Abstract

SARAH E. RANDOLPH*Department of Zoology, University of Oxford, Oxford, UKAs biologists, and specifically parasitologists, we arefortunate to live in an age of complementarity,collaboration and integration alongside competition.No longer do biologists stand at either end of thecontinuum of analytical scales, from the molecular tothe ecological, glowering at each other and arguingfor the relative merits of one over the other, as wascommon for many decades after the dawn ofmolecular biology (Judson, 1996). Our lucky stu-dents haveinherited a discipline in which the tools ofmolecular analysis are regularly used to answerquestions on complex organisational and globalspatial scales, taking this significant advance forgranted without knowing anything different. At thesametime,newanalyticaltoolsdevelopedprincipallyby ecologists are available to help reconstruct andexplain the evolutionary information carried bygenetic data.Such exercises havean extraurgencywhen appliedto parasites (which I use here to include pathogens)whose distributions have obvious public healthimplications. However sophisticated any novel con-trol device may be, deciding where it should bedeployed with maximum efficacy and efficiencydepends on knowing the parasites’ distributions andprevalence levels (i.e. the relative need for interven-tion) and the relative fragility of their transmissionsystems (i.e. the likely ease of control). Not only dothese two indicators for effective intervention rarelycoincide, theyarealso not static. Asthe papers inthisspecial issue make clear, we humans are commonlythe architects, as well as the victims, of dynamicchanges in parasite distributions. All the morereason for parasitologists to develop improvedtools to monitor, describe, explain, predict andtherebycontroltheever-changingthreatofinfectiousdiseases.We start with one of the modern drivers ofepidemiology, the aeroplane as a principal meansof parasite movement, allowing more or less instan-taneous dispersal over vast distances (Tatem et al.2012). Given the speed and distance of suchtransport, it is essential that new epidemiologicalphenomena are monitored and co-ordinated in realtime, no matter how remote the events, for whichmodernelectroniccommunicationtoolsareideal,butonly if the emergent signals are subject to carefulquality control and interpretation (Chunara et al.2012; Madder et al. ). Notwithstanding ever-improving and increasingly ubiquitous electronicwizardry, its presence depends on human presence,which is not the case for all pathogens that have thepotential to become zoonotic, or even eventuallyhuman-transmitted, if the distributions of wildlifeand humans change and start to intersect.Where should we look to be on guard againstemergent diseases? Over the past two decades,predictive risk mapping has emerged as a powerfultool, empowered by the parallel growth of infor-mation on the environment available at appropriatespatial and temporal scales from satellite imagery.The primary aim may be simply to provide blue-prints to help direct surveillance and control pro-grammes, but the best analyses can yield theadditional bonus of a deeper understanding of whyorganisms are found where they are. This can bededuced from identifying the precise predictors ofeach distribution, and relating them to the under-lying biology of transmission. It is easy to producedescriptive maps using off-the-shelf software, butvery much more demanding to handle spatially-explicit data appropriately to achieve accurate andmeaningful predictive maps, filling in the gaps inour knowledge. Spatial auto-correlations and cross-correlations may be exploited to improve thesepredictions using kriging techniques derived fromthe discipline of mining research, although suchapproaches are not designed to identify biologicallyimportant driving variables (Rogers and Sedda,2012). Interestingly, Rogers and Sedda emphasizethat, in contrast to other statistical methods (Rogers,2006), the techniques of kriging and co-kriging,although increasingly widely used by biologists,cannot in fact throw lighton the biological processes,i.e. the why and whence of species distributions, butonly on the where, which is, after all, the principalinterest of mineral exploration and exploitation.Nevertheless, geo-statisticaltechniques can be devel-oped within a Bayesian framework to allow us to

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.