important in determining the outcome<sup><xref ref-type="bibr" rid="CR10">10</xref></sup>. <xref rid="Fig3" ref-type="fig">Figure 3b</xref> illustrates this for the case of a single intermediate type. As should be expected, changing the jackpot model to an additive model, where the fitness of the intermediate is the average of the fitness of the introduced strain and fully evolved strain, increases the probability that the pathogen evolves to <italic>R</italic><sub>0</sub> > 1, whereas changing it to a fitness valley model, where the fitness of the intermediate is lower than the fitness of the introduced strain, decreases the probability of emergence.</p><p id="Par11">The key characteristic distinguishing our model from the conventional view is the <italic>R</italic><sub>0</sub> of the introduced pathogen. In the conventional view the <italic>R</italic><sub>0</sub> of these infections must be greater than one, whereas in the mechanism described here it is less than one, and evolution during the stochastic chains of transmission allows <italic>R</italic><sub>0</sub> to increase above one. In the case of human infections such as HIV<sup><xref ref-type="bibr" rid="CR1">1</xref>,<xref ref-type="bibr" rid="CR11">11</xref>,<xref ref-type="bibr" rid="CR12">12</xref></sup>, SARS<sup><xref ref-type="bibr" rid="CR13">13</xref>,<xref ref-type="bibr" rid="CR14">14</xref>,<xref ref-type="bibr" rid="CR15">15</xref>,<xref ref-type="bibr" rid="CR16">16</xref>,<xref ref-type="bibr" rid="CR17">17</xref></sup> and (potentially) monkeypox<sup><xref ref-type="bibr" rid="CR18">18</xref>,<xref ref-type="bibr" rid="CR19">19</xref>,<xref ref-type="bibr" rid="CR20">20</xref>,<xref ref-type="bibr" rid="CR21">21</xref></sup>, seroprevalence studies among groups at high risk of infection from the reservoir would allow evaluation of whether crossover events are usually dead ends, as we expect in our model, or whether they are associated with a large number of secondary cases. In the case of diseases emerging into non-human populations, such as the Nipah virus, which moved from bats to pigs<sup><xref ref-type="bibr" rid="CR22">22</xref>,<xref ref-type="bibr" rid="CR23">23</xref>,<xref ref-type="bibr" rid="CR24">24</xref></sup>, it may be possible to conduct additional tests involving controlled experimental infections to estimate the <italic>R</italic><sub>0</sub> (in this case of the bat Nipah virus in pigs) and to determine whether it evolves during the course of chains of transmission. Such studies may additionally help to identify pathogens that have an ability to evolve rapidly and thus have a high potential for emergence.</p><p id="Par12">The framework presented here has special relevance for pathogens that have been driven to extinction by vaccination. In the case of smallpox there are probably reservoirs of related zoonoses (such as, but not restricted to, monkeypox) from which smallpox may have originated. Although the <italic>R</italic><sub>0</sub> of monkeypox in the human population is clearly less than one, there are occasional chains of transmission in the human population<sup><xref ref-type="bibr" rid="CR18">18</xref>,<xref ref-type="bibr" rid="CR19">19</xref>,<xref ref-type="bibr" rid="CR20">20</xref>,<xref ref-type="bibr" rid="CR21">21</xref></sup>. As the level of herd immunity to smallpox wanes in the absence of continued vaccination, we expect an increase in <italic>R</italic><sub>0</sub> of infections with monkeypox albeit to a level still less than one (the smallpox vaccine provides about 85% cross immunity against monkeypox). Our results suggest that this increase in the effective <italic>R</italic><sub>0</sub> of monkeypox in the human population could markedly increase the probability of evolution of monkeypox, allowing it to emerge into a successful human pathogen (which, depending on the evolutionary trajectory followed, may be similar to or differ from smallpox).</p><p id="Par13">The present study could be extended in a number of directions. These include explicitly incorporating the details of ecological interactions such as heterogeneity in the transmission in different areas and subpopulations<sup><xref ref-type="bibr" rid="CR2">2</xref>,<xref ref-type="bibr" rid="CR25">25</xref>,<xref ref-type="bibr" rid="CR26">26</xref>,<xref ref-type="bibr" rid="CR27">27</xref></sup> and incorporating genetic diversity of the pathogen in its reservoir. Finally, we note that this framework can be applied to the more general problem of biological invasions<sup><xref ref-type="bibr" rid="CR28">28</xref>,<xref ref-type="bibr" rid="CR29">29</xref></sup>.</p></sec><sec id="Sec2"><title>Methods</title><p id="Par14">We describe the dynamics and evolution of emerging diseases as a multi-type branching process with the following probability-generating functions<sup><xref ref-type="bibr" rid="CR6">6</xref>,<xref ref-type="bibr" rid="CR7">7</xref>,<xref ref-type="bibr" rid="CR8">8</xref>,<xref ref-type="bibr" rid="CR9">9</xref></sup>:<disp-formula id="Equa"><graphic xlink:href="41586_2003_Article_BFnature02104_Equa_HTML.gif" position="anchor"></graphic></disp-formula></p><p id="Par15">We calculated the extinction probabilities of the above process numerically. For details and definitions see <xref rid="MOESM1" ref-type="media">Supplementary Information</xref>.</p></sec><sec sec-type="supplementary-material"><title>Supplementary information</title><sec id="Sec3"><p><supplementary-material content-type="local-data" id="MOESM1"><media xlink:href="41586_2003_BFnature02104_MOESM1_ESM.pdf"><caption><p>Supplementary Information (PDF 77 kb)</p></caption></media></supplementary-material></p></sec></sec></body><back><ack><title>Acknowledgements</title><p>We thank S. Nichol, I. Longini and D. Krakauer for discussions and comments. 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