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‘Global Origins and Dispersals’ addresses two key questions. First, how do epidemic diseases emerge and can their geographical origins be traced to any particular part of the world? Second, why do more infectious diseases appear to be emerging in recent decades and how far does this crudescence relate to the unprecedented changes in the global environment? The examination covers factors that, inter alia, have tended to increase the geographical scale of disease cycles, including the growth and relocation of the human population, globalization and the collapse of geographical space, and environmental changes associated with land use and climate change and variability. The origin and the spread of newly emerging infectious diseases are illustrated with reference to recent international epidemics of ‘bird flu’ associated with the avian influenza A (H5N1) virus, severe acute respiratory syndrome, and Ebola virus disease in West Africa (2013–16).

‘Epidemics in Small Communities’ develops an understanding of the ways in which an infection can achieve community circulation in small geographical areas. It begins by examining the local disease records of two doctors in general practice in the United Kingdom (William Pickles of Wensleydale and Edgar Hope-Simpson of Cirencester) to shed light on the processes whereby individual cases of diseases, such as measles and influenza, can develop into full-blown epidemics. The second half of the chapter focuses on Iceland as an island laboratory for the study of epidemic diffusion processes in the period 1902–1988. For this 87-year period, records of 131 discrete epidemic waves (with a recorded total of >0.5 million cases) of measles, influenza, and five other infectious diseases are examined in terms of wave spacing, wave velocity, and wave geography. These findings are related both to epidemiological theory and to aspects of the changing historical geography of the island.

A Geography of Infection explores the distinctive spatial patterns and processes by which infectious diseases spread from place to place and can grow from local and regional epidemics into global pandemics. The book focuses initially on the local scale of doctors’ practices and small islands where epidemic outbreaks are slight in the numbers infected and in geographical extent. Such local area studies raise two questions. First, how and where do epidemic diseases emerge and second, why do more diseases appear to be emerging now? To approach such questions implies a shift in spatial gear from painting epidemics with a fine-tipped local brush to an expanded palette on which doctors’ practices and small islands are replaced by regional and global populations. Simultaneously, time bands are extended backwards to the origins of civilization and forwards into the twenty-first century. It eventually leads to a consideration of global pandemics—both historical (e.g. plague, cholera, and influenza) and contemporary (HIV/AIDS and COVID-19)—and examines the ways the spread of infection can be prevented.

‘Epidemics as Diffusion Waves’ establishes the parameters of the book. It begins by defining the basic building blocks of the study: infection, contagion, and disease. Key epidemiological concepts and terms are introduced and defined, and classic compartmental (susceptible → infective → recovered; SIR) approaches to epidemic modelling are outlined. Epidemic waves in the time domain are examined in terms of their shape (logistic model, Kendall waves), as repetitive wave trains (Bartlett threshold model), and as branching networks (Reed–Frost model). The second half of the chapter examines epidemic waves in the space domain. The swash–backwash model of the single epidemic wave introduces the concept of the spatial basic reproduction number R0A, the geographical analogue of the basic reproduction number R 0. Spatial simulations of diffusion waves are explored through the work of Torsten Hägerstrand. The chapter concludes with a consideration of dyadic (lag correlation and spatial interaction) approaches to epidemic modelling.

‘Infectious Disease Control’ examines the historical development of approaches to the geographical control, elimination, and eradication of infectious diseases. It begins at a local spatial scale, seven centuries ago, among the plague-ridden lazarettos of Venice. It ends at the global scale with twenty-first-century developments in the Internet-based monitoring and surveillance of infectious diseases. Basic spatial strategies for the control of infectious diseases (defensive isolation and offensive containment) are outlined, their historical development and application in the form of such measures as cordons sanitaires, isolation, and quarantine are reviewed, and their present-day forms highlighted. Vaccines and vaccination are reviewed as a second approach to disease control, alongside initiatives for the global eradication of infectious diseases such as smallpox and poliomyelitis. Disease surveillance continues to form a cornerstone of spatially focused control activities and, so, the chapter ends with a review of the evolution of disease intelligence systems down the centuries.

‘Pandemics, II: COVID-19’ explores the spatial and temporal patterns of infection, illness, and death due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19). It covers the period from the putative beginning of the COVID-19 pandemic in late 2019 to the turn of 2021. Consecutive sections review the basic epidemiological properties of the virus and the disease, the pattern of global dispersal, and the resulting patterns of reported disease activity in the United Kingdom and the United States. The swash–backwash model is used to analyse the spatial spread of the first wave of COVID-19 in England and to estimate the spatial velocity of wave expansion and retreat, January–June 2020. Approaches to the short- and longer-term forecasting of COVID-19 are illustrated with reference to sample states of the United States.

