Thus, within the mammal-associated lineage, the viruses of Southeast Asia (KFD and LGT) are the ancestors of the viruses of the northern forests of central Russia, Far East and Siberia (OHF, FETBE and STBE), which in turn are the ancestors of the viruses of eastern and central Europe (WTBE, TSE, GGE), culminating in a virus found only in northern Spain (SSE) and the most westerly virus (LI) found in the British Isles. It is only these last four viruses that are transmitted via sheep, and LI is evidently also transmissible via red Figure 1 Phylogenetic tree of the tick-borne clade of flaviviruses: con- sensus tree based on the 1st and 2nd codon positions for 41 E genes and the NS5 gene sequence, taken from Gould et al. (2001) and Gaunt et al. (2001). The source of the gene sequences used to construct this tree is given in the original publications. The genus Flavivirus contains about 70 distinct an- tigenically related flaviviruses. These are pos itive-stranded RNA viruses that consist of three structural proteins (C capsid, M membrane and E envelope) and seven non-structural (NS) proteins. TYU, Tyuleniy; SRE, Saumarez Reef; MEA, Meaban; KAD, Kadam; POW, Powassan; KSI, Karshi; RF, Royal Farm; GGY, Gadget’s Gully; KFD, Kyasanur Forest disease; LGT, Langat; OHF, Omsk haemorrhagic fever; FETBE, Far Eastern tick-borne encephalitis; STBE, Siberian tick-borne encephalitis; WTBE, Western tick-borne encephalitis; TSE, Turkish sheep encephalitis; GGE, Greek goat encephalitis; SSE, Spanish sheep encephalitis; LI, Louping ill. Principal vertebrate host types and the geographical distribution are shown. TICK-BORNE DISEASE SYSTEMS 271 Plate 8.3 (A) The distribution of geo-referenced sites of known presence of TBE complex flaviviruses used in this analysis. In addition to those shown associated with the phylogenetic matrix (circles), see 1–3 sites for each of TSE (brown triangle) in Turkey, GGE (orange triangles) in Greece and Bulgaria, Karshi (mauve triangles) in Uzbekistan and Langat (red triangles) in SE Asia. For sources, see text. (B) The distribution of six tick-borne flaviviruses predicted in a single exercise of discriminant analysis, based on satellite- derived climatic variables. Each virus is represented by a colour that matches those in Figure 3A: LI, green; SSE, turquoise; WTBE, red; all Russian TBE, blue; OHF, yellow; KFD, black Plate 8.3 (continued) Plate 8.4 Each virus of the tick-borne encephalitis complex occupies a distinct ‘eco-climatic’ space, illustrated here in bi-variate space defined by two of the most significant climatic variables that predict the distribution of each virus. NDVI (nor- malized difference vegetation index) is an indirect measure of moisture conditions. m, vector/host ratio a, biting rate µ, vector mortality rate T, extrinsic incubation period m a T µ temperature temperature temperature temperature ?? ? + - + +?- Plate 10.1 Likely effects of increasing temperature on the variables and param- eters of the R 0 equation. The net effect is indicated by the positive or negative symbol within each panel. Notice that a positive effect here might decrease transmission (e.g. the effect on m) or increase it (e.g. the effect on a). Global Transport Networks and Infectious Disease Spread A.J. Tatem 1 , D.J. Rogers 1 and S.I. Hay 1,2 1 TALA Research Group, Tinbergen Building, Depar tment of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK 2 Malaria Public Health & Epidemiology Group, Centre for Geographic Medicine, KEMRI, PO Box 43640, 00100 Nairobi GPO, Kenya Abstract 294 1. Introduction . . 294 2. Global Transport Networks and Pandemics . . 295 2.1. Plague . . 295 2.2. Cholera . 297 2.3. Influenza. 298 2.4. HIV/AIDS 300 2.5. Severe Acute Respiratory Syndrome . . . 301 2.6. Bioterrorism 302 2.7. Predicting, Modelling and Controlling Future Pandem ics. . 304 3. Global Transport Networks and Disease Vector Invasions. . . . 306 3.1. Aedes aegypti 306 3.2. Anopheles gambiae 307 3.3. Aedes japonicus 307 3.4. Aedes albopictus 308 3.5. Predicting Future Disease Vector Invasions 308 4. Global Transport Networks and Vector-Borne Diseases 319 4.1. Yellow Fever 319 4.2. Dengue . 322 4.3. West Nile Virus . . 322 4.4. Malaria. . 323 4.5. Predicting Future Vector-Borne Disease Movement. 326 5. Conclusions . . 332 Acknowledgements . . . 332 References . . 333 ADVANCES IN PARASITOLOGY VOL 62 ISSN: 0065-308X $35.00 DOI: 10.1016/S0065-308X(05)62009-X Copyright r 2006 Elsevier Ltd. All rights of reproduction in any form reserved Figure 1 The Old World distribution of Ae. albopictus (dark grey); countries reporting established breeding pop- ulations of Ae. albopictus in the last 30 years (middle grey); countries reporting Ae. albopictus interception at ports (light grey). Data sources: Center for International Earth Science Information Network (CIESIN) (http://www.ciesin.org/docs/ 001-613/map15.gif), supplemented with information from literature sources (Gratz, 2004; Gubler, 2003; Lounibos, 2002; Medlock et al., 2005; Moore, 1999; Moore and Mitchell, 1997). GLOBAL TRANSPORT NETWORKS 309 Figure 2 Counties of the United States of America reporting the presence of Ae. albopictus in 2000. (Adapted from US Centers for Disease Control and Prevention (CDC); URL: http://www.cdc.gov/ncidod/dvbid/arbor/albopic_97_sm.htm.) A.J. TATEM ET AL.310 . black Plate 8. 3 (continued) Plate 8. 4 Each virus of the tick-borne encephalitis complex occupies a distinct ‘eco-climatic’ space, illustrated here in bi-variate space defined by two of the most significant. which in turn are the ancestors of the viruses of eastern and central Europe (WTBE, TSE, GGE), culminating in a virus found only in northern Spain (SSE) and the most westerly virus (LI) found in. period m a T µ temperature temperature temperature temperature ?? ? + - + + ?- Plate 10.1 Likely effects of increasing temperature on the variables and param- eters of the R 0 equation. The net effect is indicated by the positive or negative symbol within each