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The Russian influenza in Sweden in 1889-90: an example of Geographic Information System analysis
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
Swedish Institute for Infectious Disease Control.
2008 (English)In: Euro surveillance : bulletin Européen sur les maladies transmissibles = European communicable disease bulletin, ISSN 1560-7917, Vol. 13, no 49Article in journal (Refereed) Published
Abstract [en]

Using data from a study of the 1889-90 Russian flu in Sweden, this article describes how the application of Geographic Information System (GIS) may improve analyses and presentation of surveillance data. In 1890, immediately after the outbreak, all Swedish doctors were asked to provide information about the start and the peak of the epidemic, and the total number of cases in their region and to fill in a questionnaire on the number, sex and age of infected persons in the households they visited. General answers on the epidemic were received from 398 physicians and data on individual patients were available for more than 32,600 persons. These historic data were reanalysed with the use of GIS, in map documents and in animated video sequences, to depict the onset, the intensity and the spread of the disease over time. A stack diagram with the observations grouped into one week intervals was produced to depict the spread in one figure only. To better understand how the influenza was disseminated, Thiessen polygons were created around 70 places reported on by the doctors. Having prepared GIS layers of the population (divided into parishes), estimations could be made for all the Swedish parishes on the number of infected persons for each of the 15 weeks studied. The described models may be useful in current epidemiological investigations, as well.

Place, publisher, year, edition, pages
2008. Vol. 13, no 49
National Category
Health Sciences
Identifiers
URN: urn:nbn:se:kth:diva-142826PubMedID: 19081003Scopus ID: 2-s2.0-61749095450OAI: oai:DiVA.org:kth-142826DiVA: diva2:704519
Note

QC 20140312

Available from: 2014-03-12 Created: 2014-03-12 Last updated: 2014-10-17Bibliographically approved
In thesis
1. Spatial Analysis and Modeling for Health Applications
Open this publication in new window or tab >>Spatial Analysis and Modeling for Health Applications
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Despite the benefits of applying methods of geographic information science (GIScience), the use of such methods in health service planning and provision remains greatly underutilized. Spread of epidemic diseases is a constant threat to mankind and the globalization of the world increases the risk for global attacks from multi-resistant bacteria or deadly virus strains. Therefore, research is needed to better understand how GIScience could be used in epidemiologic analyses and other health applications.

This thesis is divided into two parts; one for epidemiologic analyses and one for neighbourhood studies. The overall objective of the epidemiologic part of this research is to understand more about the spatial spread of past pandemics and to find out if there are any common patterns. This overall objective is divided into four specific research objectives; 1) to describe the spatial spread of the Russian Influenza in Sweden, 2) to create models of propagation of the Black Death in Sweden, 3) to establish spatiotemporal characteristics common to past pandemics in Sweden and 4) to visualize the spatiotemporal occurrence of salmonella among animal herds in Sweden.

This thesis also discusses some other aspects of health related to place. Are differences in neighbourhood deprivation related to the amount of presence of goods and services? Is the way cities are planned affecting the behaviour within the local population regarding spontaneous walking and physical activity? The specific research objectives for this part are to define how deprivation is related to presence of goods and services in Sweden and to create walkability indices over the city of Stockholm including a quality test of these indices.

Case data reported by physicians were used for the epidemiologic studies. The pandemics discussed covered the entire world, but our data is from Sweden only and as regards the Black Death there was no case data at all. The data for the goods and services analyses are from all of Sweden, whereas the walkability indices are based on data from the city of Stockholm. Various methods have been used to clean, structure and geocode the data, including hand written reports on case data, maps of poor geometric quality, information from databases on climate, demography, diseases, goods and services, income data and more, to make this data feasible for spatial analysis, modeling and visualization. Network analysis was used to model food transports in the 14th century as well as walking in the city of Stockholm today. Proximity analysis was used to assess the spatio-temporal spread of the Russian Influenza. The impact of climatological factors on the propagation of the Asian Influenza was analyzed and geographically weighted mean (GWM) calculations were used to discover common characteristics in the spatio-temporal spread of three past pandemics.

Among the results generated in the epidemiologic study the following should be noted in particular; the local peaking periods of the Asian Influenza were preceded by falling temperature, the total peaking period for the three pandemics (Russian, Asian and A(H1N1)pdm09) was approximately 10 weeks and their weekly GWM followed a path from southwest to northeast (opposite direction for the A(H1N1)pdm09). From the neighborhood studies one can note that compared to the results measured and reported by tested individuals there is a positive (small but significant) association between neighborhood walkability and physical activity outcomes.

The main contribution of this work is that it gives epidemiologists and public health specialists new ideas, not only on how to formulate, model, analyze and visualize different health related research questions but also ideas on how new procedures could be implemented in their daily work. Once the data reporting is organized in a suitable manner there is a multitude of options on how to present important and critical information to officials and policy makers.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2014. 95 p.
Series
TRITA-SOM, ISSN 1653-6126 ; 2014:03
Keyword
Sweden, spatial analysis, spatial modeling, spatio-temporal spread, epidemiology, pandemic, walkability, health, Russian influenza, Asian influenza, A(H1N1)pdm09, GWM, climate factors
National Category
Environmental Engineering
Identifiers
urn:nbn:se:kth:diva-142835 (URN)978-91-7595-040-2 (ISBN)
Public defence
2014-03-28, E3, Osquarsbacke 14, KTH, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20140313

Available from: 2014-03-13 Created: 2014-03-12 Last updated: 2014-03-13Bibliographically approved

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