This chapter suggests that scale obtrudes into geographical research in three main ways: in the problem of covering the earth’s surface; in the problem of linking results obtained at one scale to those obtained at another; and in standardizing information that is available only on a mixed series of scales. One of the characteristic features of geographical research is its concern with a particular scale of reality. The scale coverage problem is simple and immediate. There is an important difference between the attempts to use sampling to circumvent the scale problem, and the way in which sampling is being used in research. This essential difference is between purposive and probability sampling. Every change in scale will bring about the statement of a new problem, and there is no basis for assuming that associations existing at one scale will also exist at another’.

By the late 1960s powerful push and pull elements were forcing a small but increasing proportion of geographers to move their energies towards the forecasting arena. Within the spatial tradition, locational analysis was running into something of an impasse. Most of the classical forecasting studies fall within the first spatial case. Thus national forecasts of future population levels and future economic activity tend to be conducted in terms of past sets of values for the nation itself. Under the advocacy of Commoner, the Ehrlichs, Earth Days, Royal Commissions, and the like, geographers were being forced to put static ecological models forward in a market-place that clamoured for the dynamic; the emphasis was on using such models to predict likely directions and rates of environmental change. Over shorter forecast periods, geographers are being drawn into national, regional, and local projections as part of planning exercises.

It is now a half-century since the ‘new geography‘ summer schools for teachers were held at Madingley Hall near Cambridge. Here, this ‘experiment’ in school-university linkage is recalled by one of...

A maximization procedure for identifying significant links in a flow matrix is described and its use illustrated. The method appears to have advantages over primary-flow linkage methods and over methods based on flow-combination procedures.

Iceland's centuries-long history of epidemics with its unusually complete disease records has attracted study from several disciplines. But detailed spatial data of particular interest to historical geographers date only from 1895 and were consistently maintained for about a century thereafter. Within this period, this paper concentrates on morbidity records of reported cases of infectious diseases for an 87-year window which was open between 1902 and 1988. In this time slice, spatially detailed data for seven demographically important infectious diseases allow the geography of 131 discrete epidemic waves with a recorded total of 529,000 cases to be tracked. Changes in the behaviour of the seven diseases over the period are analyzed and related to both epidemiological theory and to the changing historical geography of the island. The paper complements earlier Icelandic work by the authors on the historical geography of single diseases (measles, influenza and poliomyelitis) by extending the range of diseases, and by considering their common spatial behaviour and their interrelationships.

The “quantitative revolution” in human geography which swept across so many universities in the 1950s and 1960s had its main diffusion centers in a few locations which were to have global significance. Two critical early centers were the University of Washington in the Pacific Northwest and Lund University in southern Sweden. But the experience of change was different in different locations as the general forces of perturbation sweeping around academia were translated into local eddies with local repercussions. Here, small and somewhat random quirks at the outset, led eventually to fundamental divergences between adoption and rejection. The theme is illustrated by reference to changes which occurred at Cambridge, one of England's two oldest universities, as seen from the perspective of someone who—as undergraduate, graduate student, and later, faculty member—was caught up in these changes and took some small part in propagating them. Special attention is given to the role of two environmental scientists, Vaughan Lewis and Richard Chorley, in introducing changes and the way in which later developments in human geography drew on preceding experiences in physical geography. The reasons behind the “Cambridge variant” and the questions of how intellectual DNA is passed across the generations are discussed.

Background Historical data are necessary to establish long-term trends in disease incidence but pose analytical problems since their accuracy and reliability may be poorly specified. Methods A robust measure of the spatial velocity, R 0A , of epidemic waves from space-time series is proposed using binary data. The method was applied to the historical records of influenza morbidity for the island of Iceland over a 61-year period of influenza seasons from 1915-16 to 1975-76. Results The onset of influenza waves tended to speed up over the period studied and the three pandemic waves associated with viral shifts in influenza A [Spanish influenza H 1 N 1 (1918-19), Asian influenza H 2 N 2 (1957-58) and Hong Kong influenza H 3 N 2 (1968-69)] spread more rapidly around the island and struck earlier in the influenza season than did inter-pandemic waves, even when the latter were equally intensive as measured by total number of cases and case incidence. Discussion The potential for using R 0A in a real-time context is explored using French influenza data. Conclusions The new measure of wave velocity appears to be applicable to those historical time series where breakdown into regional or local areas is available. The study is being extended to (i) other countries where similar influenza time series are available and (ii) to other diseases within Iceland.

