Tracking Epidemics

Author(s):  
Matthew Smallman-Raynor ◽  
Andrew Cliff

In studies of past, present, and likely future disease distributions, the ‘added value’ provided by the geographer lies in three main areas: detecting spatial concentrations of disease; isolating the processes (environmental, social, demographic, and pathogenic) which cause these disease hotspots; and in enhancing our understanding of the space–time dynamics of disease spread. This is as true of war-related epidemics as of any others. Within geography, there is a long-standing tradition of mapping disease. In this early history, the incidence maps of yellow fever produced in 1798 are often given pride of place (Robinson, 1982). These were, however, pre-dated by maps of topics as diverse as hospital capacities and the distribution of dressing-stations on a battlefield, through to maps of pestilential swamps and other hostile medical environments. But, so far as most epidemiological reports were concerned, such maps were usually incidental. The breakthrough in disease mapping occurred in the middle of the nineteenth century with the cholera map produced by Dr John Snow to accompany the second edition of his prize-winning essay On the Mode of Communication of Cholera (1855a). What set Snow’s work apart was not the cartography (dot maps, which were a well-established cartographic device, to show the geographical distribution of individual cholera deaths), but his inductive reasoning from the map. By showing what he termed the ‘topography of the outbreak’, Snow was able to draw inferences about the central source of infection. The use of mapping as an important device for suggesting hypotheses of medical interest may be traced through to the present day. For war and disease, the classic example is the Seuchen Atlas. This atlas of epidemic disease (Zeiss, 1942–5; Anderson, 1947) was conceived by the German army as an adjunct to war, enhancing its ability to mount military campaigns. The atlas was produced as separate sheets over the years 1942–5. Its distribution was confined to military institutes and to those German university institutes involved in training medical students. The scope of the atlas was not global but confined largely to those areas where the Army High Command expected to be fighting.

2020 ◽  
Vol 7 (7) ◽  
pp. 200780 ◽  
Author(s):  
Marian-Gabriel Hâncean ◽  
Matjaž Perc ◽  
Jürgen Lerner

We describe the early spread of the novel coronavirus (COVID-19) and the first human-to-human transmission networks, in Romania. We profiled the first 147 cases referring to sex, age, place of residence, probable country of infection, return day to Romania, COVID-19 confirmation date and the probable modes of COVID-19 transmissions. Also, we analysed human-to-human transmission networks and explored their structural features and time dynamics. In Romania, local cycles of transmission were preceded by imported cases, predominantly from Italy. We observed an average of 4.8 days (s.d. = 4.0) between the arrival to a Romanian county and COVID-19 confirmation. Furthermore, among the first 147 COVID-19 patients, 88 were imported cases (64 carriers from Italy), 54 were domestic cases, while for five cases the source of infection was unknown. The early human-to-human transmission networks illustrated a limited geographical dispersion, the presence of super-spreaders and the risk of COVID-19 nosocomial infections. COVID-19 occurred in Romania through case importation from Italy. The largest share of the Romanian diaspora is concentrated especially in the northern parts of Italy, heavily affected by COVID-19. Human mobility (including migration) accounts for the COVID-19 transmission and it should be given consideration while tailoring prevention measures.


Author(s):  
Charles F. Dillon ◽  
Michael B. Dillon

Airborne disease transmission is central to many scientific disciplines including agriculture, veterinary biosafety, medicine, and public health. Legal and regulatory standards are in place to prevent agricultural, nosocomial, and community airborne disease transmission. However, the overall importance of the airborne pathway is underappreciated, e.g.,, US National Library of Medicine’s Medical Subjects Headings (MESH) thesaurus lacks an airborne disease transmission indexing term. This has practical consequences as airborne precautions to control epidemic disease spread may not be taken when airborne transmission is important, but unrecognized. Publishing clearer practical methodological guidelines for surveillance studies and disease outbreak evaluations could help address this situation. To inform future work, this paper highlights selected, well-established airborne transmission events - largely cases replicated in multiple, independently conducted scientific studies. Methodologies include field experiments, modeling, epidemiology studies, disease outbreak investigations and mitigation studies. Collectively, this literature demonstrates that airborne viruses, bacteria, and fungal pathogens have the capability to cause disease in plants, animals, and humans over multiple distances – from near range (< 5 m) to continental (> 500 km) in scale. The plausibility and implications of undetected airborne disease transmission are discussed, including the notable underreporting of disease burden for several airborne transmitted diseases.