The collapse of geographical space over the last 200 years has had profound effects on the circulation of human populations and on the transfer of infectious diseases. Three examples are used to illustrate the process: (a) the impact of the switch from sail to steamships in importing measles into Fiji over a 40-year period; (b) changes in measles epidemic behaviour in Iceland over a 150-year period; and (c) changes in the spread of cholera within the United States over a 35-year period. In each case, the link between time, travel and disease has been an intimate one.

This article examines temporal and spatial patterns in the relationship between provisional and amended reports for Hepatitis A and Hepatitis B received from each state by the Centers for Disease Control and Prevention through the U.S. National Notifiable Diseases Surveillance System from 1980 to 1992. It demonstrates that, as the 1980s unfolded, the preliminary disease reports became less representative markers of final disease counts. Practitioners at the state and community levels need to be aware of the temporal and spatial instabilities in such provisional data if they are used to provide early warning of contemporary health aberrations.

CLIFF A. D., HAGGETT P. and MARTIN R. L. (1997) Michael Chisholm: an appreciation, Reg. Studies 31, 205‐210. Over the past 40 years, Michael Chisholm has made flundamental contributions both to economic geography and to its applications in government. This paper reviews the major areas of his research (land rent and agricultural economics; development studies; regional growth studies; and the interface between geography and economics), and shows how he has applied the results to problems with which he has been involved in many years of government service. The paper is prefaced by a brief biographical note and it is completed with a section in which the authors try to identify the characteristics of his work that have given it its distinctive flavour. CLIFF A. D., HAGGETT P. et MARTIN R. L. (1997) Michael Chisholm en vedette, Reg. Studies 31, 205-210. Au cours des quarante dernieres annees, Michael Chisholm a contribue a tous les niveaux a Ia geographie economique et a sa raison d'etre sur le plan gouverne...

First published in 1967, this book explores the theme of geographical generalization, or model building. It is composed of five of the chapters from the original Models in Geography, published in 1967. The first chapter broadly outlines this theme and examines the nature and function of generalized statements, ranging from conceptual models to scale models, in a geographical context. The following chapters deal with mixed-system model building in geography, wherein data, techniques and concepts in both physical and human geography are integrated. The book contains chapters on organisms and ecosystems as geographical models as well as spatial patterns in human geography. This text represents a robustly anti-idiographic statement of modern work in one of the major branches of geography.

Islands have proved fruitful laboratories for biogeographical research from Darwin and Wallace onwards. We examine here the significance of Black's work (Journal of Theoretical Biology, 11, pp. 207–211 (1966)) on island epidemics. His original data on measles outbreaks on 19 islands over the 15 year period from 1949 to 1964 are reanalysed, and the confounding effects of island accessibility and population density upon estimates of the population threshold for measles endemicity are illustrated. Using later data, we extend Black's analysis into the post-1965 measles vaccination era both for the islands he studied and for 22 others, and then explore the potential of intra-island comparisons. Although Black confined himself to measles, this paper suggests that his ideas are extendable to a wide range of other infectious diseases. Island epidemiology has implications both for practical questions of disease control and for academic questions of the persistence and origin of diseases.

This paper illustrates the use of multidimensional scaling methods (MDS) to examine space-time patterns in epidemic data. The paper begins by outlining the principles of MDS. The model is then formally specified and illustrated by application to two data sets. The first is partly a tutorial example. It uses monthly reported measles morbidity data for the 31-year period from January 1960 to December 1990, collected for the 50 states of the USA, plus New York City and the District of Columbia. These data are used to explore the various ways in which MDS may be used to identify changing spatial patterns in geographically-coded data. In addition to their tutorial use, the data are also employed to search for any substantive changes in the geographical structure of measles epidemics in the USA that may have followed the introduction of mass vaccination in 1965. New England appears to have developed an epidemic profile distinct from the rest of the USA, and there is tentative evidence of an urban-rural split in epidemic characteristics. The second data set takes annual reported measles mortality data for New Zealand and the states of Australia from 1860 to 1949. MDS is used to show how the spatial relationships among these geographical units have changed over time in response to changes in the sizes of local susceptible populations.

The historical geography of infectious diseases of humans shows a constantly changing pattern. In the late 20th century that pattern is being affected by strong population growth in the host popula...

Changes in the spread of disease-causing viruses into Australia, New Zealand and the Southwest Pacific are examined. Particular reference is made to the impact of reduced travel times between those areas and both Western Europe and Southeast Asia on the transfer of infectious human diseases, notably smallpox, measles, influenza and rubella. The likely consequences of increasing population size and decreasing remoteness on the entry of other infectious diseases are noted.