2019 ◽  
Author(s):  
Paul Birrell ◽  
Xu-Sheng Zhang ◽  
Alice Corbella ◽  
Edwin van Leeuwen ◽  
Nikolaos Panagiotopoulos ◽  
...  

Abstract Background: Since the 2009 A/H1N1 pandemic, the UK has a suite of real-time statistical models utilising enhanced pandemic surveillance data to nowcast and forecast a future pandemic. Their ability to track seasonal influenza and predict heightened winter healthcare burden in the light of high activity in Australia in 2017 was untested. Methods: Four transmission models were used in forecasting the 2017/2018 seasonal influenza epidemic in England: a stratified primary care model using daily, region-specific, counts and virological swab positivity of influenza-like illness consultations in general practice (GP); a strain-specific (SS) model using weekly, national GP ILI and virological data; an intensive care model (ICU) using reports of ICU influenza admissions; a synthesis model that included all data sources. For the first 12 weeks of 2018, each model was applied to the latest data to provide estimates of epidemic parameters and short-term influenza forecasts. The added value of pre-season population susceptibility data was explored. Results: Estimates of disease spread were consistent over time and across models. The combined results provided valuable nowcasts of the state of the epidemic. Short-term predictions of burden on primary and secondary health services were initially highly variable before reaching consensus beyond the observed peaks in activity between weeks 3–4 of 2018. Estimates and predictions varied according to pre-season immunity levels. Conclusions: This exercise successfully applied a range of pandemic models to seasonal influenza. Forecasting early in the season remains challenging but represents a crucially important activity to inform planning. Improved knowledge of pre-existing levels of immunity would be valuable.


2021 ◽  
Author(s):  
Paul M. Severns ◽  
Christopher C. Mundt

Abstract Epidemic outbreak control often involves a spatially-explicit treatment area (quarantine, inoculation, ring cull) which covers the outbreak area and adjacent regions where hosts are thought to be latently infected. Emphasis on space however neglects the influence of treatment timing on outbreak control. We conducted field and in-silico experiments with wheat stripe rust (WSR), a long-distance dispersed plant disease, to understand interactions between treatment timing and area interact to suppress an outbreak. Full-factorial field experiments with three different ring culls (outbreak area only to a 25-fold increase in treatment area) at three different disease control timings (1.125, 1.25, and 1.5 latent periods after initial disease expression), indicated that earlier treatment timing had a conspicuously greater suppressive effect than the area treated. Disease spread computer simulations over a broad range of influential epidemic parameter values (R0, outbreak disease prevalence, epidemic duration) suggested that potentially unrealistically large increases in treatment area would be required to compensate for even small delays in treatment timing. Although disease surveillance programs are costly, our results suggest that treatments early in an epidemic disease outbreak require smaller areas to be effective, which may ultimately compensate for the upfront costs of proactive disease surveillance programs.


Author(s):  
AnneMarie Pegg

This chapter describes the explosive impact epidemic diseases can have in the humanitarian setting, and outlines four principal diseases with epidemic potential in humanitarian settings (cholera, dysentery, measles, and meningitis). It covers the fundamental precipitants of infectious disease spread in humanitarian settings, including displacement, disruption of the local health services, and overcrowding, and the important principles to prevent spread, such as advance planning, hygiene measures, surveillance, and response.


Subject Epidemic mathematical modelling. Significance Future transmission of viruses from wildlife to humans is inevitable. As such, the modelling of epidemics will become increasingly important to help policymakers. However, developing, implementing and evaluating simulations of epidemic disease spread and control options in real-time is no easy task. Impacts The science surrounding pandemic preparedness will receive growing attention from academics and biotechnology industries. Epidemic modelling may in the future also project indirect fatalities from an epidemic. Cross-discipline collaboration to fight future pandemics will benefit from crowdsourcing initiatives developed to fight COVID-19.


2002 ◽  
Vol 38 (1) ◽  
pp. 13-27 ◽  
Author(s):  
R. J. Hillocks ◽  
T. H. M. Kibani

Cotton (Gossypium hirsutum) is the main agricultural export commodity from Tanzania. The most significant disease of the crop is fusarium wilt caused by Fusarium oxysporum f.sp. vasinfectum. Phytosanitary measures instituted at the cotton ginneries to prevent the distribution, for planting, of seed infected with the wilt fungus have become difficult to apply since economic liberalization and the entry of the private sector into cotton ginning and lint marketing. Surveys of cotton fields, ginneries and cotton buying posts were conducted in order to determine the factors affecting disease incidence and spread. In affected fields, disease incidence was generally less than 5%. Where it was greater than this, wilt symptoms were associated with root damage caused by the root-knot nematode (Meloidogyne incognita). At a number of ginneries, herdsmen were allowed to remove seed husks that accumulate at the ginneries as a byproduct of oil extraction. The husks are used as cattle feed and this was identified as a potential source of disease spread. At the buying posts visited, there was no system for separating cotton varieties or for identifying seed cotton purchased from villages infected with fusarium wilt. As a result, seed subsequently distributed for planting is likely to be a source of infection for the spread of this disease. The implications of economic liberalization in the cotton sector are discussed with respect to seed distribution and management of fusarium wilt.


Author(s):  
J.R. Mcintosh

The mitotic apparatus is a structure of obvious biological and medical interest, but it has proved to be a difficult cellular machine to understand. The chemical composition of the spindle is only slightly elucidated, largely because of the difficulties in preparing useful isolates of the structure. Chemical studies of the mitotic spindle have been reviewed elsewhere (Mcintosh, 1977), and will not be discussed further here. One would think that structural studies on the mitotic apparatus (MA) in situ would be straightforward, but even with this approach there is some disagreement in the results obtained with various methods and by different investigators. In this paper I will review briefly the approaches which have been used in structural studies of the MA, pointing out the strengths and problems of each approach. I will summarize the principal findings of the different methods, and identify what seem to be fruitful avenues for further work.


Author(s):  
B. Lencova ◽  
G. Wisselink

Recent progress in computer technology enables the calculation of lens fields and focal properties on commonly available computers such as IBM ATs. If we add to this the use of graphics, we greatly increase the applicability of design programs for electron lenses. Most programs for field computation are based on the finite element method (FEM). They are written in Fortran 77, so that they are easily transferred from PCs to larger machines.The design process has recently been made significantly more user friendly by adding input programs written in Turbo Pascal, which allows a flexible implementation of computer graphics. The input programs have not only menu driven input and modification of numerical data, but also graphics editing of the data. The input programs create files which are subsequently read by the Fortran programs. From the main menu of our magnetic lens design program, further options are chosen by using function keys or numbers. Some options (lens initialization and setting, fine mesh, current densities, etc.) open other menus where computation parameters can be set or numerical data can be entered with the help of a simple line editor. The "draw lens" option enables graphical editing of the mesh - see fig. I. The geometry of the electron lens is specified in terms of coordinates and indices of a coarse quadrilateral mesh. In this mesh, the fine mesh with smoothly changing step size is calculated by an automeshing procedure. The options shown in fig. 1 allow modification of the number of coarse mesh lines, change of coordinates of mesh points or lines, and specification of lens parts. Interactive and graphical modification of the fine mesh can be called from the fine mesh menu. Finally, the lens computation can be called. Our FEM program allows up to 8000 mesh points on an AT computer. Another menu allows the display of computed results stored in output files and graphical display of axial flux density, flux density in magnetic parts, and the flux lines in magnetic lenses - see fig. 2. A series of several lens excitations with user specified or default magnetization curves can be calculated and displayed in one session.


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